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Hou H, Wang T, Li J, Zhang Y, Tang C. Vision-based algorithm for online TIG welding deviation detection of stainless steel welded pipes. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2024; 41:1175-1184. [PMID: 38856433 DOI: 10.1364/josaa.509496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 04/26/2024] [Indexed: 06/11/2024]
Abstract
Tungsten inert gas (TIG) welding is the main welding process in the production of stainless steel welded pipe. According to the morphological characteristics of the welding molten pool image during the TIG welding process of stainless steel welded pipes, the exact position of the tungsten needle tip is calculated using image moments. Extract the weld region in the contour of the molten pool, interpolate the contour curve based on the cubic B-spline curve interpolation method, utilize the characteristics of the S-G filter, remove the interference coordinates in the contour curve through the detrending of the contour curve, extract the weld feature points, and realize the accurate identification of weld seams. The experimental results show that the method can accurately calculate the welding deviation in the welding process.
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Durán-Santos M, Salazar-Varas R, Etcheverry G. Modeling the cortical response elicited by wrist manipulation via a nonlinear delay differential embedding. Phys Eng Sci Med 2024:10.1007/s13246-024-01427-8. [PMID: 38739346 DOI: 10.1007/s13246-024-01427-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 04/16/2024] [Indexed: 05/14/2024]
Abstract
Regarding motor processes, modeling healthy people's brains is essential to understand the brain activity in people with motor impairments. However, little research has been undertaken when external forces disturb limbs, having limited information on physiological pathways. Therefore, in this paper, a nonlinear delay differential embedding model is used to estimate the brain response elicited by externally controlled wrist movement in healthy individuals. The aim is to improve the understanding of the relationship between a controlled wrist movement and the generated cortical activity of healthy people, helping to disclose the underlying mechanisms and physiological relationships involved in the motor event. To evaluate the model, a public database from the Delft University of Technology is used, which contains electroencephalographic recordings of ten healthy subjects while wrist movement was externally provoked by a robotic system. In this work, the cortical response related to movement is identified via Independent Component Analysis and estimated based on a nonlinear delay differential embedding model. After a cross-validation analysis, the model performance reaches 90.21% ± 4.46% Variance Accounted For, and Correlation 95.14% ± 2.31%. The proposed methodology allows to select the model degree, to estimate a general predominant operation mode of the cortical response elicited by wrist movement. The obtained results revealed two facts that had not previously been reported: the movement's acceleration affects the cortical response, and a common delayed activity is shared among subjects. Going forward, identifying biomarkers related to motor tasks could aid in the evaluation of rehabilitation treatments for patients with upper limbs motor impairments.
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Affiliation(s)
- Martín Durán-Santos
- Department of Computing, Electronics and Mechatronics, Universidad de las Americas Puebla (UDLAP), Ex Hacienda Sta. Catarina Mártir S/N, C.P. 72810, San Andrés Cholula, Puebla, Mexico.
| | - R Salazar-Varas
- Department of Computing, Electronics and Mechatronics, Universidad de las Americas Puebla (UDLAP), Ex Hacienda Sta. Catarina Mártir S/N, C.P. 72810, San Andrés Cholula, Puebla, Mexico
| | - Gibran Etcheverry
- Department of Mathematics, Tiffin University, 155 Miami St, Tiffin, OH, 44883, USA
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North J, Saari-Nordhaus R, Doddridge G, Seefeldt M, Young DA, Liu Y. Non-destructive Raman Method Development for Quantifying Active Pharmaceutical Ingredient in an Oral Suspension Through Plastic Dosing Syringes. AAPS PharmSciTech 2024; 25:76. [PMID: 38580881 DOI: 10.1208/s12249-024-02775-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 02/19/2024] [Indexed: 04/07/2024] Open
Abstract
For liquid drug products, e.g., solutions or suspensions for oral or parenteral dosing, stability needs to be demonstrated in primary packaging during storage and in dosing devices during in-use periods per quality guidelines from the International Conference on Harmonisation (ICH) and the European Agency for the Evaluation of Medicinal Products (EMEA). One aspect of stability testing for liquid drug products is in-use stability, which typically includes transferring the liquid samples into another container for further sample preparation with extraction diluent and necessary agitation. Samples are then analyzed with traditional chromatography methods, which are laborious, prone to human errors, and time-consuming, especially when this process needs to be repeated multiple times during storage and in-use periods. Being able to analyze the liquid samples non-destructively would significantly improve testing efficiency. We investigated different Raman techniques, including transmission Raman (TRS) and back scatter Raman with a non-contact optic (NCO) probe, as alternative non-destructive tools to the UHPLC method for API quantitation in in-use liquid samples pulled into plastic dosing syringes. The linearity of the chemometric methods for these two techniques was demonstrated by cross-validation sample sets at three levels over an API concentration range of 60 to 80 mg/mL. The accuracy of the chemometric models was demonstrated by the accurate prediction of the API concentrations in independent samples from four different pilot plant batches manufactured at different sites. Both techniques were successful in measuring a signal through a plastic oral dosing syringe, and predicting the suspension API concentration to within 4% of the UHPLC-measured value. For future work, there are opportunities to improve the methodology by exploring additional probes or to expand the range of applications by using different sample presentations (such as prefilled syringes) or formulation matrices for solutions and suspensions.
