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Doping enables manipulation of both the electrical and optical properties of halide perovskites. Herein, we incorporated Te4+ into Cs2ZrCl6 single crystal, simultaneously preserving the vacancy-ordered structure, to obtain an efficient yellow-emitting perovskite with a near-unity photoluminescence quantum yield (PLQY ≈ 97.6%). Te4+ doping modifies the hue and emission color of pristine Cs2ZrCl6, generates new absorption channels, and successfully extends the excitation energy from

Accurate energy consumption modeling is an essential prerequisite for sustainable manufacturing. Recently, cutting-power-based models have garnered significant attention, as they can provide more comprehensive information regarding the machining energy consumption pattern. However, their implementation is challenging because new cutting force coefficients are typically required to address new workpiece materials. Traditionally, cutting force coefficients are calculated at a high operation cost as a dynamometer must be used. Hence, a novel indirect approach for estimating the cutting force coefficients of a new tool-workpiece pair is proposed herein. The key idea is to convert the cutting force coefficient calculation problem into an optimization problem, whose solution can be effectively obtained using the proposed simulated annealing algorithm. Subsequently, the cutting force coefficients for a new tool-workpiece pair can be estimated from a pre-calibrated energy consumption model. Machining experiments performed using different machine tools clearly demonstrate the effectiveness of the developed approach. Comparative studies with measured cutting force coefficients reveal the decent accuracy of the approach in terms of both energy consumption prediction and instantaneous cutting force prediction. The proposed approach can provide an accurate and reliable estimation of cutting force coefficients for new workpiece materials while avoiding operational or economic problems encountered in traditional force monitoring methods involving dynamometers. Therefore, this study may significantly advance the development of sustainable manufacturing.

In China, with the rapid development of economy and the advancement of urbanization, the deterioration of urban ecological environment is obvious. In order to obtain the quantitative state of urban ecological security, this paper contributes an integrated and coupled emergy ecological footprint framework and Beijing city was selected to verify methodology effect in this paper. The results demonstrate that: (1) from 2010 to 2019, the change range of EEFB is from 6.37 to 9.29%; meanwhile, EEFI is from 7.95 to 17.72%; EEFE is from 36.36 to 63.71%; EEFP is from 18.45% to 41.65%. Comparing the proportions of four subparts, the energy resource products (EEFE) and emissions (EEFP) are the main factors, far more significant than biological resources (EEFB) and industrial products (EEFI). (2) Compared to all ECCS data, there is a definite growing trend in Beijing city, from 2.68E + 4 hm2/cap in 2010 to 4.72E+4 hm2/cap in 2019, approximately 42.22% growth range. (3) Four sustainable indicators analysis: The changes of EEFT, EBI, and EEF are from 3.1, 2.46, and 1.02 in 2010 to 0.688, 9.29 and 1.14 in 2019, respectively. For EDI, total proportions of fossil land and built-up land are 85.25% to 90.43% of the entire EEF in Beijing city. These results reflect that Beijing city is suffering from a substantial ecological challenge due to remarkable ecological deficit, awfully high emergy ecological footprint intensity, and low cooperation level between ecological system and economic system. To identify key improvement factors, Pearson correlation analysis was conducted in this paper and revealed the most positive and negative elements, which are the unbalanced industrial structure and a large proportion heavy and polluting industries in Beijing city. Finally, based on the pivotal influencing factors, corresponding strategies and measures are proposed to improve and optimize the ecological security in Beijing city.

When an ultrathin silver nanowire with a diameter less than 100 nm is placed on a photonic band gap structure, surface plasmons can be excited and propagate along two side-walls of the silver nanowire. Although the diameter of the silver nanowire is far below the diffraction limit, two bright lines can be clearly observed at the image plane by a standard wide-field optical microscope. Simulations suggest that the two bright lines in the far-field are caused by the unique phase distribution of plasmons on the two side-walls of the silver nanowire. Combining with the sensing ability of surface plasmons to its environment, the configuration reported in this work is capable of functioning as a sensing platform to monitor environmental changes in the near-field region of this ultrathin nanowire.

An accurate measurement of the refractive index is necessary for the optical design of both deep ultraviolet laser diodes and light-emitting diodes. Generally, the refractive indices along different crystallographic axes of anisotropic thin films are measured using variable angle spectroscopic ellipsometry. However, there are still some limitations concerning this method. Here we proposed a potential method to measure the band edge refractive index of wide bandgap semiconductor. An aperiodic oscillation emission phenomenon due to the Fabry-Perot effect was observed in the fluorescence spectrum of an AlN film with a thickness of 1500 nm. Based on the characteristics of the fluorescence spectrum and the definition of Fabry-Perot effect, we obtained the ordinary refractive index of the AlN thin film near the band edge directly. This refractive index measurement method is a supplement to the variable angle ellipsometry, and it is a more direct and effective method for transferred film and thinner samples to measure the fluorescence spectrum.

Improving the machining dynamics performance and efficiency of machine tools is extremely important to finish the processing of complex channel parts with high quality in a short time. In this paper, a three-step frame is adopted to achieve this goal by planning the tool orientations and feed rate, which includes C-spaces determination, collaborative optimization of toolpath and feed rates, and the adjustment for over-limitation dynamic parameters. Firstly, a conical ball-end cutter is used and the feasible C-spaces computation method is provided based on the envelop theory. Secondly, a multi-objective mathematical model with multi-constraint conditions for optimizing the dynamics performance and machining efficiency is built. Thirdly, the solving algorithms for the model but simplified is designed to generate the optimal toolpath and initial variable feed rate sequence. To design the efficient algorithms, the Closed-region Parametric Encoding (CPE) method for data structure and the Parametric Data Algorithm Design (PDAD) for algorithm design are proposed, which can transform the geometric constraints into the parametric surfaces in C-space and compute with the continuous parameters to implement the adaptive local subdivision. The algorithms can automatically generate the different shape of toolpath curve to obtain better optimization results. Finally, considering the dynamic parameters limitation, an adjustment algorithm is designed to adjust the feed rates for reducing the over-limitation dynamic parameters. At the end of the paper, two sets of comparative experiments are given for verification. The first set experiment shows that our approach can efficiently improve the machining dynamics performance and efficiency for complex channel parts. The second set experiment shows that the solving algorithm designed by the CPE method and PDAD method has the better computation efficiency and optimization effect.

