Form Of Tree Research Articles

INNOVATIVE ACTIVITY OF RESTAURANTS OPERATING IN THE LARGEST POLISH CITIES

The skills of acquiring and processing information as well as creating innovations remain the key factor responsible for the market success of enterprises, one of the most important factors in gaining a competitive advantage on the market. It is also true for the tourism market of which catering services make an essential part. Hotel industry has been the subject of intensive research in this area for over 2 decades. Much less scientific attention has been paid to innovation in the restaurant sector. Therefore, the intention of the authors of this study was to analyse the process of creating innovations in restaurants operating in the largest Polish cities. The study identifies the factors responsible for the innovative activity of restaurants, perceived from the perspective of their managers. For this purpose, a multivariate method, in the form of classification trees, was used. The research material was collected in the course of a survey carried out in 250 restaurants. As a result of the applied research methods, the innovation factors were specified and 4 segments of innovative restaurants in Poland were identified. These segments are made up of 75% of restaurants applying pro-innovative activities, which for them represent an important aspect of market success. Pro-innovative activities are implemented more often by chain restaurants as well as the ones operating in hotel facilities. Small, family-run restaurants use innovations on a smaller scale. They refer to selected restaurants operating in the 6 largest Polish cities, which limits the possibility of making generalizations regarding other forms of catering establishments functioning in other geographical locations. Future research should cover a wider group of catering establishments, in various locations.

Penerapan Decision Tree Algoritma C4.5 Dalam Penentuan Izin Pembongkaran Muatan Kapal

Along with the increasing number of bulk cargoes that are dismantled every year at belawan port and for the creation of services in accordance with expectations, it is necessary to develop services in support of indonesia's logistics improvement readiness, especially in terms of demolition. Utilization of machine learning using the C4.5 algorithm can make it easier to conduct selection and classification of the feasibility of ships that get permission for demolition activities. The use of the C4.5 algorithm will produce a decision tree that can equalize the results of data mining, so that the information obtained from the data will be easier to identify in testing methods using the Orange Data Mining tool. The results obtained by the C4.5 algorithm in the form of a decision tree with an accuracy value of 84%, 90% precision and 84% recall.

Toddler Nutritional Status Classification Using C4.5 and Particle Swarm Optimization

Abstract. Purpose: This research was conducted to create a classification model in the form of the most optimal decision tree. Optimal in this case is the combination of parameters used that will produce the highest accuracy compared to other parameter combinations. From this best model, it will be used to predict the nutritional status class for the new data.Methods/Study design/approach: The dataset used is from Nutritional Status Monitoring in 2017 in Riau Province, Indonesia. From the dataset, the Knowledge Discovery in Database (KDD) stages were carried out to build several classification models in the form of decision trees. The decision tree that has the highest accuracy will then be selected to predict the class for the new data. Predictions for new data (unclassified data) will be made in a web-based system.Result/Findings: Particle Swarm Optimization is used to find optimal parameters. Before PSO is used, there are 213 parameters in the dataset that can be used to do classification. However, using many such parameters is time-consuming. After PSO is used, the optimal parameters found are the combination of 4 parameters, which can produce the most optimal decision tree. The 4 chosen parameters are gender, age (in months), height, and the way to measure the height (either stand up or lie down). The most optimal decision tree has an accuracy of 94.49%. From the most optimal decision tree, a web-based system was built to predict the class for new data (unclassified data).Novelty/Originality/Value: Particle Swarm Optimization (PSO) is a method that can help to select the most optimal parameters, or in other words produce the highest classification accuracy. The combination of parameters selected has also been confirmed by the nutritionist. The prediction system has been declared feasible to be used by nutritionists through the User Acceptance Test (UAT).