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Affiliation(s)
- Jacquelyn North
- Research & Development, AbbVie Inc, 1 N Waukegan Road, North Chicago, IL, 60064, USA
| | | | - Gregory Doddridge
- Research & Development, AbbVie Inc, 1 N Waukegan Road, North Chicago, IL, 60064, USA.
| | - Madeline Seefeldt
- Research & Development, AbbVie Inc, 1 N Waukegan Road, North Chicago, IL, 60064, USA
| | - Daniel A Young
- Research & Development, AbbVie Inc, 1 N Waukegan Road, North Chicago, IL, 60064, USA
| | - Yemin Liu
- Research & Development, AbbVie Inc, 1 N Waukegan Road, North Chicago, IL, 60064, USA.
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Yang Z, Zhang M, Li X, Xu Z, Chen Y, Xu X, Chen D, Meng L, Si X, Wang J. Fluorescence spectroscopic profiling of urine samples for predicting kidney transplant rejection. Photodiagnosis Photodyn Ther 2024; 45:103984. [PMID: 38244654 DOI: 10.1016/j.pdpdt.2024.103984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 01/08/2024] [Accepted: 01/17/2024] [Indexed: 01/22/2024]
Abstract
Rejection is the primary factor affecting the functionality of a kidney post-transplant, where its prompt prediction of risk significantly influences therapeutic strategies and clinical outcomes. Current graft health assessment methods, including serum creatinine measurements and transplant kidney puncture biopsies, possess considerable limitations. In contrast, urine serves as a direct indicator of the graft's degenerative stage and provides a more accurate measure than peripheral blood analysis, given its non-invasive collection of kidney-specific metabolite. This research entailed collecting fluorescent fingerprint data from 120 urine samples of post-renal transplant patients using hyperspectral imaging, followed by the development of a learning model to detect various forms of immunological rejection. The model successfully identified multiple rejection types with an average diagnostic accuracy of 95.56 %.Beyond proposing an innovative approach for predicting the risk of complications post-kidney transplantation, this study heralds the potential introduction of a non-invasive, rapid, and accurate supplementary method for risk assessment in clinical practice.
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Affiliation(s)
- Zhe Yang
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Minrui Zhang
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Xianduo Li
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Zhipeng Xu
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Yi Chen
- Shandong Medical College, Jinan 250000, China
| | - Xiaoyu Xu
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Dongdong Chen
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Lingquan Meng
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China
| | - Xiaoqing Si
- Department of dermatology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China.
| | - Jianning Wang
- Department of Urology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China.
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He X, Selesnick I, Zhu M. Research Progress of Eye Movement Analyses and its Detection Algorithms in Alzheimer's Disease. Curr Alzheimer Res 2024; 21:91-100. [PMID: 38661033 DOI: 10.2174/0115672050300564240416074025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/29/2024] [Accepted: 03/29/2024] [Indexed: 04/26/2024]
Abstract
Alzheimer's disease (AD) has been considered one of the most challenging forms of dementia. The earlier the people are diagnosed with AD, the easier it is for doctors to find a treatment. Based on the previous literature summarizing the research results on the relationship between eye movement and AD before 2013, this paper reviewed 34 original eye movements research papers only closely related to AD published in the past ten years and pointed out that the prosaccade (4 papers) and antisaccade (5 papers) tasks, reading tasks (3 papers), visual search tasks (3 papers) are still the research objects of many researchers, Some researchers have looked at King-Devick tasks (2 papers), reading tasks (3 papers) and special tasks (8 papers), and began to use combinations of different saccade tasks to detect the relationship between eye movement and AD, which had not been done before. These reflect the diversity of eye movement tasks and the complexity and difficulty of the relationship between eye movement and AD. On this basis, the current processing and analysis methods of eye movement datasets are analyzed and discussed in detail, and we note that certain key data that may be especially important for the early diagnosis of AD by using eye movement studies cannot be miss-classified as noise and removed. Finally, we note that the development of methods that can accurately denoise and classify and quickly process massive eye movement data is quite significant for detecting eye movements in early diagnosis of AD.
