Tree Research Articles

Living Donor-Recipient Pair Matching for Liver Transplant via Ternary Tree Representation With Cascade Incremental Learning.

Visual understanding of liver vessels anatomy between the living donor-recipient (LDR) pair can assist surgeons to optimize transplant planning by avoiding non-targeted arteries which can cause severe complications. We propose to visually analyze the anatomical variants of the liver vessels anatomy to maximize similarity for finding a suitable Living Donor-Recipient (LDR) pair. Liver vessels are segmented from computed tomography angiography (CTA) volumes by employing a cascade incremental learning (CIL) model. Our CIL architecture is able to find optimal solutions, which we use to update the model with liver vessel CTA images. A novel ternary tree based algorithm is proposed to map all the possible liver vessel variants into their respective tree topologies. The tree topologies of the recipient's and donor's liver vessels are then used for an appropriate matching. The proposed algorithm utilizes a set of defined vessel tree variants which are updated to maintain the maximum matching options by leveraging the accurate segmentation results of the vessels derived from the incremental learning ability of the CIL. We introduce a novel concept of in-order digital string based comparison to match the geometry of two anatomically varied trees. Experiments through visual illustrations and quantitative analysis demonstrated the effectiveness of our approach compared to state-of-the-art.

Regions of Force: Peirce, Frege, Carroll, and Bilateral Proof Trees

Regions of Force: Peirce, Frege, Carroll, and Bilateral Proof Trees

Tree representations of the quiver $\widetilde{\mathbb{E}}_{6}$

We explicitly describe tree representations of the canonically oriented quiver $\widetilde {\mathbb {E}}_{6}$. Recall that tree representations can be exhibited using matrices involving only the elements $0$ and $1$ and the total number of ones is exactly

Fast Generation of Unlabelled Free Trees using Weight Sequences

In this paper, we introduce a new representation for ordered trees, the weight sequence representation. We then use this to construct new representations for both rooted trees and free trees, namely the canonical weight sequence representation. We construct algorithms for generating the weight sequence representations for all rooted and free trees of order $n$, and then add a number of modifications to improve the efficiency of the algorithms. Python implementations of the algorithms incorporate further improvements by using generators to avoid having to store the long lists of trees returned by the recursive calls, as well as caching the lists for rooted trees of small order, thereby eliminating many of the recursive calls. We further show how the algorithm can be modified to generate adjacency list and adjacency matrix representations for free trees. We compared the runtimes of our Python implementation for generating free trees with the Python implementation of the well-known WROM algorithm taken from NetworkX. The implementation of our algorithm is over four times as fast as the implementation of the WROM algorithm. The runtimes for generating adjacency lists and matrices are somewhat longer than those for weight sequences, but are still over four times as fast as the corresponding implementations of the WROM algorithm.

Developing An Expert System Framework for Supporting Diagnosis and Treatment of Dyspepsia and Gastric Cancer Disease Using Local Language

Dyspepsia is a pain of the upper abdominal and it has the problem of impaired digestion like abdominal disease or other abdominal disease, which has the symptoms of heartburn, nausea, and belching, upper abdominal fullness [1]. It also related to the problem of indigestion for a group of symptoms that cause pain in the abdomen, which affects at least 25% of the world population every year [2]. From related disease of dyspepsia, Gastric cancer is the stomach cancer that develops from the lining of the stomach that affects the cell of digestive system and it is the third leading cause of death worldwide [3]. Both dyspepsia and gastric cancer is diseases that affect gastrointestinal part of human body. Therefore, this type of disease requires timely diagnosis and treatment; otherwise it can cause death and other chronic diseases. In developing countries like Ethiopia, treatment option for dyspepsia and gastric cancer is not readily available which support medical professional and also there is a scarcity of medical professional, to address such medical problems a medical expert system can play a significant role, consequently, the main objective of this research study is to develop an expert system framework for supporting diagnosis and treatment of dyspepsia and gastric cancer using local language (Amharic language). To develop this medical expert system, knowledge was acquired using both structured and unstructured interview from domain expert which are selected using purposive sampling techniques from Arba Minch General Hospital, and from document analysis. Domain knowledge is modeled using decision tree and rule-based knowledge representation was used. This medical expert system is developed by using backward chaining to infer the rule and provide an appropriate diagnosis. Finally, the performance of the system was evaluated by preparing 15 test cases by provided to domain experts and for user acceptance test, users evaluate the system through nine criteria prepared by the researcher and the system has scored 80% system performance and 85.2% user acceptance this result shows that the study has a promising result that achieves the objective of the study. The researchers recommended that to apply data mining techniques and to extract the hidden knowledge. Keywords : Expert System, Dyspepsia and Gastric Cancer, Diagnosis, and Treatment. DOI: 10.7176/CEIS/12-1-03 Publication date: January 31 st 2021

