Performance evaluation of venturi aeration system

The venturi aeration is an effective practice to increase the dissolved oxygen accessibility in the water bodies. This study aims to optimize the various geometrical parameters of the venturi aeration system. A non-dimensional technique was applied to find the optimum performance of various geometric parameters i.e. throat lengths (t_l), number of air holes (N), and converging and diverging angles (α and β). These experiments have been carried out using 1124 L capacity of tank having dimensions of 105 cm long, 105 cm wide and 102 cm deep. The experiments were conducted at a constant flow velocity of water (1.096 m/s) with varying throat length (t_l = 20–100 mm keeping 20 mm as interval between two consecutive length), number of air holes (N = 1–17 at an equal hole to hole distance of 5 mm between them), and converging and diverging angles (α and β = 10°, 15°, 20° and 25°). Multiple non-linear regression equations were also developed from the linear relation with the dependent variable (Non-dimensional form of standard aeration efficiency, NDSAE) and independent variables (t_l and N). With the geometrically optimized venturi aerator the optimum performance was found for t_l =100 mm, N = 17, and α and β = 15°. The maximum value of standard oxygen transfer rate (SOTR) and standard aeration efficiency (SAE) obtained was 0.0216 kgO₂/h and 0.611 kgO₂/kWh respectively. From the non-dimensional study, it was found that the NDSAE is the function Reynolds number (Re) and Froude number (Fr). The simulation equations were developed on the basis of Re and Fr for NDSAE, and subjected to 7.378 × 10⁻⁶ < Re < 3.689 × 10^-5 and 0.163 < Fr < 0.817, respectively.     

岩溶流域典型农业区水体氢氧同位素的空间异质性及形成机制

分别于平水期和枯水期采集了花溪河流域典型农业区地表水和地下水样品。利用氢氧同位素示踪技术,结合土地利用类型对研究区不同水体的补给来源、季节变化及主要影响过程进行了分析,并对不同水体氢氧同位素值进行了空间插值分析,同时对其形成机制进行了分析,阐明了不同土地利用类型影响下的主要水文过程。结果表明:(1)研究区不同水体的主要补给来源为当地大气降水,月亮湖水库受蒸发作用影响明显,地表水和地下水的δD和δ~(18)O整体上呈现平水期高于枯水期的特征。(2)地下水的δD和δ~(18)O在枯水期与平水期均呈现明显的空间分异性特征,西部水田/水库集中区富集,东部旱地集中区贫化,土地利用对研究区环境水文过程影响明显。该研究结果有助于了解不同土地利用方式下地表水对地下水的影响,为流域管理提供科学依据。     

PEI/APP改性脲醛树脂制备阻燃胶合板及性能

以聚乙烯亚胺(PEI)为改性剂处理聚磷酸铵(APP)制备得到APP@PEI阻燃体系,并将其加入到脲醛树脂(UF)中,制备阻燃胶合板。研究了APP@PEI对UF胶黏剂理化性能的影响,并进一步探讨其对胶合性能及阻燃性能的影响。结果表明:APP、PEI和APP@PEI对UF的黏度、pH和固化时间均有影响。当APP添加量为10%时,UF的黏度由3.843 Pa·s上升至8.270 Pa·s,pH降至5.67,固化时间由91 s降至87 s;当PEI添加量为0.91%时,由于UF体系中支化和交联程度增加,黏度上升至41.433 Pa·s,pH和固化时间分别提升至9.91和116.3 s;而APP@PEI能降低对UF各项性能的影响,添加10%APP@PEI时UF的黏度、pH和固化时间分别为5.966 Pa·s、6.33和94.3 s。添加APP后,胶合板的胶合强度均低于Ⅱ类胶合板强度标准(0.7 MPa);添加PEI后,胶合板的胶合强度能够提升18%以上;APP@PEI添加量为10%时,胶合板的胶合强度达0.85 MPa,高于Ⅱ类胶合板强度标准要求。添加APP、PEI和APP@PEI对胶合板的阻燃性能有不同影响,单独添加PEI无法改善胶合板的阻燃性能,当APP和APP@PEI添加量为10%,15%和20%时,胶合板的极限氧指数(LOI)分别比未添加阻燃剂时提高0.8%,2.0%,2.5%和1.2%,2.2%,3.1%。     

主成分分析和长短时记忆神经网络预测水产养殖水体溶解氧

为了提高水产养殖溶解氧预测的精度,提出了基于主成分分析(principal component analysis,PCA)和长短时记忆神经网络(long short-term memory,LSTM)的水产养殖溶解氧预测模型。首先通过主成分分析提取水产养殖溶解氧的关键影响因子,消除了原始变量之间的相关性,降低了模型输入向量维度;然后,在Tensorflow深度学习框架的基础上建立LSTM神经网络的水产养殖溶解氧预测模型;最后,利用该模型对浙江省淡水水产养殖研究所综合实验基地某池塘溶解氧进行验证。试验结果表明:该模型与BP神经网络等其他浅层模型相比,模型评价指标平均绝对误差、均方根误差和平均绝对误差分别为0.274、0.089和0.147,均优于传统的预测方法;该模型具有良好的预测性能和泛化能力,能够满足水产养殖溶解氧精确预测的实际需要,可以为水产养殖水质精准调控提供参考。     

