Ultrafast, broadband light polarization properties of vanadium dioxide thin films on insulating and metallic substrates

The refractive indices of vanadium dioxide (VO2) abruptly change when its phase transition temperature of 68oC is reached, the point at which it goes from an insulating state to a metallic state. Modifications of complex-valued refractive indices in VO2 have been shown to produce optical phase shifts that are unequal for the s- and p-components of polarization, thereby causing a relative phase shift Δ between the two. Under certain conditions of Δ, a linearly polarized light can rotate its polarization 90 degrees or transforms between linear and circular. In this thesis, we will demonstrate all possibilities of using a VO2 thin film to change the polarized light states of reflected or transmitted light on the nanosecond and potentially shorter timescales. Possible applications for high-contrast optical modulation over a wide spectral range are discussed

Polarization modulation by vanadium dioxide on metallic substrates

Vanadium dioxide (VO2) undergoing phase transition is known alters the polarization state of light in reflection owing to large changes in complex refractive indices. While this effect is promising for optical modulation applications, the usual VO2 films on dielectric substrates tend to offer limited tunability for polarization modulation. In this paper, we show that metallic under-layers greatly enhance the performance by widening the spectral range and include visible wavelengths, by increasing the polarization modulation amplitude, and by widening the range of workable incidence angles. The imaginary part of the refractive index in the metallic layer is found to increase the relative phase shifts between s- and p-components of polarization as well as increasing the reflectance

Uncertainty Quantification in the Directed Energy Deposition Process Using Deep Learning-Based Probabilistic Approach

peer reviewedThis study quantifies the effects of uncertainty raised from process parameters, material properties, and boundary conditions in the directed energy deposition (DED) process of M4 High-Speed Steel using deep learning (DL)-based probabilistic approach. A DL-based surrogate model is first constructed using the data obtained from a finite element (FE) model, which was validated against experiment. Then, sources of uncertainty are characterized by the probabilistic method and are propagated by the Monte-Carlo (MC) method. Lastly, the sensitivity analysis (SA) using the variance-based method is performed to identify the parameters inducing the most uncertainty to the melting pool depth. Using the DL-based surrogate model instead of solely FE model significantly reduces the computational time in the MC simulation. The results indicate that all sources of uncertainty contribute to a substantial variation on the final printed product quality. Moreover, we find that the laser power, the convection, the scanning speed, and the thermal conductivity contribute the most uncertainties on the melting pool depth based on the SA results. These findings can be used as insights for the process parameter optimization of the DED process.EDPOM

In vitro antioxidant activity and bioactive compounds from Calocybe indica

Nowadays, the use of mushrooms in medicine is ubiquitous and has achieved particular success. The antioxidants in mushrooms can deactivate free radicals. This study assesses the antioxidant potential of mushroom Calocybe indica with the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) radical scavenging methods and the total antioxidant capacity. The mushroom’s ethanol extract exhibits acceptable activity with a low IC50 value (240.11 μg/mL), approximately 2.9 times lower than that of the mushroom Ophiocordyceps sobolifera extract. The ABTS scavenging rate of the extract is around 60% at 500 µg/mL, and the total antioxidant capacity is equivalent to 64.94 ± 1.03 mg of GA/g or 77.42 ± 0.42 μmol of AS/g.  The total phenolics, flavonoids, polysaccharides, and triterpenoids are equivalent to 29.33 ± 0.16 mg of GAE/g, 17.84 ± 0.11 mg of QUE/g (5.04 ± 0.04%), and 4.96 ± 0.04 mg of oleanolic acid/g, respectively. Specifically, the total triterpenoid content has been reported for the first time. The mushroom can have potential biomedical applications

Fast and accurate prediction of temperature evolutions in additive manufacturing process using deep learning

