Pub Date : 2022-12-01DOI: 10.1088/2633-1357/acadb9
J. Grant-Jacob, M. Zervas, B. Mills
The structure of pollen has evolved depending on its local environment, competition, and ecology. As pollen grains are generally of size 10–100 microns with nanometre-scale substructure, scanning electron microscopy is an important microscopy technique for imaging and analysis. Here, we use style transfer deep learning to allow exploration of latent w-space of scanning electron microscope images of pollen grains and show the potential for using this technique to understand evolutionary pathways and characteristic structural traits of pollen grains.
{"title":"Morphology exploration of pollen using deep learning latent space","authors":"J. Grant-Jacob, M. Zervas, B. Mills","doi":"10.1088/2633-1357/acadb9","DOIUrl":"https://doi.org/10.1088/2633-1357/acadb9","url":null,"abstract":"The structure of pollen has evolved depending on its local environment, competition, and ecology. As pollen grains are generally of size 10–100 microns with nanometre-scale substructure, scanning electron microscopy is an important microscopy technique for imaging and analysis. Here, we use style transfer deep learning to allow exploration of latent w-space of scanning electron microscope images of pollen grains and show the potential for using this technique to understand evolutionary pathways and characteristic structural traits of pollen grains.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42197829","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}
Pub Date : 2022-11-21DOI: 10.1088/2633-1357/aca4ad
Marwan Al-Raeei
The Monkey-pox virus disease (MPXD) is a type of the pox disease similar to the smallpox disease. This disease produces rashes with lesions on the skin. The MPXD is an endemic in some countries of Africa, however, a recent outbreak of this disease started to appear in some countries, such as the United Kingdom, Spain, Greece, Portugal, Australia, Brazil, and the United States. Lots of indicators are employed for forecasting the 2022 outbreak of the MPXD such as the infection period, the recovery period, the force of infection, the incubation period of the disease…..etc. The aim of this study is finding the infection period, and the recovery period of the 2022 outbreak of the monkey-pox virus disease in two countries: the United States, and Spain. We apply the simulation and analytical methods on a simple epidemic model, which is the SIRD infectious disease model, for finding the previous periods. We found that the infection period of the recent outbreak of the MPXD varies from 10 days to 20 days, while we found that the recovery periods of the recent outbreak of the MPXD varies from 15 days to 30 days. Besides, we found that the average value of the infection period of the 2022 outbreak of the MPXD is about two weeks, and the average value of the recovery period of the 2022 outbreak of the MPXD is about three weeks. The analytical solution with the simulation algorithm which we used in this study can be expanded for other forecasting parameters of the MPXD, and also for multiple countries.
{"title":"The infection and recovery periods of the 2022 outbreak of monkey-pox virus disease","authors":"Marwan Al-Raeei","doi":"10.1088/2633-1357/aca4ad","DOIUrl":"https://doi.org/10.1088/2633-1357/aca4ad","url":null,"abstract":"The Monkey-pox virus disease (MPXD) is a type of the pox disease similar to the smallpox disease. This disease produces rashes with lesions on the skin. The MPXD is an endemic in some countries of Africa, however, a recent outbreak of this disease started to appear in some countries, such as the United Kingdom, Spain, Greece, Portugal, Australia, Brazil, and the United States. Lots of indicators are employed for forecasting the 2022 outbreak of the MPXD such as the infection period, the recovery period, the force of infection, the incubation period of the disease…..etc. The aim of this study is finding the infection period, and the recovery period of the 2022 outbreak of the monkey-pox virus disease in two countries: the United States, and Spain. We apply the simulation and analytical methods on a simple epidemic model, which is the SIRD infectious disease model, for finding the previous periods. We found that the infection period of the recent outbreak of the MPXD varies from 10 days to 20 days, while we found that the recovery periods of the recent outbreak of the MPXD varies from 15 days to 30 days. Besides, we found that the average value of the infection period of the 2022 outbreak of the MPXD is about two weeks, and the average value of the recovery period of the 2022 outbreak of the MPXD is about three weeks. The analytical solution with the simulation algorithm which we used in this study can be expanded for other forecasting parameters of the MPXD, and also for multiple countries.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45012141","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}
Pub Date : 2022-11-07DOI: 10.1088/2633-1357/aca0d2
Matthew Nelson, S. Laflamme, Chao Hu, A. Moura, Jonathan Hong, Austin Downey, P. Lander, Yang Wang, Erik Blasch, J. Dodson
High-rate dynamics occur when a system’s acceleration is larger than 100 gn over durations less than 100 ms. Structural health monitoring algorithms must be created for high-rate dynamic systems to maximize safety and minimize economic losses. There is a need to evaluate these algorithms for precision and accuracy prior to real-world implementation. An experimental testbed was created to simulate large-magnitude events while maintaining repeatability to accurately and robustly assess various structural health monitoring algorithms’ capability to monitor high-rate dynamic systems. All previous datasets created on the experimental testbed are discussed, examining various sensor setups, excitations, and boundary condition changes to properly simulate near-high-rate events and provide robust experimental data to evaluate structural health monitoring algorithms.
