Suffix Tree Research Articles

Analysis of the possible detection of the pulsar wind nebulae of PSR J1208-6238, J1341-6220, J1838-0537, and J1844-0346

Pulsar wind nebulae (PWNe) are a source of very high energy radiation that can reach up to tera-electron volts and even peta-electron volts. Our work uses the pulsar tree, a graph theory tool recently presented to analyze the pulsar population and select candidates of interest. We aim to discover detectable PWNe. We also aim to test to what extent the pulsar tree is able to group detectable PWNe despite only considering the intrinsic properties of pulsars. We selected four pulsars as tera-electron volt PWNe candidates based on their positions in the pulsar tree. Using observed and assumed ranges of values for relevant parameters, we anticipated the possible spectral energy distributions of the PWNe of four pulsars (PSR J1208-6238, J1341-6220, J1838-0537, and J1844-0346) via a detailed time-dependent leptonic model that was already found to be appropriate for describing almost all other detected nebulae. We estimated the likelihood of detection for the four candidates we studied by comparing the TeV fluxes predicted by the possible models with the sensitivities of different observatories. In doing so, we provide context for analyzing the advantages and caveats of using the pulsar tree position as a marker for properties that go beyond the intrinsic features of pulsars that are considered in producing the pulsar tree.

Fast and accurate short-read alignment with hybrid hash-tree data structure

Rapidly increasing the amount of short-read data generated by NGSs (new-generation sequencers) calls for the development of fast and accurate read alignment programs. The programs based on the hash table (BLAST) and Burrows-Wheeler transform (bwa-mem) are used, and the latter is known to give superior performance. We here present a new algorithm, a hybrid of hash table and suffix tree, which we designed to speed up the alignment of short reads against large reference sequences such as the human genome. The total turnaround time for processing one human genome sample (read depth of 30) is just 31 min with our system while that was more than 25 h with bwa-mem/gatk. The time for the aligner alone is 28 min for our system but around 2 h for bwa-mem. Our new algorithm is 4.4 times faster than bwa-mem while achieving similar accuracy. Variant calling and other downstream analyses after the alignment can be done with open-source tools such as SAMtools and Genome Analysis Toolkit (gatk) packages, as well as our own fast variant caller, which is well parallelized and much faster than gatk.

Mapping Forest Parameters to Model the Mobility of Terrain Vehicles

This study aims to evaluate the feasibility of using non-contact data collection methods—specifically, UAV (unmanned aerial vehicle)-based and terrestrial laser scanning technologies—to assess forest stand passability, which is crucial for military operations. The research was conducted in a mixed forest stand in the Březina military training area, where the position of trees and their DBHs (Diameter Breast Heights) were recorded. The study compared the effectiveness of different methods, including UAV RGB imaging, UAV-LiDAR, and handheld mobile laser scanning (HMLS), in detecting tree positions and estimating DBH. The results indicate that HMLS data provided the highest number of detected trees and the most accurate positioning relative to the reference measurements. UAV-LiDAR showed better tree detection compared to UAV RGB imaging, though both aerial methods struggled with canopy penetration in densely structured forests. The study also found significant variability in DBH estimation, especially in complex forest stands, highlighting the challenges of accurate tree detection in diverse environments. The findings suggest that while current non-contact methods show promise, further refinement and integration of data sources are necessary to improve their applicability for assessing forest passability in military or rescue contexts.

MITIGATING THE URBAN HEAT ISLAND EFFECT: The Thermal Performance of Shade-Tree Planting in Downtown Los Angeles

The intensifying urban heat island (UHI) effect presents a growing challenge for urban environments, yet there is a lack of comprehensive strategies that account for how multiple factors influence tree-cooling effectiveness throughout the year. While most studies focus on the effects of individual factors, such as tree shading or transpiration, over specific time periods, fewer studies address the combined impact of various factors—such as seasonal variations, building shading, transpiration rates, tree placement, and spacing—on tree cooling across different seasons. This study fills this gap by investigating the thermal environment in downtown Los Angeles through ENVI-met simulations. A novel tree-planting strategy was developed to enhance cooling performance by adjusting tree positions based on these key factors. The results show that the new strategy reduces Universal Thermal Climate Index (UTCI) temperatures by 2.2 °C on the hottest day, 0.97 °C on the coldest day, and 1.52 °C annually. The study also evaluates the negative cooling effects in colder months, demonstrating that, in cities with climates similar to Los Angeles, the benefits of tree cooling in hot weather outweigh the drawbacks during winter. These findings provide a new method for optimizing tree placement in urban planning, contributing to more effective UHI mitigation strategies.

