Topological structures of energy flow: Poynting vector skyrmions

Topological properties of energy flow of light are fundamentally interesting and have rich practical applications in optical manipulations. Here, skyrmion-like structures formed by Poynting vectors are unveiled in the focal region of a pair of counter-propagating cylindrical vector vortex beams in free space. A N\'eel-Bloch-N\'eel skyrmion type transformation of Poynting vectors is observed along the light propagating direction within a volume with subwavelength feature sizes. The corresponding skyrmion type can be determined by the phase singularities of the individual components of the coherently superposed electromagnetic field in the focal region. This work reveals a new family member of optical skyrmions and may introduce novel physical phenomena associated with light scattering and optical force

A review of high-solid anaerobic digestion (HSAD):From transport phenomena to process design

High-solid anaerobic digestion (HSAD) is an attractive organic waste disposal method for bioenergy recovery and climate change mitigation. The development of HSAD is facing several challenges such as low biogas and methane yields, low reaction rates, and ease of process inhibition due to low mass diffusion and mixing limitations of the process. Therefore, the recent progress in HSAD is critically reviewed with a focus on transport phenomena and process modelling. Specifically, the work discusses hydrodynamic phenomena, biokinetic mechanisms, HSAD-specific reactor simulations, state-of-the-art multi-stage reactor designs, industrial ramifications, and key parameters that enable sustained operation of HSAD processes. Further research on novel materials such as bio-additives, adsorbents, and surfactants can augment HSAD process efficiency, while ensuring the stability. Additionally, a generic simulation tool is of urgent need to enable a better coupling between biokinetic phenomena, hydrodynamics, and heat and mass transfer that would warrant HSAD process scale-up

Direct observation of topological surface states in the layered kagome lattice with broken time-reversal symmetry

Magnetic topological quantum materials display a diverse range of fascinating physical properties which arise from their intrinsic magnetism and the breaking of time-reversal symmetry. However, so far, few examples of intrinsic magnetic topological materials have been confirmed experimentally, which significantly hinder our comprehensive understanding of the abundant physical properties in this system. The kagome lattices, which host diversity of electronic structure signatures such as Dirac nodes, flat bands, and saddle points, provide an alternative and promising platform for in-depth investigations into correlations and band topology. In this article, drawing inspiration from the stacking configuration of MnBi$_2$Te$_4$, we conceive and then synthesize a high-quality single crystal EuTi$_3$Bi$_4$, which is a unique natural heterostructure consisting of both topological kagome layers and magnetic interlayers. We investigate the electronic structure of EuTi$_3$Bi$_4$ and uncover distinct features of anisotropic multiple Van Hove singularitie (VHS) that might prevent Fermi surface nesting, leading to the absence of a charge density wave (CDW). In addition, we identify the topological nontrivial surface states that serve as connections between different saddle bands in the vicinity of the Fermi level. Combined with calculations, we establish that, the effective time-reversal symmetry S=$\theta$$\tau_{1/2}$ play a crucial role in the antiferromagnetic ground state of EuTi$_3$Bi$_4$, which ensures the stability of the topological surface states and gives rise to their intriguing topological nature. Therefore, EuTi$_3$Bi$_4$ offers the rare opportunity to investigate correlated topological states in magnetic kagome materials.Comment: 9 pages, 4 figure

Production and characterization of a recombinant single-chain antibody against Hantaan virus envelop glycoprotein

Hantaan virus (HTNV) is the type of Hantavirus causing hemorrhagic fever with renal syndrome, for which no specific therapeutics are available so far. Cell type-specific internalizing antibodies can be used to deliver therapeutics intracellularly to target cell and thus, have potential application in anti-HTNV infection. To achieve intracellular delivery of therapeutics, it is necessary to obtain antibodies that demonstrate sufficient cell type-specific binding, internalizing, and desired cellular trafficking. Here, we describe the prokaryotic expression, affinity purification, and functional testing of a single-chain Fv antibody fragment (scFv) against HTNV envelop glycoprotein (GP), an HTNV-specific antigen normally located on the membranes of HTNV-infected cells. This HTNV GP-targeting antibody, scFv3G1, was produced in the cytoplasm of Escherichia coli cells as a soluble protein and was purified by immobilized metal affinity chromatography. The purified scFv possessed a high specific antigen-binding activity to HTNV GP and HTNV-infected Vero E6 cells and could be internalized into HTNV-infected cells probably through the clathrin-dependent endocytosis pathways similar to that observed with transferrin. Our results showed that the E. coli-produced scFv had potential applications in targeted and intracellular delivery of therapeutics against HTNV infections

Appliance of preoperative diffusion tensor imaging and fiber tractography in patients with brainstem lesions

