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To investigate the relationship between depression in early pregnancy and sleep quality in mid-pregnancy, and explore whether sleep disorders independently predicts depression across the perinatal period within women with or without depression in early pregnancy. Data were collected at 7 time points from 12 weeks of pregnancy to 6 weeks postpartum. Multiple logistic regression and survival analysis were used to explore the relationship between sleep quality in mid-pregnancy and perinatal depression within women with or without depression in early pregnancy. 390 women were included. Women with depression in early pregnancy were more likely to have sleep disorders and perinatal depression. Women with sleep disorders had a higher risk of perinatal depression compared to women without sleep disorders in mid-pregnancy. Stratified analysis based on whether depressed at 12 weeks of pregnancy found that among women without depression, those with sleep disorders in mid-pregnancy were more likely to have subsequent perinatal depression and appeared earlier; whereas, among women with depression, mid-pregnancy sleep disorders was not a predictor of subsequent perinatal depression. High rates of missed visits may lead to sample bias, with depression and sleep quality being assessed by self-report. Women with depression in early pregnancy are more likely to have sleep disorders in mid-pregnancy. There is a strong correlation between sleep quality in mid-pregnancy and perinatal depression among women without depression in early pregnancy. Routine screening and intervention for sleep disorders should be a priority in perinatal care to reduce the incidence of perinatal depression. • Women with depression were more likely to have sleep disorders in mid-pregnancy. • Depression in early pregnancy predicted the presence of depression from mid-pregnancy to 6 weeks postpartum. • Among non-depressed in early pregnancy, women with mid-pregnancy sleep disorders had a higher risk of perinatal depression. [ABSTRACT FROM AUTHOR]

A novel breast ultrasound tomography system based on a circular array of capacitive micromechanical ultrasound transducers (CMUT) has broad application prospects. However, the images produced by this system are not suitable as input for the training phase of the super-resolution (SR) reconstruction algorithm. To solve the problem, this paper proposes an improved medical image super-resolution (MeSR) method based on the sparse domain. First, we use the simultaneous algebraic reconstruction technique (SART) with high imaging accuracy to reconstruct the image into a training image in a sparse domain model. Secondly, we denoise and enhance the contrast of the SART images to obtain improved detail images before training the dictionary. Then, we use the original detail image as the guide image to further process the improved detail image. Therefore, a high-precision dictionary was obtained during the testing phase and applied to filtered back projection SR reconstruction. We compared the proposed algorithm with previously reported algorithms in the Shepp Logan model and the model based on the CMUT background. The results showed significant improvements in peak signal-to-noise ratio, entropy, and average gradient compared to previously reported algorithms. The experimental results demonstrated that the proposed MeSR method can use noisy reconstructed images as input for the training phase of the SR algorithm and produce excellent visual effects. [ABSTRACT FROM AUTHOR]

Background. Postpartum depression (PPD) is common after childbirth. Previous reviews on the prevalence of PPD have mainly included results that relied on screening instruments or a mixture of such instruments and diagnostic interviews. In this study, we aimed to assess the prevalence of PPD based exclusively on studies using diagnostic interviews, as they provide the most reliable and valid approach for defining "caseness." Methods. Using PubMed, Web of Science, Cochrane Library, Embase, CNKI, WANFANG DATA, and CBM up to September 18, 2022, we searched for original articles reporting data that could be used to calculate the prevalence of PPD based on diagnostic interviews. A random-effect meta-analysis model was then used to estimate the pooled prevalence. In addition, we assessed quality, heterogeneity, and publication bias across studies. Also, we did subgroup analyses to explore the pooled prevalence at different time points and settings. This study was registered with PROSPERO, CRD42021244539. Results. Of 17,115 articles retrieved, 54 studies were included (total sample size = 15,586 women). The pooled prevalence of all depression and major depression within one year postpartum was 12.1% (95% CI 10.3%-14.1%; I 2 = 91.0 %) and 7.0% (95% CI 5.7%-8.4%; I 2 = 83.0 %), respectively. The peaks of all depression occurred during the first 6 months postpartum, especially 2-3 weeks and 6-8 weeks. Subgroup analyses showed that the prevalence of major depression was associated with the income level of countries (higher in low- and middle-income countries (LMICs) than in high-income countries (HICs)) and diagnostic criteria (higher using ICD than using DSM and RDC). No evidence of publication bias was found. Conclusions. Approximately one in eight postpartum women experiences a depressive condition, with one in fifteen suffering major depression. The pooled prevalence based on diagnostic interviews was lower than the existing consensus, which was largely based on self-reported screening instruments. The higher prevalence in LMICs underlines the importance of strengthening research and service provision among these populations. [ABSTRACT FROM AUTHOR]

