A New Active Contour Medical Image Segmentation Method Based on Fractional Varying-Order Differential

Image segmentation technology is dedicated to the segmentation of intensity inhomogeneous at present. In this paper, we propose a new method that incorporates fractional varying-order differential and local fitting energy to construct a new variational level set active contour model. The energy functions in this paper mainly include three parts: the local term, the regular term and the penalty term. The local term combined with fractional varying-order differential can obtain more details of the image. The regular term is used to regularize the image contour length. The penalty term is used to keep the evolution curve smooth. True positive (TP) rate, false positive (FP) rate, precision (P) rate, Jaccard similarity coefficient (JSC), and Dice similarity coefficient (DSC) are employed as the comparative measures for the segmentation results. Experimental results for both synthetic and real images show that our method has more accurate segmentation results than other models, and it is robust to intensity inhomogeneous or noises.

Genome survey sequencing and characterization of simple sequence repeat (SSR) markers in Platostoma palustre (Blume) A.J.Paton (Chinese mesona)

Platostoma palustre (Blume) A.J.Paton is an annual herbaceous persistent plant of the Labiatae family. However, there is a lack of genomic data for this plant, which severely restricts its genetic improvement. In this study, we performed genome survey sequencing of P. palustre and developed simple sequence repeat (SSR) markers based on the resulting sequence. K-mer analysis revealed that the assembled genome size was approximately 1.21 Gb. A total of 15,498 SSR motifs were identified and characterized in this study; among them, dinucleotide, and hexanucleotide repeats had the highest and lowest, respectively. Among the dinucleotide repeat motifs, AT/TA repeat motifs were the most abundant, and GC/CG repeat motifs were rather rare, accounting for 44.28% and 0.63%, respectively. Genetic similarity coefficient analysis by the UPMGA methods clustered 12 clones, of P. palustre and related species into two subgroups. These results provide helpful information for further research on P. palustre resources and variety improvements.

Automatic Pancreatic Cyst Lesion Segmentation on EUS Images Using a Deep-Learning Approach

The automatic segmentation of the pancreatic cyst lesion (PCL) is essential for the automated diagnosis of pancreatic cyst lesions on endoscopic ultrasonography (EUS) images. In this study, we proposed a deep-learning approach for PCL segmentation on EUS images. We employed the Attention U-Net model for automatic PCL segmentation. The Attention U-Net was compared with the Basic U-Net, Residual U-Net, and U-Net++ models. The Attention U-Net showed a better dice similarity coefficient (DSC) and intersection over union (IoU) scores than the other models on the internal test. Although the Basic U-Net showed a higher DSC and IoU scores on the external test than the Attention U-Net, there was no statistically significant difference. On the internal test of the cross-over study, the Attention U-Net showed the highest DSC and IoU scores. However, there was no significant difference between the Attention U-Net and Residual U-Net or between the Attention U-Net and U-Net++. On the external test of the cross-over study, all models showed no significant difference from each other. To the best of our knowledge, this is the first study implementing segmentation of PCL on EUS images using a deep-learning approach. Our experimental results show that a deep-learning approach can be applied successfully for PCL segmentation on EUS images.

Preventive maintenance planning considering machines’ reliability using group technology

PurposeThe purpose of this paper is to develop an efficient and effective preventive maintenance (PM) plan that considers machines’ maintenance needs in addition to their reliability factor.Design/methodology/approachSimilarity coefficient method in group technology (GT) philosophy is used. Machines’ reliability factor is considered to develop virtual machine cells based on their need for maintenance according to the type of failures they encounter.FindingsUsing similarity coefficient method in GT philosophy for PM planning results in grouping machines based on their common failures and maintenance needs. Using machines' reliability factor makes the plan more efficient since machines will be maintained at the same time intervals and when their maintenance is due. This helps to schedule a standard and efficient maintenance process where maintenance material, tools and labor are scheduled accordingly.Practical implicationsThe proposed procedure will assist maintenance managers in developing an efficient and effective PM plans. These maintenance plans provide better inventory management for the maintenance materials and tools needed using the developed virtual machine cells.Originality/valueThis paper presents a new procedure to implement PM using the similarity coefficient method in GT. A new similarity coefficient equation that considers machines reliability is developed. Also a clustering algorithm that calculates the similarity between machine groups and form virtual machine cells is developed. A numerical example adopted from the literature is solved to demonstrate the proposed heuristic method.

