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Objective To establish a hybrid deep learning lung sound classification model based on convolutional neural network(CNN)-long short-term memory(LSTM)for electronic auscultation.Methods Wavelet transform was used to extract features from the dataset,transforming lung sound signals into energy entropy,peak value and other features.On this basis,a classification model based on hybrid algorithm incorporating CNN and LSTM neural network was constructed.The features extracted by wavelet transform were input into CNN module to obtain the spatial features of the data,and then the temporal features were detected through LSTM module.The fusion of the two types of features enabled the classification of lung sounds through the model,thereby assisting in the diagnosis of pulmonary diseases.Results The accuracy rate and F1 score of CNN-LSTM hybrid model were significantly higher than those of other single models,reaching 0.948 and 0.950.Conclusion The proposed CNN-LSTM hybrid model demonstrates higher accuracy and more precise classification,showcasing broad potential application value in intelligent auscultation.
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Aiming at the non-stationarity and temporal characteristics of variable-length electrocardiogram(ECG)signals,an arrhythmia identification algorithm is proposed based on continuous wavelet transform and higher-order statistics.Considering the varying number of data points for each sample in variable-length ECG signals,the RR interval interpolation method is employed for data preprocessing,and the signal is decomposed into different time-frequency components using continuous wavelet transform,which enables the network to better extract both temporal and frequency features from the ECG signals.Regarding the issue of insufficient utilization of temporal information,a temporal mining module is introduced based on higher-order statistics and long short-term memory network to capture and learn long-term dependencies in the ECG signals,thereby facilitating the identification and understanding of specific arrhythmia categories.Extensive experiments conducted on the publicly available MIT-BIH ECG database validate the effectiveness and superiority of the proposed method.
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This study evaluated selected structural and physical properties, such as degree of conversion (DC), Vickers hardness (VHN), and compression strength (CS), of three new dual-cure bulk-fill resin-based composites (RBCs; ACTIVA, HyperFIL, and Fill-Up) and compared them to those of a conventional RBC (Filtek Z250) at three clinically relevant depths. Samples (n=180) were prepared in three depths (2,4, and 6mm). Fourier-transform infrared spectroscopy (FTIR) analysis and VHN and CS tests were performed. The DC value was calculated by considering the relative change in the aliphatic C=C peaks. The fractured surfaces of representative samples were characterized using scanning electron microscopy (SEM). Data were statistically evaluated using two-way analysis of variance and post hoc Bonferroni tests (p<0.05). According to the VHN results, Filtek Z250 showed the highest bottom/top hardness ratio (97.94±1.01) at 2mm thickness and ACTIVA showed the lowest bottom/top hardness ratio (43.48±5.64) at 6mm thickness (p<0.001). According to the FTIR results, the DC decreased with increasing thickness in all materials (p<0.05). Filtek Z250 showed the highest (301±12.4 MPa) and ACTIVA exhibited the lowest (232±17.2 MPa) CS values at 2mm thickness (p<0.05). The lowest CS values were obtained for ACTIVA, and the highest values were obtained for Filtek Z250 for samples with thicknesses of 4 and 6mm, respectively (p<0.05). The structural features of restorative composites, such as the resin chemistry and filler type and content, and the operational parameters (i.e., material thickness and curing conditions) strongly affect crosslinking reactions and thus the DC, VHN, and CS values.
Este estudio evaluó propiedades físicas y estructurales, como el grado de conversión (DC), la dureza Vickers (VHN) y la resistencia a la compresión (CS), de tres nuevos compósitos a base de resina de curado dual tipo bulk (RBC; ACTIVA , HyperFIL y Fill-Up) y los comparó con los de una resina compuesta convencional (Filtek Z250) en tres profundidades clínicamente relevantes. Se prepararon muestras (n=180) en tres profundidades (2,4 y 6mm). Se realizaron análisis de espectroscopia infrarroja por transformada de Fourier (FTIR) y pruebas VHN y CS. El valor de DC se calculó considerando el cambio relativo en los picos alifáticos C=C. Las superficies fracturadas de muestras representativas se caracterizaron mediante microscopía electrónica de barrido (MEB). Los datos se evaluaron estadísticamente mediante análisis de varianza de dos vías y pruebas post hoc de Bonferroni (p<0,05). De acuerdo con los resultados de VHN, Filtek Z250 mostró la relación de dureza inferior/superior más alta (97,94±1,01) con un espesor de 2mm y ACTIVA mostró la relación de dureza inferior/superior más baja (43,48±5,64) con un espesor de 6mm (p<0,001). De acuerdo con los resultados de FTIR, la DC disminuyó al aumentar el espesor en todos los materiales (p<0,05). Filtek Z250 mostró los valores de CS más altos (301±12,4 MPa) y ACTIVA los más bajos (232±17,2 MPa) a 2mm de espesor (p<0,05). Los valores más bajos de CS se obtuvieron para ACTIVA y los valores más altos para Filtek Z250 para muestras con espesores de 4 y 6mm, respectivamente (p<0,05). Las características estructurales de las resinas compuestas de restauración, como la química; además del tipo y contenido del relleno, y los parámetros operativos (es decir, el espesor del material y las condiciones de curado) afectan en gran medida las reacciones de interacción química y, por lo tanto, los valores de DC, VHN y CS.
