Form Of Tree Research Articles

Geography of Distribution of Malus Varieties in Azerbaijan Depending on Soil

More than 6,000 plant species have been identified in the Caucasus, of which 4,200 species (70%) are common in Azerbaijan. 11% are trees and shrubs, and 9% are endemic plants. There are more than 280 local varieties and forms of apple trees in Azerbaijan. After the 1920s, the area of ​​fruit orchards in Azerbaijan was expanded to 21 thousand hectares due to local varieties, of which 13 thousand hectares (62%) were apple orchards. In 1926, the Azerbaijan Scientific Research Institute of Horticulture, Viticulture and Subtropical Plants was established in Azerbaijan with the aim of developing fruit growing. New varieties of apple trees are created through selection. Due to the newly created varieties through selection, apple orchards in Azerbaijan have significantly developed. In 1976, 13 thousand hectares of new industrial apple orchards were planted. Since 1982, the existing gene pool of apple trees has been studied.

Hyperparameter Tuning Decision Tree and Recursive Feature Elimination Technique for Improved Chronic Kidney Disease Classification

Purpose: This study has the purpose of classifying patients with chronic kidney disease based on specific features and improving the classification models by tuning hyperparameters. This study aims to detect chronic kidney disease at an early stage. Methods: In this study, a machine learning classifier in the form of a decision tree is used to classify chronic kidney disease on the Risk Factor Prediction of Chronic Kidney Disease dataset. After that, the performance of the classifier model is improved by using feature selection, namely Recursive Feature Elimination and Hyperparameter tuning with GridSearchCV. Result: After tests were conducted 3 times namely testing with Decision Tree, Recursive Feature Elimination, and Hyperparameter tuning GridSearchCV which is the proposed method, then compared to other tests. The results from this study is using that method can improve the Decision Tree classifier in classifying chronic kidney disease patients. Novelty: Dataset that have been used in this study is from UCI machine learning repository namely Risk Factor Prediction of Chronic Kidney Disease that have 202 instances and 28 feature and after being processess and conducting test, Recursive Feature Elimination and Hyperparameter tuning GridSearchCV can improve the Decision Tree classifier in classifying chronic kidney disease.

Формирование вторичного ареала караганы древовидной в лесопарках г. Екатеринбурга

The article is devoted to the analysis of the distribution and features of the ecological and biological confinement of Caragana arborescens Lam. in the forest parks of Yekaterinburg. Caragana plantations have been studied in 14 out of the 15 city forest parks: Kalinovskij, Zheleznodorozhnyj, Karas’ye-Ozerskij, Moskovskij, Nizhne-Isetskij, Sanatornyj, Uktusskij, Shuvakishskij, Yuzhnyj, Shartashskij, named after the Foresters of Russia, Obroshinskij, Central and South-West – on an area of 12,077 hectares based on a standard electronic database. The ontogenesis of the species and its morphological features have been studied in 10 local habitats by the example of 2 forest parks – named after the Foresters of Russia with the largest number of caragana and Uktussky with the minimum. The formation of the secondary area of caragana in the forest parks of Yekaterinburg depends on the presence of generative individuals nearby. The maximum growth area is established in the forest park named after the Foresters of Russia (98.6 ha), the minimum – in the SouthWest (0.4 ha). The area of distribution is determined by the area of plantings that have been carried out in the 1970s and 1980s, which is confirmed by our research in the forest parks. C. arborescens prefers to settle in mixed-herb (67.8 %) and berry (26.8 %) pine forests with a stand density of 0.6–0.7, being a heliosciophyte. The number of caragana trees in the habitats increases with the increase in the density of the stand from 404 to 1359 plants. When the density of the pine stand is 0.3–0.5, the amount of caragana decreases, and at 0.1–0.2 it disappears. The distribution of C. arborescens depends on the age categories and productivity of forest plantations, it grows mainly in mature pine (68.8 %) trees in high-quality (the 2nd quality class – 62.3 %) plantations. In the ontogeneisis of caragana, 2 periods and 6 agerelated conditions have been established, with the pregenirative fraction predominating. The studied habitats are normal, incomplete, but capable of self-maintenance, since under favourable conditions individuals reproduce by self-seeding. The life forms of the caragana tree are formed in open areas as an aeroxylic shrub, and in pine forests as a small tree. The Caragana arborescens introductions in the forest parks of Yekaterinburg are rare and currently pose no biological hazard to forest ecosystems.

