MethodsX最新文献_第8页

Upgrade of a variable temperature scanning tunneling microscope for nanometer-scale spectromicroscopy

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-07 DOI: 10.1016/j.mex.2025.103156

B. Cirera , A. Sáez-Coronado , D. Arribas , J. Méndez , A. Sagwal , R. de Campos Ferreira , M. Švec , P. Merino

Tip-enhanced Raman spectroscopy (TERS), tip-enhanced photoluminescence (TEPL), and scanning tunneling microscope-induced luminescence (STML) combine the high spatial resolution of probe microscopies with the spectroscopic capabilities of optical techniques. Here, we describe the upgrade of an ultrahigh vacuum (UHV) variable-temperature scanning probe microscope (VT-SPM) to perform tip-enhanced spectromicroscopy experiments at cryogenic temperatures. The home-made design includes a portable focusing lens (NA=0.45) that allows the simultaneous collection and injection of light from the tip-sample junction while assuring easy tip and sample transfers. We demonstrate the capabilities of our upgrade to resolve electroluminescence (EL), Raman, and TERS spectra using plasmonically active probes (Ag and Au tips) on various surfaces. We are able to observe the vibrational levels of C₆₀ deposited on Ag(111) with a lateral resolution of ∼2 nanometers. Moreover, we use the tunability of the gap plasmon distribution to observe intense anti-Stokes signals of C₆₀, highlighting the spectral sensitivity of the system. This upgrade opens new possibilities for studying surface chemistry, catalysis, and molecular electronics at state-of-the-art spatial and spectral resolutions using accessible SPM systems.

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Portable lens holder
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In-situ adjustable position
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Nanometer-scale vibrational spectroscopy

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引用次数: 0

Deep learning driven silicon wafer defect segmentation and classification

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-06 DOI: 10.1016/j.mex.2025.103158

Rohan Ingle, Aniket K. Shahade, Mayur Gaikwad, Shruti Patil

Integrated Circuits are made of various transistors that are embedded on a silicon wafer, these wafers are difficult to process and hence are prone to defects. Defecting these defects manually is a time consuming and labour-intensive task and hence automation is necessary. Deep Learning approach is better suited in this case as it is able to generalize defects if trained properly and can be a solution to segmentation and classification of defects automatically. The segmentation model mentioned in this study achieved a Mean Absolute Error (MAE) of 0.0036, a Root Mean Squared Error (RMSE) of 0.0576, a Dice Index (DSC) of 0.7731, and an Intersection over Union (IoU) of 0.6590. The classification model achieved 0.9705 Accuracy, 0.9678 Precision, 0.9705 Recall, and 0.9676 F1 Score. In order to make this process a more interactive, an LLM with Q&A capabilities was integrated to solve any doubts and answer any questions regarding defects in wafers.

This approach helps automate the detection process thus improving quality of end product.

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Successful and precise defect segmentation and classification using Deep Learning was achieved.
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High-intensity regions after post-processing.
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An LLM offering defect analysis and guidance was streamlined.

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引用次数: 0

A single entomopathogenic nematode infection assay for Drosophila melanogaster larvae

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-06 DOI: 10.1016/j.mex.2025.103157

Sreeradha Mallick, Eric Kenney, Jacob Rashap, Ioannis Eleftherianos

The entomopathogenic nematodes (EPNs) Steinernema carpocapsae and Steinernema hermaphroditum can efficiently infect the fruit fly, Drosophila melanogaster. The EPN infective juvenile (IJ) stage is the free-living and non-feeding stage that seeks out suitable insects to infect. While previous studies have described successful infection of D. melanogaster larvae with a standard amount of 100 IJs, the pathogenicity of a single IJ nematode towards insects remains poorly understood. Given the variability in pathogenesis among individual IJs, investigating the ability of a single IJ to cause infection in fly larvae addresses a significant gap in our understanding of host-parasite interactions. This protocol aims to evaluate the infection efficiency of a single IJ of S. carpocapsae and S. hermaphroditum. This information contributes towards a better understanding of the EPN-insect interactions and promises to improve the use of EPNs in pest management strategies. The method is summarized below:

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Individual third instar wild-type D. melanogaster larvae are infected with either a single IJ or 100 IJs of either nematode species. Uninfected control larvae are treated with sterile water.
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Larval survival is monitored over time.
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Survival curves are generated, and results are statistically analyzed to determine the effect of a single nematode on the fly larval mortality.