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Microscopy, Electron, Scanning , Composite Resins/analysis , Compressive StrengthABSTRACT
Aims: This study evaluated the physical, chemical and rheological properties of exopolysaccharides (EPSs) produced by Lactic Acid Bacteria (LAB) isolated from palm wine. Materials and Methods: EPSs from palm wine LAB strains were produced on 6% sucrose broth, purified and freeze-dried prior to analyses. Molecular weights (MW), rheological and structural composition (functional groups) of the EPSs were determined using standard methods and Fourier transform infrared spectroscopy (FTIR). Results: The average MW of the EPSs ranged from 2.02×106 to 6.53×106 Da while the flow index (n) values ranged from 0.03-3.13 at 0.2%, 0.06-1.51 at 0.4%, 0.38 - 1.85 at 0.6%, 0.14 - 2.26 at 0.8% and 0.55 - 6.42 at 1% concentrations at elevated temperatures for EPS solutions from the ten LAB species. The FTIR spectrum revealed prominent peaks of various groups of OH (3420 cm-1) and CH3 bending (2090 cm-1) in all the EPSs corresponding to both hydroxyl and amine groups, and aliphatic C-H bonds, respectively. EPS synthesized by Leuconostoc lactis, Lactococcus lactis subsp lactis and Lactiplantibacillus plantarum showed weak absorption peaks (1148 – 1145 cm-1) indicating the C-O-C and C-O bonds, while absorption peaks of Lactobacillus lactis, Lactobacillus acidophilus and Lactiplantibacillus plantarum (1267 – 1253 cm-1) indicated O- acetyl ester and other non-sugar components. Conclusions: The FTIR spectra, rheological properties and molecular weight of EPSs synthesized by the ten LAB strains indicated potentials that could be exploited in different industrial applications, and as stabilizers in food industries
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OBJECTIVES@#Fourier transform infrared spectroscopy (FTIR) was used to analyze myocardial infarction tissues at different stages of pathological change to achieve the forensic pathology diagnosis of acute and old myocardial infarction.@*METHODS@#FTIR spectra data of early ischemic myocardium, necrotic myocardium, and myocardial fibrous tissue in the left ventricular anterior wall of the sudden death group of atherosclerotic heart disease and the myocardium of the normal control group were collected using hematoxylin-eosin (HE) and immunohistochemistry (IHC) staining as a reference, and the data were analyzed using multivariate statistical analysis.@*RESULTS@#The mean normalized spectra of control myocardium, early ischemic myocardium and necrotic myocardium were relatively similar, but the mean second derivative spectra were significantly different. The peak intensity of secondary structure of proteins in early ischemic myocardium was significantly higher than in other types of myocardium, and the peak intensity of the α-helix in necrotic myocardium was the lowest. The peaks of amide Ⅰ and amide Ⅱ in the mean normalized spectra of myocardial fibrous tissue significantly shifted towards higher wave numbers, the peak intensities of amide Ⅱ and amide Ⅲ were higher than those of other types of myocardium, and the peak intensities at 1 338, 1 284, 1 238 and 1 204 cm-1 in the mean second derivative spectra were significantly enhanced. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) showed that FTIR could distinguish different types of myocardium.@*CONCLUSIONS@#FTIR technique has the potential to diagnose acute and old myocardial infarction, and provides a new basis for the analysis of the causes of sudden cardiac death.
Subject(s)
Humans , Amides , Death, Sudden, Cardiac , Myocardial Infarction/pathology , Myocardium/pathology , Spectroscopy, Fourier Transform Infrared/methods , Forensic PathologyABSTRACT
OBJECTIVE@#To propose a semi-supervised epileptic seizure prediction model (ST-WGAN-GP-Bi-LSTM) to enhance the prediction performance by improving time-frequency analysis of electroencephalogram (EEG) signals, enhancing the stability of the unsupervised feature learning model and improving the design of back-end classifier.@*METHODS@#Stockwell transform (ST) of the epileptic EEG signals was performed to locate the time-frequency information by adaptive adjustment of the resolution and retaining the absolute phase to obtain the time-frequency inputs. When there was no overlap between the generated data distribution and the real EEG data distribution, to avoid failure of feature learning due to a constant JS divergence, Wasserstein GAN was used as a feature learning model, and the cost function based on EM distance and gradient penalty strategy was adopted to constrain the unsupervised training process to allow the generation of a high-order feature extractor. A temporal prediction model was finally constructed based on a bi-directional long short term memory network (Bi-LSTM), and the classification performance was improved by obtaining the temporal correlation between high-order time-frequency features. The CHB-MIT scalp EEG dataset was used to validate the proposed patient-specific seizure prediction method.@*RESULTS@#The AUC, sensitivity, and specificity of the proposed method reached 90.40%, 83.62%, and 86.69%, respectively. Compared with the existing semi-supervised methods, the propose method improved the original performance by 17.77%, 15.41%, and 53.66%. The performance of this method was comparable to that of a supervised prediction model based on CNN.@*CONCLUSION@#The utilization of ST, WGAN-GP, and Bi-LSTM effectively improves the prediction performance of the semi-supervised deep learning model, which can be used for optimization of unsupervised feature extraction in epileptic seizure prediction.