Dendroflora diversity in the coastal zones of the Dnipro river within the Northern steppe subzone of Ukraine

Coastal tree and shrub vegetation is an important component of river catchment ecosystems, it performs a wide range of ecological functions and ecosystem services; their effectiveness largely depends on species richness and diversity. Coastal habitats are among the main centers of biodiversity, but they often perform a function of centers of active anthropogenic activity and undergo significant transformation. The creation of a cascade of the Dnipro reservoirs (Kamenske, Zaporizhia (Dniprovske), Kakhovske reservoirs) has already caused the transformations of the Dnipro river flow regime and all biological components of the aquatic and wetland ecosystems in the Northern steppe subzone of Ukraine. In the current period, on the background of global climate change, dendroflora transformation on this territory is enhanced by the anthropogenic impact of industrial cities (Kamenske, Dnipro, Zaporizhzhia). Assessment of dendroflora diversity in coastal zones was carried out within the protective strip of the Dnipro river (100 m): in native phytocenoses; semi-native vegetation associations; water protection plantings; public green spaces (excluding private plots and collections). It was determined that the dendroflora in the coastal protective strips of the Dnipro river within the Northern steppe subzone of Ukraine is characterized by significant taxonomic diversity and includes 184 plant species (excluding their decorative forms) belonging to 37 families. The highest species saturation was typical for the following families: Rosaceae (40 species), Salicaceae (23 species), Fabaceae (11 species), and Oleaceae (9 species). The dendroflora consists of 61 tree species, 78 shrubby species (including lianas) and 45 species that can be represented by both tree and shrubby forms. The highest species richness was recorded in public recreational green spaces: 181 species (98% of the total species number). The coastal tree and shrubby associations included 8 species that belong to rarity ones (the Red List of the Dnipropetrovsk region). The coenomorphic spectrum of dendroflora in coastal protective strips is dominated by culturants (70.7%), autochthonous silvants (19%), stepants (3.2%), silvomargoants (species of forest margins, 4.3%), pratants (1.6%), and paludants (1.1%). There is the dominance of mesophytes (55%) and species with a wide range of adaptations to the humidification conditions of hygrotopes in hygrospectrum (22.8%); mesotrophic species among trophomorphs (53.8%), and sciogeliophytes in heliospectrum (57%). In the dendroflora of the coastal zones of the Dnipro river, alien species completely predominated (71% of the species composition). Among them, 6.9% were invasive, mainly belonging to neophytes. In the current period, an increase in invasive activity is recorded in another 5.3% of adventive (potentially invasive) species. The significant taxonomic and ecomorphic diversity of dendroflora in the coastal zones of the Northern steppe subzone of Ukraine is associated with ecotone effects, active processes of the territory urbanization, and the use of a wide range of alien ornamental species in public green spaces of cities. It is advisable to increase the share of autochthonic and rare species participation in the composition of coastal protective and recreational plantings, which will contribute to the preservation of their gene pool and increase the native dendrological diversity in the Dnipro river basin. To reduce the threats of phytoinvasions, it is necessary to: i) prohibit the use of invasive species in the restoration of native floodplain forests; ii) conduct a preliminary assessment of environmental risks from the use of alien species; iii) monitor existing plantings with their participation.