Developing GIS-Based Algorithm of Stand Spatial Structure Index and Its Implementation

Accurate information of the fine-scale spatial patterns of trees and their interactions within a stand is critical for explaining the competition, health and vigor status, and future development of a stand. There are a number of indices which can show such patterns, but the stand spatial structure index is the most important. This index can be quantified based on the spatial information of trees (tree positions) within a stand and has paramount importance in identifying candidate trees to be thinned. This study develops a software tool (algorithm), which can conveniently and accurately estimate the stand spatial structure index. Our proposed algorithm considers the spatial relationships between a reference tree and its four adjacent trees, and computes the three most important stand structure indices (neighborhood comparison, uniform angle index and species mingling) using GIS (ArcEngine) and the C# programming language. The implementation of the developed algorithm (stand spatial structure index) shows that, for any reference tree assumed, its four adjacent trees identified by each of the three stand spatial structure indices (uniform angle index—UAI, mingling—M and neighborhood comparison—NC) are the same, indicating the consistency and accuracy between the three-stand spatial structural indices. For the same tree species in a forest stand, the computational results from each of the spatial structure indices used (UAI, M, NC) are also the same. Thus, the results of this algorithm developed in this study are consistent with that of the Winkelmass1.0 software (a type of software used to simulate stand spatial structure). As this article is based on the GIS technique, the computational results can be visually displayed and implemented on actual maps, making it more convenient and intuitive for forest management. The proposed approach will be useful for accurately identifying the trees to be thinned and helpful for maintaining the vigor stand structure. This study also demonstrates the implementation of the algorithm to the real-world data and proves that the computational process is simple and efficient. The application of this algorithm for the identification of trees to be thinned may help the stakeholders to focus their attention towards multi-functional forest management. The algorithm will also provide an important basis for optimizing thinning and maintaining well-structured forest stands.

Addition to the genus Harmajaea (Agaricales, Pseudoclitocybaceae): a new and a known species from China

A new species, Harmajaea xizangense, discovered in Tibet, China, is illustrated and described based on morphological and molecular data. Morphologically, H. xizangense is mainly characterized by its small pileus, relatively larger and longer spores, and unique geographical distribution. Phylogenetic analyses were performed based on nucleotide sequences of four molecular loci: the internal transcribed spacer (ITS), the nuclear ribosomal large subunit (nrLSU), the DNA-directed RNA polymerase II subunit 2 (RPB2), and the translation elongation factor (TEF1-α). The results indicated that the specimens belonged to the genus Harmajaea, occupying an isolated position in the phylogenetic trees. Furthermore, three collections of H. harperi are introduced for the first time from Liaoning Province of China. This study provides full descriptions, color illustrations, and phylogenetic trees of the two Harmajaea species.

Export Dynamics and Performance of Tree Seeds in Tanzania: An Analytical Study of Tanzania Forest Services Agency

Purpose: This study investigates the determinants of export performance for tree seeds by the Tanzania Forest Services (TFS) through an analytical framework grounded in the Resource-Based View (RBV) theory. It aims to identify and analyze the influence of Foreign Market Characteristics (FMC), Export Competence (EC), and Business Environment (BE) on the export performance of tree seeds in Tanzania. Design/Methodology: The study adopted a longitudinal research design to analyze the export dynamics and performance of tree seeds in Tanzania over 14 years, from 2003 to 2016. Data was collected from TFS over 14 years, covering export volumes and values. The analysis examines the effects of FMC, EC, and BE on tree seed export performance. Findings: The findings indicate that FMC, EC, and BE significantly affect export performance. Foreign market characteristics enhance export performance by improving market demand and accessibility. Export competence contributes to success through superior production quality and logistics. A supportive business environment facilitates exports by reducing trade barriers and improving infrastructure. Thus, these insights suggest the need to foster internal competencies, improve export strategies, and enhance regulatory and economic frameworks to boost the export potential of tree seeds from Tanzania. Originality/Value: This study offers new insights into how internal capabilities and external market conditions jointly influence the export performance of tree seeds. It bridges theoretical frameworks with practical implications for TFS. The study provides actionable recommendations for policymakers to improve export strategies, optimize market access, and strengthen business conditions, thereby advancing Tanzania’s position in the global tree seed market.

