Proteic plasmid addiction systems, such as the control of cell death (Ccd), have been used for efficient plasmid DNA recombination. The CcdB toxin, which has a relatively long sequence of 309 bp, has been the predominant choice for this purpose. However, the need for shorter peptide toxins has emerged. In this study, we evaluated the utility of microcin B17 (MccB17), a peptide consisting of 43 amino acids, in promoting DNA recombination within pgMAX-II, a dual expression plasmid for both prokaryotic and mammalian systems. The insertion of the α-peptide gene from lacZ (α-complementation) demonstrated highly efficient cloning of external DNA in the pgMAX-II/MccB17 plasmid. In both E. coli and mammalian cells, the pgMAX-II/MccB17 plasmid effectively facilitated the expression of the DsRed fluorescent protein gene. The results indicate that the novel pgMAX-II/MccB17 plasmid supports efficient and straightforward subcloning of external genes, achieving dual expression in both prokaryotic (E. coli) and mammalian systems. This suggests its broad applicability as a versatile dual-expression plasmid.
•
The short toxin peptide gene, MccB17, became available.
•
MccB17 showed potential for efficient DNA recombination similar to CcdB.
•
Using MccB17, we successfully established a dual expression plasmid that functions effectively in both prokaryotic and mammalian cells.
{"title":"A dual expression plasmid with Microcin B17 compatible with both prokaryotic and mammalian systems","authors":"Agnieszka M. Murakami, Katsuhiro Nagatomo, Hiroshi Koda, Yasutaka Niwa, Manabu Murakami","doi":"10.1016/j.mex.2024.103135","DOIUrl":"10.1016/j.mex.2024.103135","url":null,"abstract":"<div><div>Proteic plasmid addiction systems, such as the control of cell death (Ccd), have been used for efficient plasmid DNA recombination. The CcdB toxin, which has a relatively long sequence of 309 bp, has been the predominant choice for this purpose. However, the need for shorter peptide toxins has emerged. In this study, we evaluated the utility of microcin B17 (MccB17), a peptide consisting of 43 amino acids, in promoting DNA recombination within pgMAX-II, a dual expression plasmid for both prokaryotic and mammalian systems. The insertion of the α-peptide gene from lacZ (α-complementation) demonstrated highly efficient cloning of external DNA in the pgMAX-II/MccB17 plasmid. In both <em>E. coli</em> and mammalian cells, the pgMAX-II/MccB17 plasmid effectively facilitated the expression of the DsRed fluorescent protein gene. The results indicate that the novel pgMAX-II/MccB17 plasmid supports efficient and straightforward subcloning of external genes, achieving dual expression in both prokaryotic (<em>E. coli</em>) and mammalian systems. This suggests its broad applicability as a versatile dual-expression plasmid.<ul><li><span>•</span><span><div>The short toxin peptide gene, MccB17, became available.</div></span></li><li><span>•</span><span><div>MccB17 showed potential for efficient DNA recombination similar to CcdB.</div></span></li><li><span>•</span><span><div>Using MccB17, we successfully established a dual expression plasmid that functions effectively in both prokaryotic and mammalian cells.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103135"},"PeriodicalIF":1.6,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11755071/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029162","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}
Tartrate-resistant acid phosphatase (TRAP) staining is widely used to stain osteoclasts in histological bone sections. The red dye formed by the conventional TRAP enzymatic reaction using naphthol AS-MX (or AS-BI) phosphate and fast red-violet (or garnet) chromogens is readily soluble in alcohol or xylene and requires air-drying prior to cover slipping or the use of an aqueous mounting medium. However, the use of an aqueous mounting medium makes it difficult to store stained specimens for a long time. In this modified method, a new fuchsin (NewFuchsin) was used as a chromogen, which enabled dehydration and clearing after staining and the use of a non-aqueous organic solvent-based mounting medium. Samples prepared using this modified TRAP activity staining method (NewFuchsin TRAP staining) have the following advantages over conventional TRAP staining:
•
The staining of sections provides a clear histological image and allows for long-term preservation.
