我国内蒙古大兴安岭北麓泡状肝包虫种类的研究I.多房棘球绦虫

人兽共患泡状(多房)棘球蚴病的病原种类,一向人们都认为只有多房棘球绦虫一种,其中包含分布在不同地区的2-3个地理株(或亚种)(Vogel,1957;KumaratilakeandThompson,1982;Miyazaki,1991;等)。但在我国内蒙古东北部大兴安岭北麓呼伦贝尔草原,却存在着多房棘球绦虫(EchinococcusmultilocularisLeuckart,1863)的所谓三个“地理株(或亚种)”:欧洲的多房棘球绦虫、冻土地带的西伯利亚棘球绦虫和苏俄的多房棘球绦虫。它们在内蒙古不仅存在于同一流行区,而且成虫常混合感染于同一终宿主沙狐的体内。2001年,作者再次检查呼伦贝尔的沙狐151只,从中检出19只感染有泡状棘球绦虫成虫,其中有9只混合感染上述的不同形态的三虫种。观察了它们成虫的埋蜡连续切片的制片,说明它们的子宫是各有稳定不变的结构。这三虫种经人工感染数百只实验鼠,比较观察了各虫体幼虫期大量的埋蜡连续切片,再次证实此三虫种在中间宿主鼠类体内发育的幼虫期,是各有一定的结构和发育格式。本文着重介绍欧洲型多房棘球绦虫的成虫子宫结构和它幼虫期发育

我国内蒙古大兴安岭北麓泡状肝包虫种类的研究 II.西伯利亚棘球绦虫(Echinococcus sibiricensis Rauschet Schiller,1954)

目的Rausch and Schiller(1954)在美国阿拉斯加白令海峡St.Lawrence岛从北极狐(Alopex lagopus)和雪撬狗(sledge dogs)发现西伯利亚棘球绦虫新种(Echinococcus sibiricensis sp.nov.),但诸多学者认为E.sibiricensis Rausch et Schiller,1954是欧洲的多房棘球绦虫(Echinococcus multilocularis Leuckart,1863)的地理株(或亚种)(Vogel,1957;Skrjabin and Abuladze,1964;Kumaratilake and Thompson,1982;Meyajaki,1991等)。于1985-2002年间,作者在我国内蒙古大兴安岭北麓草场多年进行泡状棘球蚴(alveolar Echinococcus)病原的野外调查和实验室鼠类的人工感染试验,结果发现该地区同地点存在有北美西伯利亚棘球绦虫、欧洲多房棘球绦虫及苏俄多房棘球绦虫三种不同"地理株",而且三种成虫常混合感染于同一终宿主沙狐(Vulpes corsac)的体内,它们的幼虫期也存在于当地的布氏田鼠(Microtus brandti)。2001年,作者再次检查当地沙狐151只,从中检出19只感染有泡状棘球绦虫成虫。含成熟虫体的13只阳性沙狐中,感染西伯利亚棘球绦虫有11只,其中2只单独感染此虫种,另9只还混合感染了欧洲多房棘球绦虫及苏俄多房棘球绦虫三虫种。在呼伦贝尔草原的泡状棘球蚴病原中,西伯利亚棘球绦虫是优势种,它在终宿主沙狐和中间宿主的感染率都高过其他虫种。本文着重介绍西伯利亚棘球绦虫的成虫子宫结构和它幼虫期在野外布氏田鼠及人工感染实验鼠体内的发育情况

我国内蒙古大兴安岭北麓泡状肝包虫种类的研究 III.苏俄棘球绦虫(Echinococcus russicensis sp.nov.)

在我国内蒙古大兴安岭北麓草场流行有与在前苏联广泛分布的泡状棘球蚴其成虫具球形子宫相似的病原,过去称之为苏俄的多房棘球绦虫。我们在比较研究了它与欧洲的多房棘球绦虫的全程生活史的发育规律,及成虫和幼虫期的结构之后,发现两者之间有极大差异,认为不能再用多房棘球绦虫称呼之。最近,我们用内蒙古的苏俄型泡状棘球蚴人工感染4只羊羔,全部阴性不能发育,说明内蒙古的本虫种不同于所谓幼虫期可以在牛羊发育的"哈萨克亚种"。为了纪念前苏联学者最早发现和叙述本种成虫,兹暂定名为苏俄棘球绦虫新种(Echinococcus russicensis sp.nov.)