Mina #Ecosmartphone Films 2021

MINA - Mobile Innovation Network and Association is the longest-running film festival in the Southern Hemisphere dedicated to mobile & smartphone filmmaking with a focus on moving-image arts, documentary, community-engaged film productions, experimental films and emerging film production forms and formats, such as MoJo, drone videos, AR and Mobile Cinematic VR. The tenth edition of MINA is presenting a special program titled #EcoSmartphoneFilms, a showcase of contemporary mobile film production about environmental protection and ecology in all its aspects. It is an eclectic collection of short international environmentally themed films from all over the world made on smartphones, pocket cameras, laptops and Instagram. The films show the planet’s beauty as well as the various local, regional and global environmental challenges we are facing. By using a variety of creative solutions that illustrate the power of mobile film, they help to raise awareness about environmental topics from around the globe and make us aware of the role mobile media can play in this. In the spirit of Margaret Mead’s statement that we should “never doubt that a small group of thoughtful, committed citizens can change the world” with this special #EcoSmartphoneFilms program we hope to inspire a deeper critical understanding of ecological issues and strengthen our commitment as both filmmakers and curators to inspire future generations to go mobile and stay sustainable. Save Me (UK) Michael CoppolaShot on iPhone 11 Pro Max SAVE ME is an experimental sci-fi drama short film about the fragmentation of the human psyche, manmade planetary destruction and the possible end of the subjective and objective world, told through the experiences of a lost girl stranded on a deserted beach, accompanied by an epic orchestral score and futuristic sound design with the use of CGI. Iumbar Project - The First One (Australia) Martin K. Koszolko Shot on iPad Pro This music video documents human intervention into environment. The footage shows the fate of trees and other plants disposed of by human inhabitants of the land. This short film raises questions about our relationship with the natural environment and highlights the beauty of the shapes and forms of trees. This beauty is evident even if the plants have been cut down and are no longer alive. The Almeda Fire (USA) David Scott LeibowitzShot on iPhone 11 Pro My Mobile movies took a swift turn from art to ENG when the Almeda fire swept through this part of the Rogue Valley. After The Flood (USA) Alexandra GuillossouShot on iPhone XR An observational piece on two seemingly dissimilar St. Louis events that took place in June 2019. Man and nature can be equally explosive and yet only one has the option of choice. Tree Time (USA) Alexandra Lerman Shot on iPhone 7 & iPhone X Tree Time imagines a relationship between nature and technology unmediated by human presence. The video was shot in the Amazon rainforest with a drone enacting a disembodied point of view that floats through the densely compressed forest canopy, taking off, hovering above the ground, and occasionally returning to it. Kaminda (NL) David van DeldenShot on iPhone X & iPhone 11 Pro A visual poem of a 3-year-old boy's journey of self-discovery. Kaminda revisits David’s childhood adventures narrated by a young voice in spoken words written by Juan- Carlos Goilo. From the dry northern plains to the atmospheric damp caves, Kaminda takes you through the rustic landscapes of Curaçao with stunningly captured scenes. Hear the primitive sounds of Curaçao's "Muzik di Zumbi" accompanied by scenes shot underwater, on land and in the air. Little Beings (Mexico) DiAminda Ordaz Shot on iPhone 8 I tended my senses and they were there,I stopped to contemplate and they were there, I opened my eyes and they were there,I woke up and they were there,I paid attention and they were there.So I wanted to take off my sandals,as not to hurt them with my walk.

A Data-Driven Fault Tree for a Time Causality Analysis in an Aging System

This paper develops a data-driven fault tree methodology that addresses the problem of the fault prognosis of an aging system based on an interpretable time causality analysis model. The model merges the concepts of knowledge discovery in the dataset and fault tree to interpret the effect of aging on the fault causality structure over time. At periodic intervals, the model captures the cause–effect relations in the form of interpretable logic trees, then represents them in one fault tree model that reflects the changes in the fault causality structure over time due to the system aging. The proposed model provides a prognosis of the probability for fault occurrence using a set of extracted causality rules that combine the discovered root causes over time in a bottom-up manner. The well-known NASA turbofan engine dataset is used as an illustrative example of the proposed methodology.

Cumulative Impact of Biotic and Abiotic Damage Agents on Lodgepole Pine Tree Form and Stand Structure in Southern British Columbia

