GHCR-A dataset for Grantha handwritten character recognition.

This dataset presents a comprehensive collection of handwritten Grantha characters, comprising numbers and vowels, gathered from participants spanning diverse age groups. Utilizing standard A4 sheets, participants were instructed to handwrite Grantha characters. The Grantha script encompasses 10 numbers and 34 vowels. The Grantha Character dataset comprises 44 distinct characters of numbers and vowels. A dataset comprising 133 handwritten samples for each number and 133 for each vowel was collected. These samples underwent digitization and preprocessing steps, including segmentation, resizing, and grayscale conversion. The final dataset consists of 5852 images, comprising 1330 samples for numbers and 4522 samples for vowels. The data is provided in both image and CSV formats, accompanied by corresponding labels. facilitating its utilization in machine learning model development. With limited datasets available for the Grantha script, this contribution addresses a significant gap by providing a benchmark dataset for Grantha numeral and vowel recognition. Moreover, this novel dataset serves as a fundamental resource for commencing machine learning research in Indian languages that have historical connections to the Grantha script.

Balinese story texts dataset for narrative text analyses.

Automatic narrative text analysis is gaining traction as artificial intelligence-based computational linguistic tools such as named entity recognition systems and natural language processing (NLP) toolkits become more prevalent. Character identification is the first stage in narrative text analysis; however, it is difficult due to the diversity of appearances and distinctive characteristics among regions. Further challenging analyses, such as role classification, emotion and personality profiling, and character network development, require successful character identification initially, which is crucial. Because there are so many annotated English datasets, computational linguistic tools are mostly focused on English literature. However, there are restricted tools for analyzing Balinese story texts because of a scarcity of low-resource language datasets. The study presents the first annotated Balinese story texts dataset for narrative text analyses, consisting of four sub-datasets for character identification, alias clustering (named entity linking, alias resolution), and character classification. The dataset is a compilation of 120 manually annotated Balinese stories from books and public websites, spanning multiple genres such as folk tales, fairy tales, fables, and mythology. Two Balinese native speakers, including an expert in sociolinguistics and macrolinguistics, annotated the dataset using predetermined guidelines set by an expert. The inter-annotator agreement (IAA) score is calculated using Cohen's Kappa Coefficient, Jaccard Similarity Coefficient, Mean F1-score to measure the level of agreement between annotators and dataset consistency and its reliability. The first subdataset consists of 89,917 annotated words with five labels referring to the Balinese-character named entities. Each character entity's appearance in 6,634 sentences is further annotated in the second subdataset. These two sub-datasets can be used for character identification purposes at the word and sentence level. The list of character groups which are groups of various aliases for each character entity has been annotated in the third subdataset for alias clustering purposes. The third subdataset contains 930-character groups from 120 story texts with each story text containing an average of 7-to-8-character groups. In the fourth subdataset, 848-character groups-of the 930-character groups in the third subdataset-have been categorized as protagonists and antagonists. The protagonists (66.16 %) make up most character groups, with the antagonists (33.84 %) making up the rest of the groups. The fourth subdataset can be used for computing-based classification of characters into two roles between protagonist and antagonist. These datasets have the potential to improve research in narrative text analyses, especially in the areas of computational linguistic tools and advanced machine learning (ML) and deep learning (DL) models in low resource languages. It can also be used for further research including character network development, character relationship extraction, and character classification beyond protagonist and antagonist.

A scarce dataset for ancient Arabic handwritten text recognition.

Developing Deep Learning Optical Character Recognition is an active area of research, where models based on deep neural networks are trained on data to eventually extract text within an image. Even though many advances are currently being made in this area in general, the Arabic OCR domain notably lacks a dataset for ancient manuscripts. Here, we fill this gap by providing both the image and textual ground truth for a collection of ancient Arabic manuscripts. This scarce dataset is collected from the central library of the Islamic University of Madinah, and it encompasses rich text spanning different geographies across centuries. Specifically, eight ancient books with a total of forty pages, both images and text, transcribed by the experts, are present in this dataset. Particularly, this dataset holds a significant value due to the unavailability of such data publicly, which conspicuously contributes to the deep learning models development/augmenting, validation, testing, and generalization by researchers and practitioners, both for the tasks of Arabic OCR and Arabic text correction.

Longitudinal Associations between Adolescents' Character Attributes and Civic Actions.

