Original Tree Research Articles

Phylogenetic origin of Magnolia pseudokobus (Magnoliaceae), a rare Magnolia extinct in the wild, revealed by chloroplast genome sequencing, genome-wide SNP genotyping and microsatellite analysis

ABSTRACT The phylogenetic origin of endangered species extinct in the wild is not always well understood, as a consequence of limited historical records of the original populations. Magnolia pseudokobus (Magnoliaceae) is one of only a few such woody plants in Japan. This triploid species was described in 1954 on Shikoku Island, but since then, no other individuals have been found in other locations. Currently, the only genet clonally propagated from the original tree can be seen in botanic gardens. In this study, we aimed to phylogenetically position M. pseudokobus by investigating genetic variations in the chloroplast genome, genome-wide SNPs, and microsatellites of focal and related species. Phylogenetic trees based on the chloroplast genome and nuclear single nucleotide polymorphism (SNP) markers consistently showed that M. pseudokobus is well embedded within a clade consisting of M. kobus samples. Microsatellite analysis on a seedling of M. pseudokobus, which was cultivated adjacent to a M. kobus tree, showed that it was an interspecific hybrid. The genetic data suggest that M. pseudokobus was generated recently from M. kobus, allowing for the production of viable seedlings. Considering that the species is triploid and is not agamospermous, and any wild populations of M. kobus are not known from Shikoku Island, M. pseudokobus may be a ploidy variant of M. kobus, generated by spontaneous triploidization in M. kobus individual(s), which were possibly introduced by humans as ornamental tree(s). In conclusion, M. pseudokobus appears to be conspecific with M. kobus, and better recognized as M. kobus f. pseudokobus.

Relation Extraction with Convolutional Network over Learnable Syntax-Transport Graph

A large majority of approaches have been proposed to leverage the dependency tree in the relation classification task. Recent works have focused on pruning irrelevant information from the dependency tree. The state-of-the-art Attention Guided Graph Convolutional Networks (AGGCNs) transforms the dependency tree into a weighted-graph to distinguish the relevance of nodes and edges for relation classification. However, in their approach, the graph is fully connected, which destroys the structure information of the original dependency tree. How to effectively make use of relevant information while ignoring irrelevant information from the dependency trees remains a challenge in the relation classification task. In this work, we learn to transform the dependency tree into a weighted graph by considering the syntax dependencies of the connected nodes and persisting the structure of the original dependency tree. We refer to this graph as a syntax-transport graph. We further propose a learnable syntax-transport attention graph convolutional network (LST-AGCN) which operates on the syntax-transport graph directly to distill the final representation which is sufficient for classification. Experiments on Semeval-2010 Task 8 and Tacred show our approach outperforms previous methods.

The improvement of the shear stress and oscillatory shear index of coronary arteries during Enhanced External Counterpulsation in patients with coronary heart disease.

Enhanced External Counterpulsation (EECP) can chronically relieve ischemic chest pain and improve the prognosis of coronary heart disease (CHD). Despite its role in mitigating heart complications, EECP and the mechanisms behind its therapeutic nature, such as its effects on blood flow hemodynamics, are still not fully understood. This study aims to elucidate the effect of EECP on significant hemodynamic parameters in the coronary arterial tree. A finite volume method was used in conjunction with the inlet pressure wave (surrogated by the measured aortic pressure) before and during EECP and outlet flow resistance, assuming the blood as newtonian fluid. The time-average wall shear stress (TAWSS) and oscillatory shear index (OSI) were determined from the flow field. Regardless of the degree of vascular stenosis, hemodynamic conditions and flow patterns could be improved during EECP. In comparison with the original tree, the tree with a severe stenosis (75% area stenosis) demonstrated more significant improvement in hemodynamic conditions and flow patterns during EECP, with surface area ratio of TAWSS risk area (SAR-TAWSS) reduced from 12.3% to 6.7% (vs. SAR-TAWSS reduced from 7.2% to 5.6% in the original tree) and surface area ratio of OSI risk area (SAR-OSI) reduced from 6.8% to 2.5% (vs. SAR-OSI of both 0% before and during EECP in the original tree because of mild stenosis). Moreover, it was also shown that small ratio of diastolic pressure (D) and systolic pressure (S) (D/S) could only improve the hemodynamic condition mildly. The SAR-TAWSS reduction ratio significantly increased as D/S became larger. A key finding of the study was that the improvement of hemodynamic conditions along the LMCA trees during EECP became more significant with the increase of D/S and the severity degree of stenoses at the bifurcation site. These findings have important implications on EECP as adjuvant therapy before or after percutaneous coronary intervention (PCI) in patients with diffuse atherosclerosis.