Subject(s)
Humans , Memory, Short-Term , Seizures/diagnosis , ElectroencephalographyABSTRACT
Objective: This study aimed to evaluate the properties of suckermouth catfish bone extract, which allows it to be adopted as a raw material for bone graft following its graft in an artificial defect of a rat model. Material and Methods: Hydroxyapatite (HA) from suckermouth catfish bone extract was characterized using Fourier-transform infrared spectroscopy (FTIR), and its toxicity was evaluated by Brine Shrimp Lethality Test (BSLT). This material was grafted on artificial defects in rats' femoral bones, which were observed immunologically by Enzyme-linked immunosorbent assay (ELISA) after one week and four weeks, and radiographically in the second week, and histologically in the second and fourth weeks. Results: FTIR shows that this material consists of phosphate, hydroxyl, and carbonate groups, while the BSLT results show that this material is not toxic. Observations by ELISA showed an increase in the expression of Tumor necrosis factor alpha (TNF-α) in defects with HA in the fourth week. Radiographically the defect did not show closure in the second week. In contrast, histological analysis showed a better bone healing process in the defect, which was applied with the HA of the suckermouth catfish bone. Conclusion: The HA extracted from the suckermouth catfish bone has beneficial properties as an alternative to bone graft raw material and, more investigated needed to support this biomaterial to be used in the treatment of bone loss (AU)
Objetivo: Avaliar as propriedades do extrato de osso de bagre, que permitem sua adoção como material bruto para enxerto ósseo, em um defeito ósseo artificial em ratos. Material e Métodos: A hidroxiapatita (HA) do extrato de osso de bagre foi caracterizada usando espectroscopia infravermelha por transformada de Fourier (FTIR), e sua toxicidade foi avaliada pelo Teste de Letalidade do Camarão de Sal (BSLT). Esse material foi enxertado em defeitos artificiais nos ossos femorais de ratos. Análise imunológica por meio do ensaio imunoenzimático (ELISA) foi realizada uma e quatro semanas após a colocação dos enxertos. Análises radiográficas foram feitas na segunda semana e histológica na segunda e quarta semanas. Resultados: A FTIR mostrou que esse material é composto por grupos de fosfato, hidroxila e carbonato, enquanto os resultados do BSLT mostraram que esse material não é tóxico. As observações pelo ELISA mostraram um aumento na expressão do fator de necrose tumoral alfa (TNF-α) nos defeitos com HA na quarta semana. Radiograficamente, o defeito não apresentou fechamento na segunda semana. Em contraste, a análise histológica mostrou um melhor processo de cicatrização óssea no defeito que foi aplicado com a HA do osso de bagre. Conclusão: A HA extraída do osso de bagre possui propriedades benéficas como alternativa ao material bruto para enxerto ósseo, sendo necessárias mais investigações para apoiar esse biomaterial a ser usado no tratamento da perda óssea.(AU)
Subject(s)
Animals , Rats , Wound Healing , Bone Transplantation , Spectroscopy, Fourier Transform Infrared , DurapatiteABSTRACT
Objective:To analyze the clinically acceptable and reproducible bladder and rectum volumes of prostate cancer patients during radiotherapy under bladder and bowel preparation, aiming to provide quantitative indicators for bowel and bladder preparation before and after radiotherapy.Methods:Clinical data of 275 prostate cancer patients with strict bladder and bowel preparation and completion of whole course radical radiotherapy at Sun Yat-sen University Cancer Center from April 2015 to December 2020 were retrospectively analyzed. Patients were scanned with cone beam CT (CBCT) before each treatment and the setup error was recorded. Sixty-six patients were selected by simple random sampling and the bladder and rectum on daily CBCT was outlined using MIM software. The relationship between the ratio of daily bladder or rectum volume to the planned bladder or rectum volume (relative value of volume) and setup error was analyzed. Quantitative data were expressed as mean±SD. Normally distributed data were analyzed by paired t-test while non-normally distributed data were assessed by Kruskal-Wallis test.Results:The bladder and rectum volume on planning CT were (370.87±110.04) ml and (59.94±25.07) ml of 275 patients. The bladder and rectum volumes on planning CT were (357.51±107.38) ml and (65.28±35.37) ml respectively of the 66 selected patients with 1611 sets of CBCT images. And the bladder and rectum volumes on daily CBCT were (258.96±120.23) ml and (59.95 ± 30.40) ml. The bladder volume of patients was decreased by 3.59 ml per day on average during the treatment and 0.37 ml for the rectum volume. According to the bladder volume on planning CT, all patients were divided into three groups: <250 ml, 250-450 ml and >450 ml groups. The relative value of volume in the 250-450 ml group during the course of radiotherapy was the smallest. And the setup error in the superior and inferior (SI) direction was (0.28±0.24) cm and (0.19±0.17) cm in the left and right (LR) direction, significantly lower than those in the other two groups (both P≤0.027). According to the rectum volume on planning CT, all patients were divided into four groups: <50 ml, 50-<80 ml, 80-120 ml and >120 ml groups. The <50 ml group had the smallest relative value of volume during radiotherapy, and the setup error in the SI direction was (0.26±0.22) cm and (0.24±0.22) cm in the anterior and posterior (AP) direction, significantly smaller than those in the other groups (both P≤0.003). The setup errors in the SI, LR, AP directions of the enrolled 66 patients were (0.30±0.25) cm, (0.20±0.18) cm and (0.28±0.27) cm, respectively. Among them, the relative value of bladder volume in the AP direction was (0.73±0.37) in the setup error <0.3 cm group, which was statistically different from those in the setup error 0.3-0.5 cm and >0.5 cm groups (both P<0.05). Conclusion:Under the bladder and bowel preparation before planning CT, the appropriate bladder and rectum volumes are in the range of 250-450 ml and <50 ml, which yields higher reproducibility and smaller setup error.