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引用次数: 0

XSE-TomatoNet: An explainable AI based tomato leaf disease classification method using EfficientNetB0 with squeeze-and-excitation blocks and multi-scale feature fusion

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-06 DOI: 10.1016/j.mex.2025.103159

Md Assaduzzaman , Prayma Bishshash , Md. Asraful Sharker Nirob , Ahmed Al Marouf , Jon G. Rokne , Reda Alhajj

Tomatoes are globally valued for their nutritional benefits and unique taste, playing a crucial role in agricultural productivity. Accurate diagnosis of tomato leaf diseases is vital to avoid ineffective treatments that can harm plants and ecosystems. While deep learning models excel in classifying these diseases, distinguishing subtle variations remains challenging. This study introduces XSE-TomatoNet, an enhanced version of EfficientNetB0, incorporating Squeeze-and-Excitation (SE) blocks and multi-scale feature fusion to boost classification performance. XSE-TomatoNet extracts multi-scale features, refines them with SE blocks, and merges them through Global Average Pooling, providing detailed and broad insights for precise disease classification. Our approach achieves an impressive accuracy of 99.11%, with 99% precision and recall, outperforming models like MobileNet and VGG19, especially when combined with data augmentation and ablation studies. The model achieved an average training accuracy of 99.41% and a validation accuracy of 98.88% in 10-fold cross-validation, showing strong generalization to unseen data. We also used LIME and SHAP for model interpretability, offering insights into the decision-making process, and employed Grad-CAM and Grad-CAM++ to visually highlight key areas in leaf images. Finally, the best model was integrated into a web-based system for practical use by tomato cultivators.

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XSE-TomatoNet is an enhanced version of EfficientNetB0 which incorporates Squeeze-and-Excitation (SE) blocks and multi-scale feature fusion.
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XSE-TomatoNet outperformed MobileNet (87.44%) and VGG-19 (95.50%), in terms of accuracy, achieving 99.41%.
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Integration of interpretation using LIME and SHAP models gives higher level understanding of the diseases and employment of Grad-CAM and Grad-CAM++ shows visual representation of the diseased leaves.

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引用次数: 0

The solid state dispersion method for synthesizing eggshells ES/TiO2 composite to enhance photocatalytic degradation methylene blue

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-06 DOI: 10.1016/j.mex.2024.103150

Rahmawati Munir , Dadan Hamdani , Darnah , Eva Marliana , Rahmiati Munir , Sahara Hamas Intifadhah , Ratna Kusuma

The use of eggshells as a primary source for developing value-added materials has garnered significant attention in recent years due to their effectiveness as an excellent adsorbent and support. In this study, the Solid-State Dispersion (SSD) method was utilized to prepare composite photocatalysts of eggshells (ES)/TiO₂ in various ratios. TiO₂ and eggshell photocatalysts were also employed as control samples. The samples were characterized using X-ray Diffraction (XRD) to analyze the crystalline structure and phases, along with High-Resolution Transmission Electron Microscopy (HRTEM) to examine the morphology and surface structure at the microscopic level. These characterizations support the data analysis, offering insight into the relationship between structural and morphological properties and the photocatalytic performance of the composites. The photocatalytic efficiency of the composite was assessed in a suspension system using methylene blue (MB) solution as the target pollutant. Among the three different ratios, the ES/TiO2 (9:1) composite achieved the highest adsorption and 95.63 % photocatalytic degradation of MB. This indicates that the adsorptive capacity of eggshells is very high, even though it primarily serves as a support for TiO₂ in the ES/TiO₂ composite photocatalyst. The increased surface area of the TiO₂/eggshell composite photocatalyst enhanced MB solution adsorption and photocatalytic degradation, thereby improving its effectiveness. Overall, it can be concluded that eggshells have excellent potential as a support for photocatalysts and as an environmentally friendly catalyst. Some highlights in this article:

•
The Solid-State Dispersion (SSD) method is presented as an efficient and eco-friendly approach for synthesizing ES/TiO₂ composites.
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ES/TiO₂ composites effectively degraded methylene blue (MB) by 95.63 % under UV light.
•
This method promotes sustainability by reusing eggshell waste and improving environmental benefits through enhanced photocatalysis.

