Research Tool Research Articles

Disentangling genotype and environment specific latent features for improved trait prediction using a compositional autoencoder

In plant breeding and genetics, predictive models traditionally rely on compact representations of high-dimensional data, often using methods like Principal Component Analysis (PCA) and, more recently, Autoencoders (AE). However, these methods do not separate genotype-specific and environment-specific features, limiting their ability to accurately predict traits influenced by both genetic and environmental factors. We hypothesize that disentangling these representations into genotype-specific and environment-specific components can enhance predictive models. To test this, we developed a compositional autoencoder (CAE) that decomposes high-dimensional data into distinct genotype-specific and environment-specific latent features. Our CAE framework employed a hierarchical architecture within an autoencoder to effectively separate these entangled latent features. Applied to a maize diversity panel dataset, the CAE demonstrated superior modeling of environmental influences and out-performs PCA (principal component analysis), PLSR (Partial Least square regression) and vanilla autoencoders by 7 times for ‘Days to Pollen’ trait and 10 times improved predictive performance for ‘Yield’. By disentangling latent features, the CAE provided a powerful tool for precision breeding and genetic research. This work has significantly enhanced trait prediction models, advancing agricultural and biological sciences.

Citationchaser: A tool for citation chasing in academic searching

This review evaluates the Citationchaser tool as a research support application for systematic reviews, specifically focusing on its functionality and reliability in citation chasing. Citation chasing, a valuable technique in evidence synthesis, enables researchers to trace references backward (articles cited by a work) and forward (articles citing a work). This study highlights Citationchaser’s contribution to making these processes efficient and accessible. The review evaluates Citationchaser's performance by examining its dependency on the Lens.org database and comparing its citation-chasing capabilities with traditional bibliometric tools. Key features of the Citationchaser web application (Shiny app), including backward and forward citation chasing, are analyzed using a sample dataset to assess retrieval accuracy and citation coverage. Limitations, such as database dependency, update delays, and network visualization, are also discussed. Citationchaser streamlines citation chasing by automating the retrieval of references and citations, making it a valuable tool for researchers with limited access to traditional citation indexes. However, its reliance on Lens.org limits its coverage, and the discontinuation of Microsoft Academic Graph poses challenges to its comprehensiveness. Additionally, the ‘Network’ and ‘Analysis’ feature lacks the sophistication required for effective citation mapping, suggesting that researchers may need to complement Citationchaser with other bibliometric tools for advanced analyses. This review provides the first critical assessment of Citationchaser as a citation-chasing tool for systematic reviews. By examining its strengths, limitations, and future potential, this study offers insights into how Citationchaser could evolve to meet researchers' needs more comprehensively, positioning it as a potentially valuable addition to research support services for systematic reviews.

Analisis Penerapan Vektor 2D Menggunakan Laboratorium Virtual PhET

Physics explores natural phenomena ranging from everyday experiences to abstract concepts, with vectors being a fundamental component essential for analyzing motion and other physical occurrences. Vectors, defined by their magnitude and direction, are key to describing various phenomena such as force, speed, and acceleration. Utilizing virtual laboratories like PhET offers an excellent opportunity to enhance understanding of vector concepts through interactive simulations. This research focuses on the application of 2D vectors using the PhET virtual laboratory. The research methods include quantitative experiments, where participants engage with vector simulations in a virtual environment. The results indicate that variations in the angle and magnitude of vectors significantly impact the resultant vector's value. These interactive simulations allow for real-time visualization and manipulation of parameters, leading to a deeper comprehension of the subject. Despite some limitations, including the necessity for technological access and the potential for oversimplifying physical phenomena, the benefits of these simulations make them invaluable tools for teaching and research in vector studies. Overall, PhET simulations accelerate the learning process, providing students with a richer and more practical experience to better grasp vector concepts.

Methodological Quality and Content of Guidelines on Early Childhood Allergy Prevention: A Systematic Assessment and Content Analysis.

