Tree Generation Research Articles

A Combined Strategy for Path Planning of Tensegrity Manipulators Considering Structural Stability

Abstract A strategy combining an improved rapidly exploring random tree (RRT) method with the artificial potential field (APF) method is proposed for the path planning of flexible tensegrity manipulators considering typical complex constraints, such as structural stability, obstacle avoidance, and cable no-slackening. The relationship between the node displacements and the elongations of active members is established for the kinematic analysis of tensegrity manipulators. The rest lengths of active members are taken as the design variables for the generation of a random tree. The guide node is utilized for goal-biased samplings to expedite the exploration toward the final configuration, while the APF method is introduced to ensure that the obtained elongations of active members can satisfy the constraint of obstacle avoidance. The proportion of random and goal-biased samplings is adaptively adjusted based on the sampling success rate. Futile random samplings can be significantly reduced by dynamically modifying the random sampling range according to the obtained configuration nearest to the final configuration. The computational procedure of the proposed method is presented. An illustrative flexible tensegrity manipulator is employed to demonstrate the adaptability of the proposed path planning method to complex constraints, especially structural stability.

AMBER: A Modular Model for Tumor Growth, Vasculature and Radiation Response.

Computational models of tumor growth are valuable for simulating the dynamics of cancer progression and treatment responses. In particular, agent-based models (ABMs) tracking individual agents and their interactions are useful for their flexibility and ability to model complex behaviors. However, ABMs have often been confined to small domains or, when scaled up, have neglected crucial aspects like vasculature. Additionally, the integration into tumor ABMs of precise radiation dose calculations using gold-standard Monte Carlo (MC) methods, crucial in contemporary radiotherapy, has been lacking. Here, we introduce AMBER, an Agent-based fraMework for radioBiological Effects in Radiotherapy that computationally models tumor growth and radiation responses. AMBER is based on a voxelized geometry, enabling realistic simulations at relevant pre-clinical scales by tracking temporally discrete states stepwise. Its hybrid approach, combining traditional ABM techniques with continuous spatiotemporal fields of key microenvironmental factors such as oxygen and vascular endothelial growth factor, facilitates the generation of realistic tortuous vascular trees. Moreover, AMBER is integrated with TOPAS, an MC-based particle transport algorithm that simulates heterogeneous radiation doses. The impact of radiation on tumor dynamics considers the microenvironmental factors that alter radiosensitivity, such as oxygen availability, providing a full coupling between the biological and physical aspects. Our results show that simulations with AMBER yield accurate tumor evolution and radiation treatment outcomes, consistent with established volumetric growth laws and radiobiological understanding. Thus, AMBER emerges as a promising tool for replicating essential features of tumor growth and radiation response, offering a modular design for future expansions to incorporate specific biological traits.

Rethinking large scale phylogenomics with PhyloToL 6, a flexible toolkit to enable phylogeny-informed data curation and analysis.

The bulk of eukaryotic diversity is microbial, with macroscopic lineages such as plant, animals and fungi nesting among a plethora of diverse lineages that include amoebae, flagellates, ciliates, and many types of algae. Our understanding of the evolutionary relationships and genome properties of microbial eukaryotes is rapidly advancing through analyses of omics (transcriptomic, genomic) data. However, phylogenomic analyses are challenging for microeukaryotes, and particularly uncultivable lineages, as single-cell approaches generate a mixture of sequence data from hosts, associated microbiomes, and contaminants. Current practices include resampling of hand-curated gene sets that can be difficult for other researchers to replicate. To address these challenges, we present PhyloToL version 6.0, a modular, user-friendly pipeline that enables effective data curation that includes phylogeny-informed contamination removal, estimation of homologous gene families, and generation of both multisequence alignments and gene trees. We provide several databases that will be of use for those interested in eukaryotic evolution: a Hook Database of curated reference sequences for 15,000 gene families; a database of transcriptome and genomes from 1,000 taxa with GFs assigned; and a highly-curated set of MSA and gene trees for 500 GFs in these taxa. We also demonstrate a suite of stand-alone utilities that provide basic statistics on sequences, analyze compositional/codon patterns, and enable exploration of trees (e.g. clade-grabbing and efficient tip labeling). We exemplify the power of PhyloToL 6.0 in estimating eukaryotic phylogeny using the 500 conserved GFs, and set standards for curation of omics data for future research in the field.