A New Approach to Operating with Undirected Trees

A new approach has been developed and practically implemented in the created software package. It ensures the implementation, on undirected trees, of a wide set of basic operations that allows replenishment. The approach does not require the development and use of available types of formalized representation of trees (matrices of adjacency, connectivity, incidence, distance, adjacency lists, etc.), standardized description languages, and specialized programs for constructing and visualization tools for their structure. By reducing the cost of technical resources and time when solving problems from various fields of knowledge by dozens (and hundreds) of times, the approach makes the work as simple and effective as possible, allows us to obtain a number of characteristics that are important in practical terms, to solve the problem of tree isomorphism, and to generate two options of representing the adjacency matrix.

Evaluation of classification performances of minimum spanning trees by 13 different metrics

Minimum Spanning Tree (MST) is a well-known clustering algorithm that provides a graphical tree representation of the objects in a data set by exploiting local information to link each pair of similar objects. The a-posteriori analysis of this tree in terms of nodes and edges provides the basis to derive simple classifiers, namely semi-supervised classification approaches based on the minimum spanning tree approach. In this work, we propose different metrics to evaluate the MST ability to group objects of the same a-priori known classes. The classification capability of the proposed approach, using 13 different distance measures, was compared with that of classical supervised classification approaches such as N-Nearest Neighbour (N3), Binned Nearest Neighbour (BNN), Partial Least SquaresDiscriminant Analysis (PLS-DA), K-Nearest Neighbour (KNN), exponentially weighted K-Nearest Neighbour (wKNN) and Support Vector Machine with radial functions (SVMRBF) on 31 data sets. The proposed approach resulted to be competitive and comparable with the considered classical supervised classification methods. Finally, we analysed the role of the 13 different measures in terms of performance and percentage of not-assigned objects.

Neural Network-Based Tree Translation for Knowledge Base Construction

Knowledge bases (KB), such as Probase and ConceptNet, play an important role in many natural language processing tasks. Compared with resource-poor languages such as Chinese, the scale and quality of English knowledge bases are obviously superior. To expand Chinese KBs by using English KB resources, translating English KBs into Chinese is an effective way. In this direction, two major challenges are how to model more structure semantics to improve translation quality and how to avoid labor-intensive feature engineering. We address these challenges by presenting a neural network approach, which learns tree representation by different structure features. We also build a new dataset for English-Chinese KB translation from Probase and ConceptNet, and compare our proposed approach with several baselines on it. Experimental results show that the proposed method improves the translation accuracy compared with baseline methods. Meanwhile, we translate Probase and ConceptNet into Zh-Probase and Zh-ConceptNet by our proposed model, and release them to the public, in hope of speeding up the research in Chinese natural language processing tasks.

A Succinct Novel Searching Algorithm

A searching algorithm was found to be effective in producing acutely needed results in the operation of data structures. Searching is being performed as a common operation unlike other operations in various formats of algorithms. The binary and linear search book a room in most of the searching techniques. Going with each technique has its inbuilt limitations and explorations. The versatile approach of different techniques which is in practice helps in bringing out the hybrid search techniques around it. For any tree representation, the sorted order is expected to achieve the best performance. This paper exhibits the new technique named the biform tree approach for producing the sorted order of elements and to perform efficient searching.

Value chain analysis of farm grown Melia volkensii (Gurke) timber in the South Eastern Dry lands of Kenya

This paper analyzes the value chain of Melia volkensii timber grown on farms in the South Eastern dry lands of Kenya. The “filiere” approach was used to analyze the institutional and the economic dimensions of the chain, while technical dimensions were analyzed using on-farm timber sawing systems. Six main actors; tree farmers, timber merchants, sawyers, timber yard operators, furniture makers, and end consumers were mapped. Transporters, though temporary, played intermediary roles of facilitating the linkages. A variety of combinations determined costs and gains along the chain. Some actors circumvented some links to increase revenue. Quality of trees and sawn timber were key determinants of monetary value transacted along the chain. Inadequate farmers’ skills in tree silviculture, valuation and cumbersome procedures in obtaining Government permits were also mentioned as major challenges, while timber sawyers lacked efficient sawing technology, consequently lowering income along the entire value chain. To improve the value chain, there is need to address the identified challenges through enhancing information and technology transfer to the players among other interventions. Key words: Farm grown timber value chains, Melia volkensii, “filiere” approach, chainsaw.