Recommendations on Early Childhood Allergy Prevention (ECAP) are found in Clinical Practice Guidelines (CPG) and Food-Based Dietary Guidelines (FBDG). This synthesis of guidelines aims to compare the methodological quality and content of recommendations in CPGs and FBDGs for ECAP. We searched MEDLINE, the FAO directory of FBDGs and other guideline databases, including the Association of the Scientific Medical Societies in Germany (AWMF), the WHO and the Guideline International Networks database on clinical guidelines (GIN) for CPGs and FBDGs about ECAP and child nutrition. Guidelines had to be published from 2010 onwards, target infants or pregnant/breastfeeding women and contain recommendations on primary preventative interventions to decrease the onset of IgE-mediated allergies, including atopic eczema or asthma. We retrieved a sample of 36 guidelines (23 CPGs, 13 FBDGs) and assessed their methodological quality with the Appraisal of Guidelines for Research and Evaluation tool (AGREE) II. On a subset of recommendations, we performed an in-depth analysis by the type of intervention for direction and strength of recommendation and level of evidence. Descriptive analysis was conducted with SPSS 27. CPGs score higher than FBDGs in most AGREE domains (3, 4, 5 and 6). The 36 guidelines contain 287 recommendations on ECAP, with 70 addressing the introduction of complementary foods and common allergens. We found only slight differences between those recommendations in CPGs and FBDGs. FBDGs on ECAP are of lower quality than CPGs. This does not affect their recommendations on the introduction of complementary foods and common allergens but may compromise their trustworthiness.

Intersection of Studious Legal Research Philosophies and Scientific Chics In Nigeria: A Comprehensive Analysis

This study investigates the Intersection of Studious Legal Research Philosophies and Scientific Chics in Nigeria: a comprehensive analysis considering the challenges and opportunities in transitioning from traditional legal research approaches to systematic, procedural, and scientific methodologies in academic legal research in Nigeria. The study employed Non-doctrinal legal research design, though OSCOLA and NALT citation style were employed do to the nature of the study. Likert scale was used to compute the Mean for descriptive analysis and ANOVA was used for inferential statistical analysis, four hypotheses were tested to examine the utilization of scientific approaches, availability of relevant data and tools, institutional support, and the impact of citation styles on scientific legal research. The findings reveal that the utilization of scientific approaches remains low, despite adequate availability of resources. Institutional support for scientific methodologies is insufficient, and the current citation styles significantly affect the implementation of scientific approaches. Recommendations include comprehensive training programs, enhanced access to research tools, prioritization of scientific methodologies by academic institutions, and revision of citation styles or to develop Okuma-NC (hybrid) citation model to better support scientific research. These insights aim to contribute to the advancement of legal scholarship in Nigeria by promoting more rigorous, empirical, and interdisciplinary research practices.

Pharmacologically inducing regenerative cardiac cells by small molecule drugs

Adult mammals, unlike some lower organisms, lack the ability to regenerate damaged hearts through cardiomyocytes (CMs) dedifferentiation into cells with regenerative capacity. Developing conditions to induce such naturally unavailable cells with potential to proliferate and differentiate into CMs, that is, regenerative cardiac cells (RCCs), in mammals will provide new insights and tools for heart regeneration research. In this study, we demonstrate that a two-compound combination, CHIR99021 and A-485 (2C), effectively induces RCCs from human embryonic stem cell-derived TNNT2+ CMs in vitro, as evidenced by lineage tracing experiments. Functional analysis shows that these RCCs express a broad spectrum of cardiogenesis genes and have the potential to differentiate into functional CMs, endothelial cells, and smooth muscle cells. Importantly, similar results were observed in neonatal rat CMs both in vitro and in vivo. Remarkably, administering 2C in adult mouse hearts significantly enhances survival and improves heart function post-myocardial infarction. Mechanistically, CHIR99021 is crucial for the transcriptional and epigenetic activation of genes essential for RCC development, while A-485 primarily suppresses H3K27Ac and particularly H3K9Ac in CMs. Their synergistic effect enhances these modifications on RCC genes, facilitating the transition from CMs to RCCs. Therefore, our findings demonstrate the feasibility and reveal the mechanisms of pharmacological induction of RCCs from endogenous CMs, which could offer a promising regenerative strategy to repair injured hearts.

Pharmacologically inducing regenerative cardiac cells by small molecule drugs.

