MethodsXPub Date : 2025-09-02DOI: 10.1016/j.mex.2025.103603
Kai-Ti Wu , Markus Venohr , Linda See , Dagmar Haase
{"title":"Linking social media data with geospatial information to analyse changes in human sentiments in and along surface water environments","authors":"Kai-Ti Wu , Markus Venohr , Linda See , Dagmar Haase","doi":"10.1016/j.mex.2025.103603","DOIUrl":"10.1016/j.mex.2025.103603","url":null,"abstract":"<div><div>Social media data represent a valuable source of information on human activity patterns and emotional responses in relation to natural environments. These data can provide insights into the drivers of human sentiments toward freshwater ecosystems, especially in contexts where traditional survey methods are insufficient or resource intensive. A better understanding of the relationship between human sentiments and the perceived value of freshwater environments can support the integration of public perspectives into ecosystem management and regional development. In this paper, we present a replicable method for acquiring, cleaning, and analysing geolocated Twitter data from 2011 to 2018 from Germany. The method includes multiple data cleaning and filtering steps to prepare the dataset for identifying spatial and temporal trends in sentiments and to determine the primary drivers of emotional responses to water bodies. The demonstrated workflow includes the following steps:</div><div>• Geo-located Tweets were collected via the Twitter API, then sorted, indexed, and subjected to filtering and cleaning to ensure data quality.</div><div>• Language detection and sentiment analysis using a lexicon-based method (Polyglot), suitable for limited computing power, short-text social media sentiment analysis, particularly in the context of analysing the content posted by individuals spending time in freshwater ecosystems.</div><div>• Geospatial enrichment, incorporating contextual data such as weather, population density, and other location-based variables.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103603"},"PeriodicalIF":1.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-09-02DOI: 10.1016/j.mex.2025.103591
Max Hahn-Klimroth , João Pedro Meireles , Laurie Bingaman Lackey , Nick van Eeuwijk , Mads F. Bertelsen , Paul W. Dierkes , Marcus Clauss
{"title":"A semi-automatic approach to study population dynamics based on population pyramids","authors":"Max Hahn-Klimroth , João Pedro Meireles , Laurie Bingaman Lackey , Nick van Eeuwijk , Mads F. Bertelsen , Paul W. Dierkes , Marcus Clauss","doi":"10.1016/j.mex.2025.103591","DOIUrl":"10.1016/j.mex.2025.103591","url":null,"abstract":"<div><div>The depiction of populations – of humans or animals – as ‘population pyramids’ is a useful tool for the assessment of various characteristics of populations at a glance. Although these visualisations are well-known objects in various communities, formalised and algorithmic approaches to gain information from these data are less present. Here, we present an algorithm-based classification of population data into ‘pyramids’ of different shapes that can be linked to typical demographic properties. The classification accuracy of the algorithm was tested on over 50,000 population pyramids from 450 mammal species. The approach delivers plausible classifications, in particular with respect to changes in population size linked to specific series of, and transitions between, different ‘pyramid’ shapes. We believe this approach might become a useful tool for analysing and communicating historical population developments in multiple contexts and is of broad interest. Moreover, it might be useful for animal population management strategies.<ul><li><span>•</span><span><div>Introducing a deterministic algorithmic approach to classify population pyramid data.</div></span></li><li><span>•</span><span><div>Data discretization step to reduce data complexity and to unify data.</div></span></li><li><span>•</span><span><div>Classification of a population pyramid into non-species-specific shape categories that are linked to specific characteristics of the population.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103591"},"PeriodicalIF":1.9,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Voice-based user interface for hands-free data entry and automation at workplaces","authors":"Daiwiik Harihar, Vedansh Shrivastava, Pratvina Talele, Aditi Jahagirdar","doi":"10.1016/j.mex.2025.103596","DOIUrl":"10.1016/j.mex.2025.103596","url":null,"abstract":"<div><div>The increasing demand for hands-free interaction in modern workplaces has led to the development of Voice-Based User Interfaces (VUIs) that enhance accessibility, efficiency and automation. This research presents the Voice-Based User Interface for Hands-Free Data Entry and Automation at Workplaces. The system enables real-time speech-to-text transcription, allowing users to interact with workplace applications without manual input, making it intuitive, user-friendly and capable of enhancing efficiency and convenience in various workplace scenarios. Through extensive testing and evaluation, the study demonstrates the practicality and benefits of the Voice-Based User Interface for hands-free data entry and automation.</div><div><strong>Methodology Overview</strong>:<ul><li><span>•</span><span><div>Utilized WIT.AI API for speech-to-text transcription.