养殖俄罗斯鲟性腺发育及人工繁殖

在繁殖季节通过肉眼观察和组织切片对池塘养殖7龄的俄罗斯鲟(Acipenser gueldenstaedti)性腺发育进行分析,发现雌性个体间性腺发育差异较大(n=500)。其中73%卵巢中可以看到白色卵粒,卵径小于1.0mm;有16%卵巢达到Ⅲ期,卵粒已经着色;有9%卵巢发育到IV期早期,卵径平均为2.6±0.2 mm;还有2%卵巢中肉眼看不到卵粒,组织学观察属于I期卵巢。雄性俄罗斯鲟全部达到性成熟,有部分成熟好的可以挤出精液。激素催产2尾八龄和6尾九龄的雌性俄罗斯鲟,其中7尾催产成功;剖腹手术收集游离卵7.2 kg,催产后的雄鱼全部排精。     

交互性英语教学与情商培养

情商是心理素质的核心部分。在英语教学中关注学生的情商培养具有积极而深远的意义。交互活动的本质是一个认知活动和情感因素相互作用下不断变化的心理过程。在交互性英语教学中,可通过以下途径培养学生的情商：1.激发学生的学习兴趣;2.建立新型的师生关系,注重师生的情感交流;3.创设良好的课堂氛围;4.关注学生个性发展,实现积极情感的迁移。     

现代旅游中家园遗产的生态链——广西秀水村旅游开发潜伏的危机

以广西壮族自治区、贺州市富川瑶族自治县的秀水村在生态旅游开发中所面临的情形为例,试图阐明现代生态旅游给地方“家园生态”纽带可能造成断裂的后果。并以此反思现代旅游在乡土社会中所遇到的矛盾和挑战对于游客来说,生态旅游意味着到一个生态良好的环境中去休闲;纵使游客具有很好的生态保护意识,也只能说明旅游行为一个方面。而对于旅游目的地,特别是东道主社会,他们在生态旅游方面的准备,包括知识、意识、行为、规划等都可能存在问题,特别是发展中国家,情形会更严重。这种不对衬的交流,通过金钱和权力所实现的现代旅游,可能会给“自然生态”带去“人为生态”的异化。     

怒江水电开发与环境保护

怒江水电开发,国内议论较多,争论也很激烈.怒江是三江并流的主要组成部分.对三江并流作了简要介绍,提出怒江不宜全水头进行水电开发,应以不损害自然景观及人文景观为前提,力求自然景观与人文景观和谐并存,建设更加美丽的怒江;可开发河段,既要将水资源充分利用,又要保护好怒江的自然景观和生态环境,也就是保护好三江并流这一世界自然遗产的完整性和自然性,真正做到开发怒江水电,保护自然环境,实现经济、社会、资源与环境相互协调和可持续发展,构建和谐社会.     

基于人工免疫系统的计算机网络安全策略

分析了人工免疫系统的发展现状,介绍了计算机免疫系统的实现机理,提出了一种人工免疫系统的体系结构,展望了人工免疫系统在计算机安全中的应用前景。     

改进的粒子群优化算法结合人工神经网络用于有机物毒性的QSAR研究

介绍了粒子群优化算法和Alopex-B算法的基本原理,提出了一种用Alopex-B算法改进的粒子群优化算法,并将其应用于函数优化和有机物毒性的QSAR研究。结果表明:改进型粒子群算法对复杂的测试函数搜索效率明显提高,应用于有机物毒性的QSAR研究能提高计算的精确度,降低预测误差。     

翘嘴红鲌繁殖技术研究

通过试验研究了翘嘴红鲌亲鱼培育、人工催产、受精卵孵化的技术。结果表明:天然水域捕捞的翘嘴红鲌鱼种在池塘条件下,通过人工培育能够达到性成熟,其成熟系数为14.46,相对繁殖力为30.28。亲鱼采用一次性注射组合催产剂,自然产卵的方式,受精卵在孵化环道中完成胚胎发育孵化出苗,LRH-A2 1.2μg DOM 5 mg和LRH-A2 1.2μg HCG 1 000 IU PG 0.8 mg催产剂组合具有较高的催产率和受精率。     

Biocompatibility studies of silk fibroin-based artificial nerve grafts in vitro and in vivo

Silk fibroin(SF)has been used extensively in the biomedical field including tissue engineering for the generation of artificial bones,skins or ligaments.We have previously reported on good in vitro biocompatibility of SF fibers with peripheral nerve tissues and cells.In the present study,we developed a novel design of the SF-based artificial nerve graft(SF graft)which was composed of a SF-nerve guidance conduit(NGC)inserted with SF fibers.MTT assay was performed to determine the cytotoxicity of the SF-NGC extract fluid on the cultured L929 cells derived from an immortalized mouse fibroblast cell line.In addition,this SF graft was implanted into adult rats for bridging a 10-mm long sciatic nerve defect.The following-up experiments at initial stage(1-4 week)of nerve regeneration including routine blood tests and histochemical investigation were conducted to evaluate the in vivo biocompatibility of the SF graft with peripheral nerves.The results demonstrated that the SF-NGC graft was biocompatible with the surrounding tissues and cells due to its low inflammatory potential with a grade 0 under the U.S.Pharmacopeia guidelines and it was generally suitable to a certain degree for bridging peripheral nerve defects in virtue of supporting Schwann cell adherence,expansion and migration.Therefore the SF graft is a promising alternative to classical autografts for peripheral nerve repair.     

对不平衡类分类的一种组合方法

具有不平衡类分布的数据集在许多实际应用中是很常见的,但由于类分布不平衡,给那些已有的分类算法带来了很多问题。一种为处理不平衡类问题而开发的基于决策树和人工神经网络的有效组合方法被讨论。它基于数据抽样的方法构建组合分类器,并利用ROC曲线(Receiver Operating Characteristic curve)作为评价挖掘性能的分析工具,最后在PAKDD2007竞赛活动提供的实际数据上进行了有效性验证。     

Yarn Properties Prediction Based on Machine Learning Method

Although many works have been done to constructprediction models on yarn processing quality, the relationbetween spinning variables and yam properties has not beenestablished conclusively so far. Support vector machines(SVMs), based on statistical learning theory, are gainingapplications in the areas of machine learning and patternrecognition because of the high accuracy and goodgeneralization capability. This study briefly introduces theSVM regression algorithms, and presents the SVM basedsystem architecture for predicting yam properties. Model.selection which amounts to search in hyper-parameter spaceis performed for study of suitable parameters with grid-research method. Experimental results have been comparedwith those of artificial neural network(ANN) models. Theinvestigation indicates that in the small data sets and real-life production, SVM models are capable of remaining thestability of predictive accuracy, and more suitable for noisyand dynamic spinning process.