•
The red dye formed by NewFuchsin TRAP staining can be detected not only in the bright field, but also in the fluorescent field.
•
Combined with tissue clearing using ethyl cinnamate, osteoclasts are observed using three-dimensional imaging.
{"title":"Osteoclast visualization: Tartrate-resistant acid phosphatase activity staining using NewFuchsin compatible with non-aqueous mounting and tissue clearing","authors":"Takashi Nakamura , Katsuhiro Kawaai , Yukiko Kuroda , Koichi Matsuo","doi":"10.1016/j.mex.2024.103136","DOIUrl":"10.1016/j.mex.2024.103136","url":null,"abstract":"<div><div>Tartrate-resistant acid phosphatase (TRAP) staining is widely used to stain osteoclasts in histological bone sections. The red dye formed by the conventional TRAP enzymatic reaction using naphthol AS-MX (or AS-BI) phosphate and fast red-violet (or garnet) chromogens is readily soluble in alcohol or xylene and requires air-drying prior to cover slipping or the use of an aqueous mounting medium. However, the use of an aqueous mounting medium makes it difficult to store stained specimens for a long time. In this modified method, a new fuchsin (NewFuchsin) was used as a chromogen, which enabled dehydration and clearing after staining and the use of a non-aqueous organic solvent-based mounting medium. Samples prepared using this modified TRAP activity staining method (NewFuchsin TRAP staining) have the following advantages over conventional TRAP staining:<ul><li><span>•</span><span><div>The staining of sections provides a clear histological image and allows for long-term preservation.</div></span></li><li><span>•</span><span><div>The red dye formed by NewFuchsin TRAP staining can be detected not only in the bright field, but also in the fluorescent field.</div></span></li><li><span>•</span><span><div>Combined with tissue clearing using ethyl cinnamate, osteoclasts are observed using three-dimensional imaging.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103136"},"PeriodicalIF":1.6,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11750265/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008217","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}
Pub Date : 2024-12-25DOI: 10.1016/j.mex.2024.103118
Yaochao Zheng, Alexander Lunn, Jinghui Gao, Hongyu Chen, Yao Yao
Muscle strength is a crucial metric for assessing motor function, with significant diagnostic and prognostic value. It is widely used in clinical and preclinical studies as a phenotypic indicator. In mouse models of neuromuscular disorders, grip strength provides a direct, repeatable measure of motor function changes throughout disease progression. Hindlimbs are critical evaluative targets in research due to their relevancy to rodent motor functions, but assessing their strength remains a challenge. Existing methods, such as the wire-hanging test, in vivo quadriceps contractility measurements, and isolated muscle or myofiber tests, each have limitations. The wire-hanging test, though repeatable, does not explicitly isolate hindlimbs, while in vivo contractility testing requires deep anesthesia, potentially compromising accuracy. Isolated muscle tests offer precise measurements but necessitate animal sacrifice, preventing longitudinal measurements. This study introduces an optimized method for assessing hindlimb grip strength that improves consistency and accessibility.
•
It can be applied to measure both hindlimbs simultaneously, allowing for repeatable pre- and post-treatment comparisons.
•
It enables single-hindlimb evaluation, supporting self-comparisons.
•
This method is sensitive, user-friendly, and suitable for researchers of all expertise levels. It offers a robust tool for future research on neuromuscular interventions.