Twenty-Five Years after Stand Thinning and Repeated Fertilization in Lodgepole Pine Forest: Implications for Tree Growth, Stand Structure, and Carbon Sequestration

Silvicultural practices such as pre-commercial thinning (PCT) and repeated fertilization have been used successfully around the world to increase forest biomass for conventional wood products, biofuels, and carbon sequestration. Two complementary studies were designed to test the hypotheses (H) that large-scale PCT and PCT with repeated fertilization of young (13–17 years old) lodgepole pine (Pinus contorta var. latifolia) stands, at 25 years after the onset of treatments, would enhance (H1) productivity and structural features (diameter and height growth, crown volume and dimensions) of crop trees; (H2) merchantable volume of crop trees, (H3) abundance of understory conifer, herb and shrub layers, and (H4) carbon storage (sequestration) of all layers. Results are from two studies in south-central British Columbia, Canada. The PCT study had three densities: 500, 1000, and 2000 stems/ha, an unthinned, and old-growth stand replicated at three areas. The PCT-FERT study had four densities: 250, 500, 1000, and 2000 stems/ha with and without a repeated fertilization treatment, and an unthinned-unfertilized stand, replicated at two areas. Heavily thinned (≤1000 stems/ha) and fertilized stands generally had larger mean diameters and crown dimensions than lightly thinned or unfertilized stands, whereas mean heights of crop trees remained relatively unaffected, and hence partial support for H1. Despite differences in stand density (4- and 8-fold) of original crop trees, ingress of intermediate crop trees over the 25 years changed density dramatically. There was no support for H2, as mean merchantable volume of total crop trees was similar across stand densities owing to ingress, and was also similar in fertilized and unfertilized stands. In stands thinned to ≤500 trees/ha, there is an anticipated increase in crop tree density of 2.2 to 4.3 times over 25 years compared with the original post-thinning densities. Mean abundance of understory conifers was generally similar among stands owing to successional development towards canopy closure, whereas herbs and shrubs persisted only in canopy gaps in heavily thinned stands, thereby providing no support for H3. Mean carbon storage was similar across densities in both studies with ingress contributing a considerable amount to carbon sequestration at the lower densities. Fertilization increased (1.4 times) mean carbon storage significantly among total crop trees, total conifers, and the grand total of all layers, thereby providing partial support for H4. Thus, much of the potential above-ground carbon storage lost by thinning was restored in the heavily thinned stands at 25 years post-treatment.

A failure modes and effects analysis quality management framework for image-guided small animal irradiators: A change in paradigm for radiation biology.

Image-guided small animal irradiators (IGSAI) are increasingly being adopted in radiation biology research. These animal irradiators, designed to deliver radiation with submillimeter accuracy, exhibit complexity similar to that of clinical radiation delivery systems, including image guidance, robotic stage motion, and treatment planning systems. However, physics expertise and resources are scarcer in radiation biology, which makes implementation of conventional prescriptive QA infeasible. In this study, we apply the failure modes and effect analysis (FMEA) popularized by the AAPM task group 100 (TG-100) report to IGSAI and radiation biological research. Radiation biological research requires a change in paradigm where small errors to large populations of animals are more severe than grievous errors that only affect individuals. To this end, we created a new adverse effects severity table adapted to radiation biology research based on the original AAPM TG-100 severity table. We also produced a process tree which outlines the main components of radiation biology studies performed on an IGSAI, adapted from the original clinical IMRT process tree from TG-100. Using this process tree, we created and distributed a preliminary survey to eight expert IGSAI operators in four institutions. Operators rated proposed failure modes for occurrence, severity, and lack of detectability, and were invited to share their own experienced failure modes. Risk probability numbers (RPN) were calculated and used to identify the failure modes which most urgently require intervention. Surveyed operators indicated a number of high (RPN >125) failure modes specific to small animal irradiators. Errors due to equipment breakdown, such as loss of anesthesia or thermal control, received relatively low RPN (12-48) while errors related to the delivery of radiation dose received relatively high RPN (72-360). Errors identified could either be improved by manufacturer intervention (e.g., electronic interlocks for filter/collimator) or physics oversight (errors related to tube calibration or treatment planning system commissioning). Operators identified a number of failure modes including collision between the collimator and the stage, misalignment between imaging and treatment isocenter, inaccurate robotic stage homing/translation, and incorrect SSD applied to hand calculations. These were all relatively highly rated (90-192), indicating a possible bias in operators towards reporting high RPN failure modes. The first FMEA specific to radiation biology research was applied to image-guided small animal irradiators following the TG-100 methodology. A new adverse effects severity table and a process tree recognizing the need for a new paradigm were produced, which will be of great use to future investigators wishing to pursue FMEA in radiation biology research. Future work will focus on expanding scope of user surveys to users of all commercial IGSAI and collaborating with manufacturers to increase the breadth of surveyed expert operators.

