基于模拟植物生长算法构造Steiner最优树问题研究

Steiner最优树问题是指对于给定区域内的点集,通过引入Steiner点集将区域中的点连接并保证连通的网络达到最小.该问题已成为经典的优化组合问题之一.提出一种基于模拟植物生长算法生成Steiner最优树的连通算法来实现网络连通.通过对实例的实验及结果分析,结果表明本算法不仅可获得最优解,精度和性能也有提高,明显优于其它方法.     

A novel methodological approach for δ18O analysis of sugars using gas chromatography-pyrolysis-isotope ratio mass spectrometry

Although the instrumental coupling of gas chromatography-pyrolysis-isotope ratio mass spectrometry (GC-Py-IRMS) for compound-specific δ¹⁸O analysis has been commercially available for more than a decade, this method has been hardly applied so far. Here we present the first GC-Py-IRMS δ¹⁸O results for trimethylsilyl-derivatives of plant sap-relevant sugars and a polyalcohol (glucose, fructose, sucrose, raffinose and pinitol). Particularly, we focus on sucrose, which is assimilated in leaves and which is the most important transport sugar in plants and hence of utmost relevance in plant physiology and paleoclimate studies. Replication measurements of sucrose standards and concentration series indicate that the GC-Py-IRMS δ¹⁸O measurements are not stable over time and that they are amount (area) dependent. We, therefore, suggest running sample batch replication measurements in alternation with standard concentration series of reference material. This allows for carrying out (i) a drift correction, (ii) a calibration against reference material and (iii) an amount (area) correction. Tests with ¹⁸O-enriched water do not provide any evidence for oxygen isotope exchange reactions affecting sucrose and raffinose. We present the first application of GC-Py-IRMS δ¹⁸O analysis for sucrose from needle extract (soluble carbohydrate) samples. The obtained δ¹⁸O_{sucrose/ Vienna Standard Mean Ocean Water (VSMOW)} values are more positive and vary in a wider range (32.1–40.1 ‰) than the δ¹⁸O_{bulk/ VSMOW} values (24.6–27.2 ‰). Furthermore, they are shown to depend on the climate parameters maximum day temperature, relative air humidity and cloud cover. These findings suggest that δ¹⁸O_sucrose of the investigated needles very sensitively reflects the climatically controlled evaporative ¹⁸O enrichment of leaf water and thus highlights the great potential of GC-Py-IRMS δ¹⁸O_sucrose analysis for plant physiology and paleoclimate studies.     

Multielement Analytical Spectroscopy in Plant Ionomics Research

Abstract: The study of the ionome (ionomics) is defined as quantitative and simultaneous measurement of the element composition of living organisms and changes in this composition in response to physiological stimuli, development stage, and genetic modifications (Salt et al., Ann. Rev. Plant Biol., Vol. 59, 2008). The necessity of understanding the regulation processes of elements in the organisms demands determination of many elements in the organism, tissue, and cell (Baxter, Plant Biol., Vol. 12, 2009). A prospect for ionomics is environmental pollution where great variety of conditions and pollutants exist resulting in concentration and interelemental changes in the plant ionome. The capabilities of and problems with several multielement analytical techniques, including instrumental neutron activation analysis (INAA), X-ray fluorescence, inductively coupled plasma–atomic emission spectrometry (ICP-AES), inductively coupled plasma–mass spectrometry (ICP-MS), and atomic absorption spectrometry (AAS), which are adequate and most promising in ionomic and environmental studies of plants, are reviewed. References are confined mainly to the last 10–15 years. Information about concentrations, roles, binding forms, and pollution sources of the elements and comparison between methods with respect to limits of detection, determined elements, interferences, and economic considerations are tabulated. Some combinations of instrumental techniques supplementing each other are highly valued, namely, ICP-MS and ICP-AES and INAA and AAS or ICP-AES.     

An Overview of Infrared Spectroscopy Based on Continuous Wavelet Transform Combined with Machine Learning Algorithms: Application to Chinese Medicines,Plant Classification,and Cancer Diagnosis

Abstract

Infrared spectroscopy has been a workhorse technique for materials analysis and can result in positively identifying many different types of material. In recent years there have been reports using wavelet analysis and machine learning algorithms to extract features of Fourier transform infrared spectrometry (FTIR). The machine learning algorithms contain back-propagation neural network (BPNN), radial basis function neural network (RBFNN), and support vector machine (SVM). This article reviews the important advances in FTIR analysis employing a continuous wavelet transform (CWT) and machine learning algorithms, especially in the applications of the method for Chinese medicine identification, plant classification, and cancer diagnosis.     

Natural radionuclide concentrations in soils around Baoji coal-fired power plant,China

Radionuclides are released together with fly ash from the coal-fired power plant and thus add to the natural radiation. Fifty soil samples were collected around the Baoji coal-fired power plant from 25 locations and the natural radionuclide concentrations were determined by a gamma ray spectrometric system. The results show that the activity concentrations in soil samples range from 12.54 to 40.18 Bq kg^?1, 38.02 to 72.55 Bq kg^?1 and 498.02 to 1126.98 Bq kg^?1 for ²²⁶Ra, ²³²Th and ⁴⁰K with the mean values of 27.35, 52.66 and 764.72 Bq kg^?1, respectively. In order to evaluate the radiological hazard of the natural radioactivity, the radium equivalent activity (Ra_eq), the absorbed dose rate (D) and the annual effective dose rate have been calculated and compared with the internationally approved values. The radium equivalent activity in all the soil samples is lower than the safe limit set in the Organization for Economic Cooperation and Development report (370 Bq kg^?1). The average value of the calculated dose rates is higher than the global average value 55 nGy h^?1, and the calculated annual effective dose rate is significantly lower than the average annual external effective dose rate (460 μSv y^?1) of the normal background radiation.     