Predicting cutting force is always the research hotspot due to its significant effect on machining process. In this work, an analytical model of cutting force based on unequal division parallel-sided shear zone has been developed for orthogonal cutting. An unequal division parallel-sided shear model together with a prediction model of shear angle are integrated into the shear cutting force model in the primary shear zone. The classical Waldrof’s slip-line model is employed to describe the plow effect induced by edge radius of cutter and then the plow cutting force is calculated. The modeling algorithm of cutting force is subsequently proposed by integrating the shear cutting force with the plow cutting force. Cylindrical turning of Inconel 718 alloy is taken as a case to verify the proposed prediction model of cutting force. The measured results show that the predicted cutting force agrees well with the measured value. The average prediction errors of the main cutting force and the feed force are 8.39% and 12.03%, respectively. Compared with the classical shear models, it is found that the developed cutting force model shows higher accuracy on predicting cutting force. Additionally, the proposed model is then further verified by predicting cutting force with five different J-C constitutive models.

The gangue content in iron ore pellets that are used to produce direct-reduced iron (DRI) affects the slag volume during subsequent electric furnace steelmaking. Industrial and laboratory measurements and simulations have shown that unfluxed gangue from DRI also strongly affects the degree of saturation of the steelmaking slag with MgO. Laboratory tests show slag-line attack of such undersaturated slag on an MgO crucible, in support of reported refractory wear during steelmaking with higher-gangue DRI.

A limitation of standard brightfield microscopy is its low contrast images, especially for thin specimens of weak absorption, and biological species with refractive indices very close in value to that of their surroundings. We demonstrate, using a planar photonic chip with tailored angular transmission as the sample substrate, a standard brightfield microscopy can provide both darkfield and total internal reflection (TIR) microscopy images with one experimental configuration. The image contrast is enhanced without altering the specimens and the microscope configurations. This planar chip consists of several multilayer sections with designed photonic band gaps and a central region with dielectric nanoparticles, which does not require top-down nanofabrication and can be fabricated in a larger scale. The photonic chip eliminates the need for a bulky condenser or special objective to realize darkfield or TIR illumination. Thus, it can work as a miniaturized high-contrast-imaging device for the developments of versatile and compact microscopes., The authors design a planar photonic chip with several multilayers of photonic band gaps and a region of dielectric nanoparticles for tailored angular transmission. They use it as sample substrate for high-contrast darkfield and total internal reflection microscopy on a conventional microscope.

Osteosarcoma, a highly aggressive cancer, can rapidly metastasize to distant organs such as lung, liver, brain. Despite much progress in the therapeutic regime has been made, the prognosis of osteosarcoma remains poor. In present study, microRNA-511 (miR-511) is lowly expressed in osteosarcoma cells, including MG63, U-2 OS, Saos-2 cells, while mitogen activated protein kinase1 (MAPK1) is highly expressed in osteosarcoma cells. Interestingly, MAPK1 might be a target of miR-511. We found that overexpression of miR-511 by miR-511 mimic transfection may result to low expression of MAPK1. Further study showed that miR-511 mimic inhibits the development of osteosarcoma MG63 cell, including proliferation and invasion. Moreover, miR-511 mimic transfection reduces metastatic osteosarcoma tumor burden in nude mice. These activities are mediated by targeting MAPK1. Our study provides a new sight for the molecular pathogenesis of osteosarcoma.

Cloud data centers, such as Amazon EC2, host myriad big data applications using Virtual Machines (VMs). As these applications are communication-intensive, optimizing network transfer between VMs is critical to the performance of these applications and network utilization of data centers. Previous studies have addressed this issue by scheduling network flows with coflow semantics or optimizing VM placement with traffic considerations. However, coflow scheduling and VM placement have been conducted orthogonally. In fact, these two mechanisms are mutually dependent, and optimizing these two complementary degrees of freedom independently turns out to be suboptimal. In this paper, we present VirtCO, a practical framework that jointly schedules coflows and places VMs ahead of VM launch to optimize the overall performance of data center applications. We model the joint coflow scheduling and VM placement optimization problem, and propose effective heuristics for solving it. We further implement VirtCO with OpenStack and deploy it in a testbed environment. Extensive evaluation of real-world traces shows that compared with state-of-the-art solutions, VirtCO greatly reduces the average coflow completion time by up to 36.5%. This new framework is also compatible with and readily deployable within existing data center architectures.

Modern manufacturing enterprises are consuming a considerable amount of energy every year. Improving energy efficiency will not only benefit the enterprises economically, but also help the world to overcome various problems such as energy crisis and air pollution. To achieve this, an accurate energy consumption model is essential. The main objective of this paper is to develop an improved cutting power-based energy consumption model for general end milling process. The proposed model consists of an idle part due to auxiliary components and spindle rotation, and an additional part due to cutting workpiece materials. The first part is modelled as a function of spindle rotation speed, and the other part is considered proportional to the cutting power. Experiments under various milling conditions have demonstrated the effectiveness and efficacy of the proposed model. Comparative studies show that the proposed model is more accurate than other models. Although calibrated from slotting experiments when cutting aluminium alloy, the proposed model is applicable for general milling process. Partial-immersion milling experiments show that the prediction error of the proposed model is as low as 1.74%. When workpiece material changes to titanium alloy, its performance remains decent, with low prediction error of 2.81%. This reveals its capability to provide reliable estimation for different workpiece materials. As such, it could help avoid tedious model calibration, thus saving time, material, and energy. Finally, the energy efficiency of general end milling process is investigated through numerical experiments with the proposed model. By revealing the relationship between energy consumption and various cutting parameters, the proposed model could serve as an excellent platform towards energy-efficient manufacturing/cleaner production.

Molecular electrical doping has been proved as an effective strategy to improve the performance of traditional binary polymer solar cells (PSCs). However, its effectiveness is not demonstrated yet ...

Herein, the pyrolysis characteristics of low-rank coal under a CO-containing atmosphere was studied via thermogravimetry coupled with mass spectrometry and Fourier transform infrared analysis. Furt...