Graph Convolution Over Multiple Latent Context-Aware Graph Structures for Event Detection

Event detection is a particularly challenging problem in information extraction. The current neural network models have proved that dependency tree can better capture the correlation between candidate trigger words and related context in the sentence. However, syntactic information conveyed by the original dependency tree is insufficient for detecting trigger since the dependency tree obtained from natural language processing toolkits ignores semantic context information. Existing approaches employ a static graph structure based on original dependency tree which is incompetent in terms of distinguishing interrelations among trigger words and contextual words. So how to effectively make use of relevant information while ignoring irrelevant information from the dependency trees remains a challenging research question. To address this problem, we investigate a graph convolutional network over multiple latent context-aware graph structures to perform event detection. We exploit a multi-head attention mechanism on BERT representation and original adjacency matrix to generate multiple latent context-aware graph structures (a “dynamic cutting” strategy), which can automatically learn how to select the useful dependency information. Furthermore, we investigate graph convolutional networks with residual connections to combine the local and non-local contextual information. Experimental results on ACE2005 dataset show that our model achieves competitive performances compared with the methods based on dependency tree for event detection.

A Gray Box for Visualizing Instruction Sequence Based on Improved Suffix Tree

Gray box is a kind of device in which the working process of a program or system is locally recognized. Gray box testing, also known as gray box analysis, is a software debugging method based on the limited cognition of the internal details of the program. Testers may know how system components interact with each other, but they lack a detailed understanding of internal program functions and operation. So the construction of gray box is particularly important. The most original gray boxes are static debugger and dynamic debugger. And then reflexion model, which reduces the manual work greatly, is developed and applied. The latest gray boxes are focus on regarding instructions as a natural language using the mature mathematical model to mine their internal value. Adhering to the idea of latest researches, our paper improves the original suffix tree and use the improved suffix tree as a mathematical models to analyse and visualize the internal logic of instructions. Our gray box aims at solving three problems in practical application. In addition, we explain the complexity of instruction sequence and put forward a prediction formula for the building part. By experiment, we prove the time complexity of each part and the correctness of the prediction formula, and show the effect of visualizing part.

Asymptotic enumeration of compacted binary trees of bounded right height

A compacted binary tree is a graph created from a binary tree such that repeatedly occurring subtrees in the original tree are represented by pointers to existing ones, and hence every subtree is unique. Such representations form a special class of directed acyclic graphs. We are interested in the asymptotic number of compacted trees of given size, where the size of a compacted tree is given by the number of its internal nodes. Due to its superexponential growth this problem poses many difficulties. Therefore we restrict our investigations to compacted trees of bounded right height, which is the maximal number of edges going to the right on any path from the root to a leaf.We solve the asymptotic counting problem for this class as well as a closely related, further simplified class.For this purpose, we develop a calculus on exponential generating functions for compacted trees of bounded right height and for relaxed trees of bounded right height, which differ from compacted trees by dropping the above described uniqueness condition. This enables us to derive a recursively defined sequence of differential equations for the exponential generating functions. The coefficients can then be determined by performing a singularity analysis of the solutions of these differential equations.Our main results are the computation of the asymptotic numbers of relaxed as well as compacted trees of bounded right height and given size, when the size tends to infinity.