Research suggests that character attributes may enable youth to envision and perform civic actions that benefit society, but few studies have examined the longitudinal associations between character attributes and civic actions. As a response to this gap, this study investigated how specific character attributes (purpose, future mindedness, humility, and moral courage) may be differently linked to various civic actions (community service, political activities, social activism) cross-sectionally and longitudinally. Survey data were collected from 521 adolescents (Mage = 14.44, SD = 1.92, 58.5% girls, 60.8% White). Structural equation models demonstrated that purpose and future mindedness were positively associated with all three civic actions at Time 1, but not at Time 2. Humility was not associated with any Time 1 civic actions, but was negatively associated with Time 2 political activities. Moral courage was positively associated with Time 1 social activism and Time 2 political activities. Results illuminate the short-term interplay between character attributes and civic actions and point to internal resources that may promote different forms of youth civic action.

Total substitution and partial modification of the set of non-ribosomal peptide synthetases clusters lead to pyoverdine diversity in the Pseudomonas fluorescens complex.

Pyoverdines are high affinity siderophores produced by most Pseudomonas with a wide role in microbial interspecies interactions. They are primarily composed of a conserved chromophore moiety, an acyl side chain and a peptide backbone which may be highly variable among strains. Upon ferric iron sequestration, pyoverdines are internalized through specialized receptors. The peptide precursor of pyoverdine, termed ferribactin, is synthesized by a set of non-ribosomal peptide synthetase (NRPS) enzymes and further modified by tailoring enzymes. While PvdL, the NRPS responsible for the synthesis of the peptide moiety that derives into the chromophore is conserved, the NRPSs for the peptide backbone are different across fluorescent Pseudomonas. Although the variation of pyoverdine is a widely recognized characteristic within the genus, the evolutionary events associated with the diversity and distribution of this trait remain mostly unknown. This study analyzed the NRPSs clusters for the biosynthesis of the peptide backbone of ferribactin in the genomes of a representative subset of strains of the Pseudomonas fluorescens complex. Bioinformatic analysis of the specificity of adenylation domains of the NRPSs allowed the prediction of 30 different pyoverdine variants. Phylogenetic reconstruction and mapping of the NRPS clusters pinpointed two different general levels of modifications. In the first level, a complete replacement of the set of NRPRs by horizontal transfer occurs. In the second level, the original set of NRPSs is modified through different mechanisms, including partial substitution of the NRPS genes by horizontal transfer, adenylation domain specificity change or NRPS accessory domain gain/loss.

Character recognition system for pegon typed manuscript.

The Pegon script is an Arabic-based writing system used for Javanese, Sundanese, Madurese, and Indonesian languages. Due to various reasons, this script is now mainly found among collectors and private Islamic boarding schools (pesantren), creating a need for its preservation. One preservation method is digitization through transcription into machine-encoded text, known as OCR (Optical Character Recognition). No published literature exists on OCR systems for this specific script. This research explores the OCR of Pegon typed manuscripts, introducing novel synthesized and real annotated datasets for this task. These datasets evaluate proposed OCR methods, especially those adapted from existing Arabic OCR systems. Results show that deep learning techniques outperform conventional ones, which fail to detect Pegon text. The proposed system uses YOLOv5 for line segmentation and a CTC-CRNN architecture for line text recognition, achieving an F1-score of 0.94 for segmentation and a CER of 0.03 for recognition.

Decoding the neural impact of radical complexity in Chinese characters during working memory task.

Readers of Chinese characters need to recognize how they are formed in order to identify them correctly. However, our understanding of the cognitive processing of characters in working memory is limited. In Experiment 1, using the character N-back task paradigm, electrophysiological data were recorded from 26 participants to investigate the effects of the visual feature of radicals on neural activity during the character recognition, updating and maintenance in the N-back task. Results showed that compound characters required longer response times than single-component characters. For the event-related potentials (ERPs), the compound character condition had more negative N2pc and lower P300 amplitudes than the single-component character condition. In Experiment 2, data from 26 participants were used to analyse the effect of the phonological feature of radicals on neural activity during the character recognition, updating and maintenance in the N-back task. Results showed that there was a larger P200 in the irregular character condition than in the regular character condition, but there was no difference between the regular and the irregular characters in the N2pc, P300 and slow wave (SW) components. The visual feature and the phonological feature of the radicals may have different effects on the character processing. This study reveals the neural effects of Chinese character radicals on cognitive processing in a working memory task and provides behavioural and electrophysiological evidence for a theoretical model of verbal working memory subprocesses.