A holistic matrix norm-based alternative solution method for Markov reward games

In this study, we focus on examining single-agent stochastic games, especially Markov reward games represented in the form of a decision tree. We propose an alternative solution method based on the matrix norms for these games. In contrast to the existing methods such as value iteration, policy iteration, and dynamic programming, which are state-and-action-based approaches, the proposed matrix norm-based method considers the relevant stages and their actions as a whole and solves it holistically for each stage without computing the effects of each action on each state's reward individually. The new method involves a distinct transformation of the decision tree into a payoff matrix for each stage and the utilization of the matrix norm of the obtained payoff matrix. Additionally, the concept of the moving matrix is integrated into the proposed method to incorporate the impacts of all actions on the stage simultaneously, rendering the method holistic. Moreover, we present an explanatory algorithm for the implementation of the method and also provide a comprehensive solution diagram explaining the method figuratively. As a result, we offer a new and alternative perspective for solving the games with the help of the proposed method due to the simplicity of utilization of the matrix norms in addition to the existing methods. For clarification of the matrix norm-based method, we demonstrate the figurative application of the method on a benchmark Markov reward game with 2-stages and 2-actions and a comprehensive implementation of the method on a game consisting of 3-stages and 3-actions.

Modelling water quality parameters using model tree, random forest, and non-linear regression for Mula-Mutha River, Pune, India.

Evaluation of vital water-quality indicators, especially biological and chemical demand of oxygen (BOD and COD), is important for environmental factors, human health, and agricultural output. In the recent past, data-driven techniques (DDT) offer the ability to automate water quality assessment with more reliable and rapid evaluation. The present study thus aims to utilize various DDTs: random forest (RF), model tree (MT), and non-linear-regression (NLR) to predict vital water quality indicators such as BOD and COD for the three stretches of Mula-Mutha River, Pune, India. Since the river has three stretches: Mutha, Mula, and Mula-Mutha respectively, BOD-COD models have been developed separately for each using MT, RF, and NLR. Data analysis using a violin diagram is done to understand the data characteristics. Further, the models developed were developed using the appropriate input parameters for predicting BOD and COD. Error measures including coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE) were used to evaluate the constructed models. The Taylor diagram, scatter plot, and hydrograph were also used for visual performance analysis. The findings suggest that the MT and RF techniques exhibit a stronger connection between the actual and anticipated levels of BOD and COD, with NLR following closely behind. Practical acceptance of these approaches is increased by RF in the form of trees, MT with an output in the form of a sequence of equations, and NLR with a single equation. These findings help us gain insight into DDT's water quality assessment model, which will also help future researchers and water quality professionals make decisions.

Code Completion Using Markov Chains

Modern software engineers use many tools to speed up the development process. Many of them use integrated development environments (IDEs), which provide services such as text editors, debuggers and even intelligent code completion. This paper is dedicated to the development of a model for predicting variants of program source code termination. To improve the accuracy of the model, we used combinations of Markov chains constructed using different ways of calculating the current context of the program: linear and with AST. The linear way of computing the context is an analysis of the tokenized representation of the source code. The second method, on the other hand, uses a representation of the source code in the form of an abstract syntax tree. Combining the different models preserves more semantic information about the code, also adding the ability to support custom code writing style features. In order to compare the different models, a new dataset has been created specifically for the Pascal language. A detailed comparison of the working mechanisms as well as the prediction accuracy on the collected data is given. The proposed model showed high enough accuracy of predictions with minimal computation costs, which allows using it in integrated development environments.

Morphological analysis of system studies of automatic space applications in a synergetically disturbing environment

