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We reliably judge locations of static objects when we walk despite the retinal images of these objects moving with every step we take. Here, we showed our brains solve this optical illusion by adopting an allocentric spatial reference frame. We measured perceived target location after the observer walked a short distance from the home base. Supporting the allocentric coding scheme, we found the intrinsic bias1, 2, which acts as a spatial reference frame for perceiving location of a dimly lit target in the dark, remained grounded at the home base rather than traveled along with the observer. The path-integration mechanism responsible for this can utilize both active and passive (vestibular) translational motion signals, but only along the horizontal direction. This anisotropic path-integration finding in human visual space perception is reminiscent of the anisotropic spatial memory finding in desert ants3, pointing to nature’s wondrous and logically simple design for terrestrial creatures.

Phytoremediation of arsenic (As) by Pteris vittata (P. vittata) is a cost-effective and environmentally friendly method for restoring As-contaminated sites. However, the phytoextraction efficiency is low in some cases, such as clay soil, thus biochar was applied to enhance the efficiency of As extraction. The paper investigated the effect of biochar on soil characteristic, As mobility, and As uptake in P. vittata with a 90-day greenhouse experiment. Biochar derived from rice straw was added at rates of 0.5, 1.5, and 4% (w/w). The results showed that, under biochar amendment, soil pH raised from 5.24 to 6.03 and 4.91 to 5.85, soil dissolved organic carbon (DOC) increased 11.1–46.1% and 2.8–11.2%, respectively, in rhizosphere and bulk soils. Biochar also increased soil catalase (CAT) activity significantly, especially for the rhizosphere soil. Besides, biochar increased the labile As in the soils and transfer coefficient from roots to aboveground, thereby enhancing As accumulation by P. vittata tissues. The accumulation of As in fronds of P. vittata was up to 350 mg kg−1 in 1.5% biochar, which was more than twice the control and far beyond other biochar treatments. The results indicate that biochar addition is favorable to improve phytoremediation of P. vittata in As-contaminated soil and 1.5% (w/w) biochar may be a reasonable application ratio, thus providing an effective solution to enhance the efficiency of As phytoextraction. Biochar increased soil catalase activity in the rhizosphere of P. vittata. Biochar increased the labile concentration of arsenic in soil and arsenic accumulation in P. vittata significantly. Combining biochar and P. vittata reduced arsenic in soil. Biochar amendment was favorable for phytoremediation of P. vittata in arsenic-contaminated soil.

Tanning sludge, chrome tanned buffing dust and chrome shavings were selected as experimental materials. The non-isothermal distributed activation energy model (DAEM) was used to study the pyrolysis kinetic parameters. The effects of particle size and temperature on the distribution of co-pyrolysis products of various tanning wastes were investigated in a fixed-bed pyrolysis reactor, which provided a new approach for comprehensive thermal treatment of various tannery wastes. The results showed that the total activation energy required for the co-pyrolysis decreased and then increased in the range of conversion rate of 0.1 to 0.8. The tar yield decreased with raising particle size, while the yields of gas and char increased. With the increase of pyrolysis temperature, the tar yield increased rapidly to a peak value of 17% at 600 ℃, and then decreased, correspondingly the char yield decreased while the gas yield increased. When the pyrolysis temperature was 600 ℃ and the particle size of the material was 1.6–2.5 mm, the specific surface area of char was larger, and the light fractions in tar was higher. Thus the co-pyrolysis was conducive to the clean treatment of tannery wastes.

Fourteen new sulphur-containing amides, glycocramides A-N (1-14), as well as nine known analogues (15-23) were isolated and characterized from Glycosmis craibii Tanaka. The chemical structures of new sulphur-containing amides 1-14 were ambiguously elucidated by extensive spectroscopic methods, while the known compounds 15-23 were identified by the comparison of their experimental spectral data with those described data in the literatures. The antiproliferative effects of all isolated sulphur-containing amides were evaluated in vitro. As a result, part of sulphur-containing amides showed remarkable inhibitory effects against MGC-803 cell line with IC

The goal of this study was to evaluate the effectiveness of radiomics signatures on pre-treatment computed tomography (CT) images of lungs to predict the tumor responses of non-small cell lung cancer (NSCLC) patients treated with first-line chemotherapy, targeted therapy, or a combination of both. This retrospective study included 322 NSCLC patients who were treated with first-line chemotherapy, targeted therapy, or a combination of both. Of these patients, 224 were randomly assigned to a cohort to help develop the radiomics signature. A total of 1946 radiomics features were obtained from each patient’s CT scan. The top-ranked features were selected by the Minimum Redundancy Maximum Relevance (MRMR) feature-ranking method and used to build a lightweight radiomics signature with the Random Forest (RF) classifier. The independent predictive (IP) features (AUC > 0.6, p value

A new tyramine derivative, glycosamide A (1), together with two known amide alkaloids, N-benzoyltyramine methyl ether (2) and aurantiamide acetate (3), was isolated from the branches and leaves of Glycosmis craibii Tanaka. Their structures were elucidated through extensive 1D and 2D NMR and HR-ESI-MS spectroscopic analyses. All known compounds were isolated from the genus Glycosmis for the first time. Furthermore, the antiproliferative activities of all isolated alkaloids in vitro were evaluated. Compound 2 displayed weak antiproliferative activities against five human cancer cell lines, HL-60, SMMC-7721, A-549, MCF-7, and SW480.