Numerical Study on the Summer High-Temperature Climate Adaptation of Traditional Dwellings in the Western Plains of Sichuan, China

Ongoing global climate change, marked by sustained warming and extreme weather events, poses a severe threat to both the Earth’s ecosystems and human communities. Traditional settlements that underwent natural selection and evolution developed a unique set of features to adapt to and regulate the local climate. A comprehensive exploration of the spatial patterns and mechanisms of the adaptation of these traditional settlements is crucial for investigating low-energy climate adaptation theories and methods as well as enhancing the comfort of future human habitats. This study used numerical simulations and field measurements to investigate the air temperature, relative humidity, wind speed, wind direction, and thermal comfort of traditional settlements in Western Sichuan Plain, China, and uncovered their climate suitability characteristics to determine the impact mechanisms of landscape element configurations (building height, building density, tree coverage, and tree position) and spatial patterns on microclimates within these settlements. The results revealed the structural and layout strategies adopted by traditional settlements to adapt to different climatic conditions, providing valuable insights for future rural protection and planning and enhancing climate resilience through natural means. These findings not only contribute to understanding the climate adaptability of Earth’s ecosystems and traditional settlements but also offer new theories and methods to address the challenges posed by climate change.

Linear time online algorithms for constructing linear-size suffix trie

The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a text string T of length n has O(n) nodes and edges, and the string label of each edge is encoded by a pair of positions in T. Thus, even after the tree is built, the input string T needs to be kept stored and random access to T is still needed. The linear-size suffix tries (LSTs), proposed by Crochemore et al. [Linear-size suffix tries, TCS 638:171-178, 2016], are a “stand-alone” alternative to the suffix trees. Namely, the LST of an input text string T of length n occupies O(n) total space, and supports pattern matching and other tasks with the same efficiency as the suffix tree without the need to store the input text string T. Crochemore et al. proposed an offline algorithm which transforms the suffix tree of T into the LST of T in O(nlog⁡σ) time and O(n) space, where σ is the alphabet size. In this paper, we present two types of online algorithms which “directly” construct the LST, from right to left, and from left to right, without constructing the suffix tree as an intermediate structure. Both algorithms construct the LST incrementally when a new symbol is read, and do not access the previously read symbols. Both of the right-to-left construction algorithm and the left-to-right construction algorithm work in O(nlog⁡σ) time and O(n) space. The main feature of our algorithms is that the input text string does not need to be stored.

Mining Weighted Patterns from Time Series Databases Based on Sliding Window

Data mining has traditionally relied heavily on sliding window-based challenges, which has sparked a variety of studies. For each new window in time series mining, current literature mandates the rebuilding of the underlying structure, Suffix Tree - A trie-based structure representing all the suffixes of a string. However, reconstruction struggles when the window is wide or when sliding happens frequently. As a result, we provide a new technique Dynamic Tree-Based Approach to handle Sliding Windows (DTSW) in time series in this study that dynamically changes the representative suffix tree structure rather than reconstructing it after every alteration or sliding. In addition, we also put forth a different approach to the issue of extracting weighted periodic patterns from time series. To prevent testing pointless patterns, existing studies mostly rely on the weight of the database's highest-weighted item. However, these methods continue to examine numerous patterns. These methods still examine numerous patterns to see whether they can be candidates. Our proposed measure Maximum Possible Weighted Support (MPWS) accelerates the candidate generation process by removing numerous unnecessary patterns in advance. The novelty of MPWS is it considers the maximum weighted average over the maximum weighted item extension by enforcing more constraints. The usefulness of our two techniques in handling sliding windows and trimming redundant candidate patterns is demonstrated by experimental results using a variety of real-world datasets. Our experiments state that our dynamic handling technique significantly improves runtime than the reconstruction in a dynamic sliding window-based environment with simultaneous insertion and deletion actions and MPWS reduces the number of tested patterns resulting in lesser mining time in weighted time series pattern mining. DUJASE Vol. 8 (1) 13-25, 2023 (January)