Metal-halide perovskites are promising optical gain materials because of their excellent photophysical properties. Recently, large perovskite single crystals with phase purity, less defects, and over millimeter dimensions have been successfully synthesized. However, the optical gain effect from these large-size single crystals has not yet been realized. Herein, we for the first time report efficient two-photon pumped amplified spontaneous emission (ASE) from millimeter-sized CsPbBr3 single crystals (SCs) with a low threshold of 0.65 mJ cm-2 and an optical gain of 38 cm-1. Furthermore, the CsPbBr3 SCs also exhibit ultrastable ASE under continuous laser irradiation for more than 40 h (corresponds to 1.5 × 108 laser shots) at ambient condition. This work suggests the potential application of large-size perovskite single crystals in practical nonlinear optical devices.

Background Constipation is a gastrointestinal symptom with high incidence rate and large number of patients. It is becoming one of the urgent medical problems. Poor intestinal motility is one of the important causes of constipation. Current drug treatments for constipation are associated with many side effects; thus, it is necessary to study more effective treatment methods and potential mechanism. Methods A zebrafish model of intestinal motility obstruction was established by loperamide hydrochloride to evaluate the effect of probiotic, food ingredients, and combination on intestinal peristalsis according to intestinal peristalsis frequency counts. The gastrointestinal survival ability of the best probiotics was evaluated by surface hydrophobicity, self-aggregation, acid and bile salt tolerance, and gastrointestinal transit tolerance. Interactions between probiotics and food ingredients were studied in vivo and in vitro. The expression of 5-HT was detected by ELISA and fluorescence immunoassay, and 5-HT related genes were detected by RT-PCR. Key results We obtained the probiotics, food ingredients, and combination that effectively promoted intestinal peristalsis, X11 and YRL577, P. persica and KGM, KGM + X11, respectively. Both KGM and P. persica promoted colonization of probiotics in vivo. KGM + X11 could effectively promote the increase in 5-HT synthesis in zebrafish via up-regulating gene expression of TPH-1, TPH-2, and 5-HTR and down-regulating gene expression of SERT. The specific in-depth mechanism needs further study. Conclusions and inferences The combinations of KGM with X11 effectively promoted intestinal peristalsis. We provide a theoretical basis for new modalities that can promote intestinal peristalsis and alleviate constipation.

Chin augmentation procedures are gaining in popularity. The purpose of this study was to validate the China (Allergan) Chin Retrusion Scale (CACRS) and to evaluate the reliability of the scale. A team of 10 physicians based in Beijing, China, consisting of 1 principal investigator and 9 independent raters, assessed a pool of subject images. Using standardized equipment to capture 2-dimensional images, 100 subjects were photographed from a left, lateral, 90° view. Two measures were used to assess the validity of the scale: rater evaluations of clinically significant differences in 52 pairs of images and rater assessment of chin retrusion using the CACRS to grade the 100 images. The CACRS demonstrated almost perfect inter-rater agreement during 2 validation sessions, with intraclass correlation coefficients of 0.89 and 0.90 at sessions 1 and 2, respectively. Overall inter-rater agreement for all 9 raters was almost perfect, with a weighted kappa of 0.82. Based on inter- and intra-rater agreement, the CACRS was validated for physician ratings of chin retrusion in Chinese subjects. Results from clinical significance evaluations indicated that a 1-grade difference between image pairs was considered clinically meaningful for the CACRS. The CACRS is a validated and reliable photonumeric scale for the assessment of chin retrusion in Chinese men and women. The scale is a clinically significant reference tool for evaluating the effect of chin augmentation.

Dielectric multilayer photonic-band-gap structures, called one-dimensional photonic crystals (1DPCs), have drawn considerable attention in the fields of physics, chemistry, and biophotonics. Here, experimental results verify the feasibility of a 1DPC working as a substrate for switchable manipulations of colloidal microparticles. The optically induced thermal convective force on a 1DPC can assemble colloidal particles that are dispersed in a water solution, while the photonic scattering force on the same 1DPC caused by propagating evanescent waves can guide these particles. Additionally, in the 1DPC, one internal mode can be excited that has seldom been noticed previously. This mode shows an ability to assemble particles over large areas even when the incident power is low. The assembly and guidance of colloidal particles on the 1DPC are switchable just through tuning the polarization and angle of the incident laser beam. Numerical simulations are carried out, which are consistent with these experimental observations.

The traditional weighing and selling process of non-barcode items requires manual service, which not only consumes manpower and material resources but is also more prone to errors or omissions of data. This paper proposes an intelligent self-service vending system embedded with a single camera to detect multiple products in real-time performance without any labels, and the system realizes the integration of weighing, identification, and online settlement in the process of non-barcode items. The system includes a self-service vending device and a multi-device data management platform. The flexible configuration of the structure gives the system the possibility of identifying fruits from multiple angles. The height of the system can be adjusted to provide self-service for people of different heights, then, deep learning skill is applied implementing product detection, and real-time multi-object detection technology is utilized in the image-based checkout system. In addition, on the multi-device data management platform, the information docking between embedded devices, WeChat applets, Alipay, and the database platform can be implemented. We conducted experiments to verify the accuracy of the measurement. The experimental results demonstrate that the correlation coefficient R2 between the measured value of the weight and the actual value is 0.99, and the accuracy of non-barcode item prediction is 93.73%. In Yangpu District, Shanghai, a comprehensive application scenario experiment was also conducted, proving that our system can effectively deal with the challenges of various sales situations.

Various characterization methods are used to investigate the physical and chemical properties of steel plant flying dust and waste oil sludge, and the combustion characteristics of the mixtures with pulverized coal are studied via thermogravimetric analysis; the catalytic combustion mechanism is also explored. The results show that two types of metallurgical by-products with small particle sizes and developed pores are evenly dispersed in the pulverized coal and are stably combined with it. The additives reduce the ignition temperature and the temperature corresponding to the maximum combustion rate of pulverized coal; simultaneously, they increase the heat released during pulverized coal combustion. During the pyrolysis stage of pulverized coal, the heat generated via organic component combustion in waste oil sludge promotes a cracking reaction and improves the development of the char's micropore. During the char combustion stage, no catalyst deactivation phenomenon occurs under the ratios of inorganic components in the two types of metallurgical dust and sludge. Two additives markedly reduce the activation energy of the combustion reaction.

