A regular calligraphy script of each calligrapher has unique strokes, and a script’s authenticity can be identified by comparing them. Hence, this study introduces a method for identifying the authenticity of regular script calligraphy works based on the improved YOLOv7 algorithm. The proposed method evaluates the authenticity of calligraphy works by detecting and comparing the number of single-character features in each regular script calligraphy work. Specifically, first, we collected regular script calligraphy works from a well-known domestic calligrapher and divided each work into a single-character dataset. Then, we introduced the PConv module in FasterNet, the DyHead dynamic detection header network, and the MPDiou bounding box loss function to optimize the accuracy of the YOLOv7 algorithm. Thus, we constructed an improved algorithm named YOLOv7-PDM, which is used for regular script calligraphy identification. The proposed YOLOv7-PDM model was trained and tested using a prepared regular script single-character dataset. Through experimental results, we confirmed the practicality and feasibility of the proposed method and demonstrated that the YOLOv7-PDM algorithm model achieves 94.19% accuracy (mAP50) in detecting regular script font features, with a single-image detection time of 3.1 m and 31.67M parameters. The improved YOLOv7 algorithm model offers greater advantages in detection speed, accuracy, and model complexity compared to current mainstream detection algorithms. This demonstrates that the developed approach effectively extracts stroke features of regular script calligraphy and provides guidance for future studies on authenticity identification.
{"title":"Authenticity identification method for calligraphy regular script based on improved YOLOv7 algorithm","authors":"Jinyuan Chen, Zucheng Huang, Xuyao Jiang, Hai Yuan, Weijun Wang, Jian Wang, Xintong Wang, Zheng Xu","doi":"10.3389/fphy.2024.1404448","DOIUrl":"https://doi.org/10.3389/fphy.2024.1404448","url":null,"abstract":"A regular calligraphy script of each calligrapher has unique strokes, and a script’s authenticity can be identified by comparing them. Hence, this study introduces a method for identifying the authenticity of regular script calligraphy works based on the improved YOLOv7 algorithm. The proposed method evaluates the authenticity of calligraphy works by detecting and comparing the number of single-character features in each regular script calligraphy work. Specifically, first, we collected regular script calligraphy works from a well-known domestic calligrapher and divided each work into a single-character dataset. Then, we introduced the PConv module in FasterNet, the DyHead dynamic detection header network, and the MPDiou bounding box loss function to optimize the accuracy of the YOLOv7 algorithm. Thus, we constructed an improved algorithm named YOLOv7-PDM, which is used for regular script calligraphy identification. The proposed YOLOv7-PDM model was trained and tested using a prepared regular script single-character dataset. Through experimental results, we confirmed the practicality and feasibility of the proposed method and demonstrated that the YOLOv7-PDM algorithm model achieves 94.19% accuracy (mAP50) in detecting regular script font features, with a single-image detection time of 3.1 m and 31.67M parameters. The improved YOLOv7 algorithm model offers greater advantages in detection speed, accuracy, and model complexity compared to current mainstream detection algorithms. This demonstrates that the developed approach effectively extracts stroke features of regular script calligraphy and provides guidance for future studies on authenticity identification.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141107135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-23DOI: 10.3389/fphy.2024.1384415
K. Altenmüller, J. F. Castel, S. Cebrián, T. Dafni, D. Díez-Ibañez, A. Ezquerro, E. Ferrer-Ribas, J. Galan, J. Galindo, J. A. García, A. Giganon, C. Goblin, I. G. Irastorza, C. Loiseau, G. Luzón, X. F. Navick, C. Margalejo, H. Mirallas, L. Obis, A. Ortiz de Solórzano, T. Papaevangelou, O. Pérez, A. Quintana, J. Ruz, J. K. Vogel
In this paper we present measurements performed with a Micromegas X-ray detector setup. The detector is a prototype in the context of the BabyIAXO helioscope, which is under construction to search for an emission of the hypothetical axion particle from the Sun. An important component of such a helioscope is a low background X-ray detector with a high efficiency in the 1–10 keV energy range. The goal of the measurement was to study techniques for background discrimination. In addition to common techniques we used a multi-layer veto system designed to tag cosmic-ray induced neutron background. Over an effective time of 52 days, a background level of 8.6 × 10−7 counts keV−1 cm−2 s−1 was reached in a laboratory at above ground level. This is the lowest background level achieved at surface level. In this paper we present the experimental setup, show simulations of the neutron-induced background, and demonstrate the process to identify background signals in the data. Finally, prospects to reach lower background levels down to 10–7 counts keV−1 cm−2 s−1 are discussed.
