A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality. ● Improved model quickly converges to the global optimal fitness and remains stable. ● The prediction accuracy of water quality parameters is significantly improved. Water quality prediction is vital for solving water pollution and protecting the water environment. In terms of the characteristics of nonlinearity, instability, and randomness of water quality parameters, a short-term water quality prediction model was proposed based on variational mode decomposition (VMD) and improved grasshopper optimization algorithm (IGOA), so as to optimize long short-term memory neural network (LSTM). First, VMD was adopted to decompose the water quality data into a series of relatively stable components, with the aim to reduce the instability of the original data and increase the predictability, then each component was input into the IGOA-LSTM model for prediction. Finally, each component was added to obtain the predicted values. In this study, the monitoring data from Dayangzhou Station and Shengmi Station of the Ganjiang River was used for training and prediction. The experimental results showed that the prediction accuracy of the VMD-IGOA-LSTM model proposed was higher than that of the integrated model of Ensemble Empirical Mode Decomposition (EEMD), the integrated model of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Autoregressive Network with Exogenous Inputs (NARX), Recurrent Neural Network (RNN), as well as other models, showing better performance in short-term prediction. The current study will provide a reliable solution for water quality prediction studies in other areas.     

杀虫剂及抗生素对发光菌的短期毒性与长期毒性

以毒物对青海弧菌Q67 (Vibrio-qinghaiensis sp.-Q67)发光抑制为毒性指标,基于短期微板毒性分析法(S-MTA法),建立了长期微板毒性分析法(L-MTA法),测定了吡虫啉(IMI)、抗蚜威(PIR)、啶虫脒(ACE)及敌百虫(DIP)等4种杀虫剂与氯霉素(CHL)、盐酸四环素(TET)、硫酸链霉素(STR)及硫酸巴龙霉素(PAR)等4种抗生素的短期(15 min)毒性和长期(12 h)毒性.采用短期毒性与长期毒性EC₅₀之比(RSL)为指标,表征同一物质的毒性差异. 结果表明:3种杀虫剂(IMI,ACE及PIR)的短期毒性与长期毒性差异不大(其RSL分别为0.84,0.81和1.11);杀虫剂DIP和2个抗生素(CHL及TET)的短期毒性与长期毒性差异明显(其RSL分别为11.76,9.67及154.38);另2个抗生素(STR和PAR)只有较强的长期毒性.      

The potential of statistical state space models in urban ozone forecasting

State space models for tropospheric urban ozone prediction are introduced and compared with linear regression models. The linear and non-linear state space models make accurate short-term predictions of the ozone dynamics. The average prediction error one hour in advance is 7 μg/m³ and increases logarithmically with time until it reaches 26 μg/m³ after 30 days. For a given sequence of solar radiation inputs, predictions converge exponentially with a time scale of 8 hours, so that the model is insensitive to perturbations of more than 150 μg/m³ O₃. The slow increase of the prediction error in addition to the uniqueness of the prediction are encouraging for applications of state space models in forecasting ozone levels when coupled with a model that predicts total radiation. Since a radiation prediction model will be more accurate during cloud-free conditions, in addition to the fact that the state space models perform better during the summer months, state space models are suitable for applications in sunny environments.     

Financial inadequacy and the disadvantageous changes in time perspective and goal-striving strategies throughout life

As inequality in wealth and income continues to grow, it is important to consider the implications of financial disparities for worker motivation and behavior. While workers with socioeconomic disadvantages have a decreased chance of career success and upward social mobility, the potential mechanisms linking financial status to work motivation outcomes are not fully known. Drawing on theory on resource scarcity, we address this issue and propose that financial inadequacy shapes the extent to which workers consider and plan for the future, with consequences for goal-striving strategies throughout adulthood. Latent change analyses of data from a heterogeneous sample of 4,446 working adults largely supported the hypotheses. Results showed that a high level of financial inadequacy predicted increases in short-term time horizon and decreases in future-oriented planning, which then predicted disadvantageous changes in goal-striving strategies over an 18-year period. Short-term time horizon also predicted subsequent increases in financial inadequacy. By highlighting the motivational challenges associated with inadequate finances that accompany low-wage employment, our study offers evidence for the motivational mechanisms that may reinforce economic inequality and social mobility in the workforce.     

生物炭添加对土壤温室气体排放影响的长短期效应研究进展

人类活动引起的大气温室气体浓度增加是气候变暖的主要原因,全球变暖已经成为了当今人类社会所面临的严峻挑战,应对气候变暖的关键是减少温室气体排放和增加生态系统碳汇,由于生物炭特有的理化和生物学特性,将其施入土壤被认为是一种有前景的减排增汇措施.因此进行生物炭对土壤温室气体排放的影响研究对于减缓温室效应和实现“碳中和”具有重要意义.通过综述生物炭对土壤温室气体排放影响的长短期效应及其影响机制,发现生物炭添加对土壤温室气体排放的影响因生物炭原料类型、热解温度、添加量、土壤和植被类型的不同而不同.此外,因老化时间、老化方式和培养方法的不同,老化生物炭对土壤温室气体的减排效应可能增强或减弱甚至消失.同时,在总结现有研究不足的基础上,对未来生物炭影响土壤温室气体排放研究的方向和重点进行了分析和展望,提出了今后应加强CO₂、 N₂O和CH₄排放影响的同步研究、减排与固碳效应的同步研究、不同老化方式生物炭和不同培养方法的联合研究和利用¹³C和¹⁵N示踪技术从过程层次上揭示影响机制.     

