Corrosion resistance of Al–Cr-slag containing chromium–corundum refractories to slags with different basicity

Al–Cr slag is the solid waste generated by the smelting of Cr metal. It presents a range of environmental hazards. This study addressed the corrosion resistance of Al–Cr slag containing chromium–corundum refractories to slags with different basicity. Herein, we provide suggestions for the use of Cr–corundum of different basicity in kilns. Al–Cr slag, brown fused Al₂O₃, and chrome green were used as the raw materials, with pure calcium aluminate cement being used as a binder. The brick samples, prepared using different blends of chrome green and corundum, were fired at 1600?°C, and subsequently subjected to a slag corrosion test. After corrosion by slag of different basicity, the phase composition and microstructure of the sample were analyzed by X-ray diffraction, energy dispersive spectrometer and scanning electron microscopy. There were two major findings. First, Cr–corundum brick made from Al–Cr slag has a better slag corrosion resistance than that made from Cr₂O₃ and brown fused Al₂O₃. Second, Cr–corundum brick made from Al–Cr slag has superior corrosion resistance to slag with a CaO:SiO₂ ratio of 2:1.     

可控中子孔隙度测井仪器设计

源距与屏蔽体厚度是直接影响可控中子孔隙度测井仪器测量准确性的重要参数。源距不仅影响测井仪器的测量误差，还影响测井仪器对地层孔隙度的灵敏度。屏蔽体厚度是保障测井响应完全反映地层的重要参数。从灵敏度、屏蔽率以及误差3个方面确定可控中子孔隙度测井仪器的源距与屏蔽体厚度。研究结果表明:近探测器源距越小，测井仪器灵敏度越高；近远探测器的间距对测量误差的影响随间距的增大，先减小再增大；当屏蔽率在70%以上且屏蔽率随厚度的变化较为缓慢时的屏蔽体厚度可作为屏蔽体最低厚度。     

细菌纤维素合成与鉴定研究综述

细菌纤维素（BC）因其独特性能被广泛应用于医药、食品等领域，目前其高产量菌株筛选、合成成本降低及合成途径改良等成为研究热点。本文依据国内外文献并结合团队研究成果对BC合成与鉴定的相关研究进行综述。首先对BC合成菌筛选及碳源利用的研究进行了分析，总结了降低BC合成成本的研究思路。其次对鉴定菌株合成产物的方法进行了归纳，总结了不同方法的特点。然后结合本团队筛选出的BC生产菌XJL-06-4 BC合成酶基因分析结果，综述了BC合成途径、合成酶存在形式以及基因水平调控作用，为BC在分子水平上通过改变合成途径提高产量提供新思路。最后，总结BC微生物发酵生产存在的问题，多角度提出解决方案。     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

高能量离子束诊断质谱仪的研制及性能表征

本研究开发了一台应用于高能量离子束诊断的直线式飞行时间质谱仪，实现了其与高能真空弧放电离子源的联用。该仪器加速电压30 kV，飞行腔有效飞行距离1.5 m，通过短脉冲离子门精确截取，ICCD高速相机优化聚焦，仪器分辨率优于90 FWHM，对放电过程中产生的等离子体可实现不同时间的离子成分分析。将该方法用于真空弧放电离子源放电过程中离子成分的检测，放电2 μs时，电离成分以气态离子C⁺、O⁺、C²⁺、O²⁺为主；放电6 μs后，除气体成分外，还可以检测到Fe⁺、Cu⁺及其同位素金属离子峰。该仪器能够给出离子源放电产生离子的种类、价态以及相对含量等信息，可实现整个放电过程产生离子成分信息的准确诊断。     

Microplastics in soils: a review of possible sources,analytical methods and ecological impacts

Microplastics are emerging persistent pollutants that have been extensively detected in aqueous environments. Yet, scientists have little knowledge of microplastic pollution in soils. This study reviewed over 60 articles, with the following objectives: (i) to discuss sources and the global distribution of microplastics in soils; (ii) to evaluate current extraction techniques and analytical methods for microplastics in soils; and (iii) to comprehensively assess their adverse impacts on soils and soil organisms. Moreover, this review highlights the lack of research into microplastic contamination in soils as a significant knowledge gap. Research into the fate, sources and analytical techniques of soil microplastics and the interactions between soil organisms, soils and microplastics is essential in order to underpin management decisions aimed at safeguarding the ecological integrity of our soils. © 2020 Society of Chemical Industry     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

天然染料银杏叶染亚麻纱的染色性能研究

以天然染料银杏叶为原料,采用微波提取法进行染料原液的提取,并以提取后的原液作为染料原液对28 tex亚麻纱进行染色,采用p H、染色温度、媒染剂用量、渗透剂用量4个因素分析染色效果,以单因素分析结果作为基础,进行4因素3水平的正交试验,将正交试验后的染色纱样进行色牢度测定。研究结果表明,染色最佳工艺条件为:渗透剂用量1.5 m L,媒染剂用量5 m L,染色p H 7,染色温度80℃,亚麻纱染色后的色牢度达到3级以上。     

The impact of inoculum source,inoculum to substrate ratio and sample preservation on methane potential from different substrates

Batch experiments were conducted to evaluate the impact of inoculum sources, inoculum to substrate (IS) ratio and storage conditions on the potential and production rate of methane (CH₄) from different substrates: wheat straw, whole crop maize, cattle manure, grass and cellulose.The results of the test with four inocula and four substrates indicated that inoculum source could have a significant impact on both CH₄ potential (BMP) and the kinetics parameters of different substrates. The two inocula showing the highest BMP and production rates in each period were those coming from a feeding with more than 70% of animal manure under thermophilic conditions. The impact of the IS ratio in the range 0.25–2.5, in terms of g volatile solids (VS) substrate/g VS inoculum, depended on substrate type. Maize silage was more affected to changes in the IS ratio than wheat straw. The optimal IS ratio range for maize was 1.0–1.5, however, a wider IS range can be used in wheat straw (0.5–2.5). The impact of freezing and drying depended on biomass type. Freezing, drying and ensiling of grass increased the CH₄ yield compared to fresh grass. Drying of maize had no impact while freezing reduced the CH₄ potential. Drying and freezing had no impact on straw.