Modifications induced in soil physicochemical properties by repeated fire for different fuel load treatment in a West African savanna-woodland

Fire is known to stimulate growth of savanna vegetation, promote species’ diversity, and regulate tree and grass balance. However, the timing and frequency at which savannas are burned and the fuel properties can affect residual soil nutrient content and, ultimately, productivity. The objective of this study is to characterize changes in soil physical and chemical properties in a savanna-woodland subject to different fuel load treatments of burning. To characterize the soil physical and chemical variables, particle size distribution, total carbon, pH, phosphorous content and nitrogen were analyzed for three different soil layers. The results indicated no difference in soil texture between the different topsoil profiles before and after the burning event. Further, there was greater nutrient enrichment of the upper soil layer (p=0.014) due to ash deposition. The spatial patterns of soil temperature during the studied experimental fires could affect soil properties, resulting in new spatial pattern of soil nutrients. The findings of the present study have practical implications for savanna management. The current implementation of prescribed early fires should be continued with due consideration of the burning and fuel properties to avoid detrimental effects of intense fire on soil layers. Key words: Early fire, fire behavior, fire temperature, soil properties, Savanna ecosystem.

“Minus Stroke-operation” and its Declarative Aspects

The article considers the capacities of “Minus stroke-operation”, which was introduced as the inverse of “stroke-operation” (dereferencing a pointer).Addressing higher ranks Address Programming is based on “stroke-operation” and, in contrast to the dereference (or indirection) operator, allows you to specify the rank of addressing, which can be both an integer value or an expression of integer type. The paper gives an example of using a “stroke-operation” to obtain the address of an arbitrary element of a linear single-linked list by its sequence number. The dereference operator of modern programming languages does not allow to make it and demands implementation with use of a cycle.“Minus stroke operation” operation is not used in imperative high-level programming languages, be- cause it belongs to the declarative paradigm of programming.Address programming language has the dynamic types of data, which are based on “minus stroke-operation”.This article provides some specific examples of the use of “minus stroke-operation” in the Address Programming language and compares the capabilities of this operation with some modern declarativeprogramming tools. From the above examples it follows the universal power of “minus stroke-operation” as a tool of declarative programming.The paper presents an example of tree representation using “minus stroke-operation”. In Address Programming, you can represent trees by defining only the vertex parents. The result of applying to the address of the node “minus the stroke-operation” is a set of sons of this node. An example of a tree representation in the Address Programming Language with parent-only indication is given.The Address Programming Language is multi-conceptual and combines the concepts of imperative and declarative programming. The basis of the declarative concept of Address Programming (1955) is “minus stroke-operation”.Manuscript received 11.06.2020

نقش مدیریت سود در شناسایی صورتهای مالی متقلبانه در شرکتهای پذیرفتهشده در بورس اوراق بهادار تهران

هدف: ارائۀ گزارش‌های سالانه منبع باارزشی برای سرمایه‌گذاران، اعتباردهندگان و سایر استفاده‌کنندگان اطلاعات حسابداری است؛ با این حال، بخشی از گزارش‌ها به دلایل مختلف به‌صورت واقعی ارائه نشده است و این موضوع سبب کاهش سودمندی گزارش‌ها می‌شود. مسئلۀ مهم در حسابداری، پیش‎‌بینی و کشف صورت‌های مالی متقلبانه است. روش: این پژوهش برای کمک به شناسایی این صورت‌های مالی، رابطۀ مدیریت سود و صورت‌های مالی متقلبانه را در شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران بررسی کرده است. برای سنجش توانایی الگو‌های مدیریت سود در شناسایی صورت‌های مالی متقلبانه، داده‌های 1303 سال – شرکت (شامل 21 شرکت متقلب و 168 شرکت غیرمتقلب) طی سال‌های 1388 تا 1394 انتخاب و تجزیه و تحلیل با استفاده از روش‌های داده‌کاوی شامل درخت تصمیم، شبکه‌های عصبی و روش بیزین انجام شده است؛ بدین منظور 7 معیار مشهور مدیریت سود استفاده‌شده در پژوهش‌های قبلی بررسی شده است. نتایج: نتایج پژوهش نشان می‌دهد از بین الگو‌های پژوهش، الگوی درخت تصمیم و از بین الگو‌های اقلام تعهدی، الگوی اقلام تعهدی تعدیل‌شدۀ جونز1 (1991) با نسبت ارزش دفتری، بیشترین ارتباط را با صورت‌های مالی متقلبانه دارد.