Typical computer-based parameter optimization and uncertainty quantification of the additive manufacturing process usually requires significant computational cost for performing high-fidelity heat transfer finite element (FE) models with different process settings. This work develops a simple surrogate model using a feedforward neural network (FFNN) for a fast and accurate prediction of the temperature evolutions and the melting pool sizes in a metal bulk sample (3D horizontal layers) manufactured by the DED process. Our surrogate model is trained using high-fidelity data obtained from the FE model, which was validated by experiments. The temperature evolutions and the melting pool sizes predicted by the FFNN model exhibit accuracy of 99% and 98%, respectively, compared with the FE model for unseen process settings in the studied range. Moreover, to evaluate the importance of the input features and explain the achieved accuracy of the FFNN model, a sensitivity analysis (SA) is carried out using the SHapley Additive exPlanation (SHAP) method. The SA shows that the most critical enriched features impacting the predictive capability of the FFNN model are the vertical distance from the laser head position to the material point and the laser head position.VINIF.2020.DA15 EDPOMP projec

TỔNG HỢP VÀ ĐẶC TRƯNG hydrogel glucomannan – poly(acrylic acid) NHẠY pH ĐỊNH HƯỚNG ỨNG DỤNG TRONG HỆ THỐNG PHÂN PHỐI 5-aminosalicylic acid CÓ KIỂM SOÁT

In this study, glucomannan-poly(acrylic acid) hydrogels were synthesized under different conditions. The hydrogels consist of glucomannan and acrylic acid and are crosslinked by N,N-methylene-bis-(acrylamide). The structure and morphology of the hydrogels were investigated by using Fourier-transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM). The swelling ratio, biodegradation and pH-sensitive properties, relationship between hydrogel swelling rate and 5-ASA adsorption-desorption capacity, influence of medium pH on 5-ASA desorption, and 5-ASA adsorption kinetics were studied. The swelling ratio of the synthesized hydrogel samples is 16.70–56.21 times. This ratio is low in the pH 1.0 media and increases significantly in the pH 7,4 media. The hydrogels are biodegradable in the presence of cellulase (400 U·mg–1) in a pH 7.4 phosphate buffer at 37 °C (69.8% after ten days; the cellulase concentration 1.5 g·L­–1). The hydrogels exhibit high adsorption and desorption capacities for 5-ASA. The adsorption kinetics follows the pseudo-first-order model. These hydrogels can be applied to smart drug delivery systems.Trong nghiên cứu này, hydrogel glucomannan-poly(acrylic acid) đã được tổng hợp ở các điều kiện khác nhau với mục đích ứng dụng vào hệ thống phân phối thuốc 5-amiosalicylic acid (5-ASA) có kiểm soát. Hydrogel được tạo thành từ glucomannan và acrylic acid với tác nhân liên kết N,N-methylene-bis-(acrylamide). Cấu trúc và hình thái của hydrogel được nghiên cứu bằng phổ hồng ngoại chuyển dịch Fourier (FT-IR) và kính hiển vi điện tử quét (SEM). Tỷ lệ trương nở, tính chất phân huỷ sinh học và nhạy pH, mối quan hệ giữa tỷ lệ trương nở của hydrogel và khả năng hấp phụ-giải hấp 5-ASA, ảnh hưởng của pH môi trường để khả năng giải hấp 5-ASA và động học hấp phụ 5-ASA đã được nghiên cứu. Kết quả cho thấy tỷ lệ trương nở của các mẫu hydrogel là 16,70–56,21 lần. Tỷ lệ trương nở của hydrogel thấp ở môi trường pH 1 và tăng lên đáng kể trong môi trường pH 7,4.  Cellulase (400 U·mg–1) trong môi trường đệm pH 7,4 ở 37 °C có khả năng phân hủy sinh học hydrogel (69,8% sau 10 ngày; nồng độ cellulase 1,5 g·L–1). Hydrogel có cả khả năng hấp phụ và giải hấp tốt 5-ASA. Động học quá trình hấp phụ tuân theo mô hình biểu kiến bậc 1. Đây là vật liệu có tiềm năng ứng dụng trong phát triển hệ thống phân phối thuốc thông minh

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling

IntroductionNeoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow.MethodsIn this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP).ResultsWe detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data.DiscussionThis integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients

Лексические средства связности в речи телеведущего в жанре интерактивной белорусскоязычной телебеседы

Материалы XII Междунар. науч. конф. студентов, магистрантов, аспирантов и молодых ученых, Гомель, 16–17 мая 2019 г