Objective This study examined the role of agrin in the development of cholangiocarcinoma (CCA). Methods Western blotting was performed to detect the expression of target genes. The correlation between agrin expression and prognosis was analyzed using the Kaplan–Meier method. Proliferation, migration, invasion, and tumorigenesis were examined in CCA cells and tissues using the Cell Counting Kit-8 assay, cell cycle analysis, transwell migration assay, and nude mouse tumorigenicity assay in vivo, respectively. Results Agrin expression was significantly upregulated in CCA tissues compared with that in adjacent non-tumor tissues, and agrin expression was correlated with poorer tumor characteristics such as portal vein tumor thrombus, intrahepatic metastasis, and worse survival. Forced agrin expression in CCA cells apparently promoted proliferation, colony formation, migration, invasion, and cell cycle progression, but agrin depletion had the opposite effects. Furthermore, agrin-depleted CCA cells developed fewer and smaller tumors than control cells in vivo. Mechanistic analyses indicated that agrin activated the Hippo signaling pathway and induced the translocation of YAP to the nucleus. Conclusions Agrin promoted CCA progression by activating the Hippo signaling pathway, suggesting its promise as a target for CCA therapy.

Background: MicroRNAs have been recently declared to be contributed to the various aspects of osteosarcoma cells, including growth and survival, apoptosis, invasion, and chemoresistance. Objectives: The present study aimed to investigate the potentiating effects of miR-129 on the chemosensitivity of Saose-2 osteosarcoma cells to methotrexate (MTX) and underlying mechanisms. Methods: Saose-2 cells were transfected with miR-129 mimics using Lipofectamine. The cytotoxic effects of miR-129 and MTX on Saose-2 cells were measured using MTT assay. Scratch wound healing assay was used to evaluate cell migration. The apoptosis rate of cancer cells was also measured using ELISA Cell Death Assay and flow cytometry. The mRNA expression levels of target genes were measured using quantitative RT-PCR. Results: miR-129 mimic transfection significantly increased the expression levels of this miRNA in Saose-2 cells (P

Electrohydraulic Stewart platform is a multi-input and multi-output mechanical-hydraulic coupling system, which has the advantages of large power-to-weight ratio and high accuracy. It has been widely used in construction machinery, aerospace, and other fields. In the actual working process, especially in the high-speed motion, the Stewart platform movement process will produce a large impact and vibration and then affect the stability, accuracy, and service life of the platform. When the frequency of the external excitation coincides with the natural frequency of the electrohydraulic Stewart platform, it may cause the failure of the platform. Therefore, based on the relationship between the volumetric elastic modulus of the gas-bearing oil and the hydraulic stiffness of the leg, a mechanical-hydraulic coupling dynamic model of the electrohydraulic Stewart platform was established, and the natural frequencies and modal shapes of the platform were analyzed under typical conditions. The sensitivity calculation formula of the natural frequency of the system on the upper platform mass and the hydraulic stiffness of the outer leg is given by an analytical method, and the influence law of the upper platform mass and the outer leg stiffness on the natural frequency and the sensitivity of the electrohydraulic Stewart platform under typical conditions is discussed. This study can provide theoretical support for dynamic optimization of the electrohydraulic Stewart platform.

Objective. To research the impact of neutrophil-lymphocyte ratio (NLR) as a prognostic parameter in non-small-cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Methods. We searched the databases such as the American Society of Clinical Oncology (ASCO), EMBASE, PubMed, the European Society of Medical Oncology (ESMO), Wanfang, and CNKI for articles illustrating the impact of pretreatment NLR on survival data in NSCLC patients undergoing EGFR-TKIs treatment. We did a meta-analysis for overall survival (OS) and progression-free survival (PFS). Results. We recruited 10 studies in our meta-analysis. Our study suggested that patients with low NLR had better PFS (hazard ratio (HR) = 1.67, 95% confidence interval (CI) = (1.16–2.39), and P value = 0.005) and OS (HR = 1.66, 95% CI = (1.08–2.55), and P value = 0.02) in comparison to patients with high NLR. Conclusion. In conclusion, our meta-analysis revealed that lower NLR predicted a better survival (PFS and OS) in patients receiving the treatment of EGFR-TKIs.

In recent decades, heart disease threatens people’s health seriously because of its prevalence and high risk of death. Therefore, predicting heart disease through some simple physical indicators obtained from the regular physical examination at an early stage has become a valuable subject. Clinically, it is essential to be sensitive to these indicators related to heart disease to make predictions and provide a reliable basis for further diagnosis. However, the large amount of data makes manual analysis and prediction taxing and arduous. Our research aims to predict heart disease both accurately and quickly through various indicators of the body. In this paper, a novel heart disease prediction model is given. We propose a heart disease prediction algorithm that combines the embedded feature selection method and deep neural networks. This embedded feature selection method is based on the LinearSVC algorithm, using the L1 norm as a penalty item to choose a subset of features significantly associated with heart disease. These features are fed into the deep neural network we built. The weight of the network is initialized with the He initializer to prevent gradient varnishing or explosion so that the predictor can have a better performance. Our model is tested on the heart disease dataset obtained from Kaggle. Some indicators including accuracy, recall, precision, and F1-score are calculated to evaluate the predictor, and the results show that our model achieves 98.56%, 99.35%, 97.84%, and 0.983, respectively, and the average AUC score of the model reaches 0.983, confirming that the method we proposed is efficient and reliable for predicting heart disease.

