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.     

地域文化元素融入都江堰旅游产品的设计策略

目的 针对目前市面上都江堰旅游产品识别性较弱、同质化严重，对具有地域文化特色的旅游产品开发较少的问题，以地域文化元素作为都江堰旅游产品设计的核心，提出旅游产品的设计策略。方法 研究都江堰旅游产品设计，应从地域化和文化内涵入手。通过分析旅游产品现状，地域文化元素及新旅游时代背景下旅游产品的发展趋势，结合情感化设计理念，围绕用户体验进行探究，总结出都江堰旅游产品设计开发模式。以李冰石像和鱼嘴段水利工程元素为例，进行产品实践。结论 提出符合都江堰区域特色的旅游产品设计策略，即树立品牌意识、打造IP形象，以地域文化元素为设计核心，加强情感互动、与科技相融合的设计策略。赋予旅游产品更深层次的内涵，打造更多具有地域文化特色的旅游产品，从而推动历史文化与商业价值的融合，也能够为同类型旅游产品提供具有应用价值和参考的设计策略和思路。     

ZnO·2.7Al2O3 nanocomposite with high optical transparency

Here we report a transparent dual-phase ZnO·2.7Al₂O₃ ceramic. The composite is pore-free and consists of thin nanosheets with a spinel phase and a hexagonal phase, while the two phases match closely in both lattice and refractive index. Such features result in excellent optical transmittance (maximum value >80% in the visible spectrum) at comparable phase volume. This work may provide a new thought for the rational structural design of optical nanocomposites.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

Experimental study on mitigating wind erosion of calcareous desert sand using spray method for microbially induced calcium carbonate precipitation

Wind erosion is one of the significant natural calamities worldwide, which degrades around one-third of global land. The eroded and suspended soil particles in the environment may cause health hazards, i.e. allergies and respiratory diseases, due to the presence of harmful contaminants, bacteria, and pollens. The present study evaluates the feasibility of microbially induced calcium carbonate precipitation (MICP) technique to mitigate wind-induced erosion of calcareous desert sand (Thar desert of Rajasthan province in India). The temperature during biotreatment was kept at 36 °C to stimulate the average temperature of the Thar desert. The spray method was used for bioaugmentation of Sporosarcina (S.) pasteurii and further treatment using chemical solutions. The chemical solution of 0.25 pore volume was sprayed continuously up to 5 d, 10 d, 15 d, and 20 d, using two different concentration ratios of urea and calcium chloride dihydrate viz 2:1 and 1:1. The biotreated samples were subjected to erosion testing (in the wind tunnel) at different wind speeds of 10 m/s, 20 m/s, and 30 m/s. The unconfined compressive strength of the biocemented crust was measured using a pocket penetrometer. The variation in calcite precipitation and microstructure (including the presence of crystalline minerals) of untreated as well as biotreated sand samples were determined through calcimeter, scanning electron microscope (SEM), and energy-dispersive X-ray spectroscope (EDX). The results demonstrated that the erosion of untreated sand increases with an increase in wind speeds. When compared to untreated sand, a lower erosion was observed in all biocemented sand samples, irrespective of treatment condition and wind speed. It was observed that the sample treated with 1:1 cementation solution for up to 5 d, was found to effectively resist erosion at a wind speed of 10 m/s. Moreover, a significant erosion resistance was ascertained in 15 d and 20 d treated samples at higher wind speeds. The calcite content percentage, thickness of crust, bulk density, and surface strength of biocemented sand were enhanced with the increase in treatment duration. The 1:1 concentration ratio of cementation solution was found effective in improving crust thickness and surface strength as compared to 2:1 concentration ratio of cementation solution. The calcite crystals formation was observed in SEM analysis and calcium peaks were observed in EDX analysis for biotreated sand.     

Model of reactive precipitation process of preparation nano-ZnO in rotating packed bed: Contribution ratio

With excellent micromixing characteristic of rotating packed bed (RPB), many nanoparticles with small average size, narrower distribution and good morphology had been successfully and continuously prepared. To reveal complex crystal process, an empirical model were developed to simulate nano-ZnO by considering mass changed, population balance equation, growth rate G, nucleation rate B, drop sizes D_i, and resident time t. The predicted particle sizes were shown good agreement with experimental data with error of ±10%. Therefore, it was further adopted to predict the effects of rotating speed, liquid flow rate and reactant concentration on the mean particle size. To look more deeply insight in this process, their contribution ratios were further analyzed. The proposed empirical models were of great helpful to obtain suitable operation conditions for preparing much better properties of nanoparticles with fewer experiments. It was also beneficial to produce other nanoparticles in RPB.     

基于三种干旱指标的朝阳市干旱特征分析

旱灾具有出现频率高、持续时间长、波及范围广等特点，本文运用降水距平百分率、Z指数、SPI标准化降水指数，对朝阳地区50a（1969～2018）干旱特征进行分析。结果表明：Z指数与SPI标准化降水指标得到的朝阳地区干旱特征情况基本一致，能较好地反映出该地区的干旱特征，朝阳地区1969～2018年自然灾害频繁发生，严重干旱年份主要集中在1980、1981、1982 年，与实际相符。     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

混菌矿化增强再生粗骨料的物理力学性能

为克服单一微生物培养成本高且矿化鲁棒性不足的缺陷，提出了一种混菌矿化增强再生粗骨料物理力学性能的方法.通过筛选矿化效率较高的好氧嗜碱混菌，考察了混菌矿化对再生粗骨料物理力学性能和混凝土抗压强度的影响.结果表明：相同增强时间下，混菌比纯菌呈现出更优异的矿化增强效果；随着混菌矿化增强时间的延长，再生粗骨料吸水率和压碎指标呈现出先减小后增大的趋势，最优增强时间为15 d；采用矿化增强再生粗骨料制备的再生混凝土抗压强度提高幅度达到22.1%.     

Cold and wet: Diatoms dominate the phytoplankton community during a year of anomalous weather in a Great Lakes estuary

As sentinels of climate change and other anthropogenic forces, freshwater lakes are experiencing ecosystem disruptions at every level of the food web, beginning with the phytoplankton, a highly responsive group of organisms. Most studies regarding the effects of climate change on phytoplankton focus on a potential scenario in which temperatures continuously increase and droughts intersperse heavy precipitation events. Like much of the conterminous United States in 2019, the Muskegon River watershed (Michigan, USA) experienced record-breaking rainfall accompanied by unusually cool temperatures, affording an opportunity to explore how an alternate potential climate scenario may affect phytoplankton. We conducted biweekly sampling of environmental variables and phytoplankton in Muskegon Lake, a Great Lakes Area of Concern that connects to Lake Michigan. We compared environmental variables in 2019 to the previous eight years using long-term data from the Muskegon Lake Observatory buoy, and annual monitoring excursions provided historical phytoplankton data. Under cold and wet conditions, diatoms were the single dominant division throughout the entire growth season – an unprecedented scenario in Muskegon Lake. In 10 of the 13 biweekly sampling days in 2019, diatoms comprised over 75% of the phytoplankton community in the lake by count, indicating that the spring diatom bloom persisted through the fall. Additionally, phytoplankton seasonal succession and abundance patterns typically seen in this lake were absent. In a world experiencing reduced predictability, increased variability, and regional climate anomalies, studying periods of extreme weather events may offer insight into how natural systems will be affected and respond under future climate scenarios.