Mapping pathogenic fungi in decayed Norway spruce stands: Insights from harvester positional data

Abstract Root and butt rot caused by pathogenic fungi in the genera Heterobasidion and Armillaria is a pressing issue in managed Norway spruce forests. The disease results in financial losses for the forest owners and reduces the volume of wood that can be used in long‐lived products. Pathogenic wood decay fungi spread either with the aid of airborne spores or via mycelial growth among neighbouring trees, the latter leading to clustering (tendency of decayed trees to be in close proximity relative to their neighbouring trees) of decay‐affected trees in forests. Understanding the spatial patterns of the decay‐affected trees at the forest stand level is vital for designing management strategies to address this problem. We examined decay clustering in 273 clear‐cut Norway spruce stands in Norway using harvester‐recorded data on spatial occurrence of decayed and healthy Norway spruce trees. We tested clustering using three global‐cluster tests that account for population density and distribution, evaluating clustering without identifying specific cluster locations. The proportions of clustered and non‐clustered stands differed depending on the statistical test used for clustering assessment, resulting in overall agreement of 32.8% for clustered and 36.9% for non‐clustered. Clustered stands exhibited a median cluster distance (maximum distance between the decay‐affected trees within a cluster) of 12 m (Inter‐Quantile Range, IQR, 6–20 m) and a median of 6 (IQR 3–16) nearest neighbour trees (number of decayed trees forming a cluster), estimates comparable with prior studies focused on assessment of trees infected by mycelial spread of the same fungal individual. The decay incidence in the clustered stands was 16.24%, while the non‐clustered stands had a butt‐rot incidence of 20.97%. In clustered stands the average number of trees per hectare was higher (693) than in non‐clustered stands (553). Synthesis and applications: Our study demonstrates that Norway spruce stands display a diverse range of spatial patterns of butt rotted trees. We found that higher densities of Norway spruce trees probably facilitate the vegetative spread of pathogenic wood decay fungi, leading to clustering of decay‐affected trees. To disrupt the spread of decay fungi between tree generations, precision planting of trees other than Norway spruce around infested stumps of prior generation trees has been recommended by earlier studies. We discussed the potential of using harvester‐derived geoposition data for butt‐rotted trees upon planning and execution of forest regeneration.

Regeneration of the Austrian forests and browsing impact – Insights from the latest National Forest Inventory

Abstract The initial development stage of forests forms the basis for the future tree generation. Various driving and interacting factors determine the regeneration process at small and large scale. Based on the latest Austrian National Forest Inventory 2016–2021 the regeneration assessments and estimation methods were collated. Analyses were conducted to estimate the forest area regarding regeneration necessity and occurrence, the causes of regeneration deficits, the origin from natural and artificial regeneration, tree species occurrence as well as browsing impact. The results show a sea level gradient of increasing shares of necessary but missing regeneration, ranging between 15% at the lowest and 60% at the highest altitudes. Accordingly, high shares can be found in protective forest without yield (50%) and in the growth regions of the mountainous areas of the Alps (up to 40%). Due to the multitude of driving and interacting factors, the assessed causes of regeneration deficits show divers patterns. Light as a limiting factor appears to be more relevant at low altitudes, and competition through ground vegetation is highest at low and high altitudes. The influence of the humus layer on the seed bed was assessed to increase with altitude, as well as the impact of forest pasture, while game browsing as cause of regeneration deficits show no clear tendency over the analysed strata. About 91% of the necessary and occurring regeneration originates from natural regeneration and the remaining from artificial or a mixture of both regeneration types. The number of tree species in the ground vegetation layer decreases with altitude. Considering browsing impact the results show percentages of affected areas between 40% and 80%. The highest browsing impacts were found at intermediate altitudes between 600 and 1,500 m above sea level. From a large-scale perspective as provided by NFIs, the results show divers patterns of regeneration necessity and occurrence and impacts on the regeneration. Representative large-scale monitoring by NFIs provides the opportunity to identify and quantify the adverse impacts and forest strata that are affected by regeneration deficits, and therefore support the development of forest management strategies that aim at the establishment of the future tree generation under changing climate conditions.