{"title":"Background discrimination with a Micromegas detector prototype and veto system for BabyIAXO","authors":"K. Altenmüller, J. F. Castel, S. Cebrián, T. Dafni, D. Díez-Ibañez, A. Ezquerro, E. Ferrer-Ribas, J. Galan, J. Galindo, J. A. García, A. Giganon, C. Goblin, I. G. Irastorza, C. Loiseau, G. Luzón, X. F. Navick, C. Margalejo, H. Mirallas, L. Obis, A. Ortiz de Solórzano, T. Papaevangelou, O. Pérez, A. Quintana, J. Ruz, J. K. Vogel","doi":"10.3389/fphy.2024.1384415","DOIUrl":"https://doi.org/10.3389/fphy.2024.1384415","url":null,"abstract":"In this paper we present measurements performed with a Micromegas X-ray detector setup. The detector is a prototype in the context of the BabyIAXO helioscope, which is under construction to search for an emission of the hypothetical axion particle from the Sun. An important component of such a helioscope is a low background X-ray detector with a high efficiency in the 1–10 keV energy range. The goal of the measurement was to study techniques for background discrimination. In addition to common techniques we used a multi-layer veto system designed to tag cosmic-ray induced neutron background. Over an effective time of 52 days, a background level of 8.6 × 10<jats:sup>−7</jats:sup> counts keV<jats:sup>−1</jats:sup> cm<jats:sup>−2</jats:sup> s<jats:sup>−1</jats:sup> was reached in a laboratory at above ground level. This is the lowest background level achieved at surface level. In this paper we present the experimental setup, show simulations of the neutron-induced background, and demonstrate the process to identify background signals in the data. Finally, prospects to reach lower background levels down to 10<jats:sup>–7</jats:sup> counts keV<jats:sup>−1</jats:sup> cm<jats:sup>−2</jats:sup> s<jats:sup>−1</jats:sup> are discussed.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-22DOI: 10.3389/fphy.2024.1393279
Bertram Schwind, Xia Wu, Michael Tiemann, Helge-Otto Fabritius
Leaky mode resonances of the setae of Cataglyphis bombycina are found to enhance the thermal emission of the animals by near field coupling to the chitinous exoskeleton. This is remarkable, as the setae are also an adaption to enhance the reflectivity in the visible wavelength range. Both effects are dependent on morphology, dimensions and spatial arrangement. These parameters were experimentally characterized and simulated by finite difference time domain simulations to elucidate the optical impact of the setae in the mid infrared range and the contribution of leaky mode resonances. This mode of action and the setae’s optical properties in the visible range explain evolutionary strains that led to the actual morphology and size of the setae.