Autonomous Self-Healing of Electrical Degradation in Dielectric Polymers Using In Situ Electroluminescence

Summary Dielectric polymers are ubiquitous as electrical insulation in electrical power systems and electronic devices. Electrical treeing is typically regarded as an irreversible degradation process of dielectric polymers subjected to high electric stresses, which significantly limits their lifespan and endangers the reliability of electronics and electrical power systems. Here, we report self-healing polymers consisting of microcapsules that are capable of completely restoring the dielectric properties as a direct response to electrical tree degradation. We design the microcapsules with a relatively higher dielectric constant than polymer matrix to guide the propagation of electrical trees. The electroluminescence generated in situ during electrical treeing of polymers triggers crosslinking of the healing agents released from the capsules to repair the electrically damaged areas under ambient conditions. Notably, the breakdown strength of the mended region is largely enhanced upon healing, which was initiated at different locations. The integration of autonomous healing capability into dielectric materials opens new avenues to smart polymers for electronics and energy applications.

Manipulating Chain Type and Flail Drum Speed for Better Fibre Recovery in Chain-Flail Delimber-Debarker-Chipper Operations

A chain-flail delimber-debarker-chipper (CFDDC) was adapted for treating smaller trees than normal by replacing the standard flails with lighter ones, and by reducing flail drum rotation speed. The machine produced 16 full containers (24 t each) for the standard configuration and 24 full containers for the innovative one. For each container the researchers measured: original tree mass, chip mass, time consumption and fuel use. Results indicated that the innovative setting accrued a 12% improvement on fiber recovery compared with the standard setting (control). At the same time, productivity increased by 20% and fuel consumption was reduced by 30%. Product quality was largely unaffected, with bark content remaining below the 1% threshold specification. If at all, product quality was improved through the reduction of fine particles, possibly derived from less diffused fraying. These results have triggered the real scale adoption of the new setting by contractors who participated in the study. The success of the innovative treatment is likely explained by its better alignment with the weaker structure of small trees from low-yielding stands.

Similarity Graph-Based Camera Tracking for Effective 3D Geometry Reconstruction with Mobile RGB-D Camera.

In this paper, we present a novel approach for reconstructing 3D geometry from a stream of images captured by a consumer-grade mobile RGB-D sensor. In contrast to previous real-time online approaches that process each incoming image in acquisition order, we show that applying a carefully selected order of (possibly a subset of) frames for pose estimation enables the performance of robust 3D reconstruction while automatically filtering out error-prone images. Our algorithm first organizes the input frames into a weighted graph called the similarity graph. A maximum spanning tree is then found in the graph, and its traversal determines the frames and their processing order. The basic algorithm is then extended by locally repairing the original spanning tree and merging disconnected tree components, if they exist, as much as possible, enhancing the result of 3D reconstruction. The capability of our method to generate a less error-prone stream from an input RGB-D stream may also be effectively combined with more sophisticated state-of-the-art techniques, which further increases their effectiveness in 3D reconstruction.

Fractal networks induced by movements of random walkers on a tree graph

We show that a fractal, scale-free, and small-world network can grow on a non-fractal Cayley tree through the simple random process of shortcut creation by movements of random walkers. The Cayley tree provides a stage for the walkers to diffuse into a locally one-dimensional structure with the small-world property. Self-organization of fractal graph by adding shortcut edges to the locally one-dimensional structure generated by walkers’ flow from the root vertex to the outermost shell of the Cayley tree is a novel mechanism for generating fractal graphs. Also, we show numerically that the fractal box counting dimension and a power-law exponent describing the degree distribution of the resulting graph are mainly determined by the bifurcation number of the original Cayley tree. In our model, the fractal cluster dimension must change with the size of the evolving graph. This is a general result that resolves an apparent contradiction between the fractality in the context of the cluster-growing method and the small-world property of the graph.