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Objective To compare the principles and performance of three Hough transform algorithms(standard Hough transform,gradient based Hough transform,and random Hough transform)in order to establish a suitable control basis for precise and rapid recognition of targets and acquisition of target center coordinates for craniocerebral puncture robots.Methods A simulation environment in MATLAB software was built to study and analyze image feature recognition,filtering,edge detection,cumulative voting and other processing engineering.Contour recognition and fitting of target circles were achieved in multiple scenarios before their center coordinates were obtained.The recognition and fitting performance of these algorithms was quantitatively compared.Finally,a better detection algorithm based on the actual environment of the craniocerebral puncture robot was determined.Results The standard Hough transform algorithm had the largest error between the mark circle and the target circle,and the running time of this algorithm was the longest due to large computation.The detection speed of the random Hough transform algorithm was lower than that of the gradient-based Hough transform algorithm,but the fitting accuracy was slightly better than that of the standard Hough transform algorithm.The speed and accuracy of circle fitting based on the gradient Hough transform algorithm had significant advantages over the other two.Conclusion The gradient based Hough transform algorithm is more suitable for obtaining the target center coordinates of the craniocerebral puncture robot system.
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The existing automatic sleep staging algorithms have the problems of too many model parameters and long training time, which in turn results in poor sleep staging efficiency. Using a single channel electroencephalogram (EEG) signal, this paper proposed an automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning (TL-SDResNet). Firstly, a total of 30 single-channel (Fpz-Cz) EEG signals from 16 individuals were selected, and after preserving the effective sleep segments, the raw EEG signals were pre-processed using Butterworth filter and continuous wavelet transform to obtain two-dimensional images containing its time-frequency joint features as the input data for the staging model. Then, a ResNet50 pre-trained model trained on a publicly available dataset, the sleep database extension stored in European data format (Sleep-EDFx) was constructed, using a stochastic depth strategy and modifying the output layer to optimize the model structure. Finally, transfer learning was applied to the human sleep process throughout the night. The algorithm in this paper achieved a model staging accuracy of 87.95% after conducting several experiments. Experiments show that TL-SDResNet50 can accomplish fast training of a small amount of EEG data, and the overall effect is better than other staging algorithms and classical algorithms in recent years, which has certain practical value.
Subject(s)
Humans , Sleep Stages , Algorithms , Sleep , Wavelet Analysis , Electroencephalography/methods , Machine LearningABSTRACT
Mannitol-calcium chloride metal organic framework (MOF) cocrystal significantly improved the tabletability of β-mannitol and could be developed as a new tablet filler. However, mannitol monomer was found in the product during the scale-up production of the excipient, which significantly affected the functional properties of the excipient. In this study, we intend to quantify the multi-component eutectic system of mannitol-calcium chloride. In this experiment, the MOF cocrystal excipient mannitol-calcium chloride cocrystal was used as the model compound, and infrared spectrum was collected. Based on partial least squares regression (PLSR) method, the abnormal bands were removed and the spectrum was preprocessed by normalization. The quantitative correction model of mannitol-calcium chloride MOF cocrystal content in cocrystal excipients was established and compared by two different variable screening methods, genetic algorithm (GA) and competitive adaptive reweighting algorithm (CARS). Two different variable screening methods, GA method and CARS method, were used to screen out 160 and 14 variables, respectively. The mannitol-calcium chloride cocrystal model established by CARS-PLSR method had the best performance, and the average relative error (MRE) and corrected root mean square error (RMSEC) of the model were 0.008 8 and 0.892 5, respectively, the determination coefficient (R2) of the model was increased from 0.978 3 to 0.994 4. The quantitative method of eutectic system established in this study has high prediction accuracy, fast detection speed and good stability, which is of great significance for optimizing the preparation process conditions and quality control methods of such eutectic excipients.