The article considers the use of a new methodological cognitive-variable synergetic (CVS) approach to the analysis of the problems of the theory of systems research conducted on board automated spacecraft (AS) [1]. The methodological basis of the CVS approach is based on cybernetic [2]and synergetic [3] theories of dynamic systems management, as well as the methodology of proactive management of the functioning of complex technical objects (STO), based on the concept of integrated modeling of STO [2]. The results of the previously conducted morphological analysis of the problems of the theory of systemic cybernetic studies of the movement of dynamic systems are known, presented in the form of a morphological tree containing four branches (modeling-analysis-observation-choice) and leaves (particular tasks) [4]. The number of tasks is determined by the interaction of the control system (environment) with four types of effects of the disturbing environment – deterministic, stochastic, purposeful and with unknown characteristics - in the formation of input effects on the control system. The CVS approach is based on the use of a new type of environment in the management of dynamic systems – synergetically disturbing. To display the new environment and tasks on the morphological tree of problem analysis, in addition to the existing tasks of systemic cybernetic research, new leaves are introduced - particular tasks of systemic synergetic research. The paradigm of problem analysis is formed on the basis of knowledge, management experience and system research aimed at solving the problem of providing resources for on-board AS systems and the stability of their functioning during flight. The goal–setting of a new methodological approach to the analysis of the problems of the theory of systems research is aimed at the rational use of the main structural and functional resources of the BS, obtaining synergetic resources and preventing failures caused by calculated and non-calculated abnormal processes. Further, synergetic will be called such a type of resources that is formed by spontaneous self-organization of processes in management systems and transformed into purposeful self-organization in objectively existing multi-place relationships describing synergetic interactions and interrelations during the movement of processes in a synergetically disturbing external environment [5, 6].

A Framework for Developing Intelligent Tutoring Systems Based on Domain Models in the Form of Decision Trees

A Framework for Developing Intelligent Tutoring Systems Based on Domain Models in the Form of Decision Trees

Mapping, geography

AbstractThis Themed Intervention consists of short papers written by nine plenary speakers at the 2024 Annual Conference of the Royal Geographical Society with the Institute of British Geographers plus a paper by the Society's Cartographic Collections Manager. In this introduction, I explain why I chose mapping as the conference Chair's theme. I give a sense of how the relationship between geography and mapping has been addressed through previous conference addresses and themes. I then explore three types of cartographic genealogies. The first shows how histories of cartography traditionally took the form of family trees. The second explores disjunctures between previous phases of cartography and brings us to current definitions of mapping. The third genealogy is that of previously subjugated forms of mapping knowledge and practice which are now defining features of the field (critical quantitative; empire, race, and Indigenous; counter‐; representational and more‐than‐representational).

DeepTree: Modeling Trees With Situated Latents.

In this article, we propose DeepTree, a novel method for modeling trees based on learning developmental rules for branching structures instead of manually defining them. We call our deep neural model "situated latent" because its behavior is determined by the intrinsic state -encoded as a latent space of a deep neural model- and by the extrinsic (environmental) data that is "situated" as the location in the 3D space and on the tree structure. We use a neural network pipeline to train a situated latent space that allows us to locally predict branch growth only based on a single node in the branch graph of a tree model. We use this representation to progressively develop new branch nodes, thereby mimicking the growth process of trees. Starting from a root node, a tree is generated by iteratively querying the neural network on the newly added nodes resulting in the branching structure of the whole tree. Our method enables generating a wide variety of tree shapes without the need to define intricate parameters that control their growth and behavior. Furthermore, we show that the situated latents can also be used to encode the environmental response of tree models, e.g., when trees grow next to obstacles. We validate the effectiveness of our method by measuring the similarity of our tree models and by procedurally generated ones based on a number of established metrics for tree form.

Climate change impacts of forest conversion (Study on forest conversion for food estate/ national food granary program in Central Kalimantan)

Background: The Food Estate policy or national food granary program is a food development concept that is integrated with agriculture, plantations and animal husbandry, one of which is in the area of openings in natural forests covering an area of 156,000 ha in Central Kalimantan. This program is designed to prepare national food security in order to respond to the Food and Agriculture (FAO) Report on the threat of a global food crisis due to the impact of the Covid 19 pandemic. Changes in forest cover from previously green land to agricultural land will cause loss of forest cover in the form of vegetation or trees that have ecosystem services as carbon dioxide absorbers from the air. Methods: The impact of forest conversion is analyzed by conducting spatial analysis of land cover and calculating potential carbon stocks lost, as well as providing suggestions or solutions to problems or gaps from an economic, social, and political environmental perspective. Findings: From the results of literature studies, the government must learn from the experience of food estate projects on peatlands in the past where peatlands became thin and when the dry season arrived, the land would be flammable due to lack of attention to the biophysical aspects of the soil. Conclusion: In addition, economic and social aspects involve and assist the community in carrying out food security programs and agricultural technology sophistication. Novelty/Originality of this Study: This analysis provides a unique perspective on the climate change impacts of forest conversion for food estate programs, bridging the gap between national food security policies and environmental conservation imperatives.