On suffix tree detection

A suffix tree is a fundamental data structure for string processing and information retrieval, however, its structure is still not well understood. The suffix trees reverse engineering problem, which its research aims at reducing this gap, is the following. Given an ordered rooted tree T with unlabeled edges, determine whether there exists a string w such that the unlabeled-edges suffix tree of w is isomorphic to T. Previous studies on this problem consider the relaxation of having the suffix links as well as assume a binary alphabet. This paper is the first to consider the suffix tree detection problem, in which the relaxation of having suffix links as input is removed. We study suffix tree detection on two scenarios that are interesting per se. We provide a suffix tree detection algorithm for general alphabet periodic strings. Given an ordered tree T with n leaves, our detection algorithm takes O(n+|Σ|p)-time, where p is the unknown in advance length of a period that repeats at least 3 times in a string S having a suffix tree structure identical to T, if such S exists. Therefore, it is a polynomial time algorithm if p is a constant and a linear time algorithm if, in addition, the alphabet has a sub-linear size. We also show some necessary (but insufficient) conditions for binary alphabet general strings suffix tree detection. By this we take another step towards understanding suffix trees structure.

GenRepAI: Utilizing Artificial Intelligence to Identify Repeats in Genomic Suffix Trees

Background: The human genome is densely populated with repetitive DNA sequences that play crucial roles in genomic functions and structures but are also implicated in over 40 human diseases. The computational challenge of identifying and characterizing these repeats is significant due to the complexity and size of the genome, which are overwhelming traditional algorithms. Methods: To address these challenges, we propose GenRepAI, a deep learning framework to navigate and analyze genomic suffix trees. GenRepAI employs supervised machine learning classifiers trained on labeled datasets of repeat annotations and unsupervised anomaly detection to identify novel repeat sequences. The models are trained using convolutional neural networks (CNNs), long short-term memory networks (LSTMs), and vision transformers to classify and annotate repeats within the human genome. Results: GenRepAI is designed to comprehensively profile repeats that underlie various neurological diseases, allowing researchers to identify pathogenic expansions. The framework will integrate into existing genomic analysis pipelines, with the capability to screen patient genomes and highlight potential causal variants for further validation. Conclusion: GenRepAI is set to become a foundational tool in genomics, leveraging artificial intelligence to enhance the characterization of repetitive sequences. It promises significant advancements in the molecular diagnosis of repeat expansion disorders and contributes to a deeper understanding of genomic structure and function, with broad applications in personalized medicine.

Automatic detection of color markings and numbers on trees in point clouds from Personal Laser Scanning (PLS) and Terrestrial Laser Scanning (TLS)

In forestry, colored spray paint is used for different purposes, such as marking trees that are chosen for the next harvest or that will be promoted by future silvicultural activities, or for the demarcation of skid/cable roads. Numerous studies have demonstrated the application of Terrestrial Laser Scanners (TLS) and Personal Laser Scanners (PLS) for the acquisition of tree parameters (diameters, heights, and tree positions) in a forest inventory context. However, no studies have included classification based on spectral information by applying colored markings to trees. When a laser scanner is combined with a camera, the color information can be mapped onto the laser point cloud, allowing for additional analysis of spectral information. In this study, we have tested the analysis of joint information from imagery and 3D point clouds in two different settings: (i) PLS point cloud data from a GeoSLAM ZEB Horizon were complemented with spectral information from images collected with a NCTech iSTAR Pulsar 360-degree camera, (ii) TLS point cloud data from a RIEGL VZ-400i were combined with imagery from a Nikon D850 digital single lens reflex (DSLR) camera with 14 mm fisheye lens. The major objective was to automatically classify trees that were marked with colored sprays automatically identify the numbers sprayed on the trees. The marked trees could be classified correctly with a balanced accuracy of 77.26% for PLS and 98.01% for the data collected with the TLS system using a support vector machine (SVM) model. The numbers written on the trees were classified from the TLS data using a YOLOv8 model. The accuracy of the digit classification reached up to 97.30%. In conclusion, it is possible to automatically detect marked trees and to automatically recognize the numbers spayed on these trees from colored point cloud data. However, accuracy strongly depends on the selected combination of scanner and camera. The findings of future research on this subject might differ with the ongoing development of PLS systems and could be enhanced by creating a large dataset of handwritten numbers collected using laser scanning systems.