Two new aldoximes A–B (1−2), and two known analogues (3−4), were identified from ethanolic extracts of Glycosmis craibii. The structures of new compounds 1−2 were unambiguously elucidated based on spectroscopic methods. All isolated aldoximes were evaluated for their anti-inflammatory activity in vivo. Compounds 1−4 displayed remarkable inhibitory effects against nitric oxide (NO) production stimulated by lipopolysaccharide in mouse macrophage RAW 264.7 cells with the IC50 values ranging from 2.38 ± 0.08–8.43 ± 0.21 μM.

As one of the most important and frequently used molecular imaging techniques in the clinic, positron emission tomography (PET) features high sensitivity and specificity, which generally involves the use of PET contrast agents. Despite the exceptional promise, the availability of novel PET agents could limit its application and there is a clear need to develop new PET agents to improve our understanding of targets of interest and increase the diagnostic specificity.Based on the fact that amino acid transport and protein anabolism are increased in tumor tissues, a series ofOur data shows that [Clearly, [

Background Previous studies proved that pyrin domain-containing protein 3 (NLRP3)-induced pyroptosis plays an important role in Myocardial ischemia-reperfusion injury (MIRI). Insulin can inhibit the activation of NLRP3 inflammasome, although the exact mechanism remains unclear. The aim of this study was to determine whether insulin reduces NLRP3-induced pyroptosis by regulating pyruvate dehydrogenase E1alpha subunit (PDHA1) dephosphorylation during MIRI. Methods Rat hearts were subject to 30 min global ischemia followed by 60 min reperfusion, with or without 0.5 IU/L insulin. Myocardial ischemia-reperfusion injury was evaluated by measuring myocardial enzymes release, Cardiac hemodynamics, pathological changes, infarct size, and apoptosis rate. Cardiac aerobic glycolysis was evaluated by measuring ATP, lactic acid content, and pyruvate dehydrogenase complex (PDHc) activity in myocardial tissue. Recombinant adenoviral vectors for PDHA1 knockdown were constructed. Pyroptosis-related proteins were measured by Western blotting analysis, immunohistochemistry staining, and ELISA assay, respectively. Results It was found that insulin significantly reduced the area of myocardial infarction, apoptosis rate, and improved cardiac hemodynamics, pathological changes, energy metabolism. Insulin inhibits pyroptosis-induced inflammation during MIRI. Subsequently, Adeno-associated virus was used to knock down cardiac PDHA1 expression. Knockdown PDHA1 not only promoted the expression of NLRP3 but also blocked the inhibitory effect of insulin on NLRP3-mediated pyroptosis in MIRI. Conclusions Results suggest that insulin protects against MIRI by regulating PDHA1 dephosphorylation, its mechanism is not only to improve myocardial energy metabolism but also to reduce the NLRP3-induced pyroptosis.

Boron neutron capture therapy (BNCT) is a promising cancer treatment strategy that utilizes boron-containing ligands. In this report, a series of substituted boramino acids were synthesized and evaluated, aiming to obtain metabolically stable boron-derived agents that could integrate positron emission tomography (PET) with BNCT (a theranostic agent). Based on the phenylalanine (Phe) core structure, the impact of substitution groups on tumor accumulation was studied. The agents were labeled with fluorine-18 in 27.2-66.8% yield via the

Deep neural networks (DNNs) have been widely adopted in brain lesion detection and segmentation. However, locating small lesions in 2D MRI slices is challenging, and requires to balance between the granularity of 3D context aggregation and the computational complexity. In this paper, we propose a novel view-disentangled transformer to enhance the extraction of MRI features for more accurate tumour detection. First, the proposed transformer harvests long-range correlation among different positions in a 3D brain scan. Second, the transformer models a stack of slice features as multiple 2D views and enhance these features view-by-view, which approximately achieves the 3D correlation computing in an efficient way. Third, we deploy the proposed transformer module in a transformer backbone, which can effectively detect the 2D regions surrounding brain lesions. The experimental results show that our proposed view-disentangled transformer performs well for brain lesion detection on a challenging brain MRI dataset., International Symposium on Biomedical Imaging (ISBI) 2022, code: https://github.com/lhaof/ISBI-VDFormer

The stability, elastic properties and conductive properties of Cu-doped SnO2, S-doped SnO2 and Cu, S-codoped SnO 2were studied by using the first-principles calculation method based on the density functional theory. The corresponding doped SnO2 powders were prepared by sol–gel method, while AgSnO2–Cu and AgSnO2–Cu–S contacts were obtained by powder metallurgy method for experimental verification. No diffraction peaks were associated with Cu and S in the XRD patterns of the doped SnO2 powders, indicating that the doped SnO2 retained the tetragonal crystal structure. The doping formation energy of Cu, S co-doped system was found to be lower than that of Cu single doping system and S single doping system. The bulk modulus, shear modulus and Young's modulus of the co-doped system became lower, the ability to resist compression deformation and shear deformation was also weakened, while its toughness was greatly improved. The hardness of the AgSnO2–Cu–S contact was 103.55 HV, which is less than the hardness of the AgSnO2–Cu contact (112.86 HV). The calculations indicated that Cu, S co-doping could narrow the band gap, reduce the hole effective mass and the acceptor ionization energy, improve the hole mobility, and enhance the conductivity of the material. The electrical contact simulation experiments showed that the conductive properties, arc corrosion resistance and welding resistance of AgSnO2–Cu–S contact were better than those of the AgSnO2–Cu contact. The conductivity of AgSnO2–Cu–S contact was 29.948 mS · m–1, the contact resistance was 1.109 Ωm ; the average arc duration and average arc energy were 1.480 ms and 171.65 mJ, respectively.

