Chemical composition and larvicidal activity of Algerian Foeniculum vulgare seed essential oil

A laboratory study was conducted to determine the effect of three extraction parameters (soaking time, extraction time and the ratio of solid to liquid) on the yield and chemical composition of Foeniculum vulgare seeds essential oils. The bioactivity of the essential oil extracted for the optimum extraction parameters was assessed against Culex pipiens mosquito. F. vulgare essential oil composition included large amounts of phenylpropanoids. Through an extraction time of 6 h and a ratio solid to liquid of 300 g/L we can get over than 72% of trans-anethol without soaking the seeds. With bioassays, essential oils showed different activities on C. pipiens larvae and pupae. Results show that a concentration at 40 mg/L was sufficient to register 50% mortality for the second instars larvae and this, after 2 h exposition time. Moreover, concentration at 60 mg/L ensured after 4 h exposition time 90% mortality for the fourth instars larvae. However, pupae needed 24 h exposition time to show promising mortalities when using concentration at 200 mg/L. Even if laboratory bioassays are only the first step towards the use of essential oils in practical applications, these substances represent a potential alternative to chemical insecticides in some markets.     

Comparative evaluation of antibacterial potentials of nano cobalt oxide with standard antimicrobials

Development of suitable potent antimicrobial is the urgent need of modern era to cope up the problem of antimicrobial resistance. The applications of nanotechnology in metal oxides have shown favorable effects to some extent in this area. Thus, the present study was investigated to evaluate the antibacterial properties of cobalt oxide (Co₃O₄) nanoparticles at different concentrations and their comparison with standard antimicrobials i.e. tetracycline and gentamicin. Nanoparticles were synthesized and characterized by standard techniques. The antibacterial potentials of Co₃O₄ nanoparticles against S. aureus and E. coli were determined at various concentrations. The maximum zone of inhibitions of Co₃O₄ nanoparticles against S. aureus and E. coli at 500 μg/ml were 21.17 mm and 24.00 mm, respectively. The Co₃O₄ nanoparticles seemed more effective than gentamicin against S. aureus and E. coli. The nanoparticles with respect to tetracycline showed higher than 1 activity index at ≥ 125 μg/ml for E. coli and ≥31.25 μg/ml for S. aureus. It was also higher than 1 at all compared concentrations with respect to gentamicin against both bacteria. In conclusion, Co₃O₄ nanoparticles seemed to have potent antibacterial potential and these might be very helpful to replace the conventional antimicrobials to solve the problem of antibacterial resistance.     

Marginal filtering in large state spaces

Recognising everyday activities including information about the context requires to handle large state spaces. The usage of wearable sensors like six degree of freedom accelerometers increases complexity even more. Common approaches are unable to maintain an accurate belief state within such complex domains. We show how marginal filtering can overcome limitations of standard particle filtering and efficiently infer the context of actions. Symbolic models of human behaviour are used to recognise activities in two different settings with different state space sizes. Based on these scenarios we compare the marginal filter to the standard particle filter. An evaluation shows that the marginal filter performs comparably in small state spaces but outperforms the particle filter in large state spaces.     

Raman Optical Activity (ROA) as a New Tool to Elucidate the Helical Structure of Poly(phenylacetylene)s

Poly(phenylacetylene)s are a family of helical polymers constituted by conjugated double bonds. Raman spectra of these polymers show a structural fingerprint of the polyene backbone which, in combination with its helical orientation, makes them good candidates to be studied by Raman optical activity (ROA). Four different well‐known poly(phenylacetylene)s adopting different scaffolds and ten different helical senses have been prepared. Raman and ROA spectra were recorded and allowed to establish ROA‐spectrum/helical‐sense relationships: a left/right‐handed orientation of the polyene backbone (M_helix/P_helix) produces a triplet of positive/negative ROA bands. Raman and ROA spectra of each polymer exhibited the same profile, and the sign of the ROA spectrum was opposite to the lowest‐energy electronic circular dichroism (ECD) band, indicating a resonance effect. Resonance ROA appears then as an indicator of the helical sense of poly(phenylacetylene)s, especially for those with an extra Cotton band in the ECD spectrum, where a wrong helical sense is assigned based on ECD, while ROA alerts of this misassignment.     