Phytochemical profile and biological activities of Deverra tortuosa (Desf.)DC.: a desert aromatic shrub widespread in Northern Region of Saudi Arabia

The present study describes the chemical composition of the essential oil of different plant parts of Devrra tortuosa; in vivo and in vitro biological activities of plant extract and essential oils. Apiol was found to be the major component of the oil (between 65.73% and 74.41%). The best antioxidant activities were observed for the oil of flowers (IC50 = 175 μg/ml). The samples of stems and roots exhibit lower antioxidant activity (IC50 = 201 μg/ml and 182 μg/ml, respectively). The values of IC50 showed that the extracts of methanol exhibit the highest antioxidants activities (IC50 = 64.8 102 μg/ml). EOs showed excellent antifungal activity against yeasts with low azole susceptibilities (i.e. Malassezia spp. and Candida krusei). The MIC values of oils varied between 2.85 mg/mL and 27 mg/mL. The obtained results also showed that the plant extracts inhibited the germination and the shoot and root growth of Triticum æstivum seedlings.     

Screening of medicinal plants traditionally used in Peruvian Amazon for in vitro antioxidant and anticancer potential

Plants mentioned in this study have numerous records in traditional Peruvian medicine being used in treatment of cancer and other diseases likely to be associated with oxidative stress. Amongst the eight plant species tested, only Dysphania ambrosioides exhibited combinatory antioxidant and anti-proliferative effect on a broad spectrum of cancer cells (DPPH and ORAC values = 80.6 and 687.3 μg TE/mg extract, respectively; IC₅₀ against Caco-2, HT-29 and Hep-G2 = 129.2, 69.9 and 130.6, respectively). Alkaloids and phenolic compounds might significantly contribute to anticancer/antioxidant activity of this plant. The results justify the traditional medicinal use of this plant. Our findings further suggest that D. ambrosioides might serve as a prospective material for further development of novel plant-based antioxidant and/or anti-proliferative agents. Detailed analysis of chemical composition together with toxicology assessments and in vivo antioxidant/anti-proliferative activity of this plant should be carried out in order to verify its potential practical use.     

Formulation of Environmentally Safe Graffiti Remover Containing Esterified Plant Oils and Sugar Surfactant

The removal of graffiti or over-painting requires special attention in order to not induce the surface destruction but to also address all of the important eco-compatibility concerns. Because of the necessity to avoid the use of volatile and toxic petroleum-based solvents that are common in cleaning formulations, much attention has recently been paid to the design of a variety of sustainable formulations that are based on biodegradable raw materials. In the present contribution we propose a new approach to graffiti cleaning formulations that are composed of newly synthesized green solvents such as esterified plant oils, i.e., rapeseed oil (RO), sunflower oil (SO), or used cooking oil (UCO), ethyl lactate (EL), and alkylpolyglucosides (APGs) as surfactants. Oil PEG-8 ester solvents were synthesized through the direct esterification/transesterification of these oils using monobutyltin(IV) tris(2-ethylhexanoate) and titanium(IV) butoxide catalysts under mild process conditions. The most efficient formulations, determined by optimization through the response surface methodology (RSM) was more effective in comparison to the reference solvents such as the so-called Nitro solvent (denoting a mixture of toluene and acetone) and petroleum ether. Additionally, the optimal product was found to be effective in removing graffiti from glass, metal, or sandstone surfaces under open-field conditions in the city of Wrocław. The performed studies could be an invaluable tool for developing future green formulations for graffiti removal.     

Chemical characterisation of bioactive compounds in Medicago sativa growing in the desert of Oman

Medicago sativa Linn growing in Omani desert were chemically characterised using flame photometry, inductively coupled plasma, gas chromatography–mass spectrometry and high performance liquid chromatographic (HPLC) analysis. HPLC analyses were performed to determine the phenolics and flavonoids present in M. sativa. The major compounds detected in M. sativa leaves were protchaechenic acid (3.22%), hydroxyl benzoic acid (1.05%), β-Phenyl caffate (0.97%) and kaempherol (0.89%). Pterostilbene, a cholesterol-lowering compound, was detected in M. sativa.     

Modelling of Dewatering and Desalting Processes for Large-capacity Oil Treatment Technology

This paper is devoted to analysis of oil treatment technology in the case of complex industrial process realization and further selection of technological mode. Mathematical modelling method is used to improve the efficiency of dewatering and desalting processes. The simulation system based on module modelling principle is developed. Every module is described in terms of appropriate combination of phenomena and processes. Problems of oil treatment analysis of complex structured technological scheme and searching of effective dewatering and desalting processes technological modes are solved.