计入热效应的曲轴主轴承润滑性能影响因素分析

针对曲轴主轴承润滑性能的影响因素，建立计入热效应的主轴承弹性流体动力润滑模型，模型将轴承外部载荷、轴承间隙和进油温度作为变量，分析了主轴承在不同变量下的最大油膜压力、最小油膜厚度、最高轴承温度和最大摩擦功率损失。结果表明，计入热效应对曲轴主轴承有较大影响，当轴承外部载荷增大时，轴承的最大油膜压力、最小油膜厚度和最大摩擦功率损失均会增大；当轴承间隙变小时，轴承的最大油膜压力减小，轴承温度升高；当进油温度增加，轴承最大油膜压力增大、最小油膜厚度减小、最大摩擦功率损失减小

一种金属空气电池系统用电解液存储盒

一种金属空气电池系统用电解液存储盒，与金属空气电池系统的电解液腔相连，包括电解液存储盒为一中空容器，容器内部从左至右依次设有产物隔离挡板、产物过滤网；产物隔离挡板、产物过滤网将容器分隔成相互独立的产物腔、电解液/产物混合腔和电解液腔；产物腔与金属空气电池系统的电解液腔上部设置的电解液循环口通过管路相连，电解液腔与金属空气电池系统电解液腔下部设置的电解液加注口通过管路相连。本发明所述金属空气电池用产物管理系统具有：①产物可以得到充分的沉淀和分级过滤，②产物可以随时排出，③电池中的热量可以随产物的排出得到及时的排出，④电池阳极极板的有效利用率得到提高

Defining kerogen maturity from orbital hybridization by machine learning

Kerogen is the primary material for oil and gas. Its maturity is used to determine the potential for hydrocarbon generation. Nowadays, kerogen maturity is mainly measured experimentally and characterized by its chemical composition. The fundamental reason for the change in its chemical composition during the maturation is the breaking and recombination of chemical bonds, manifested by the transformation in atomic hybridization based on quantum mechanics. While traditional methods are time-consuming and labor-intensive, machine learning technique has been introduced to clarify the relationship between hybridization and maturity. A kerogen maturity prediction model based on hybridization is constructed. The average error of the predicted values is only 4.91%, and more than 87% of the test samples have an error of less than 10%. The results demonstrate that the model can accurately predict the maturity of kerogen. As the evolution of kerogen maturity increases the proportion of sp(2) hybridized carbons, the orbital hybridization maturity index (OrbHMI) is proposed. The chemical changes in the thermal evolution and pyrolysis mechanism of kerogen can be explained and understood more essentially by OrbHMI. The results provide a basis for guiding artificial maturation and pave a promising path toward studying the kerogen structure and predicting hydrocarbon generating potential

Effect of GA_3 and Thiourea on Newly Developed Rhizome and Fibrous Root of Polygonatum sibiricum Redoute

为诱导无芽黄精根状茎产生不定芽,选择不同的化学物质进行诱导处理。结果表明,GA3处理效果明显,选用0.4 mg/L的GA3浸泡25 min对黄精根状茎不定芽的产生和须根生长有明显促进作用,高浓度抑制其生长;1%硫脲浸泡处理对黄精无顶芽根状茎萌发新芽和须根有明显的抑制作用

Predicting the components and types of kerogen in shale by combining machine learning with NMR spectra

This study aims to develop a new method that combines machine learning with nuclear magnetic resonance (NMR) spectra to predict the kemgen components and types. Kerogen is the primary hydrocarbon source of shale oil/gas, and nearly half of the hydrocarbons in shale are adsorbed in kemgen. The adsorption and hydrocarbon generation capacity of kerogen is directly related to its types, molecular components, and structures. Fruitful researches studying kerogen at the molecular level have been conducted. Unfortunately, these methods are complicated, time-consuming, and labor-intensive. Our method has the advantages of high-throughput prediction, high accuracy, and time savings compared with the existing methods. Additionally, this method simplifies the operations from repetitive trial and error. This study proposes a solution to convert non-uniform two-dimensional (2D) graph into a uniform one-dimensional (1D) matrix, which makes 2D graph data available for machine learning models. An automatic labeling platform is constructed that annotated over 22,000 groups of organic matter molecules and their NMR spectra. The results show that the carbon, hydrogen, and oxygen element prediction accuracy reach 96.1%, 94.8%, and 81.7%, respectively. In addition, the accuracy of the three kerogen types is approximately 90% in total. These results reflect the excellent performance of the machine learning method. Therefore, our work provides an automated and intelligent prediction and analysis method, which is a powerful and superior tool in kerogen studies at the molecular level

一种电解液间歇循环式金属/空气电池系统

本发明涉及一种电解液间歇循环式金属/空气电池系统，包括金属/空气电池组（1）、电解液存储盒（2）、电解液循环系统（3）、产物排出系统（4）及与金属/空气电池组并联的二次电池；该金属/空气电池系统的操作控制方法，包括金属/空气电池组对外放电：二次电池的充放电过程以及产物的排出及电解液的置换。与现有技术相比，本发明可实现电解液的自主加注和产物的自主排出，简化了电池维护过程；电解液间歇循环，循环泵不连续工作，降低了泵的能耗和电池工作过程的噪音；电池工作过程中产生的热量可随电解液排出电池外，依靠静态过程实现热量散出；电池停止工作后，电解液与金属阳极分割储存，避免了金属阳极在储存过程中的自腐蚀，提高了金属阳极的利用率