Inverting the cut-tree transform

Nous considérons des fragmentations d’un $\mathbb{R}$-arbre $T$ dirigées par des coupures qui arrivent selon un processus de Poisson sur $T\times[0,\infty)$, où la première composante désigne le point auquel se produit la coupure et le deuxième, l’instant auquel elle a lieu. La généalogie d’une telle fragmentation est codée par l’arbre des coupes, qui a été introduit par Bertoin et Miermont (Ann. Appl. Probab. 23 (4) (2013) 1469–1493) pour une fragmentation de l’arbre brownien. L’arbre des coupes a ensuite été généralisé par Dieuleveut (Ann. Appl. Probab. 25 (4) (2015) 2215–2262) à une fragmentation des arbres $\alpha$-stables, pour $\alpha\in(1,2)$, et par Broutin et Wang (Bernoulli 23 (4A) (2017) 2380–2433) aux arbres continus inhomogènes d’Aldous et Pitman (Probab. Theory Related Fields 118 (4) (2000) 455–482). Dans les deux premiers cas, l’évolution de la suite des masses des sous-arbres apparaissant dans le processus de fragmentation constitue une famille importante de processus de fragmentation auto-similaires de Bertoin (Ann. Inst. Henri Poincaré Probab. Stat. 38 (3) (2002) 319–340); dans le premier cas, une fois inversée dans le temps, la fragmentation devient un coalescent additif. Remarquablement, dans tous ces cas, la loi de l’arbre des coupes est la même que celle du $\mathbb{R}$-arbre initial. Dans cet article, nous développons un cadre général pour l’étude de l’arbre des coupes d’un $\mathbb{R}$-arbre. Par la suite, nous nous concentrons particulièrement sur le problème de la reconstruction : comment retrouver le $\mathbb{R}$-arbre initial à partir de son arbre des coupes. Ce problème a été étudié pour l’arbre brownien par Broutin et Wang (Electron. J. Probab. 22 (2017) 80), qui démontrent qu’il est possible de reconstruire l’arbre initial en loi. Nous décrivons un enrichissement de la construction de l’arbre des coupes, qui dote l’arbre des coupes d’une structure supplémentaire que nous appelons une collection cohérente de routages. Nous démontrons que ce procédé est bien défini sous des conditions minimales sur le $\mathbb{R}$-arbre. Ensuite, nous démontrons que pour l’arbre brownien ainsi que pour l’arbre $\alpha$-stable avec $\alpha\in(1,2)$, l’arbre initial muni de son processus de Poisson de coupures peut être reconstruit presque sûrement à partir de l’arbre des coupes enrichi. Pour ces derniers résultats, nous utilisons de façon essentielle l’auto-similarité et l’invariance par réenracinement de ces $\mathbb{R}$-arbres aléatoires.

Morphological, Pomological, and Specific Molecular Marker Resources for Genetic Diversity Analyses in Fig (Ficus carica L.)

Fig (Ficus carica L.) considers the original cultivated fruit trees and currently has become extinct. Such genetic resources should be identified, documented, and conserved. Morphology, pomology, and molecular markers are successful tools in assessing genetic diversity and classifying fig accessions. Twenty-one cultivated fig (F. carica L.) accessions were collected from Egypt and Libya. In Egypt, fig accessions are dispersed from Sinai in the east to El-Saloom in the west and from Alexandria in the north to Aswan in the south, whereas Libyan accessions were collected from Tubryq, Bengazi, and AlKufrah. Seventeen morphological, pomological, and fruit traits were used to characterize the fig accessions. Moreover, frozen young leaves were used to extract genomic DNA; 13 expressed sequence tag (EST) common fig primer pairs with 12 intersimple sequence repeat (ISSR)-anchored primers were used to detect the genetic diversity. Analysis of variance for fig accessions showed highly significant differences concerning morphological traits, i.e., the leaf length (centimeters) and width (centimeters) ranged from 5.4 and 6 cm to 23 and 23.5 cm, for Komesrey-El-Hammam, Abodey-Giza, and Black_Mission accessions, respectively. Also, fig accessions showed different shapes of leaf edge and fruits; they were categorized into four groups: straight, waved, zigzag, and serrated. The number of leaf lobes data ranged from one lobe for the ‘Green-yellow’, ‘Sultani Red Siwa’, and ‘Sultany Red Amria’ accessions to 10 lobes in the Aswany accession. The two-way hierarchical morphological cluster analysis distributed fig accessions into two main groups. The results detected high genetic diversity for the fig accessions that could be useful in the future breeding programs. Concerning molecular data, the EST markers showed highly polymorphism and informative (r = 0.61; 90.0%), with a total number of identified alleles of 78. We proved that a relatively greater number of alleles per locus characterizes the targeted loci among fig accessions, for which only one and two alleles per locus have been revealed, respectively, although ISSR showed a clear pattern and bands of the primers UBC807, UBC811, UBC812, UBC814, UBC815, UBC817, UBC818, and UBC823. In conclusion, a great range of variability was detected within the fig accessions. This diversification could enrich the genetic base of this genus, and more experiments are needed to reach its full potential.