Rapid advance of climatic tree limits in the Eastern Alps explained by on-site temperatures

In the European Alps, mean temperature has risen by 2.5 K since the end of the nineteenth century. A 2 K warming of the growing season has taken place in the last 4 decades only. The 2.5 K warming should rise the position of the climatic treeline by about 400 m. Actual shifts in uppermost tree positions reported here for the Austrian Defereggen Valley and the Swiss Lower Engadine region of the Eastern Alps reach only around 140 m of elevation above the limit of old trees that date back to the nineteenth century. Uppermost Pinus cembra trees of > 2 m height currently occur at c. 2500 m, representing elevation records for the Eastern Alps. In situ temperature records for 2022–2023 revealed seasonal mean temperatures for uppermost trees that are 1–3 K higher than the equilibrium treeline isotherm of c. 6 °C in both regions (corrected for temperature anomalies from long-term records). The 2 K span reflects microhabitat differences and two ways to define the season. Thus, tree advances lag behind the upslope shift of the treeline isotherm, on average, by more than 200 m. The uppermost trees currently grow under quite warm conditions with annual shoot length increments frequently reaching 20 cm. Even without additional future warming, the new steady-state climatic treeline will exceed the Holocene maximum elevation in the Eastern Alps substantially.

Rhymes and Syntax: A Morpho-Syntactic Analysis of Czech Poetry

A linguistically informed distant reading presupposes an adequate performance of Natural Language Processing tools. This article describes our evaluation of the UDPipe parser on a manually annotated sample of nineteenth-century Czech poetry in the following steps: (1) creation of a documented data set for this domain (poetry, nineteenth century, Czech); (2) domain-specific annotation decisions; (3) error analysis. The sample consisted of 29 randomly selected poems which were first automatically tagged and parsed with the UDPipe parser and then manually checked word by word. The following features were checked: word segmentation (chunking), lemmatization, part of speech assignment, assignment of more fine-grained morphological details, the position in the syntactic dependency tree (selection of the syntactic parent), as well as the label of the syntactic relation between the word and its parent. The findings were analyzed. The most typical parser errors are associated with complex noun phrases that contain other noun(s) as modifier(s), especially when these occur in a poetry-specific word order, that is, preposed to the governing noun. On the other hand, neither archaic orthography nor neologisms posed substantial issues.

Eupransor demetentiae gen. nov., sp. nov., a novel fructophilic lactic acid bacterium from bumble bees.

Strain LMG 33000T was isolated from a Bombus lapidarius gut sample. It shared the highest percentage 16S rRNA sequence identity, average amino acid identity, and amino acid identity of conserved genes with Convivina intestini LMG 28291T (95.86 %, 69.9 and 76.2 %, respectively), and the highest percentage OrthoANIu value with Fructobacillus fructosus DSM 20349T (71.4 %). Phylogenomic analyses by means of 107 or 120 conserved genes consistently revealed Convivina as nearest neighbour genus. The draft genome of strain LMG 33000T was 1.44 Mbp in size and had a DNA G+C content of 46.1 mol%. Genomic and physiological analyses revealed that strain LMG 33000T was a typical obligately fructophilic lactic acid bacterium that lacked the adhE and aldh genes and that did not produce ethanol during glucose or fructose metabolism. In contrast, Convivina species have the adhE and aldh genes in their genomes and produced ethanol from glucose and fructose metabolism, which is typical for heterofermentative lactic acid bacteria. Moreover, strain LMG 33000T exhibited catalase activity, an unusual characteristic among lactic acid bacteria, that is not shared with Convivina species. Given its position in the phylogenomic trees, and the difference in genomic percentage G+C content and in physiological and metabolic characteristics between strain LMG 33000T and Convivina species, we considered it most appropriate to classify strain LMG 33000T into a novel genus and species within the Lactobacillaceae family for which we propose the name Eupransor demetentiae gen. nov., sp. nov., with LMG 33000T (=CECT 30958T) as the type strain.