{"title":"Quantitative evaluation of hindlimb grip strength in mice as a measure of neuromuscular function","authors":"Yaochao Zheng, Alexander Lunn, Jinghui Gao, Hongyu Chen, Yao Yao","doi":"10.1016/j.mex.2024.103118","DOIUrl":"10.1016/j.mex.2024.103118","url":null,"abstract":"<div><div>Muscle strength is a crucial metric for assessing motor function, with significant diagnostic and prognostic value. It is widely used in clinical and preclinical studies as a phenotypic indicator. In mouse models of neuromuscular disorders, grip strength provides a direct, repeatable measure of motor function changes throughout disease progression. Hindlimbs are critical evaluative targets in research due to their relevancy to rodent motor functions, but assessing their strength remains a challenge. Existing methods, such as the wire-hanging test, <em>in vivo</em> quadriceps contractility measurements, and isolated muscle or myofiber tests, each have limitations. The wire-hanging test, though repeatable, does not explicitly isolate hindlimbs, while <em>in vivo</em> contractility testing requires deep anesthesia, potentially compromising accuracy. Isolated muscle tests offer precise measurements but necessitate animal sacrifice, preventing longitudinal measurements. This study introduces an optimized method for assessing hindlimb grip strength that improves consistency and accessibility.<ul><li><span>•</span><span><div>It can be applied to measure both hindlimbs simultaneously, allowing for repeatable pre- and post-treatment comparisons.</div></span></li><li><span>•</span><span><div>It enables single-hindlimb evaluation, supporting self-comparisons.</div></span></li><li><span>•</span><span><div>This method is sensitive, user-friendly, and suitable for researchers of all expertise levels. It offers a robust tool for future research on neuromuscular interventions.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103118"},"PeriodicalIF":1.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008245","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}
Pub Date : 2024-12-22DOI: 10.1016/j.mex.2024.103122
Syed Ahmed Rizvi , Kaniz F Chowdhury , Chiara Borsetto , Emma R Travis , Mohammad Saif , Vikar Ahmed , Laura J Carter , Iqbal Ahmad , Alan McNally , Qazi Mohd Rizwanul Haq
Microbial pathogens have developed resistance mechanisms to almost every antibiotic available. There is a need to synthesize or screen new natural compounds to combat the development of drug-resistant pathogens. One of the commonly used methods to evaluate the antimicrobial activity of two or more antibiotics involves a checkerboard assay, which is cumbersome, time-consuming, and expensive. We have developed a quick, reliable, and cost-effective method to evaluate the antimicrobial effect of two or more antibiotics at fixed doses with different concentrations of a novel natural ingredient or test compound.
The technique involves the following steps:
•
Preparation of a bacterial culture of the test strain at 0.5 McFarland standard (0.1 OD at 600 nm), and preparation of stock solutions for the chemical of interest and standard drugs.
•
The required amount of all three components can be dispensed into respective wells of a microplate using multichannel pipette.
•
Optical density (OD) values obtained would be directly related to the individual as well as combined effect of compounds on the given bacterial strain.
{"title":"A new method for concomitant evaluation of drug combinations for their antimicrobial properties","authors":"Syed Ahmed Rizvi , Kaniz F Chowdhury , Chiara Borsetto , Emma R Travis , Mohammad Saif , Vikar Ahmed , Laura J Carter , Iqbal Ahmad , Alan McNally , Qazi Mohd Rizwanul Haq","doi":"10.1016/j.mex.2024.103122","DOIUrl":"10.1016/j.mex.2024.103122","url":null,"abstract":"<div><div>Microbial pathogens have developed resistance mechanisms to almost every antibiotic available. There is a need to synthesize or screen new natural compounds to combat the development of drug-resistant pathogens. One of the commonly used methods to evaluate the antimicrobial activity of two or more antibiotics involves a checkerboard assay, which is cumbersome, time-consuming, and expensive. We have developed a quick, reliable, and cost-effective method to evaluate the antimicrobial effect of two or more antibiotics at fixed doses with different concentrations of a novel natural ingredient or test compound.</div><div>The technique involves the following steps:<ul><li><span>•</span><span><div>Preparation of a bacterial culture of the test strain at 0.5 McFarland standard (0.1 OD at 600 nm), and preparation of stock solutions for the chemical of interest and standard drugs.</div></span></li><li><span>•</span><span><div>The required amount of all three components can be dispensed into respective wells of a microplate using multichannel pipette.</div></span></li><li><span>•</span><span><div>Optical density (OD) values obtained would be directly related to the individual as well as combined effect of compounds on the given bacterial strain.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103122"},"PeriodicalIF":1.6,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11741016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008190","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}
Pub Date : 2024-12-22DOI: 10.1016/j.mex.2024.103132
Davide Biagini
The most frequently used environmental assessment methods are often applied, through a product-based approach, to analyse a single productive process, but such methods neglect the interactions that characterise complex and integrated biological systems (CIS), and often only consider the negative impacts. In order to overcome these gaps and since a material balance can highlight the relationships and interactions of a CIS, a systemic carbon (C) balance is here proposed as a complementary analysis tool to highlight the relationships that exist between different productive processes carried out by the same production unit and to characterise its environmental role. The method was applied to a beef farm consortium to its validation. Conducting a mass balance involves considering the input and output material flows and their accumulation within a system. The systemic C balance applied to the consortium was found to result in the removal of 96,100 t C from the atmosphere over a period of one year, thereby leading to different conclusions from those obtained with other assessment methods. Based on these results, it appears that here presented method can describe a CIS and to highlight the relationship that exists between rearing and agricultural activities in order to characterise their environmental roles.