A New Record of Epicoccum draconis Isolated from the Soil in Korea

A fungal isolate US-18-11 was isolated from the soil in Uiseong, Korea. The mycelium growth measured after 7 days of incubation at 22℃ on malt extract agar (MEA) and oatmeal agar (OA) media was 42-43 mm and 41-44 mm in diameter, respectively. The fungal colony formed white to dull green aerial mycelia that were floccose with regular margins and olivaceous black with leaden gray patches on the reverse side. The conidia were hyaline to brown in color, ellipsoidal to ovoid, guttulate, abundant, globose, solitary, or confluent measuring 3.2-7.2×1.1-2.3 μm. A BLAST search of the large subunit (LSU), internal transcribed spacer (ITS) region, second largest subunit of DNA-directed RNA polymerase II (RPB2) and β-tubulin (TUB2) gene sequences revealed that the isolate US-18-11 has similarities of 99, 100, 97, and 99% with those of Epicoccum draconis CBS 186.83, respectively. A neighbor-joining phylogenetic tree constructed based on the concatenated dataset of above-mentioned sequences showed that isolate US-18-11 clustered with Epicoccum draconis CBS 186.83 in the same clade. Based on the results of morphological, cultural, and phylogenetic analysis, the isolate US-18-11 was identical to the previously described E. draconis CBS 186.83. To our knowledge, this is the first report of E. draconis in Korea.

Estructura y carbono específico en una cronosecuencia de sistemas agroforestales de Teobroma cacao L. en Tabasco, México

Ante el impacto que representa el cambio de uso de suelo en la pérdida de biodiversidad y deterioro del medio ambiente, los sistemas agroforestales de cacao de sombra son una alternativa para la conservación de biodiversidad y almacén de carbono. El objetivo de este trabajo fue conocer el efecto de la edad de los sistemas agroforestales de cacao en la diversidad arbórea y almacenes de carbono de su vegetación de sombra. Se compararon 258 parcelas distribuidas en once sistemas agroforestales entre 10 años y 70 años, totalizando 7.87 ha. Dentro de cada parcela se midió el diámetro normal (DN) y altura total de todos los árboles >5 cm (DN) para estimar su biomasa aérea con una ecuación general y otra específica, y conocer la discrepancia de ambos métodos. Los sistemas agroforestales de 70 años presentaron en promedio más especies arbóreas por hectárea (23), índice de diversidad Shannon (2.0) y almacén de carbono (75 Mg ha-1) que los de 10 años (p < 0.01; 10 Mg ha-1, 1.1 Mg ha-1 y 36 Mg ha-1; respectivamente). La ecuación alométrica específica estimó 27.7% (p = 0.05) más biomasa aérea que la ecuación general, por lo que se considera de mayor precisión para estos sistemas agroforestales en particular, y se recomienda su uso para estos tipos de vegetación. Se concluye que, particularmente para México, conservar sistemas agroforestales de cacao de edad madura contribuye a la conservación de la biodiversidad arbórea y almacenes de carbono de la vegetación tropical, asemejando relictos de la vegetación original.

Parámetros genéticos de caracteres de crecimiento en un ensayo de progenies de Pinus oocarpa

Pinus oocarpa Schiede ex Schltdl. es una de las especies forestales en México de mayor importancia ecológica (por su amplia distribución geográfica) y económica (por la extracción de su resina en poblaciones naturales). Una resinación más intensiva requerirá de plantaciones comerciales, que podrían ser multipropósito: resina y madera. El objetivo del presente trabajo fue conocer el control genético (heredabilidad) de caracteres de crecimiento (altura total, ALT), diámetro a la base del tallo (DIAM) y diámetro a la altura del pecho (DAP), de progenies de medios hermanos de árboles originalmente seleccionados para producción de resina. Esto con la finalidad de valorar la factibilidad de un programa de mejoramiento genético multipropósito. Se estableció un ensayo de progenies en el año 2011 en Michoacán, México con 27 familias de medios hermanos en un diseño de 10 bloques completos al azar. A los cinco años después de la plantación, los promedios fueron ALT = 5.5 m, DIAM = 13.4 cm y DAP = 10.4 cm. Hubo diferencias significativas entre familias para todos los caracteres. La heredabilidad a nivel individual (h2i) fue: ALT = 0.15, DIAM = 0.22 y DAP = 0.17; a nivel media de familias (h2f) fue de 0.44, 0.54 y 0.47, respectivamente. A una intensidad de selección de mejores individuos de i=1.4, las ganancias genéticas para ALT, DIAM y DAP fueron de 3.9%, 5.2% y 5.0%, respectivamente. De demostrarse posteriormente asociación entre diámetro y producción de resina, sería factible incrementar ambos, mediante selección de individuos con mayores diámetros.