Adult mammals, unlike some lower organisms, lack the ability to regenerate damaged hearts through cardiomyocytes (CMs) dedifferentiation into cells with regenerative capacity. Developing conditions to induce such naturally unavailable cells with potential to proliferate and differentiate into CMs, that is, regenerative cardiac cells (RCCs), in mammals will provide new insights and tools for heart regeneration research. In this study, we demonstrate that a two-compound combination, CHIR99021 and A-485 (2C), effectively induces RCCs from human embryonic stem cell-derived TNNT2+ CMs in vitro, as evidenced by lineage tracing experiments. Functional analysis shows that these RCCs express a broad spectrum of cardiogenesis genes and have the potential to differentiate into functional CMs, endothelial cells, and smooth muscle cells. Importantly, similar results were observed in neonatal rat CMs both in vitro and in vivo. Remarkably, administering 2C in adult mouse hearts significantly enhances survival and improves heart function post-myocardial infarction. Mechanistically, CHIR99021 is crucial for the transcriptional and epigenetic activation of genes essential for RCC development, while A-485 primarily suppresses H3K27Ac and particularly H3K9Ac in CMs. Their synergistic effect enhances these modifications on RCC genes, facilitating the transition from CMs to RCCs. Therefore, our findings demonstrate the feasibility and reveal the mechanisms of pharmacological induction of RCCs from endogenous CMs, which could offer a promising regenerative strategy to repair injured hearts.

Cell-free placental DNA: What do we really know?

Cell-free placental DNA (cfpDNA) is present in maternal circulation during gestation. CfpDNA carries great potential as a research and clinical tool as it provides a means to investigate the placental (epi)genome across gestation, which previously required invasive placenta sampling procedures. CfpDNA has been widely implemented in the clinical setting for noninvasive prenatal testing (NIPT). Despite this, the basic biology of cfpDNA remains poorly understood, limiting the research and clinical utility of cfpDNA. This review will examine the current knowledge of cfpDNA, including origins and molecular characteristics, highlight gaps in knowledge, and discuss future research directions.

Students’ Attitude Toward Pursuance of Higher Education in Abroad Study: A Study Among Grade 12 Students in Pokhara

This article, ‘Students’ Attitude toward Pursuance of Higher Education in Abroad Study: A Study among Grade 12 Students in Pokhara’ is prepared by investigating the pertinent reasons for motivating students going abroad for higher education after completing grade twelve in Nepal. This research is guided by the objectives to study grade 12 students’ views about going abroad for higher education and to explore the migration trends in the resent years in the context of Nepal. Field visit, informal interview and the questionnaire are the major research tools for data collection. Both the qualitative and quantitative methods are used to process the received data and they are presented in the tables, charts, graphs, etc. The final data are analyzed both in numerical and theoretical interpretations. The results indicate that a large number of students are willing to go abroad for education or for job purposes whereas some students think about continuing their study here in Nepal after completing grade 12. Only one third students do not have a concrete plan for going abroad currently. Similarly, more than half of the students have a plan to go abroad in future once in their life for education which is a challenging question for our education system in Nepal and it is recommended to bring the applicable policy and create the ample opportunities for students to keep them back in the country.

Establishment and characterization of a novel patient-derived cell line from conventional central grade 3 chondrosarcoma, NCC-CS1-C1.

Chondrosarcoma (CS) is a malignant tumor that produces cartilaginous matrix and is the second most common primary bone sarcoma. CS encompasses a range of histological subtypes, with high-grade conventional central CS being particularly rare, occurring at a rate of 1.81 cases per 1 million person-years. Complete surgical resection is the standard curative treatment for this subtype, as radiation therapy and chemotherapy have proven ineffective. High-grade conventional central CS is highly metastatic and prone to recurrence, resulting in a poor prognosis. Therefore, effective multidisciplinary treatment strategies are urgently needed. Patient-derived cell lines offer promising tools for exploring new therapeutic approaches. However, only two cell lines of high-grade CSs are currently available in public cell banks. In this study, we aimed to establish a novel cell line for high-grade conventional central CS. We successfully developed the NCC-CS1-C1 cell line using surgically resected tumor tissues from a patient with conventional central grade 3 CS. This cell line harbored an IDH1 mutation (p.R132S), commonly found in 50% of CS cases, and exhibited complex copy number variants. A high-throughput screening of 221 anti-cancer drugs identified five candidates-bortezomib, carfilzomib, doxorubicin, panobinostat, and romidepsin-that demonstrated low IC50 values, indicating potential efficacy in treating CS. These findings suggest that NCC-CS1-C1 is a valuable tool for both preclinical and basic research on high-grade conventional central CS.