</div></span></li><li><span>•</span><span><div>Implemented chunking, caching, and concurrency control to optimize processing.</div></span></li><li><span>•</span><span><div>Evaluated performance using Word Error Rate (WER), Levenshtein Distance and Cosine Similarity on real world datasets.</div></span></li></ul>The system proves to be upto 88.8% accurate in recognizing spoken commands and efficiently converting them into text with best performance achieved when the audio was divided into 7 optimal chunks. Cosine Similarity for these chunks is more accurate than that of sizeable file and approximately 2. Moreover, the integration of real-time updates across different domains (educational, legal, medical) and data synchronization enhances productivity and usability. In conclusion, the Voice-Based User Interface offers a viable solution for hands-free data entry and automation at workplaces.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103596"},"PeriodicalIF":1.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-08-28DOI: 10.1016/j.mex.2025.103593
Md Shaheenur Rahman , Anna Chlingaryan , Peter C. Thomson , Mohammed Rafiq Islam , Angela M. Lees , Pablo Gregorini , Fabiellen Cristina Pereira , Cameron E.F. Clark
{"title":"In vitro simulation of drinking events in cattle","authors":"Md Shaheenur Rahman , Anna Chlingaryan , Peter C. Thomson , Mohammed Rafiq Islam , Angela M. Lees , Pablo Gregorini , Fabiellen Cristina Pereira , Cameron E.F. Clark","doi":"10.1016/j.mex.2025.103593","DOIUrl":"10.1016/j.mex.2025.103593","url":null,"abstract":"<div><div>Drinking causes a rapid decline in reticulorumen temperature (RT) followed by an exponential recovery, which may potentially impact the reticulorumen ecosystem. However, the nexus between drinking events and their effects on ruminal fermentation and microbial diversity has not yet been studied, either <em>in vitro</em> or <em>in vivo</em>. Although artificial (<em>in vitro</em>) rumen systems are widely used in ruminant research to simulate the reticulorumen environment, no such simulation has been described to consider the impact of drinking events on the reticulorumen environment. Therefore, we have developed a method for the <em>in vitro</em> simulation of drinking events in the fermentation jar where the jar temperature was considered a proxy for RT is reduced by adding a measured amount of cold water to the water bath, and the subsequent recovery period is achieved following a temperature profile regulated by a heating immersion circulator. This method enables the replication of RT fluctuations from drinking events, allowing for the monitoring of their impact on fermentation characteristics and microbial ecology in future research. The features of this method are:</div><div>Creation of a hypothetical drinking event</div><div>Estimation of volume and temperature of cold water for a drinking event</div><div>Establishing a temperature profile to regulate the recovery period</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103593"},"PeriodicalIF":1.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-08-28DOI: 10.1016/j.mex.2025.103598
Ole Desens, Jörg Meyer, Achim Dittler
{"title":"Application of python image analysis tools for particle structure detachment detection in high‑speed videos during model filter regeneration","authors":"Ole Desens, Jörg Meyer, Achim Dittler","doi":"10.1016/j.mex.2025.103598","DOIUrl":"10.1016/j.mex.2025.103598","url":null,"abstract":"<div><div>Combustion-related particulate emissions are a challenge to air quality and regulatory compliance. In modern combustion engines, wall-flow particulate filters effectively capture soot particles, whereby periodic high-temperature (0<sub>2</sub>) regeneration or passive (NO<sub>2</sub>) regeneration is necessary to reduce the pressure drop. During regeneration, the soot layer breaks up, and small particle structures can detach and be transported further downstream towards the end of the filter channel. A Python-based image analysis workflow is presented for detecting and verifying particle structure detachments in high-speed video recordings of the filter regeneration. The method consists of two integrated modules using OpenCV and NumPy. In the first step, background subtraction (MOG2) and morphological operations are applied to identify candidate structures across video frames. The second step checks the particle structures detected in the first step, isolates a region of interest around the potential detachment and analyzes it using thresholding and pixel-wise difference mapping to confirm or reject the detachment event. Both modules allow parameters to be set and generate visual outputs for verification. The method was validated using a 796,000 frames dataset in which a model filter channel with carbon black loading was regenerated and six small detachment events (<em>x</em><sub>eq</sub> ≈ 100 - 300 µm) were detected.</div><div>• A Python-based method for detection of particle structure detachments in high‑speed videos of model filter regeneration.</div><div>• Semi-automated two-step detection and verification of detachments.</div><div>• Validated on 796 000 frames, reliably finding detachment events while reducing manual review time.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103598"},"PeriodicalIF":1.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-08-28DOI: 10.1016/j.mex.2025.103592