Real-Time Estimation of Tree Position, Tree Height, and Tree Diameter at Breast Height Point, Using Smartphones Based on Monocular SLAM

Precisely estimating the position, diameter at breast height (DBH), and height of trees is essential in forest resource inventory. Augmented reality (AR)-based devices help overcome the issue of inconsistent global point cloud data under thick forest canopies with insufficient Global Navigation Satellite System (GNSS) coverage. Although monocular simultaneous localization and mapping (SLAM) is one of the current mainstream systems, there is still no monocular SLAM solution for forest resource inventories, particularly for the precise measurement of inclined trees. We developed a forest plot survey system based on monocular SLAM that utilizes array cameras and Inertial Measurement Unit (IMU) sensors provided by smartphones, combined with augmented reality technology, to achieve a real-time estimation of the position, DBH, and height of trees within forest plots. Our results from the tested plots showed that the tree position estimation is unbiased, with an RMSE of 0.12 m and 0.11 m in the x-axis and y-axis directions, respectively; the DBH estimation bias is −0.17 cm (−0.65%), with an RMSE of 0.83 cm (3.59%), while the height estimation bias is −0.1 m (−0.95%), with an RMSE of 0.99 m (5.38%). This study will be useful in designing an algorithm to estimate the DBH and position of inclined trees using point clouds constrained by sectional planes at the breast height of the trunk, developing an algorithm to estimate the height of inclined trees utilizing the relationship between rays and plane positions, and providing observers with visual measurement results using augmented reality technology, allowing them to judge the accuracy of the estimates intuitively. Clearly, this system has significant potential applications in forest resource management and ecological research.

TRGST: An enhanced generalized suffix tree for topological relations between paths

This paper introduces the TRGST data structure, which is designed to handle queries related to topological relations between paths represented as sequences of stops in a network. As an example, these paths could correspond to stops on a public transport network, and a query of interest is to retrieve paths that share at least k consecutive stops. While topological relations among spatial objects have received extensive attention, the efficient processing of these relations in the context of trajectory paths, considering both time and space efficiency, remains a relatively less explored domain. Taking inspiration from pattern matching implementations, the TRGST data structure is constructed on the foundation of the Generalized Suffix Tree. Its purpose is to provide a compact representation of a set of paths and to efficiently handle topological relation queries by leveraging the pattern search capabilities inherent in this structure. The paper provides a detailed account of the structure and algorithms of TRGST, followed by a performance analysis utilizing both real and synthetic data. The results underscore the remarkable scalability of the TRGST in terms of both query time and space utilization.

Effects of slope and tree position on soil properties in a temperate deciduous forest

Effects of slope and tree position on soil properties in a temperate deciduous forest

Anaerobic fungi in the tortoise alimentary tract illuminate early stages of host-fungal symbiosis and Neocallimastigomycota evolution

Anaerobic gut fungi (AGF, Neocallimastigomycota) reside in the alimentary tract of herbivores. While their presence in mammals is well documented, evidence for their occurrence in non-mammalian hosts is currently sparse. Culture-independent surveys of AGF in tortoises identified a unique community, with three novel deep-branching genera representing >90% of sequences in most samples. Representatives of all genera were successfully isolated under strict anaerobic conditions. Transcriptomics-enabled phylogenomic and molecular dating analyses indicated an ancient, deep-branching position in the AGF tree for these genera, with an evolutionary divergence time estimate of 104-112 million years ago (Mya). Such estimates push the establishment of animal-Neocallimastigomycota symbiosis from the late to the early Cretaceous. Further, tortoise-associated isolates (T-AGF) exhibited limited capacity for plant polysaccharides metabolism and lacked genes encoding several carbohydrate-active enzyme (CAZyme) families. Finally, we demonstrate that the observed curtailed degradation capacities and reduced CAZyme repertoire is driven by the paucity of horizontal gene transfer (HGT) in T-AGF genomes, compared to their mammalian counterparts. This reduced capacity was reflected in an altered cellulosomal production capacity in T-AGF. Our findings provide insights into the phylogenetic diversity, ecological distribution, evolutionary history, evolution of fungal-host nutritional symbiosis, and dynamics of genes acquisition in Neocallimastigomycota.