Thermoplastic polyimides(PIs)with shape memory potential have received growing attention in recent years.In this work,highperformance thermoplastic PIs were fabricated by introducing PIs with chain rigidity(r-PI)into ...Thermoplastic polyimides(PIs)with shape memory potential have received growing attention in recent years.In this work,highperformance thermoplastic PIs were fabricated by introducing PIs with chain rigidity(r-PI)into PI with chain flexibility(f-PI).The influences of molecular chain entanglement andπ-πinteractions on their thermomechanical and shape memory properties were investigated.The degree of molecular chain entanglement was quantitively characterized based on dynamic mechanical analysis(DMA).Theπ-πinteractions were investigated in detail by X-ray diffraction(XRD)and UV-Vis spectroscopy.It was found that the entanglement density increased andπ-πinteractions became stronger with the introduction of r-PI into f-PI,leading to the improvement of shape recovery.Moreover,a broad and increased glass transition temperature(T_(g))was achieved,endowing the PIs with multiple shape memory properties.The synergistic effects of increased entanglement density and enhancedπ-πinteractions were beneficial to regulating interchain interactions and thereby achieving high shape memory performance of the PIs.展开更多
Electrocardiogram (ECG) signals are used to identify cardiovascular disease. The availability of signal processing and neural networks techniques for processing ECG signals has inspired us to do research that consists...Electrocardiogram (ECG) signals are used to identify cardiovascular disease. The availability of signal processing and neural networks techniques for processing ECG signals has inspired us to do research that consists of extracting features of an ECG signals to identify types of cardiovascular diseases. We distinguish between normal and abnormal ECG data using signal processing and neural networks toolboxes in Matlab. Data, which are downloaded from an ECG database, Physiobank, are used for training and testing the neural network. To distinguish normal and abnormal ECG with the significant accuracy, pattern recognition tools with NN is used. Feature Extraction method is also used to identify specific heart diseases. The diseases that were identified include Tachycardia, Bradycardia, first-degree Atrioventricular (AV), and second-degree Atrioventricular. Since ECG signals are very noisy, signal processing techniques are applied to remove the noise contamination. The heart rate of each signal is calculated by finding the distance between R-R intervals of the signal. The QRS complex is also used to detect Atrioventricular blocks. The algorithm successfully distinguished between normal and abnormal data as well as identifying the type of disease.展开更多
Even with the development of more advanced technology of ECG, there are still problems on interference to ECG signals. Many attempts have been made to detect and eliminate the source of noises and artifacts from the o...Even with the development of more advanced technology of ECG, there are still problems on interference to ECG signals. Many attempts have been made to detect and eliminate the source of noises and artifacts from the original ECG signals. Several studies have been done to observe and study the EMI effect, however, most of?them only focus on the EMI effect of mobile phone during ECG acquisition. Thus, this study is emphasized on the interference problem when other medical devices were being used together with the ECG device. The R-R peak distance of the ECG signal was detected by using QRS detection algorithm invented by J. Pan and W. J. Tompkins. The data from the experiment showed that even the EMI from the medical devices did not affect the physical shape of ECG, but it does affect the R-R peak distance of the ECG signal.展开更多
The appearance and hair color between these two subspecies Rattus rattus Sladeni and R.r. Hainanicus are similar to each other. Their most major distinctive characteristic is the length ratio of tail to body. However... The appearance and hair color between these two subspecies Rattus rattus Sladeni and R.r. Hainanicus are similar to each other. Their most major distinctive characteristic is the length ratio of tail to body. However, this characteristic was unstable in some measuring records. In Guangdong, R.r. Hainanicus is restrictedly distributed in the west region, and R.r. Sladeni is widely distributed in the other regions of this province. In this study, we detected the sequences of mitochondrial 12S rRNA gene fragments of 9 samples from R.r. Hainanicus and R.r. Sladeni (Longmen and Hong Kong populations). These 385 nucleotide positions of 12S rRNA gene fragment include 26 variable sites and 14 parsimony-informative sites. 3 insertion/deletion sites are observed. The phylogenetic relationships among these samples were constructed by Neighbor-joining and Maximum parsimony methods. The analysis shows that R.r. Hainanicus is more closely relative to the Longmen population of R.r. Sladeni than to the Hong Kong population of R.r. Sladeni. The sequencing analysis of 12S rRNA gene fragments is not agreement on the classification of subspecies R. r. Hainanicus inferred from the morphology and geographical distribution. The morphological variation of R.r. Hainanicus should result from the natural selection, which causes local adaptation and geographic isolation.展开更多
