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Direct energy budget is carried out for both cold and hot flow in gas–solid fluidization systems. First, the energy paths are proposed from thermodynamic viewpoints. Energy consumption means total power input to the specific system, and it can be decomposed into energy retention and energy dissipation. Energy retention is the variation of accumulated mechanical energy in the system, and energy dissipation is the energy converted to heat by irreversible processes. Then based on the Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) framework, different energy terms are quantified from the specific flow elements of fluid cells and particles as well as their interactions with the wall. In order to clarify the energy budget, it is important to identify which system is studied: the particle-fluid system or the particle sub-system. For the cold flow, the total energy consumption of the particle sub-system can well indicate the onset of bubbling and turbulent, while the variation of local energy consumption terms can reflect the evolution of heterogeneous structures. For the hot flow, different heat transfer mechanisms are analyzed and the solver is modified to reproduce the experimental results. The impact of the heat transfer mechanisms and heat production on energy consumption is also investigated. The proposed budget method has proven to be energy-conservative and easy to conduct, and it is hopeful to be applied to other multiphase flow systems.

Sea salt aerosols play a critical role in regulating the global climate through their interactions with solar radiation. The size distribution of these particles is crucial in determining their bulk optical properties. In this study, we analyzed in situ measured size distributions of sea salt aerosols from four field campaigns and used multi-mode lognormal size distributions to fit the data. We employed super-spheroids and coated super-spheroids to account for the particles’ non-spherictty, inhomogeneity, and hysteresis effect during the deliquescence and crystallization processes. To compute the single-scattering properties of sea salt aerosols, we used the state-of-the-art invariant imbedding T-matrix method, which allows us to obtain accurate optical properties for sea salt aerosols with a maximum volume-equivalent diameter of 12 µm at a wavelength of 532 nm. Our results demonstrated that the particle models developed in this study were successful in replicating both the measured depolarization and lidar ratios at various relative humidity (RH) levels. Importantly, we observed that large-size particles with diameters larger than 4 µm had a substantial impact on the optical properties of sea salt aerosols, which has not been accounted for in previous studies. Specifically, excluding particles with diameters larger than 4 µm led to underestimating the scattering and backscattering coefficients by 27%–38% and 43%–60%, respectively, for the ACE-Asia field campaign. Additionally, the depolarization ratios were underestimated by 0.15 within the 50%–70% RH range. These findings emphasize the necessity of considering large particle sizes for optical modeling of sea salt aerosols.

A fiber-optic temperature sensor based on the harmonic Vernier effect (HVE) was proposed, which consists of a sensing Sagnac interferometer (SSI) and a reference Sagnac interferometer (RSI) in parallel. Different order HVEs are generated by controlling the length of the panda fiber in the SSI to be about an integer multiple of that in the RSI. The sensitivity and detuning of different order HVEs compared with the normal Vernier effect (NVE) are investigated, and the results show that the HVEs have almost the same temperature sensitivity as the NVE when they have the same magnification factor, while their detunings are much larger than that of the NVE, and the higher the order of the HVE, the larger the detuning. As we all know that the larger the detuning, the easier the magnification factor is to be controlled, that is, the easier the sensor is to be prepared, so from the point of view, the sensors based on the HVEs are better than those based on the NVE. This conclusion is also suitable for other fiber-optic sensors based on Vernier effect.

Exploring the fine-structure of cesium lead bromide (CsPbBr3) perovskite nanocrystals (NCs) is not only vital to fundamental understanding of recombination mechanism of exciton but also crucial for improving the performance of quantum light emitters and spintronic devices. Herein, utilizing low-temperature magneto-photoluminescence (PL) measurement, we provide the direct PL spectral feature of the dark exciton in CsPbBr3single crystal, and demonstrate that the singlet dark exciton is located ∼20 meV below the triplet bright exciton. Furthermore, no significant polarization effect was measured from magnetic-polarization method, indicating that there is no spin selectivity for dark exciton.

The study of magneto-optical absorption has stimulated diverse energy-technology-related explorations, showing potential in breaking the current theoretical efficiency limits of energy devices compared with reciprocal counterparts. However, experimentally realizing strong infrared non-reciprocal absorption remains an open challenge, and existing proposals of non-reciprocal absorbers are restricted to a narrow working waveband. Here we observe highly asymmetric absorption spectra over a broad mid-infrared band (nearly 10 μm) using doped InAs multilayers with gradient epsilon-near-zero frequencies. We reveal that the magnetized epsilon-near-zero behaviours and material loss play important roles in achieving strongly non-reciprocal absorption under a moderate external magnetic field using a thin epsilon-near-zero film (<λ/40, λis the wavelength). Our approach enables flexible control over the working frequencies and non-reciprocal bandwidths by designing magnetized InAs films with different doping concentrations. The proposed principles can also be generalized to other III–V semiconductors, magnetized metals, topological Weyl semimetals, magnetized zero-index metamaterials and metasurfaces.

Dynamic PET imaging provides superior physiological information than conventional static PET imaging. However, the dynamic information is gained at the cost of a long scanning protocol; this limits the clinical application of dynamic PET imaging. We developed a modified Logan reference plot model to shorten the acquisition procedure in dynamic PET imaging by omitting the early-time information necessary for the conventional reference Logan model. The proposed model is accurate theoretically, but the straightforward approach raises the sampling problem in implementation and results in noisy parametric images. We then designed a self-supervised convolutional neural network to increase the noise performance of parametric imaging, with dynamic images of only a single subject for training. The proposed method was validated via simulated and real dynamic $^{{18}}\text{F}$ -fallypride PET data. Results showed that it accurately estimated the distribution volume ratio (DVR) in dynamic PET with a shortened scanning protocol, e.g., 20 minutes, where the estimations were comparable with those obtained from a standard dynamic PET study of 120 minutes of acquisition. Further comparisons illustrated that our method outperformed the shortened Logan model implemented with Gaussian filtering, regularization, BM4D and the 4D deep image prior methods in terms of the trade-off between bias and variance. Since the proposed method uses data acquired in a short period of time upon the equilibrium, it has the potential to add clinical values by providing both DVR and Standard Uptake Value (SUV) simultaneously. It thus promotes clinical applications of dynamic PET studies when neuronal receptor functions are studied.

Sr-doped LaMnO3, as one of the most successful cathodes for solid oxide fuel cells (SOFCs), can effectively function at high temperatures. However, its cathode kinetics considerably decreases with decreasing temperature, rendering it unsuitable for SOFCs operating at intermediate temperatures. In this study, La0.5Sr0.5MnO3−δ(LSM) is coated with TiO2to create the LSM + TiO2cathode. TiO2is shown to modify the electronic structure at the LSM/TiO2interface, allowing for charge accumulation for the O atoms at the interface. The activated O atoms enhance the formation of oxygen vacancies, which benefit the oxygen diffusion ability. Using LSM + TiO2as a cathode for proton-conducting SOFCs (H-SOFCs) operating at intermediate temperatures, the corresponding fuel cell demonstrated enhanced cell output performance compared with cells employing solely LSM or TiO2cathodes, exhibiting the synergistic effect of combining LSM and TiO2. Additionally, the LSM + TiO2cells achieved a power output of 1118 mWcm−2at 700°C, the highest yet reported value for H-SOFCs with LSM cathodes. LSM + TiO2was demonstrated to be stable against CO2and steam, allowing for steady functioning of the cell under working conditions, thereby resolving the problem of LSM’s poor performance in H-SOFCs while retaining remarkable stability.