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Affiliation(s)
- Xueying He
- School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei, CN, USA
- Tandon School of Engineering, New York University, Brooklyn, NY, USA
| | - Ivan Selesnick
- Tandon School of Engineering, New York University, Brooklyn, NY, USA
| | - Ming Zhu
- School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei, CN, USA
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Tian M, Ma X, Liang M, Zang H. Application of Rapid Identification and Determination of Moisture Content of Coptidis Rhizoma From Different Species Based on Data Fusion. J AOAC Int 2023; 106:1389-1401. [PMID: 37171863 DOI: 10.1093/jaoacint/qsad058] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/25/2023] [Accepted: 05/08/2023] [Indexed: 05/13/2023]
Abstract
BACKGROUND For thousands of years, traditional Chinese medicine (TCM) has been clinically proven, and doctors have highly valued the differences in utility between different species. OBJECTIVE This study aims to replace the complex methods traditionally used for empirical identification by compensating for the information loss of a single sensor through data fusion. The research object of the study is Coptidis rhizoma (CR). METHOD Using spectral optimization and data fusion technology, near infrared (NIR) and mid-infrared (MIR) spectra were collected for CR. PLS-DA (n = 134) and PLSR (n = 63) models were established to identify the medicinal materials and to determine the moisture content in the medicinal materials. RESULTS For the identification of the three species of CR, the mid-level fusion model performed better than the single-spectrum model. The sensitivity and specificity of the prediction set coefficients for NIR, MIR, and data fusion qualitative models were all higher than 0.95, with an AUC value of 1. The NIR data model was superior to the MIR data model. The results of low-level fusion were similar to those of the NIR optimization model. The RPD of the test set of NIR and low-level fusion model was 3.6420 and 3.4216, respectively, indicating good prediction ability of the model. CONCLUSIONS Data fusion technology using NIR and MIR can be applied to identify CR species and to determine the moisture content of CR. It provides technical support for the rapid determination of moisture content, with a fast analysis speed and without the need for complex pretreatment methods. HIGHLIGHTS This study is the first to introduce spectral data fusion technology to identify CR species. Data fusion technology is feasible for multivariable calibration model performance and reduces the cost of manual identification. The moisture content of CR can be quickly evaluated, reducing the difficulty of traditional methods.
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Affiliation(s)
- Mengyin Tian
- Shandong University, NMPA Key Laboratory for Technology Research and Evaluation of Drug Products, Cheeloo College of Medicine, Jinan, Shandong 250012, China
- Shandong University, Key Laboratory of Chemical Biology (Ministry of Education), Jinan, Shandong 250012, China
| | - Xiaobo Ma
- Shandong University, NMPA Key Laboratory for Technology Research and Evaluation of Drug Products, Cheeloo College of Medicine, Jinan, Shandong 250012, China
- Shandong University, Key Laboratory of Chemical Biology (Ministry of Education), Jinan, Shandong 250012, China
| | - Mengying Liang
- Shandong University, NMPA Key Laboratory for Technology Research and Evaluation of Drug Products, Cheeloo College of Medicine, Jinan, Shandong 250012, China
- Shandong University, Key Laboratory of Chemical Biology (Ministry of Education), Jinan, Shandong 250012, China
| | - Hengchang Zang
- Shandong University, NMPA Key Laboratory for Technology Research and Evaluation of Drug Products, Cheeloo College of Medicine, Jinan, Shandong 250012, China
- Shandong University, Key Laboratory of Chemical Biology (Ministry of Education), Jinan, Shandong 250012, China
- Shandong University, National Glycoengineering Research Center, Jinan, Shandong 250012, China
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Grossman SN, Calix R, Hudson T, Rizzo JR, Selesnick I, Frucht S, Galetta SL, Balcer LJ, Rucker JC. Accuracy of clinical versus oculographic detection of pathological saccadic slowing. J Neurol Sci 2022; 442:120436. [PMID: 36183516 DOI: 10.1016/j.jns.2022.120436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 08/23/2022] [Accepted: 09/18/2022] [Indexed: 10/31/2022]
Abstract
Saccadic slowing as a component of supranuclear saccadic gaze palsy is an important diagnostic sign in multiple neurologic conditions, including degenerative, inflammatory, genetic, or ischemic lesions affecting brainstem structures responsible for saccadic generation. Little attention has been given to the accuracy with which clinicians correctly identify saccadic slowing. We compared clinician (n = 19) judgements of horizontal and vertical saccade speed on video recordings of saccades (from 9 patients with slow saccades, 3 healthy controls) to objective saccade peak velocity measurements from infrared oculographic recordings. Clinician groups included neurology residents, general neurologists, and fellowship-trained neuro-ophthalmologists. Saccades with normal peak velocities on infrared recordings were correctly identified as normal in 57% (91/171; 171 = 9 videos × 19 clinicians) of clinician decisions; saccades determined to be slow on infrared recordings were correctly identified as slow in 84% (224/266; 266 = 14 videos × 19 clinicians) of clinician decisions. Vertical saccades were correctly identified as slow more often than horizontal saccades (94% versus 74% of decisions). No significant differences were identified between clinician training levels. Reliable differentiation between normal and slow saccades is clinically challenging; clinical performance is most accurate for detection of vertical saccade slowing. Quantitative analysis of saccade peak velocities enhances accurate detection and is likely to be especially useful for detection of mild saccadic slowing.