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The study investigates the therapeutic potential of the Citrus aurantium var. amara essential oil extracted from the blossoms of the bitter orange plant by examining its chemical composition, thermal stability, and potency against infectious disease-causing pathogens. Initially, the volatile components of the essential oil were evaluated by obtaining a chromatographic fingerprint using HPTLC and FTIR spectrum identification. Furthermore, a thermal profile of the essential oil was obtained using the thermogravimetric-differential thermal analysis and differential scanning calorimetric analysis. A predetermined set of antibiotic-resistant microorganisms were used to examine the antibacterial activity of the essential oil. Lastly, its anti-inflammatory activity was assessed using the albumin denaturation assay. The research concluded that the Citrus aurantium var. Amara essential oil exhibits potential therapeutic characteristics which can be further explored through in vivo studies.
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Introduction. Laryngeal disorders are characterized by a change in the vibratory pattern of the vocal folds. This disorder may have an organic origin described by anatomical fold modification, or a functional origin caused by vocal abuse or misuse. The most common diagnostic methods are performed by invasive imaging features that cause patient discomfort. In addition, mild voice deviations do not stop the in-dividual from using their voices, which makes it difficult to identify the problem and increases the possibility of complications. Aim. For those reasons, the goal of the present paper was to develop a noninvasive alternative for the identification of voices with a mild degree of vocal deviation ap-plying the Wavelet Packet Transform (WPT) and Multilayer Perceptron (MLP), an Artificial Neural Network (ANN). Methods. A dataset of 74 audio files were used. Shannon energy and entropy mea-sures were extracted using the Daubechies 2 and Symlet 2 families and then the processing step was performed with the MLP ANN. Results. The Symlet 2 family was more efficient in its generalization, obtaining 99.75% and 99.56% accuracy by using Shannon energy and entropy measures, re-spectively. The Daubechies 2 family, however, obtained lower accuracy rates: 91.17% and 70.01%, respectively. Conclusion. The combination of WPT and MLP presented high accuracy for the identification of voices with a mild degree of vocal deviation
ntroducción. Los trastornos laríngeos se caracterizan por un cambio en el patrón vibratorio de los pliegues vocales. Este trastorno puede tener un origen orgánico, descrito como la modificación anatómica de los pliegues vocales, o de origen fun-cional, provocado por abuso o mal uso de la voz. Los métodos de diagnóstico más comunes se realizan mediante procedimientos invasivos que causan malestar al pa-ciente. Además, los desvíos vocales de grado leve no impiden que el individuo utilice la voz, lo que dificulta la identificación del problema y aumenta la posibilidad de complicaciones futuras.Objetivo. Por esas razones, el objetivo de esta investigación es desarrollar una he-rramienta alternativa, no invasiva para la identificación de voces con grado leve de desvío vocal aplicando Transformada Wavelet Packet (WPT) y la red neuronal artifi-cial del tipo Perceptrón Mutlicapa (PMC). Métodos. Fue utilizado un banco de datos con 78 voces. Fueron extraídas las me-didas de energía y entropía de Shannon usando las familias Daubechies 2 y Symlet 2 para después aplicar la red neuronal PMC. Resultados. La familia Symlet 2 fue más eficiente en su generalización, obteniendo un 99.75% y un 99.56% de precisión mediante el uso de medidas de energía y en-tropía de Shannon, respectivamente. La familia Daubechies 2, sin embargo, obtuvo menores índices de precisión: 91.17% y 70.01%, respectivamente. Conclusión. La combinación de WPT y PMC presentó alta precisión para la iden-tificación de voces con grado leve de desvío vocal
Subject(s)
Humans , Vocal Cords , Aphonia/diagnosis , Voice Disorders , Patients , Voice , Aphonia/physiopathology , Larynx/abnormalitiesABSTRACT
OBJECTIVES@#To establish a method to identify unknown sample based on the combined use of Fourier transform infrared spectroscopy (FTIR), gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOF-MS), ultra-high performance liquid chromatography-linear ion trap quadrupole-orbitrap mass spectrometry (UPLC-LTQ-Orbitrap MS) and 1H-nuclear magnetic resonance spectroscopy (1H-NMR) technique.@*METHODS@#The unknown sample was directly analyzed by FTIR. The unknown sample was dissolved in methanol solution containing internal standard SKF525A and the supernatant was detected by GC-QTOF-MS and UPLC-LTQ-Orbitrap MS. The unknown sample was dissolved in methanol-d4 solution for structural analysis of 1H-NMR.@*RESULTS@#The characteristic absorption peaks of FTIR spectra obtained from unknown sample were 1 682 (C=O bond), 1 503, 1 488, 1 436, 1 363, 1 256, 1 092, 1 035, 935, 840 and 800 cm-1, the characteristic fragment ions (m/z) of GC-QTOF-MS were 86.096 4 (base peak), 58.065 1, 149.023 5, 121.028 6 and 65.038 6, the accurate mass [M+H]+ detected by UPLC-LTQ-Orbitrap MS was 236.127 7. The sample was identified as synthetic cathinone new psychoactive substance Eutylone by 1H-NMR.@*CONCLUSIONS@#The method established in this study can be used for structural confirmation of Eutylone.