Rationale: Venous leiomyosarcoma (LMS) is a malignant tumor arising from the smooth muscle cell of the vein wall. The diagnosis of venous LMS is usually delayed owing to its rarity, absence of serological markers, and mimicry with deep vein thrombosis (DVT). Herein, we report a case of a primary external ilian vein LMS characterized by long-term, unexplained DVT in the left lower limb. Contrast-enhanced ultrasound (CEUS) played a crucial role in the preoperative diagnosis. No improvement was observed in the lower limb status; a rapid, high-level, heterogeneous wash-in and wash-out mass of the vein, as seen with CEUS, could indicate angiogenic malignancy. CEUS also helped evaluate the percent of intratumoral necrosis, which is an important parameter for predicting the prognosis. Patient Concerns: A 37-year-old Chinese women presented to the Vascular Surgery Department of our hospital for accurate diagnosis of her condition. She began experiencing edema and pain in her left leg 2 years ago. She was diagnosed with DVT in the left lower extremity and was administered anticoagulant therapy since then. However, her symptoms started to aggravate 8 months ago. Diagnoses: The laboratory results including D-dimer, prothrombin time (PT), activated partial thrombin time (APTT), and prothrombotic conditions screening were within normal ranges. A pelvic ultrasound detected a heterogeneous, hypoechoic mass compressing the external iliac vein and obstructing the venous drain of the lower extremity. The mass showed a rapid, high-level, heterogeneous wash-in and wash-out on CEUS, which suggested angiogenic malignancy. Contrast-enhanced CT (CECT) confirmed the result of CEUS but revealed no metastasis. Interventions: She underwent complete surgical removal of the tumor, which was resected successfully. There was no infiltration in the inguinal nodes sent for the study. Outcomes: Pathological examination and immunohistochemistry confirmed that the mass was a well-differentiated LMS originating from the external iliac vein. There was no sign of local recurrence or distant metastasis during a 12–month follow-up. Lessons: Effective imaging techniques and differential diagnosis of venous LMS is vital and should be considered for patients with chronic thrombosis presenting with normal laboratory results.

Graphene with linear energy dispersion and weak electron-phonon interaction is highly anticipated to harvest hot-electrons in a broad wavelength range from ultraviolet to terahertz. However, the limited absorption (~2.3%) and serious backscattering of hot-electrons associated with single-layer graphene result in inadequate quantum yields, impeding their practically broadband photodetection, especially in the mid-infrared range. Here, we report a macroscopic assembled graphene (MAG)/silicon heterojunction for ultrafast mid-infrared photodetection. The highly crystalline 2-inch scale MAG with tunable thickness from 10 to 60 nm is produced by scalable wet-assembly of commercial graphene oxide followed by thermal annealing. The MAG/Si Schottky diode exhibits broadband photodetection capability in 1-10 μm at room temperature with fast response (120-130 ns, 4 mm2 window) and high detectivity (1011 to 106 Jones), outperforming single-layer graphene/Si photodetectors by 2 to 8 orders in transient photocurrent. This optoelectronic performance is attributed to the superior advantages of MAG (~40% of light absorption, ~23 ps of carrier relaxation time, and high quasi-equilibrated hot-carrier-multiplication gain), atomic-scale contact interface of MAG and silicon, and impact-ionization avalanche gain (~100 times) from silicon. The MAG provides a long-range platform to understand the hot-carrier dynamics in stacked 2D materials, leading to next-generation broadband silicon-based image sensors.

In low light condition, the captured images suffer from severe noise and loss of textures and details due to low signal-to-noise ratio (SNR). In this paper, we propose low light image enhancement by multispectral fusion of color (RGB) and near infrared (NIR) images. We adopt adaptive weighted total variation to take the multispectral advantages in fusion. Since the NIR imaging depends on the NIR light strength, the NIR values are not reliable out of the range that NIR light can reach. Thus, based on a sigmoid function, we selectively perform total variation regularization according to the NIR values. If the NIR values are reliable, we perform the multispectral fusion with the guidance of the NIR image. If the NIR values are not reliable, i.e. none or too low, we only perform total variation regularization for denoising on the RGB image without NIR gradient transfer. For optimization, we convert the non-convex total variation regularization into a linear system using iterative reweighted least squares. Experimental results demonstrate that the proposed method successfully transfer the NIR details into the fusion result while removing noise and keeping colors as well as it produces natural looking fusion results even with unreliable NIR values.

The demand for low-power flexible spintronics for sensing, communicating, and data processing applications boosts an intense search for novel ways of controlling magnetism. In this work, a photovoltaic controllable flexible spintronic device within a Kapton/Ta/Co/(PC71BM/PTB7-Th)/Pt heterostructure was demonstrated, and the magnetic anisotropy change of this flexible heterostructure as a function of the external light radiation and strain was quantitatively determined. 150 mW/cm2 white light illumination induced 489 Oe out-of-plane ferromagnetic resonance field modulation, which was attributed to the photogenerated electron doping in the cobalt film. The chemical contamination effect and the interfacial oxidation effect during the photovoltaic doping process were eliminated. Moreover, it was found that the working function of the thin-film electrodes were different from the bulk values via an ultraviolet photoelectron spectroscopy test. Our results on flexible photovoltaic spintronics systems will invigorate the research toward the development of solar-driven energy-efficient spintronics.

Layered two-dimensional (2D) hybrid perovskites are naturally formed multiple quantum well (QW) materials with promising applications in quantum and optoelectronic devices. In principle, the transport of excitons in 2D perovskites is limited by their short lifetime and small mobility to a distance within a few hundred nanometers. Herein, we report an observation of long-distance carrier transport over 2 to 5 μm in 2D perovskites with various well thicknesses. Such a long transport distance is enabled by trap-induced exciton dissociation into long-lived and nonluminescent electron-hole separated state, followed by a trap-mediated charge transport process. This unique property makes 2D perovskites comparable with 3D perovskites and other traditional semiconductor QWs in terms of a carrier transport property and highlights their potential application as an efficient energy/charge-delivery material.

Strong coupling between hyperbolic phonon-polaritons (HP) and magnetic polaritons (MP) is theoretically studied in a hexagonal boron nitride (hBN) covered deep silver grating structure. It is found that MP in grating trenches strongly interacts with HP in an anisotropic hBN thin film, leading to a large Rabi splitting with near-perfect dual band light absorption. Numerical results indicate that MP-HP coupling can be tuned by geometric parameters of the structure. More intriguingly, the resonantly enhanced fields for two branches of the hybrid mode demonstrate unusually different field patterns. One exhibits a volume-confined Zigzag propagation pattern in the hBN film, while the other shows a field-localization near the grating corners. Furthermore, resonance frequencies of these strongly coupled modes are very robust over a wide-angle range. The angle-insensitive strong interaction of hyperbolic-magnetic polaritons with dual band intense light absorption in this hybrid system offers a new paradigm for the development of various optical detecting, sensing and thermal emitting devices.