The Ba0.5Sr0.5Co0.8Fe0.2O3−δ(BSCF) + Co3O4composite material is evaluated as a cathode for proton-conducting solid oxide fuel cells (H-SOFCs), which provides a new strategy to solve the thermal mismatch problem between the cathode and electrolyte without impairing the cathode performance. BSCF is a well-known cathode material for intermediate-temperature SOFCs, but its performance for H-SOFCs is unsatisfactory. One reason for the relatively low performance is the poor contact between the BSCF cathode and the electrolyte due to the high thermal expansion of BSCF. The relatively low melting point of Co3O4is taken in this study as an advantage to bond the BSCF cathode to the electrolyte, mitigating the poor contact problem for the BSCF with the electrolyte. Furthermore, the addition of Co3O4promotes the catalytic activity of the BSCF cathode as demonstrated by experimental studies and first-principles calculations, leading to an impressively high performance of BSCF-based cathodes for H-SOFCs.

Motion estimation is a fundamental step in dynamic medical image processing for the assessment of target organ anatomy and function. However, existing image-based motion estimation methods, which optimize the motion field by evaluating the local image similarity, are prone to produce implausible estimation, especially in the presence of large motion. In addition, the correct anatomical topology is difficult to be preserved as the image global context is not well incorporated into motion estimation. In this study, we provide a novel motion estimation framework of dense-sparse-dense (DSD), which comprises two stages. In the first stage, we process the raw dense image to extract sparse landmarks to represent the target organ’s anatomical topology, and discard the redundant information that is unnecessary for motion estimation. For this purpose, we introduce an unsupervised 3-D landmark detection network to extract spatially sparse but representative landmarks for the target organ’s motion estimation. In the second stage, we derive the sparse motion displacement from the extracted sparse landmarks of two images of different time points. Then, we present a motion reconstruction network to construct the motion field by projecting the sparse landmarks’ displacement back into the dense image domain. Furthermore, we employ the estimated motion field from our two-stage DSD framework as initialization and boost the motion estimation quality in light-weight yet effective iterative optimization. We evaluate our method on two dynamic medical imaging tasks to model cardiac motion and lung respiratory motion, respectively. Our method has produced superior motion estimation accuracy compared to the existing comparative methods. Besides, the extensive experimental results demonstrate that our solution can extract well-representative anatomical landmarks without any requirement of manual annotation. Our code is publicly available online: https://github.com/yyguo-sjtu/DSD-3D-Unsupervised-Landmark-Detection-Based-Motion-Estimation.

Smart windows with tunable optical properties for energy-saving and privacy protection applications are receiving increasing attention. However, current studies of smart windows either involve the use of complex material preparation processes and complex device systems for window switching or continue to face several challenges, including low luminous transmittance, low luminous and solar modulation, and narrow wavelength range management problems. Here, we report a dual-responsive smart window that achieves solar light management in the range of 200–2500 nm. This smart window is fabricated by combining a reversible thermoresponsive hydrogel that acts as a thermochromic material with a ZnO/Ag/ZnO multilayer film that acts as a transparent heater. The as-prepared smart window can modulate solar light over a range from ultraviolet to infrared and achieves active responses to high-temperature weather, with passive responses being produced through electrical heating. The smart window shows high luminous transmittance (81.7%) and high luminous modulation (81.6%), together with an outstanding solar modulation performance (62.9%). In outdoor demonstrations, the as-prepared smart window exhibited a promising temperature regulation ability under strong solar irradiation. Therefore, the proposed smart window promises to provide a simple and effective energy management technology for buildings.

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical particles. This paper proposes a deep learning (DL) scheme in conjunction with an optical property database to achieve this goal. Deep neural network (DNN) architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters, size parameters, and refractive indices. The dataset was computed through the invariant imbedding T-matrix method. Four separate DNN architectures were created to compute the extinction efficiency factor, single-scattering albedo, asymmetry factor, and phase matrix. The criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN parameters. The numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database, which indicates that the DNN can reproduce the optical properties in the dataset with high accuracy. In addition, the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the database. Importantly, the ratio of the database size (∼127 GB) to that of the DNN parameters (∼20 MB) is approximately 6810, implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models.

LiCoO2, a widely used electrode material for Li-ion batteries, was found to be suitable as a cathode material for proton-conducting solid oxide fuel cells (H-SOFCs). Although the evaporation of Li in LiCoO2was detrimental to the Li-ion battery performance, the Li-evaporation was found to be beneficial for the H-SOFCs. The partial evaporation of Li in the LiCoO2material preparation procedure led to the in-situformation of the LiCoO2+Co3O4composite. Compared to the cell using the pure phase LiCoO2cathode that only generated moderate fuel cell performance, the H-SOFCs using the LiCoO2+Co3O4cathode showed a high fuel cell performance of 1160 mW·cm−2at 700 °C, suggesting that the formation of Co3O4was critical for enhancing the performance of the LiCoO2cathode. The first-principles calculation gave insights into the performance improvements, indicating that the in-situformation of Co3O4due to the Li-evaporation in LiCoO2could dramatically decrease the formation energy of oxygen vacancies that is essential for the high cathode performance. The evaporation of Li in LiCoO2, which is regarded as a drawback for the Li-ion batteries, is demonstrated to be advantageous for the H-SOFCs, offering new selections of cathode candidates for the H-SOFCs.

Tracking the pathogen of coronavirus disease 2019 (COVID-19) in live subjects may help estimate the spatiotemporal distribution of SARS-CoV-2 infection in vivo. This study developed a positron emission tomography (PET) tracer of the S2 subunit of spike (S) protein for imaging SARS-CoV-2. A pan-coronavirus inhibitor, EK1 peptide, was synthesized and radiolabeled with copper-64 after being conjugated with 1,4,7-triazacyclononane-1,4,7-triyl-triacetic acid (NOTA). The in vitrostability tests indicated that [64Cu]Cu-NOTA-EK1 was stable up to 24 h both in saline and in human serum. The binding assay showed that [64Cu]Cu-NOTA-EK1 has a nanomolar affinity (Ki= 3.94 ± 0.51 nM) with the S-protein of SARS-CoV-2. The cell uptake evaluation used HEK293T/S+and HEK293T/S–cell lines that showed that the tracer has a high affinity with the S-protein on the cellular level. For the in vivostudy, we tested [64Cu]Cu-NOTA-EK1 in HEK293T/S+cell xenograft-bearing mice (n= 3) and pseudovirus of SARS-CoV-2-infected HEK293T/ACE2 cell bearing mice (n= 3). The best radioactive xenograft-to-muscle ratio (X/Nxenograft8.04 ± 0.99, X/Npseudovirus6.47 ± 0.71) was most evident 4 h postinjection. Finally, PET imaging in the surrogate mouse model of beta-coronavirus, mouse hepatic virus-A59 infection in C57BL/6 J mice showed significantly enhanced accumulation in the liver than in the uninfected mice (1.626 ± 0.136 vs 0.871 ± 0.086 %ID/g, n= 3, P< 0.05) at 4 h postinjection. In conclusion, our experimental results demonstrate that [64Cu]Cu-NOTA-EK1 is a potential molecular imaging probe for tracking SARS-CoV-2 in extrapulmonary infections in living subjects.