Dynamic Fault Tree Generation and Quantitative Analysis of System Reliability for Embedded Systems Based on SysML Models.

As embedded systems become increasingly complex, traditional reliability analysis methods based on text alone are no longer adequate for meeting the requirements of rapid and accurate quantitative analysis of system reliability. This article proposes a method for automatically generating and quantitatively analyzing dynamic fault trees based on an improved system model with consideration for temporal characteristics and redundancy. Firstly, an "anti-semantic" approach is employed to automatically explore the generation of fault modes and effects analysis (FMEA) from SysML models. The evaluation results are used to promptly modify the system design to meet requirements. Secondly, the Profile extension mechanism is used to expand the SysML block definition diagram, enabling it to describe fault semantics. This is combined with SysML activity diagrams to generate dynamic fault trees using traversal algorithms. Subsequently, parametric diagrams are employed to represent the operational rules of logic gates in the fault tree. The quantitative analysis of dynamic fault trees based on probabilistic models is conducted within the internal block diagram of SysML. Finally, through the design and simulation of the power battery management system, the failure probability of the top event was obtained to be 0.11981. This verifies that the design of the battery management system meets safety requirements and demonstrates the feasibility of the method.

Case-Based Deduction for Entailment Tree Generation

Maintaining logical consistency in structured explanations is critical for understanding and troubleshooting the reasoning behind a system’s decisions. However, existing methods for entailment tree generation often struggle with logical consistency, resulting in erroneous intermediate conclusions and reducing the overall accuracy of the explanations. To address this issue, we propose case-based deduction (CBD), a novel approach that retrieves cases with similar logical structures from a case base and uses them as demonstrations for logical deduction. This method guides the model toward logically sound conclusions without the need for manually constructing logical rule bases. By leveraging a prototypical network for case retrieval and reranking them using information entropy, CBD introduces diversity to improve in-context learning. Our experimental results on the EntailmentBank dataset show that CBD significantly improves entailment tree generation, achieving performance improvements of 1.7% in Task 1, 0.6% in Task 2, and 0.8% in Task 3 under the strictest Overall AllCorrect metric. These findings confirm that CBD enhances the logical consistency and overall accuracy of AI systems in structured explanation tasks.

Post-Pyrogenic Successions in Oak-Korean Pine Forests with Schisandra chinensis and Corylus mandshurica in Sikhote-Alin

This article discusses the results of long-term stationary studies of the formation and development of oak-cedar pine forests with magnolia berry and hazel growing in the Southern and Middle Sikhote-Alin. Considered here are the peculiarities of stands decline, seed-based reforestation, as well as the tree species growth and development courses during the process of reforestation successions in areas with different intensity of fire exposure. Following persistent ground fires, the stands decline is most intensive in the first 5 years, with decay rates and the number of surviving trees varying in different types of burnt areas. The most active seed-based reforestation occurs on post-fire sites mainly during the first 2 years, with birch, aspen and other early stage species predominating. The rate of annual growth of the young generation of trees is the most intensive on plots significantly damaged by fire, in serial species (birch, aspen, Maak’s bird cherry, etc.) they are an order of magnitude higher than in climax broadleaved and coniferous species. Determination of dominance indices, equally dependent on the numbers of undergrowth, thin and large trees, showed that during reforestation successions after both rapid and persistent lowland fires, the phytocenotic importance dynamics in Korean pine, Mongolian oak and other forest forming species has its own peculiarities.