Subject(s)
Methanol , Chromatography, High Pressure Liquid/methods , Mass Spectrometry , Gas Chromatography-Mass Spectrometry/methods , Magnetic Resonance SpectroscopyABSTRACT
To solve the problem of real-time detection and removal of EEG signal noise in anesthesia depth monitoring, we proposed an adaptive EEG signal noise detection and removal method. This method uses discrete wavelet transform to extract the low-frequency energy and high-frequency energy of a segment of EEG signals, and sets two sets of thresholds for the low-frequency band and high-frequency band of the EEG signal. These two sets of thresholds can be updated adaptively according to the energy situation of the most recent EEG signal. Finally, we judge the level of signal interference according to the range of low-frequency energy and high-frequency energy, and perform corresponding denoising processing. The results show that the method can more accurately detect and remove the noise interference in the EEG signal, and improve the stability of the calculated characteristic parameters.
Subject(s)
Algorithms , Electroencephalography , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio , Wavelet AnalysisABSTRACT
Objective:To distinguish the differences between Olibanum and Myrrha by using modern analytical methods such as Differential Scanning Calorimeter (DSC) and Fourier Transform InfraRed (FT-IR). Methods:By collecting Olibanum and Myrrha in different growing areas and different processed prosecures, this paper to analizes the influence of temperature increase and its speed , as well as the particle size on the DSC experiment. The DSC method was used to perform a differential thermal map of Olibanum and Myrrha scanning and analysis; FT-IR was used to scan and analyze 20 batches of Olibanum and Myrrha. Results:TThe results of DSC analysis showed that the DSC experimental condition ranged between 30-600 ℃; the speed of temperature increase was 30 ℃/min; the particle size was 100 mesh. The DSC spectra of of Olibanum and Myrrha were significantly different. Only the processed products of frankincense had endothermic peak near 297 ℃, and there was no characteristic peak in this temperature range. Their exothermic peaks are close at 326 ℃, but their enthalpy values are quite different. The position of endothermic peak near 100 ℃ is close to the size of peak shape. FT-IR test showed that the absorption peaks of Olibanum and Myrrha at wave numbers 2 925, 1 710, 1 454, 1 371, 1 242, 1 029 cm -1 appeared, and the positions of strong peaks were also similar. The intensity of the characteristic peak of Myrrha wave number 1 029 cm -1 is greater than that of Olibanum. Conclusion:The DSC spectra of Olibanum and Myrrha are significantly different, and the difference between the two FT-IR spectra is small. Differential scanning Calorimetry is an effective, fast, and simple way to identify resinous Chinese medicinal materials, and is worthy of further popularization.
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A rapid and sensitive method for analyzing trace β-blockers in complex biological samples,which involved magnetic solid-phase extraction(MSPE)coupled with Fourier transform ion cyclotron reso-nance mass spectrometry(FTICR-MS),was developed.Novel nanosilver-functionalized magnetic nano-particles with an interlayer of poly(3,4-dihydroxyphenylalanine)(polyDOPA@Ag-MNPs)were synthesized and used as MSPE adsorbents to extract trace β-blockers from biological samples.After extraction,the analytes loaded on the polyDOPA@Ag-MNPs were desorbed using an organic solvent and analyzed by FTICR-MS.The method was rapid and sensitive,with a total detection procedure of less than 10 min as well as limits of detection and quantification in the ranges of 3.5-6.8 pg/mL and 11.7-22.8 pg/mL,respectively.The accuracy of the method was also desirable,with recoveries ranging from 80.9%to 91.0%following the detection of analytes in human blood samples.All the experimental results demonstrated that the developed MSPE-FTICR-MS method was suitable for the rapid and sensitive analysis of trace β-blockers in complex biological samples.
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OBJECTIVE: The aim of this study was to use a wavelet technique to determine whether the number of suicides is similar between developed and emerging countries. METHODS: Annual data were obtained from World Health Organization (WHO) reports from 1986 to 2015. Discrete nondecimated wavelet transform was used for the analysis, and the Daubechies wavelet function was applied with five-level decomposition. Regarding clustering, energy (variance) was used to analyze the clusters and visualize the clustering process. We constructed a dendrogram using the Mahalanobis distance. The number of groups was set using a specific function in the R program. RESULTS: The cluster analysis verified the formation of four groups as follows: Japan, the United States and Brazil were distinct and isolated groups, and other countries (Austria, Belgium, Chile, Israel, Mexico, Italy and the Netherlands) constituted a single group. CONCLUSION: The methods utilized in this paper enabled a detailed verification of countries with similar behaviors despite very distinct socioeconomic, geographic and climate characteristics.