Sc-doped Sr2Fe1.5Mo0.5O6−δ(SFMSc) was successfully synthesized by partially substituting Mo in Sr2Fe1.5Mo0.5O6−δ* (SFM) with Sc, resulting in a higher proton diffusion rate in the resultant SFMSc sample. Theoretical calculations showed that doping Sc into SFM lowered the oxygen vacancy formation energy, reduced the energy barrier for proton migration in the oxide, and increased the catalytic activity for oxygen reduction reaction. Next, a proton-conducting solid oxide fuel cell (H-SOFC) with a single-phase SFMSc cathode demonstrated significantly higher cell performance than that of cell based on an Sc-free SFM cathode, achieving 1258 mW cm−2at 700°C. The performance also outperformed that of many other H-SOFCs based on single-phase cobalt-free cathodes. Furthermore, no trade-off between fuel cell performance and material stability was observed. The SFMSc material demonstrated good stability in both the CO2-containing atmosphere and the fuel cell application. The combination of high performance and outstanding stability suggests that SFMSc is an excellent cathode material for H-SOFCs.

Silver nanoparticles (AgNPs) have been widely used in biomedical and consumer products. It remains challenging to distinguish the toxicity of AgNPs derived from the particle form or the released silver ions (Ag+). In this study, the toxic effects of two citrate-coated AgNPs (20 and 100 nm) and Ag+were investigated in hepatoblastoma cells (HepG2 cells). The suppression tests showed that AgNPs and Ag+induced cell apoptosis via different pathways, which led us to speculate on the AgNP-induced mitochondrial damage. Then, the mitochondrial damages induced by AgNPs and Ag+were compared under the same intracellular Ag+concentration, showing that the mitochondrial damage might be mainly attributed to Ag nanoparticles but not to Ag+. The interaction between AgNPs and mitochondria was analyzed using a scattered light imaging method combined with light intensity profiles and transmission electron microscopy. The colocalization of AgNPs and mitochondria was observed in both NP20- and NP100-treated HepG2 cells, indicating a potential direct interaction between AgNPs and mitochondria. These results together showed that AgNPs induced apoptosis in HepG2 cells through the particle-specific effects on mitochondria.

A high-entropy ceramic oxide is used as the cathode for the first time for proton-conducting solid oxide fuel cells (H-SOFCs). The Fe0.6Mn0.6Co0.6Ni0.6Cr0.6O4(FMCNC) high-entropy spinel oxide has been successfully prepared, and the in situchemical stability test demonstrates that the FMCNC material has good stability against CO2. The first-principles calculation indicates that the high-entropy structure enhances the properties of the FMCNC material that surpasses their individual components, leading to lower O2adsorption energy for FMCNC than that for the individual components. The H-SOFC using the FMCNC cathode reaches an encouraging peak power density (PPD) of 1052 mW·cm−2at 700 °C, which is higher than those of the H-SOFCs reported recently. Additional comparison was made between the high-entropy FMCNC cathode and the traditional Mn1.6Cu1.4O4(MCO) spinel cathode without the high-entropy structure, revealing that the formation of the high-entropy material allows the enhanced protonation ability as well as the movement of the O p-band center closer to the Fermi level, thus improving the cathode catalytic activity. As a result, the high-entropy FMCNC has a much-decreased polarization resistance of 0.057 Ω·cm2at 700 °C, which is half of that for the traditional MCO spinel cathode without the high-entropy design. The excellent performance of the FMCNC cell indicates that the high-entropy design makes a new life for the spinel oxide as the cathode for H-SOFCs, offering a novel and promising route for the development of high-performance materials for H-SOFCs.

Sr-doped LaMnO3(LSM) which is the first-generation cathode for solid oxide fuel cells (SOFCs) has been tailored with Zn ions, aiming to achieve improved protonation ability for proton-conducting SOFCs (H-SOFCs). The new Sr and Zn co-doped LaMnO3(LSMZ) can be successfully synthesized. The first-principle studies indicate that the LSMZ improves the protonation of LSM and decreases the barriers for oxygen vacancy formation, leading to high performance of the LSMZ cathode-based cells. The proposed LSMZ cell shows the highest fuel cell performance among ever reported LSM-based H-SOFCs. In addition, the superior fuel cell performance does not impair its stability. LSMZ is stable against CO2, as demonstrated by both in-situCO2corrosion tests and the first-principles calculations, leading to good long-term stability of the cell. The Zn-doping strategy for the traditional LSM cathode with high performance and good stability brings back the LSM cathode to intermediate temperatures and paves a new way for the research on the LSM-based materials as cathodes for SOFCs.

Interaction between light and magnetism in magneto-optical (MO) nanophotonic devices has been actively studied in the past few years. The recent development of MO all-dielectric resonators and metasurfaces has led to the emergence of various novel MO phenomena that were not observed in their bulk counterparts. For example, a large s-polarized transverse MO Kerr effect can be observed at magnetic resonance wavelength, which cannot exist in the bare MO films. We review recent developments in nanophotonic devices based on MO materials and focus on different modes and related MO effects in nanophotonic structures with emphasis on recently discovered new MO phenomena in magnetoplasmonics and all-dielectric nanostructures, such as dark mode, all-dielectric Mie resonance and waveguide mode. Further, we discuss the potential applications of these nanostructures for biological/chemical sensing, magnetic field sensing, and magnetic field-controlled active and nonreciprocal metasurfaces.

As the key link connecting the earth’s spheres, continental weathering plays an important role in regulating the global biogeochemical cycle and long-term climate change. Siliciclastic sediments derived from large river basins can record continental weathering and erosion signals, and are thus widely used to investigate weathering processes. However, sediment grain size, hydrodynamic sorting and sedimentary recycling complicate the interpretation of sediment weathering proxies. This study presents elemental and lithium isotope compositions of estuarine surface sediments (SS) and suspended particulate matters (SPM) collected from the Changjiang (Yangtze River) Estuary. Based on a simple mass balance model, the proportions of different end-members (i.e., igneous rocks, modern weathering products and inherited weathering products) in sediments were quantitatively calculated and thus the silicate weathering process can be estimated. Overall, the sediments in the Changjiang Estuary are mainly eroded from un-weathered rock fragments (>60%), while modern weathering products account for less than 40%. The fine-grained SPM contain more shale components (52–66%), and the modern weathering products account for 21–40%. Comparatively, the coarse-grained surface sediments contain more un-weathered igneous rock fragments (63–84%) and less modern weathering products (only 4–18%). The comparison of δ7Li values with the weathering proxy (Chemical Index of Alteration, CIA) suggests that sediment weathering intensity declines with increasing proportion of un-weathered igneous rock fragments. Additionally, the occurrence of inherited weathering products (i.e., shale) in modern sediments makes it a challenge to simply use CIA and δ7Li as indicators of weathering intensity. This study confirms that fine-grained particles are more suitable for tracing contemporary weathering process, albeit with the influence of sedimentary recycling. Lithium isotopes combining with the mass balance model can quantitatively constrain the continental weathering processes in large river basins.