•
A new approach to CIS evaluation is presented.
•
C fluxes were used to evaluate the relationships among integrated productive processes.
•
A mass balance can be used to evaluate resource depletion or the enrichment of a system.
{"title":"A systemic C balance as a tool to evaluate the environmental role of complex and integrated productive systems","authors":"Davide Biagini","doi":"10.1016/j.mex.2024.103132","DOIUrl":"10.1016/j.mex.2024.103132","url":null,"abstract":"<div><div>The most frequently used environmental assessment methods are often applied, through a product-based approach, to analyse a single productive process, but such methods neglect the interactions that characterise complex and integrated biological systems (CIS), and often only consider the negative impacts. In order to overcome these gaps and since a material balance can highlight the relationships and interactions of a CIS, a systemic carbon (C) balance is here proposed as a complementary analysis tool to highlight the relationships that exist between different productive processes carried out by the same production unit and to characterise its environmental role. The method was applied to a beef farm consortium to its validation. Conducting a mass balance involves considering the input and output material flows and their accumulation within a system. The systemic C balance applied to the consortium was found to result in the removal of 96,100 t C from the atmosphere over a period of one year, thereby leading to different conclusions from those obtained with other assessment methods. Based on these results, it appears that here presented method can describe a CIS and to highlight the relationship that exists between rearing and agricultural activities in order to characterise their environmental roles.<ul><li><span>•</span><span><div>A new approach to CIS evaluation is presented.</div></span></li><li><span>•</span><span><div>C fluxes were used to evaluate the relationships among integrated productive processes.</div></span></li><li><span>•</span><span><div>A mass balance can be used to evaluate resource depletion or the enrichment of a system.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103132"},"PeriodicalIF":1.6,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11741046/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008194","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}
Pub Date : 2024-12-21DOI: 10.1016/j.mex.2024.103124
Jarrett Fowler , Andrew B. Robbins , Cathryn Gunawan , Andrew Jastram , Michael Moreno
Physical anatomical models constructed from medical images are valuable research tools for evaluating patient-specific clinical circumstances. For example, 3D models replicating a patient's internal anatomy in the cardiovascular system can be used to validate Computational Fluid Dynamics (CFD) models, which can then be used to identify potential hemodynamic consequences of surgical decisions by providing insight into how blood and vascular tissue mechanics may contribute to disease progression and post-operative complications. Patient-specific models have been described in the literature; however, rapid prototyping models that achieve anatomical accuracy, optical transparency, and thin-walled compliance in a cost and time-effective approach have proven challenging. This limits their utility for modeling flows in vessels, e.g., the aorta, where compliance is particularly important. The work described herein is focused on a unique design and fabrication process implemented to produce physical patient-specific models that replicate the original anatomy dimensions and compliance with optical properties consistent with clinical imaging techniques. The patient-specific models are produced for under $150 of easily accessible consumable raw materials within 30 h using a relatively basic approach.