Carrier recombination and charge loss at the interfaces of perovskite layers have a significant influence on high-performance planar perovskite solar cells (PSCs). We employed two-dimensional graphitic carbon nitride (g-C3N4), which is a heat-resistant n-type semiconductor, to modify the electron-transport layer/perovskite and perovskite/hole-transport layer interfaces, respectively. g-C3N4 could passivate the surface trap states of the methylammonium lead iodide light absorber through the formation of a Lewis adduct between N and the under-coordinated Pb, and it could also remarkably reduce the grain boundaries between perovskite crystal particles. A maximum power conversion efficiency (PCE) of 19.67% (Voc = 1.14 V, Jsc = 21.45 mA cm−2, FF = 0.807) could be obtained from planar PSCs with long-term stability using dual-positioned g-C3N4. Therefore, we consider that ultrathin semiconductor films with a Lewis base nature are suitable as dual-functional transport materials for devices. This work provides new guidance for dual-interfacial modification to improve the PCE and stability of devices.

18F-Labeled blood pool agents (BPAs) have attracted great attention for identifying bleeding sites. However, many BPAs are not sufficiently evaluated partially due to the limitations of labeling methods. In our previous work, we noticed that 18F-PEG1-vinyl sulfone (18F-VS) could efficiently label red blood cells (RBCs) ex vivo and in situ. However, its application as BPA is not fully evaluated. In this study, we systematically explored the feasibility of using 18F-VS-labeled RBCs as a positron emission tomography (PET) BPA for intra-abdominal bleeding diagnosis. In brief, we first optimized the labeling conditions, which lead to an 80% labeling yield of RBCs after incubating with 18F-VS in phosphate-buffered saline (PBS) at 37°C for 20 min. 18F-VS-labeled RBCs were found to be stable in vitro, which could simplify its transportation/storage for in vivo applications. In normal rat PET study, the cardiovascular system could be clearly imaged up to 5 h post injection (p.i.). An intra-abdominal hemorrhage rat model demonstrated that the 18F-VS-labeled RBCs clearly showed the dynamic changes of extravascular radioactivity due to intra-abdominal hemorrhage. Validation in the model of gastrointestinal bleeding clearly demonstrated the great potential of using 18F-VS-labeled RBCs as a BPA, which could be further evaluated in future studies.

The memristor is also a basic electronic component, just like resistors, capacitors and inductors. It is a nonlinear device with memory characteristics. In 2008, with HP’s announcement of the discovery of the TiO2 memristor, the new memristor system, memory capacitor (memcapacitor) and memory inductor (meminductor) were derived. Fractional-order calculus has the characteristics of non-locality, weak singularity and long term memory which traditional integer-order calculus does not have, and can accurately portray or model real-world problems better than the classic integer-order calculus. In recent years, researchers have extended the modeling method of memristor by fractional calculus, and proposed the fractional-order memristor, but its concept is not unified. This paper reviews the existing memristive elements, including integer-order memristor systems and fractional-order memristor systems. We analyze their similarities and differences, give the derivation process, circuit schematic diagrams, and an outlook on the development direction of fractional-order memristive elements.

Purpose This paper aims to build a legal intelligent auxiliary discretionary system for predicting the penalty and damage compensation values. After extensively considering current the characteristics of the current Chinese legal system, a practical legal intelligent auxiliary discretionary system based on genetic algorithm-backpropagation (GA-BP) neural network (NN) is proposed herein. Design/methodology/approach An experiment is designed to analyze cases involving mental anguish compensation in medical disputes, and a Chinese legal intelligent auxiliary discretionary adviser system is built based on a GA-BP NN. Because BP neural networks perform well for nonlinear problems and GAs can improve their ability to find optimal values, and accelerate their convergence, a combined GA–BP algorithm is used. In addition, an ontology is used to reduce the semantic ambiguities and extract the implied semantic information. Findings We confirm that a case-based legal intelligent auxiliary discretionary adviser system based on a GA-BP NN and ontology techniques has good performance in prediction. By predicting the mental anguish compensation values, the legal intelligent auxiliary discretionary adviser system can help judges to handle cases more quickly and ordinary people to discover the suggested compensation or penalty. In contrast to BP NN or SVM, the result seems more close to the actual compensation rate. Practical implications Recently, smart court has been developed in China; the purpose of which is to build the legal advice system for improving judicial justice and reducing differences in sentencing. A practical legal advice system is an urgent requirement for the judiciary. Originality/value This paper presents a study of a case-based legal intelligent auxiliary discretionary adviser system based on a GA-BP NN and ontology techniques. The findings offer advice to optimize legal intelligent auxiliary discretionary adviser systems for mental anguish compensation in medical disputes.