Not all pests kill trees or compromise final tree form; however, the cumulative effect of one or more damage agents over time can significantly limit final expectations at harvest, severely reducing or compromising wood quality and timber supply expectations going forward. This study highlights the effects of damage agents on young lodgepole pine insouthern British Columbia during the formative years of stand development. Over 4,300ntrees were monitored for up to three decades with over 40 damage agents recorded, causing significant repercussions on stocking, health, and form of potential crop trees. By the final assessment, density of potential crop trees had declined dramatically, with 84% affectedby one or more pests, and 63% of natural ingress dead. Most natural ingress was severely suppressed; thus, it is unlikely to fill in stand gaps caused by mortality and damage agents affecting larger potential crop trees. Lodgepole pine terminal weevil and western gall rust were the predominant damage agents influencing form and quality of potential crop trees. Lodgepole pine terminal weevil attacked up to 73% of pine and over 24% suffered multiple attacks. Results from this study emphasize the need for more short- and long-term monitoring of young stands to inform the development of forest policy and promote healthy, resilient new forests. KEYWORDS: lodgepole pine, damage agents, lodgepole pine terminal weevil, western gall rust, Southern British Columbia

FractureNet: A 3D Convolutional Neural Network Based on the Architecture of m-Ary Tree for Fracture Type Identification.

To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional neural network (CNN) to learn fracture features from voxelized bone models which are obtained by establishing isomorphic mapping from fractured bones to a voxelized template. The network, which is named FractureNet, consists of four discriminators forming a multi-stage hierarchy. Each discriminator includes multiple sub-classifiers. These sub-classifiers are chained by two kinds of feature chains (feature map chain and classification feature chain) in the form of a full m-ary tree to perform multi-stage classification tasks. The features learned and classification results obtained at previous stages serve as prior knowledge for current learning and classification. All sub-classifiers are jointly learned in an end-to-end network via a multi-stage loss function integrating losses of the four discriminators. To make our FractureNet more robust and accurate, a data augmentation strategy termed r-combination with constraints is further proposed on the basis of an adjacency relation and a continuity relation between voxels to create a large-scale fracture dataset of voxel models. Extensive experiments show that the proposed method can recognize various fracture types in patients accurately and effectively, and enables significant improvements over the state-of-the-arts on a variety of fracture recognition tasks. Moreover, ancillary experiments on the CIFAR-10 and the PadChest datasets at large scales further support the superior performance of the proposed FractureNet.

An Updated Decision Tree for Horizontal Ridge Augmentation: A Narrative Review.

Horizontal ridge augmentation is a common surgical procedure performed prior to or simultaneously with implant placement, depending on the extent of the ridge deficiency. Many horizontal augmentation surgical options have been developed, spanning a wide range of materials and techniques. Given the numerous permutations available, the most suitable strategy to regenerate ridge width for an individual case often confounds clinicians. Based on an extensive review of the literature, this article provides up-to-date technique selection guidelines, in the form of a decision tree, for predictable horizontal bone augmentation dependent on the amount of bone gain needed.

Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm.

The Brillouin Optical Time-Domain Analyzer assisted by the AdaBoost Algorithm for Brillouin frequency shift (BFS) extraction is proposed and experimentally demonstrated. The Brillouin gain spectrum classification under different BFS is realized by iteratively updating the weak classifier in the form of a decision tree, forming several base classifiers and combining them into a strong classifier. Based on the pseudo-Voigt curve training set with noise, the performance of the AdaBoost Algorithm is studied, and the influence of different signal-to-noise ratio (SNR), frequency range, and frequency step is also studied. Results show that the performance of BFS extraction decreases with the decrease in SNR, the reduction in frequency range, and the increase in frequency step.

An empirical financial analysis of integrating biomass procurement in sawtimber and pulpwood harvesting in eastern Canada

Integrating forest biomass procurement in wood procurement for conventional products is a potential means of reducing bioenergy system supply costs. We studied forest harvest operations to procure biomass in the form of trees and tree sections, along with sawtimber and pulpwood. We evaluated the cost-effectiveness of the supply chain with a particular focus on harvest costs and the potential silvicultural savings from a reduced need for site preparation and reforestation. We compared four wood procurement scenarios of increasing intensity (from harvesting only sawtimber to harvesting sawtimber, pulpwood and biomass for bioenergy) at three sites in eastern Canada. Wood procurement intensity did not affect feedstock unit costs (CAD·m−3). At the stand scale, procuring biomass for bioenergy had limited impact on harvest costs (CAD·ha−1) for low-density stands with large trees. In contrast, high-density stands with small trees generated more feedstock for bioenergy (up to 50 m3·ha−1), but biomass procurement increased harvest costs. The cost-effectiveness of the wood supply chain did not vary significantly along the wood procurement intensity gradient we studied when silvicultural savings are considered. The proportion of biomass harvested, stand characteristics, and market conditions proved to be important factors that influence wood procurement profitability.