•
This method can be tuned for anatomies with different shapes and compliance.
•
This method can produce models to investigate medical device performance in vitro.
{"title":"Rapid Manufacturing Method of Cardiovascular Models for Experimental Flow Analysis","authors":"Jarrett Fowler , Andrew B. Robbins , Cathryn Gunawan , Andrew Jastram , Michael Moreno","doi":"10.1016/j.mex.2024.103124","DOIUrl":"10.1016/j.mex.2024.103124","url":null,"abstract":"<div><div>Physical anatomical models constructed from medical images are valuable research tools for evaluating patient-specific clinical circumstances. For example, 3D models replicating a patient's internal anatomy in the cardiovascular system can be used to validate Computational Fluid Dynamics (CFD) models, which can then be used to identify potential hemodynamic consequences of surgical decisions by providing insight into how blood and vascular tissue mechanics may contribute to disease progression and post-operative complications. Patient-specific models have been described in the literature; however, rapid prototyping models that achieve anatomical accuracy, optical transparency, and thin-walled compliance in a cost and time-effective approach have proven challenging. This limits their utility for modeling flows in vessels, <em>e.</em>g<em>.</em>, the aorta, where compliance is particularly important. The work described herein is focused on a unique design and fabrication process implemented to produce physical patient-specific models that replicate the original anatomy dimensions and compliance with optical properties consistent with clinical imaging techniques. The patient-specific models are produced for under $150 of easily accessible consumable raw materials within 30 h using a relatively basic approach.<ul><li><span>•</span><span><div>This method can be tuned for anatomies with different shapes and compliance.</div></span></li><li><span>•</span><span><div>This method can produce models to investigate medical device performance <em>in vitro</em>.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103124"},"PeriodicalIF":1.6,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743567/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008246","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}
Pub Date : 2024-12-21DOI: 10.1016/j.mex.2024.103130
Irtaza Ijaz , Abdallah Namoun , Nasser Aljohani , Meshari Huwaytim Alanazi , Mohammad N. Alanazi , Junaid Shuja , Mohammad Ali Humayun
Optical character recognition (OCR) is vital in digitizing printed data into a digital format, which can be conveniently used for various purposes. A significant amount of work has been done in OCR for well-resourced languages like English. However, languages like Urdu, spoken by a large community, face limitations in OCR due to a lack of resources and the complexity and diversity of handwritten scripts. One of the major hindrances in the development of OCR for low-resource languages like Urdu is the lack of extensive datasets. However, such datasets can be obtained from old handwritten books with reference text available online. This study presents a method to leverage this resource and automatically process Urdu handwritten poetry books with corresponding scripts available online. The images are segmented at the sentence level using automated neighborhood-connected component analysis, followed by manual adjustment. Corresponding Unicode text for each image are obtained by web scraping followed by text similarity analysis. A sample dataset collected comprises purely handwritten Urdu text images for Urdu poetry by Mirza Ghalib and Allama Iqbal, arguably the two most influential poets in Urdu. The dataset comprises 2888 images with Unicode transcriptions from poetry by Mirza Ghalib and Allama Iqbal.
•
The method automates OCR dataset creation by segmenting handwritten text images and scraping corresponding text from the web for alignment.
•
Handwritten images are segmented into sentences using a resource-efficient Neighborhood Component Analysis approach.
•
Possible text samples are scraped from the web, and the corresponding labels are aligned with images based on the minimum edit distance between the scraped text and the predictions by an OCR engine.