Simple Summary: The meat quality of small ruminants is adversely affected when the feeding mode is changed from grazing to captivity. We found that adding probiotics to lamb feed regulated the intestinal metabolites (SCFAs) of Sunit lambs, acting as signaling factors that affected the gene mRNA expression of MyHC isoforms and the activity of metabolic enzymes, thereby promoting the transformation of muscle fiber types and increasing the proportion of oxidative muscle fibers. Finally, the tenderness of the meat was improved. The development of animal husbandry is closely related to the meat quality of small ruminants. Intestinal metabolites and the muscle fiber types of lambs are important factors that affect their meat quality, but few studies have examined the regulation of the "intestinal muscle axis" by probiotics. In this study, 12 Sunit lambs were divided into a control group (C) and a probiotics group (P). The gene expressions of the myosin heavy chain, metabolic enzyme activity, and short-chain fatty acids in the intestines were analyzed using gas chromatography-mass spectrometry (GC-MS) and quantitative real-time PCR. The results showed that levels of propionic acid and butyric acid in the intestines of group P were significantly higher than in group C (p < 0.05). In addition, probiotics increased the number and area ratio of type I muscle fibers. They also increased the mRNA expression of MyHC IIA and the activity of malate dehydrogenase (MDH) and succinate dehydrogenase (SDH). Propionic acid was negatively correlated with the number ratio of type IIB muscle fibers. Butyric acid was found to be significantly positively correlated with the number ratio of type IIA muscle fibers. Cooking loss, pH24h, and shear force decreased significantly in group P. In conclusion, intestinal metabolites (SCFAs) altered the activity of oxidative-myofibril-metabolizing enzymes and the expression of myosin heavy-chain type IIA, reduced the meat shear values, and improved meat tenderness. This study provides a new basis for improving the production and meat quality of small ruminants. [ABSTRACT FROM AUTHOR]

Although computer-aided diagnosis (CAD) have shown excellent performance in Breast cancer (BC) histopathological image, it commonly requires a high-level network, and the recognition efficiency is frequently unsatisfied due to the complex structure of histopathological image. In this study, a ten-layers convolutional neural network (CNN) model called "ColorDeep" is used to extract color features corresponding to the different tissue parts in cell, pure color image slices obtained by a three-channel separation and reconstruction method are used as model input. Two models are tested on the BreaKHis dataset show that images under four magnifications achieved the recognition accuracy of 96.89%–99.67% at the image level, which is better than many state-of-the-art methods. The characteristics contained by the B channel have the largest effect on BC recognition, and compared to other research results, the proposed model improves the recognition speed on a single image by about 0.1s. More importantly, instead of using large histopathological images to input into the model for BC diagnosis, and instead of segmenting the nuclei, only the reconstructed B-channel features containing the nuclei region in the stained BC image need to be input into the model to enable accurate diagnosis of BC. • Three-channel reconstructed slices contain better color features of breast cancer. • Reconstructed B-channel features contain more information about the cell nucleus. • Using color features to diagnose breast cancer can avoid segmentation of nuclei. • Reconstructed color slices enable low-complexity model to identify breast cancer. • Considering recognition accuracy and speed, feature fusion model is more suitable for breast cancer diagnosis. [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks (DCNN) are extensively used in image classification. However, it is typically impossible to receive ideal effects if directly using it in synthetic aperture radar (SAR) image target recognition. During the data acquisition process, it is difficult to acquire a large number of labeled training data and to ensure the image targets in the center. To extract the width and height features of SAR images and reduce the computational complexity, we constructed an asymmetric parallel convolution module. The module avoids severe over-fitting due to limited training samples and effectively deals with displacement changes with test samples. Meanwhile, the residual learning method is used in the algorithm to avoid the deep network degradation and improve algorithm recognition accuracy (RA). Experimental results show that the RA of the DCNN with residual-learning-based APCRLNet reaches 99.75% under standard operating conditions, which is superior to existing recognition methods. Furthermore, the algorithm also performs well for incomplete training samples and test samples with displacement changes. [ABSTRACT FROM AUTHOR]