The pivotal role of magnetic anisotropy in stabilising two-dimensional (2D) magnetism has been widely accepted, however, direct correlation between magnetic anisotropy and long-range magnetic ordering in the 2D limit is yet to be explored. Here, using angle- and temperature-dependent tunnelling magnetoresistance, we report unprecedented metamagnetic phase transitions in atomically-thin CrOCl, triggered by magnetic easy-axis flipping instead of the conventional spin flop mechanism. Few-layer CrOCl tunnelling devices of various thicknesses consistently show an in-plane antiferromagnetic (AFM) ground state with the easy axis aligned along the Cr-O-Cr direction (b-axis). Strikingly, with the presence of a magnetic field perpendicular to the easy-axis (H||c), magnetization of CrOCl does not follow the prevalent spin rotation and saturation pattern, but rather exhibits an easy-axis flipping from the in-plane to out-of-plane directions. Such magnetic anisotropy controlled metamagnetic phase transitions are manifested by a drastic upturn in tun- nelling current, which shows anomalous shifts towards higher H when temperature increases. By 2D mapping of tunnelling currents as a function of both temperature and H, we determine a unique ferrimagnetic state with a superstructure periodicity of five unit cells after the field-induced metam- agnetic transitions. The feasibility to control 2D magnetism by manipulating magnetic anisotropy may open enormous opportunities in spin-based device applications., Comment: 7 pages, 4 figures

Hardy-Weinberg equilibrium assay for rs653765 and rs514049 genotypes in sepsis patients and healthy controls.

Background: LncRNA ZNFX1 antisense RNA 1 (ZFAS1) is largely reported to be abnormally expressed in various human cancers and associated with unfavorable prognosis. So this study aims to further investigate its clinical value in multifarious cancers.Methods: Databases of PubMed, Web of science, Cochrane library, Embase, Chinese National Knowledge Infrastructure and Wanfang was retrieved to collect eligible studies until October 22, 2020. The clinical role of ZFAS1 was comprehensively assessed by STATA 12.0. Additionally, the CeRNA network in which ZFAS1 involved was constructed. And function analysis of targeted mRNAs was performed by R package “cluster profiler”.Results: 23 studies of 2263 cancer patients met the inclusion criteria in this meta-analysis. The comprehensive results suggested that patients with elevated ZFAS1 expression got poor overall survival (OS) (HR=1.80, 95%CI: 1.50-2.10, P≤0.001), and they are prone to lymph node metastasis (OR=2.67, 95%CI: 1.73-4.14, P≤0.001), distant metastasis (DM) (OR=3.45, 95%CI: 1.61-7.39, P=0.001), advanced TNM stage (HTS) (OR=2.99, 95%CI: 1.97-4.54, P≤0.001), larger tumor size (LTS) (OR=1.54, 95%CI: 1.05-2.24, P≤0.001), poor histologic grade (PHG) (OR=1.57, 95%CI: 1.09-2.26, P=0.015). The CeRNA network and function analysis revealed the potential mechanism which ZFAS1 may involve in cancers.Conclusion: The current analysis revealed that elevated ZFAS1 expression is common in various cancer and was significantly associated with poor OS and clinical characteristics, thus it may function as prognostic biomarker in various cancer. Nevertheless, larger well-designed clinical research a is still warranted to verify our findings.

Hydrogen energy, as an ideal renewable resource and green energy replacement, has attracted growing attention. However, constructing highly active and stable catalysts for hydrogen evolution from Formic acid (FA) is still a challenging issue for development of renewable hydrogen energy. Herein, we develop a facile defect engineering strategy to construct N-deficient ordered mesoporous graphitic carbon nitride coupled with AgPd nanoparticles (denoted as AgPd/N-ompg-C3N4). Impressively, the as-prepared Ag0.1Pd0.9/N-ompg-C3N4 catalyst exhibits remarkable activity with the Turnover frequency (TOF) value of 1588.2 h−1 and robust stability with only a slight decrease in activity after ten cycles. Such markedly enhanced catalytic performance of Ag0.1Pd0.9/N-ompg-C3N4 is mainly attributed to the unique structure of N-ompg-C3N4 with higher surface area and abundant surface defects, the strong metal − support interaction between AgPd and N-ompg-C3N4, and charge transfer from Pd to Ag. This study provides a novel and efficient strategy for designing efficient catalysts to drive the hydrogen evolution from FA.