Brain Tumor Segmentation Based on Deep Learning’s Feature Representation

Brain tumor is considered as one of the most serious causes of death in the world. Thus, it is very important to detect it as early as possible. In order to predict and segment the tumor, many approaches have been proposed. However, they suffer from different problems such as the necessity of the intervention of a specialist, the long required run-time and the choice of the appropriate feature extractor. To address these issues, we proposed an approach based on convolution neural network architecture aiming at predicting and segmenting simultaneously a cerebral tumor. The proposal was divided into two phases. Firstly, aiming at avoiding the use of the labeled image that implies a subject intervention of the specialist, we used a simple binary annotation that reflects the existence of the tumor or not. Secondly, the prepared image data were fed into our deep learning model in which the final classification was obtained; if the classification indicated the existence of the tumor, the brain tumor was segmented based on the feature representations generated by the convolutional neural network architectures. The proposed method was trained on the BraTS 2017 dataset with different types of gliomas. The achieved results show the performance of the proposed approach in terms of accuracy, precision, recall and Dice similarity coefficient. Our model showed an accuracy of 91% in tumor classification and a Dice similarity coefficient of 82.35% in tumor segmentation.

SSR based molecular profiling of elite cultivars of basmati rice (Oryza sativa L.)

The experiment was conducted to assess the available genetic variability amongst Indian Basmati rice and identify co-dominant and reproducible robust simple sequence repeat markers for drought resistance and their utilization in marker assisted selection for developing drought resistant / tolerant aromatic rice cultivars in various parts of India as well as in world. DNA was isolated from fresh and young leaf tissues of 35 cultivars of basmati rice using the CTAB procedure of Doyle and Doyle with slightly modifications. The DNA was further quantified by spectrophotometer at 260 nm and 280 nm. The quality and quantity of DNA were checked by agarose gel electrophoresis. Out of 60 SSR markers, 18 were found to be polymorphic and the rest 42 primers were monomorphic. One of the main purposes of SSR markers in genomic study is the characterization of genetic resources to help gene bank management. The informative (18) SSR markers were capable to discriminate the entire cultivars of basmati rice used in this research work. A total of 52 alleles at 18 loci could be scored. The allelic richness per locus diversified from 2 to 5 with an average of 2.89 alleles per locus. The amplitude of Polymorphism Information Content (PIC) value is 0.066 (RM 1068) to 0.730 (RM 1059) with an average of 0.505. The Jaccard’s similarity coefficient ranged from 0.79 to 0.95. Polymorphic finding content showed a positive correlation (r =0.69) with number of alleles at the SSR locus. However it is recommended that SSR markers can be efficiently utilized for this purpose. The maximum similarity coefficient was observed between Jeerakasab and Kalanamak with a coefficient value of 95% and the minimum similarity was found between Jeerakasab and Pusa basmati-1 with a coefficient value of 79%.

TYPOLOGICAL, TECHNICAL AND TECHNOLOGICAL CHARACTERISTICS OF THE EARLY VOLOSOVO CERAMICS IN THE MARI VOLGA REGION

В статье представлены новые результаты изучения керамики волосовской культуры территории Среднего Поволжья. В ходе обобщающего исследования было выявлено, что в ранней волосовской керамике преобладают прямые и утолщенные венчики. Преимущественно прямая профилировка сосудов. Высок процент орнаментированной посуды, общая схема орнаментации горизонтальная и вертикальная. В качестве элемента орнамента превалируют оттиски гребенчатого штампа. При подсчете коэффициента сходства 9 рассмотренных в работе памятников, относящихся к ранней волосовской культуре, было выявлено, что наиболее высокие коэффициенты сходства получены при подсчете по формам венчиков и элементам орнамента. По результатам технико-технологического анализа также выражена стандартизация рассматриваемых материалов. The paper presents new results of study of ceramics from the Volosovo culture sites located in the Middle Volga region which is important for research of the Volosovo culture. This synthesis-oriented research has found that straight and thick rims predominate among the early Volosovo ceramics. Vessel profiling is predominantly straight. The ornamented vessels account for a large percentage share of the found vessels, the decoration pattern is organized horizontally and vertically. The comb stamp imprints predominate as a decorative element. The calculations of the similarity coefficient for nine sites attributed to the Early Volosovo culture demonstrate that the highest similarity coefficients have been obtained for rim shapes and decorative pattern elements. The results of the technical and technological analysis also demonstrate standardization of the analyzed materials.