短期填埋龄垃圾堆体内微生物群落结构与种群分布特征

填埋垃圾的稳定化过程一般经历好氧过渡、水解酸化、初期产甲烷及稳定产甲烷阶段,固相垃圾的厌氧水解酸化阶段常被视为垃圾降解的限速步骤,而这一阶段微生物的降解作用是影响垃圾稳定化进程的关键.以青岛市小涧西生活垃圾填埋场短期填埋龄垃圾为研究对象,采用MiSeq高通量测序研究了填埋龄0～1、1.0～1.5、1.5～2 a垃圾堆体内微生物的群落结构多样性及种群分布特征.结果表明,0～1 a填埋龄垃圾微生物多样性高于1.0～1.5 a和1.5～2 a垃圾堆体,且微生物多样性整体上随填埋深度呈降低趋势.参与垃圾降解细菌多样性比真菌更丰富,而真菌多样性随填埋区域、填埋龄的不同呈现更显著的差异.参与短期填埋龄垃圾降解的细菌中,Firmicutes在填埋层上层为优势菌门,最大比例达到65%,Proteobacteria在填埋层中下层为优势菌门,最大比例达到88%.填埋上层细菌菌属以Defluviitoga、Aerococcus、Clostridium III和Proteiniphilum为主,而在中下层以Thiopseudomonas、Sporosarcina和Eionea为主.真菌主要包括3个菌门,Ascomycota在各点位均为最优势菌门,属水平上Kernia及Aspergillus作为常见的腐生菌属,在不同点位均有较高的丰度.冗余分析表明短期填埋龄垃圾堆体内微生物不同时空分布存在显著差异性,且细菌群落结构的变化受pH值影响较大,而真菌群落结构的变化与垃圾有机质密切相关.     

基于机器学习的短临预报方法及其在空气质量保障中的应用

基于多个数值模式(NAQPMS、CMAQ)预报结果和站点观测资料,采用岭回归机器学习方法构建了一种多污染物短临预报方法,并应用于2017年厦门金砖国家峰会和2019年武汉军运会空气质量保障工作,评估总结了短临预报方法的可行性和预报效果。结果表明:短临预报表现出很好的预报能力,可以有效改进数值模式的预报趋势和量值。从日均模拟效果来看,短临预报的颗粒物相关系数达到0.9以上,均方根误差小于5μg/m~3,而且预报的臭氧相关系数和均方根误差分别为0.99和2μg/m~3。相较于日均数值模式预报结果,短临预报可使颗粒物和臭氧的预报相关系数至少提升16%和9%,预报均方根误差至少下降50%和86%。对于小时模拟效果,短临预报能够更好地把握颗粒物的小时变化特征,其相关系数较模式提升了0.2以上;同时短临预报能够更好地再现观测到的臭氧日循环特征,对白天的峰值和夜晚的低值预报更好,其相关系数高达0.9。总体来说,短临预报方法可为重大活动空气质量保障提供较为精准的临近预报结果,具有较好的应用价值。     

MONITORING TRANSIENT WATER QUALITY EVENTS ELECTRONICALLY1

ABSTRACT: Electronic instruments are ideally suited to gathering information regarding transient events. Data loggers equipped with water quality sensors offer an opportunity to study events on fine time scales which cannot be sampled using other means. The utility and significance of this type of data gathering is illustrated with data gathered from two small streams. Three examples are used to illustrate some types of transients that can be observed using electronic data acquisition techniques.     

A pharmacokinetic modeling of inorganic arsenic: a short-term oral exposure model for humans

This study presents a pharmacokinetic modeling of inorganic arsenic disposition in human body for short-term oral exposures. Effort on the development of the model is directed toward the prediction of the kinetic behavior of inorganic arsenic and its metabolites in the body. The current model considers the 4 circulating species; As^III, As^v, and two metabolites such as monomethylarsenic (MMA) and dimethylarsenic (DMA) in the blood and tissue groups. While it is difficult to estimate some parameters used in the models at this time, the current model assumptions and predictions seem to be consistent with the experimental observations found in the literature. Hence, the current model, when more fully developed, is expected to provide insight into the behavior of inorganic arsenic and its methylated metabolites within the body, and may help increase the understanding of risk assessment issues associated with inorganic arsenic in drinking water.