Mixing characteristics for the single and air-water two-phase flows in miniaturized parallel multichannel-based devices

Investigation on the miniaturized parallel multichannel-based devices packed with glass beads to improve the mass exchange execution is the critical focal point of the current study. One of the essential parameters to specify the miniaturized devices' flow distribution is the residence time distribution (RTD). In the present context, the RTDs of a liquid tracer were investigated for the air-water multiphase flows (concurrent) across the multichannel-based miniaturized devices (comprising of 11 similar dimensional parallel channels). The devices were variable in height and packed with glass beads. The conductivity estimations generated the RTD curves and were addressed by the axial dispersion model (ADM). The fluid-flow rates differed within the range of 5–23 ml min⁻¹. The axial dispersion coefficients and the rate of the specific energy dispersion were investigated. The effects of pressure difference and geometry on the hydrodynamic attributes and mixing properties were well-illustrated, and the new correlations were suggested.     

智能化电子信息技术发展及应用分析

文章首先对智能化电子信息技术进行了深入的研究,而后分析了该技术在应用过程中出现的问题,最后结合该技术的相关特点给出了相应的问题解决措施,希望能够对智能化电子信息技术的发展提供帮助。     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.     

中国智能机械制造评价及发展研究

以中国规模以上工业企业数据库为基础，结合在智能制造主要区域调研的结果，筛选出15145家智能制造企业，经同行评议后，生成322家候选企业名单；再由资深产业专家从“开发式创新”和“探索式创新”两个方面去考察候选企业的能力，得到中国智能制造百强排行榜；随后根据行业分类，得到智能机械制造企业排行榜。在概述了智能机械制造上榜企业的基本情况后，着重分析了前20强企业，并提出了中国智能机械制造发展路径和未来的发展趋势。     

单片机应用系统综合实验装置的设计

单片机原理与应用作为电子技术类学科中的必修课程具有很强实践性,要求学生掌握实际应用能力,为此研制了基于单片机系统通信为基础的实验板,依据单片机应用系统特点,可完成SPI、I^2C、UART串行通信以及并行总线方式通信。实验板有利于学生更好地了解和掌握单片机应用系统设计的方法,有利于学生进行自主设计和内容拓展。做到培养学生的学习能力、提高学生的学习兴趣、发挥学生的创造性。     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

“聚龙一号”装置四层圆盘锥磁绝缘传输线的三维粒子模拟研究

介绍了"聚龙一号"中四层圆盘锥磁绝缘传输线(MITL)的基本理论。在CPIPIC平台上,采用非均匀网格和周期性对称边界条件,建立了"聚龙一号"的四层圆盘锥MITL的三维粒子模拟模型。设置相应的参数并用并行算法模拟得到了该器件中各层在绝缘堆上和MITL中间位置的电流和汇流后的电流,并与理论和实验数据进行相互对比验证。模拟结果表明整个器件在达到磁绝缘状态后具有很高的传输效率,并与实验结果相互验证,为以后进一步的研究提供了保证。     

Kariya (Hildegardia barteri) seed oil extraction: comparative evaluation of solvents,modeling, and optimization techniques

In this work, the effects of solid/solvent ratio (0.10–0.25?g/ml), extraction time (3–8?h), and solvent type (n-hexane, ethyl acetate, and acetone) together with their shared interactions on Kariya seed oil (KSO) yield were investigated. The oil extraction process was modeled via response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) while the optimization of the three input variables essential to the oil extraction process was carried out by genetic algorithm (GA) and RSM methods. The low mean relative percent deviation (MRPD) of 0.94–4.69% and high coefficient of determination (R²) > 0.98 for the models developed demonstrate that they describe the solvent extraction process with high accuracy in this order: ANFIS, ANN, and RSM. The best operating condition (solid/solvent ratio of 0.1?g/ml, extraction time of 8?h, and acetone as solvent of extraction) that gave the highest KSO yield (32.52?wt.%) was obtained using GA-ANFIS and GA-ANN. Solvent extraction efficiency evaluation showed that ethyl acetate, n-hexane, and acetone gave maximum experimental oil yields of 19.20?±?0.28, 25.11?±?0.01, and 32.33?±?0.04?wt.%, respectively. Properties of the KSO varied based on the type of solvent used. The results of this work showed that KSO could function as raw material in both food and chemical industries.