Rossana Margaret Kadar Yanti , Ria Asih Aryani Soemitro , Mahendra Andiek Maulana , Trihanyndio Rendy Satrya , Dwa Desa Warnana , Moh Muntaha
{"title":"Monthly monitoring of suspended sediment variability using bottle samplers in the LUSI outfall area of the Porong River","authors":"Rossana Margaret Kadar Yanti , Ria Asih Aryani Soemitro , Mahendra Andiek Maulana , Trihanyndio Rendy Satrya , Dwa Desa Warnana , Moh Muntaha","doi":"10.1016/j.mex.2025.103592","DOIUrl":"10.1016/j.mex.2025.103592","url":null,"abstract":"<div><div>Monitoring suspended sediment concentration (SSC) is important for understanding sediment dynamics in extreme tropical rivers influenced by both natural and human activities. The Porong River in East Java constantly receives sediment input from LUSI (short for Lumpur Sidoarjo), a hot mud volcano formed after a drilling incident at Banjar Panji-1 in May 2006. The eruption inundated over 6.3 km² of settlements, farmland, and infrastructure, displacing about 30,000 people and causing persistently high sediment loads with extremely turbid flows. This study developed a field-based SSC sampling method by modifying the USDH-48 bottle, replacing standard rods with flexible ropes for manual operation of orientation and depth in deep, high-energy flows. The method uses a systematic spatial-vertical sampling strategy across several cross-sections to capture sediment variability. In contrast to ASTM D3977–97, which is designed mainly for shallow, steady-flow rivers, this method accommodates greater depths and unsteady-flow rivers through flexible deployment and structured sampling coverage. Over one year, monthly monitoring produced 864 samples. Validation against a messenger-system vertical sampler at the same location and depth showed strong statistical agreement (R² > 0.80; RMSE < 20 %).</div><div>Adaptive field methods based on the modification of USDH-48 for extreme tropical rivers.</div><div>Structured design capturing spatial and vertical sediment variability.</div><div>Statistically validated against an established vertical water sampling system.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103592"},"PeriodicalIF":1.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-08-24DOI: 10.1016/j.mex.2025.103583
Ary Mazharuddin Shiddiqi , Moch. Nafkhan Alzamzami , Ilham Gurat Adillion , Mohammad Idris Arif Budiman , Ricardo Supriyanto , Muhammad Machmud
{"title":"Findme-scholar: a contextual researcher recommender system for enhancing research collaboration using adaptive topic interest area modelling","authors":"Ary Mazharuddin Shiddiqi , Moch. Nafkhan Alzamzami , Ilham Gurat Adillion , Mohammad Idris Arif Budiman , Ricardo Supriyanto , Muhammad Machmud","doi":"10.1016/j.mex.2025.103583","DOIUrl":"10.1016/j.mex.2025.103583","url":null,"abstract":"<div><div>Identifying potential research collaborators with aligned expertise and complementary interests remains a persistent challenge, particularly in multidisciplinary and large-scale academic environments. This paper introduces Findme-Scholar, a contextual researcher recommender system aimed at enhancing research collaboration through adaptive topic interest area modelling. The system dynamically captures researchers' evolving thematic interests by analyzing publication metadata and semantic content to provide context-aware recommendations that surpass traditional static profile matching approaches. Our method successfully recommended researchers without prior co-authorship links to the target individual, demonstrating its ability to identify potential collaborators beyond existing networks. This result reflects the method’s effectiveness in capturing thematic and contextual similarities to discover relevant yet previously unconnected researchers.<ul><li><span>•</span><span><div>Findme-Scholar models evolving research interests for better collaboration.</div></span></li><li><span>•</span><span><div>Recommends collaborators beyond existing co-authorship networks.</div></span></li><li><span>•</span><span><div>Uses semantic and metadata analysis for context-aware suggestions.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103583"},"PeriodicalIF":1.9,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-08-22DOI: 10.1016/j.mex.2025.103574
Umair Mohammad , Fahad Saeed
{"title":"MLSPred-bench: Transforming electroencephalography (EEG) datasets into machine learning-ready epileptic seizure prediction benchmarks","authors":"Umair Mohammad , Fahad Saeed","doi":"10.1016/j.mex.2025.103574","DOIUrl":"10.1016/j.mex.2025.103574","url":null,"abstract":"<div><div>Predicting epileptic seizures is a significantly more challenging task compared to seizure detection. However, most publicly available electroencephalography (EEG) datasets are geared towards detection because the ictal phase (main symptomatic period) is annotated. In contrast, prediction requires the availability of annotated preictal and interictal phases. To this end, we designed and developed a method called <strong><em>MLSPred-Bench</em></strong> that can be used for converting any EEG big data annotated for detection into ML-ready data suitable for prediction. We apply our methods to the existing EEG data corpus to generate 12 ML-ready benchmarks comprising data for training, validating, and testing seizure prediction models. Our strategy uses different variations of seizure prediction horizon (SPH) and the seizure occurrence period (SOP) to produce >150GB of ML-ready data. To illustrate the usefulness of the generated data, we technically validate all the benchmarks using multiple machine learning (ML) and deep learning (DL) models. We hope that the generated benchmarking data will be utilized by various computational groups for their seizure prediction model development.