{"title":"Natural near field coupled leaky-mode resonant anti-reflection structures: the setae of Cataglyphis bombycina","authors":"Bertram Schwind, Xia Wu, Michael Tiemann, Helge-Otto Fabritius","doi":"10.3389/fphy.2024.1393279","DOIUrl":"https://doi.org/10.3389/fphy.2024.1393279","url":null,"abstract":"Leaky mode resonances of the setae of Cataglyphis bombycina are found to enhance the thermal emission of the animals by near field coupling to the chitinous exoskeleton. This is remarkable, as the setae are also an adaption to enhance the reflectivity in the visible wavelength range. Both effects are dependent on morphology, dimensions and spatial arrangement. These parameters were experimentally characterized and simulated by finite difference time domain simulations to elucidate the optical impact of the setae in the mid infrared range and the contribution of leaky mode resonances. This mode of action and the setae’s optical properties in the visible range explain evolutionary strains that led to the actual morphology and size of the setae.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141112375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-21DOI: 10.3389/fphy.2024.1387608
Qianxi Ni, Luqiao Chen, Jianfeng Tan, Jinmeng Pang, Longjun Luo, Jun Zhu, Xiaohua Yang
The implementation of patient-specific quality assurance (PSQA) has become a crucial aspect of the radiation therapy process. Machine learning models have demonstrated their potential as virtual QA tools, accurately predicting the gamma passing rate (GPR) of volumetric modulated arc therapy (VMAT)plans, thereby ensuring safe and efficient treatment for patients. However, there is limited multi-center research dedicated to predicting the GPR. In this study, a dosiomics-based machine learning approach was employed to construct a prediction model for classifying GPR in multiple radiotherapy institutions. Additionally, the model’s performance was compared by evaluating the impact of two distinct feature selection methods.A retrospective data collection was conducted on 572 VMAT patients across three radiotherapy institutions. Utilizing a three-dimensional dose verification technique grounded in real-time measurements, γ analysis was conducted according to the criteria of 3%/2 mm and 2%/2 mm, employing a dose threshold of 10% along with absolute dose and global normalization mode. Dosiomics features were extracted from the dose files, and distinct subsets of features were selected as inputs for the model using the random forest (RF) and RF combined with SHapley Additive exPlanations (SHAP) methods. The data underwent training using the extreme gradient boosting (XGBoost) algorithm, and the model’s classification performance was assessed through F1-score and area under the curve (AUC) values.The model exhibited optimal performance under the 3%/2 mm criteria, utilizing a subset of 20 features and attaining an AUC value of 0.88 and an F1-score of 0.89. Similarly, under the 2%/2 mm criteria, the model demonstrated superior performance with a subset of 10 features, resulting in an AUC value of 0.91 and an F1-score of 0.89. The feature selection methods of RF and RF + SHAP have achieved good model performance by selecting as few features as possible.Based on the multi-center PSQA results, it is possible to utilize dosiomics features extracted from dose files to construct a machine learning predictive model. This model demonstrates excellent discriminative abilities, thus promoting the progress of gamma passing rate prognostic models in clinical application and implementation. Furthermore, it holds potential in providing patients with secure and efficient personalized QA management, while also reducing the workload of medical physicists.
{"title":"Predicting the PSQA results of volumetric modulated arc therapy based on dosiomics features: a multi-center study","authors":"Qianxi Ni, Luqiao Chen, Jianfeng Tan, Jinmeng Pang, Longjun Luo, Jun Zhu, Xiaohua Yang","doi":"10.3389/fphy.2024.1387608","DOIUrl":"https://doi.org/10.3389/fphy.2024.1387608","url":null,"abstract":"The implementation of patient-specific quality assurance (PSQA) has become a crucial aspect of the radiation therapy process. Machine learning models have demonstrated their potential as virtual QA tools, accurately predicting the gamma passing rate (GPR) of volumetric modulated arc therapy (VMAT)plans, thereby ensuring safe and efficient treatment for patients. However, there is limited multi-center research dedicated to predicting the GPR. In this study, a dosiomics-based machine learning approach was employed to construct a prediction model for classifying GPR in multiple radiotherapy institutions. Additionally, the model’s performance was compared by evaluating the impact of two distinct feature selection methods.A retrospective data collection was conducted on 572 VMAT patients across three radiotherapy institutions. Utilizing a three-dimensional dose verification technique grounded in real-time measurements, γ analysis was conducted according to the criteria of 3%/2 mm and 2%/2 mm, employing a dose threshold of 10% along with absolute dose and global normalization mode. Dosiomics features were extracted from the dose files, and distinct subsets of features were selected as inputs for the model using the random forest (RF) and RF combined with SHapley Additive exPlanations (SHAP) methods. The data underwent training using the extreme gradient boosting (XGBoost) algorithm, and the model’s classification performance was assessed through F1-score and area under the curve (AUC) values.The model exhibited optimal performance under the 3%/2 mm criteria, utilizing a subset of 20 features and attaining an AUC value of 0.88 and an F1-score of 0.89. Similarly, under the 2%/2 mm criteria, the model demonstrated superior performance with a subset of 10 features, resulting in an AUC value of 0.91 and an F1-score of 0.89. The feature selection methods of RF and RF + SHAP have achieved good model performance by selecting as few features as possible.Based on the multi-center PSQA results, it is possible to utilize dosiomics features extracted from dose files to construct a machine learning predictive model. This model demonstrates excellent discriminative abilities, thus promoting the progress of gamma passing rate prognostic models in clinical application and implementation. Furthermore, it holds potential in providing patients with secure and efficient personalized QA management, while also reducing the workload of medical physicists.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141115148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-20DOI: 10.3389/fphy.2024.1353425
Brian M. Andersen, Andreas Kreisel, P. J. Hirschfeld
A growing number of superconducting materials display evidence for spontaneous time-reversal symmetry breaking (TRSB) below their critical transition temperatures. Precisely what this implies for the nature of the superconducting ground state of such materials, however, is often not straightforward to infer. We review the experimental status and survey different theoretical mechanisms for the generation of TRSB in superconductors. In cases where a TRSB complex combination of two superconducting order parameter components is realized, defects, dislocations and sample edges may generate superflow patterns that can be picked up by magnetic probes. However, even single-component condensates that do not break time-reversal symmetry in their pure bulk phases can also support signatures of magnetism inside the superconducting state. This includes, for example, the generation of localized orbital current patterns or spin-polarization near atomic-scale impurities, twin boundaries and other defects. Signals of TRSB may also arise from a superconductivity-enhanced Ruderman-Kittel-Kasuya-Yosida exchange coupling between magnetic impurity moments present in the normal state. We discuss the relevance of these different mechanisms for TRSB in light of recent experiments on superconducting materials of current interest.
{"title":"Spontaneous time-reversal symmetry breaking by disorder in superconductors","authors":"Brian M. Andersen, Andreas Kreisel, P. J. Hirschfeld","doi":"10.3389/fphy.2024.1353425","DOIUrl":"https://doi.org/10.3389/fphy.2024.1353425","url":null,"abstract":"A growing number of superconducting materials display evidence for spontaneous time-reversal symmetry breaking (TRSB) below their critical transition temperatures. Precisely what this implies for the nature of the superconducting ground state of such materials, however, is often not straightforward to infer. We review the experimental status and survey different theoretical mechanisms for the generation of TRSB in superconductors. In cases where a TRSB complex combination of two superconducting order parameter components is realized, defects, dislocations and sample edges may generate superflow patterns that can be picked up by magnetic probes. However, even single-component condensates that do not break time-reversal symmetry in their pure bulk phases can also support signatures of magnetism inside the superconducting state. This includes, for example, the generation of localized orbital current patterns or spin-polarization near atomic-scale impurities, twin boundaries and other defects. Signals of TRSB may also arise from a superconductivity-enhanced Ruderman-Kittel-Kasuya-Yosida exchange coupling between magnetic impurity moments present in the normal state. We discuss the relevance of these different mechanisms for TRSB in light of recent experiments on superconducting materials of current interest.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.3389/fphy.2024.1398261
Min Fu, Ying Mei, Lixin Tian, Chao Zhang
This paper introduces a new green decomposition model of carbon productivity that aims to further analyze the regional differences in carbon productivity and its interaction with regional industrial performance. We combine desired outputs and undesired outputs orientation, and multiple factor inputs to derive a new green decomposition theorem, establish a new green decomposition model of carbon productivity, and obtain nine effects of regional carbon productivity differences. Empirical analysis is conducted using input-output data from 29 provinces and 15 industries in China, comparing the differences in carbon productivity from both the provincial and industry perspectives and exploring the mechanism of action. This paper provides theoretical basis and empirical evidence for regional carbon productivity enhancement and economic and industrial optimization from the perspective of multi-factor inputs, as well as policy insights for regional low-carbon transition development.
