Estimation of protein synthesis rates using the flooding method and [15N] lysine

After injection of a single dose of double labelled lysine (1 MBq L-[u-¹⁴C]lysine and 150 μmol L-[α¹⁵N]lysine (95 atom% ¹⁵N)) to growing rats the fractional protein synthesis rates (FSR) of some organs were estimated by the “large dose-” or “flooding method”. Data obtained with both substances were compared and the following conclusions can be drawn:

—In principle lysine is suited as a flooding substance.

—In flooding experiments [¹⁴C]lysine and [¹⁵N]lysine gave identical FSR-values for the investigated organs.

—By application of [¹⁵N]lysine instead of the ¹⁴C labelled amino acid as flooding substance this method is suited for larger animals (pigs, sheep, ruminants) too, because of the absence of any radioactive burden.

Nach einmaliger Verabfolgung von doppelt markiertem Lysin (1 MBq L-[u-¹⁴C]Lysin und 150 μmol L-[α¹⁵N]Lysin (95 Atom% ¹⁵N)) an wachsende Ratten wurden nach der “Large dose-” oder “Flooding-Methode” die fraktionellen Proteinsyntheseraten (FSR) einiger Organe bestimmt und die für beide Substanzen erhaltenen Werte verglichen. Es ergaben sich folgende Schlußfolgergungen:

—Lysin ist grundsätzlich als Flooding-Substanz geeignet.

—[¹⁴C]Lysin und [¹⁵N]Lysin ergeben im Floodingversuch am gleichen Tier für die FSR der Organe identische Werte.

—Durch den Fortfall der radioaktiven Belastung bei Einsatz von [¹⁵N]Lysin anstelle von [¹⁴C]Lysin als Flooding-Substanz ist die Methode auch bei Croßtieren anwendbar.     

Bestimmung der 15N Häufigkeit bei nichtstatistischer 15N-verteilung in N2 sowie bei N2O in Bodenluftproben mittels GC-R-IRMS-Kopplung in einem Probenlauf

Abstract

An analysis technique based on GC-R-IRMS coupling (Gas-Chromatography-Reduction-Isotope Ratio Mass Spectrometry) is demonstrated. The ¹⁵N abundance of N² and N²O in atmospheric air or soil atmosphere from nitrification or denitrification processes with nonrandom distribution is determined in one run. The 12 ml sample is separated from CO² and transported by a helium gas stream through a cooling trap. The N²O is trapped in the cooling trap while the N² passes through it and enters the GC. After GC separation and O² removal in a reduction column, part of the N² enters an isotope mass spectrometer to determine the masses m/z 28,29 and 30. The interferences on mass 30 by the formation of NO in the ion source of the mass spectrometer are eliminated by a calibration and a correction procedure. Upon removing the cooling trap, the N²O is injected into the GC, where it is separated and then quantitatively reduced to N² in a reduction column. The measurement of one sample takes 16 minutes. The detection limit of the ³⁰R_t in alteration N₂ is Δ³⁰R_t = 5 · 10^?7. The detection limit of the N₂O is 3.6 nl.     