OBJETIVO: Verificar se existe relação de similaridade entre o número de suicídio em países desenvolvidos e emergentes usando a técnica de ondaletas. MÉTODOS: Os dados anuais foram obtidos a partir do relatório da Organização Mundial da Saúde (OMS), no período de 1986 a 2015. Para análise, foi empregada a transformada discreta não decimada de ondaleta (NDWT), a função ondaleta aplicada foi a Daubechies com cinco níveis de decomposição. Com relação ao agrupamento, utilizou-se a energia (variância) para analisar os clusters e, para a visualização do processo de clusterização, trabalhamos com o dendograma, no qual se empregou a distância de Mahalanobis. A quantidade de grupos foi definida por meio da função NbCluster. RESULTADOS: A partir da análise de cluster, verificou-se a formação de quatros grupos. No qual, Japão e Estados Unidos e Brasil localizam-se em grupos distintos e isolados. E os demais países (Áustria, Bélgica, Chile, Israel, México, Itália e Holanda) em um único grupo. CONCLUSÃO: Utilizando esse método, foi possível verificar com mais detalhes quais países apresentaram comportamentos semelhantes, mesmo apresentando características bem distintas entre si, tanto socioeconômica, geográfica e climática.
Subject(s)
Humans , Male , Female , Adolescent , Adult , Aged , Suicide/psychology , Suicide/statistics & numerical data , Developed Countries , Developing Countries , Wavelet Analysis , Time Series Studies , Risk Factors , Mental Disorders/epidemiologyABSTRACT
ABSTRACT Introduction: Currently there is a lack of clarity around the use of Fourier transform infrared (FT-IR) spectroscopy to analyze the effect of creatine (Cr) supplementation on the secondary structures of skeletal muscle tissue protein subjected to exercise. Objective: The objective of this study was to evaluate the spectral characteristics of the tibialis anterior muscle in rats subjected to exercise in a pool and to Cr supplementation. Methods: Experiment 1. First, an experiment was conducted to ensure that FT-IR would be able to detect change in the secondary structures of skeletal muscle tissue protein in the group of sedentary rats (SED) and in the group of rats that received creatine supplementation (CRE). Experiment 2. Next, the effect of physical exercise on the spectral characteristics of muscle tissue, especially when compared to the groups without exercise practice, was examined. Results: It was possible to verify that the peaks centered on 1658 cm-1 (amide I) and 1546 cm-1 (amide II) are characteristic spectra and indicated as markers of protein content. Conclusion: Thus, FT-IR spectroscopy proved to be able to monitor changes in secondary structures of skeletal muscle protein in both animals that received supplements and in those subjected to exercise and both cases reconciled. Furthermore, the FT-IR technique proved to be a viable method for the nondestructive evaluation of skeletal muscle protein structures. Level of evidence II, Investigation of treatment results.
RESUMEN Introducción: Actualmente, no hay claridad en lo que se refiere al uso de la técnica de espectroscopia de Infrarrojo con transformada de Fourier (FT-IR) para análisis del efecto de la suplementación de creatina (Cr) sobre las estructuras secundarias de la proteína del tejido muscular esquelético sometido a ejercicio. Objetivo: El objetivo de este estudio fue evaluar las características espectrales del músculo tibial anterior de ratones sometidos a ejercicio en piscina y a la suplementación con Cr. Métodos: Experimento 1. En primer lugar, fue realizada una experiencia para asegurar que la FT-IR sería capaz de detectar la variación en las estructuras secundarias de la proteína del tejido muscular esquelético en el grupo de ratones sedentarios (SED) y el grupo de ratones que sólo recibieron suplemento de creatina (CRE). Experimento 2. A continuación, fue examinado el efecto del ejercicio físico sobre las características espectrales del tejido muscular, especialmente cuando comparado con los grupos sin práctica de ejercicio. Resultados: Fue posible verificar que los picos centrados en 1658 cm−1 (amida I) y 1546 cm−1 (amida II) son espectros característicos e indicados como marcadores del tenor proteico. Conclusión: Siendo así, la técnica de espectroscopia de FT-IR mostró ser capaz de monitorizar las variaciones en las estructuras secundarias de la proteína del tejido muscular esquelético, tanto en animales que recibieron suplementos, como en los que fueron sometidos a ejercicio y ambos casos conciliados. Además, la técnica FT-IR probó ser un método viable para la evaluación no destructiva de las estructuras proteicas en el músculo esquelético. Nivel de evidencia II, Investigación de los resultados del tratamiento.