Parameter/gradient exchange plays an important role in large-scale distributed machine learning (DML). However, prior solutions such as parameter server (PS) or ring-allreduce (Ring) fall short since they are not resilient to issues or uncertainties like oversubscription, congestion or failures that may occur in datacenter networks (DCN). This paper proposes RAT, a new solution that determines the communication pattern for DML. At its heart, RAT establishes allreduce trees taking into account the physical topology and its oversubscription condition. The allreduce trees specify the aggregation pattern in which each aggregator is responsible for aggregating gradients from all workers within an oversubscribed region at the reduce phase, and broadcasting the updates back to workers at the broadcast phase. We show that such an approach can effectively reduce cross-region traffic and shorten dependency chain compared to prior solutions. We have evaluated RAT in both oversubscribed network and network with failures and found that RAT is resilient to these issues or uncertainties. For example, it delivers an average of 25X and 5.7X speedup compared to PS in oversubscribed network and Ring in network with failures, respectively.

Background: Recently, patients with COVID-19 who showed persistently positive SARS-CoV-2 nucleic acid test results despite resolved clinical symptoms have attracted a lot of attention. We report the case of a patient with mild symptoms of coronavirus disease (COVID-19), who achieved clinical recovery but showed persistently positive SARS-CoV-2 nucleic acid test results until Day 92 after disease onset.Case presentation: The patient is a 50-year-old man with mild symptoms of coronavirus disease (COVID-19). He was quarantined for 105 days. Of these, inpatient quarantine lasted for 75 days. When the nucleic acid test results were negative for 3 consecutive days, the patient was discharged at Day 75 after disease onset. During this period, multiple samples were collected from the patient’s body surface, the surrounding environment, and physical surfaces, but none of these tested positive for SARS-CoV-2. These samples included those from anal swabs, hands, inner surface of mask, cell phone, bed rails, floor around the bed, and toilet bowl surface. However, nucleic acid retest results on Day 80 and Day 92 after disease onset were positive for SARS-CoV-2 nucleic acids. The patient continued with quarantine and observation at home. After the test results on Days 101 and 105 after disease onset were negative, quarantine was terminated at last.Conclusion: Per our knowledge, this is the longest known time that a patient has tested positive for SARS-CoV-2 nucleic acids. No symptoms were observed during follow-up. During hospitalization, the SARS-CoV-2 nucleic acid positivity was not observed in samples from the body surface and surrounding environment, and no verified transmission event occurred during the quarantine at home. After undergoing clinical recovery a minority of patients with COVID-19 have shown long-term positive results for the presence of the SARS-CoV-2 nucleic acid. This has provided new understanding and research directions for coronavirus infection. Long-term follow-up and quarantine measures have been employed for such patients. Further studies are required to analyze potential infectivity in such patients and determine whether more effective antiviral drugs or regimens to enable these patients to completely clear viral infection should be researched.

Controllable and precise design of bimetal- or multimetal-semiconductor nanostructures with efficient light absorption, charge separation and utilization is strongly desired for photoredox catalysis applications in solar energy conversion. Taking advantage of Au nanorods, Pt nanoparticles, and CdS as the plasmonic metal, nonplasmonic co-catalyst and semiconductor respectively, we report a steerable approach to engineer the heterointerface of bimetal-semiconductor hybrids. We show that the ingredient composition and spatial distribution between the bimetal and semiconductor significantly influence the redox catalytic activity. CdS deposited anisotropic Pt-tipped Au nanorods, which feature improved light absorption, structure-enhanced electric field distribution and spatially regulated multichannel charge transfer, show distinctly higher photoactivity than blank CdS and other metal-CdS hybrids for simultaneous H2 and value-added aldehyde production from one redox cycle.

Background and Aims: The coronavirus pandemic has become a growing public health concern worldwide, and there are insufficient epidemiological data on critical illness. We sought to investigate the clinical course and features of critical patients with Corona Virus Disease 2019 (COVID-19).Method: The data on 94 critical patients from 8th February through 16th March 2020, including demographic and clinical information, were obtained from the intensive care unit (ICU) of Wuhan Huoshenshan Hospital. A cross-sectional survey and comparisons of key biomarkers between survivors and nonsurvivors were performed.Results: Over the study period, 42 nonsurvivors and 52 survivors were included. The overall case fatality rate for critical patients with COVID-19 was approximately 45%. The average age was 69.17±9.55 years, and the majority had underlying health problems such as hypertension (56[60%]) and diabetes (18[19%]). The median length of ICU stay was 8 days (IQR 4, 13). Compared with survivors, nonsurvivors were more likely to develop sepsis (42[100%] vs. 34[65%]), acute respiratory distress syndrome (40[95%] vs. 28[54%]) and organ dysfunction. In addition, the dynamic changes in some biomarkers were significantly different between the two groups. The trajectories of temperature revealed that the group with a high temperature on admission that steadily declined had the highest percentage of deaths (93.33%).Conclusion: Patients aged 60 years or older with many concomitant diseases were at highest risk, and the fatality rate started to increase with age. Lymphocyte, platelet, C-reactive protein and hypersensitivity troponin I were revealed to have potential as prognostic factors, whereas some other biomarkers, such as hepatic enzymes, may not offer additional information. Moreover, patients with high temperatures on admission should receive extra care.

In this Letter, we describe an aperiodic-oscillation emission phenomenon originating from the Fabry–Perot effect in the deep-ultraviolet backscattering fluorescence spectrum of the c -plane AlGaN film, which is related to the dispersion of its ordinary refractive index near the band edge. Based on this fluorescence spectrum, the ordinary refractive index of the AlGaN film near the band edge could be directly obtained. Certainly, by means of variable angle spectroscopic ellipsometry, the ordinary refractive index of the AlGaN film could be also achieved. Comparing the results obtained by both methods, we discovered that the refractive indices are quite similar, which suggests that the aperiodic-oscillation fluorescence spectrum is also a reliable approach to capture the refractive index of anisotropic optical films.