Targeting metastatic esophageal squamous cell carcinoma (ESCC) has been a challenge in clinical practice. Emerging evidence demonstrates that C-X-C chemokine receptor 4 (CXCR4) highly expresses in ESCC and plays a pivotal role in the process of tumor metastasis. We developed a copper-64 (t1/2= 12.7 h, 19% beta+) labeling route of NOTA-CP01 derived from LY2510924, a cyclopeptide-based CXCR4 potent antagonist, in an attempt to noninvasively visualize CXCR4 expression in metastatic ESCC. Precursor NOTA-CP01 was designed by modifying the C-terminus of LY2510925 with bis-t-butyl NOTA via a butane-1,4-diamine linker. The radiolabeling process was finished within 15 min with high radiochemical yield (>95%), radiochemical purity (>99%), and specific activity (10.5–21 GBq/μmol) (non-decay-corrected). The in vitrosolubility and stability tests revealed that [64Cu]NOTA-CP01 had a high water solubility (log P= −3.44 ± 0.12, n= 5) and high stability in saline and fetal bovine serum. [64Cu]NOTA-CP01 exhibited CXCR4-specific binding with a nanomolar affinity (IC50= 1.61 ± 0.96 nM, Kd= 0.272 ± 0.14 nM) similar to that of the parental LY2510924. The in vitrocell uptake assay indicated that the [64Cu]NOTA-CP01-selective accumulation in EC109 cells was CXCR4-specific. Molecular docking of the CXCR4/NOTA-CP01 complex suggested that the Lys, Arg, and NOTA of this ligand have a strong polar interaction with the key residues of CXCR4, which explains the tight affinity of [64Cu]NOTA-CP01 for CXCR4. To test the target engagement in vivo, prolonged-time positron emission computed tomography (PET) imaging was performed at 0.5, 4, 6, 8, 12, 16, and 24 h postinjection of [64Cu]NOTA-CP01 to the EC109 tumor-bearing mice. The EC109 tumors were most visible with high contrast to the contralateral background at 6 h postinjection. The tracer revealed receptor-specific tumor accumulation, which was illustrated by effective blocking via coinjection with a blocking dose of LY2510924. Quantification analysis of the prolonged-time images showed that there was obvious radioactivity accumulation in the tumor (1.27 ± 0.19%ID/g) with the best tumor-to-blood ratio (4.79 ± 0.06) and tumor-to-muscle ratio (15.44 ± 2.94) at 6 h postinjection of the probe. The immunofluorescence and immunohistochemistry confirmed the positive expression of CXCR4 in the EC109 tumor and ESCC and metastatic lymph nodes of patients, respectively. We concluded that [64Cu]NOTA-CP01 possessed a very high target engagement for CXCR4-positive ESCC and could be a potential candidate in the clinical detection of metastatic ESCC.

Genomic instability induced by DNA damage and improper DNA damage repair is one of the main causes of malignant transformation and tumorigenesis. DNA double strand breaks (DSBs) are the most detrimental form of DNA damage, and nonhomologous end-joining (NHEJ) mechanisms play dominant and priority roles in initiating DSB repair. A well-studied oncogene, the ubiquitin ligase Cullin 4A (CUL4A), is reported to be recruited to DSB sites in genomic DNA, but whether it regulates NHEJ mechanisms of DSB repair is unclear. Here, we discovered that the CUL4A-DTL ligase complex targeted the DNA-PKcs protein in the NHEJ repair pathway for nuclear degradation. Overexpression of either CUL4A or DTL reduced NHEJ repair efficiency and subsequently increased the accumulation of DSBs. Moreover, we demonstrated that overexpression of either CUL4A or DTL in normal cells led to genomic instability and malignant proliferation. Consistent with the in vitro findings, in human precancerous lesions, CUL4A expression gradually increased with increasing malignant tendency and was negatively correlated with DNA-PKcs and positively correlated with γ-H2AX expression. Collectively, this study provided strong evidence that the CUL4A-DTL axis increases genomic instability and enhances the subsequent malignant transformation of normal cells by inhibiting NHEJ repair. These results also suggested that CUL4A may be a prognostic marker of precancerous lesions and a potential therapeutic target in cancer.

Manipulation of spin degree of freedom (DOF) of electrons is the fundamental aspect of spintronic and valleytronic devices. Two-dimensional transition metal dichalcogenides (2D TMDCs) exhibit an emerging valley pseudospin, in which spin-up (-down) electrons are distributed in a +K (−K) valley. This valley polarization gives a DOF for spintronic and valleytronic devices. Recently, magnetic exchange interactions between graphene and magnetic insulator yttrium iron garnet (YIG) have been exploited. However, the physics of 2D TMDCs with YIG have not been shown before. Here we demonstrate strong many-body effects in a heterostructure geometry comprising a MoS2monolayer and YIG. High-order trions are directly identified by mapping absorption and photoluminescence at 12 K. The electron doping density is up to ∼1013cm–2, resulting in a large splitting of ∼40 meV between trions and excitons. The trions exhibit a high circular polarization of ∼80% under optical pumping by circularly polarized light at ∼1.96 eV; it is confirmed experimentally that both phonon scattering and electron–hole exchange interaction contribute to the valley depolarization with temperature; importantly, a magnetoresistance (MR) behavior in the MoS2monolayer was observed, and a giant MR ratio of ∼30% is achieved, which is 1 order of magnitude larger than the reported ratio in MoS2/CoFe2O4heterostructures. Our experimental results confirm that the giant MR behaviors are attributed to the interfacial spin accumulation due to YIG substrates. Our work provides an insight into spin manipulation in a heterostructure of monolayer materials and magnetic substrates.

Hyperuricemia is characterized by elevated blood uric acid (UA) levels, which can lead to certain diseases. Epidemiological studies have explored the association between environmental contaminant exposure and hyperuricemia. However, few studies have investigated the role of chemical exposure in the development of hyperuricemia. Here, we sought to investigate the effects of bisphenol exposure on the occurrence of hyperuricemia. Fifteen bisphenol chemicals (BPs) were detected in human serum and urine samples collected from an area with a high incidence of hyperuricemia in China. Serum UA levels positively correlated with urinary bisphenol S (BPS), urinary bisphenol P (BPP), and serum bisphenol F (BPF). The effects of these three chemicals on UA levels in mice were explored at various exposure concentrations. An increase in serum UA levels was observed in BPS- and BPP-exposed mice. The results showed that BPS exposure increased serum UA levels by damaging the structure of the kidneys, whereas BPP exposure increased serum UA levels by disturbing purine metabolism in the liver. Moreover, BPF did not induce an increase in serum UA levels owing to the inhibition of guanine conversion to UA. In summary, we provide evidence of the mechanisms whereby exposure to three BPs disturbs UA homeostasis. These findings provide new insights into the risks of exposure to bisphenol chemicals.