Entomopathogenic fungi have high potential for controlling insect pests, although the slow killing speed has blocked their widespread application. To increase the virulence of entomopathogenic fungi, genetic modification can be employed. Egf1.0 is an immunosuppressive protein encoded by polydnavirus, carried by parasitoid wasp Microplitis demolitor, which blocks the prophenoloxidase (PPO) activation response of host insects. In this study, we explored the feasibility of genetically modifying entomopathogenic fungi with increased virulence by expressing Egf1.0. In comparison with the wild-type parents, the median lethal concentration (LC50) of Beauveria bassiana expressing Egf1.0 against Helicoverpa armigera was reduced by 2.7-fold, and the median lethal time (LT50) was reduced by 22.8%. In vitro assay showed that recombinant Egf1.0 was able to inhibit the PPO activation response of H. armigera. In vivo assay revealed that the expression of Egf1.0 in B. bassiana caused a higher degree of suppression to PPO activation response of H. armigera. These assays suggested that the increased virulence of the transgenic fungi is due to the increased ability to suppress the host insect's immune response. Moreover, colony growth, conidia yield, and germination assays revealed that the expression of Egf1.0 in B. bassiana had no effect on its growth and development. In conclusion, the expression of Egf1.0 can significantly enhance the pathogenicity of B. bassiana against host insects.

This paper is a summary of the author's research process in the developing and designing the image recognition system based on artificial intelligence. ARTIFICIAL INTELLIGENCE CONCEPTS •Image recognition refers to the technology of using computer to process, analyze and understand the image to identify different patterns of targets and objects. It is a practical application of deep learning algorithm. At present, image recognition technology is generally divided into face recognition and commodity recognition. Face recognition is mainly used in security inspection, identity verification and mobile payment. Commodity recognition is mainly used in commodity circulation process, especially in unmanned retail fields such as unmanned shelf and intelligent retail cabinet.

Objectives: To establish a radiomic algorithm based on grayscale ultrasound images and to make preoperative predictions of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. Methods: In this retrospective study, 322 cases of histopathologically confirmed HCC lesions were included. The classifications based on preoperative grayscale ultrasound images were performed in two stages: (1) classifier #1, MVI-negative and MVI-positive cases; (2) classifier #2, MVI-positive cases were further classified as M1 or M2 cases. The gross-tumoral region (GTR) and peri-tumoral region (PTR) signatures were combined to generate gross- and peri-tumoral region (GPTR) radiomic signatures. The optimal radiomic signatures were further incorporated with vital clinical information. Multivariable logistic regression was used to build radiomic models. Results: Finally, 1,595 radiomic features were extracted from each HCC lesion. At the classifier #1 stage, the radiomic signatures based on features of GTR, PTR, and GPTR showed area under the curve (AUC) values of 0.708 (95% CI, 0.603–0.812), 0.710 (95% CI, 0.609–0.811), and 0.726 (95% CI, 0.625–0.827), respectively. Upon incorporation of vital clinical information, the AUC of the GPTR radiomic algorithm was 0.744 (95% CI, 0.646–0.841). At the classifier #2 stage, the AUC of the GTR radiomic signature was 0.806 (95% CI, 0.667–0.944). Conclusions: Our radiomic algorithm based on grayscale ultrasound images has potential value to facilitate preoperative prediction of MVI in HCC patients. The GTR radiomic signature may be helpful for further discriminating between M1 and M2 levels among MVI-positive patients.

Denoising images contaminated by the mixture of additive white Gaussian noise (AWGN) and impulse noise (IN) is an essential but challenging problem. The presence of impulsive disturbances inevitably affects the distribution of noises and thus largely degrades the performance of traditional AWGN denoisers. Existing methods target to compensate the effects of IN by introducing a weighting matrix, which, however, is lack of proper priori and thus hard to be accurately estimated. To address this problem, we exploit the Pareto distribution as the priori of the weighting matrix, based on which an accurate and robust weight estimator is proposed for mixed noise removal. Particularly, a relatively small portion of pixels are assumed to be contaminated with IN, which should have weights with small values and then be penalized out. This phenomenon can be properly described by the Pareto distribution of type 1. Therefore, armed with the Pareto distribution, we formulate the problem of mixed noise removal in the Bayesian framework, where nonlocal self-similarity priori is further exploited by adopting nonlocal low rank approximation. Compared to existing methods, the proposed method can estimate the weighting matrix adaptively, accurately, and robust for different level of noises, thus can boost the denoising performance. Experimental results on widely used image datasets demonstrate the superiority of our proposed method to the state-of-the-arts.

We study the two-echelon vehicle routing problem, in which the delivery to customers from a depot with transits through satellites. The goal is to find the minimum total routing cost and minimize the cost of single point of demand, more precisely, to find an approximate algorithm minimizing the approximation ratio, which compares the performance of this approximate algorithm with the optimal solution. In this paper, we describe a formulation for this problem and present an approximate algorithm GA to find the minimum total routing cost. We prove approximation ratio for the algorithm GA. Finally, we conduct extensive computational experiments to measure the performance of the approximate algorithm GA, the computational results indicate that the approximate algorithm GA can effectively solve various instances of the problem.