Microscale temperature mapping in liquids is of great importance in many areas of research such as microfluidics and biology. Among the current thermometric approaches, optical probing using fluorescence is particularly desirable because of its high spatial resolution and non-invasive nature. Here we report a new microscale two-dimensional (2D) fluorescence thermometry. This method exploits the temperature dependence of rotational molecular motion and its influence on the depolarization of fluorescence light, by measuring the difference in fluorescence intensities excited by orthogonal polarizations. With one charge coupled device (CCD) camera, we get 2D ratiometric mappings of temperature from successively recorded fluorescence images under alternatively polarized excitations. We demonstrate reliable temperature mapping in liquids at sub-1 °C temperature accuracy and sub-10 µm spatial resolution. We also show that the proposed thermometry approach is robust against fluorescence intensity variations, suitable for 2D mapping and of fast readout that is comparable to CCD framerate. Moreover, it is easy to be integrated into microscope systems since only rotation of excitation polarization is needed.

Over the past two decades, solar- and astrophysicists and material scientists have been researching and developing new-generation semiconductor-based vacuum ultraviolet (VUV) detectors with low power consumption and small size for replacing traditional heavy and high-energy-consuming microchannel-detection systems, to study the formation and evolution of stars. However, the most desirable semiconductor-based VUV photovoltaic detector capable of achieving zero power consumption has not yet been achieved. With high-crystallinity multistep epitaxial grown AlN as a VUV-absorbing layer for photogenerated carriers and p-type graphene (with unexpected VUV transmittance >96%) as a transparent electrode to collect excited holes, we constructed a heterojunction device with photovoltaic detection for VUV light. The device exhibits an encouraging VUV photoresponse, high external quantum efficiency (EQE) and extremely fast tempera response (80 ns, 104-106 times faster than that of the currently reported VUV photoconductive devices). This work has provided an idea for developing zero power consumption and integrated VUV photovoltaic detectors with ultrafast and high-sensitivity VUV detection capability, which not only allows future spacecraft to operate with longer service time and lower launching cost but also ensures an ultrafast evolution of interstellar objects.

In the process of conversion of solar energy into electricity and fuel, efficient electrocatalysts are indispensable. Rieske iron–sulfur protein and FeS catalysts play an important role in natural photosynthesis (NPS), and in artificial photoelectrochemical cells, respectively. Nano–micro composite catalysts (NMCCs) possess not only high catalytic activity but also fast electron transport. Herein, we prepared a nano–micro composite (NMC) of Fe1−xS nanoparticles decorated on sulfur-doped graphene oxide (S-GO) sheets (namely, Fe1−xS@S-GO–NMC) to be used as a cathode in dye-sensitized solar cells (DSCs). The GO effectively inhibit the aggregation of Fe1−xS nanoparticles. Notably, DSCs based on an Fe1−xS@S-GO–NMC cathode achieved a high solar-to-electrical conversion efficiency up to 7.23%. The conversion efficiency is, to our knowledge, one of the highest efficiencies for DSCs based on an FeS or FeS2 cathode. Although the Fe1−xS@S-GO–NMC exhibited a low thermodynamic possibility for redox reactions, it showed a higher kinetic rate than that of Pt for the charge transfer between the reaction medium and the cathode. This indicates that a fast electron exchange process occurs at the interface between the reaction and the cathode. The value of the time constant (τ) corresponding to the charge exchange resistance based on Fe1−xS@S-GO–NMC (0.0215 ms) was smaller than that obtained with Pt (0.261 ms). Therefore, we ascribed the superior performance of the photoelectrochemical device based on Fe1−xS@S-GO–NMC to its good electrocatalytic performance. The results are of great interest for fundamental research and for practical applications of FeS and FeS2 and their composites in the solar splitting of water, artificial photoelectrochemical cells, and electrocatalysts.

Mixed-composition perovskites (m-perovskites) are emerging as one of the hottest materials in the field of photovoltaics. However, a satisfactory m-perovskite film cannot always be attained even through a standard operating procedure. The formation of a m-perovskite film during transitory one-step spin-coating is a train of complex dynamic processes which are intimately bound up with solvent evaporation and anti-solvent interdiffusion. In these processes, many underappreciated variables that will greatly alter the mode of solvent behavior have rarely been taken into serious consideration. In this paper, the air flow velocity during spin-coating is proved to be a very important factor. A precise control over the formation as well as the decomposition of the intermediate phase can be realized through high-air-flow-velocity assisted spin-coating, which guarantees a subsequent controllable and high-quality crystallization of the m-perovskite. Finally, the planar-structured device exhibits the best efficiency of 20.24% (19.58% stabilized) with alleviated hysteresis and better long-term stability.

Organic–inorganic hybrid-based lead perovskites show inherent and unavoidable problems such as structural instability and toxicity. Therefore, developing low-cost and environment-friendly organic–inorganic hybrid materials is extremely urgent. In this study, we prepared earth-abundant and environment-friendly organic–inorganic hybrid tetrachloroferrate salt CH3NH3FeCl4 (MAFeCl4) for optoelectronic applications. The single crystal diffraction data are assigned to the orthorhombic MAFeCl4 (Pnma space group), with parameters a = 11.453 (5) A, b = 7.332 (3) A, c = 10.107 (5) A, α = 90.000, β = 90.000, and γ = 90.000. The band gap of MAFeCl4 is approximately 2.15 eV. Moreover, three-emission luminescence (398, 432 and 664 nm) was observed. To the best of our knowledge, this is the first study involving the investigation of the structure, adsorption properties and photoelectric behavior of MAFeCl4. A low cost photodetector based on the MAFeCl4 thin film is efficient under different monochromatic light from 330 nm to 410 nm with different chopping frequencies (1.33 Hz to 40 Hz). The photoelectric conversion efficiency based on FTO/TiO2/MAFeCl4/carbon electrode device reaches 0.054% (Voc = 319 mV, Jsc = 0.375 mA cm−2, and fill factor = 0.45) under AM1.5, 100 mW cm−2 simulated illumination. Our findings will attract attention from the magnetic, piezoelectric and photoelectronic research fields.