A Study of New Approaches to Statistical Analysis of Research data

Statistical analysis has been at the heart of scientific research, providing critical tools for data interpretation, decision-making, and hypothesis testing. Some of the ancient techniques used were hypothesis testing, regression analysis, and time series analysis, among others. Such methods have proved to be good tools for researchers dealing with smaller and more structured datasets. However, the large size and complexity of the dataset exposed the weaknesses in such classical approaches, especially in handling large, unstructured, or non-linear datasets. Increased computing power and the development of machine learning algorithms have increased flexibility, nudging the statistical approach towards more flexible, data-driven methods. This paper reviews emerging approaches such as machine learning, deep learning, Bayesian methods, and network analysis and places an emphasis on how these approaches can be applied over a range of fields where they could vastly transform statistical analysis. Based on this review, comparing traditional and modern methodologies, it thereby demonstrates how innovations better complement rather than replacing the capabilities of statistical analysis, thus shaping the future of research in this changing environment.

Impact of the Quality of Financial and Banking Applications Used on Smartphone on the Customer Satisfaction of Jordanian Islamic Bank

This study aimed to identify the impact of the quality of financial and banking applications through the dimensions of (information security, trust, privacy) used on smartphones on the satisfaction of Jordanian Islamic bank customers. The researcher employed a descriptive-analytical approach in constructing the study. The study population consisted of all customers of Jordanian Islamic banks. The researcher developed a research tool (a questionnaire) to align with the study’s dimensions. A random sample of Islamic bank customers was selected, and the research tool was distributed to them electronically. The researcher was able to obtain responses from 249 participants. One of the key findings of the study was that there is a high level of usage of financial and banking applications on smartphones in Islamic banks. Among the dimensions, “privacy” ranked the highest in importance based on the participants’ responses. The results also revealed a significant impact of the quality of financial and banking applications used on smartphones, through the dimensions of (information security, trust, and privacy), at a significance level of (α ≤ 0.05) on the satisfaction of Jordanian Islamic bank customers. Among the key recommendations was the need for greater focus on quality factors related to financial and banking applications by emphasizing the dimensions of information security, trust, privacy, and data protection due to their significant role and impact on customers using these applications. Additionally, there is a potential for further research and studies on the factors affecting the quality of financial and banking applications on smartphones for electronic banking services offered to customers.

Toxicological Effects of Pendimethalin: Behavioral Changes and LC50 Analysis in Cyprinus carpio

The pre-emergent herbicide pendimethalin is a selective dinitroaniline compound that interferes with the production of microtubules, potentially contaminating groundwater. The current investigation sought to ascertain the acute toxicity levels and behavioral effects of pendimethalin (30% EC) on Cyprinus carpio. Finney's probit bioassay method estimated the lethal toxicity LC50 values for commercial-grade herbicide pendimethalin on C. carpio. This method entails fitting the data collected from experiments to a probit model, which converts the results obtained (such as mortality rates) into a normal distribution scale. It is a useful tool in toxicological research since it enables more precise estimations of the LC50. The lethal toxicity (LC50) values of pendimethalin to C. carpio exposed to 24, 48, 72 and 96-hr were determined to be 2.83µL/L, 2.59µL/L, 2.39µL/L and 2.20µL/L based on the mortality estimations. Pendimethalin-induced behavioral abnormalities in C. carpio were investigated using sublethal concentrations (i.e., 1/15th, 1/10th, and 1/5th of the 96-hour LC50 value) at intervals of 0, 7, 14, 21 and 28 days. Our research observed behavioral shifts such as reduced general activity, reduced foraging behavior, diminished schooling behavior, reduced reflex stimuli, increased opercula movements, irregular movements, mucus secretion, enhanced breathing rates and increased surface air gulping. Our studies showed that pendimethalin can produce both mortality and behavioral alterations in Cyprinus carpio, offering important insights into the pendimethalin fatal and sub-lethal effects. These results highlight how crucial it is to keep an eye on herbicide poisoning in aquatic habitats since even sub-lethal levels can have an effect on fish behavior and the general health of the ecosystem.