Immunocheckpoint inhibitors have shown impressive efficacy in patients with colon cancer and other types of solid tumor that are mismatch repair-deficient (dMMR). Currently, PCR-capillary electrophoresis is one of the mainstream detection methods for dMMR, but its accuracy is still limited by germline mismatch repair (MMR) mutations, the functional redundancy of the MMR system, and abnormal methylation of MLH1 promoter. Therefore, this study aimed to develop new biomarkers for dMMR based on artificial intelligence (AI) and pathologic images, which may help to improve the detection accuracy. To screen for the differential expression genes (DEGs) in dMMR patients and validate its diagnostic and prognostic efficiency, we used the expression profile data from the Cancer Genome Atlas (TCGA). The results showed that the expression of immunoglobulin λ joining (LGLJ) 3 in dMMR patients was significantly downregulated and negatively correlated with the prognosis. Meanwhile, our diagnostic models based on pathologic image features showed good performance with area under the curves (AUCs) of 0.73, 0.86, and 0.81 in the training, test, and external validation sets (Jiangsu Traditional Chinese Medicine Hospital cohort). Based on gene expression and pathologic characteristics, we developed an effective prognosis model for dMMR patients through multiple Cox regression analysis (AUC at 1, 3, and 5 years were 0.88, 0.89, and 0.88, respectively). In conclusion, our results showed that LGLJ3 and nucleus shape–related parameters (such as nuclear texture, nuclear eccentricity, nuclear size, and nuclear pixel intensity) were independent diagnostic and prognostic factors, suggesting that they could be used as new biomarkers for dMMR patients.

Optical isolators and circulators are important components for photonic integrated circuits. Despite significant progress on silicon-on-insulator (SOI) platforms, integrated optical isolators and circulators have rarely been reported on silicon nitride (SiN) platforms. In this paper, we report monolithic integration of magneto-optical (MO) isolators on SiN platforms with record-high performances based on standard silicon photonics foundry process and MO thin film deposition. We successfully grow high-quality MO garnet thin films on SiN with large Faraday rotation up to -−5900deg/cm. We show superior MO figure of merit (FoM) of MO/SiN waveguides compared to that of MO/SOI in an optimized device design. We demonstrate transverse magnetic (TM)/transverse electric (TE) mode broadband and narrowband optical isolators and circulators on SiN with high isolation ratio, low cross talk, and low insertion loss. In particular, we observe 1 dB insertion loss and 28 dB isolation ratio in a SiN racetrack resonator-based isolator at 1570.3 nm wavelength. The low thermo-optic coefficient of SiN also ensures excellent temperature stability of the device. Our work paves the way for integration of high-performance nonreciprocal photonic devices on SiN platforms.

Active metasurfaces, in which the optical property of a metasurface device can be controlled by external stimuli, have attracted great research interest recently. For optical switching and modulation applications, high-performance active metasurfaces need to show high transparency, high power efficiency, as well as ultrafast switching and large-scale fabrication capability. This paper reports Au/VO2-based active metasurfaces meeting the requirements above. Centimeter-scale Au/VO2metasurfaces are fabricated by polystyrene sphere colloidal crystal self-assembly. The devices show optical modulation on-off ratio up to 12.7 dB and insertion loss down to 3.3 dB at 2200 nm wavelength in the static heating experiment, and ΔT/Tof 10% in ultrafast pump-probe experiments. In particular, by judiciously aligning the surface plasmon resonance wavelength to the pump wavelength of the femtosecond laser, the enhanced electric field at 800 nm is capable to switch off the extraordinary optical transmission effect at 2200 nm in 100 fs time scale. Compared to VO2thin-film samples, the devices also show 50% power reduction for all-optical modulation. Our work provides a practical way to fabricate large-scale and power-efficient active metasurfaces for ultrafast optical modulation.

Forward radiative transfer models (RTM) are an indispensable tool for quantitative applications of satellite radiometers, e.g., for data calibration, instrument development, retrieval, and so on. In this study, we develop an accurate and efficient RTM for radiometers onboard Fengyun satellites, namely FYRTM (RTM for Fengyun Radiometers). Correlated k-distribution models are developed to improve the computational efficiency for gas absorption, and the effects of cloud and aerosol multiple scattering and emission are accelerated with pre-computed look-up tables. FYRTM is evaluated with a rigorous simulation based on discrete ordinate radiative transfer model (DISORT) as well as a popular fast forward model, i.e., the Community Radiative Transfer Model (CRTM). Results indicate that FYRTM-based simulations are two to three orders of magnitudes faster than the DISORT-based simulations. Compared to the rigorous model, FYRTM relative errors are within 2% at solar channels, and brightness temperatures (BT) differences are within 1 K at infrared channels. Compared with CRTM, FYRTM is computationally similar at solar channels, but three times faster at infrared channels. Furthermore, simulated reflectances/BTs using FYRTM are in a good agreement with the satellite observations. Overall, FYRTM is capable to simulate satellite observations under different atmospheric conditions, and can be extended to other radiometers onboard the Fengyun satellites (both geostationary and polar-orbiting satellites). It is expected to play important roles in future applications with Fengyun observations.

The primary advantage of a hollow structure is the likelihood of introducing diverse components in a single particle to achieve multiple missions. Herein, hollow microspheres with multicomponent nanocores (HMMNs) have been prepared based on a template-free strategy via a microwave-assisted hydrothermal treatment of Chlorella. The resulting HMMNs retain the near-spherical hollow morphology and functional groups of the cell wall of Chlorella, obviating the need for templates and chemical modification. The elements (iron, cobalt, calcium, magnesium, chlorine, and phosphorus) naturally present within the Chlorellacells react to form hydroxyapatite/chlorapatite and magnetic nanocores without the need for exogenous chemical reagents. The performances of HMMNs for cadmium ion (Cd2+) removal and antibiotic detection are explored. HMMNs exhibit relatively high adsorbance of Cd2+(1035.8 mmol/kg) and can be easily recovered by application of an external magnetic field. Ion exchange with Ca2+and Mg2+is shown to be the main mechanism of Cd2+elimination. In addition, HMMNs are a suitable carrier for the construction of a magnetic immunosensor, as demonstrated by the successful development of such an immunosensor with acceptable analytical performance for the detection of neomycin in milk samples. The versatile applications of HMMNs result from their multicomponent nanocores, hollow structure, and the functional groups on their shell. This work not only offers a simple and eco-friendly strategy for the fabrication of novel HMMNs but also provides a valuable advanced material for contaminant detection and heavy-metal removal.

Detection of individual molecules is the ultimate goal of any chemical sensor. In the case of gas detection, such resolution has been achieved in advanced nanoscale electronic solid-state sensors, but it has not been possible so far in integrated photonic devices, where the weak light-molecule interaction is typically hidden by noise. Here, we demonstrate a scheme to generate ultrasensitive down-conversion four-wave-mixing (FWM) in a graphene bipolar-junction-transistor heterogeneous D-shaped fiber. In the communication band, the FWM conversion efficiency can change steeply when the graphene Fermi level approaches 0.4 eV. In this condition, we exploit our unique two-step optoelectronic heterodyne detection scheme, and we achieve real-time individual gas molecule detection in vacuum. Such combination of graphene strong nonlinearities, electrical tunability, and all-fiber integration paves the way toward the design of versatile high-performance graphene photonic devices.

Chiral nanophotonic devices are promising candidates for chiral molecule sensing, polarization of diverse nanophotonics, and display technologies. Active chiral nanophotonic devices, where the optical chirality can be controlled by an external stimulus has triggered great research interest. However, efficient modulation of the optical chirality has been challenging. Here, we demonstrate switching of the extrinsic chirality by applied magnetic fields in a magnetoplasmonic metasurface device based on a magneto-optical oxide material, Ce1Y2Fe5O12(Ce:YIG). Due to the low optical loss and strong magneto-optical effect of Ce:YIG, we experimentally demonstrated giant and continuous far-field circular dichroism (CD) modulation by applied magnetic fields from −0.6 ± 0.2° to +1.9 ± 0.1° at 950 nm wavelength under glancing incident conditions. The far-field CD modulation is due to both magneto-optical circular dichroism and near-field modulation of the superchiral fields by applied magnetic fields. Finally, we demonstrate magnetic-field-tunable chiral imaging in millimeter-scale magnetoplasmonic metasurfaces fabricated using self-assembly.