Influence of Hydrological and Climatic Changes on Tree Growth in Narew National Park, NE Poland, over the Past 50 Years

Over the last 50 years, groundwater levels have been decreasing and air temperatures have been increasing in Poland. Maintaining this trend may make it impossible to maintain hydrogenic habitats in good condition. Reactions to ongoing climate change recorded in tree rings may be a good indicator describing the degree of this threat. The aim of this study was to determine the influence of climatic and hydrological changes on the growth of scotch pine (Pinus sylvestris L.) and black alder (Alnus glutinosa (L.) Gaertn) in the Narew National Park over past 50 years. The research was based on tree increment cores extracted from 42 pine trees and 57 alder trees that were randomly selected and ranged in age from 25 to 88 years, as well as climatic and hydrological data. Standardised data (5-year index) were analysed by species, generation (Y—21–40 years, M—41–60, O—61–90), and decade using correlation analysis. The results of the study show that pine responded more strongly to changes in air temperature and changes in precipitation totals, while alder growth was more strongly related to fluctuations in the water level of the Narew River and changes in precipitation totals. Our research showed that differences in response to environmental factors also occur between tree generations. The decrease in the water level of the Narew River that occurred over the last 50 years did not adversely affect the condition of the trees. Analysis of DBH growth rates showed that the younger generations (Y, M) grow faster than the older generation (O). This is positive news for managers of commercial and protected forests, but accelerated tree growth may be associated with specific consequences, such as increased wind damage as a result of reduced wood density or reduced sensitivity of trees to climate and hydrological changes.

Soil Legacies of Tree Species Composition in Mature Forest Affect Tree Seedlings’ Performance

AbstractTrees affect the biotic and abiotic properties of the soil in which they grow. Tree species-specific effects can persist for a long time, even after the trees have been removed. We investigated to what extent such soil legacies of different tree species may impact tree seedlings in their emergence and growth. We performed a plant–soil feedback experiment, using soil that was conditioned in plots that vary in tree species composition in Białowieża Forest, Poland. Soil was taken from plots varying in proportion of birch, hornbeam, pine, and oak. In each soil, seeds of the same four target species were sown in pots. Seedling emergence and growth were monitored for one growing season. To further explore biotic implications of soil legacies, ectomycorrhizal root tip colonization of oak, a keystone forest species, was determined. We found no effect of soil legacies of tree species on the emergence measures. We, however, found a clear negative effect of pine legacies on the total biomass of all four seedling species. In addition, we found relationships between the presence of pine and soil fertility and between soil fertility and root tip colonization. Root tip colonization was positively correlated with the biomass of oak seedlings. We conclude that tree species can leave legacies that persist after that species has been removed. These legacies influence the growth of the next generation of trees likely via abiotic and biotic pathways. Thus, the choice of species in today’s forest may also matter for the structure and composition of future forests.

In Silico Design of Heterogeneous Microvascular Trees Using Generative Adversarial Networks and Constrained Constructive Optimization.

Designing physiologically adequate microvascular trees is of crucial relevance for bioengineering functional tissues and organs. Yet, currently available methods are poorly suited to replicate the morphological and topological heterogeneity of real microvascular trees because the parameters used to control tree generation are too simplistic to mimic results of the complex angiogenetic and structural adaptation processes invivo. We propose a method to overcome this limitation by integrating a conditional deep convolutional generative adversarial network (cDCGAN) with a local fractal dimension-oriented constrained constructive optimization (LFDO-CCO) strategy. The cDCGAN learns the patterns of real microvascular bifurcations allowing for their artificial replication. The LFDO-CCO strategy connects the generated bifurcations hierarchically to form microvascular trees with a vessel density corresponding to that observed in healthy tissues. The generated artificial microvascular trees are consistent with real microvascular trees regarding characteristics such as fractal dimension, vascular density, and coefficient of variation of diameter, length, and tortuosity. These results support the adoption of the proposed strategy for the generation of artificial microvascular trees in tissue engineering as well as for computational modeling and simulations of microcirculatory physiology.

Habitat requirements of deadwood-dependent invertebrates that occupy tree hollows.