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Affiliation(s)
- Scott N Grossman
- Department of Neurology, New York University Grossman School of Medicine, United States of America.
| | - Rachel Calix
- Department of Neurology, New York University Grossman School of Medicine, United States of America
| | - Todd Hudson
- Department of Neurology, New York University Grossman School of Medicine, United States of America; Rusk Institute of Rehabilitation, New York University Grossman School of Medicine, United States of America
| | - John Ross Rizzo
- Department of Neurology, New York University Grossman School of Medicine, United States of America; Rusk Institute of Rehabilitation, New York University Grossman School of Medicine, United States of America
| | - Ivan Selesnick
- Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, United States of America
| | - Steven Frucht
- Department of Neurology, New York University Grossman School of Medicine, United States of America
| | - Steven L Galetta
- Department of Neurology, New York University Grossman School of Medicine, United States of America; Department of Ophthalmology, New York University Grossman School of Medicine, United States of America
| | - Laura J Balcer
- Department of Neurology, New York University Grossman School of Medicine, United States of America; Department of Ophthalmology, New York University Grossman School of Medicine, United States of America; Department of Population Health, New York University Grossman School of Medicine, United States of America
| | - Janet C Rucker
- Department of Neurology, New York University Grossman School of Medicine, United States of America; Department of Ophthalmology, New York University Grossman School of Medicine, United States of America
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Barnova K, Kahankova R, Jaros R, Litschmannova M, Martinek R. A comparative study of single-channel signal processing methods in fetal phonocardiography. PLoS One 2022; 17:e0269884. [PMID: 35984866 PMCID: PMC9390939 DOI: 10.1371/journal.pone.0269884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 05/29/2022] [Indexed: 11/18/2022] Open
Abstract
Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography. This study focuses on the comparison of fetal phonocardiography filtering using eight algorithms: Savitzky-Golay filter, finite impulse response filter, adaptive wavelet transform, maximal overlap discrete wavelet transform, variational mode decomposition, empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. The effectiveness of those methods was tested on four types of interference (maternal sounds, movement artifacts, Gaussian noise, and ambient noise) and eleven combinations of these disturbances. The dataset was created using two synthetic records r01 and r02, where the record r02 was loaded with higher levels of interference than the record r01. The evaluation was performed using the objective parameters such as accuracy of the detection of S1 and S2 sounds, signal-to-noise ratio improvement, and mean error of heart interval measurement. According to all parameters, the best results were achieved using the complete ensemble empirical mode decomposition with adaptive noise method with average values of accuracy = 91.53% in the detection of S1 and accuracy = 68.89% in the detection of S2. The average value of signal-to-noise ratio improvement achieved by complete ensemble empirical mode decomposition with adaptive noise method was 9.75 dB and the average value of the mean error of heart interval measurement was 3.27 ms.