{"title":"Generated datasets from dynamic reproduction of projectiles in ballistic environments for advanced research (DROPBEAR) testbed","authors":"Matthew Nelson, S. Laflamme, Chao Hu, A. Moura, Jonathan Hong, Austin Downey, P. Lander, Yang Wang, Erik Blasch, J. Dodson","doi":"10.1088/2633-1357/aca0d2","DOIUrl":"https://doi.org/10.1088/2633-1357/aca0d2","url":null,"abstract":"High-rate dynamics occur when a system’s acceleration is larger than 100 gn over durations less than 100 ms. Structural health monitoring algorithms must be created for high-rate dynamic systems to maximize safety and minimize economic losses. There is a need to evaluate these algorithms for precision and accuracy prior to real-world implementation. An experimental testbed was created to simulate large-magnitude events while maintaining repeatability to accurately and robustly assess various structural health monitoring algorithms’ capability to monitor high-rate dynamic systems. All previous datasets created on the experimental testbed are discussed, examining various sensor setups, excitations, and boundary condition changes to properly simulate near-high-rate events and provide robust experimental data to evaluate structural health monitoring algorithms.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46773922","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}
Pub Date : 2022-10-07DOI: 10.1088/2633-1357/ac986e
Nirupama Saini, P. Bhadury
Oceanimonas sp. NSJ1 was isolated from macroplastic debris collected previously from Junput, an intertidal beach, facing the northeast coastal Bay of Bengal of the Northern Indian Ocean. The genome of this isolate is closely related to Oceanimonas doudoroffii with a genome size of 3.56 Mbp. The genome annotation confirmed the presence of 5919 total genes, out of which 5809 were CDSs (coding sequences) and all are protein-coding. The genome codes for 110 RNA with 25 rRNA, 84 tRNA (transfer RNA), and one tmRNA (transfer-messenger RNA). Analyses of the annotated genome of Oceanimonas sp. NSJ1 revealed the presence of enzymes involved in the degradation of polycyclic aromatic hydrocarbons. The presence of phthalate 4,5-dioxygenase oxygenase reductase subunit pht2 within the genome also highlights the novelty of this isolate and future functional potential for studying phthalate degradation in marine environment.