不同光质LED光源对鱼腥草幼苗膜脂过氧化及抗氧化酶的影响

以鱼腥草为材料,以日光灯处理为对照,分析了不同光质LED光源(白、红、黄、绿、蓝LED灯)对鱼腥草叶片活性氧、类黄酮含量及抗氧化酶的影响。结果表明,蓝光下叶片中TBARS(硫代巴比妥酸)含量最高,较对照高30.18%,与希夫试剂染色结果相一致;过氧化氢产生最多,较对照高190.21%,与DAB染色结果一致;超氧阴离子产生速率在蓝光下最高,为对照组的1.54倍,白光下最低;蓝、绿光下脯氨酸含量是对照的2倍;蓝光和黄光处理下,黄酮含量较对照提高了21.4%。蓝、绿光提高了SOD2同工酶的表达,且在蓝光下最高;蓝、绿、红、黄光处理分别诱导了更多的POD基因位点的表达;不同LED光质均提高了CAT抗氧化酶活性,其中蓝、绿光下CAT同工酶的表达量明显高于对照。综上所述,蓝色光处理可以有效提高幼苗的抗氧化能力,可为鱼腥草品质的控制提供参考。     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.     

土壤氮素内循环对生态覆被变化响应的研究进展

随着人口增长对粮食需求的不断提高,人类对自然生态系统扰动频繁,生态覆被/土地利用变化伴随着土壤活性氮库、氮形态组分及氮素内循环过程的改变,直接影响生态系统的持续与稳定,进而引起全球气候变暖,生物多样性减少等诸多生态环境问题。生态覆被/土地利用变化是全球生态系统变化的重要内容。本综述探讨了活性氮的基本概念及其引发的环境效应,国内外自然生态系统中森林与草地间转换、自然生态系统开垦为农田、弃耕撂荒或退耕还林还草、城市化发展等生态覆被/土地利用变化对土壤氮库消长、氮矿化产物形态变化以及影响氮循环的关键土壤微生物影响等,并探讨了制约氮循环的土壤微生物研究进展。指出农业开垦或农田弃耕撂荒会导致土壤全氮大幅度下降,同时引起土壤硝态氮(NO3--N)增加,造成环境活性氮增加的风险;退耕还林修复生态覆被过程中氮库完全恢复需要漫长的时间;运用现代微生物分子生态学的前沿技术是研究土壤氮循环对生态覆被/土地利用变化响应机理的关键。本综述为自然生态系统的保护与开发利用、退化生态系统的修复与重建以及人工生态系统的科学规划等提供了理论依据。     

草莓白化相关病毒中国分离物全基因组分析

草莓白化相关病毒(strawberrypallidosis-associatedvirus,SPa V)属于长线形病毒科(Closteroviridae)毛形病毒属(Crinivirus),可引起草莓病害,2017年在中国首次报道。采用高通量测序、RACE和RT-PCR技术获得了SPa V中国分离物(FJ)的基因组全长。该病毒含有两条正单链基因组RNA1和RNA2。RNA1全长8 048 nt,5′和3′非编码区序列分别为264和197 nt,含有3个开放阅读框(ORF),分别编码ORF 1a/1b融合蛋白和p9蛋白。RNA2全长7 977 nt,5′和3′非编码区序列分别为248和186 nt,含有8个开放阅读框(ORF),分别编码HSP70h、CPh、CP、CPm、p7、p6、p9和p28等8个蛋白。RNA1和RNA2与美国M1分离物分别具有98.5%和99.0%的核苷酸一致性;系统发育分析结果表明,SPa V中国分离物(FJ)单独处在一个分支。对SPa V来源的小RNA的分析表明,来源于SPa V的小RAN长度以21和22 nt为主。     

有机培肥与耕作方式对稻麦轮作土壤团聚体和有机碳组分的影响

为了明确不同外源有机物和耕作方式对土壤地力培育的影响,以水稻-小麦轮作系统为对象,通过2个年度(2016—2018年)大田试验研究了外源有机物(秸秆和有机肥)和耕作方式及其交互作用[稻麦秸秆还田配合旋耕(SR),稻麦秸秆还田配合翻耕(SP),秸秆不还田、增施有机肥配合旋耕(MR),秸秆不还田、增施有机肥配合翻耕(MP),秸秆不还田、不施用有机肥、旋耕深度15 cm(CKR)]对土壤团聚体和有机碳组成的短期影响。结果表明:SR处理能够降低水稻季土壤容重并增加总孔隙度。相比CKR,小麦季SR处理显著增加0.05mm水稳性团聚体含量,增加量为7.2%。此外,外源有机物和耕作对土壤有机碳活性组分具有显著影响。其中,易氧化有机碳(EOC)主要受耕作与有机物交互作用影响,酸水解有机碳(LPIc和LPII_c)主要受耕作措施的影响, SR处理的土壤EOC和LPI_c含量比CKR提高0.3～2.6 g·kg~(-1)。颗粒有机碳(POC)主要受外源有机物的影响,并且秸秆还田处理POC平均含量高于增施有机肥处理,增加量为0.75g·kg~(-1)。短期内,外源有机物和耕作及其交互作用对稳定性有机碳(黑碳和矿物结合态有机碳)的影响较小。综上,秸秆还田配合旋耕有助于提高土壤水稳性团聚体和活性有机碳的含量(EOC、LPI_c和POC)。