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Affiliation(s)
- Katerina Barnova
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, Ostrava, Czechia
| | - Radana Kahankova
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, Ostrava, Czechia
| | - Rene Jaros
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, Ostrava, Czechia
- * E-mail:
| | - Martina Litschmannova
- Department of Applied Mathematics, Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, Ostrava, Czechia
| | - Radek Martinek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, Ostrava, Czechia
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Shu M, Zhou L, Chen H, Wang X, Meng L, Ma Y. Estimation of amino acid contents in maize leaves based on hyperspectral imaging. FRONTIERS IN PLANT SCIENCE 2022; 13:885794. [PMID: 35991404 PMCID: PMC9381814 DOI: 10.3389/fpls.2022.885794] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 07/11/2022] [Indexed: 06/15/2023]
Abstract
Estimation of the amino acid content in maize leaves is helpful for improving maize yield estimation and nitrogen use efficiency. Hyperspectral imaging can be used to obtain the physiological and biochemical parameters of maize leaves with the advantages of being rapid, non-destructive, and high throughput. This study aims to estimate the multiple amino acid contents in maize leaves using hyperspectral imaging data. Two nitrogen (N) fertilizer experiments were carried out to obtain the hyperspectral images of fresh maize leaves. The partial least squares regression (PLSR) method was used to build the estimation models of various amino acid contents by using the reflectance of all bands, sensitive band range, and sensitive bands. The models were then validated with the independent dataset. The results showed that (1) the spectral reflectance of most amino acids was more sensitive in the range of 400-717.08 nm than other bands. The estimation accuracy was better by using the reflectance of the sensitive band range than that of all bands; (2) the sensitive bands of most amino acids were in the ranges of 505.39-605 nm and 651-714 nm; and (3) among the 24 amino acids, the estimation models of the β-aminobutyric acid, ornithine, citrulline, methionine, and histidine achieved higher accuracy than those of other amino acids, with the R 2, relative root mean square error (RE), and relative percent deviation (RPD) of the measured and estimated value of testing samples in the range of 0.84-0.96, 8.79%-19.77%, and 2.58-5.18, respectively. This study can provide a non-destructive and rapid diagnostic method for genetic sensitive analysis and variety improvement of maize.
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Affiliation(s)
- Meiyan Shu
- College of Land Science and Technology, China Agricultural University, Beijing, China
| | - Long Zhou
- College of Biological Science, China Agricultural University, Beijing, China
| | - Haochong Chen
- College of Land Science and Technology, China Agricultural University, Beijing, China
| | - Xiqing Wang
- College of Biological Science, China Agricultural University, Beijing, China
| | - Lei Meng
- Department of Geography, Environment, and Tourism, Western Michigan University, Kalamazoo, MI, United States
| | - Yuntao Ma
- College of Land Science and Technology, China Agricultural University, Beijing, China
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Rapid Automatized Picture Naming in an Outpatient Concussion Center: Quantitative Eye Movements during the Mobile Universal Lexicon Evaluation System (MULES) Test. CLINICAL AND TRANSLATIONAL NEUROSCIENCE 2022. [DOI: 10.3390/ctn6030018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Number and picture rapid automatized naming (RAN) tests are useful sideline diagnostic tools. The main outcome measure of these RAN tests is the completion time, which is prolonged with a concussion, yet yields no information about eye movement behavior. We investigated eye movements during a digitized Mobile Universal Lexicon Evaluation System (MULES) test of rapid picture naming. A total of 23 participants with a history of concussion and 50 control participants performed MULES testing with simultaneous eye tracking. The test times were longer in participants with a concussion (32.4 s [95% CI 30.4, 35.8] vs. 26.9 s [95% CI 25.9, 28.0], t=6.1). The participants with a concussion made more saccades per picture than the controls (3.6 [95% CI 3.3, 4.1] vs. 2.7 [95% CI 2.5, 3.0]), and this increase was correlated with longer MULES times (r = 0.46, p = 0.026). The inter-saccadic intervals (ISI) did not differ between the groups, nor did they correlate with the test times. Following a concussion, eye movement behavior differs during number versus picture RAN performance. Prior studies have shown that ISI prolongation is the key finding for a number-based RAN test, whereas this study shows a primary finding of an increased saccade number per picture with a picture-based RAN test. Number-based and picture-based RAN tests may be complimentary in concussion detection, as they may detect different injury effects or compensatory strategies.
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11
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Smart-Median: A New Real-Time Algorithm for Smoothing Singing Pitch Contours. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12147026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Pitch detection is usually one of the fundamental steps in audio signal processing. However, it is common for pitch detectors to estimate a portion of the fundamental frequencies incorrectly, especially in real-time environments and when applied to singing. Therefore, the estimated pitch contour usually has errors. To remove these errors, a contour smoother algorithm should be employed. However, because none of the current contour-smoother algorithms has been explicitly designed to be applied to contours generated from singing, they are often unsuitable for this purpose. Therefore, this article aims to introduce a new smoother algorithm that rectifies this. The proposed smoother algorithm is compared with 15 other smoother algorithms over approximately 2700 pitch contours. Four metrics were used for the comparison. According to all the metrics, the proposed algorithm could smooth the contours more accurately than other algorithms. A distinct conclusion is that smoother algorithms should be designed according to the contour type and the result’s final applications.
