Effect of flaxseed root performance on the structural quality of a Haplumbrept under conservationist management system, in Santa Catarina, Brazil

Our goal was to evaluate the root development of flaxseed and its relationship with soil aggregation and organic carbon storage in two sowing seasons under soil conservationist management, in Santa Catarina state, Brazil. We used three flaxseed genotypes: Aguará and Caburé from Argentina, and Gold from Brazil, sowings in April and May in a no-tillage system under Haplumbrept. In the flowering stage, the root system was evaluated by image analyze using a Safira software. Root distribution maps were used by geostatistical kriging. At the harvest stage, soil blocks were sampled for analyze the aggregates morphometry by image with Quantporo software and the soil organic carbon. Undisturbed soil were sampled to determine the physical attributes. The experimental design was in randomized blocks with three repetitions, anova was performed by Fisher and the means compared by Tukey test. No physical impediments were found for the roots performance in the Haplumbrept under conservationist management system, these favored the irregularity of the aggregates surface observed by the low values of aspect and roughness in the different tested diameter ranges. Both Caburé and Aguará genotypes showed good roots spatial distribution in the soil profile in both sowing seasons with an increase in carbon storage in the smallest diameter aggregates (here considered the aggregates of 4.76-1 mm). Caburé genotype is the best genotype adapted to the edaphoclimatic conditions evaluated because had a greater roots volume, area and length below to 0.15 m depth.

ART THERAPY SEBAGAI ART-BASED ASSESSMENT PADA ANAK OPPOSITIONAL DEFIANT DISORDER (ODD) DI PANTI ASUHAN X DAN Y

<p><em>This study uses art therapy as an art-based assessment in children with </em>ODD<em> in orphanages. Art therapy is one form of therapy that also has an assessment function, especially as a projection test tool. Art therapy can be used as an assessment tools by using art media called art based assessment. The purpose of this study to determine the characteristics of children with </em>ODD<em> in orphanages through the use of art therapy as an art based assessment. The image analyze is based on colors, themes, styles of expression and composition. The study was conducted in August</em> – <em>November 2017. The results showed that five subjects used dominant colors is hot color and dark; theme a form of aggression; style of expression in drawing is well-controlled line but disorganized; and the combination of many images in middle position. Art therapy as an art-based assessment in this study is reliable because its accordance with the principle of reability such as repetitions theme, repetitions forms, and repetitions color. There is a matching result with the final diagnosis of children with </em>ODD<em>. Art-based assessment can be used as a consideration for assessing children with </em>ODD<em> to determine the appropriate treatment in children.</em></p><p><em> </em></p><p><strong><em>Keywords: </em></strong><em>Art </em><em>T</em><em>herapy, </em><em>A</em><em>rt </em><em>B</em><em>ased </em><em>A</em><em>ssessment, </em>ODD<em>, </em><em>O</em><em>rphanage<strong></strong></em></p><p><em> </em></p>

Multi-Scale Deep Neural Network for Mitosis Detection in Breast Cancer Histological Images

Accurate assessment of the breast cancer deterioration degree plays a crucial role in making medical plan, and the important basis for degree assessment is the number of mitoses in a given area of the pathological image. We utilized deep multi-scale fused fully convolutional neural network (MFF-CNN) combing with conditional random felid (CRF) to detect mitoses in hematoxylin and eosin stained histology image. Analyze the characteristics of mitotic detection ----scale invariance and sparsity, as well as the difficulties ---- small amount of data , inconsistent image staining and sample class unbalanced. Based on this, mitotic detection model is designed. In this paper, a tissue-based staining equalization method is used, and to establish an effective training sample set, we select training samples by using CNN. A mitotic detection model fusing multi-level and multi-scale features and context information was designed, and the corresponding training strategy was made to reduce over-fitting. As preliminarily validated on the public 2014 ICPR MITOSIS data, our method achieves a better performance in term of detection accuracy than ever recorded for this dataset.

Research on Recognition Method of Handwritten Numerals Segmentation Based on B-P Neural Network

We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characters binary image; analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning , character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.