Personality-Driven Adoption of WhatsApp and Facebook for Educational Collaboration: Academic Performance as a Mediator

The Big Five Personality Traits—openness, conscientiousness, extraversion, agreeableness, and neuroticism—are widely regarded as a comprehensive framework for understanding individual differences. These traits influence various behaviors, including social interactions, learning preferences, and technology adoption. Objectives of the study were; 1) To analyze the relationship between the Big Five Personality Traits and students' adoption of WhatsApp and Facebook for educational collaboration. 2) To investigate the association between social network site usage and academic performance of the students. 3) To evaluate the mediating role of academic performance in the relationship between the Big Five Personality Traits and the educational use of WhatsApp and Facebook. All 8617 Students of grade 10th of District Attock, (4,868 Boys & 3,749 Girls) at secondary and higher secondary school level in 248 public schools were the population of the study. 816 students were the sample for this study from the population. Proportional Sampling technique was used for sampling. Big Five Personality Tool consists of 39, Usage of Social Network Sites tool consists of twenty nine different items for five basic and commonly used Social Network Sites. Reliability of the tools was found by using Cronbach’s Alpha. For content validity, both research tools were validated from the experts of field of education while for construct validity, EFA was performed. The findings from the PROCESS procedure (Model 4) offer insights into the relationships between Big Five Personality Traits (BFPTs), Academic Performance (AP), and Social Network Sites (SNSs). The analysis shows that BFPTs significantly predict Scholastic Performance (SP), with a positive coefficient of 1.528 (p < 0.01). The model's R-squared value of 0.528 indicates that 52.81% of the variance in Scholastic Performance can be explained by BFPTs. This relationship suggests that students' personality traits are strongly related to their academic performance. Hence, it is recommended that, Interventions should focus on improving both Scholastic Performance and personality traits to help students manage their social media usage effectively.

DL-CSPF: deep-learning-based cell segmentation with a physical framework for digital holographic microscopy

Digital holographic microscopy (DHM) offers label-free, full-field imaging of live-cell samples by capturing optical path differences to produce quantitative phase images. Accurate cell segmentation from phase images is crucial for long-term quantitative analysis. However, complicated cellular states (e.g., cell adhesion, proliferation, and apoptosis) and imaging conditions (e.g., noise and magnification) pose significant challenge to the accuracy of cell segmentation. Here, we introduce DL-CSPF, a deep-learning-based cell segmentation method with a physical framework designed for high-precision live-cell analysis. DL-CSPF utilizes two neural networks for foreground-background segmentation and cell detection, generating foreground edges and “seed points.” These features serve as input for a marker-controlled watershed algorithm to segment cells. By focusing on foreground edges and “seed points”, which have lower information entropy than complete cell contours, DL-CSPF achieves accurate segmentation with a reduced dataset and without manual parameter tuning. We validated the feasibility and generalization of DL-CSPF using various open-source and DHM-collected datasets, including HeLa, pollen, and COS-7 cells. Long-term live-cell imaging results further demonstrate that DL-CSPF reliably characterized and quantitatively analyzed the morphological metrics across the cellular lifecycle, rendering it a promising tool for biomedical research.

Advances and Challenges in Species Ecological Niche Modeling: A Mixed Review

Species distribution modeling (SDM) is a vital tool for ecological and biogeographical research, allowing precise predictions of species distributions based on environmental variables. This study reviews the evolution of SDM techniques from 1985 to 2023, focusing on model development and applications in conservation, climate change adaptation, and invasive species management. We employed a mixed review with bibliometric and systematic element approaches using the Scopus database, analyzing 982 documents from 275 sources. The MaxEnt model emerged as the most frequently used technique, applied in 85% of the studies due to its adaptability and accuracy. Our findings highlight the increasing trend in international collaboration, particularly between China, the United Kingdom, and Brazil. The study reveals a significant annual growth rate of 11.99%, driven by technological advancements and the urgency to address biodiversity loss. Our analysis also shows that while MaxEnt remains dominant, deep learning and other advanced computational techniques are gaining traction, reflecting a shift toward integrating AI in ecological modeling. The results emphasize the importance of global cooperation and the continued evolution of SDM methodologies, projecting further integration of real-time data sources like UAVs and satellite imagery to enhance model precision and applicability in future conservation efforts.