Recognition of inscribed cursive Pashtu numeral through optimized deep learning.

Pashtu is one of the most widely spoken languages in south-east Asia. Pashtu Numerics recognition poses challenges due to its cursive nature. Despite this, employing a machine learning-based optical character recognition (OCR) model can be an effective way to tackle this issue. The main aim of the study is to propose an optimized machine learning model which can efficiently identify Pashtu numerics from 0-9. The methodology includes data organizing into different directories each representing labels. After that, the data is preprocessed i.e., images are resized to 32 × 32 images, then they are normalized by dividing their pixel value by 255, and the data is reshaped for model input. The dataset was split in the ratio of 80:20. After this, optimized hyperparameters were selected for LSTM and CNN models with the help of trial-and-error technique. Models were evaluated by accuracy and loss graphs, classification report, and confusion matrix. The results indicate that the proposed LSTM model slightly outperforms the proposed CNN model with a macro-average of precision: 0.9877, recall: 0.9876, F1 score: 0.9876. Both models demonstrate remarkable performance in accurately recognizing Pashtu numerics, achieving an accuracy level of nearly 98%. Notably, the LSTM model exhibits a marginal advantage over the CNN model in this regard.

Long Non-Coding RNA AGAP2-AS1: A Comprehensive Overview on Its Biological Functions and Clinical Significances in Human Cancers.

Long non-coding RNAs (lncRNAs) are well known for their oncogenic or anti-oncogenic roles in cancer development. AGAP2-AS1, a new lncRNA, has been extensively demonstrated as an oncogenic lncRNA in various cancers. Abundant experimental results have proved the aberrantly high level of AGAP2-AS1 in a great number of malignancies, such as glioma, colorectal, lung, ovarian, prostate, breast, cholangiocarcinoma, bladder, colon and pancreatic cancers. Importantly, the biological functions of AGAP2-AS1 have been extensively demonstrated. It could promote the proliferation, migration and invasion of cancer cells. Simultaneously, the clinical significances of AGAP2-AS1 were also illustrated. AGAP2-AS1 was exceptionally overexpressed in various cancer tissues. Clinical studies disclosed that the abnormal overexpression of AGAP2-AS1 was tightly connected with overall survival (OS), lymph nodes metastasis (LNM), clinical stage, tumor infiltration, high histological grade (HG), serous subtype and PFI times. However, to date, the biological actions and clinical significances of AGAP2-AS1 have not been systematically reviewed in human cancers. In the present review, the authors overviewed the biological actions, potential mechanisms and clinical features of AGAP2-AS1 according to the previous studies. In summary, AGAP2-AS1, as a vital oncogenic gene, is a promising biomarker and potential target for carcinoma prognosis and therapy.

Buying Game Derivative Products Is Different from In-Game Purchases: A Mixed-Method Approach.

The consumption of games has received increasing attention due to their high profits and addiction issues. However, previous studies have focused mainly on players' in-game purchases, neglecting the purchase of game derivative products. This article provides the first exploration of the differences and similarities between in-game purchases and derivative product purchases with a mixed-method approach. A quantitative survey collected data from 9864 game players, and the results suggested that there were differences between in-game purchases and derivative product consumption in terms of consumption amount and number of participants, and that derivative product purchases had a stronger relationship with character attachment and game loyalty. Subsequent interviews were conducted with 22 players. The findings supported the quantitative results and revealed that players exhibited a distinct understanding of each type of purchase in terms of ownership. Overall, these findings contribute to the understanding of game derivative product purchases and explore the factors influencing in-game purchases and derivative product purchases. We strongly argue that the pattern of spending on game derivative products is very different from that of spending on in-game purchases and is, thus, worthy of dedicated research.

Hypocrisy moderates self-interest bias in moral character judgments.

Self-interest bias describes an observer's tendency to judge moral transgression leniently when they benefit from it. However, what factors moderate the self-interest bias is an open empirical question. Here, we investigated to what extent hypocrisy moderates the self-interest bias. Preregistered Study 1a (N = 194) and replication in Study 1b (N = 193) demonstrated that observers' interest impacts moral character judgments of hypocritical transgressors. This effect was explained by observers' goal attainment due to transgression (Study 2, N = 713) and agreement to aid observers' or ingroup interests (Study 3, N = 634). Importantly, transgressors' hypocrisy moderated the impact of observers' interests in moral character judgments (Studies 2 & 3). In summary, when judging hypocritical transgressors, peoples' moral character judgments tend to be biased by their or their group's interests. However, in comparison to non-hypocritical transgressors, this impact is less pronounced.