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Gold DM, Rizzo JR, Lee YSC, Childs A, Hudson TE, Martone J, Matsuzawa YK, Fraser F, Ricker JH, Dai W, Selesnick I, Balcer LJ, Galetta SL, Rucker JC. King-Devick Test Performance and Cognitive Dysfunction after Concussion: A Pilot Eye Movement Study. Brain Sci 2021; 11:brainsci11121571. [PMID: 34942873 PMCID: PMC8699706 DOI: 10.3390/brainsci11121571] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 11/17/2021] [Accepted: 11/24/2021] [Indexed: 11/30/2022] Open
Abstract
(1) Background: The King-Devick (KD) rapid number naming test is sensitive for concussion diagnosis, with increased test time from baseline as the outcome measure. Eye tracking during KD performance in concussed individuals shows an association between inter-saccadic interval (ISI) (the time between saccades) prolongation and prolonged testing time. This pilot study retrospectively assesses the relation between ISI prolongation during KD testing and cognitive performance in persistently-symptomatic individuals post-concussion. (2) Results: Fourteen participants (median age 34 years; 6 women) with prior neuropsychological assessment and KD testing with eye tracking were included. KD test times (72.6 ± 20.7 s) and median ISI (379.1 ± 199.1 msec) were prolonged compared to published normative values. Greater ISI prolongation was associated with lower scores for processing speed (WAIS-IV Coding, r = 0.72, p = 0.0017), attention/working memory (Trails Making A, r = −0.65, p = 0.006) (Digit Span Forward, r = 0.57, p = −0.017) (Digit Span Backward, r= −0.55, p = 0.021) (Digit Span Total, r = −0.74, p = 0.001), and executive function (Stroop Color Word Interference, r = −0.8, p = 0.0003). (3) Conclusions: This pilot study provides preliminary evidence suggesting that cognitive dysfunction may be associated with prolonged ISI and KD test times in concussion.
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Affiliation(s)
- Doria M. Gold
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
| | - John-Ross Rizzo
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
- Department of Physical Medicine & Rehabilitation, New York University Grossman School of Medicine, New York, NY 10016, USA; (Y.S.C.L.); (A.C.); (Y.K.M.); (J.H.R.)
- Department of Mechanical & Aerospace Engineering, New York University Tandon School of Engineering, New York, NY 11201, USA
- Department of Biomedical Engineering, New York University Tandon School of Engineering, New York, NY 11201, USA
| | - Yuen Shan Christine Lee
- Department of Physical Medicine & Rehabilitation, New York University Grossman School of Medicine, New York, NY 10016, USA; (Y.S.C.L.); (A.C.); (Y.K.M.); (J.H.R.)
| | - Amanda Childs
- Department of Physical Medicine & Rehabilitation, New York University Grossman School of Medicine, New York, NY 10016, USA; (Y.S.C.L.); (A.C.); (Y.K.M.); (J.H.R.)
| | - Todd E. Hudson
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
- Department of Physical Medicine & Rehabilitation, New York University Grossman School of Medicine, New York, NY 10016, USA; (Y.S.C.L.); (A.C.); (Y.K.M.); (J.H.R.)
| | - John Martone
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
| | - Yuka K. Matsuzawa
- Department of Physical Medicine & Rehabilitation, New York University Grossman School of Medicine, New York, NY 10016, USA; (Y.S.C.L.); (A.C.); (Y.K.M.); (J.H.R.)
| | - Felicia Fraser
- Department of Physical Medicine & Rehabilitation, MetroHeath System, Cleveland, OH 44109, USA;
| | - Joseph H. Ricker
- Department of Physical Medicine & Rehabilitation, New York University Grossman School of Medicine, New York, NY 10016, USA; (Y.S.C.L.); (A.C.); (Y.K.M.); (J.H.R.)
| | - Weiwei Dai
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
- Department of Electrical & Computer Engineering, New York University Tandon School of Engineering, New York, NY 11201, USA;
| | - Ivan Selesnick
- Department of Electrical & Computer Engineering, New York University Tandon School of Engineering, New York, NY 11201, USA;
| | - Laura J. Balcer
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
- Department of Population Health, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Steven L. Galetta
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Janet C. Rucker
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA; (D.M.G.); (J.-R.R.); (T.E.H.); (J.M.); (W.D.); (L.J.B.); (S.L.G.)
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Correspondence: ; Tel.: +1-212-263-7744
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Nicolas G, Castet E, Rabier A, Kristensen E, Dojat M, Guérin-Dugué A. Neural correlates of intra-saccadic motion perception. J Vis 2021; 21:19. [PMID: 34698810 PMCID: PMC8556557 DOI: 10.1167/jov.21.11.19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Retinal motion of the visual scene is not consciously perceived during ocular saccades in normal everyday conditions. It has been suggested that extra-retinal signals actively suppress intra-saccadic motion perception to preserve stable perception of the visual world. However, using stimuli optimized to preferentially activate the M-pathway, Castet and Masson (2000) demonstrated that motion can be perceived during a saccade. Based on this psychophysical paradigm, we used electroencephalography and eye-tracking recordings to investigate the neural correlates related to the conscious perception of intra-saccadic motion. We demonstrated the effective involvement during saccades of the cortical areas V1-V2 and MT-V5, which convey motion information along the M-pathway. We also showed that individual motion perception was related to retinal temporal frequency.