{"title":"Analysis of regional carbon productivity differences and influencing factors—based on new green decomposition model","authors":"Min Fu, Ying Mei, Lixin Tian, Chao Zhang","doi":"10.3389/fphy.2024.1398261","DOIUrl":"https://doi.org/10.3389/fphy.2024.1398261","url":null,"abstract":"This paper introduces a new green decomposition model of carbon productivity that aims to further analyze the regional differences in carbon productivity and its interaction with regional industrial performance. We combine desired outputs and undesired outputs orientation, and multiple factor inputs to derive a new green decomposition theorem, establish a new green decomposition model of carbon productivity, and obtain nine effects of regional carbon productivity differences. Empirical analysis is conducted using input-output data from 29 provinces and 15 industries in China, comparing the differences in carbon productivity from both the provincial and industry perspectives and exploring the mechanism of action. This paper provides theoretical basis and empirical evidence for regional carbon productivity enhancement and economic and industrial optimization from the perspective of multi-factor inputs, as well as policy insights for regional low-carbon transition development.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.3389/fphy.2024.1392767
Jing Huang, Feng Chen, Ke Wang, Sheng Chen
Currently, there is an urgent need for a fast and portable intracerebral hemorrhage (ICH) detection technology for pre-hospital emergency scenarios. Owing to the disproportionately elevated permittivity of blood compared to other brain tissues, Electrical Capacitance Tomography (ECT) offers a viable modality for mapping the spatial distribution of permittivity within the brain, thus facilitating the imaging-based identification of ICH. Currently, ECT is confined to time-differential imaging due to limited sensitivity, and this methodology requires non-hemorrhagic measurements for comparison, data that are frequently inaccessible in clinical contexts. To overcome this limitation, in accordance with the natural bilateral symmetry of the cerebral hemispheres, a symmetrical cancellation scheme is introduced. In this method, electrodes are uniformly arrayed around the cranial periphery and strategically positioned in a symmetrical manner relative to the sagittal suture. Subsequently, the measured capacitances for each electrode pair are subtracted from those of their symmetrical counterparts aligned with the sagittal suture. As a result, this process isolates the capacitance attributable solely to hemorrhagic events within a given hemisphere, permitting the absolute imaging of ICH. To assess the feasibility of this method, simulation and empirical imaging were conducted respectively on a numerical hemorrhage model and three physical models (a water-wrapped hemorrhage model, an isolated porcine fat-wrapped hemorrhage model, and an isolated porcine brain tissue-wrapped hemorrhage model). Traditional absolute imaging, time-differential imaging and symmetrical cancellation imaging were performed on all models. The results substantiate that the proposed imaging modality is capable of obtaining absolute imaging of ICH. But a mirrored artifact, symmetrical to the site of the actual hemorrhage image appeared in each of the imaging results. This mirror artifact was characterized by identical dimensions and an inverted pixel-value schema, an intrinsic consequence of the symmetrical cancellation imaging algorithm. The real image of hemorrhage can be ascertained through pre-judgment with the symptoms of the patient. Additionally, the quality of this imaging is seriously dependent on the precise alignment between the electrodes and the sagittal suture of the brain; even a minor deviation in symmetry could introduce excessive noises. Thus, the complicated operational procedures remain as challenges for practical application.