Aplikasi Teknologi QR Code Pada Identifikasi Tumbuhan Di Wisata De-Djawatan

De-Djawatan Tourism Destinations are known by various tourists both local and non-local with their natural beauty in the form of large and lush trees that are still beautiful or natural. De-Djawatan tourism does not yet have detailed information either manually or digitally related to the biological and general classification of plants in that location. As smartphone technology develops, the information needed to be very easy to obtain. QR Code is one method to obtain complete information. QR Code is a type of two-dimensional image that displays data in the form of text. This community partnership program aims to provide appropriate technology in the form of the QR code method in determining the identification of plants found in De-Djawatan tourist destinations. This aims to make it easier for tourists to find information on various plants both biologically and in general.
 The stages of program implementation start from the observation stage, media creation, and implementation. The results of this program using the QR Code can include the identity of the identification results of plants, such as division, order, family, genus and species of plants in the De-Djawatan location. In this QR Code method there are features such as Home, Collection, and Admin. Before the QR Code is created, the document data is encrypted and then used as a QR Code. The result of scanning the QR Code is in the form of a Uniform Resource Locator (URL) that points to the document data. When the URL is executed on the web browser, the system performs a description of the URL, then it is matched with the database, and then displayed to the web browser. The final result is a Document Validation application in the form of a QR Code which is used to convey plant identification information, such as division, order, family, genus and species of plants.

Peculiarities of the phenological development of <i>Malus</i> P. Mill species in the conditions of the steppe zone of the southern urals

The article presents the results of phenological observations of five-year-old trees of introduced species and forms of apple trees. The research was conducted in the Orenburg branch of the Federal Horticulture Research Center for Breeding, Argotechnology and Nursery in 2019-2021. Phenological studies were carried out according to the methodology of G. N. Zaitsev, statistical data processing was carried out using the methods of G. N. Zaitsev and B. A. Dospekhov. Data on the passage of 10 phenological phases were used (bud opening, beginning of flowering, end of flowering, end of shoot growth, lignification of shoots, beginning of fruit ripening, end of fruit ripening, autumn leaf coloring, beginning of leaf fall, end of leaf fall). In variable weather and climatic conditions during the growing season, it was found that the timing of the onset of the main phenological phases directly depends on the amount of accumulated positive temperatures, in particular, for the beginning of the growing season, this parameter is 245.2-304.7°C; for the beginning of the flowering phase — 630-609.4°C; the end of shoot growth was accompanied by the accumulation of positive temperatures from 2 152.8 to 2 398°C; at the end of fruit ripening, the sum of positive temperatures was 2 736.3-3 386°C; the beginning of leaf fall corresponds to the sum of positive temperatures from 2 873.9 to 3 200.8°C. In the conditions of the study, the duration of the growing season is 169-176 days, which is a short growing season. Weather and climatic conditions had a significant impact on the processes of active growth and flowering, the genotype of the studied species and forms caused the processes of fruit ripening, lignification of shoots, leaf fall. The duration of the shoot growth period is in direct correlation (r = 0.74-0.81) with the hydrothermal coefficient. The main decorative periods, including flowering, fruit ripening, and the period of autumn coloring, depend to varying degrees on both genotypic characteristics and meteorological conditions in the growing area.