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Affiliation(s)
- Gaëlle Nicolas
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000 Grenoble, France.,
| | - Eric Castet
- LPC, Laboratoire de Psychologie Cognitive (UMR 7290), Aix-Marseille Univ, CNRS, LPC, Marseille, France.,
| | - Adrien Rabier
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000 Grenoble, France.,
| | | | - Michel Dojat
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, GIN, 38000 Grenoble, France.,
| | - Anne Guérin-Dugué
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000 Grenoble, France.,
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14
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Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation. ENERGIES 2021. [DOI: 10.3390/en14175377] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Harnessing wind energy is one of the fastest-growing areas in the energy industry. However, wind power still faces challenges, such as output intermittency due to its nature and output reduction as a result of the wake effect. Moreover, the current practice uses the available renewable energy resources as a fuel-saver simply to reduce fossil-fuel consumption. This is related mainly to the inherently variable and non-dispatchable nature of renewable energy resources, which poses a threat to power system reliability and requires utilities to maintain power-balancing reserves to match the supply from renewable energy resources with the real-time demand levels. Thus, further efforts are needed to mitigate the risk that comes with integrating renewable resources into the electricity grid. Hence, an integrated strategy is being created to determine the optimal size of the hybrid wind-solar photovoltaic power systems (HWSPS) using heuristic optimization with a numerical iterative algorithm such that the output fluctuation is minimized. The research focuses on sizing the HWSPS to reduce the impact of renewable energy resource intermittency and generate the maximum output power to the grid at a constant level periodically based on the availability of the renewable energy resources. The process of determining HWSPS capacity is divided into two major steps. A genetic algorithm is used in the initial stage to identify the optimum wind farm. A numerical iterative algorithm is used in the second stage to determine the optimal combination of photovoltaic plant and battery sizes in the search space, based on the reference wind power generated by the moving average, Savitzky–Golay, Gaussian and locally weighted linear regression techniques. The proposed approach has been tested on an existing wind power project site in the southern part of the Sultanate of Oman using a real weather data. The considered land area dimensions are 2 × 2 km. The integrated tool resulted in 39 MW of wind farm, 5.305 MW of PV system, and 0.5219 MWh of BESS. Accordingly, the estimated cost of energy based on the HWSPS is 0.0165 EUR/kWh.
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15
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Rizzo JR, Hudson TE, Martone J, Dai W, Ihionu O, Chaudhry Y, Selesnick I, Balcer LJ, Galetta SL, Rucker JC. How sandbag-able are concussion sideline assessments? A close look at eye movements to uncover strategies. Brain Inj 2021; 35:426-435. [PMID: 33529094 DOI: 10.1080/02699052.2021.1878554] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Background: Sideline diagnostic tests for concussion are vulnerable to volitional poor performance ("sandbagging") on baseline assessments, motivated by desire to subvert concussion detection and potential removal from play. We investigated eye movements during sandbagging versus best effort on the King-Devick (KD) test, a rapid automatized naming (RAN) task.Methods: Participants performed KD testing during oculography following instructions to sandbag or give best effort.Results: Twenty healthy participants without concussion history were included (mean age 27 ± 8 years). Sandbagging resulted in longer test times (89.6 ± 39.2 s vs 48.2 ± 8.5 s, p < .001), longer inter-saccadic intervals (459.5 ± 125.4 ms vs 311.2 ± 79.1 ms, p < .001) and greater numbers of saccades (171.4 ± 47 vs 138 ± 24.2, p < .001) and reverse saccades (wrong direction for reading) (21.2% vs 11.3%, p < .001). Sandbagging was detectable using a logistic model with KD times as the only predictor, though more robustly detectable using eye movement metrics.Conclusions: KD sandbagging results in eye movement differences that are detectable by eye movement recordings and suggest an invalid test score. Objective eye movement recording during the KD test shows promise for distinguishing between best effort and post-injury performance, as well as for identifying sandbagging red flags.