{"title":"Genome analysis of a plastisphere-associated Oceanimonas sp. NSJ1 sequenced on Nanopore MinION platform","authors":"Nirupama Saini, P. Bhadury","doi":"10.1088/2633-1357/ac986e","DOIUrl":"https://doi.org/10.1088/2633-1357/ac986e","url":null,"abstract":"Oceanimonas sp. NSJ1 was isolated from macroplastic debris collected previously from Junput, an intertidal beach, facing the northeast coastal Bay of Bengal of the Northern Indian Ocean. The genome of this isolate is closely related to Oceanimonas doudoroffii with a genome size of 3.56 Mbp. The genome annotation confirmed the presence of 5919 total genes, out of which 5809 were CDSs (coding sequences) and all are protein-coding. The genome codes for 110 RNA with 25 rRNA, 84 tRNA (transfer RNA), and one tmRNA (transfer-messenger RNA). Analyses of the annotated genome of Oceanimonas sp. NSJ1 revealed the presence of enzymes involved in the degradation of polycyclic aromatic hydrocarbons. The presence of phthalate 4,5-dioxygenase oxygenase reductase subunit pht2 within the genome also highlights the novelty of this isolate and future functional potential for studying phthalate degradation in marine environment.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48401884","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}
Pub Date : 2022-09-01Epub Date: 2022-10-07DOI: 10.1088/2633-1357/ac95e2
James Ingham, Caroline I Smith, Barnaby G Ellis, Conor A Whitley, Asterios Triantafyllou, Philip J Gunning, Steve D Barrett, Peter Gardener, Richard J Shaw, Janet M Risk, Peter Weightman
A machine learning algorithm (MLA) has been applied to a Fourier transform infrared spectroscopy (FTIR) dataset previously analysed with a principal component analysis (PCA) linear discriminant analysis (LDA) model. This comparison has confirmed the robustness of FTIR as a prognostic tool for oral epithelial dysplasia (OED). The MLA is able to predict malignancy with a sensitivity of 84 ± 3% and a specificity of 79 ± 3%. It provides key wavenumbers that will be important for the development of devices that can be used for improved prognosis of OED.
一种机器学习算法（MLA）被应用于傅立叶变换红外光谱（FTIR）数据集，该数据集之前曾用主成分分析（PCA）线性判别分析（LDA）模型进行过分析。这一比较证实了傅立叶变换红外光谱作为口腔上皮发育不良（OED）预后工具的稳健性。MLA 预测恶性肿瘤的灵敏度为 84 ± 3%，特异度为 79 ± 3%。它提供的关键波数对于开发可用于改善 OED 预后的设备非常重要。
{"title":"Prediction of malignant transformation in oral epithelial dysplasia using machine learning.","authors":"James Ingham, Caroline I Smith, Barnaby G Ellis, Conor A Whitley, Asterios Triantafyllou, Philip J Gunning, Steve D Barrett, Peter Gardener, Richard J Shaw, Janet M Risk, Peter Weightman","doi":"10.1088/2633-1357/ac95e2","DOIUrl":"10.1088/2633-1357/ac95e2","url":null,"abstract":"<p><p>A machine learning algorithm (MLA) has been applied to a Fourier transform infrared spectroscopy (FTIR) dataset previously analysed with a principal component analysis (PCA) linear discriminant analysis (LDA) model. This comparison has confirmed the robustness of FTIR as a prognostic tool for oral epithelial dysplasia (OED). The MLA is able to predict malignancy with a sensitivity of 84 ± 3% and a specificity of 79 ± 3%. It provides key wavenumbers that will be important for the development of devices that can be used for improved prognosis of OED.</p>","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":"3 3","pages":"034001"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40665811","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 : 2022-06-17DOI: 10.1088/2633-1357/ac79e7
T. Altair, D. Galante, H. Varela
Iron (II) sulfide minerals have gained attention in the last decades due to their relevance in hypotheses for the emergence of life on the early Earth around 4 billion years ago. In the submarine vent theory, it has been proposed that those minerals, especially mackinawite, had a key role in prebiotic processes. Those are estimated to be present in a natural electrochemical setting, analogous to a chemiosmotic one, formed in the interface between the early ocean and the interior of the alkaline hydrothermal systems, the early vent-ocean interface. To evaluate this and other hypotheses, voltammetric studies were performed to better understand the electrochemical behavior of minerals under conditions analogous to the vent-ocean interface. The preliminary results presented here indicate that, in the potential range estimated to exist in that interface, mackinawite can transition to other mineral phases and may posibly coexist with other minerals, resulting from its oxidation. This can create a local chemical diversity. In addition, it has been tested a protocol for Ni incorporation in mackinawite structure, resulting in a surface that showed an interesting behavior in the presence of CO2, although definitive experiments showed necessary for a deeper comprehension of that behavior. Overall, the results are consistent with previous results on electrocatalytical properties of Fe-Ni-S materials for CO2 reduction, and also could lead to the emergence of a protometabolism on early Earth.