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引用次数: 0

Decoding user experience in exergames: A systematic scoping review of assessment methods

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-04 DOI: 10.1016/j.mex.2024.103054

Fabrízzio Martin Pelle Perez , Ericles Andrei Bellei , Juliana Rosa Nascimento , Larissa Tumelero Bombarda , Vitor de Farias Belger , Ana Carolina Bertoletti De Marchi

Exergames, which blend physical activity with digital gaming, are increasingly recognized for their potential to boost user engagement in exercise. The user perception of these games plays a critical role in sustaining this engagement. Therefore, understanding and effectively assessing user experience (UX) in exergames is crucial to maximizing their appeal and effectiveness. This study analyzes the methods and metrics for assessing UX in exergames through a systematic scoping review across multiple databases, including ACM, IEEE, ScienceDirect, Springer, and PubMed, considering publications up to November 2023. A total of 1,229 records were identified, of which 18 studies met the inclusion criteria for summarizing the assessment instruments and techniques used, the key constructs and elements discussed, and the times or settings where UX is assessed. The findings indicate a preference for validated questionnaires, underscoring a commitment to methodological soundness and enabling comparability. Additionally, the employment of motivational and physiological assessments reflects a commitment to capturing the holistic user experience. Tailored questionnaires and observational techniques underscore a customized assessment approach, attuned to the unique features of exergames and their audiences. The conclusions highlight the necessity for further longitudinal and cross-cultural studies to enhance understanding and improvement of UX in exergames.

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引用次数: 0

Development of a risk assessment software for cumulative effect

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-03 DOI: 10.1016/j.mex.2025.103155

Effah Kwabena Antwi , Gifty Osei , Wiafe Owusu-Banahene , John Boakye-Danquah , Prisca-Maria Okafor , Kobina Korankye , Akua Nyamekye Darko , Priscilla Toloo Yohuno (Apronti)

Regional Risk Assessment is essential for evaluating the environmental impacts of large-scale resource development projects. However, existing Regional Asessement (RA) frameworks often lack generalizability which hinders result standardization. To address these challenges, the Risk Assessment Framework for Cumulative Effects (RAFCE) was developed to provide a standardized approach for impact identification, prioritization, and mitigation during RA. Despite these strengths, the RAFCE's reliance on spreadsheet-based manual data entry and calculations, coupled with the absence of collaborative features, increases the risks of human error and inflates operational costs including time taken to complete an RA.

This paper proposes a software implementation of RAFCE to enhance efficiency and accuracy in the RA process. This is a novel approach that provides a platform unique of its kind for systematically evaluating the cumulative effects of resource exploration by multiple stakeholders. The development process involved three main steps:

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Developing a NoSQL Database to efficiently store and retrieves RA data,
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Implementing an API and Backend with Java Spring Boot automates critical functionalities and
•
Building a React-based Frontend Development: that provides a user-friendly interface, that simplifies data entry and software interaction.

By automating calculations and improving the user interface, the proposed software mitigates the risks associated with manual processes and significantly reduces the cost and time required for the RA process, thereby enhancing its reliability and efficiency.

{"title":"Development of a risk assessment software for cumulative effect","authors":"Effah Kwabena Antwi , Gifty Osei , Wiafe Owusu-Banahene , John Boakye-Danquah , Prisca-Maria Okafor , Kobina Korankye , Akua Nyamekye Darko , Priscilla Toloo Yohuno (Apronti)","doi":"10.1016/j.mex.2025.103155","DOIUrl":"10.1016/j.mex.2025.103155","url":null,"abstract":"<div><div>Regional Risk Assessment is essential for evaluating the environmental impacts of large-scale resource development projects. However, existing Regional Asessement (RA) frameworks often lack generalizability which hinders result standardization. To address these challenges, the Risk Assessment Framework for Cumulative Effects (RAFCE) was developed to provide a standardized approach for impact identification, prioritization, and mitigation during RA. Despite these strengths, the RAFCE's reliance on spreadsheet-based manual data entry and calculations, coupled with the absence of collaborative features, increases the risks of human error and inflates operational costs including time taken to complete an RA.</div><div>This paper proposes a software implementation of RAFCE to enhance efficiency and accuracy in the RA process. This is a novel approach that provides a platform unique of its kind for systematically evaluating the cumulative effects of resource exploration by multiple stakeholders. The development process involved three main steps:<ul><li><span>•</span><span><div>Developing a NoSQL Database to efficiently store and retrieves RA data,</div></span></li><li><span>•</span><span><div>Implementing an API and Backend with Java Spring Boot automates critical functionalities and</div></span></li><li><span>•</span><span><div>Building a React-based Frontend Development: that provides a user-friendly interface, that simplifies data entry and software interaction.</div></span></li></ul>By automating calculations and improving the user interface, the proposed software mitigates the risks associated with manual processes and significantly reduces the cost and time required for the RA process, thereby enhancing its reliability and efficiency.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103155"},"PeriodicalIF":1.6,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786697/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143080629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning and Fuzzy logic fusion approach for osteoporosis risk prediction 骨质疏松症风险预测的机器学习和模糊逻辑融合方法。