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Affiliation(s)
- John-Ross Rizzo
- Department of Physical Medicine & Rehabilitation, NYU School of Medicine, New York, NY, United States.,Department of Neurology, NYU School of Medicine, New York, NY, United States.,Department of Mechanical & Aerospace Engineering, NYU Tandon School of Engineering, New York, NY, United States.,Department of Biomedical Engineering, NYU Tandon School of Engineering, New York, NY, United States
| | - Todd E Hudson
- Department of Physical Medicine & Rehabilitation, NYU School of Medicine, New York, NY, United States.,Department of Neurology, NYU School of Medicine, New York, NY, United States
| | - John Martone
- Department of Neurology, NYU School of Medicine, New York, NY, United States
| | - Weiwei Dai
- Department of Electrical & Computer Engineering, NYU Tandon School of Engineering, New York, NY, United States
| | - Oluchi Ihionu
- Department of Neurology, NYU School of Medicine, New York, NY, United States
| | - Yash Chaudhry
- Department of Neurology, NYU School of Medicine, New York, NY, United States
| | - Ivan Selesnick
- Department of Electrical & Computer Engineering, NYU Tandon School of Engineering, New York, NY, United States
| | - Laura J Balcer
- Department of Neurology, NYU School of Medicine, New York, NY, United States.,Department of Population Health, NYU School of Medicine, New York, NY, United States.,Department of Ophthalmology, NYU School of Medicine, New York, NY, United States
| | - Steven L Galetta
- Department of Neurology, NYU School of Medicine, New York, NY, United States.,Department of Ophthalmology, NYU School of Medicine, New York, NY, United States
| | - Janet C Rucker
- Department of Neurology, NYU School of Medicine, New York, NY, United States.,Department of Ophthalmology, NYU School of Medicine, New York, NY, United States
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16
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Cutsuridis V, Jiang S, Dunn MJ, Rosser A, Brawn J, Erichsen JT. Neural modeling of antisaccade performance of healthy controls and early Huntington's disease patients. CHAOS (WOODBURY, N.Y.) 2021; 31:013121. [PMID: 33754760 DOI: 10.1063/5.0021584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 12/14/2020] [Indexed: 06/12/2023]
Abstract
Huntington's disease (HD), a genetically determined neurodegenerative disease, is positively correlated with eye movement abnormalities in decision making. The antisaccade conflict paradigm has been widely used to study response inhibition in eye movements, and reliable performance deficits in HD subjects have been observed, including a greater number and timing of direction errors. We recorded the error rates and response latencies of early HD patients and healthy age-matched controls performing the mirror antisaccade task. HD participants displayed slower and more variable antisaccade latencies and increased error rates relative to healthy controls. A competitive accumulator-to-threshold neural model was then employed to quantitatively simulate the controls' and patients' reaction latencies and error rates and uncover the mechanisms giving rise to the observed HD antisaccade deficits. Our simulations showed that (1) a more gradual and noisy rate of accumulation of evidence by HD patients is responsible for the observed prolonged and more variable antisaccade latencies in early HD; (2) the confidence level of early HD patients making a decision is unaffected by the disease; and (3) the antisaccade performance of healthy controls and early HD patients is the end product of a neural lateral competition (inhibition) between a correct and an erroneous decision process, and not the end product of a third top-down stop signal suppressing the erroneous decision process as many have speculated.
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Affiliation(s)
- Vassilis Cutsuridis
- School of Computer Science, University of Lincoln, Lincoln LN6 7TS, United Kingdom
| | - Shouyong Jiang
- School of Computer Science, University of Lincoln, Lincoln LN6 7TS, United Kingdom
| | - Matt J Dunn
- School of Optometry and Vision Sciences, Cardiff University, Cardiff CF24 4HQ, United Kingdom
| | - Anne Rosser
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff CF14 4XN, United Kingdom
| | - James Brawn
- School of Optometry and Vision Sciences, Cardiff University, Cardiff CF24 4HQ, United Kingdom
| | - Jonathan T Erichsen
- School of Optometry and Vision Sciences, Cardiff University, Cardiff CF24 4HQ, United Kingdom
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17
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Abstract
Infantile nystagmus (IN) describes a regular, repetitive movement of the eyes. A characteristic feature of each cycle of the IN eye movement waveform is a period in which the eyes are moving at minimal velocity. This so-called “foveation” period has long been considered the basis for the best vision in individuals with IN. In recent years, the technology for measuring eye movements has improved considerably, but there remains the challenge of calibrating the direction of gaze in tracking systems when the eyes are continuously moving. Identifying portions of the nystagmus waveform suitable for calibration typically involves time-consuming manual selection of the foveation periods from the eye trace. Without an accurate calibration, the exact parameters of the waveform cannot be determined. In this study, we present an automated method for segmenting IN waveforms with the purpose of determining the foveation positions to be used for calibration of an eye tracker. On average, the “point of regard” was found to be within 0.21° of that determined by hand-marking by an expert observer. This method enables rapid clinical quantification of waveforms and the possibility of gaze-contingent research paradigms being performed with this patient group.
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