Towards reconciling usability and usefulness of policy explanations for sequential decision-making systems.

Safefy-critical domains often employ autonomous agents which follow a sequential decision-making setup, whereby the agent follows a policy to dictate the appropriate action at each step. AI-practitioners often employ reinforcement learning algorithms to allow an agent to find the best policy. However, sequential systems often lack clear and immediate signs of wrong actions, with consequences visible only in hindsight, making it difficult to humans to understand system failure. In reinforcement learning, this is referred to as the credit assignment problem. To effectively collaborate with an autonomous system, particularly in a safety-critical setting, explanations should enable a user to better understand the policy of the agent and predict system behavior so that users are cognizant of potential failures and these failures can be diagnosed and mitigated. However, humans are diverse and have innate biases or preferences which may enhance or impair the utility of a policy explanation of a sequential agent. Therefore, in this paper, we designed and conducted human-subjects experiment to identify the factors which influence the perceived usability with the objective usefulness of policy explanations for reinforcement learning agents in a sequential setting. Our study had two factors: the modality of policy explanation shown to the user (Tree, Text, Modified Text, and Programs) and the "first impression" of the agent, i.e., whether the user saw the agent succeed or fail in the introductory calibration video. Our findings characterize a preference-performance tradeoff wherein participants perceived language-based policy explanations to be significantly more useable; however, participants were better able to objectively predict the agent's behavior when provided an explanation in the form of a decision tree. Our results demonstrate that user-specific factors, such as computer science experience (p 0.05), and situational factors, such as watching agent crash (p 0.05), can significantly impact the perception and usefulness of the explanation. This research provides key insights to alleviate prevalent issues regarding innapropriate compliance and reliance, which are exponentially more detrimental in safety-critical settings, providing a path forward for XAI developers for future work on policy-explanations.

Decision support for strategic microgrid design integrating governance, business, intelligence, communication, and physical perspectives

Microgrids are custom-designed, but their extensive design options hinder their dissemination. Consequently, microgrid-interested parties need strategic support to identify suitable design options for their use case. This paper develops a decision support artifact in the form of a decision tree for recommending the most suitable microgrid design for a project. A multi-step design science-oriented process was used. First, a morphological analysis of academic literature was conducted to deduce all possible microgrid design options and visualize them in a morphological box. Once done, 62 real-world microgrids of diverse types and locations were classified according to the morphological box. The produced dataset was used to derive five microgrid design archetypes algorithmically using cluster analysis. The dataset and their associated archetypes were then fed into a rule-mining algorithm to generate a decision tree that recommends the appropriate microgrid archetype based on up to four questions about, for instance, the microgrid's objective and the connectivity to the main grid. Furthermore, design principles for each microgrid archetype recommendation were formulated. The developed design artifact serves as applicable knowledge and a benchmark framework for researchers, as well as a comprehensive and simultaneously simplified decision-making framework for practitioners.

Correlaciones, parámetros genéticos y fenotípicos en rasgos cuantitativos y cualitativos de Swietenia macrophylla en Ucayali, Perú

The speed of growth in height of Swietenia macrophylla stands out in terms of resistance to attack by the Hypsipyla grandella borer and the selection of fast-growing families can make commercial plantings viable. The characters height, diameter, number of leaves and stem form of trees from 4 families of S. macrophylla, aged 47.5 months, planted in Ucayali, Peru, were used to investigate the possibility of selecting fast-growing genotypes. The average heritability (h2m) and selective accuracy (Acprog) between families were moderate for total height (Ht: h2m: 0.407; Acprog: 0.638) and commercial height (Hc: h2m: 0.472; Acprog: 0.687), in addition to Hc positively correlating with susceptibility to the drill attack. The stem form showed statistical differences between families and great h2m (0.984) and Acprog (0.921). The genetic (rg) and phenotypic (rf) correlations between traits showed that a selection of individuals with greater heights will generally result in greater growth in diameter, number of leaves and better stem form. The study highlights the importance of selecting families with fast growth in height and straight stems to enable, improve the quality and increase the productivity of commercial plantations with the species.