Hierarchical Process Based Failure Analysis and Application to Marine Pipeline Engineering

For evaluation of subsea pipeline structural reliability, an efficient approach to identify the risk factors is extremely important. In this paper, a more comprehensive and objective methodology, the Hierarchical Energy Expansion Tree (HEET), is achieved by combining the Energy Expansion Tree (EET) with Analytical Hierarchical Process (AHP). First being applied to the useful life phase of a subsea pipeline structure, the new results are shown to be more realistic by comparing the HEET results with the original Full Tree Analysis (FTA)’s and EET’s. Also, the HEET has advantages over the conventional combination of FTA & AHP. The evolution from FTA to EET to HEET is explained and demonstrated.

Long‐term effects of repeated fuel‐reduction burning and logging on bats in south‐eastern Australia

AbstractFire regimes have a major influence on biodiversity in many ecosystems around the globe, yet our understanding of the longer‐term response of fauna is typically poor. We sampled bats with ultrasonic detectors in three different years in dry sclerophyll forests of south‐eastern Australia in a long‐term, management‐scale experiment. Frequent low‐intensity burning (every 2 or 4 years plus unburnt) and logging (with 33% retention of the original unlogged tree basal area) were manipulated to assess their effects on bats. We found that both the fire regime and regrowth after logging influenced the local bat community. The routine burning treatment (burnt every 4 years) in unlogged forest was consistently related to higher total bat activity (2–3 times) and species richness when compared to unburnt controls and logging treatments. Foraging activity was more variable, but it was typically lowest in Unlogged Unburnt Controls. These patterns were evident at both the detector site scale and the block scale and were probably due to a reduction in understorey stem density with burning, especially in unlogged forest. Bat activity was significantly lower across the entire study area (including controls) in 1 year, when sampling occurred within 6 months of burning. When pooled across burning treatments, unlogged forest supported higher bat activity (1.5 times) and species richness than logged forest (12‐ to 17‐year‐old regrowth), again most likely because of a negative association with high stem density in regrowth after logging. We conclude that low‐intensity burning had positive benefits for echolocating bats, most notably in unlogged forest. However, careful planning is required to generate heterogeneous vegetation patterns that are likely to be most suitable for a range of taxa.

Cyclic outbreaks of forest insects: A two-dimensional individual-based model

An individual-based model is presented which shows that cyclic insects outbreaks in the forest (here presented as a certain type of the dynamics of total numbers of insects in the forest) can be a result of the joint action of four factors: (1) spatial structure of the system — resources, green tree biomass, used by larval insects are distributed in a two-dimensional space, (2) properties of trees — their limited resistance to feeding by insects, and regeneration ability after some time of relaxation, when they cannot sustain a local insect population, (3) insect properties — the most important of which is the ability of adult individuals to move between spatially distributed resources and to lay eggs on neighbouring trees, and (4) the type of dynamics of local insect population exploiting resources of a tree, which depends on individual variability of insects and their progeny production. Insects disperse from the original tree and occupy successive not infested trees over the forest, omitting the trees with exploited resources that need time for regeneration. The cyclic outbreak dynamics will take place when insects have opportunity to return to the places where there are trees with regenerated resources. In addition to the cyclic outbreak, we will observe permanent outbreaks (small fluctuations of insect, combined with a similar dynamics of tree biomass) or pulse outbreaks (an increase in the number of insects, followed by their extinction and leading to a temporary destruction of tree biomass). The type of the simulation output will depend on the values of the model parameters. Intermediate resistance of trees to insect feeding and their not very short regeneration time will lead to cyclic outbreaks. Additionally great number of dispersing insects will promote cyclic outbreaks. High degree of individual variability, high mortality of adult insects or small progeny production will produce favourable conditions for permanent outbreaks. Pulse outbreaks can easily occur when insect individual variability is small or progeny production is high.