KKN TEMATIK UNTIRTA : PELATIHAN PEMBUATAN NATA DE COCO DAN PELATIIHAN DIGITAL MARKETING DI DESA RAMAYA KECAMATAN MENES KABUPATEN PANDEGLANG

Student Work Lecture is a form of community service carried out by universities through student activities as part of the course. The form of PT's contribution to the problems faced by the community through KKM activities as an effort to get closer to PT and also make students as agents of change change and community empowerment. KKM Regular 1 Untirta is carried out still in the Covid-19 pandemic situation, where this pandemic has a very significant impact on all aspects of people's lives, especially in the economic sector and community welfare. The impact is in the form of job cuts, limited employment of other workers, and for people who have businesses or act as sellers, there is a decrease in sales turnover. This is the background in the regular KKM 1 Untirta activities in Ramaya Village, Menes District, Pandeglang Regency, education is carried out to the community through nata de coco manufacturing training activities and digital marketing training through market places to the community. Ramaya Villagers mostly work in the agricultural sector where Ramaya Village has the potential for plantation products in the form of coconuts, palm trees and abundant melinjo fruit, for coconut fruit itself has not been optimized for its benefits, only limited to utilization for cooking needs in the household. Educational activities by the KKM 1 Group are carried out gradually, for phase 1 in the form of digital marketing training education activities and stage 2 training in making nata de coco from coconut water. From the results of these educational activities, it is hoped that the people of Ramaya Village can take advantage of the potential of coconut water into food that can be traded through simple marketing and can increase through digital marketing in the market place

Interactive Multi-Modal Motion Planning With Branch Model Predictive Control

Motion planning for autonomous robots and vehicles in presence of uncontrolled agents remains a challenging problem as the reactive behaviors of the uncontrolled agents must be considered. Since the uncontrolled agents usually demonstrate multimodal reactive behavior, the motion planner needs to solve a continuous motion planning problem under these behaviors, which contains a discrete element. We propose a branch Model Predictive Control (MPC) framework that plans over feedback policies to leverage the reactive behavior of the uncontrolled agent. In particular, a scenario tree is constructed from a finite set of policies of the uncontrolled agent, and the branch MPC solves for a feedback policy in the form of a trajectory tree, which shares the same topology as the scenario tree. Moreover, coherent risk measures such as the Conditional Value at Risk (CVaR) are used as a tuning knob to adjust the tradeoff between performance and robustness. The proposed branch MPC framework is tested on an autonomous vehicle planning problem in simulation, and on an autonomous quadruped robot alongside an uncontrolled quadruped in experiments. The result demonstrates interesting human-like behaviors, achieving a balance between safety and performance.

Developing The Educational Game Tool to Improve Reading Ability of Early Childhood

This research aims to developing the educational game tool (word tree) to improve reading ability of early childhood. This is research used Borg & Gall model and has been modified with six steps, they are potential and problem, data collection, product design, design validation, resign revision, and usage trial. The subject is 5-6 years old children in RA Babul Ilmi Rantauparapat. The instrument used is validation questionnaire sheet. Data analysis technique is formulation of mean score percentage and gain score. The research result showed that: (1) the development of educational game too (word tree) is very worthy to be used to improve reading children of 5-6 years old children; and (2) educational game tool (word tree) developed has high level of effectiveness in improving reading ability of 5-6 years old children. This research suggest to the readers, teachers and other researchers to be creative and innovative in designing learning activity, which one of them is developing the product giving real contribution for their students’ ability. This research developed educational game tool in form of word tree that did not only improve children’s reading ability but also create happiness to learn.

Analytical Investigation of Jiatang Scroll Paintings in the Seventh Year of the Guangxu Era

Jiatang scroll paintings listed in the Chinese intangible cultural heritage list are an important form of family trees. In this paper, a Jiatang scroll painting drawn in the seventh year of Guangxu (AD 1881) was chosen as a prototype to analyze its components. Samples were taken from different parts of the Jiatang scroll painting to analyze the composition of fibers, pigments, and adhesives. Herein, fiber analyzer, Fourier transform infrared spectroscopy (FTIR), and Herzberg stain were conducted to identify the type of fiber used. Microstructural and microchemical analyses by means of SEM-EDX and Raman spectroscopy were performed to characterize the pigments present in the painting, while the nature of the adhesive was examined using pyrolysis gas chromatography–mass spectrometry (Py-GC/MS). The results show that the painting fiber is from cotton, while the red, black, and green pigments were identified as cinnabar, carbon black, and emerald green, respectively. Finally, the adhesive is a mixture of animal glue, benzoin gum, and starch. The research results provide a basis for the protection and restoration of this precious cultural heritage in the future.

