Poorly crystalline iron and aluminium oxides contribute to the carbon saturation and sorption of dissolved organic carbon in the soil

Soil carbon (C) saturation implies an upper limit to a soil's capacity to store C depending on the contents of silt + clay and poorly crystalline Fe and Al oxides. We hypothesized that the poorly crystalline Fe and Al oxides in silt + clay fraction increased the C saturation and thus reduced the capacity of the soil to sorb additional C input. To test the hypothesis, we studied the sorption of dissolved organic carbon (DOC) on silt + clay fractions (<53 µm) of highly weathered oxic soils, collected from three different land uses (i.e., improved pasture, cropping and forest). Soils with high carbon saturation desorbed 38% more C than soils with low C saturation upon addition of DOC, whereas adsorption of DOC was only observed at higher concentration (>15 g kg^?1). While high Al oxide concentration significantly increased both the saturation and desorption of DOC, the high Fe oxide concentration significantly increased the desorption of DOC, supporting the proposition that both oxides have influence on the DOC sorption in soil. Our findings provide a new insight into the chemical control of stabilization and destabilization of DOC in soil.     

Osteosarcoma of the distal femur, combined with multiple bone infarcts: the case of a 10-year-old poodle

A ten-year-old female poodle was presented for left hindlimb lameness. Radiographically, irregular intramedullary densities of long bones (bone infarcts) and a lytic lesion in the left distal femur were detected. Two years after the first examination, the lesions in the distal femur were definitely identified as osteosarcoma and the dog was euthanized. Pathological and histological changes of the bone infarcts as well as of the osteosarcoma are described. Regarding bibliographical data, occurrence and aetiopathogenesis of osteosarcoma associated with multifocal bone infarction in man and dog are discussed.     

Electromyography and spinal evoked potentials in cauda equina syndrome of dogs

In order to investigate usefulness of electrodiagnostic methods in Cauda Equina-Compression, 26 dogs with this disease were subjected to electromyography and spinal evoked potentials. 16 normal dogs served as controls. It was found that--after stimulation of the Nn.tibialis, peronaeus, pudendus and coccygeales and recording at the lumbosacral junction--latencies and nerve-conduction velocities were largely normal. However the amplitudes were decreased and--depending on the severity of the compression--the morphology of the potentials was altered although considerable standard deviations were obtained. Electromyographically, increased spontaneous activity with fibrillations and positive sharp waves were found in the myotomes of the lumbosacral nerves. Their number increased according to the severity of the cauda equina compression and they had a centrifugal distribution pattern. Based on these results it appears indicated to perform an electromyographic exam before applying myelography. The technique of spinal evoked potentials will need more refinement and standardisation before being useful in a clinical situation.     

The study on site quality evaluation for dahurian larch (Larix gmelinii Rupr.)

Site quality of larch (Larix gmelinii Rupr.) in Da Xingan Mountain in Inner Mongolia was studied systematically with about 1000 temporary plots and computer software. The nature of site class and site index curve was discussed in view of general mathematical model of height growth. The height growth of dominant tree of four divisions of forest stands were studied and site index tables were constructed respectively. In order to unify the comparing standard and convenience for management in this region, site index table was constucted too. Based on discussing the action and accuracy of forest type, a series of site quality evaluation (forest type-site index class-site index) was suggested. This subject of study is supported by the National Natural Scientific Fund (No. 39270549).     

非公有制林业主体融资问题的思考

针对不同层次的个体林业,设计了民间融资、"报账制"式银行信贷等方式以求解决个体林农融资困难问题.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

基于SDAE-BP的联合收割机作业故障监测

为了解决联合收割机作业故障的非线性特征信号难以提取的问题,该研究提出了一种基于堆叠去噪自动编码器(Stack Denoising Auto Encoder, SDAE)和BP神经网络(Back Propagation,BP)融合的联合收割机作业故障监测及诊断的方法(SDAE-BP)。以转速传感器采集联合收割机脱粒滚筒转速、籽粒搅龙转速、喂入搅龙转速、杂余搅龙转速、风机转速、输送链耙转速、割刀频率以及逐稿器振动频率,并将采集的数据集作为系统的输入。利用SDAE提取输入信号的深层次特征,并由BP神经网络辨识收割机作业状态,实现联合收割机故障监测。在SDAE-BP模型训练过程中,去噪自动编码器(Denoising Auto Encode, DAE)依次经带有不同分布中心噪声的原始数据进行训练,然后将其堆叠,并通过误差反向传播算法对模型参数进行优化,以提升模型识别故障性能和泛化能力。试验结果表明,对于2018年联合收割机田间试验数据,模型的故障诊断准确率达到99.00%,与SDAE和BP神经网络相比,分别提高了1.5和4.5个百分点。将SDAE-BP故障诊断模型用2019年的试验数据进行更新,并用2018年和2019年试验数据进行测试,结果表明,更新后的模型对2018年试验数据的故障识别准确率为99.25%,对2019年试验数据的故障识别准确率为98.74%,更新后模型在2019试验数据集上的故障识别准确率较未更新模型提高了6.52个百分点。该文所建模型能够准确识别联合收割机的故障类型,且具有较好的鲁棒性,对旋转型机械故障监测及预警具有参考价值。