Theoretical investigation of the effects of diverse hydrogen-bonding characteristics on the 17O chemical shielding and electric field gradient tensors within the active sites of MraYAA bound to nucleoside antibiotics capuramycin, carbacaprazamycin, 3'-Hydroxymureidomycin A, and muraymycin D2.

This study builds upon our prior researches and seeks to investigate and clarify the influences of various characteristics of hydrogen bonds (H-bonds) and charge transfer (CT) interactions, which were detected within the inhibitor binding pockets (labeled as the QM models I-IV) of MraYAA-capuramycin, MraYAA-carbacaprazamycin, MraYAA-3'-hydroxymureidomycin A, and MraYAA-muraymycin D2 complexes by QTAIM and NBO analyses from DFT QM/MM MD calculations, on the 17O chemical shielding (CS) and electric field gradient (EFG) tensors of carboxylate (Oδ), carbonyl (C═O), and hydroxyl (O-H) oxygens in these models. The 17O CS and EFG tensors of these three types of oxygens in QM models I-IV were calculated at the M06-2X/6-31G** level by including the solvent effects using the polarizable continuum model. From the computed 17O CS and EFG tensors in these models, it was found that the nuclear shielding, σiso, for carboxylate or carbonyl oxygen increases (shielding effect) as the H-bond length decreases and the percentage p-character of nOδ/nC═O lone pair partner in the CT interaction enhances. In contrast, the σiso (17O-H) decreases (deshielding effect) with a reduction in the H-bond length as well as with an enhancement in percentage s-character of the nOH lone pair/σ*O-H antibond. By reducing the H-bond length or by increasing p-character of the nOδ/nC═O lone pair, the 17Oδ/17O═C quadrupole coupling constant smoothly decreases, while the 17Oδ/17O═C asymmetry parameter smoothly increases. Moreover, these calculated parameters are in a good agreement with the experimental values. The information garnered here is valuable particularly for further understanding of empirical correlations between 17O NMR spectroscopic and H-bonding characteristics in the protein-ligand complexes.

Does exercise adherence during the COVID-19 pandemic contribute to improved subjective well-being? A cross-sectional study.

Introduction: This study aims to investigate whether exercise adherence and positive mental character significantly affect subjective well-being among Chinese college students during the COVID-19 pandemic and whether positive mental character plays a mediating role. Methods: The study employed questionnaires, including the Exercise Adherence Scale, the Positive Mental Character Scale, and the Subjective Well-Being Scale, which were administered to students across seven universities in Henan Province, China. A total of 1,001 participants were analyzed in the final sample. Data were analyzed using SPSS 21.0 for descriptive statistics, independent samples T-test, correlation, and regression analyses. Furthermore, structural equation model with AMOS was conducted to examine the potential mediating effect of positive mental characteristics on the relationship between exercise adherence and subjective well-being. Results: The results indicated significant differences in exercise adherence, positive mental character, and subjective well-being between male and female participants, with males scoring higher in all three domains. Among Chinese university students during the COVID-19 pandemic, there was a significant correlation among exercise adherence, positive mental character, and subjective well-being. Exercise adherence was found to have a significant and positive impact on both positive mental character and subjective well-being. Additionally, it was found that positive mental character had a significant positive association with subjective well-being. The mediating role of positive mental character in the relationship between exercise adherence and subjective well-being was partially supported. Discussion: Exercise adherence among Chinese college students had a significant positive association on both positive mental character and subjective well-being throughout the COVID-19 pandemic. The exercise adherence can directly or indirectly enhance subjective well-being through its association with positive mental character. Therefore, positive mental and subjective well-being can be enhanced by consistent physical activity even during a pandemic.

The Systematics and Evolution of Gymnosperms with an Emphasis on a Few Problematic Taxa.