Scalable Species Tree Inference with External Constraints.

Species tree inference is a basic step in biological discovery, but discordance between gene trees creates analytical challenges and large data sets create computational challenges. Although there is generally some information available about the species trees that could be used to speed up the estimation, only one species tree estimation method that addresses gene tree discordance-ASTRAL-J, a recent development in the ASTRAL family of methods-is able to use this information. Here we describe two new methods, NJst-J and FASTRAL-J, that can estimate the species tree, given a partial knowledge of the species tree in the form of a nonbinary unrooted constraint tree. We show that both NJst-J and FASTRAL-J are much faster than ASTRAL-J and we prove that all three methods are statistically consistent under the multispecies coalescent model subject to this constraint. Our extensive simulation study shows that both FASTRAL-J and NJst-J provide advantages over ASTRAL-J: both are faster (and NJst-J is particularly fast), and FASTRAL-J is generally at least as accurate as ASTRAL-J. An analysis of the Avian Phylogenomics Project data set with 48 species and 14,446 genes presents additional evidence of the value of FASTRAL-J over ASTRAL-J (and both over ASTRAL), with dramatic reductions in running time (20 hours for default ASTRAL, and minutes or seconds for ASTRAL-J and FASTRAL-J, respectively).

A quantitative argumentation-based Automated eXplainable Decision System for fake news detection on social media

Social media is flooded with rumors, which make fake news detection a pressing problem. Many black-box approaches have been proposed to automatically predict the veracity of claims. These methods are lack of interpretability. Thus, we propose a Quantitative Argumentation-based Automated eXplainable Decision-making System (QA-AXDS) to tackle this problem and provide users with explanations about the results. The system is fully data-driven in its processes, which allows our models to make greater use of data and be more automatic and scalable than other quantitative framework models. In terms of interpretability, the system can automatically acquire human-level knowledge, and interact with users in the form of dialog trees through explanatory models, thus helping them understand the internal reasoning process of the system. The experimental results show that our system has better transparency and interpretability than other approaches based on the pure machine learning methods, and performs competitively in accuracy among others. In addition, the explanation model provides a way to improve the algorithms when some problems are identified by checking the explanations.

Tree-to-Shrub Shift Benefits the Survival of Quercus mongolica Fisch. ex Ledeb. at the Xeric Timberline

Woody species are either trees or shrubs, with the exception of approximately 9.2% “trub” species exhibiting both tree and shrub growth forms. Little is known thus far about the ecological importance of plant growth-form plasticity under a drying climate. Quercus mongolica Fisch. ex Ledeb., a dominant tree species of temperate forests in East Asia, typically shows tree-to-shrub growth-form shifts at the xeric timberline and is suitable to test whether growth-form plasticity can physiologically benefit plant drought acclimation. We quantified the tree architecture, drought stress, physiological drought tolerance, and nonstructural carbohydrates of Q. mongolica trees and shrubs on the opposite slope of the same mountain at the xeric timberline in July 2018. Compared with Q. mongolica trees on shady slopes, the shrubs on sunny slopes had less available water to use and were more severely threatened by drought. Moreover, the shrubs had stronger tolerance to drought but still tended to have less nonstructural carbohydrate accumulation. The tree-to-shrub shift effectively benefits the survival of Q. mongolica under a dry climate and may strongly contribute to forest dynamics and even fire regimes under climate drying, especially for sensitive ecosystems such as the xeric timberline, which will be vulnerable under future climate change scenarios.