</div><div>The work can be summarized as follows:<ul><li><span>1.</span><span><div>Extract short preictal and interictal segments from long-duration annotated EEG montages.</div></span></li><li><span>2.</span><span><div>Generate a comprehensive list of ML-ready benchmarks with varying SPH and SOP.</div></span></li><li><span>3.</span><span><div>Technically validate the generated data with multiple ML and DL models with up-to 88.73 % validation accuracy</div></span></li><li><span>4.</span><span><div>Opensource code and related materials are available at <span><span>https://github.com/pcdslab/MLSPred-Bench</span><svg><path></path></svg></span>.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103574"},"PeriodicalIF":1.9,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MethodsXPub Date : 2025-08-19DOI: 10.1016/j.mex.2025.103576
Preeti Mishra , Sayali Apte , Vaishnavi Dhok
{"title":"Assessing the environmental impact and risks associated with uncontrolled disposal of end-of-life lithium-ion batteries on soil","authors":"Preeti Mishra , Sayali Apte , Vaishnavi Dhok","doi":"10.1016/j.mex.2025.103576","DOIUrl":"10.1016/j.mex.2025.103576","url":null,"abstract":"<div><div>The growing use of electric vehicles (EVs) has led to a sharp increase in battery waste, particularly from end-of-life (EOL) lithium-ion batteries (LiBs). A significant portion of this waste is not properly recycled but instead ends up being incinerated, landfilled, or processed through informal channels. Such practices contribute to environmental degradation by releasing potentially toxic elements into the air, soil, and water. This study presents a method for quantifying ecological risks from the leaching of these elements. The risk assessment considers different scenarios involving weather conditions, soil types, and groundwater levels, and presents outcomes through a risk matrix. A detailed cause-consequence analysis and quantitative risk evaluation are conducted. Laboratory testing on soil samples contaminated with LiB waste, compared against control samples, revealed marked degradation in the soil's index and engineering properties. The findings indicate that improper LiB disposal not only degrades soil quality but also poses serious threats to human health and surrounding ecosystems. Additionally, a scenario-based focused group discussion corroborated these risks. The research underscores the urgent need for effective LiB waste management practices and regulatory oversight to mitigate long-term environmental and health impacts.<ul><li><span>•</span><span><div>Quantified environmental risks of EOL lithium-ion battery waste through scenario-based analysis.</div></span></li><li><span>•</span><span><div>Laboratory testing confirmed soil degradation due to improper LiB disposal.</div></span></li><li><span>•</span><span><div>Highlights the need for regulatory action and improved waste management strategies.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103576"},"PeriodicalIF":1.9,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144890088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A workflow to discover partial differential equations from data: Application to the dynamics of tree biomass","authors":"Emilie Peynaud , Paulin Melatagia , Serge Stinckwich , Jean-François Barczi","doi":"10.1016/j.mex.2025.103560","DOIUrl":"10.1016/j.mex.2025.103560","url":null,"abstract":"<div><div>Mixed data and theory driven methods are promising approaches that can be used to bring better understanding of complex dynamics in life sciences. For vegetation growth, integrated knowledge may be lacking to design theoretical models like partial differential equations (PDE). This lack can be complemented by using data. The method presented in this paper is a generic computational workflow called CEDI that aims at discovering PDE models from data. As an illustration, we tested the workflow on biomass dynamics of three different 3D trees of specific architectural types.</div><div>● The name CEDI represents the four steps composing the workflow: data Collection, Extrapolation, Differentiation and Identification.</div><div>● The originality of this workflow is twofold: first, it encompasses the whole modeling process from the definition of the variables to the design of a PDE, and second it has been designed to be generic in a sense that it can apply to any dynamics and it covers most existing data driven PDE discovering methods.</div><div>● The workflow offers a framework to better understand data driven PDE discovering methods and a tool for modeling any dynamics, provided that right data and knowledge and also good algorithm settings are available.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"15 ","pages":"Article 103560"},"PeriodicalIF":1.9,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}