Background: Surgical resection of brainstem lesions has a high risk of morbidity, because vital fasciculi in the brainstem can be damaged along the entry routes. Diffusion tensor imaging (DTI) is an in vivo method for mapping white matter fiber tracts in the brain. Objective: To summarize the experience of surgical treatment of brainstem lesions with the assistance of DTI and fiber tractography. Materials and Methods: A retrospective analysis clinical data of nine patients with brainstem lesions were investigated between July 2007 and September 2009. The analysis included age distribution, clinical presentation, pre- and postoperative modified Rankin score (mRS), and surgical approach. DTI and fiber tractography were used to reconstruct the corticospinal tracts and the medial lemnisci. Results: DTI and fiber tractography showed that most of the corticospinal tracts were compressed anteriorly or anterolaterally, except for one case (posteriorly). All the medial lemnisci were displaced posteriorly or posterolaterally. Individualized surgical approaches were designed according to the information provided by DTI and fiber tractography. Total resection was achieved in two patients with brainstem cavernomas and two patients with pilocytic astrocytoma. Partial resection was performed in the other patients. The neurological functional status was better than preoperative period in eight patients, one patient with medulla oblongata astrocytoma deteriorated. The preoperative average mRS score was 2.22 points. At the time of the last follow-up, the average postoperative score had improved by 0.56 to 1.66 points. Conclusions: DTI and fiber tractography can provide valuable information regarding the relationship between the principal fiber tracts and brainstem lesions, which is useful in neurosurgical planning

Monte Carlo simulation of propylene polymerization (I) effects of impurity on propylene polymerization

A comprehensive mechanism for propylene polymerization was proposed by considering the effects of main impurities in the material on propylene polymerization. According to the proposed mechanism, Monte Carlo simulation was employed to investigate the polymerization kinetics in order to determine the effects of the main impurities on the polymerization. Significant influences of the main impurities on the rate, number-average degree and controlling capability of hydrogen of the polymerization were analyzed

Modeling and Prediction of Coal Ash Fusion Temperature based on BP Neural Network

Coal ash is the residual generated from combustion of coal. The ash fusion temperature (AFT) of coal gives detail information on the suitability of a coal source for gasification procedures, and specifically to which extent ash agglomeration or clinkering is likely to occur within the gasifier. To investigate the contribution of oxides in coal ash to AFT, data of coal ash chemical compositions and Softening Temperature (ST) in different regions of China were collected in this work and a BP neural network model was established by XD-APC PLATFORM. In the BP model, the inputs were the ash compositions and the output was the ST. In addition, the ash fusion temperature prediction model was obtained by industrial data and the model was generalized by different industrial data. Compared to empirical formulas, the BP neural network obtained better results. By different tests, the best result and the best configurations for the model were obtained: hidden layer nodes of the BP network was setted as three, the component contents (SiO2, Al2O3, Fe2O3, CaO, MgO) were used as inputs and ST was used as output of the model

Modeling and Prediction of Coal Ash Fusion Temperature based on BP Neural Network

Coal ash is the residual generated from combustion of coal. The ash fusion temperature (AFT) of coal gives detail information on the suitability of a coal source for gasification procedures, and specifically to which extent ash agglomeration or clinkering is likely to occur within the gasifier. To investigate the contribution of oxides in coal ash to AFT, data of coal ash chemical compositions and Softening Temperature (ST) in different regions of China were collected in this work and a BP neural network model was established by XD-APC PLATFORM. In the BP model, the inputs were the ash compositions and the output was the ST. In addition, the ash fusion temperature prediction model was obtained by industrial data and the model was generalized by different industrial data. Compared to empirical formulas, the BP neural network obtained better results. By different tests, the best result and the best configurations for the model were obtained: hidden layer nodes of the BP network was setted as three, the component contents (SiO2, Al2O3, Fe2O3, CaO, MgO) were used as inputs and ST was used as output of the model

Co-gasification of digestate and lignite in a downdraft fixed bed gasifier: effect of temperature

To improve energy efficiency and biomass utilization in the process of anaerobic digestion, co-gasification is considered as an effective method to post-treat anaerobic digestion residues. In this work, the effect of temperature (650 °C, 750 °C, 850 °C and 950 °C) on the co-gasification of digestate and lignite was thoroughly investigated in a downdraft fixed bed gasifier. The results showed that the increase of gasification temperature increased the gas yield and the lower heating value (LHV) of product gas. Physicochemical properties of biochar were characterized by physical adsorption analyzer, Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy and thermogravimetric analyzer (TG). It was shown that the average pore diameter increased in the range of 650 °C to 950 °C, while specific surface area and pore volume first increased from 650 °C to 850 °C and then decreased at 950 °C. The Raman analysis of biochar indicated that small aromatic rings condensed to large aromatic ring and increased the content of Caromatic-Calkyl and the crosslinking density at higher temperature. The variation of biochar properties at the higher temperature caused a decrease in the gasification reactivity. With the increase of temperature, the content of carbolic oil in the tar increased, but the contents of light oil, naphthalene oil and washing oil decreased. This study comprehensively analyzed the products properties and demonstrated the feasibility of co-gasification of digestate and lignite

Inter-frame Accelerate Attack against Video Interpolation Models

Deep learning based video frame interpolation (VIF) method, aiming to synthesis the intermediate frames to enhance video quality, have been highly developed in the past few years. This paper investigates the adversarial robustness of VIF models. We apply adversarial attacks to VIF models and find that the VIF models are very vulnerable to adversarial examples. To improve attack efficiency, we suggest to make full use of the property of video frame interpolation task. The intuition is that the gap between adjacent frames would be small, leading to the corresponding adversarial perturbations being similar as well. Then we propose a novel attack method named Inter-frame Accelerate Attack (IAA) that initializes the perturbation as the perturbation for the previous adjacent frame and reduces the number of attack iterations. It is shown that our method can improve attack efficiency greatly while achieving comparable attack performance with traditional methods. Besides, we also extend our method to video recognition models which are higher level vision tasks and achieves great attack efficiency