主成分分析结合BP神经网络对短程生物脱氮中氮的近红外光谱研究

为实现高效短程生物脱氮及氨氮和亚硝酸盐氮的快速检测,采用主成分分析结合BP神经网络的方法建立短程生物脱氮工艺中氨氮和亚硝酸盐氮的近红外光谱定量分析模型(BP神经网络模型)。工艺运行结果表明：原水经过好氧阶段氨氮从45.3 mg·L-1下降到2.7 mg·L-1,亚硝酸盐氮从0.01 mg·L-1上升到19.6 mg·L-1,硝酸盐氮受到抑制;在缺氧段亚硝酸盐氮从19.6 mg·L-1下降至1.2 mg·L-1,系统实现了良好的短程生物脱氮效果。水样原始光谱主成分分析表明：前13个主成分代表了原始光谱数据的信息,其累计贡献率达到95.04%,排除了冗余信息且大大降低了模型的维数,光谱数据矩阵从192×2 203减少到192×13,大大降低了运算量并提高了模型的精度。BP神经网络模型校正结果显示：BP神经网络模型对氨氮、亚硝酸盐氮校正时的决定系数(R2)分别达到0.950 4和0.976 2,校正均方根误差(RMSECV)分别为0.016 6和0.010 9。BP神经网络模型预测结果显示：BP神经网络模型对氨氮、亚硝酸盐氮预测输出与期望输出之间的决定系数(R2)分别为0.974 0和0.981 4,预测均方根误差(RMSEP)分别为0.033 7和0.028 7,模型预测效果良好。研究表明,BP神经网络模型可以通过快速测定水样的近红外光谱数据预测短程生物脱氮工艺中氨氮和亚硝酸盐氮浓度,并根据氨氮和亚硝酸盐氮浓度变化及时、灵活地控制工艺的运行,为生物脱氮提供快速有效的检测技术和科学依据。     

低渗透油藏聚合物强化泡沫调剖剂

为改善某低渗透油田的水驱开发效果,开展了聚合物强化氮气泡沫调剖提高采收率研究.根据该油田的地质油藏条件,建立典型地质概念模型,地质模型能够比较完整地反映地层静态状况和井网条件.对聚合物强化泡沫调剖注采参数进行了优化设计.研究结果表明,聚合物强化氮气泡沫调剖最佳注采参数为:聚合物分子量为800万,聚合物浓度为1000mg/L,最佳泡沫剂浓度为0.25%(质量分数),气液比为1:1.     

Energetics of carbon and nitrogen impurities and their interactions with vacancy in vanadium

We studied the energetic behaviors of interstitial and substitution carbon(C)/nitrogen(N) impurities as well as their interactions with the vacancy in vanadium by first-principles simulations. Both C and N impurities prefer the octahedral site(O-site). N exhibits a lower formation energy than C. Due to the hybridization between vanadium-d and N/C-p, the N-p states are located at the energy from-6.00 e V to-5.00 e V, which is much deeper than that from-5.00 e V to-3.00 e V for the C-p states. Two impurities in bulk vanadium, C–C, C–N, and N–N can be paired up at the two neighboring Osites along the 111 direction and the binding energies of the pairs are 0.227 e V, 0.162 e V, and 0.201 e V, respectively.Further, we find that both C and N do not prefer to stay at the vacancy center and its vicinity, but occupy the O-site off the vacancy in the interstitial lattice in vanadium. The possible physical mechanism is that C/N in the O-site tends to form a carbide/nitride-like structure with its neighboring vanadium atoms, leading to the formation of the strong C/N–vanadium bonding containing a covalent component.     

竖直环形通道内液氮自然循环沸腾可视化实验研究

采用基于高速摄像手段的可视化方法研究了竖直环形通道内的液氮自然循环沸腾过程,建立了汽泡脱离直径及汽泡脱离频率的实验关联式,以新建方程结合双流体模型进行了数值计算。与实验数据的对比表明,建立的实验关联式对于液氮自然循环沸腾过程中的汽泡脱离直径及汽泡脱离频率具有很好的预测精度。     

Different effect of NiMnCo or FeNiCo on the growth of type-Ⅱa large diamonds with Ti/Cu as nitrogen getter

In order to synthesize high-quality type-Ⅱa large diamond, the selection of catalyst is very important, in addition to the nitrogen getter. In this paper, type-IIa large diamonds are grown under high pressure and high temperature(HPHT) by using the temperature gradient method(TGM), with adopting Ti/Cu as the nitrogen getter in Ni_(70)Mn_(25)Co_5(abbreviated as NiMnCo) or Fe_(55)Ni_(29)Co_(16)(abbreviated FeNiCo) catalyst. The values of nitrogen concentration(N_c) in both synthesized high-quality diamonds are less than 1 ppm, when Ti/Cu(1.6 wt%) is added in the FeNiCo or Ti/Cu(1.8 wt%) is added in the NiMnCo. The difference in solubility of nitrogen between both catalysts at HPHT is the basic reason for the different effect of Ti/Cu on eliminating nitrogen. The nitrogen-removal efficiency of Ti/Cu in the NiMnCo catalyst is less than in the FeNiCo catalyst. Additionally, a high-quality type-Ⅱa large diamond size of 5.0 mm is obtained by reducing the growth rate and keeping the nitrogen concentration of the diamond to be less than 1 ppm, when Ti/Cu(1.6 wt%) is added in the FeNiCo catalyst.     