Valley pseudospin in two-dimensional (2D) transition-metal dichalcogenides (TMDs) allows optical control of spin-valley polarization and intervalley quantum coherence. Defect states in TMDs give rise to new exciton features and theoretically exhibit spin-valley polarization; however, experimental achievement of this phenomenon remains challenges. Here, we report unambiguous valley pseudospin of defect-bound localized excitons in CVD-grown monolayer MoS2; enhanced valley Zeeman splitting with an effective g-factor of −6.2 is observed. Our results reveal that all five d-orbitals and the increased effective electron mass contribute to the band shift of defect states, demonstrating a new physics of the magnetic responses of defect-bound localized excitons, strikingly different from that of A excitons. Our work paves the way for the manipulation of the spin-valley degrees of freedom through defects toward valleytronic devices.

Long-range magnetic orders in atomically thin ferromagnetic CrI3trigger new fascinating physics and application perspectives. The physical properties of two-dimensional (2D) ferromagnetism CrI3are significantly influenced by interlayer spacing and stacking order, which are sensitive to the hydrostatic pressure and external environments. However, there remains debate on the stacking order at low temperature. Here, we study the interlayer coupling and stacking order of non-encapsulated 2–5 layer and bulk CrI3at 10 K by Raman spectroscopy; demonstrate a rhombohedral stacking in both antiferromagnetic and ferromagnetic CrI3. The opposite helicity dependence of Agand Egmodes arising from phonon symmetry further validates the rhombohedral stacking. An anomalous temperature-dependent behavior is observed due to spin-phonon coupling below 60 K. Our study provides insights into the interlayer coupling and stacking orders of 2D ferromagnetic materials.

Low-carbon steel is widely used for household appliance and automotive panel steel because of its excellent plasticity. Unfortunately, yield point phenomena easily appear in the low-carbon steel produced by a continuous annealing process and cause degradation to the surface quality during processing. The effect of the coiling temperature (600–750 °C) and annealing temperature (740–820 °C) on the yield point behavior is studied. Tensile tests show that coiling temperature has a greater effect on yield point elongation (YPE) and aging index (AI) than the annealing temperature. Microstructure observations show that coiling temperature at 750 °C would make the micron-sized carbides appearing at the grain boundary disappear and a number of dispersed nanoscale carbides precipitate in grain interior, corresponding to the highest solid solution carbon content in the matrix of 750 °C coiled sample. The experimental results suggest that AI rather than YPE has a positive relationship with the solid solution carbon content of the low-carbon steel. And YPE has a positive relationship with the upper/lower yield strength.

Salvianolic acid A (Sal A) has a wide range of pharmacological activities. To date, there have been no systematic and detailed metabolite research data of Sal A after oral administration in vitro and in vivo. In this study, a rapid and systematic method based on ultrafast liquid chromatography-quadrupole-time-of-flight mass spectrometry was developed to detect metabolites of Sal A in vitro (human liver microsome, human intestinal microbiota, artificial gastric, and intestinal juice) and in vivo (urine, plasma, feces, and various organs collected after oral administration of Sal A to normal rats and pseudo-germ-free rats). A total of 26 metabolites of Sal A were characterized. These metabolites were formed through extensive metabolic reactions, such as hydroxylation, hydrogenation, and glucuronidation reactions. This study provides novel possibility for exploring the potential biological mechanism of Sal A, and aids the promotion of clinical application.

Efficient and accurate computation of the single‐scattering properties of black carbon (BC) aerosols is fundamental in various fields, including remote sensing and climate simulations. In this study, we developed a composite model of fractal aggregates of BC encapsulated with hygroscopic aerosols to represent the ambient BC. We used the invariant imbedding T‐matrix method to compute the optical properties of fully and partially encapsulated BC aerosols. In this new model, the traditional assumption of unoverlapped surfaces in the super‐position T‐matrix method is unnecessary. After extensive simulations, we established a database of single‐scattering properties, including the extinction efficiency, the single‐scattering albedo, the asymmetry factor and six phase matrix elements. Moreover, we obtained deep neural networks (DNNs) from this database using a deep learning method. These DNN models provide a universal interface for predicting the optical properties of ambient BC aerosols. Specifically, through a modified architecture of the DNN, we trained two models based on the database to predict three integrated optical properties (extinction efficiency, single‐scattering albedo, and asymmetry factor) and six phase matrix elements. We performed statistical assessments based on the true values in the database and the predicted values from the DNNs, demonstrating that the DNNs accurately predicted all single‐scattering properties. Therefore, the developed DNN models can be conveniently implemented in aerosol optical parameterization for remote sensing studies and atmospheric models. Black carbon (BC) aerosol plays a significant role in the atmosphere, influencing climate through its interactions with radiation, such as scattering and absorbing. The accurate determination of the single‐scattering properties of BC, including the extinction efficiency, the single‐scattering albedo, the asymmetry factor and six phase matrix elements, is crucial for understanding its radiation effects. In this study, we developed a comprehensive model for BC particles that incorporates complex morphological characteristics and the mixing of BC with other hygroscopic aerosols. We established a database of single‐scattering properties for these models using the invariant imbedding T‐matrix method. However, the large storage space required by this database (over 20 GB) makes it impractical for widespread applications. Therefore, we employed a deep learning method to compress the storage consumption. Two deep neural networks (DNNs) were trained using the database, enabling the prediction of all single‐scattering properties. Remarkably, the performance of the DNNs was excellent, with a coefficient of determination greater than 0.99 for all single‐scattering properties, as determined through statistical assessment. These DNN models hold great potential for various atmospheric radiation and remote sensing studies in the future. A flexible model of partially and fully encapsulated fractal black carbon particles was developedA database of single‐scattering properties of encapsulated fractal black carbon particles was constructedTwo deep neural networks were obtained, offering a flexible approach to calculating the optical properties of black carbon aerosols A flexible model of partially and fully encapsulated fractal black carbon particles was developed A database of single‐scattering properties of encapsulated fractal black carbon particles was constructed Two deep neural networks were obtained, offering a flexible approach to calculating the optical properties of black carbon aerosols

The mixing state and fractal dimension (Df) of soot particles are two major factors affecting their absorption capacity and their climate effects. Here we investigated these factors of soot particles found in a typical valley of the southeastern Tibetan Plateau where wood burning in local villages was one major source of soot particles. Our motivation revealed Dfand the aging property of soot particles in remote air and discussed their regional climatic implications. We found that 64% of total analyzed particles by number were soot-bearing particles and most of them aged with sulfate or organic coating. The Dfsequence is bare-like soot (1.75 ± 0.08) < partly coated soot (1.82 ± 0.05) < embedded soot (1.88 ± 0.05). The aging process enlarged the overall size of the soot-bearing particles and increased the compactness of soot. Soot aging critically depended on high relative humidity (RH) during nighttime. Besides emission sources and coating processes, the coating aerosol phase under different RHs is another important factor affecting the soot Df.