目前，院前急救急需一种快速、便携的脑出血（ICH）检测技术。由于血液的介电常数比其他脑组织高得不成比例，电容断层扫描（ECT）为绘制脑内介电常数的空间分布图提供了一种可行的模式，从而促进了基于成像的 ICH 识别。目前，ECT 因灵敏度有限而仅限于时差成像，而且这种方法需要非出血测量数据进行比较，而这些数据在临床上往往无法获得。为了克服这一局限性，根据大脑半球的天然双侧对称性，引入了对称消除方案。在这种方法中，电极均匀地排列在颅骨周围，并以相对于矢状缝的对称方式进行战略定位。随后，从与矢状缝对齐的对称电极对中减去每个电极对的测量电容。因此，这一过程可分离出仅由特定半球内出血事件引起的电容，从而对 ICH 进行绝对成像。为了评估这种方法的可行性，分别对一个出血数值模型和三个物理模型（水包裹出血模型、猪脂肪包裹出血模型和猪脑组织包裹出血模型）进行了模拟和经验成像。对所有模型都进行了传统的绝对成像、时差成像和对称消除成像。结果证明，所提出的成像模式能够获得 ICH 的绝对成像。但在每个成像结果中都出现了与实际出血部位对称的镜像伪影。这种镜像伪影的特征是尺寸相同，像素值模式颠倒，这是对称取消成像算法的内在结果。出血的真实图像可以通过与患者的症状进行预先判断来确定。此外，这种成像的质量严重依赖于电极与大脑矢状缝之间的精确对齐；即使是对称性的微小偏差也会带来过多的噪声。因此，复杂的操作程序仍然是实际应用的挑战。
{"title":"Research on electrical capacitance tomography (ECT) detection of cerebral hemorrhage based on symmetrical cancellation method","authors":"Jing Huang, Feng Chen, Ke Wang, Sheng Chen","doi":"10.3389/fphy.2024.1392767","DOIUrl":"https://doi.org/10.3389/fphy.2024.1392767","url":null,"abstract":"Currently, there is an urgent need for a fast and portable intracerebral hemorrhage (ICH) detection technology for pre-hospital emergency scenarios. Owing to the disproportionately elevated permittivity of blood compared to other brain tissues, Electrical Capacitance Tomography (ECT) offers a viable modality for mapping the spatial distribution of permittivity within the brain, thus facilitating the imaging-based identification of ICH. Currently, ECT is confined to time-differential imaging due to limited sensitivity, and this methodology requires non-hemorrhagic measurements for comparison, data that are frequently inaccessible in clinical contexts. To overcome this limitation, in accordance with the natural bilateral symmetry of the cerebral hemispheres, a symmetrical cancellation scheme is introduced. In this method, electrodes are uniformly arrayed around the cranial periphery and strategically positioned in a symmetrical manner relative to the sagittal suture. Subsequently, the measured capacitances for each electrode pair are subtracted from those of their symmetrical counterparts aligned with the sagittal suture. As a result, this process isolates the capacitance attributable solely to hemorrhagic events within a given hemisphere, permitting the absolute imaging of ICH. To assess the feasibility of this method, simulation and empirical imaging were conducted respectively on a numerical hemorrhage model and three physical models (a water-wrapped hemorrhage model, an isolated porcine fat-wrapped hemorrhage model, and an isolated porcine brain tissue-wrapped hemorrhage model). Traditional absolute imaging, time-differential imaging and symmetrical cancellation imaging were performed on all models. The results substantiate that the proposed imaging modality is capable of obtaining absolute imaging of ICH. But a mirrored artifact, symmetrical to the site of the actual hemorrhage image appeared in each of the imaging results. This mirror artifact was characterized by identical dimensions and an inverted pixel-value schema, an intrinsic consequence of the symmetrical cancellation imaging algorithm. The real image of hemorrhage can be ascertained through pre-judgment with the symptoms of the patient. Additionally, the quality of this imaging is seriously dependent on the precise alignment between the electrodes and the sagittal suture of the brain; even a minor deviation in symmetry could introduce excessive noises. Thus, the complicated operational procedures remain as challenges for practical application.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.3389/fphy.2024.1391608
Guozhong Lei, Wenchang Lai, Qi Meng, Wenda Cui, Hao Liu, Yan Wang, Kai Han
In this manuscript, an automated optimization neural network is applied in Hadamard single-pixel imaging (H-SPI) and Fourier single-pixel imaging (F-SPI) to improve the imaging quality at low sampling ratios which is called AO-Net. By projecting Hadamard or Fourier basis illumination light fields onto the object, a single-pixel detector is used to collect the reflected light intensities from object. The one-dimensional detection values are fed into the designed AO-Net, and the network can automatically optimize. Finally, high-quality images are output through multiple iterations without pre-training and datasets. Numerical simulations and experiments demonstrate that AO-Net outperforms other existing widespread methods for both binary and grayscale images at low sampling ratios. Specially, the Structure Similarity Index Measure value of the binary reconstructed image can reach more than 0.95 when the sampling ratio is less than 3%. Therefore, AO-Net holds great potential for applications in the fields of complex environment imaging and moving object imaging.