Effects of stem size and age on resprouting ability of different tree species after clear-cutting in a warm temperate secondary forest

ABSTRACT Understanding the resprouting abilities of various tree species provides valuable insights into managing coppice forests and predicting forest dynamics. Clear-cutting was conducted in a secondary forest comprising warm-temperate broadleaf trees, and the stump size, age, and traits of the resprouts were measured to study their effects on resprouting ability. The number of resprouts that emerged from a stump was not significantly different when comparing different tree forms (canopy and shrub) or leaf longevity (evergreen and deciduous). Taller species generated taller and fast-growing resprouts. The ability to generate more resprouts with age was more important for species dominance than the ability to generate more resprouts with increase in stem size. Most shrub layer species exhibited age-related reductions in resprouting ability. Evergreen canopy species tended to have a larger number of resprouts and higher stump survival rate. The results suggest that the diversity of the resprouting traits among tree species could largely influence the stand dynamics and contribute to the coexistence of tree species.

Form factors and volume models for Falcataria moluccana in smallholder plantations, Central Kalimantan, Indonesia

ABSTRACT Falcataria moluccana (sengon) is grown extensively for timber production in smallholder plantations in Indonesia. However, stem form and volume information necessary for its sustainable forest management, yield estimation and carbon assessment are largely unavailable. Therefore, this study developed form factor and stem volume models for sengon trees in Central Kalimantan, Indonesia. Data were collected using a destructive method from 24 trees across six diameter classes. Two types of form factors, artificial and absolute, were determined, and their relationship with tree growth was established. Four form factor functions were fitted, and the accuracy of volume estimation using a default form factor was compared to the functions. Additionally, 11 stem volume models were developed, and their performance was compared with the commonly used published models. The form factor for sengon was estimated at 0.48, which was higher and more accurate than the absolute form factor. A linear relationship was observed between sengon tree form and growth, particularly with the artificial form factor (R 2 = 0.55–0.62). The Pollanschütz function was identified as the best form factor function, accurately predicting form factors for precise tree volume computations. Using the default form factor of 0.5 led to an overestimation of volume by up to 17%. Among the volume models, the power models with diameter as the sole predictor (MD3: V = 0.00018 * DBH2.3817) and with both diameter and height variables (MDH4: V = 0.000095 * DBH1.9974 * H0.6327) were the most accurate. Importantly, the models developed in this study offer improved accuracy compared to existing models from Java, which tend to overestimate stem volume. Therefore, this study provides suitable models and valuable insights for better valuation and management of smallholder sengon plantations in Central Kalimantan and other areas with similar site and stand conditions.

Use of Toxic and Allergen Plants in Landscape Arrangements of Urban Historical Areas: The Case of Çeşme Castle (İzmir)

Urban historical areas and buildings are structures that provide important information, culture and tradition transfer from the past to the present. These places are both an effective tourism area and a part of urban life. In addition to the aesthetic, ecological and functional benefits of the plants to be used in urban historical areas, their allergenic and toxic effects should be paid attention. Exposure to plants with toxic effects may cause mild or serious adverse effects on human health. The study was carried out to identify toxic and allergenic plants in the historical area of Çeşme Castle and to make evaluations about the area. Plants were examined on site in the study area and photographs were taken. According to the literature, the allergenic effects, toxic status, toxic parts and active ingredient of the plant species were determined. The data obtained were analysed and as a result of the analyses; 30 plant species, 29 genera and 22 families were identified in the area. Toxic plant species ratio in the area was 53.33 % and allergenic plant species ratio was 36.66 %. According to their forms, toxic plant species ratio was 37.5 % and allergenic plant species ratio was 81.81 %, with the highest proportion found in tree form plant species. Among the identified plants, 5 species have both toxic and allergenic effects. Recommendations have been made regarding the use of poisonous and allergenic plants in the field. Recommendations was made regarding the use of toxic and allergenic plants in the area.