The significance of flu prediction is that the appropriate preventive and control measures can be taken by relevant departments after assessing predicted data; thus, morbidity and mortality can be reduced. In this paper, three flu prediction models, based on twitter and US Centers for Disease Control’s (CDC’s) Influenza-Like Illness (ILI) data, are proposed (models 1-3) to verify the factors that affect the spread of the flu. In this work, an Improved Particle Swarm Optimization algorithm to optimize the parameters of Support Vector Regression (IPSO-SVR) was proposed. The IPSO-SVR was trained by the independent and dependent variables of the three models (models 1-3) as input and output. The trained IPSO-SVR method was used to predict the regional unweighted percentage ILI (%ILI) events in the US. The prediction results of each model are analyzed and compared. The results show that the IPSO-SVR method (model 3) demonstrates excellent performance in real-time prediction of ILIs, and further highlights the benefits of using real-time twitter data, thus providing an effective means for the prevention and control of flu. [ABSTRACT FROM AUTHOR]

Abstract The fireworks algorithm, which is inspired by the explosion of fireworks, is a new swarm-based meta-heuristic algorithm for global optimization. This work proposes an improved fireworks optimization algorithm (IFWA) based on the enhanced fireworks algorithm (EFWA). Three aspects of improvement are presented after an analysis of the drawbacks of EFWA. These improvements are a new explosion scheme, GS-Gaussian explosion operator, and deep information exchange strategy. The proposed IFWA is tested on 23 benchmark function optimization problems and a real engineering problem, namely, optimal controller design for automotive active suspension. Optimization results prove that IFWA has competitive advantage compared with EFWA and other popular meta-heuristic algorithms and demonstrates the potential to solve real problems effectively. [ABSTRACT FROM AUTHOR]

A wide beam miniaturized broadband omnidirectional circularly polarized antenna operating at S‐band is proposed. It is composed of a hub‐shaped circular horizontally polarized radiator, a vertically polarized radiator consisting of a monopole and eight shorting‐circuited pins, and a coupling feed device. The measured results indicate that the impedance matching band of |S11| < −10 dB is from 2.15 to 2.75 GHz (24.4%), and the band of the axial ratio <3 dB is from 2.2 to 2.7 GHz (20.4%). The gain of the antenna is about 1 dB, and the noncircularity in the azimuth plane is <1.2 dB. In addition, the antenna has the characteristics of wide axis ratio beam in the pitch plane with sizes of 0.68 λ0 × 0.68 λ0 × 0.14 λ0. The antenna is very suitable for satellite receiving system and short‐range wireless communication system. [ABSTRACT FROM AUTHOR]

The global k-means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k-means to minimize the sum of the intra-cluster variances. However the global k-means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k-means algorithm. In this paper, we modified the global k-means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k-means clustering error method to global k-means algorithm to overcome the effect of bad initialization, proposed the global Minmax k-means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k-means algorithm, the global k-means algorithm and the MinMax k-means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper. [ABSTRACT FROM AUTHOR]

The MinMax k-means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical framework is given. Such framework extends the MinMax k-means to automatically adapt the exponent parameter to the data set. It has been believed that if the maximum exponent parameter has been set, then the programme can reach the lowest intraclustering errors. However, our experiments show that this is not always correct. In this paper, we modified the MinMax k-means algorithm by PSO to determine the proper values of parameters which can subject the algorithm to attain the lowest clustering errors. The proposed clustering method is tested on some favorite data sets in several different initial situations and is compared to the k-means algorithm and the original MinMax k-means algorithm. The experimental results indicate that our proposed algorithm can reach the lowest clustering errors automatically. [ABSTRACT FROM AUTHOR]

In this paper, a novel ultra-wideband (UWB) all-metal Vivaldi antenna with an inclined groove is proposed. The antenna structure is very simple, and it consists of Vivaldi metal plate, 2.4 mm-K connector and supporting ground. The machining of the antenna is very convenient, and the Vivaldi metal plate can be easily processed by wire cutting technology. To verify the design, the metal Vivaldi plate was machined and measured. From the measured results, the Vivaldi antenna achieves a wide impedance bandwidth of 25:1 from 2 to 50 GHz with a return loss better than 10 dB. Moreover, the gain of the Vivaldi antenna is 4−12dBi, and the radiation pattern is also symmetric and stable over the whole frequency range of 2–50 GHz. [ABSTRACT FROM AUTHOR]