Our aim was to develop an interactive 3D direct volume rendering (DVR) visualization solution to interpret and analyze complex, serial multi-modality imaging datasets from positron emission tomography–computed tomography (PET–CT). Our approach uses: (i) a serial transfer function (TF) optimization to automatically depict particular regions of interest (ROIs) over serial datasets with consistent anatomical structures; (ii) integration of a serial segmentation algorithm to interactively identify and track ROIs on PET; and (iii) parallel graphics processing unit (GPU) implementation for interactive visualization. Our DVR visualization more easily identifies changes in ROIs in serial scans in an automated fashion and parallel GPU computation which enables interactive visualization. Our approach provides a rapid 3D visualization of relevant ROIs over multiple scans, and we suggest that it can be used as an adjunct to conventional 2D viewing software from scanner vendors.

Integrated optical isolators have been a longstanding challenge for photonic integrated circuits (PICs). An ideal integrated optical isolator for a PIC should be made by a monolithic process, have a small footprint, exhibit broadband and polarization-diverse operation, and be compatible with multiple materials platforms. Despite significant progress, the optical isolators reported so far do not meet all of these requirements. In this paper we present monolithically integrated broadband magneto-optical isolators on silicon and silicon nitride (SiN) platforms operating for both TE and TM modes with record-high performances, fulfilling all the essential characteristics for PIC applications. In particular, we demonstrate fully TE broadband isolators by depositing high-quality magneto-optical garnet thin films on the sidewalls of Si and SiN waveguides, a critical result for applications in TE-polarized on-chip lasers and amplifiers. This work demonstrates monolithic integration of high-performance optical isolators on-chip for polarization-diverse silicon photonic systems, enabling new pathways to impart nonreciprocal photonic functionality to a variety of integrated photonic devices.

Accurate choroidal vessel segmentation with swept-source optical coherence tomography (SS-OCT) images provide unprecedented quantitative analysis towards the understanding of choroid-related diseases. Motivated by the leading segmentation performance in medical images from the use of deep learning methods, in this study, we proposed the adoption of a deep learning method, RefineNet, to segment the choroidal vessels from SS-OCT images. We quantitatively evaluated the RefineNet on 40 SS-OCT images consisting of ~3,900 manually annotated choroidal vessels regions. We achieved a segmentation agreement (SA) of 0.840 ± 0.035 with clinician 1 (C1) and 0.823 ± 0.027 with clinician 2 (C2). These results were higher than inter-observer variability measure in SA between C1 and C2 of 0.821 ± 0.037. Our results demonstrated that the choroidal vessels from SS-OCT can be automatically segmented using a deep learning method and thus provided a new approach towards an objective and reproducible quantitative analysis of vessel regions.

Integrated nonlinear metasurfaces leading to high-efficiency optical second harmonic generation (SHG) are highly desirable for optical sensing, imaging, and quantum photonic systems. Compared to traditional metal-only metasurfaces, their hybrid counterparts, where a noncentrosymmetric nonlinear photonic material is incorporated in the near-field of a metasurface, can significantly boost SHG efficiency. However, it is difficult to integrate such devices on-chip due to material incompatibilities, thickness scaling challenges, and the narrow band gaps of nonlinear optical materials. Here, we demonstrate significantly enhanced SHG in on-chip integrated metasurfaces by using nanometer thin films of ferroelectric Y:HfO2. This material has the merit of CMOS compatibility, ultraviolet transparency up to 250 nm, and significant scalability down to sub-10 nm when deposited on silicon. We observe a 20-fold magnitude enhancement of the SHG intensity from the hybrid metasurface compared to a bare ferroelectric HfO2thin film. Moreover, a 3-fold SHG enhancement is observed from the hybrid metasurface compared to a control structure using nonferroelectric HfO2, demonstrating a major contribution to the SHG signal from ferroelectric Y:HfO2. The effective second-order nonlinear optical coefficient χ(2)of Y:HfO2is determined to be 6.0 ± 0.5 pm/V, which is comparable to other complex nonlinear photonic oxide materials. Our work provides a general pathway to build an efficient on-chip nanophotonic nonlinear light source for SHG using ferroelectric HfO2thin films.

Sea salt aerosols were assumed to be homogeneous spheres in most climate models. However, observations show that sea salt particles are inhomogeneous during the deliquesce and crystallization processes. Using a two‐layer sphere model, we found that backscattering of solar radiation associated with sea salts is underestimated in homogeneous sea salt models. The Community Earth System Model is used to assess the inhomogeneity effect on direct radiative forcing. For global climate model simulation, the inhomogeneity effect on radiative transfer is found to be small as high RHs over widespread oceans suppress the impact of inhomogeneity. On the other hand, in coastal regions, the inhomogeneity effect can cause up to 10% radiative forcing difference of sea salt aerosols. The inhomogeneity effect of sea salt aerosols has to be considered over coastal regions, especially in the Mediterranean, Australia, and the eastern coast of South America. In a humid environment, solid sea salt particles can be coated with water. Sea salt aerosol has a cooling effect on the Earth, but coated sea salt has even stronger cooling effect. However, in most climate models, coated sea salt is not considered. This study confirms that coated sea salt aerosols may not significantly affect the global radiation budget, but they should definitely be considered in the coastal climate where large changes in relative humidity are evident. For some range of relative humidity (50‐80%), sea salt is assumed to be an inhomogeneous two‐layer sphereThe inhomogeneity of sea salt decreases the asymmetry factor and increases backscattering of solar radiationInhomogeneity has a relatively large impact (up to 10%) on sea salt radiative forcing over coastal waters

It is vital for emission reduction and energy saving to lighten the weight of automobile. Low-density Fe–Mn–Al–C steels with high strength and excellent ductility have become a promising type of material in the automotive industry. Thus, a new approach was proposed by using centrifugal casting to produce the low-density Fe–12Mn–9Al–1.2C steel with high performance under near-rapid solidification in a near-net shape. The produced steel strips, with a thickness of 2.5 mm and a density of 6.89 g/cm3, were examined for their microstructures and mechanical properties. The results showed that mechanical properties of as-cast steel strip reached 1182 MPa in ultimate tensile strength and 28.1% in total elongation. Aging treatment at 400 or 600 °C for 3 h enhanced tensile strength of the steel strips, while aging at 800 °C dramatically decreased its elongation. Moreover, Young’s modulus of the steel strip improved with the increment of aging temperature. The relationship between the mechanical properties and the microstructures was discussed. The results demonstrated that advanced low-density steels with promising mechanical properties could be directly produced from liquid by this simple process.

Plasmacytoma variant translocation 1 (PVT1) is an lncRNA that plays vital roles in breast cancer (BC) pathogenesis. Increasing evidence suggests that miRNAs that reside in the PVT1 locus are the main driver of the oncogenic roles of PVT1 in cancer. However, the oncogenic role and underlying mechanism of miR-1204, located in the PVT1 locus, in human cancer is still unclear. In this study, we discovered that increased expression of miR-1204 is associated with poor prognosis in BC. Moreover, miR-1204 promotes proliferation, epithelial-mesenchymal transition and invasion of BC cells both in vitro and in vivo. Mechanistic investigations demonstrated that VDR is a novel target gene of miR-1204. Interference of VDR restored miR-1204-mediated BC cell proliferation, tumorigenesis, and metastasis. Collectively, our results demonstrated that the miR-1204-VDR pathway exerts oncogenic effects in BC with potential therapeutic applications in blocking BC development and progression.