Objectives The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the risk of complications. This study aims to develop a cross-modal 3D neural network based on CT images and prior clinical knowledge for accurate prediction of LN metastasis in clinical stage T1 lung adenocarcinoma. Patients and methods Five hundred one lung adenocarcinoma patients with clinical stage T1 were enrolled. Data including: corresponding 3D nodule-centered patches of CT; prior clinical features; and pathological labels of LN status were obtained. We proposed a cross-modal deep learning system, which can successfully incorporate prior clinical knowledge and CT images into a 3D neural network to predict LN metastasis. We trained and validated our system with 401 cases and tested its performance with 100 cases. The result was compared with that of the logistic regression integration model, the single deep learning model without prior clinical knowledge integration, radiomics method, and manual evaluation by radiologists. Results The model proposed DensePriNet achieved an AUC of 0.926, which is significantly higher than the logistic regression integration model (0.904) single deep learning model (0.880), and radiomics method (0.891). The Matthews Correlation Coefficient (MCC) of DensePriNet (0.705) was significantly higher than manual classification by one senior radiologist (0.534) and one junior radiologist (0.416), respectively. Conclusion The performance of the single deep learning method is significantly higher than the radiomics method and the radiologists, and integration of prior clinical knowledge into the deep learning model enhance the diagnostic precision of LN status and facilitate the application of precision medicine.

Bi-bearing Al-Ga-In-Sn quinary alloys were prepared by a high-temperature melting technique. The alloys primarily consist of Al(Ga) matrix and Ga, In, Sn, Bi (GISB) grain boundary phase, mainly in the form of Ga-InSn4-InBi. The microstructure of GISB particles was obviously equiaxed with the increasing Bi dosage. Al-water reaction was tested at 40 °C. Owing to the Bi-doping, the hydrogen generation yields of alloys with InSn4 intermetallic compound are obviously improved and hydrogen release rates gradually tend to be stable, which show great potential in applications. At the dosage of 2.53 wt% Bi, the hydrogen generation performance of alloys was more prominent in Al-water reaction, including a theoretical hydrogen generation yield and hydrogen released extremum rate to ∼0.076 L/min·g Al alloy. Furthermore, the Al-water reaction mechanism of Bi-bearing Al-rich low-In quinary alloys has been put forward.

Cu-containing Al-Ga-InSn4 quinary alloys were prepared by a simple smelting method under a high-purity nitrogen atmosphere, and the alloys were cast at room temperature. The microstructures were investigated using X-ray diffraction (XRD) and scanning electron microscopy (SEM) with energy-dispersive X-ray (EDX) spectroscopy analysis. In addition to the InSn4 intermetallic compounds, elemental Cu was found in the alloys. As the Cu content increased, more holes and cracks were formed, and the Al(Ga) solid solution was pulverized. The melting points of Al compounds with the other elements were determined by differential scanning calorimetry (DSC). The alloy and water reactions were investigated at a water temperature of 40 °C. The Cu addition not only increased the hydrogen yield of the Al-Ga-InSn4 alloys but also stabilized the hydrogen generation from the Al-water reaction, which indicated that the Al-Ga-InSn4-Cu alloys are more suitable as fuel hydrogen sources for proton exchange membrane fuel cells. Based on the DSC and SEM with EDX studies, we propose the reasons for the changes in the Al-water reaction with the Cu addition.

Cyprotuoside C (1) and cyprotuoside D (2), two new cycloartane glycosides were isolated from the ethanol extract of the rhizomes of Cyperus rotundus. Their structures were identified as 24R-9,10-seco-cycloartan-1(10),9(11)-dien-3β,7β,24,25-tetraol 3-O-β-D-xylopyranosyl-(1→4)-[α-L-arabinopyranosyl-(1→6)]-β-D-glucopyranosyl-25-O-β-D-glucuronide (1) and 9,10-seco-cycloartan-1(10),9(11),23(24)-trien-3β,7β,25-triol 3-O-β-D-xylopyranosyl-(1→4)-{α-L-arabinopyranosyl-(1→6)-[α-L-rhamnopyranosyl-(1→2)]}-β-D-glucopyranosyl-25-O-β-D-glucuronide (2) by spectroscopic methods.

Ni-rich cathodes used in lithium-ion batteries can provide a desirable increase in energy density due to their high specific capacity, such as NMC622 (LiNi0.6Co0.2Mn0.2O2) and NMC811 (LiNi0.8Co0.1Mn0.1O2). However, the higher capacity of Ni-rich cathodes comes with a downside: faster capacity fade and lower cycling stability. The source of capacity fade for these cathodes has been attributed to multiple degradation mechanisms including particle cracking[1], irreversible structural changes[2], and side reactions that catalyze electrolyte decomposition[3]. Previous studies have shown evidence that electrolyte additives that influence the cathode surface can inhibit cycling-induced degradation with high-nickel cathodes[4,5]. In this study, we investigate the cycling stability of multi-layer pouch cells with NMC622 or NMC811 cathodes and graphite anodes, and the effects of different additives on cycling performance and impedance. Our study shows that in batteries with Ni-rich cathodes, organosilicon additives significantly improve cycling stability, as well as reduce gas generation during cycling. We use XPS to study the electrode surface compositions after different stages of cycling, and specific surface features are identified that correlate to performance and impedance over the course of cycling. NMR is used to monitor the consumption of additives from the liquid electrolyte. Through depth profiling and XPS signal attenuation, the surface layer thicknesses on the anodes and cathodes are estimated, and compared across different cycling protocols and different additives. It is proven that organosilicon additives alter the cathode and anode surface compositions, and the effect of changing the additive concentration on cycling stability and the electrode surfaces is also demonstrated. Varying structural features on the organosilicon additives, such as the degree of fluorination and type of functional group, are shown to impact the electrode interaction, impedance, and cycling stability. The impact of additives on reducing gas generation and affecting the gas composition is also quantified by the Archimedes method and gas chromatography. Overall, through this study we aim to provide enhanced understanding of the role of surface chemistry as an agent and an indicator of battery performance, and the effects of additives on surface chemistry and cycling stability. S. Oswald, D. Pritzl, M. Wetjen, H. A. Gasteiger, J. Electrochem. Soc., 167 (2020) 100511. C. Xu, K. Märker, J. Lee, A. Mahadevegowda, P. J. Reeves, S. J. Day, M. F. Groh, S. Emge, C. Ducati, B. L. Mehdi, C. C. Tang, C. P. Grey, Nat. Mater. (2020). A. T. S. Freiberg, M. K. Roos, J. Wandt, R. de Vivie-Riedle, H. A. Gasteiger, J. Phys. Chem. A, 122 (2018) 8828. T. Yim, K. S. Kang, J. Mun, S. H. Lim, S-G. Woo, K. J. Kim, M-S. Park, W. Cho, J. H. Song, Y-K. Han, J-S. Yu, Y-J. Kim, J. Power Sources, 302 (2016) 431. K. Kim, Y. Kim, S. Park, H. J. Yang, S. J. Park, K. Shin, J-J. Woo, S. Kim, S. Y. Hong, N-S. Choi, J. Power Sources, 396 (2018) 276.