Gymnosperms originated in the Middle Devonian and have experienced a long evolutionary history with pulses of speciation and extinction, which resulted in the four morphologically distinct extant groups, i.e., cycads, Ginkgo, conifers and gnetophytes. For over a century, the systematic relationships within the extant gymnosperms have been debated because different authors emphasized different characters. Recent phylogenomic studies of gymnosperms have given a consistent topology, which aligns well with extant gymnosperms classified into three classes, five subclasses, eight orders, and 13 families. Here, we review the historical opinions of systematics of gymnosperms with special reference to several problematic taxa and reconsider the evolution of some key morphological characters previously emphasized by taxonomists within a phylogenomic context. We conclude that (1) cycads contain two families, i.e., the Cycadaceae and the Zamiaceae; (2) Ginkgo is sister to cycads but not to conifers, with the similarities between Ginkgo and conifers being the result of parallel evolution including a monopodial growth pattern, pycnoxylic wood in long shoots, and the compound female cones, and the reproductive similarities between Ginkgo and cycads are either synapomorphic or plesiomorphic, e.g., the boat-shaped pollen, the branched pollen tube, and the flagellate sperms; (3) conifers are paraphyletic with gnetophytes nested within them, thus gnetophytes are derived conifers, and our newly delimited coniferophytes are equivalent to the Pinopsida and include three subclasses, i.e., Pinidae, Gnetidae, and Cupressidae; (4) fleshy cones of conifers originated multiple times, the Podocarpaceae are sister to the Araucariaceae, the Cephalotaxaceae and the Taxaceae comprise a small clade, which is sister to the Cupressaceae; (5) the Cephalotaxaceae are distinct from the Taxaceae, because the former family possesses typical female cones and the fleshy part of the seed is derived from the fleshiness of integument, while the latter family has reduced female cones and preserves no traces of the seed scale complexes.

Creating a resilient pedagogy: Character strengths intervention for aspiring educators.

Teachers play a crucial role in guiding learners through life's challenges. They face educational and socio-economic shifts while striving to teach for a better future. Our study focuses on equipping future teachers, called pre-service teachers, with resilience-building resources during their teacher training program. A potential antecedent to resilience, which facilitates cognitive strategies and attentional processes, is cognitive flexibility. We first tested whether cognitive flexibility predicts resilience. Next, relying on the tenets of positive psychology, which studies resilience, we developed and tested the effectiveness of character strengths intervention in enhancing pre-service teachers' resilience and cognitive flexibility. An individual's belief in their ability to change personal resources could influence how an intervention manifests. Hence, we studied how mindset impacts the intervention's effect on cognitive flexibility and, thus, resilience. We adopted a multi-method approach, guided by Polk's theory of resilience, to test out objectives. Using a cross-sectional design, study one (n = 273) found that cognitive flexibility significantly predicted resilience. Study two (N = 193; nexp = 133, ncont = 60) was a multi-site field experiment. We found that intervention significantly enhanced resilience (experimental group M = 29.62, control group M = 28.33) and cognitive flexibility (experimental group M = 54.42, control group M = 52.01). Further, a growth mindset, was found to moderate the indirect effect of character strengths intervention on resilience via cognitive flexibility. The study contributes to theoretical and practical advancements in resilience. Taken together, the findings highlight the cognitive-affective-behavioural makeup of resilience and, importantly, the role of cognitive flexibility. The intervention can be seamlessly integrated into teacher training curricula for a resilient future.

A Thermally Populated Germylene-Based Donor-Acceptor Diradical.

This work reports synthesis of a germylene based donor-acceptor molecule and its thermal excitation to a triplet state by coordination with a Lewis acid. Products have been characterized by single crystal X-ray diffraction, EPR spectroscopy, and SQUID measurement, in conjunction with DFT calculation. The singlet-triplet energy gap of the donor-acceptor molecule is dramatically reduced from -18.8 to -7.2 kcal/mol by the coordination with B(C6F5)3 (BCF), which enables an intramolecular single electron transfer from one germylene moiety to another upon heating, forming an intramolecular radical ion pair with diradical character. The work provides an approach to the formation of thermally populated open-shell species of heavier main group elements.

Bullying and Cyberbullying in School: Rapid Review on the Roles of Gratitude, Forgiveness, and Self-Regulation.