Tree hollows support a specialised species-rich fauna. We review the habitat requirements of saproxylic (= deadwood dependent) invertebrates which occupy tree hollows. We focus on studies quantifying relationships between species occurrence patterns and characteristics of tree hollows, hollow trees, and the surrounding landscape. We also explore the processes influencing species occurrence patterns by reviewing studies on the spatio-temporal dynamics of populations, including their dispersal and genetic structure. Our literature search in the database Scopus identified 52 relevant publications, all of which were studies from Europe. The dominant taxonomic group studied was beetles. Invertebrates in hollow trees were often more likely to be recorded in trees with characteristics reflecting a large amount of resources or a stable and warm microclimate, such as a large diameter, large amounts of wood mould (= loose material accumulated in the hollows mainly consisting of decaying wood), a high level of sun exposure, and with entrance holes that are large and either at a low or high height, and in dry hollows, with entrances not directed upwards. A stable microclimate is probably a key factor why some species of saproxylic invertebrates are confined to tree hollows. Other factors that are different in comparison to downed dead wood is the fact that hollows at a given height from the ground provide shelter from ground-living predators, that hollows persist for longer, and that the content of nutrients might be enhanced by the accumulation of dead leaves, insect frass, and remains from dead insects. Several studies have identified a positive relationship between species occupancy per tree and the amount of habitat in the surrounding landscape, with a variation in the spatial scale at which characteristics of the surrounding landscape had the strongest effect over spatial scales from 200 to 3000 m. We found empirical support for the extinction threshold hypothesis, which predicts that the frequency of species presence per tree is greater if a certain number of trees are aggregated into a few large clusters of hollow trees rather than distributed among many small clusters. Observed thresholds in species occurrence patterns can be explained by colonisation-extinction dynamics, with species occupancy per tree influenced by variation in rates of immigration. Consistent with this assumption, field studies suggest that dispersal rate and range can be low for invertebrates occupying tree hollows, although higher in a warmer climate. For one species in which population dynamics has been studied over 25 years (Osmoderma eremita), the observed population dynamics have characteristics of a "habitat-tracking metapopulation", as local extinctions from trees occur possibly because those trees become unsuitable as well as due to stochastic processes in small populations. The persistence of invertebrate fauna confined to tree hollows may be improved by prolonging the standing life of existing hollow trees. It is also important to recruit new generations of hollow trees, preferably close to existing larger groups of hollow trees. Thus, the spatio-temporal dynamics of hollow trees is crucial for the invertebrate fauna that rely upon them.

VSNP: a SNP pipeline for the generation of transparent SNP matrices and phylogenetic trees from whole genome sequencing data sets

BackgroundSeveral single nucleotide polymorphism (SNP) pipelines exist, each offering its own advantages. Among them and described here is vSNP that has been developed over the past decade and is specifically tailored to meet the needs of diagnostic laboratories. Laboratories that aim to provide rapid whole genome sequencing results during outbreak investigations face unique challenges. vSNP addresses these challenges by enabling users to verify and validate sequence accuracy with ease- having utility across various pathogens, being fully auditable, and presenting results that are easy to interpret and can be comprehended by individuals with diverse backgrounds.ResultsvSNP has proven effective for real-time phylogenetic analysis of disease outbreaks and eradication efforts, including bovine tuberculosis, brucellosis, virulent Newcastle disease, SARS-CoV-2, African swine fever, and highly pathogenic avian influenza. The pipeline produces easy-to-read SNP matrices, sorted for convenience, as well as corresponding phylogenetic trees, making the output easily understandable. Essential data for verifying SNPs is included in the output, and the process has been divided into two steps for ease of use and faster processing times. vSNP requires minimal computational resources to run and can be run in a wide range of environments. Several utilities have been developed to make analysis more accessible for subject matter experts who may not have computational expertise.ConclusionThe vSNP pipeline integrates seamlessly into a diagnostic workflow and meets the criteria for quality control accreditation programs, such as 17025 by the International Organization for Standardization. Its versatility and robustness make it suitable for use with a diverse range of organisms, providing detailed, reproducible, and transparent results, making it a valuable tool in various applications, including phylogenetic analysis performed in real time.

Structured Generation Method of 3D Synthetic Tree Models for Precision Assessment

Abstract. The technology for 3D reconstruction of tree models based on point clouds has been extensively researched, necessitating effective datasets for the study of branch and leaf separation, skeleton point extraction, and tree parameter extraction methods. However, existing datasets for 3D tree models face several challenges, including insufficient data volume for deep learning network training, low accuracy of model ground truth impeding effective method precision evaluation, and a lack of dataset richness to satisfy the needs of multi-type method assessments. In response to these challenges, This paper introduces, for the first time, a fully automated method for generating structured three-dimensional synthetic tree models, and constructs a large-scale 3D synthetic tree dataset enriched with comprehensive structural information. This method facilitates automated computation across several processes, including the mass generation of simulated trees, separation of branches and leaves, noise generation, extraction of skeleton points, and volume calculation. To validate the usability of this dataset across various applications, this paper employs state-of-the-art (SoTA) algorithms to verify the accuracy of methods in 3D tree model reconstruction and carbon stock calculation, thereby thoroughly demonstrating the dataset’s effectiveness.