Abstract

Breaking the time reversal symmetry (TRS) in a topological insulator (TI) by introducing a magnetic order gives rise to exotic quantum phenomena. One of the promising routes to inducing a magnetic order in a TI is utilizing magnetic proximity effect between a TI and a strong magnetic insulator (MI). In this article, we demonstrate a TI/MI heterostructure prepared through transferring a molecular beam epitaxy (MBE)-grown Bi2Se3film onto a yttrium iron garnet (YIG) substrate viawet transfer. The transferred Bi2Se3exhibits excellent quality over a large scale. Moreover, through wet transfer we are able to engineer the interface and perform a comparative study to probe the proximity coupling between Bi2Se3and YIG under different interface conditions. A detailed investigation of both the anomalous Hall effect and quantum corrections to the conductivity in magnetotransport measurements reveals an induced magnetic order as well as TRS breaking in the transferred Bi2Se3film on YIG. In contrast, a thin layer of AlOxat the interface obstructs the proximity coupling and preserves the TRS, indicating the critical role of the interface in mediating magnetic proximity effect.

A detailed assessment is carried out in relation to the influence of the uncertainties associated with the input auxiliary atmospheric state parameters on retrieving aerosol optical properties from high-spectral-resolution lidar (HSRL) observations. The study starts from a review of the main spectral structure of the Rayleigh backscattering followed by evaluating the temperature effects on a backscattering cross section of atmospheric molecules based on numerical simulation. It shows that the transmittance of the background interference filter should be taken into account, depending on the full width at half maximum, although overall temperature dependence is negligible. Based on the Taylor expansion of the Tenti S6 model, the systematic errors arising from input temperature and pressure profiles are analyzed. It is demonstrated that the atmospheric pressure profiles have limited effects on the inversion results of aerosol optical parameters, as the atmospheric pressure is usually quite stable. The relative errors of the aerosol backscatter coefficient mainly stem from temperature profile errors and highly depend on the aerosol concentration. Quantitatively, the aerosol backscatter coefficient error could be larger than 5% with a 3 K deviation of temperature when the backscatter ratio is larger than 1.1. The accuracy of aerosol extinction coefficient retrieval is affected not only by the error in temperature, but also by the error in temperature lapse rate; the retrieval accuracy is more sensitive to the latter than the former. Further analysis based on the sounding temperature data shows that the variation of the temperature inversion layer during the night could induce a bias larger than 0.04  km^−1 on the aerosol extinction coefficient retrieval. Therefore, the time resolution of temperature measurement from sounding balloons twice per day is too low to obtain an accurate retrieval of the aerosol optical properties from the HSRL.

The nonsphericity and inhomogeneity of marine aerosols (sea salts) have not been addressed in pertinent radiative transfer calculations and remote sensing studies. This study investigates the optical properties of nonspherical and inhomogeneous sea salts using invariant imbedding T‐matrix simulations. Dry sea salt aerosols are modeled based on superellipsoidal geometries with a prescribed aspect ratio and roundness parameter. Wet sea salt particles are modeled as coated superellipsoids, as spherical particles with a superellipsoidal core, and as homogeneous spheres depending on the level of relative humidity. Aspect ratio and roundness parameters are found to be critical to interpreting the linear depolarization ratios (LDRs) of NaCl crystals from laboratory measurements. The optimal morphology parameters of NaCl necessary to reproduce the measurements are found to be consistent with data gleaned from an electron micrograph. The LDRs of wet sea salts are computed based on inhomogeneous models and compared with the measured data from ground‐based LiDAR. The dependence of the LDR on relative humidity is explicitly considered. The increase in the LDR with relative humidity at the initial phase of deliquescence is attributed to both the size increase and the inhomogeneity effect. For large humidity values, the LDR substantially decreases because the overall particle shape becomes more spherical and the inhomogeneity effect in a particle on the LDR is suppressed for submicron sea salts. However, the effect of inhomogeneity on optical properties is pronounced for coarse‐mode sea salts. These findings have important implications for atmospheric radiative transfer and remote sensing involving sea salt aerosols. Sea salts are modeled as homogeneous and inhomogeneous superellipsoids as a function of relative humidityNonsphericity and inhomogeneity are shown to be key in interpreting laboratory measurements and LiDAR field observationsThe effect of inhomogeneity on the asymmetry factor is significant for coarse‐mode sea salt aerosols

Proton-conducting oxides offer a promising electrolyte solution for intermediate temperature solid oxide fuel cells (SOFCs) due to their high conductivity and low activation energy. However, the lower operation temperature leads to a reduced cathode activity and thus a poorer fuel cell performance. La0.8Sr0.2MnO3−δ(LSM) is the classical cathode material for high-temperature SOFCs, which lack features as a proper SOFC cathode material at intermediate temperatures. Despite this, we here successfully couple nanostructured LSM cathode with proton-conducting electrolytes to operate below 600°C with desirable SOFC performance. Inkjet printing allows depositing nanostructured particles of LSM on Y-doped BaZrO3(BZY) backbones as cathodes for proton-conducting SOFCs, which provides one of the highest power output for the BZY-based fuel cells below 600°C. This somehow changes the common knowledge that LSM can be applied as a SOFC cathode materials only at high temperatures (above 700°C). 质子导体氧化物因其高导电性和低活化能, 成为一种很有前途的中温固体氧化物燃料电池(SOFCs)电解质材料. 然而, 较低的操作温度会降低阴极活性, 从而降低燃料电池的性能. La0.8Sr0.2MnO3−δ(LSM)是一种经典的高温SOFCs阴极材料, 但其很多特性不符合中温SOFCs阴极材料的要求. 针对这一问题, 我们成功将纳米化的LSM阴极和质子导体电解质结合在一起, 在600°C下运行, 获得了理想的电池性能. 喷墨印刷技术可以将LSM的纳米结构粒子构筑在Y-掺杂的BaZrO3(BZY)骨架上, 从而作为质子导体SOFCs的阴极. 以此为阴极的单电池成为600°C以下的BZY基燃料电池中输出功率最高的之一. 本工作也打破了LSM只能作为高温SOFCs阴极材料(超过700°C)的传统思维局限.

A half-wave plate (HWP) is a critical component for calibrating the gain ratio in polarization lidars. In this paper, the effects of a nonideal HWP on the gain ratio calibration measurements are analyzed. We focus on the ±45° method and the multi-rotation HWP method, which are the two main approaches for calibrating the gain ratio. Specifically, we discuss the influences of a nonideal HWP from two scenarios: an HWP with nonideal polarization properties and an ideal HWP under nonideal external conditions. The allowable ranges of relevant parameters for the nonideal polarization properties of HWPs are obtained, which can help to determine qualified HWPs in polarization lidars. Several external conditions, including ambient temperature variations, wavelength differences, and the tilt angles of HWPs, are also analyzed in detail. To the best of our knowledge, this paper represents the first comprehensive study on the effects of nonideal HWPs on the gain ratio calibration measurements, offering some guidelines on choosing a qualified HWP for proper use in polarization lidars.