{"title":"Voltammetric investigation on iron-(nickel-)sulfur surface under conditions for the emergence of life","authors":"T. Altair, D. Galante, H. Varela","doi":"10.1088/2633-1357/ac79e7","DOIUrl":"https://doi.org/10.1088/2633-1357/ac79e7","url":null,"abstract":"Iron (II) sulfide minerals have gained attention in the last decades due to their relevance in hypotheses for the emergence of life on the early Earth around 4 billion years ago. In the submarine vent theory, it has been proposed that those minerals, especially mackinawite, had a key role in prebiotic processes. Those are estimated to be present in a natural electrochemical setting, analogous to a chemiosmotic one, formed in the interface between the early ocean and the interior of the alkaline hydrothermal systems, the early vent-ocean interface. To evaluate this and other hypotheses, voltammetric studies were performed to better understand the electrochemical behavior of minerals under conditions analogous to the vent-ocean interface. The preliminary results presented here indicate that, in the potential range estimated to exist in that interface, mackinawite can transition to other mineral phases and may posibly coexist with other minerals, resulting from its oxidation. This can create a local chemical diversity. In addition, it has been tested a protocol for Ni incorporation in mackinawite structure, resulting in a surface that showed an interesting behavior in the presence of CO2, although definitive experiments showed necessary for a deeper comprehension of that behavior. Overall, the results are consistent with previous results on electrocatalytical properties of Fe-Ni-S materials for CO2 reduction, and also could lead to the emergence of a protometabolism on early Earth.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47079044","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}
Pub Date : 2022-06-14DOI: 10.1088/2633-1357/ac78ac
Arkajit Aich
Bakreswar-Tantloi region of India, besides being a geothermally active region, also harbours a high amount of Radon in soil-gas and groundwater of the region. Measurement of Radon-content across the region is an active area of research aimed to properly understand the geothermal potential of the region, the study of local geology and to determine the risks of Radon exposure in the area. In an aim to evaluate the Radon potential of this important geothermal hub, we have done a pilot study on the region by doing spot measurements of Soil-Radon activity in 41 specific geographic locations spread out across the region of interest which will act as groundwork for further in-depth analysis. The measurements showed that Radon activity varies widely in the region with the Radon activity ranging from 1 kBqm−3 to 52 kBqm−3 across the measured locations. Mean Radon activity across the measured locations was found to be 16 kBqm−3 with standard deviation of the sample set of 14 kBqm−3. Seven locations recorded Radon activity to be greater than standard deviation from average while four locations recorded Radon activity greater than twice the standard deviation from average.