反应条件对钌基氨合成催化剂性能的影响

用氨合成催化剂性能评价装置,研究了反应温度、压力、空速和氢氮比对以活性炭为载体的钌基氨合成催化剂活性的影响。研究表明,低于400℃时,随着反应温度降低,催化剂的活性急剧降低。随着压力升高,催化剂活性增大。但钌催化剂具有较高的低压活性,适宜低压合成氨。随着空速的降低,催化剂的活性明显提高。在空速和压力一定的条件下,最佳氢氮比随反应温度而异,并且当空速较高或反应温度较低时,氢氮比的变化对催化剂活性的影响更加明显。     

一种限制周期气固两相流直接数值模拟中整体质量流率的新方法

全周期边界条件的气固两相流系统是研究气固相互作用的一个常用计算模型。为平衡周期气固系统在流向上的受力,常对系统施加平衡系统总重力的固定压力梯度,但由于数值误差的影响,这种固定压力梯度的方法会使得气固系统整体不断加速进而导致模拟失真。为了降低系统质心加速度的影响,本文先后采用了前人提出的固定整体质量流率方法和本文提出的压力梯度后验修正方法,并对两种方法的模拟结果进行了对比。     

中药复杂组效关系的变结构神经网络辨识方法

针对中药复杂组效关系的辨识问题,研究了变结构多层前馈神经网络,推导出一种新型的变结构网络学习算法,成功地应用于中药川芎药效活性预测计算.该方法从一个规模较小的网络出发,当网络无法达到预定的学习精度时,自动增加隐含层神经元个数,并在原有学习结果的基础上确定新的网络参数,自适应地确定前馈神经网络结构,可用于处理复杂化学模式信息.计算机仿真实验结果表明,该方法能有效地确定多层前馈神经网络的最佳结构,提高网络学习效率和函数逼近精度,解决复杂非线性函数映射关系准确建模问题.     

磺酰脲类除草剂的三维药效团模型

磺酰脲类除草剂是七十年代末期[1，2]开发的一类超高效除草剂，杀草谱广，用量极低．它通过抑制植物体内乙酰乳酸合成酶（ALS，acetolactatesynthase）的活性[3]，破坏支链氨基酸缬氨酸、亮氨酸和异亮氨酸的合成，造成杂草的死亡．本文从三维角度出发，利用先进的三维分子设计软件APEX（ActivityPredictionExpertSystem）－3D[4]，建立破酸豚类除草剂药效团模型（biophoremodel），辅助设计、筛选活性化合物；再由药效团构造出模拟ALS酶活性位点（activesites）的空间结构，以该模拟结构为基点，以期设计出全新结构的ALS酶抑制剂的…     

Calculating physical properties of organic compounds for environmental modeling from molecular structure

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values – that is the value of the physical and chemical constants that govern reactivity. Although empirical structure–activity relationships have been developed that allow estimation of some constants, such relationships are generally valid only within limited families of chemicals. The computer program, SPARC, uses computational algorithms based on fundamental chemical structure theory to estimate a large number of chemical reactivity parameters and physical properties for a wide range of organic molecules strictly from molecular structure. Resonance models were developed and calibrated using measured light absorption spectra, whereas electrostatic interaction models were developed using measured ionization pK_as in water. Solvation models (i.e., dispersion, induction, H-bonding, etc.) have been developed using various measured physical properties data. At the present time, SPARC’s physical property models can predict vapor pressure and heat of vaporization (as a function of temperature), boiling point (as a function of pressure), diffusion coefficient (as a function of pressure and temperature), activity coefficient, solubility, partition coefficient and chromatographic retention time as a function of solvent and temperature. This prediction capability crosses chemical family boundaries to cover a broad range of organic compounds.     

氢化硝基苯合成对氨基酚中活性炭负载铂催化剂的新制备方法研究

采用不同还原剂（甲醛、甲酸、硼氢化钾和氢气）,或于还原Pt(IV)过程中引入少量Pt/AC(AC：活性炭)催化剂“催化”氢气分子,制备了Pt/AC催化剂。其催化氢化硝基苯制对氢基酚的反应结果表明,制备催化剂时所用的还原剂对催化剂的活性影响很大,但对反应选择性影响较小。用甲醛、甲酸和硼氢化钾还原制成的催化剂的活性皆较高;以氢气还原制得的催化剂活性较差;采用“催化”氢气还原法,可大大提高Pt/AC催化剂的活性,与传统甲醛还原法相比,甲酸和“催化”氢气还原制备Pt/AC催化剂的方法较简便、有效。