钠碱法硫酸尾气处理装置改造的生产实践

介绍了新疆某公司钠碱法硫酸尾气处理装置的原理、运行状况及改造实践。针对排放尾气中颗粒物及硫酸雾2项指标达不到新疆地区工业污染物排放限值要求的问题,采取在脱硫塔后部增加1台湿式电除尘器的方法对该脱硫系统进行改造,改造后硫酸雾质量浓度在3 mg/m^3以下,颗粒物质量浓度在1 mg/m3以下,远低于排放限值的要求,达到了预期目标。     

Electric characteristic and cavitation bubble dynamics using underwater pulsed discharge

Underwater pulsed discharge is widely applied in medicine, machining, and material modification. The induced cavitation bubble and subsequent cavitation collapse are considered the major motivations behind these applications. This paper presents an underwater pulsed discharge system. The experimental setup is established to induce and investigate the cavitation bubble assisted with a high-speed camera. Three aspects, including the characteristic of the discharge with different applied voltages and conductivities, the evolution of the cavitation bubble profile, and the energy efficiency of cavitation bubble inducing, are investigated, respectively. Especially, the mechanism of pre-discharge time delay in the low field intensity case is explained using the Joule heat effect. The results show the validity of the underwater pulsed discharger and experimental setup. The present underwater pulsed discharger is proved to be a simple, portable, and easy-to-implement device for the investigation of cavitation bubble dynamics.     

Detection of K in soil using time-resolved laser-induced breakdown spectroscopy based on convolutional neural networks

One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy (LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem, this paper investigated a combination of time-resolved LIBS and convolutional neural networks (CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R²_c=0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network (ANN), showing R²_v=0.6318 and the root mean square error of validation (RMSEV)=0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R²_v=0.7366 and RMSEV=0.7855. These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K. However, due to limited calibration samples, the two-dimensional models presented over-fitting. The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R²_v=0.9968 and RMSEV=0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.     

Making friends in online games: gender differences and designing for greater social connectedness

ABSTRACT

While online multiplayer games provide an opportunity for players to both maintain and establish new connections, male and female players have been found to experience these environments differently. Interviews (n?=?22) and focus groups (n?=?14) were used to explore these differences as they impact on creating new social connections, as well as to provide recommendations for the development of new social tools and features that account for these differences. While all participants experienced toxicity and performance pressure as barriers to forming new connections, female players uniquely reported the impacts of misogynistic targeting and stereotype threat. In turn, female players wishing to avoid these stresses would often mask their gender. The common practice of gender misrepresentation by both male and female players impacted female players’ ability to create social connections through voice technology, as well as building their distrust of unknown others. Recommendations are made to build social connectedness between players taking into account the specific constraints faced by female players. These include establishing mentoring opportunities as well as profiling players beyond their immediate skill or rank. Additionally, the desire for control of one’s online identity presents practical challenges that may be overcome through thoughtful design.     

某型发动机自反馈调节阀动态仿真分析

基于FLUENT软件提供的计算方法和物理模型，利用动网格技术及用户自定义函数（User-define Function，UDF），对发动机预燃室调节阀的自反馈调节过程进行动态数值模拟，并分析阻尼参数对调节效果的影响。结果表明：自反馈机构可实现对不同压力扰动的及时响应，具有稳定流量的效果，改变阻尼参数可对调节响应速度和流量稳定性进行优化，其中摩擦力对调节影响最显著。     

Crude Oil Production

Current data on crude oil, field/lease condensate, and natural gas liquids produced from NGL plants. Updated on a monthly basis.     

Diffusion of ions in an electrostatic stochastic field and a space-dependent unperturbed magnetic field

We calculate the diffusion coefficients for ions moving in a prescribed electromagnetic field. Thefield is considered to be a superposition of an electrostatic stochastic field and a space-dependent and sheared magnetic field. We have considered as parameters involved in the calculation of the diffusion coefficients the shear ion Kubo number K_s~(ion), the electrostatic Kubo number K, the parallel shear ion Kubo number K_(zs)~(ion), and the parallel thermal ion Kubo number K_z~(ion).A geometrical parameter which is the measure of the product of the stochastic perpendicular correlation length and the gradient in the magnetic field strength(see definitions in the text) is found not to be important in our calculation. The results concerning the diffusion coefficients obtained in our model are in agreement with experimental data and with those corresponding to other models, and the neoclassical and anomalous values for the diffusion coefficients are obtained.     

Hybrid fully convolutional networks-based skin lesion segmentation and melanoma detection using deep feature

Fully convolutional networks (FCNs) take the input of arbitrary size and produce correspondingly sized output with efficient inference and learning. The automatic diagnosis of melanoma is very essential for reducing the mortality rate by identifying the disease in earlier stages. A two-stage framework is used for implementing the melanoma detection, segmentation of skin lesion, and identification of melanoma lesions. Two FCNs based on VGG-16 and GoogLeNet are incorporated for improving the segmentation accuracy. A hybrid framework is used for incorporating these two FCNs. The classification is done by extracting the feature from segmented lesion by using deep residual network and a hand-crafted feature. Classification is done by support vector machine. The performance analysis of our framework gives a promising accuracy, that is, 0.8892 for classification in ISBI 2016 dataset and 0.853 for ISIC 2017 dataset.     

无人机影像目标检测技术研究进展

无人机影像目标检测技术是无人机影像智能化分析中的关键技术，开展无人机影像目标检测技术的研究有着广阔的应用前景和价值。介绍了无人机影像中目标检测技术的发展历程，简述了无人机影像目标检测技术在森林防火、农业信息采集、电力线路检测、路桥损害检测以及军事侦察等5种特定领域的应用情况，总结归纳了目标检测性能评价时常用的数据集和标准，并对未来无人机影像目标检测技术的发展态势进行了展望。