To improve the poor thermal properties of traditional structural insulated panels (SIPs) for better energy saving effect in the building, composited structural insulated panels (CSIPs) with glass fiber reinforced plastic (GFRP) and cement (GFRC) materials were developed in this study. ANSYS is used to simulate the thermal properties of SIPs and CSIPs, and energy consumption of a house with these creative CSIPs were simulated by EnergyPlus. The results indicated that the zone method and modified zone method are acceptable to compute the R-value of the SIPs and the CSIPs. However, isothermal method and the parallel method are unsuitable to calculate their thermal resistance. A reduction in the stud web area and replacement of the steel web by less conductive materials are two effective ways to improve the thermal performance of SIPs. Furthermore, in terms of energy savings and thermal properties, GFRP SIPs are considerably better than steel SIPs. The conclusions are: the thermal properties of CSIPs with GFRP, GFRC or wood sheathings are nearly the same. However, a tube stud should be preferentially selected considering that its mechanical properties, easy design and construction are better than that of a folded plate. Moreover, GFRP and GFRC sheathings are given priority over wood. The novelty and new contribution of this paper is to design a thermal insulation, mechanical and durable CSIP with GFRP and GFRC, and use ANSYS to calculate its thermophysical properties and use EnergyPlus to simulate the energy consumption of a house with this CSIP.

The bimodal resonance phenomena in photonic structure have received particular attention due to their intriguing optical properties and numerous potential applications. In this work, we investigated the mode transformation behaviors of the guided modes in an integrated bimodal resonance structure consisting of a single groove on the surface of an abruptly ended slab waveguide. Numerical simulations demonstrated that the strong mode transformation can occur in the anticrossing region of resonance at the oblique incidence of a transverse electric (TE)-polarized guided mode on the groove. According to the multiple-beam interference model, a theoretical formula was developed to study the resonance and mode transformation behaviors of the guided modes. The results showed that the different anticrossing behaviors of structure are resulting from the constructive and destructive interference of bimodal resonance. The resonance and mode transformation properties of structure can be controlled by adjusting the geometrical parameters of groove. The mode manipulation with high efficiency in the slab waveguide will have many applications in lab-on-a-chip devices, switching and on-chip spectroscopy.

Because of the removal of the material, the material quality and stiffness matrix of the thin-walled parts will be directly changed and the dynamic characteristics will be significantly changed in the aviation thin-walled parts of the NC machine. When the structural parameters caused by the removal process frequently change slightly, it is necessary to solve the generalized feature problem, by using the classical method to obtain the dynamic characteristics repeatedly or the measured mode. However, it is clear that these methods are time consuming, labor intensive, and are not suitable for efficient prediction of dynamic modes. The method of matrix perturbation is proposed in order to solve the natural modal of the modified thin-walled structure. The finite element method is used to analyze the free vibration of the thin-walled structured blades. Based on the frequency, stiffness matrix, mass array, and vibration data which were extracted from the analysis results, the natural frequency of the modified structural parameters is calculated by the matrix perturbation method; then, the calculated results are compared with the finite element calculation results as well as the measured results. These results show that the process of applying the matrix perturbation method to modify the natural mode is effective, reliable, and time saving in the dynamic mode prediction of thin-walled NC machine, which lays the foundation for the establishment of three-dimensional stability domain. Finally, it can also provide theoretical basis for the resonance suppression of milling process by analyzing the evolutional rule of thin-walled part milling.

Recently, two-dimensional organic–inorganic perovskites have attracted increasing attention due to their unique photophysical properties and high stability. Here we report a lead-free, two-dimensional perovskite, (PEA)2GeI4 (PEA = C6H5(CH2)2NH3+). Structural characterization demonstrated that this 2D perovskite structure is formed with inorganic germanium iodide planes separated by organic PEAI layers. (PEA)2GeI4 has a direct band gap of 2.12 eV, in agreement with 2.17 eV obtained by density functional theory (DFT) calculations, implying that it is suitable for a tandem solar cell. (PEA)2GeI4 luminesces at room-temperature with a moderate lifetime, exhibiting good potential for photovoltaic applications. In addition, 2D (PEA)2GeI4 is more stable than 3D CH3NH3GeI3 in air, owing to the presence of a hydrophobic organic long chain. This work provides a direction for the development of 2D Ge-based perovskites with potential for photovoltaic applications.

Multi-axis ball-end milling is the most commonly used operation in machining aerospace engine parts. Because of multi-output characteristic, the process improvement often requires multi-objective optimization. Recently, the grey relational analysis (GRA) has been more and more widely used in engineering manufacture with multiple responses. But, the original GRA method only suits for the optimization problem in discrete space. This paper proposes an integrated multi-objective optimization method with GRA, radial basis function (RBF) neural network, and particle swarm optimization (PSO) algorithm. Compared with the original GRA, it expands the optimal solution space to continuous space. This approach is subsequently applied to the multi-objective optimization of multi-axis ball-end milling Ni-based superalloy Inconel 718. The purpose is to simultaneously obtain minimum surface roughness and maximum compressive residuals tress by optimizing the inclination angle, cutting speed, and feed. A hybrid experiment scheme with single factor design and orthogonal array is utilized to generate the sample data set. The multi-response optimization problem is successfully converted into the single objective optimization of grey relational grade (GRG). Then, the RBF neural network is employed to establish the mapping relation between the GRG and the process parameters. And its adequacy is proved by five test experiments with a low prediction error of 6.86%. Finally, the PSO algorithm is adopted to optimize the process parameters. Verification experiments show that a higher improvement of the GRG is obtained with the proposed method (62.87%) than that of the original GRA (50.00%). The developed approach is proved to be feasible and can be generalized for other multi-objective optimization problem in manufacturing industry.

Cervical cancer is one of most malignant gynecological tumors. However, effective means for diagnosing and treating cervical cancer have yet to be identified. A few decades ago, long non-coding RNAs (lncRNAs) were regarded as useless parts of the genome, however, increasing data have demonstrated the importance of lncRNAs in the diagnosis and treatment of cervical cancers. The aim of the present study is to summarize the role(s) of HOTAIR, MALAT1, CCAT2, SPRY4-IT1, RSU1P2, CCHE1, lncRNA-EBIC and PVT1. Approximately 14 lncRNAs are involved in cervical cancer and several important proteins, miRNAs and other molecules and play crucial roles in a few traditional signaling pathways that have been proven to be related to those lncRNAs. In conclusion, lncRNAs may be useful as exact treatment targets and diagnostic biomarkers for improving therapies in cervical cancer patients and lncRNAs may contribute to effective diagnosis and treatment methods for cervical cancer.