Potencial da madeira de Pinus glabra para produção de polpa celulósica

Há mais de um século as espécies de Pinus estão presentes no Brasil, com destaque para o Pinus taeda, com aplicações em diversos setores. Entretanto o Pinus glabra, objeto deste estudo, não conta com muitas informações sobre o potencial tecnológico de sua madeira. Assim o objetivo do estudo é inferir sobre a qualidade da madeira do P. glabra para produção de polpa celulósica, comparando-a ao P. taeda, principal espécie empregada para fabricação de polpa celulósica de fibra longa no Brasil. Para isso foram abatidas quatro árvores, das quais retiraram-se discos visando a caracterização física, química e anatômica da madeira. Em relação a densidade básica (massa seca/volume verde), observaram-se os valores médio e ponderado de 0,421 g/cm-3 e 0,424 g/cm-3, respectivamente, o que a classifica como de baixa densidade. Na caracterização anatômica obtiveram-se os valores médios de comprimento de 3,14 mm, largura de 27,18 µm, diâmetro do lúmen de 15,39 µm e espessura da parede de 5,89 µm dos traqueídeos, que resultaram em 44,72%, 55,28%, 0,90 e 120,72 para os parâmetros de fração parede, coeficiente de flexibilidade, índice de Runkel e índice de enfeltramento, respectivamente. Para a composição química foram observados baixos teores de cinzas (0,25%) e extrativos (1,91%), e teores intermediários de lignina (29,93%) e holocelulose (67,91%). Desta forma a madeira de P. glabra apresenta potencial para produção de polpa celulósica, o qual deve ser comprovado por meio de ensaios de polpação.

Ankara Üniversitesi 10. Yıl (Beşevler) Yerleşkesinin Bitki Biyoçeşitliliği

Bu çalışmada, Ankara Üniversitesi 10. Yıl (Beşevler) yerleşkesinin tohumlu bitki çeşitliliği belirlenmesi amaçlanmıştır. Çalışma sonucunda yerleşke içerisinde 79 farklı familyadan, 281 cinse ait tür ve tür altı düzeyde toplam 445 takson tespit edilmiştir. Gymnospermae alt şubesinde 5 familyadan 14 cinse ait toplam 31 takson tespit edilmiştir. Angiospermae alt şubesi Monokotil gruba ait 10 familyadan 57 takson, Ödikotil gruba ait 63 familyadan toplam 356 takson ve Ödikotil olmayan bazal gruba ait 1 familyadan (Nynphaceae) 1 takson tespit edilmiştir. Tespit edilen 445 taksondan sadece 8 tanesi endemik olup endemizm oranı ise % 1,8’dir. Ayrıca, yerleşke içerisinde belirlenen taksonlardan 151’i odunlu (ağaç, ağaççık veya çalı), geriye kalan 294 takson ise tek veya çok yıllık otsu bitkilerdir.

ПРЕДСТАВЛЕНИЕ СЕТЕЙ СТРУКТУРОЙ ОСТОВНОГО ДЕРЕВА

The most effective representation of the class of ordinary graphs (in the sense of in-formation capacity) is representation of the structure of the trees. The paper considers the different ways of the graphs assignments. The theorem on the possibility of networks representation by a tree structure is given. In proving this theorem the necessary and sufficient conditions compliance with their representation is formulated. The issues of representations transformation are considered. An example of network coding is given. The network can be set by any tree representation if this represen-tation sets a tree accurate within the numbering of all its vertices.

Defect Prediction With Semantics and Context Features of Codes Based on Graph Representation Learning

To optimize the process of software testing and to improve software quality and reliability, many attempts have been made to develop more effective methods for predicting software defects. Previous work on defect prediction has used machine learning and artificial software metrics. Unfortunately, artificial metrics are unable to represent the features of syntactic, semantic, and context information of defective modules. In this article, therefore, we propose a practical approach for identifying software defect patterns via the combination of semantics and context information using abstract syntax tree representation learning. Graph neural networks are also leveraged to capture the latent defect information of defective subtrees, which are pruned based on a fix-inducing change. To validate the proposed approach for predicting defects, we define mining rules based on the GitHub workflow and collect 6052 defects from 307 projects. The experiments indicate that the proposed approach performs better than the state-of-the-art approach and five traditional machine learning baselines. An ablation study shows that the information about code concepts leads to a significant increase in accuracy.