{"title":"Preliminary studies on soil radon activity at geothermal hotspot of Bakreswar-Tantloi","authors":"Arkajit Aich","doi":"10.1088/2633-1357/ac78ac","DOIUrl":"https://doi.org/10.1088/2633-1357/ac78ac","url":null,"abstract":"Bakreswar-Tantloi region of India, besides being a geothermally active region, also harbours a high amount of Radon in soil-gas and groundwater of the region. Measurement of Radon-content across the region is an active area of research aimed to properly understand the geothermal potential of the region, the study of local geology and to determine the risks of Radon exposure in the area. In an aim to evaluate the Radon potential of this important geothermal hub, we have done a pilot study on the region by doing spot measurements of Soil-Radon activity in 41 specific geographic locations spread out across the region of interest which will act as groundwork for further in-depth analysis. The measurements showed that Radon activity varies widely in the region with the Radon activity ranging from 1 kBqm−3 to 52 kBqm−3 across the measured locations. Mean Radon activity across the measured locations was found to be 16 kBqm−3 with standard deviation of the sample set of 14 kBqm−3. Seven locations recorded Radon activity to be greater than standard deviation from average while four locations recorded Radon activity greater than twice the standard deviation from average.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48756008","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}
Pub Date : 2022-05-05DOI: 10.1088/2633-1357/ac6d2e
Gauraw Kumar, P. Bhadury
Fixation and transportation of human fecal samples is often difficult in geographically remote locations due to unavailability of options for immediate freezing. In this study effectiveness of five different chemical fixatives were evaluated on human fecal samples including for supernatant using RNAprotect® Bacteria Reagent (Qiagen), 95% ethanol, acetone, TRIzol® and a mixture of all these fixatives, in addition to immediate freezing. DNA was extracted from the fecal samples using QIAamp® Fast DNA Stool Mini Kit as well as quality and yield of extracted DNA was monitored for a period of 30 days. It was found that except TRIzol®, all other preservatives showed good DNA quality and yield for a period of one month based on agarose gel electrophoresis, Nanodrop and Qubit fluorometric measurements. It was also found that supernatant of fecal sample fixed with RNAprotect Bacteria Reagent gave reliable DNA yield in comparison to other various fixatives. The study also revealed that quality and yield of DNA from fecal samples fixed in acetone were very promising since it is a cost-effective fixative. Overall, the study shows future applicability for downstream DNA analyses of the RNAprotect® Bacteria Reagent, 95% ethanol, acetone, and a mixture of all these fixatives for fixing human fecal samples to be collected from geographically remote locations or in regions where available resources are largely limited.
在地理位置偏远的地方，由于无法选择立即冷冻，人类粪便样本的固定和运输通常很困难。在这项研究中，除了立即冷冻外，还评估了五种不同化学固定剂对人类粪便样本的有效性，包括使用RNAprotect®细菌试剂（Qiagen）、95%乙醇、丙酮、TRIzol®和所有这些固定剂的混合物的上清液。使用QIAamp®Fast DNA Stool Mini试剂盒从粪便样本中提取DNA，并监测提取DNA的质量和产量30天。根据琼脂糖凝胶电泳、Nanodrop和Qubit荧光测量，发现除TRIzol®外，所有其他防腐剂在一个月内都显示出良好的DNA质量和产量。还发现，与其他各种固定剂相比，用RNAprotect细菌试剂固定的粪便样品的上清液提供了可靠的DNA产量。该研究还表明，固定在丙酮中的粪便样本的DNA的质量和产量非常有希望，因为它是一种具有成本效益的固定剂。总的来说，这项研究表明，RNAprotect®细菌试剂、95%乙醇、丙酮和所有这些固定剂的混合物未来适用于下游DNA分析，用于固定从地理偏远地区或可用资源有限的地区收集的人类粪便样本。
{"title":"Effect of different fixatives on yield of DNA from human fecal samples","authors":"Gauraw Kumar, P. Bhadury","doi":"10.1088/2633-1357/ac6d2e","DOIUrl":"https://doi.org/10.1088/2633-1357/ac6d2e","url":null,"abstract":"Fixation and transportation of human fecal samples is often difficult in geographically remote locations due to unavailability of options for immediate freezing. In this study effectiveness of five different chemical fixatives were evaluated on human fecal samples including for supernatant using RNAprotect® Bacteria Reagent (Qiagen), 95% ethanol, acetone, TRIzol® and a mixture of all these fixatives, in addition to immediate freezing. DNA was extracted from the fecal samples using QIAamp® Fast DNA Stool Mini Kit as well as quality and yield of extracted DNA was monitored for a period of 30 days. It was found that except TRIzol®, all other preservatives showed good DNA quality and yield for a period of one month based on agarose gel electrophoresis, Nanodrop and Qubit fluorometric measurements. It was also found that supernatant of fecal sample fixed with RNAprotect Bacteria Reagent gave reliable DNA yield in comparison to other various fixatives. The study also revealed that quality and yield of DNA from fecal samples fixed in acetone were very promising since it is a cost-effective fixative. Overall, the study shows future applicability for downstream DNA analyses of the RNAprotect® Bacteria Reagent, 95% ethanol, acetone, and a mixture of all these fixatives for fixing human fecal samples to be collected from geographically remote locations or in regions where available resources are largely limited.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43844001","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}
Pub Date : 2022-04-14DOI: 10.1088/2633-1357/ac6780
J. Grant-Jacob, M. Praeger, R. Eason, B. Mills
Pollen grains dehydrate during their development and following their departure from the host stigma. Since the size and shape of a pollen grain can be dependent on environmental conditions, being able to predict both of these factors for hydrated pollen grains from their dehydrated state could be beneficial in the fields of climate science, agriculture, and palynology. Here, we use deep learning to transform images of dehydrated Ranunculus pollen grains into images of hydrated Ranunculus pollen grains. We also then use a deep learning neural network that was trained on experimental images of different genera of pollen grains to identify the hydrated pollen grains from the generated transformed images, to test the accuracy of the image generation neural network. This pilot work demonstrates the first steps needed towards creating a general deep learning-based rehydration model that could be useful in understanding and predicting pollen morphology.