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2025-01-03 DOI: 10.1016/j.mex.2024.103152

Rabia Khushal, Dr. Ubaida Fatima

The metabolic disorder osteoporosis has affected a humongous number of individuals globally. Its progression can be slowed down by modifying lifestyle risk factors and by following appropriate treatment. In this research work, modifiable risk factors of osteoporosis have been considered. All these variables are binary thus providing incomplete information. Machine learning implementation on these factors took a large computation time and has shown poor accuracy. Thus fuzzy concept has been introduced leading to the development of a fusion of machine learning and fuzzy logic approach. Three binary variables of the considered dataset have been compared thus fuzzy input is produced which also considers the uncertainty of these binary variables and since three input variables are transformed into one the number of features has also been reduced leading to optimization of computation time and accuracy. Moreover, it guides the individual to modify lifestyle factors to slow down the disease progression or reduce the risk of osteoporosis. The proposed model is validated on the diabetes risk prediction dataset.

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The study examines modifiable binary risk factors for osteoporosis, such as diet, smoking, and exercise etc.
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A fusion of machine learning and fuzzy logic is introduced to improve accuracy and reduce computation time.
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The model, which condenses three binary inputs into one, is validated using a diabetes risk prediction dataset.

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引用次数: 0

The effectiveness of non-invasive brain stimulation in enhancing lower extremity function in children with spastic cerebral palsy: Protocol for a systematic review and meta-analysis

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2024-12-31 DOI: 10.1016/j.mex.2024.103141

Clàudia Arumí-Trujillo , Francisco José Verdejo-Amengual , Oriol Martínez-Navarro , Jord J.T. Vink , Fran Valenzuela-Pascual

Non-invasive brain stimulation (NIBS¹) techniques have emerged as a promising non-pharmacological adjunct to neurorehabilitation. Children with Cerebral Palsy (CP²) exhibit altered cortical excitability, and while CP remains incurable, physiotherapy combined with other interventions is essential for managing motor dysfunction. Although some studies have examined NIBS using various stimulation parameters, there is limited evidence regarding its effects on the lower extremities and optimal administration protocols. This review aims to evaluate the effectiveness of NIBS techniques, such as transcranial direct current stimulation (tDCS³) and repetitive transcranial magnetic stimulation (rTMS⁴), for the treatment of motor function in spastic cerebral palsy, specifically in the lower extremity. A systematic search will be conducted in databases including MEDLINE, CINAHL Plus, EMBASE, Scopus, ISI Web of Science, and the Cochrane Central Register of Controlled Trials. The search strategy will follow the PICO framework (Participants, Intervention, Comparison, Outcomes), focusing on randomized controlled trials (RCTs). Two independent reviewers will manage screening, selection, data extraction, risk of bias assessment, and grading of evidence. This review will provide key insights into the effectiveness of NIBS for lower-extremity function in children with spastic CP, guiding future research and clinical applications.

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引用次数: 0

Technique for improving concrete characteristics with bacillus: Insights on strength and durability

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2024-12-31 DOI: 10.1016/j.mex.2024.103151

Sayali Sandbhor, Sayali Apte, Shubham Puranik, Mansi Asati, Samyak Rai

Numerous problems, including weathering, cracks, leaks, and bending, among others, appear in concrete after construction. The optimum procedure for treating concrete cracks is the subject of this study. The research goal is to find potential crack treatment materials and analyze the effect on the properties of concrete caused by the addition of bacterial solution to the concrete mix along with a particular method of preparation of bacterial solution. The principal results of the experimental testing showcased a successive growth in the compressive strength when the concrete cubes were casted with the bacterial addition from Bacillus family with a significant change in the quality of concrete. Following are the primary research outcomes of the method:

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Use of Bacillus bacterial with direct addition in concrete improves concrete's performance.
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The proposed method of concrete mix with Bacillus Sphaericus Solution in 30 ml concentration, replacing partial water cement ratio, yields maximum compressive strength on 28th day curing. For expediting setting time with high compressive strength, adding Bacillus Sphaericus solution in 45 ml concentration is recommended.
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For achieving a homogenous mix with lesser cracks on 28th day, Bacillus Subtilis Spores in 30 ml concentration can be added to concrete with partial replacement of the water requirement.

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引用次数: 0