A climate-induced tree species bottleneck for forest management in Europe.

Large pulses of tree mortality have ushered in a major reorganization of Europe's forest ecosystems. To initiate a robust next generation of trees, the species that are planted today need to be climatically suitable throughout the entire twenty-first century. Here we developed species distribution models for 69 European tree species based on occurrence data from 238,080 plot locations to investigate the option space for current forest management in Europe. We show that the average pool of tree species continuously suitable throughout the century is smaller than that under current and end-of-century climate conditions, creating a tree species bottleneck for current management. If the need for continuous climate suitability throughout the lifespan of a tree planted today is considered, climate change shrinks the tree species pool available to management by between 33% and 49% of its current values (40% and 54% of potential end-of-century values), under moderate (Representative Concentration Pathway 2.6) and severe (Representative Concentration Pathway 8.5) climate change, respectively. This bottleneck could have strong negative impacts on timber production, carbon storage and biodiversity conservation, as only 3.18, 3.53 and 2.56 species of high potential for providing these functions remain suitable throughout the century on average per square kilometre in Europe. Our results indicate that the option space for silviculture is narrowing substantially because of climate change and that an important adaptation strategy in forestry-creating mixed forests-might be curtailed by widespread losses of climatically suitable tree species.

Ash seedlings in a reciprocal transplant experiment—the extent of damage of mature forest stands affects ash offspring performance

In past decades, ash dieback has caused a rapid decline of European ash (Fraxinus excelsior) in temperate forests of Europe. Numerous studies focus on mitigating the negative impacts of ash dieback to forest ecosystems or identifying resistant genotypes. The role of natural selection toward genotypes withstanding ash dieback for ash regeneration has been less frequently studied with experimental means to date. This is, however, necessary in times of global change, because the preservation of ash in Europe’s forests will depend, above all, on the adaptability of the future generations of ash trees. To quantify the extent and effects of ash dieback severity for ash regeneration we selected five forest stands moderately damaged and five forest stands highly damaged by ash dieback, in Schleswig-Holstein, Germany. We reciprocally transplanted naturally regenerated ash seedlings sampled in the field between these 10 sites. A shading treatment added to each half of the plots per site was meant to test for effects of altered light conditions in the herb layer due to canopy opening caused by ash dieback. With this approach, we tested seedling survival, performance and fungal infection for an interacting effect of origin and target site in regard to ash dieback severity and environmental factors over 2 years and recorded leaf traits (specific leaf area, leaf dry matter content) in the second year. Reduced light conditions under the shading nets had strong effects, influencing first year performance and infection probability as well as second year survival, growth and leaf trait characteristics. Soil conditions had only a marginal influence on transplanted seedlings. Transplantation direction between moderately and highly damaged sites affected infection marginally during the first year and survival as well as leaf traits significantly during the second year. Most notably, seedlings transplanted from moderately damaged to severely damaged sites exhibited the highest infection probability and lowest SLA, while seedlings transplanted vice versa were least likely to be infected and exhibited the highest SLA. Results hint at a first filtering effect by the ash dieback history of a forest stand and might indicate a transition from ecologically to evolutionary driven differentiation of ash seedling responses.