This study aims to assist decision-making in anti-bullying interventions by highlighting the importance of positive factors such as gratitude, forgiveness, and self-regulation in mitigating the negative impacts of bullying/cyberbullying. The objective was to examine and synthesize available evidence on the impact of gratitude, forgiveness, and self-regulation practices in the school context regarding bullying/cyberbullying phenomena. Three databases were consulted (Web of Science, Scopus, and Scielo), and the results include 14 articles. The three character strengths were associated with psychological well-being, life and school satisfaction, improved mental health, increased likelihood of engaging in pro-social behavior, and reduced involvement in bullying/cyberbullying situations. These strengths have the potential to enhance overall well-being and decrease risk behaviors, leading to more positive outcomes in experiences of violence. These results underscore the importance of considering students' individual strengths and the possible interventions to promote healthy school environments.

The Correlation between the MBTI-Based Personality Analysis of Anime Characters and Their Popularity.

Anime has become a global phenomenon due to its diverse cultural representations, relatable characters, and unique storytelling. However, there is limited research on the relationship between character personality and popularity. The aim of this study is to understand the relevance of the characters' personalities to the audience's evaluation of various characters. This study analyzed the correlation between the MBTI personality evaluations of characters in anime and their popularity, based on the data of the personality of each animation character reviewed by audiences. In this study, 885 characters from 200 anime aimed at a male audience were selected as a sample for research. The results showed that personality traits such as introversion, intuition, and thinking had an impact on the popularity of female characters but not male characters. The overall results were influenced by the larger sample size of female characters. By addressing this question, the study can contribute to the design of a character's personality and overall success in anime.

Characterization of a new Camellia plant resource with low caffeine and high theobromine for production of a novel natural low-caffeine tea.

Yuanbaoshancha (YBSC) is characterized as a new wild tea relative morphologically and phytochemically distinguished from the closest wild tea plants Rongjiangcha (Camellia yungkiangensis, RJC) and Tulecha (Camellia costata, TLC). YBSC young leaves contain higher tea polyphenol and theobromine contents but lower caffeine and theanine as compared with RJC, TLC, and other tea landraces and modern cultivars. The major alkaloid detected in YBSC, TLC, and RJC is theobromine while caffeine is a minor; the primary catechins in YBSC leaves are non-galloylated catechins, significantly different from Camellia sinensis and other low-caffeine tea resources. The unique phytochemical profiles featured YBSC black tea with extremely lower caffeine and higher theobromine, as well as unique flavors and health benefits. This botanical characterization of YBSC and two related low-caffeine wild tea resources lays a foundation for future better utilization for the production of a highly valuable natural low-caffeine/high-theobromine tea. Chemical compounds: Caffeine (PubChem CID: 2519); Theobromine (PubChem CID: 5429); Catechins (PubChem CID: 9064); Epigallocatechin gallate (PubChem CID: 65064); Theanine (PubChem CID: 439378); Jasmone (PubChem CID: 1549018); cis-3-Hexenyl hexanoate (PubChem CID: 5352543); Hexyl 2-methylbutanoate (PubChem CID: 24838).

Exploring the Macroevolutionary Signature of Asymmetric Inheritance at Speciation.

Popular comparative phylogenetic models such as Brownian Motion, Ornstein-Ulhenbeck, and their extensions, assume that, at speciation, a trait value is inherited identically by two descendant species. This assumption contrasts with models of speciation at a micro-evolutionary scale where descendants' phenotypic distributions are sub-samples of the ancestral distribution. Different speciation mechanisms can lead to a displacement of the ancestral phenotypic mean among descendants and an asymmetric inheritance of the ancestral phenotypic variance. In contrast, even macro-evolutionary models that account for intraspecific variance assume symmetrically conserved inheritance of ancestral phenotypic distribution at speciation. Here we develop an Asymmetric Brownian Motion model (ABM) that relaxes the assumption of symmetric and conserved inheritance of the ancestral distribution at the time of speciation. The ABM jointly models the evolution of both intra- and inter-specific phenotypic variation. It also infers the mode of phenotypic inheritance at speciation, which can range from a symmetric and conserved inheritance, where descendants inherit the ancestral distribution, to an asymmetric and displaced inheritance, where descendants inherit divergent phenotypic means and variances. To demonstrate this model, we analyze the evolution of beak morphology in Darwin finches, finding evidence of displacement at speciation. The ABM model helps to bridge micro- and macro-evolutionary models of trait evolution by providing a more robust framework for testing the effects of ecological speciation, character displacement, and niche partitioning on trait evolution at the macro-evolutionary scale.