{"title":"Generating images of hydrated pollen grains using deep learning","authors":"J. Grant-Jacob, M. Praeger, R. Eason, B. Mills","doi":"10.1088/2633-1357/ac6780","DOIUrl":"https://doi.org/10.1088/2633-1357/ac6780","url":null,"abstract":"Pollen grains dehydrate during their development and following their departure from the host stigma. Since the size and shape of a pollen grain can be dependent on environmental conditions, being able to predict both of these factors for hydrated pollen grains from their dehydrated state could be beneficial in the fields of climate science, agriculture, and palynology. Here, we use deep learning to transform images of dehydrated Ranunculus pollen grains into images of hydrated Ranunculus pollen grains. We also then use a deep learning neural network that was trained on experimental images of different genera of pollen grains to identify the hydrated pollen grains from the generated transformed images, to test the accuracy of the image generation neural network. This pilot work demonstrates the first steps needed towards creating a general deep learning-based rehydration model that could be useful in understanding and predicting pollen morphology.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45678408","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}
Pub Date : 2022-02-24DOI: 10.1088/2633-1357/ac585e
M. V. Pithapuram, M. Raghavan
Studying spinal interactions with muscles has been of great importance for over a century. However, with surging spinal-related movement pathologies, the need for computational models to study spinal pathways is increasing. Although spinal cord connectome models have been developed, anatomically relevant spinal neuromotor models are rare. However, building and maintaining such models is time-consuming. In this study, the concept of the rule-based generation of a spinal connectome was introduced and lumbosacral connectome generation was demonstrated as an example. Furthermore, the rule-based autogenerated connectome models were synchronized with lower-limb musculoskeletal models to create an in-silico testbed. Using this setup, the role of the autogenic Ia-excitatory pathway in controlling the ankle angle was tested.
{"title":"Automatic rule-based generation of spinal cord connectome model for a neuro-musculoskeletal limb in-silico","authors":"M. V. Pithapuram, M. Raghavan","doi":"10.1088/2633-1357/ac585e","DOIUrl":"https://doi.org/10.1088/2633-1357/ac585e","url":null,"abstract":"Studying spinal interactions with muscles has been of great importance for over a century. However, with surging spinal-related movement pathologies, the need for computational models to study spinal pathways is increasing. Although spinal cord connectome models have been developed, anatomically relevant spinal neuromotor models are rare. However, building and maintaining such models is time-consuming. In this study, the concept of the rule-based generation of a spinal connectome was introduced and lumbosacral connectome generation was demonstrated as an example. Furthermore, the rule-based autogenerated connectome models were synchronized with lower-limb musculoskeletal models to create an in-silico testbed. Using this setup, the role of the autogenic Ia-excitatory pathway in controlling the ankle angle was tested.","PeriodicalId":93771,"journal":{"name":"IOP SciNotes","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42703077","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}
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