基金financially supported by the Engineering Research Center for Clean Production of Textile Printing and Dyeing,Ministry of Education(No.FZYR2021001)Shanghai Pujiang Program(No.19PJ1400400)Shanghai Key Laboratory of Lightweight Composite(No.2232019A4-04)。
文摘Thermoplastic polyimides(PIs)with shape memory potential have received growing attention in recent years.In this work,highperformance thermoplastic PIs were fabricated by introducing PIs with chain rigidity(r-PI)into PI with chain flexibility(f-PI).The influences of molecular chain entanglement andπ-πinteractions on their thermomechanical and shape memory properties were investigated.The degree of molecular chain entanglement was quantitively characterized based on dynamic mechanical analysis(DMA).Theπ-πinteractions were investigated in detail by X-ray diffraction(XRD)and UV-Vis spectroscopy.It was found that the entanglement density increased andπ-πinteractions became stronger with the introduction of r-PI into f-PI,leading to the improvement of shape recovery.Moreover,a broad and increased glass transition temperature(T_(g))was achieved,endowing the PIs with multiple shape memory properties.The synergistic effects of increased entanglement density and enhancedπ-πinteractions were beneficial to regulating interchain interactions and thereby achieving high shape memory performance of the PIs.
文摘Electrocardiogram (ECG) signals are used to identify cardiovascular disease. The availability of signal processing and neural networks techniques for processing ECG signals has inspired us to do research that consists of extracting features of an ECG signals to identify types of cardiovascular diseases. We distinguish between normal and abnormal ECG data using signal processing and neural networks toolboxes in Matlab. Data, which are downloaded from an ECG database, Physiobank, are used for training and testing the neural network. To distinguish normal and abnormal ECG with the significant accuracy, pattern recognition tools with NN is used. Feature Extraction method is also used to identify specific heart diseases. The diseases that were identified include Tachycardia, Bradycardia, first-degree Atrioventricular (AV), and second-degree Atrioventricular. Since ECG signals are very noisy, signal processing techniques are applied to remove the noise contamination. The heart rate of each signal is calculated by finding the distance between R-R intervals of the signal. The QRS complex is also used to detect Atrioventricular blocks. The algorithm successfully distinguished between normal and abnormal data as well as identifying the type of disease.
文摘Even with the development of more advanced technology of ECG, there are still problems on interference to ECG signals. Many attempts have been made to detect and eliminate the source of noises and artifacts from the original ECG signals. Several studies have been done to observe and study the EMI effect, however, most of?them only focus on the EMI effect of mobile phone during ECG acquisition. Thus, this study is emphasized on the interference problem when other medical devices were being used together with the ECG device. The R-R peak distance of the ECG signal was detected by using QRS detection algorithm invented by J. Pan and W. J. Tompkins. The data from the experiment showed that even the EMI from the medical devices did not affect the physical shape of ECG, but it does affect the R-R peak distance of the ECG signal.
文摘 The appearance and hair color between these two subspecies Rattus rattus Sladeni and R.r. Hainanicus are similar to each other. Their most major distinctive characteristic is the length ratio of tail to body. However, this characteristic was unstable in some measuring records. In Guangdong, R.r. Hainanicus is restrictedly distributed in the west region, and R.r. Sladeni is widely distributed in the other regions of this province. In this study, we detected the sequences of mitochondrial 12S rRNA gene fragments of 9 samples from R.r. Hainanicus and R.r. Sladeni (Longmen and Hong Kong populations). These 385 nucleotide positions of 12S rRNA gene fragment include 26 variable sites and 14 parsimony-informative sites. 3 insertion/deletion sites are observed. The phylogenetic relationships among these samples were constructed by Neighbor-joining and Maximum parsimony methods. The analysis shows that R.r. Hainanicus is more closely relative to the Longmen population of R.r. Sladeni than to the Hong Kong population of R.r. Sladeni. The sequencing analysis of 12S rRNA gene fragments is not agreement on the classification of subspecies R. r. Hainanicus inferred from the morphology and geographical distribution. The morphological variation of R.r. Hainanicus should result from the natural selection, which causes local adaptation and geographic isolation.