RESUMO Introdução: Atualmente, não há clareza no que diz respeito ao uso da técnica de espectroscopia de infravermelho com transformada de Fourier (FT-IR) para análise do efeito da suplementação de creatina (Cr) sobre as estruturas secundárias da proteína do tecido muscular esquelético submetido a exercício. Objetivo: O objetivo deste estudo foi avaliar as características espectrais do músculo tibial anterior de ratos submetidos a exercício em piscina e à suplementação com Cr. Métodos: Experimento 1. Em primeiro lugar, foi realizada uma experiência para assegurar que a FT-IR seria capaz de detectar a variação nas estruturas secundárias da proteína do tecido muscular esquelético no grupo de ratos sedentários (SED) e no grupo de ratos que só receberam suplemento de creatina (CRE). Experimento 2. Em seguida, foi examinado o efeito do exercício físico sobre as características espectrais do tecido muscular, especialmente quando comparado com os grupos sem prática de exercício. Resultados: Foi possível verificar que os picos centrados em 1658 cm−1(amida I) e 1546 cm−1(amida II) são espectros característicos e indicados como marcadores do teor proteico. Conclusão: Assim sendo, a técnica de espectroscopia de FT-IR mostrou ser capaz de monitorar as variações nas estruturas secundárias da proteína do tecido muscular esquelético tanto em animais que receberam suplementos, quanto nos que foram submetidos a exercício e ambos os casos conciliados. Além disso, a técnica FT-IR provou ser um método viável para a avaliação não destrutiva de estruturas proteicas no músculo esquelético. Nível de evidência II, Investigação dos resultados do tratamento.
Subject(s)
Animals , Male , Rats , Dietary Supplements , Creatinine/administration & dosage , Muscles , Muscles/drug effects , Muscles/chemistry , Physical Conditioning, Animal , Swimming , Rats, Wistar , Spectroscopy, Fourier Transform InfraredABSTRACT
Introduction: This study aims to analyze the influence of particles size of sol-gel derived calcium silicate particles in the setting reaction of bioactive endodontic cements. Materials and Methods: Sol-gel derived calcium silicate particles were synthesized and sieved to separate the particles in different sizes: CS400, CS200, and CS100. A commercial MTA (Control) was used as control. The particle size and the specific surface area were assessed by laser diffraction and nitrogen adsorption. The cements were prepared with water as the liquid for the reaction. The setting time was conducted according to ISO 6876, and the setting kinetics was analyzed by Fourier trans-formed infrared spectroscopy (FTIR) at different time points between 120s to 72h. Results: The particle size varied from 9.45µm (CS400 ) to 31.01 (Control). The higher specific surface area valuer reached 15.14g/cm2 in the CS400. The smallest particle sizes, the higher specific surface area, and the lowest setting time were found for CS400 (p < 0.05). Control presented the highest setting time (p < 0.05). The FTIR analyses showed the differences in materials structure over time, with faster hydration and crystallization for CS400. The setting kinetics was slower for Control even when compared to a sol-gel derived group with similar particle size. Conclusion:The route of synthesis and the particle size influences the setting reaction of calcium silicate-based cements. The reduction of particle size for sol-gel derived calcium silicates lead to the acceleration of the setting reaction of the produced bioactive endodontic cement.
Introdução: Este estudo tem como objetivo analisar a influência do tamanho de partículas de silicato de cálcio derivadas de sol-gel na reação de presa de cimentos endodônticos bioativos. Materiais e Métodos: Partículas de silicato de cálcio derivadas de sol-gel foram sintetizadas e peneiradas para separar as partículas em diferentes tamanhos: CS400, CS200 e CS100. Um MTA comercial (Controle) foi usado como controle. O tamanho das partículas e a área superficial específica foram avaliados por difração a laser e adsorção de nitrogênio. Os cimentos foram preparados com água como líquido para a reação. O tempo de presa foi conduzido de acordo com a ISO 6876, e a cinética de presa foi analisada por espectroscopia de infravermelho transformada de Fourier (FTIR) em diferentes pontos de tempo entre 120s a 72h. Resultados: O tamanho de partícula variou entre 9,45µm (CS400) e 31,01 (Controle). A maior área de superfície foi encontrada nas partículas do grupo CS400 (15.14g/cm2). Os menores tamanhos de partícula, a maior área de superfície específica e o menor tempo de presa foram encontrados para CS400 (p < 0,05). O Control apresentou o maior tempo de presa (p < 0,05). As análises de FTIR mostraram as diferenças na estrutura dos materiais ao longo do tempo, com hidratação e cristalização mais rápidas para CS400. A cinética de presa foi mais lenta para Control mesmo quando comparado a um grupo derivado de sol-gel com tamanho de partícula semelhante. Conclusão: A rota de síntese e o tamanho das partículas influenciam a reação de endurecimento dos cimentos à base de silicato de cálcio. A redução do tamanho de partícula para silicatos de cálcio derivados de sol-gel leva à aceleração da reação de pega do cimento endodôntico bioativo produzido.