The removal of cationic dyes, methylene blue(MB) and rhodamine B(RB), and anionic dyes, methyl orange(MO) and eosin Y(EY), from aqueous solutions by adsorption using Cu2Se nanoparticles(Cu2SeNPs) was stu-died. The effects of the initial pH values, adsorbent doses, contact time, initial dye concentrations, salt concentrations, and operation temperatures on the adsorption capacities were investigated. The adsorption process was better fitted the Langmuir equation and pseudo-second-order kinetic model, and was spontaneous and endothermic as well. The adsorption mechanism was probably based on the electrostatic interactions and π-π interactions between Cu2SeNPs and dyes. For an adsorbent of 0.4 g/L of Cu2SeNPs, the adsorption capacities of 23.1(MB), 22.9(RB) and 23.9(EY) mg/g were achieved, respectively, with an initial dye concentration of 10 mg/g(pH=8 for MB and pH=4 for RB and EY) and a contact time of 120 min. The removal rate of MB was still 70.4% for Cu2SeNPs being reused in the 5th cycle. Furthermore, the recycled Cu2SeNPs produced from selenium nanoparticles adsorbing copper were also an ef-fective adsorbent for the removal of dyes. Cu2SeNPs showed great potential as a new adsorbent for dyes removal due to its good stability, functionalization and reusability.

Short DNA represents an important class of biomacromolecules that are widely applied in gene therapy, editing, and modulation. However, the development of simple and reliable methods for their intracellular delivery remains a challenge. Herein, we describe that seven water-soluble, homogeneous supramolecular organic frameworks (SOFs) with a well-defined pore size and high stability in water that can accomplish in situ inclusion of single-stranded (ss) and double-stranded (ds) DNA (21, 23, and 58 nt) and effective intracellular delivery (including two noncancerous and six cancerous cell lines). Fluorescence quenching experiments for single and double end-labeled ss- and ds-DNA support that the DNA sequences can be completely enveloped by the SOFs. Confocal laser scanning microscopy and flow cytometry reveal that five of the SOFs exhibit excellent delivery efficiencies that, in most of the studied cases, outperform the commercial standard Lipo2000, even at low SOF–nucleic acid ratios. In addition to high delivery efficiencies, the water-soluble, self-assembled SOF carriers have a variety of advantages, including convenient preparation, high stability, and in situ DNA inclusion, which are all critical for practical applications in nucleic acid delivery.

Polar codes are proved to be able to theoretically achieve the Shannon limit. However, the performance of polar codes with short code length is not well in practice. One widely used method to improve the short length codes is concatenation. Recently, staircase coding structure provides an efficient concatenation scheme for finite length block codes, which the component block code can concatenate itself to improve the coding performance. Thus, in this paper, we propose a high-rate polar-staircase coding scheme with systematic polar codes as the component codes. The polar-staircase coding scheme can enhance the unreliable parts of the polar codes through the concatenation. To achieve the asymptotic performance, which is mainly depending on the decoding algorithms, three soft decoding algorithms are analyzed for our polar-staircase coding. We first investigate the conventional belief propagation (BP) decoding and soft cancellation (SCAN) decoding. The performance of the two algorithms is not well in the short length regime. Then, we adopt and optimize a soft successive cancellation list (SSCL) decoding algorithm for the polar-staircase codes with the tradeoff between reliability and complexity. Simulations show that the SSCL decoding outperforms than the other soft decoding algorithms over the AWGN channels.