Different Chemical Compound Profiles of Indonesian Coffee Beans as Studied Chromatography/Mass Spectrometry

Coffee is a favourite beverage worldwide, with all of its benefits. The taste and flavour of coffee depending on the chemical components of the coffee. And the presence of chemicals in the coffee ground depends on the original tree as well as on processing. In this report, some volatiles from ground and brewed coffee beans of Robusta, Arabica, and peaberry coffee beans were extracted to be described after chemical analysis. Mainly gas chromatography/mass spectrometry methods were the main spectroscopy utilized to obtain chemistry information that was taken from hot brewed coffees. The result showed that peaberry coffee beans were very rich in components compared to others. Arabica coffee beans also had stronger in taste and flavour compared to robusta as seen from the profile compositions of chloroform and n-hexane extracts. Better processing would also be suggested for each type of coffee beans.

Fault tree analysis of the causes of urban smog events associated with vehicle exhaust emissions: A case study in Jinan, China

The excessive consumption of fuels associated with rapid industrialization, urbanization, and modernization has caused serious smog events in many Chinese cities. Vehicle exhaust is one of the primary causes of smog events due to the rapid growth of motor vehicle ownership and increased fuel consumption. In this study, fault tree analysis (FTA) was used as a relatively simple but effective way to analyze the causes of smog associated with vehicle exhaust emissions in Jinan, China. First, after the identification of the top event, intermediate events, and basic events, a comprehensive fault tree system for urban smog associated with vehicle exhaust emissions was constructed. Then, during the qualitative analysis stage, minimal cut sets (MCSs) were grouped using Boolean algebra operations, and the original fault tree was simplified to an equivalent tree based on 6 MCSs. Finally, during the quantitative analysis stage, the effects of the 12 basic events on the top event were evaluated and ranked according to the structural importance, probabilistic importance, and critical importance of their analytical measures. Our results indicated that traffic congestion, superabundance of vehicles, poor supervision, and yellow-label vehicles with long use ages had the greatest impact on smog events, with importance degrees of 0.52930, 0.52920, 0.22719, and 0.22716, respectively. These results are consistent with common sense. Although different basic events exert different influences, all of the basic events should be comprehensively taken into consideration and corresponding precautionary measures developed. This research provides a good case study of the application of FTA in the analysis of the causes of urban smog events associated with vehicle exhaust emissions. Our study further demonstrates that FTA is a relatively simple but effective method for the causal analysis of smog, as well as an effective tool for environmental risk management.

Improved disaggregation of conventional soil maps

The disaggregation of conventional soil maps is an alternative for producing high-quality soil maps when point observations are not available. Previous studies developed the DSMART algorithm (“Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees”) for this purpose. In this study, we tested the sensitivity of DSMART towards the input data by using two different conventional soil maps covering Denmark at scales of 1:1,000,000 and 1:2,000,000. As a potential way to improve the algorithm, we tested an implementation of soil-landscape relationships, using maps of wetlands and soil texture. We also tested two different sampling schemes, generating either a set number of virtual samples per polygon in the input map or a number of virtual samples in proportion to the areas of the polygons. Thirdly, we tested the replacement of the resampling procedure and decision tree model with Random Forest. The original procedure repeated the generation of the virtual samples 50 times, fitting a decision tree in each repetition. We modified it by sampling only once and fitting a Random Forest model. The area-proportional sampling scheme and soil-landscape relationships both improved the accuracy. Random Forest yielded a lower accuracy than the original resampling and decision tree procedure, but was far more computationally efficient. The accuracy also depended strongly on the input maps. In the best case, the algorithm predicted soil types with 18% accuracy and soil groups with 47% accuracy. The results demonstrated that there are several ways to improve the disaggregation of conventional soil maps, and that a suitable approach can provide reliable soil maps at a national extent.