In this paper, an efficient approach of combining Takagi–Sugeno–Kang fuzzy system with wavelet based neural network is presented. The model replaces the constant or a linear function of inputs in conclusion part of traditional TSK fuzzy model with wavelet neural network (WNN), thus each rule uses fuzzy set to separate the input space into subspaces spanned by different wavelet functions. For finding the optimal values for parameters of our proposed fuzzy wavelet neural network (proposed-FWNN), a hybrid learning algorithm integrating an improved particle swarm optimization (PSO) and gradient descent algorithm is employed. The two-layer inline-PSO process is proposed in this paper, whose adjustment scheme is more fitting the consequent pattern learning based gradient descent optimization and will locate a good region in the search space. Simulation examples are given to test the efficiency of proposed-FWNN model for identification of the dynamic plants. It is seen that our modeling and optimization approach results in a better performance. [ABSTRACT FROM AUTHOR]

There have been reports of association between psoriasis and psychological illnesses. Nevertheless, it is not easy to draw conclusions with high quality causality from conventional observational studies. The objective of this study was to evaluate the causality of psoriasis and psychological illnesses. All summary-level data from genome-wide association studies for psoriasis and psychological illnesses were collected from Neale Lab and MRC Integrative Epidemiology Unit. Bidirectional Mendelian randomization analysis was performed to determine the random orientation with an independent genetic variation. The main estimated effects are derived using Inverse-Variance Weighted, weighted median, and MR Egger methods. Multiple data sets were validated against each other, and a series of sensitivity studies were conducted to ensure the reliability of the results. Mendelian randomization analysis revealed a causal effect of psoriasis [odds ratio (OR) 1·34, 95% confidence interval (CI) 1·21–1·46, P < 0.001; and OR 1.28, CI 1.17–1.39, P < 0.001] on psychological illnesses, and vice versa (OR 1.23, CI 1.14–1.31, P < 0.001; and OR 1.21, CI 1.11–1.31, P < 0.001). The results were supported by a series of sensitivity analyses. The findings of this Mendelian randomization study support a causal effect between psoriasis and psychological illnesses, and vice versa. [ABSTRACT FROM AUTHOR]

Due to the complex underwater environment and the selective absorption and scattering effect of water on light waves, underwater images often suffer from issues such as low contrast, color distortion, and blurred details. This paper presents a stable and effective algorithm for enhancing underwater images to address these challenges. Firstly, an improved color correction algorithm based on the gray world and minimum information loss is employed to remove the blue-green bias present in the images. Secondly, a contrast enhancement algorithm is based on the guided filter and wavelet decomposition to make the texture details of the image clearer. Then, the normalized weight map of the image is obtained to carry out multi-scale fusion. Finally, the fused image is applied to perform the multi-scale decomposition. The experimental results show that the algorithm proposed in this paper can correct the image color deviation, improve the image contrast and enhance the image details. [ABSTRACT FROM AUTHOR]

Abstract Endometrial carcinoma is a life-threatening disease that causes serious damage to the women's health. This paper discusses classifications of 87 endometrial samples with gene expressions that are cancerous or cancer-free. Every sample has 5 indicators. For every indicator, the corresponding genes of the missing data are deleted and the signal noise ratios (SNRs) are calculated to filter the irrelevant genes. Then the obtained new samples use the principle component analysis to decrease the dimensions. Finally 10 random samples are selected to be the testing samples for classification. Thus the classification accuracy rate is given for every indicator. Based on cancer related to 5 indicators, the combination of the 5 indicators is used to classify to make new 87 endometrial samples as cancerous or cancer-free. We repeatedly process these new samples by deleting the missing data, filtering the irrelevant genes with SNRs, and decreasing the dimensions with PCA, an obtain the new data. The proposed method is that the particle swarm algorithm (PSO) and the grey wolf optimizer (GWO) is combined to optimize the parameters of Elman recurrent neural network (ERNN), written as PSOGWO-ERNN. The results show that PSOGWO-ERNN is superior to the single ERNN, ERNN optimized by PSO or GWO (PSO-ERNN or GWO-ERNN), and the classification accuracy rate of PSOGWO-ERNN reaches 88.8506%. The results also show that the neural networks optimized by some swarm intelligence algorithms are more useful for classification. [ABSTRACT FROM AUTHOR]