SnO2 has attracted extensive attention in planar perovskite solar cells (PSCs) owing to its outstanding photoelectric properties and low temperature preparation. However, pinholes are easy to appear in the annealing process of SnO2 films, which limits its application in planar PSCs. Here lists a simple and low-cost method: Urea-complexed tin oxide in deionized water can effectively control the concentration of SnO2. This process is conducive to forming a compact surface morphology. Meanwhile, the work explored the effect of the properties of PSCs with different thicknesses of SnO2 layers. The system analysis showed that PSCs based on 60 nm SnO2 layer and the methamphetamine lead iodide (MAPbI3) light absorber yielded the highest power conversion efficiency (PCE) over 18%, a fill factor (FF) of 0.793, and good stability. Therefore, we believe our study provides an effective way for preparing electron transport layers.

The battery industry is constantly seeking to improve battery capacity, lifetime, and safety. Electrolytes are a key development focus in achieving these goals, as traditional carbonate-based electrolytes cause capacity fade and gassing through degradation processes, as well as representing a safety risk due to flammability. The release of gasses through electrolyte decomposition is a problem of prominent concern in the battery industry, due to the negative impact of gassing on cell safety and performance. Studies on battery gassing have been reported for a wide range of battery systems,1-3 but the mechanisms and conditions of gas release are complex and not fully understood. Gaining a greater understanding of gassing mechanisms, and the specific electrolyte components that cause them, will allow for precise design of battery electrolyte formulations that optimize performance and minimize gassing. In addition to understanding traditional electrolyte blends, the investigation of new electrolytes and additives is essential in developing low-gassing batteries. Organosilicon (OS) materials have been developed by Silatronix® as critical high stability additions to conventional carbonate electrolytes to enable next-generation Li-ion batteries. This novel organosilicon chemistry involves the merging of a silane with a Li+ coordinating functionality. For example, the OS3® solvent family contains a nitrile functionality. The adoption of new Li-ion battery electrolyte materials is driven by the desire to deploy higher energy density batteries capable of performing under broader operating conditions of temperature and voltage, and the design of OS solvents results in low molecular-weight molecules that have demonstrated superior thermal and electrochemical stability,4,5 as well as good safety properties with a high flash point and low vapor pressure. Silatronix® has conducted commercially relevant performance testing and fundamental mechanistic studies to investigate gassing phenomena in advanced Li-ion chemistries under both cycling and storage test conditions. In these studies, commercially relevant electrolytes were evaluated as well as electrolytes designed to specifically isolate the effect of selected electrolyte components, including OS3® and other industry-relevant solvents. The dependence of gassing on storage and voltage conditions was investigated, and connections between gas analysis and the electrode surface chemistry are also reported. Gas component analysis was performed with a calibrated dual-column GC-TCD, a similar analytical system to that utilized in previous studies,6 which provides excellent resolution and quantification of every gaseous product. Key experimental results show that all OS3® concentrations reduce gas generation after 60°C storage and higher OS3® content provides greater benefit. Overall, we show that organosilicon additives substantially reduce gassing from carbonate-based electrolytes while maintaining good cell performance. Zhang, S.S., Insight into the Gassing Problem of Li-ion Battery. Frontiers in Energy Research 2014, 2, 59. Self, J.; Aiken, C.P.; Petibon, R.; Dahn, J.R., Survey of Gas Expansion in Li-Ion NMC Pouch Cells. Journal of the Electrochemical Society 2015, 162, A796-A802. Jung, R.; Metzger, M.; Maglia, F.; Stinner, C., Chemical vs Electrochemical Electrolyte Oxidation on NMC111, NMC622, LNMO, and Conductive Carbon. The Journal of Physical Chemistry Letters 2017, 8, 4820-4825. Guillot, S.L.; Peña-Hueso, A.; Usrey, M.; Hamers, R.J., Thermal and Hydrolytic Decomposition Mechanisms of Organosilicon Electrolytes with Enhanced Thermal Stability for Lithium-Ion batteries. Journal of the Electrochemical Society 2018, 164, A1907-A1917. Chen, X.; Usrey, M.; Peña-Hueso, A.; West, R.; Hamers, R.J., Thermal and Electrochemical Stability of Organosilicon Electrolytes for Lithium-Ion Batteries. Journal of Power Sources 2013, 241, 311-319. Xiong, D.J.; Ellis, L.D.; Petibon, R.; Hynes, T.; Liu, Q.Q.; Dahn, J.R., Studies of Gas Generation, Gas Consumption and Impedance Growth in Li-Ion Cells with Carbonate or Fluorinated Electrolytes Using the Pouch Bag Method. Journal of the Electrochemical Society 2017, 164, A340-A347.

The extraction and solvent partition of the leaves of Eucalyptus citriodora, and repeated column chromatography for n-BuOH fraction yielded a new flavonoid glycoside, citrioside C (1), along with three known flavonoid glycosides (2–4). The latter were identified with kaempferol-3-O-β-d-glucopyranosyl (12)-α-l-rhamnoside (2), kaempferol-3-O-α-l-rhamnoside (3), and quercetin-3-O-α-l-rhamnoside (4). Their chemical structures were identified on the basis of spectroscopic data analyses including NMR, MS, UV, and IR. All constitutents were isolated for the first time from the leaves of Eucalyptus citriodora. The potential antivirus activity of all the isolated compounds was evaluated. Compound 4 showed potent antiviral activity against respiratory syncytial virus with 50% inhibition concentration (IC50) value of 1.9 μg/mL and selective index value of 9.8.