在本手稿中，一种自动优化神经网络被应用于哈达玛单像素成像（H-SPI）和傅立叶单像素成像（F-SPI），以提高低采样率下的成像质量，这种网络被称为 AO-Net。通过将哈达玛或傅里叶基照明光场投射到物体上，使用单像素探测器收集物体的反射光强度。将一维检测值输入设计好的 AO 网络，网络就能自动优化。最后，通过多次迭代输出高质量图像，而无需预先训练和数据集。数值模拟和实验证明，在低采样率的二值图像和灰度图像中，AO-Net 的表现优于其他现有的普遍方法。特别是，当采样率小于 3% 时，二值重建图像的结构相似性指数测量值可以达到 0.95 以上。因此，AO-Net 在复杂环境成像和移动物体成像领域具有巨大的应用潜力。
{"title":"Low-sampling high-quality Hadamard and Fourier single-pixel imaging through automated optimization neural network","authors":"Guozhong Lei, Wenchang Lai, Qi Meng, Wenda Cui, Hao Liu, Yan Wang, Kai Han","doi":"10.3389/fphy.2024.1391608","DOIUrl":"https://doi.org/10.3389/fphy.2024.1391608","url":null,"abstract":"In this manuscript, an automated optimization neural network is applied in Hadamard single-pixel imaging (H-SPI) and Fourier single-pixel imaging (F-SPI) to improve the imaging quality at low sampling ratios which is called AO-Net. By projecting Hadamard or Fourier basis illumination light fields onto the object, a single-pixel detector is used to collect the reflected light intensities from object. The one-dimensional detection values are fed into the designed AO-Net, and the network can automatically optimize. Finally, high-quality images are output through multiple iterations without pre-training and datasets. Numerical simulations and experiments demonstrate that AO-Net outperforms other existing widespread methods for both binary and grayscale images at low sampling ratios. Specially, the Structure Similarity Index Measure value of the binary reconstructed image can reach more than 0.95 when the sampling ratio is less than 3%. Therefore, AO-Net holds great potential for applications in the fields of complex environment imaging and moving object imaging.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.3389/fphy.2024.1413037
Xutao Jia, Tianhong Song, Guang Liu
As an effective particle measurement method, laser-based particle sensors combined with unmanned aerial vehicles (UAVs) can be used for measuring air quality in near ground space. The Sniffer4D Mini2 features portability and real-time acquisition of accurate spatial distribution information on air pollution. Additionally, a new fine-grained analysis method called Co-KNN-DNN has been proposed to assess air quality between flight trajectories, allowing for a more detailed presentation of the continuous distribution of air quality. Therefore, this article introduces an unmanned aerial vehicle measurement fine-grained analysis method based on laser light scattering particle sensors. Firstly, the overall scheme was designed, M30T UAV was selected to carry the portable air quality monitoring equipment, with laser-based laser particulate matter sensor and Mini2, to collect AQI and related attributes of the near-ground layer in the selected research area, to do the necessary processing of the collected data, to build a data set suitable for model input, etc., to train and optimize the model, and to carry out practical application of the model. This article is based on the Co-KNN-DNN model for fine-grained analysis of air quality in spatial dimensions. Three experiments were conducted at different altitudes in the study area to investigate the practical application of fine-grained analysis of near-surface air quality. The experimental results show that the average R-squared value can reach 0.99. Choose to conduct experiments using the M30T UAV equipped with Sniffer4D Mini2 and a laser-based particulate matter sensor. The application research validates the effectiveness and practicality of the Co-KNN-DNN model.