Linseed as a common oil crop that has been implicated in regulating the meat quality of animals. The aim of this investigation was to establish the effects of dietary linseed supplementation on carcass traits, meat quality, muscle fiber characteristics, volatile compounds and antioxidant capacity of sheep. Twenty‐four Sunit sheep were distributed into 2 groups with different diet: control (CO) fed a standard diet and linseed (LS, 8% of extruded linseed). The results showed that linseed not only increased M. longissimus thoracis (LT) increased the loin‐eye area but also decreased pH24h, L* and shear force. Meanwhile, linseed increased mRNA expression of MyHCI and MyHCIIx and decreased in cross‐sectional area (CSA) and muscle fiber diameter. In addition, linseed altered the composition of meat volatile flavor compounds, such as Z‐10‐Pentadecen‐1‐ol, pentanal, 2‐Octenal, (E)‐, decanal, butane, and 2‐heptanone. Moreover, linseed increased total antioxidative capacity (T‐AOC) activity, the mRNA expression of glutathione peroxidase (GSH‐Px) and catalase (CAT), decreased malondialdehyde (MDA) content. Overall, the results suggest that linseed is an effective feed additive in improving meat quality and flavor. The underlying mechanisms for its effectiveness may be partly due to a change in muscle fiber characteristics and antioxidant capacity. [ABSTRACT FROM AUTHOR]

Opium is the raw material for the production of heroin, and the characterization of opium seizures through laboratory analysis is a valuable tool for law enforcement agencies to trace clandestine opium production and trafficking. In this work, a method for opium profiling based on the relative content of five principal and 14 minor opium alkaloids was developed and validated. UPLC‐Q‐TOF was adopted in alkaloid analysis for its high selectivity and sensitivity, which facilitated the sample preparation and testing. The authentic sample set consisted of 100 “Myanmar” and 45 “Afghanistan” opium seizures; based on the data set of the 19 alkaloid variables in them, a partial least squares discriminant analysis classification model was successfully achieved. Minor alkaloids were found to be vitally important for opium profiling, although combined use of both principal and minor alkaloids resulted in the best geographical classification result. The developed method realized a simple and accurate way to differentiate opium from Myanmar and Afghanistan, which may find wide application in forensic laboratories. [ABSTRACT FROM AUTHOR]

The illicit manufacture of heroin results in the formation of trace levels of acidic and neutral manufacturing impurities that provide valuable information about the manufacturing process used. In this work, a new ultra performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF) method; that features high resolution, mass accuracy and sensitivity for profiling neutral and acidic heroin manufacturing impurities was developed. After the UPLC-Q-TOF analysis, the retention times and m/z data pairs of acidic and neutral manufacturing impurities were detected, and 19 peaks were found to be evidently different between heroin samples from "Golden Triangle" and "Golden Crescent". Based on the data set of these 19 impurities in 150 authentic heroin samples, classification of heroin geographic origins was successfully achieved utilizing partial least squares discriminant analysis (PLS-DA). By analyzing another data set of 267 authentic heroin samples, the developed discrimiant model was validated and proved to be accurate and reliable. [ABSTRACT FROM AUTHOR]

It was reported that within the head and neck cancer (HNC) cell line CAL21 the epithelial-mesenchymal transition (EMT) and cell proliferation were promoted by Urokinase-Type Plasminogen Activator (PLAU) proteinase through TNFRSF12A. Additionally, in this paper HNC cell lines refer to Fadu and Tu686. A novel PLAU-STAT3 axis was found to be involved in HNC cell line proliferation and metastasis. PLAU expression in HNC samples was upregulated, besides, the elevated expression of PLAU was linked to the lower overall survival (OS) and disease-free survival (DFS). Ectopic PLAU expression promoted cell proliferation and migration, while PLAU knockdown exhibited opposite results. RNA-seq data identified the JAK-STAT signaling pathway, confirmed by western blotting. A recovery assay using S3I-201, a selective inhibitor of signal transducer and activator of transcription 3 (STAT3), indicated that PLAU promoted HNC cell line progression via STAT3 signaling in vitro. The oncogenic role of PLAU in HNC tumor growth in vivo was confirmed using xenograft models. In summary, we identified the tumorigenic PLAU function in the HNC progress. PLAU may represent a potential prognostic biomarker of HNC and the PLAU-STAT3 pathway might be considered a therapeutic target of HNC. • High PLAU expression indicates poor overall and disease-free survival of HNC. • PLAU promotes HNC cell proliferation and migration via JAK-STAT signaling pathway. • PLAU suppresses HNC tumor growth in vivo. [ABSTRACT FROM AUTHOR]