{"title":"Automated compilation of Urdu poetry handwritten image datasets for optical character recognition","authors":"Irtaza Ijaz , Abdallah Namoun , Nasser Aljohani , Meshari Huwaytim Alanazi , Mohammad N. Alanazi , Junaid Shuja , Mohammad Ali Humayun","doi":"10.1016/j.mex.2024.103130","DOIUrl":"10.1016/j.mex.2024.103130","url":null,"abstract":"<div><div>Optical character recognition (OCR) is vital in digitizing printed data into a digital format, which can be conveniently used for various purposes. A significant amount of work has been done in OCR for well-resourced languages like English. However, languages like Urdu, spoken by a large community, face limitations in OCR due to a lack of resources and the complexity and diversity of handwritten scripts. One of the major hindrances in the development of OCR for low-resource languages like Urdu is the lack of extensive datasets. However, such datasets can be obtained from old handwritten books with reference text available online. This study presents a method to leverage this resource and automatically process Urdu handwritten poetry books with corresponding scripts available online. The images are segmented at the sentence level using automated neighborhood-connected component analysis, followed by manual adjustment. Corresponding Unicode text for each image are obtained by web scraping followed by text similarity analysis. A sample dataset collected comprises purely handwritten Urdu text images for Urdu poetry by Mirza Ghalib and Allama Iqbal, arguably the two most influential poets in Urdu. The dataset comprises 2888 images with Unicode transcriptions from poetry by Mirza Ghalib and Allama Iqbal.<ul><li><span>•</span><span><div>The method automates OCR dataset creation by segmenting handwritten text images and scraping corresponding text from the web for alignment.</div></span></li><li><span>•</span><span><div>Handwritten images are segmented into sentences using a resource-efficient Neighborhood Component Analysis approach.</div></span></li><li><span>•</span><span><div>Possible text samples are scraped from the web, and the corresponding labels are aligned with images based on the minimum edit distance between the scraped text and the predictions by an OCR engine.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103130"},"PeriodicalIF":1.6,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743332/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008157","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}
Recent advancements in artificial intelligence (AI) have increased interest in intelligent transportation systems, particularly autonomous vehicles. Safe navigation in traffic-heavy environments requires accurate road scene segmentation, yet traditional computer vision methods struggle with complex scenarios. This study emphasizes the role of deep learning in improving semantic segmentation using datasets like the Indian Driving Dataset (IDD), which presents unique challenges in chaotic road conditions. We propose a modified CANet that incorporates U-Net and LinkNet elements, focusing on accuracy, efficiency, and resilience. The CANet features an encoder-decoder architecture and a Multiscale Context Module (MCM) with three parallel branches to capture contextual information at multiple scales. Our experiments show that the proposed model achieves a mean Intersection over Union (mIoU) value of 0.7053, surpassing state-of-the-art models in efficiency and performance.
Here we demonstrate:
•
Traditional computer vision methods struggle with complex driving scenarios, but deep learning based semantic segmentation methods show promising results.
•
Modified CANet, incorporating U-Net and LinkNet elements is proposed for semantic segmentation of unstructured driving scenarios.
•
The CANet structure consists of an encoder-decoder architecture and a Multiscale Context Module (MCM) with three parallel branches to capture contextual information at multiple scales.
{"title":"Enhancing semantic segmentation for autonomous vehicle scene understanding in indian context using modified CANet model","authors":"Smita Khairnar , Sudeep D. Thepade , Suresh Kolekar , Shilpa Gite , Biswajeet Pradhan , Abdullah Alamri , Bhagyesha Patil , Shrutee Dahake , Radhika Gaikwad , Atharva Chaudhari","doi":"10.1016/j.mex.2024.103131","DOIUrl":"10.1016/j.mex.2024.103131","url":null,"abstract":"<div><div>Recent advancements in artificial intelligence (AI) have increased interest in intelligent transportation systems, particularly autonomous vehicles. Safe navigation in traffic-heavy environments requires accurate road scene segmentation, yet traditional computer vision methods struggle with complex scenarios. This study emphasizes the role of deep learning in improving semantic segmentation using datasets like the Indian Driving Dataset (IDD), which presents unique challenges in chaotic road conditions. We propose a modified CANet that incorporates U-Net and LinkNet elements, focusing on accuracy, efficiency, and resilience. The CANet features an encoder-decoder architecture and a Multiscale Context Module (MCM) with three parallel branches to capture contextual information at multiple scales. Our experiments show that the proposed model achieves a mean Intersection over Union (mIoU) value of 0.7053, surpassing state-of-the-art models in efficiency and performance.