GENETIC DIVERSITY EEL Anguilla marmorata BY RAPD IN THUA THIEN HUE PROVINCE, VIETNAM

Anguilla marmorata is a species with high economic value and increasingly interested by organizations and scientists. So far, many of the eel's biological characteristics remain mysterious, and they are often classified according to morphological features such as pigmentation patches, number of vertebrae, ... It is even difficult to distinguish one individual from another in some species, especially in the larval stage. In this study, the Random amplification of polymorphic DNA (RAPD) molecular marker was used to evaluate the genetic diversity of 48 eels collected in Thua Thien Hue province. Results showed that the genetic diversity of individuals in the Eel population studied is quite high. With 8 random primers via PCR, 77 DNA tapes with 76 polymorphic tapes were obtained, the tape size ranged from 170-2,500 bp, in which primer S10 showed the highest diversity with an average Ho value of 0.563, followed by primer S8 (Ho = 0.558). The lowest diversity was in the OPD5 primer (Ho = 0.300). The OPG17 primer is the primer that produces the most polymorphic tapes (13/13 tapes) and the S3 primer for the least amplified tapes polymorphism (9/10 DNA tapes). The diversity coefficient in each random primer ranged from about 0.300 to 0.563, with an average of 0.433. The genetic variation in the Eel population is random. Genetic variation can be attributed mainly to different eel breeding conditions and origins. Genetic similarity coefficients among the Eels varied from 0.660 to 0.910 and were divided into two main groups in genetic similarity coefficient 0.660.

Analysis of Genetic Diversity of Myrtle (Myrtus Communis L.) by Using SSR Technique

This research carried out to compare some of the individuals of Myrtle from bushes in different environmental sites (Lattakia, Safita, Qusul Maaf, northern Aleppo and at different altitudes from the sea surface). The genetic diversity of 19 genotypes was tested using simple sequence repeats (SSRs) technique with 10 primers. The results of DNA extraction showed a high molecular size fragment as a band at the top of each lane, additionally to a partial degradation. At the end DNA concentration, integrity and purity were enough for SSR marker. Genetic variations were detected by SSR marker with similarity coefficient ranged between 0.08 – 0.89 based on Dice coefficient. Total of 27 alleles were scored from 19 genotypes, and the number of alleles was ranged between 2 (myrcom8 and 9) and 4 (myrcom2 and 6). The calculated value of polymorphism information content (PIC) was ≤ 0.5. Nineteen genotypes were distributed on three main clusters, two of them II and III included minimum number of genotypes from humid climate sites, while the majority of genotypes was distributed on cluster I in mixed manner.

Morphological characterization of natural orchids Dendrobium spp.

Dendrobium is characterized by long pseudobulbs or canes with soft leaves over the entire length, or in some species short or swollen pseudobulbs with two leathery leaves. The inflorescence is composed from dozens of flowers of different sizes and colors. This study aimed to identify the quantitative morphological character of five species of Dendrobium spp. namely D. mirbelianum, D. lamellatum from Java, D. anosmum from South Kalimantan, D. bracteosum from Papua, and D. purpureum from North Sumatera. The resulted dendrogram based on the similarity matrix were divided into two clusters, among the five species the value of similarity coefficient is 1.50. The first cluster is only composed from D. mirbelianum, the second cluster is D. lamellatum, D. purpureum, D. bracteosum, and D. anosmum which have more distant relationship with the other three orchids. Moreover, D. lamellatum and D. purpureum have the closest similarity coefficient with 0.81 value, which have bigger chance to use as the parents for hybridization. There are many Dendrobiums spp. distribution which based on the relationship area. In addition to quantitative properties, it also needs to be expanded to qualitative, anatomy, cytology, and also molecular characteristic to have more comprehensive data.