The method for designing the profile of forest roads supported by genetic algorithm

This study examines a method for designing an optimum profile of a forest road in a short matter of time. In this method, a genetic algorithm (GA) searches for points where the gradient changes and dynamic programing (DP) designs the longitudinal slope. This method can be applied to the ground heights of an actual forest road. The evaluation function of the DP assesses the total expenditure. The inverse of this function is the fitness function. Crossover and mutation are operators of an evolution simulation of a GA. They are each repeated 20 times and 420 profiles are designed and assessed, all within about 10 min. A comparison of the profile designed by the GA with that of an actual forest road shows only one section where the formation level differed substantially. Overall, both profiles seem to show a high degree of correspondence. From this result, we believe that the profile designed by the GA is best, or the one of the best. A conventional method takes about 65 h to calculate all changing points of gradients. However, by using the GA, the calculation time was reduced to about 1/389 that of the coventional method, showing that the method which uses the GA through the profile design is very useful.     

银木的光合与水分生理特性的研究

银木(Cinnamomum septentrionale Hand.Mazz.)系樟科樟属的常绿乔木,主要分布在年平均气温14℃,降水量800 mm以上的四川、陕西南部、甘肃南部、湖南等地区,是自然分布最北面的樟科植物.该树种系典型的北亚热带树种,对水、热条件的要求低于其它樟科植物,既能耐-10℃的低温,又能耐干旱[1].银木树皮灰色、光滑,叶近革质,互生,椭圆状、倒圆状披针形,具有较好的观赏性和较高的开发价值,在湖南、四川等地已人工栽培多年,形成特色鲜明的城市行道树.     

鸟类羽被防水性能的形态学基础

提出用水-羽毛接触点密度(Dp)的指标来描述鸟类廓羽表面的防水性能。29种鸟类胸部廓羽的检测表明,除了极少数物种以外,陆禽的Dp较小,涉禽和潜水鸟类的Dp居中,而游禽的Dp较大。这表明鸟类通过羽毛微观结构的变化来使羽毛具有相应水平的防水性能。因此,Dp是一个连接羽毛结构和功能的指标,对鸟类的适应性进化的研究具有重要意义。图3表1参9。     

不同种源翅荚木的抗寒性

以5个种源的翅荚木叶为材料,采用叶片离析法和石蜡制片技术观测叶片结构特征、电导率法测定其半致死温度、差示热量扫描仪测定其过冷点温度,并结合田间试验分析不同种源翅荚木苗期的抗寒性及其与叶片结构的关系.结果表明:湖南通道翅荚木种源抗寒性最强,苗期在湖南株洲无冻害,在浙江丽水冻害率为4.83%,极显著低于其他种源;其叶片半致死温度为-5.34 ℃,过冷点温度为-15.04 ℃,均低于广东翁源和广西忻城种源. 不同种源翅荚木叶片细胞结构紧密度(CTR)和疏松度(SR)与种源的抗寒性有一定的关系,CTR值越大、SR值越小,种源的抗寒性越强.     

桂林岩溶石山阴香种群的空间分布格局

通过野外调查,选取6块有代表性的样地,采用点格局分析方法研究了阴香种群的空间分布格局。结果表明,6块样地中,Q1和Q5样地阴香种群多数尺度上表现为集群分布,Q2和Q3以随机分布为主,Q4和Q6样地少数尺度上为集群分布,多数尺度上呈随机分布。阴香种群的空间分布格局与物种本身的繁殖特性、生境条件以及种内种间竞争等密切相关,由岩石的覆盖而形成的小环境对种群的分布格局类型有影响。点格局分析法较好地体现了不同尺度下阴香种群的分布格局特征。     

青檀耐荫性的初步研究

在连续３年测定比较几个不同树种的生理特性和树冠结构的基础上，本文对青檀的耐荫性进行了初步分析，结果表明，青檀的耐荫性随年龄的增大而降低，１２年生以前，青檀是耐荫的；１３至２５年生之间，青檀是喜光树种；２６年生以后青檀则逐渐变为阳性树种。比较的结果还表明，青檀的耐荫性较马尾松强，较杉木弱，从总体看属中偏阳树种。     

田间和盆栽核桃与柿子苗木光合特性的初步研究

研究了核桃(Juglans regia L.)、柿子(Diospyros kaki L.f.)两种苗木在田间和盆栽栽培条件下的光合特性。通过室内人工控制光强和CO2浓度,测得盆栽的核桃、柿子的光补偿点分别是62 μmol CO2/m2·s、40μmol CO2/ m2·s;饱和点分别是1 582 μmol CO2/m2·s、1 064 μmol CO2/m2·s;CO2补偿点分别是135 ml/L、230 ml/L。6月的晴天,核桃、柿子盆栽栽培中的净光和速率日变化呈"双峰"型;田问栽培中仅出现1次高峰。两种栽培均出现"午休"现象。     

Geographic Information System‐Based Analysis of the Spatial and Spatio‐Temporal Distribution of Zoonotic Cutaneous Leishmaniasis in Golestan Province,North‐East of Iran

Zoonotic cutaneous leishmaniasis (ZCL), a vector‐borne disease, poses serious psychological as well as social and economic burden to many rural areas of Iran. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial and spatio‐temporal clusters of the disease to better understand spatio‐temporal epidemiological aspects of ZCL in rural areas of an endemic province, located in north‐east of Iran. Cross‐sectional survey was performed on 2983 recorded cases during the period of 2010–2012 at village level throughout the study area. Global clustering methods including the average nearest‐neighbour distance, Moran's I, general G indices and Ripley's K‐function were applied to investigate the annual spatial distribution of the existing point patterns. Presence of spatial and spatio‐temporal clusters was investigated using the spatial and space–time scan statistics. For each year, semivariogram analysis and all global clustering methods indicated meaningful persistent spatial autocorrelation and highly clustered distribution of ZCL, respectively. Eight significant spatial clusters, mainly located in north and northeast of the province, and one space–time cluster, observed in northern part of the province and during the period of September 2010–November 2010, were detected. Comparison of the location of ZCL clusters with environmental conditions of the study area showed that 97.8% of cases in clusters were located at low altitudes below 725 m above sea level with predominantly arid and semi‐arid climates and poor socio‐economic conditions. The identified clusters highlight high‐risk areas requiring special plans and resources for more close monitoring and control of the disease.     

基于无人机多光谱影像和关键点检测的雪茄烟株数提取

为从无人机遥感影像中准确识别烟草,实现植株定位与计数,以雪茄烟草植株为研究对象,提出一种新的深度学习模型。区别于传统的利用检测框识别目标,本文模型利用少量的关键点学习烟草中心形态学特征,并采用轻量级的编、解码器从无人机遥感影像快速识别烟草并定位计数。首先,提出的模型针对烟草植物形态学特点,通过中心关键点标注的方法,使用高斯函数生成概率密度图,引入更多监督信息。其次,对比不同主干网络在模型中的效果,ResNet18作为主干网络时平均精度大于99.5%,精度和置信度都高于测试的其他主干网络。而MobileNetV2在CPU环境下达到运行效率最优,但平均置信度相对较低。使用损失函数Focal Loss与MSE Loss结合的Union Loss时,平均精度大于99.5%。最后,利用不同波段组合作为训练数据,对比结果发现使用红边波段更有助于模型快速收敛且能够很好地区分烟草和杂草。由于红边波段与植株冠层结构相关,使用红边、红、绿波段时平均精度达到99.6%。本文提出的深度学习模型能够准确地检测无人机遥感影像中的烟草,可为烟草的农情监测提供数据支持。