{"title":"Fine grained analysis method for unmanned aerial vehicle measurement based on laser-based light scattering particle sensing","authors":"Xutao Jia, Tianhong Song, Guang Liu","doi":"10.3389/fphy.2024.1413037","DOIUrl":"https://doi.org/10.3389/fphy.2024.1413037","url":null,"abstract":"As an effective particle measurement method, laser-based particle sensors combined with unmanned aerial vehicles (UAVs) can be used for measuring air quality in near ground space. The Sniffer4D Mini2 features portability and real-time acquisition of accurate spatial distribution information on air pollution. Additionally, a new fine-grained analysis method called Co-KNN-DNN has been proposed to assess air quality between flight trajectories, allowing for a more detailed presentation of the continuous distribution of air quality. Therefore, this article introduces an unmanned aerial vehicle measurement fine-grained analysis method based on laser light scattering particle sensors. Firstly, the overall scheme was designed, M30T UAV was selected to carry the portable air quality monitoring equipment, with laser-based laser particulate matter sensor and Mini2, to collect AQI and related attributes of the near-ground layer in the selected research area, to do the necessary processing of the collected data, to build a data set suitable for model input, etc., to train and optimize the model, and to carry out practical application of the model. This article is based on the Co-KNN-DNN model for fine-grained analysis of air quality in spatial dimensions. Three experiments were conducted at different altitudes in the study area to investigate the practical application of fine-grained analysis of near-surface air quality. The experimental results show that the average R-squared value can reach 0.99. Choose to conduct experiments using the M30T UAV equipped with Sniffer4D Mini2 and a laser-based particulate matter sensor. The application research validates the effectiveness and practicality of the Co-KNN-DNN model.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140926929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.3389/fphy.2024.1383537
Yiyi Ma, Linjiang Guo, Yuanhao Xiao, Anhua Ji
Bubble mass transfer is a common phenomenon in industrial applications. In this paper, bubble dynamics in both still and turbulent flow were introduced first, followed by the mass transfer properties of a single bubble and bubble swarms. Then, bubble mass transfer models for different scenarios were summarized, including three classical models, extended models, eddy diffusion and whirlpool theoretical models, and semi- or empirical correlations. Finally, existing methods for mass transfer intensification in industries were reviewed. Despite extensive researches, the mechanism for bubble mass transfer has not been fully understood. Models are commonly limited to some specific conditions and the accuracy is limited, especially for bubble swarms and bubble mass transfer in turbulent and non-Newtonian fluids. Also, the mass transfer intensification methods have their own limitations. Additional exploration of knowledge on bubble mass transfer models and further improvement in mass transfer intensification technologies are still required in the future.
{"title":"Bubble mass transfer in fluids under gravity: a review of theoretical models and intensification technologies in industry","authors":"Yiyi Ma, Linjiang Guo, Yuanhao Xiao, Anhua Ji","doi":"10.3389/fphy.2024.1383537","DOIUrl":"https://doi.org/10.3389/fphy.2024.1383537","url":null,"abstract":"Bubble mass transfer is a common phenomenon in industrial applications. In this paper, bubble dynamics in both still and turbulent flow were introduced first, followed by the mass transfer properties of a single bubble and bubble swarms. Then, bubble mass transfer models for different scenarios were summarized, including three classical models, extended models, eddy diffusion and whirlpool theoretical models, and semi- or empirical correlations. Finally, existing methods for mass transfer intensification in industries were reviewed. Despite extensive researches, the mechanism for bubble mass transfer has not been fully understood. Models are commonly limited to some specific conditions and the accuracy is limited, especially for bubble swarms and bubble mass transfer in turbulent and non-Newtonian fluids. Also, the mass transfer intensification methods have their own limitations. Additional exploration of knowledge on bubble mass transfer models and further improvement in mass transfer intensification technologies are still required in the future.","PeriodicalId":12507,"journal":{"name":"Frontiers in Physics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140926839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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