2 research outputs found
Abundance and production of bacteria and their correlations with environmental factor
以2014年8月南海北部海水样品为研究对象,利用平板计数法和流式细胞仪计数法对南海北部表层和垂直海域可培养细菌和细菌总数分布状况进行研究,对细菌; 生产力进行测定,并结合环境因子进行相关性分析。结果表明:珠江口到南海北部海域,水平方向可培养细菌总数变化范围是3.70*10~2 ~; 1.42*10~3 CFU/mL,细菌总数变化范围是5.12 * 10~5 ~1.61 * 10~6; cells/mL,细菌生产力的变化范围是0.03 ~0.40 mg/m~3/h;垂直方向上可培养细菌变化范围是1.08 *10~3 ~9.00; *10~3 CFU/mL,细菌生产力变化范围是0.01 ~0.08; mg/m~3/h,其中表层海水中的细菌生产力明显高于底层。与环境因子相关性分析表明,水平方向上,影响南海北部表层海水细菌总数和细菌生产力的主要因; 素是温度、盐度、硝酸盐(NO_3-N)、硅酸盐(SiO_3-Si)、亚硝酸盐(NO_2-N)和磷酸盐(PO_4-P)(P<0.05);垂直方向上; ,影响南海北部可培养细菌总数的主要因素是NO_2-N(P<0.05),影响细菌生产力的主要影响因素是温度和盐度(P; <0.05)。可见,南海北部表层海水中细菌总数高于可培养细菌总数2; ~3个数量级,表明该海域表层海水存在大量不可培养细菌;细菌的生命活动在海水表层相较底层更为活跃。Distribution of abundance and production of bacteria and their; correlations with environmental factor were investigated, using plate; count method and flow cytometry, in the surface and vertical waters of; the northern south China sea in August 2014. The cultivable bacterial; abundance ranged from 3.70 * 10~2 CFU/mL to 1.42 * 10~3 CFU/ mL, the; total bacterial abundance ranged from 5.12 * 10~5 cells/mL to 1.61 *; 10~6 cells/mL and the bacterial productions varied from 0.03 mg/m~3/h to; 0.40 mg/m~3/h in horizontal distribution. In vertical distribution, the; cultivable bacterial abundance ranged from 1.08 * 10~3 CFU/mL to 9.00 *; 10~3 CFU/mL and the bacterial productions varied from 0.01 mg/m~3/h to; 0.08 mg/m~3/h, respectively. The correlation analysis results showed; that the environmental factors affecting the abundance of total bacteria; and bacterial productivity included temperature, salinity,; nitrate(NO_3-N),silicate (SiO_3-Si), nitrite (NO_2-N),and phosphate; (PO_4-P) (P<0.05). NO_2-N was the main influencing factor to cultivable; bacteria abundance (P < 0.05), while bacterial productivity was highly; correlated with temperature and salinity in vertical distribution of; northern south China sea (P < 0.05). The total bacterial abundance was 2; ~ 3 orders of magnitude higher than cultivable bacteria, suggesting that; there were many uncultured bacterium in surface water of northern south; China sea and bacterial activities in the surface maybe more active than; in the bottom.全球变化与海气交互作用; 国家重点研发计划全球变化及应对专项; 海洋公益性行业科研专
基于扩散模型数据增广的域泛化方法
域泛化是计算机视觉领域中一个重要且具有挑战性的问题,该问题源于现实场景中的数据分布偏移。在实际应用中,通常会遇到训练数据和测试数据来自不同的数据域的情况,这种数据分布的差异会导致测试时准确率下降。因此,提出了一种基于隐空间数据增广的域泛化方法,与传统图像级数据增广方法不同,该方法在隐空间中引入扩散模型,以实现对特征的精细控制和多样性生成,从而提升模型在目标域上的泛化能力。具体来说,基于分类器的隐式扩散模型在隐空间训练后可以条件生成准确且丰富的源域特征,并利用高效的采样方法加速生成增广特征。实验结果表明,新提出的方法在各种域泛化任务上取得了显著的性能提升,在真实场景中有较好的有效性和鲁棒性。该方法的创新点在于将数据增广焦点转移到隐空间级别,并引入扩散模型进行增广,为解决域泛化问题提供了一种新的思路