Inventorying and proposing solutions for street tree management in Thu Duc city, Ho Chi Minh City

Tree inventory plays an essential role in the urban landscape master plan. It serves as the foundation for data acquisition that supports the planning strategy and decisions relating to the community’s interests, particularly in recently established cities like Thu Duc city. This research was carried out from October 2021 to December 2022 in this city and aimed to inventory to gather qualified information for managing the city’s street trees. The study used an inventory form of street trees including criteria such as name, family, diameter at breast height (DBH), total height, and indicators of vitality and distance from trees to infrastructure. By this form, 287 streets were surveyed. The total number of investigated trees was 31.023 trees belonging to 65 species and 24 flora families, of which the species with a high percentage (from 10% or more) were Dipterocarpus alatus, Hopea odorata, Peltophorum pterocarpum, and Lagerstroemia speciosa. The most numerous plant family was Fabaceae. These trees typically had a height of less than 10 m, with a DBH of less than 20 cm. Many streets did not guarantee the distance between trees and infrastructure, particularly the distance to the electrical systems. The survey also showed that the majority of trees were healthy and grow healthily. From the current situation of Thu Duc city street trees, three solutions must be prioritized in order to improve street trees in this city.

From Dawn to Dusk: High-Resolution Tree Shading Model Based on Terrestrial LiDAR Data

Light availability and distribution play an important role in every ecosystem as these affect a variety of ecosystem processes and functions. To estimate light availability and distribution, light simulations can be used. Many previous models were based on highly simplified tree models and geometrical assumptions about tree form, or were sophisticated and computationally demanding models based on 3D data which had to be acquired in every season to be simulated. The aim of this study was to model the shadow cast by individual trees at high spatial and temporal resolution without the need for repeated data collection during multiple seasons. For our approach, we captured trees under leaf-off conditions using terrestrial laser scanning and simulated leaf-on conditions for individual trees over the remainder of the year. The model was validated against light measurements (n=20,436) collected using 60 quantum sensors underneath an apple tree (Malus domestica Borkh.) on a sunny and cloudless summer day. On this day, the leaves and the shadow were simulated with a high spatial (1 cm) and temporal resolution (1 min). The simulated values were highly correlated with the measured radiation at r=0.84. Additionally, we simulated the radiation for a whole year for the sample apple tree (tree height: 6.6 m, crown width: 7.6 m) with a resolution of 10 cm and a temporal resolution of 10 min. Below the tree, an area of 49.55 m² is exposed to a radiation reduction of at least 10%, 17.74 m² to at least 20% and only 0.12 m² to at least 30%. The model could be further improved by incorporating branch growth, curved leaf surfaces, and gravity to take the weight of the foliage into account. The presented approach offers a high potential for modelling the light availability in the surroundings of trees with an unprecedented spatial and temporal resolution.

Treegraph: tree architecture from terrestrial laser scanning point clouds

AbstractAccurate quantification of tree architecture is critical to interpreting the growth, health and functioning of trees and forests. Terrestrial laser scanning (TLS) offers millimetre‐level point cloud data, but current approaches to 3D tree reconstruction from TLS point clouds primarily focus on retrieving total volume at tree scale for aboveground biomass (AGB) estimation. Few methods have been designed specifically to provide tree architectural properties, including branch‐level morphology and topology, rather than AGB; derived topological traits have tended to be a compromise, and of secondary importance to volume. We present Treegraph, a new approach explicitly designed to retrieve the architectural traits of trees at multiple scales, from the whole tree scale down to individual branches and internodes, using TLS data with limited assumptions about tree form. It provides morphological traits such as branch length and diameter, alongside topological traits including parent–daughter connections of branches and internodes, furcation (branching) number and branch order. We compare Treegraph‐derived morphological and topological traits with manual measurements of branches from eight destructively harvested trees, yielding RMSE values of 0.60 m (5.96%) for branch length, 2.99 cm (33.45%) for branch diameter, 0.46 (19.38%) for furcation number and 0.08 m (33.16%) for internode length, respectively. In a broader application to 603 trees from tropical, temperate and urban forests, we demonstrate that the derived morphological and topological traits support testing of structure‐related metabolic scaling theories. Testing branches over 10 cm in diameter across 18 657 branching nodes shows that Treegraph‐derived branch‐level scaling exponents deviate from WBE predictions, exhibiting area‐preserving behaviour while displaying asymmetry in length and diameter of daughter branches. Available as open‐source Python software, Treegraph provides fine‐level branching network information, promoting improved insights into tree structure and function. This data‐driven approach reduces the need for empirical heuristic parameters, which has the potential for advancing large‐scale ecological studies on tree architecture.