</div><div>Here we demonstrate:<ul><li><span>•</span><span><div>Traditional computer vision methods struggle with complex driving scenarios, but deep learning based semantic segmentation methods show promising results.</div></span></li><li><span>•</span><span><div>Modified CANet, incorporating U-Net and LinkNet elements is proposed for semantic segmentation of unstructured driving scenarios.</div></span></li><li><span>•</span><span><div>The CANet structure consists of an encoder-decoder architecture and a Multiscale Context Module (MCM) with three parallel branches to capture contextual information at multiple scales.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103131"},"PeriodicalIF":1.6,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11751566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143024087","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}
Lithology classification is crucial for efficient and sustainable resource exploration in the oil and gas industry. Missing values in well-log data, such as Gamma Ray (GR), Neutron Porosity (NPHI), Bulk Density (RHOB), Deep Resistivity (RS), Delta Time Compressional (DTCO), Delta Time Shear (DTSM), and Resistivity Deep (RD), significantly affect machine learning classification accuracy. This study applied three algorithms, extreme gradient boosting (XGBoost), K-nearest neighbours (KNN), and the artificial neural network (ANN), to handle missing values in well-log datasets, particularly datasets with extreme missing data (30 %). Results indicated that XGBoost was the most efficient and accurate, especially for RHOB, NPHI, DTCO, and DTSM, with the lowest Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The ANN also performed effectively, particularly on the GR, RS, and RD features, after the use of preprocessing techniques such as isolation forest and bias correction. However, the ANN can suffer from overfitting and requires large datasets for optimal performance. In contrast, KNN struggled with missing-not-at-random (MNAR) data due to its reliance on the k parameter and distance metric, making it less effective in mapping missing data relationships.
•
Missing values in well-log data can hinder lithology classification accuracy for efficient resource exploration in the oil and gas industry.
•
This research aims to address the problem of missing values in well-log datasets by applying machine learning algorithms such as XGBoost, ANN, and KNN to enhance classification performance.
•
XGBoost demonstrated superior performance in handling extreme missing data (30 %) in well-log datasets. ANN was effective but prone to overfitting for small datasets, while KNN struggled with missing-not-at-random (MNAR) data due to limitations in its distance-based approach.
{"title":"Filling-well: An effective technique to handle incomplete well-log data for lithology classification using machine learning algorithms","authors":"Sherly Ardhya Garini , Ary Mazharuddin Shiddiqi , Widya Utama , Alif Nurdien Fitrah Insani","doi":"10.1016/j.mex.2024.103127","DOIUrl":"10.1016/j.mex.2024.103127","url":null,"abstract":"<div><div>Lithology classification is crucial for efficient and sustainable resource exploration in the oil and gas industry. Missing values in well-log data, such as Gamma Ray (GR), Neutron Porosity (NPHI), Bulk Density (RHOB), Deep Resistivity (RS), Delta Time Compressional (DTCO), Delta Time Shear (DTSM), and Resistivity Deep (RD), significantly affect machine learning classification accuracy. This study applied three algorithms, extreme gradient boosting (XGBoost), K-nearest neighbours (KNN), and the artificial neural network (ANN), to handle missing values in well-log datasets, particularly datasets with extreme missing data (30 %). Results indicated that XGBoost was the most efficient and accurate, especially for RHOB, NPHI, DTCO, and DTSM, with the lowest Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The ANN also performed effectively, particularly on the GR, RS, and RD features, after the use of preprocessing techniques such as isolation forest and bias correction. However, the ANN can suffer from overfitting and requires large datasets for optimal performance. In contrast, KNN struggled with missing-not-at-random (MNAR) data due to its reliance on the k parameter and distance metric, making it less effective in mapping missing data relationships.<ul><li><span>•</span><span><div>Missing values in well-log data can hinder lithology classification accuracy for efficient resource exploration in the oil and gas industry.</div></span></li><li><span>•</span><span><div>This research aims to address the problem of missing values in well-log datasets by applying machine learning algorithms such as XGBoost, ANN, and KNN to enhance classification performance.</div></span></li><li><span>•</span><span><div>XGBoost demonstrated superior performance in handling extreme missing data (30 %) in well-log datasets. ANN was effective but prone to overfitting for small datasets, while KNN struggled with missing-not-at-random (MNAR) data due to limitations in its distance-based approach.</div></span></li></ul></div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103127"},"PeriodicalIF":1.6,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008211","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}