Transport and deposition of microplastics and nanoplastics in the human respiratory tract

Recent studies have unveiled the presence of nano- and microplastics (NMPs) within both human and avian respiratory systems, prompting an exploration into the interactions between these particles and the human respiratory system. Experimental evidence has strongly suggested that these plastic particles amplify human susceptibility to a spectrum of lung disorders, including chronic obstructive pulmonary disease, fibrosis, dyspnea, asthma, and the formation of frosted glass nodules. To advance the understanding, this study employs computational fluid-particle dynamics (CFPD) to study the transfer and deposition of poly-dispersed 1-100 nm nanoplastics and 1-100 μm microplastics under three breathing conditions. Notably, this investigation utilized a computerized tomography-based full respiratory tract model, comprehensively spanning regions from the nasal cavity to the 13th generation of the bronchial tree, providing a highly detailed representation of the anatomical complexities of the human respiratory system. The outcomes reveal distinctive deposition patterns of spherical, cylindrical, and tetrahedral NMPs in the human respiratory tract, elucidating the significant impact of breathing rate, pinpointing specific deposition hotspots, and highlighting the critical role of particle size in governing transport and deposition behavior. This study establishes a link between the behavior of nanoplastics within the respiratory tract and its consequential impact, providing insights that extend across three critical domains. Firstly, in environmental health, the research contributes to understanding NMP-related air pollution. Secondly, within respiratory medicine, the findings shed light on NMPs' role in respiratory disorders. Finally, this study guides the formulation of regulations addressing permissible NMP levels and mitigating associated health and environmental risks.

Analyzing Argumentative Texts Produced by English Education Master's Students at UIN Syarif Hidayatullah Jakarta

This research investigates the grammatical construction and common logical problems in argumentative essays produced by Master of English Education students at UIN Syarif Hidayatullah Jakarta. This study utilized a qualitative research framework and content analysis as the design. The data collection involves a detailed syntactical analysis, facilitated by Shang’s syntax tree generator, with the researcher actively engaged in the evaluation and categorization of grammatical and logical elements. The main arguments are identified, and connections to the overarching thesis are established. Systematic coding is applied to categorize findings, encompassing sentence structure, evidence usage, tone, logical connectives, cohesions, counterarguments, and identification of logical fallacies. Findings reveal notable technical errors in sentence construction, especially in constructing complex sentences. Moreover, difficulties in understanding the appropriate genre in argumentative writing and logical errors in expressing opinions and drawing conclusions are identified. This study discovered that students encounter difficulties in maintaining a coherent and logically sound progression of ideas throughout their essays.

Stochastic Modelling Frameworks for Dragon Fruit Supply Chains in Vietnam under Uncertain Factors

Managing uncertainties and risks is always a difficult but fascinating task in fresh fruit supply chains, especially when dealing with the strategy for the production and conveyance of fresh fruit in Vietnam. Following the COVID-19 outbreak, the confluence of economic recession and persistent adverse weather conditions has exacerbated challenges faced by dragon fruit cultivators. This research investigates a two-stage stochastic programming (TSSP) approach which is developed and served as a valuable tool for analyzing uncertainties, optimizing operations, and managing risks in the fresh fruit industry, ultimately contributing to the sustainability and resilience of supply chains in the agricultural sector. A prototype is provided to illustrate the complex and dynamic nature of dragon fruit cultivation and consumption in Vietnam. Data on the selling prices of dragon fruit were collected from several sources between 2013 and 2022 in Binh Thuan Province, Vietnam. The results were obtained from the model by using three different approaches in order of their versatility and efficacy: (1) Scenario tree generation; (2) Sample average approximation; (3) Chance-constrained programming.

Vine copula‐based scenario tree generation approaches for portfolio optimization

AbstractThis paper presents an efficient heuristic to generate multi‐stage scenario trees for portfolio selection problems. In the case of two or more risky assets, investors need to account for the complex multivariate dependence among different assets. The dependence patterns have shown not only asymmetric and fat tails but also time‐varying, and the upper and lower tails have different effect on portfolio management. In this paper, we design a new scenario generation method by combining the GARCH‐type model and vine copula model to properly reflect these complex dependence patterns in multiple assets in a flexible way. A multi‐stage scenario tree is generated sequentially from this model by simultaneously utilizing the simulation and clustering methods. The scenarios' nodal probabilities are determined by solving an improved moment matching model, whose objective is to maintain the central moments and lower tails of the original distribution. The resulting scenario trees are then tested on a multi‐stage portfolio selection model. The experimental results prove the efficiency and advantages of our proposed scenario generation method over other existing models or methods and the positive influence of moment matching on our method.