OPTIMAL INVESTMENT IN THE PROTECTION OF A VULNERABLE BIOLOGICAL RESOURCE

It is assumed that the probability of destruction of a biological asset by natural hazards can be reduced through investment in protection. Specifically a model, in which the hazard rate depends on both the age of the asset and the accumulated invested protection capital, is assumed. The protection capital depreciates through time and its effectiveness in reducing the hazard rate is subject to diminishing returns. It is shown how the investment schedule to maximize the expected net present value of the asset can be determined using the methods of deterministic optimal control, with the survival probability regarded as a state variable. The optimal investment pattern involves “bang-bang-singular” control. A numerical scheme for determining jointly the optimal investment policy and the optimal harvest (or replacement) age is outlined and a numerical example involving forest fire protection is given.     

Design of an experimental procedure for energy evaluation from biomass

The rational and sustainable exploitation of nature resources is one of the priority objectives of our society. In this article a method is proposed to evaluate and exploit the energetic resources contained in different forest formations. This method is based on the use of a combustion bomb calorimeter to determine the calorific values of the different samples studied. These results were complemented with chemical analysis of the samples and with environmental and geomorphological studies of the zones were samples were taken. The results obtained during the last 3 years for the residual biomass originated from the forest formations existing in Galicia ensure the reliability and usefulness of the method that can be extended to any forest formation all over the world.     

Sparse graph certificates for mixed connectivity

We give a short proof for the Mixed Connectivity Certificate Theorem of Even, Itkis and Rajsbaum and provide an upper bound on the edge number of a certificate of local T-mixed connectivity up to k.     

森林发展系统的一个非线性半离散模型

本文建立了森林发展系统的一类非线性林龄面积结构的半离散模型 ,并讨论了半离散系统解的存在唯一性 ,给出了线性半离散系统稳定的一些充分条件     

Stable Solution of Nonlinear Age-structured Forest Evolution System

This paper studies the dynamical behavior of a class of total area dependent nonlinear age-structured forest evolution model. We give the problem of equal value for the forest system, and discuss the stable solution of system. We obtained the necessary and sufficient conditions for there exists the stable solution.     

基于突变论的林火蔓延分析

在对森林火灾进行能量和质量守恒分析的基础上,把尖点突变模型应用于森林火灾蔓延的预测,使突变理论在 森林火灾的模型中从理论上有了初步的应用。文中计算了林火发生突变时的一些分歧点,分析了林火突变的特点和变化规 律。     

THPep: A machine learning-based approach for predicting tumor homing peptides

In the present era, a major drawback of current anti-cancer drugs is the lack of satisfactory specificity towards tumor cells. Despite the presence of several therapies against cancer, tumor homing peptides are gaining importance as therapeutic agents. In this regard, the huge number of therapeutic peptides generated in recent years, demands the need to develop an effective and interpretable computational model for rapidly, effectively and automatically predicting tumor homing peptides. Therefore, a sequence-based approach referred herein as THPep has been developed to predict and analyze tumor homing peptides by using an interpretable random forest classifier in concomitant with amino acid composition, dipeptide composition and pseudo amino acid composition. An overall accuracy and Matthews correlation coefficient of 90.13% and 0.76, respectively, were achieved from the independent test set on an objective benchmark dataset. Upon comparison, it was found that THPep was superior to the existing method and holds high potential as a useful tool for predicting tumor homing peptides. For the convenience of experimental scientists, a web server for this proposed method is provided publicly at http://codes.bio/thpep/.     

TETRA通信与干扰信号智能识别技术

陆上集群无线电(Terrestrial Trunked Radio,TETRA)数字集群通信系统因其开放性易受到内外部电磁干扰。干扰信号的类型多种多样,针对不同的干扰样式,采取的抗干扰措施也各不相同,因此干扰信号的识别具有重大意义。基于此,提出了一种干扰信号智能识别技术。该技术首先对受到不同干扰后的TETRA音频数据进行特征提取,并筛选出具有分类能力的特征,其次使用决策树、支持向量机和随机森林3种分类模型对特征提取后的待测试信号进行智能分类识别。实验结果表明,使用的这3种模型能够有效判断TETRA系统中的信号是否受到干扰,以及受到何种样式的干扰,可为后续TETRA系统中的信号干扰识别提供参考。     

Measurements Of Biogenic Hydrocarbons And Their Atmospheric Degradation In Forests

Abstract

An analytical procedure for the sampling and quantitative determination of biogenic hydrocarbons in the atmosphere is presented. The method is based on the adsorptive preconcentration of the hydrocarbons using Tenax TA/Carbopack B filled sampling tubes followed by thermodesorption of the trapped compounds and gas chromatographic analysis. To avoid losses of the biogenic alkenes as a consequence of their reaction with ozone on the adsorbents during the sampling step, an ozone scrubber is used in front of the adsorption tubes. Diurnal variations of the monoterpene- and ozone-concentrations are determined at different heights in and above a forest stand (coniferous and deciduous trees) in the Vosges (Col du Donon, 760 m a.s.l.) in order to elucidate the importance of terpene-oxidation reactions on the formation of peroxidic products in forest air.