Towards the development of an algorithm for automatic analysis and detection of shock waves in the schlieren visualization technique

This paper presents the development of an algorithm for identifying shock waves formed during the supersonic combustion process, detonation, in a pulsed detonation chamber. The algorithm is based on image binarization techniques, followed by the identification of regions of interest in the images, the detection and isolation of the edges of these regions, and the determination of the wave speed between two consecutive frames. The advantage of this automation process is the efficiency in analysing the repeated detonation cycles of a pulsed detonation chamber. Additionally, it can provide a more accurate evaluation of the data, making it a valuable tool for researchers and engineers in various scientific fields and shock wave applications.

Coupled Hydrodynamic and Biogeochemical Modeling in the Galician Rías Baixas (NW Iberian Peninsula) Using Delft3D: Model Validation and Performance

Estuaries are dynamic and resource-rich ecosystems renowned for their high productivity and ecological significance. The Rías Baixas, located in the northwest of the Iberian Peninsula, consist of four highly productive estuaries that support the region’s economy through key fisheries and aquaculture activities. Numerical modeling of biogeochemical processes in the rias is essential to address environmental and anthropogenic pressures, particularly in areas facing intense human development. This study presents a high-resolution water quality model developed using Delft3D 4 software, integrating the hydrodynamic (Delft3D-FLOW) and water quality (Delft3D-WAQ) modules. Calibration and validation demonstrate the robust performance and reliability of the model in simulating critical biogeochemical processes, such as nutrient cycling and phytoplankton dynamics. The model effectively captures seasonal and spatial variations in water quality parameters, including water temperature, salinity, inorganic nutrients, dissolved oxygen, and chlorophyll-a. Of the variables studied, the model performed best for dissolved oxygen, followed by nitrates, phosphates, ammonium, silicate, and chlorophyll-a. While some discrepancies were observed in the inner zones and deeper layers of the rias, the overall performance metrics aligned closely with the observed data, enhancing confidence in the model’s utility for future research and resource management. These results highlight the model’s value as a tool for research and managing water and marine resources in the Rías Baixas.

Exploratory assessment of the parent attitudes about childhood vaccines survey tool to assess vaccine hesitancy and pet vaccination status among pet owners.

To assess the applicability of the parent attitudes about childhood vaccines (PACV) survey to pet owners and its association with vaccine hesitancy. A national survey including an adapted version of the PACV was administered to 2,853 dog and 1,977 cat owners. Respondents were queried about the vaccination status of their pets. Exploratory factor analysis, Mokken scale analysis, Cronbach α, McDonald ω, and bivariate analyses were used to assess the validity and reliability of the PACV and shortened versions. The Fisher exact test and linear probability models were used to assess the association between the PACV and other factors and vaccination status. The PACVs for pet owners were valid and reliable with high internal consistency and served as correlates for vaccination status. In multivariate analyses, long-term relationships with veterinarians were also associated with vaccination. Individual survey items indicated substantial concerns about vaccine safety, side effects, and efficacy. Most respondents indicated trust and good relationships with their veterinarian, had not avoided or delayed vaccinations, understood the severity of pet diseases, supported the recommended vaccine schedule, and did not self-identify as vaccine hesitant (VH). The PACV identified 21.7% of dogs and 25.9% of cat owners as VH. The full and the reduced versions of the PACV are valid and reliable tools to assess VH status in dog and cat owners. The PACV could serve as an important tool for veterinary researchers to identify factors associated with vaccine hesitancy and develop effective interventions.

I.Sicily as a Tool for the Study of Roman Sicily: An Experiment in Institutional Annotation

Study of Roman Sicily is well established and has a long tradition, with the two most authoritative and well-established epigraphic corpora –CIL X (1883) and IG XIV (1890)– dating to the late 19th century. While I.Sicily was conceived to offer easy and up-to-date access to the evergrowing but increasingly scattered epigraphic evidence of Sicily, its digital nature also enables the adoption of new approaches and the pursuit of novel research questions. The open-access dataset has recently been expanded to include institutional annotations, which hold great promise for research, particularly in fields that rely on extensive and detailed datasets, such as administrative and onomastic history (prosopographic annotation will follow). This paper aims to demonstrate both the potential and the limitations of a digitally annotated dataset as a tool for historical research, through a preliminary case study on the practice of dedications to the Roman emperor in Sicily. Recent scholarship suggests that provincial subjects also contributed to shaping the notion and the expectations around emperorship, which were not only imposed from above. The data-driven approach facilitated by an annotated corpus is well-suited to the new bottom-up perspective, but it is not without methodological pitfalls, which will be highlighted in this paper.