Pub Date : 2024-12-21DOI: 10.1016/j.mex.2024.103125
Le Thi Tuyet Trinh , Nguyen Thi Thu Hang , Le Minh Cuong , Ngo Van Dinh , Hoang Khanh Linh , Do Thi Trinh , Nguyen Thuy Phuong Tram , Ho Nguyen , Manh-Tung Ho
The open science movement aims to democratize essential scientific values, including rigor, transparency, availability, and replicability. However, open science resources are still often underutilized. A comprehensive evaluation of the factors influencing the use of these resources is urgently needed. This evaluation not only supports evidence-based policymaking to help researchers thrive in a highly competitive academic environment but also prevents misunderstandings and confusions related to emerging scientific practices. This article presents a survey-based framework for understanding the factors that affect the ability to utilize open science resources. To achieve this, we will integrate relevant factors such as capabilities, attitudes, perceived costs and benefits, cultural and institutional influences, and alignment of values into our analytical framework. These factors are derived from significant theories that have been applied to study the acceptance and use of information systems: the Theory of Planned Behavior, Self-Determination Theory, the Unified Theory of Technology Use and Acceptance, Self-Efficacy Theory, and the value-filtering model known as Mindsponge Theory.We will briefly introduce the key elements of these frameworks and discuss their applications in the context of utilizing open science resources as well as in the broader context of innovation adoption. Furthermore, we argue that elements from these models significantly overlap and complement one another. Therefore, to thoroughly evaluate the factors affecting the utilization of open science resources, it is essential to coherently combine aspects from these models into a unified analytical framework.
{"title":"State-of-the-arts methods for studying factors driving the utilization of open science resources","authors":"Le Thi Tuyet Trinh , Nguyen Thi Thu Hang , Le Minh Cuong , Ngo Van Dinh , Hoang Khanh Linh , Do Thi Trinh , Nguyen Thuy Phuong Tram , Ho Nguyen , Manh-Tung Ho","doi":"10.1016/j.mex.2024.103125","DOIUrl":"10.1016/j.mex.2024.103125","url":null,"abstract":"<div><div>The open science movement aims to democratize essential scientific values, including <em>rigor, transparency, availability, and replicability</em>. However, open science resources are still often underutilized. A comprehensive evaluation of the factors influencing the use of these resources is urgently needed. This evaluation not only supports evidence-based policymaking to help researchers thrive in a highly competitive academic environment but also prevents misunderstandings and confusions related to emerging scientific practices. This article presents a survey-based framework for understanding the factors that affect the ability to utilize open science resources. To achieve this, we will integrate relevant factors such as capabilities, attitudes, perceived costs and benefits, cultural and institutional influences, and alignment of values into our analytical framework. These factors are derived from significant theories that have been applied to study the acceptance and use of information systems: the Theory of Planned Behavior, Self-Determination Theory, the Unified Theory of Technology Use and Acceptance, Self-Efficacy Theory, and the value-filtering model known as Mindsponge Theory.We will briefly introduce the key elements of these frameworks and discuss their applications in the context of utilizing open science resources as well as in the broader context of innovation adoption. Furthermore, we argue that elements from these models significantly overlap and complement one another. Therefore, to thoroughly evaluate the factors affecting the utilization of open science resources, it is essential to coherently combine aspects from these models into a unified analytical framework.</div></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"14 ","pages":"Article 103125"},"PeriodicalIF":1.6,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096624","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}
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