复合支持向量机方法及其在光谱分析中的应用

SVC和SVR是支持向量机研究的两个主要问题。文章把两种建模方法相结合,先由SVC模型判别分类,后由各类的局部SVR模型进行定量分析,提出了复合支持向量机(CSVM)方法。根据71个试验小区的水稻冠层高光谱与叶片含氮量建立定量分析模型,考证了CSVM算法。基于模拟研究的思想,随机划分建模集和预测集,比例为55∶16。经过5次划分试验,复合支持向量机方法建模对叶片含氮量的预测值与凯氏定氮实际值之间的平均相关系数为0.89,平均绝对误差为0.088;而传统的支持向量机方法得到的平均相关系数为0.87,平均绝对误差为0.091。由此可见,复合支持向量机方法相对于传统的支持向量机方法预测精度有所提高。文章研究方法的提出为化学计量学定量分析研究给出了新的思路。     

南疆农田土壤全氮含量的中红外光谱反演模型

快速准确监测农田土壤全氮含量,可显著提高土壤肥力诊断与评价工作的效率。传统测定土壤全氮的方法存在耗时费力、成本高、环境污染等缺点,而基于光谱学原理的土壤全氮定量方法克服了传统测量的劣势。中红外(MIR)光谱相较于可见光-近红外(VNIR)光谱而言,具有更多的波段数和信息量,如何利用中红外光谱监测土壤全氮含量是具有重要应用前景的研究课题。为了探索中红外光谱对土壤全氮监测的可行性,以新疆南疆地区采集的246个农田土样为研究对象,以室内测定的全氮含量和中红外光谱反射率数据为数据源,分析了不同全氮含量土样的中红外光谱特征差异,以主成分分析法(PCA)和连续投影算法(SPA)对光谱数据进行降维,然后采用偏最小二乘回归(PLSR)、支持向量机(SVM)、随机森林(RF)和反向传播神经网络(BPNN)四种建模方法分别构建基于全波段和降维数据的土壤全氮含量定量反演模型。研究结果表明：(1)土壤在中红外波段光谱反射率随全氮含量的增加而增加,在3 620, 2 520, 1 620和1 420 cm^-1附近存在明显的吸收谷;将中红外光谱数据进行最大值归一化处理后,可明显提高土壤光谱反...     

Nitrogen retention in the Szczecin Lagoon,Baltic Sea

Nitrogen (N) retention and transformation in the Szczecin Lagoon, southern Baltic Sea, were studied by means of budget calculations and stable isotope data of dissolved and particulate matter. Two stations, one located at the main outlet of the lagoon (?wina Strait) and the other 100 km to the south, on the Oder River (Widuchowa), were sampled biweekly over the years 2000–2002. The Oder River is one of the five largest rivers draining into the Baltic Sea and the largest one discharging its waters into the western Baltic. According to our data, the Oder River carried approximately 60 kt y^?1 total N, of which 7 kt y^?1 (<12 %) are particulate organic nitrogen and 46 kt y^?1 (77 %) dissolved inorganic nitrogen. Seasonal patterns of particulate nitrogen and nitrate concentrations were similar at Widuchowa and ?wina Strait station, but nitrate concentrations in the ?wina Strait were much lower, pointing not only to the dilution effect but also to considerable nutrient removal capacity (especially of nitrate) in the lagoon. The loss of nitrate suggests that denitrification is the major N-removal process, whereas primary production was only a minor contributor, due to the very low particle load. Combining budget calculations with stable isotope measurements reveal unique information about nitrogen turnover processes in the lagoon.