杂化包覆玄武岩鳞片/环氧涂料制备与性能

本文在环氧涂料中添加玄武岩鳞片，提高其防腐蚀性能。针对玄武岩鳞片的团聚问题，通过机械力化学改性工艺，采用正硅酸四乙酯、HY-311型钛酸酯偶联剂、E-44型环氧树脂对玄武岩鳞片进行杂化包覆，结果表明，杂化包覆后玄武岩鳞片的沉降时间从2h提高至96 h。杂化包覆玄武岩鳞片添加量为20%涂层的性能最优，附着力为13.40 MPa，耐盐雾时间为2000 h，在3.5%NaCl溶液中浸泡2000 h后，0.01 Hz的阻抗模值仍然有5.15×109 Ω·cm2。     

电石汽车卸料、破碎、除尘、输送一体化智能系统——中吴天玺系统

针对PVC企业电石车间存在的粉尘污染严重、人工操作安全隐患大等问题,江苏中吴环境工程设计研究有限公司开发了电石汽车卸料、破碎、除尘、输送一体化智能系统(即中吴天玺系统),对该系统的工艺流程、系统组成、占地空间、经济效益和社会效益簣方面进行了介绍。     

钢混结构大型厂房整体式爆破拆除

采用整体式控制爆破拆除方案对华电扬州电厂钢筋混凝土框-排架结构厂房进行了爆破拆除。爆破前,对汽机房、厂房外墙和楼梯进行了预处理。将厂房划分为3个爆区,采用非电多回路网格式爆破网路,依靠东侧锅炉房倒塌施加在西侧锅炉房上的倾覆力矩,有效地克服了西侧锅炉房向西倒的难题,可为同类工程提供一定的参考。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

“黄金分割法”在爆破工程中的应用探讨

"黄金分割法"是一种古老的数学方法,它无处不在并造就了事物的和谐美,多年来经常被应用到艺术、摄影、绘画、设计等多个领域,而且得到了意想不到的效果。根据多年的爆破工程实践,将"黄金分割法"与工程爆破实例相结合,应用到露天爆破、高耸建(构)筑物爆破拆除等工程中,取得了很好的爆破效果。     

Digestive protection of probiotic Lacticaseibacillus rhamnosus in Ricotta cheese by monoglyceride structured emulsions

This research aimed at studying the potential use of monoglyceride (MG) structured emulsions (MSEs) as delivery and protective systems for probiotic bacteria in Ricotta cheese. To this purpose, a low-fat commercial Ricotta cheese was added with MSEs formulated with milk, as water phase, and sunflower oil (MSE-SO) or anhydrous milk fat (MSE-AMF), as lipid phase. A commercial whole milk Ricotta cheese (W-RC) was considered as reference. A probiotic Lacticaseibacillus rhamnosus strain was inoculated as free cells in W-RC or embedded into the MSEs and added to the low-fat Ricotta at the same reference fat content. After physico-chemical characterisation, L. rhamnosus viability and sample destructuring behaviour upon in vitro digestion were evaluated. At the end of in vitro digestion, both W-RC and sample containing MSE-SO were unable to protect cells. By contrast, sample with AMF ensured a sufficient probiotic viability, even after 14 days of storage at 4 °C. This result was attributed to system composition and structure. During the gastric phase, the presence of caseins and MG-AMF mixed structures induced the formation of clots, entrapping and protecting cells against the acidic pH of the stomach, as confirmed by confocal micrographs and particle size. During the intestinal phase, cell viability was guaranteed by the formation of mixed micelles promoted by MG. It was demonstrated that microbial cells located near MG structures where they found protection.     

Impact of TiO2 nanoparticles and nanowires on corrosion protection performance of chemically bonded phosphate ceramic coatings

The impact of the addition of TiO₂ nanoparticles and nanowires on the morphology, phase characteristics, contact angle, and electrochemical performance of chemically bonded phosphate ceramic coatings (CBPCs) was investigated. The chemical composition and surface morphology of the TiO₂ nanoparticle and nanowire modified with and without (heptadecafluoro-1,1,2,2-tetradecyl) trimethoxysilane were characterized. Results indicated that the hydrophobic –CF₂– and –CF₃ groups were successfully introduced into the TiO₂ nanoparticles and nanowires after modification. Corrosion resistance of CBPCs with TiO₂ was evidently improved compared with that without TiO₂. Such improvement was mainly due to the combined effects of low surface energy materials and micro/nano structures. In addition, CBPCs with TiO₂ nanowires exhibited higher hydrophobicity and corrosion resistance than those with TiO₂ nanoparticles because of the special columnar structure of the nanowires.     

基于TRNSYS的茯砖茶生产工艺能源系统节能环保特性研究

茯砖茶发酵、干燥过程中，烘房内温湿度稳定性和能源系统低能耗是保证茯砖茶品质与成本的重要因素。本文采用TRNSYS仿真与实验研究相结合的方法，对咸阳某茯砖茶厂实际使用的空气源热泵系统进行建模，通过研究各季节典型代表月烘房温湿度的波动情况，确定该空气源热泵系统在全年的运行状态是否满足工艺要求，在此基础上，对比了该系统在全年可运行季节代表月与该生产厂房早期使用的燃气锅炉系统的能耗仿真结果，对空气源热泵系统的节能与环保特性进行研究。结果表明：由于夏季送风质量流量过大且室外空气含湿量较高，7月烘房温湿度不满足工艺要求。热泵系统在1、4、10月的总标煤消耗量的平均值是锅炉系统的44.42%，平均CO2、SO2、NOx排放量分别为锅炉系统的34.13%、44.1%、40.60%。在茯砖茶发酵、干燥的过程中，相比于燃气锅炉系统，空气源热泵系统具有更好的节能与环保特性。     

广义正交码索引调制系统的性能分析

摘 要：为了提高码索引调制（code index modulation，CIM）系统的传输效率，提出了一种具有更低复杂度的单输入单输出（single input single output，SISO）的广义正交码索引调制（generalized orthogonal code index modulation，GQCIM）系统。CIM 系统使用扩频码和星座符号传输信息，但只能激活两个扩频码索引和一个调制符号。而 GQCIM 系统以一种新颖的方式克服了只激活一个调制符号的限制，同时充分利用了调制符号的正交性，增加扩频码索引以传输更多的额外信息位，提高了系统的传输效率。此外，分析了GQCIM系统的理论性能，推导了误码率性能的上界。通过蒙特卡罗仿真验证了GQCIM系统的性能，对比发现GQCIM系统的理论和仿真性能一致。而且在相同的传输效率下，结果显示GQCIM系统的性能优于同样具有正交性的调制系统，如广义码索引调制（generalized code index modulation，GCIM）系统、CIM系统、码索引调制-正交空间调制（code index modulation aided quadrature spatial modulation，CIM-QSM）系统、码索引调制-正交空间调制（code index modulation aided spatial modulation，CIM-SM）系统、脉冲索引调制（pulse index modulation，PIM）系统。