Breast cancer is regarded as the leading killer of women today. The early diagnosis and treatment of breast cancer is the key to improving the survival rate of patients. A method of breast cancer histopathological images recognition based on deep semantic features and gray level co-occurrence matrix (GLCM) features is proposed in this paper. Taking the pre-trained DenseNet201 as the basic model, part of the convolutional layer features of the last dense block are extracted as the deep semantic features, which are then fused with the three-channel GLCM features, and the support vector machine (SVM) is used for classification. For the BreaKHis dataset, we explore the classification problems of magnification specific binary (MSB) classification and magnification independent binary (MIB) classification, and compared the performance with the seven baseline models of AlexNet, VGG16, ResNet50, GoogLeNet, DenseNet201, SqueezeNet and Inception-ResNet-V2. The experimental results show that the method proposed in this paper performs better than the pre-trained baseline models in MSB and MIB classification problems. The highest image-level recognition accuracy of 40×, 100×, 200×, 400× is 96.75%, 95.21%, 96.57%, and 93.15%, respectively. And the highest patient-level recognition accuracy of the four magnifications is 96.33%, 95.26%, 96.09%, and 92.99%, respectively. The image-level and patient-level recognition accuracy for MIB classification is 95.56% and 95.54%, respectively. In addition, the recognition accuracy of the method in this paper is comparable to some state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Pathological examination is the gold standard for breast cancer diagnosis. The recognition of histopathological images of breast cancer has attracted a lot of attention in the field of medical image processing. In this paper, on the base of the Bioimaging 2015 dataset, a two-stage nuclei segmentation strategy, that is, a method of watershed segmentation based on histopathological images after stain separation, is proposed to make the dataset recognized to be the carcinoma and non-carcinoma recognition. Firstly, stain separation is performed on breast cancer histopathological images. Then the marker-based watershed segmentation method is used for images obtained from stain separation to achieve the nuclei segmentation target. Next, the completed local binary pattern is used to extract texture features from the nuclei regions (images after nuclei segmentation), and color features were extracted by using the color auto-correlation method on the stain-separated images. Finally, the two kinds of features were fused and the support vector machine was used for carcinoma and non-carcinoma recognition. The experimental results show that the two-stage nuclei segmentation strategy proposed in this paper has significant advantages in the recognition of carcinoma and non-carcinoma on breast cancer histopathological images, and the recognition accuracy arrives at 91.67%. The proposed method is also applied to the ICIAR 2018 dataset to realize the automatic recognition of carcinoma and non-carcinoma, and the recognition accuracy arrives at 92.50%. [ABSTRACT FROM AUTHOR]

Background Piracetam is a positive allosteric modulator of the AMPA receptor that has been used in the treatment of cognitive disorders for decades. Recent surveys and drug analyses have demonstrated that a heroin mixture adulterated with piracetam has spread rapidly in heroin addicts in China, but its addictive properties and the damage it causes to the central neural system are currently unknown. Methods The effect of piracetam on the reward properties of heroin was assessed by conditioned place preference (CPP). Electron microscopy and radioimmunoassay were used to compare the effects of heroin mixed with equivalent piracetam (HP) and heroin alone on neuronal apoptosis and the levels of beta-endorphin (β-EP) in different brain subregions within the corticolimbic system, respectively. Results Piracetam significantly enhanced heroin-induced CPP expression while piracetam itself didn’t induce CPP. Morphological observations showed that HP-treated rats had less neuronal apoptosis than heroin-treated group. Interestingly, HP normalized the levels of β-EP in the medial prefrontal cortex (mPFC) and core of the nucleus accumbens (AcbC) subregions, in where heroin-treated rats showed decreased levels of β-EP. Conclusions These results indicate that piracetam potentiate the heroin-induced CPP and protect neurons from heroin-induced apoptosis. The protective role of HP might be related to the restoration of β-EP levels by piracetam. Our findings may provide a potential interpretation for the growing trend of HP abuse in addicts in China. [ABSTRACT FROM AUTHOR]

This paper proposes an improved dynamic particle swarm optimization algorithm, which uses a new and effective exponential decreasing inertia weight (EDIW) strategy. Based on the improved EDIW-PSO algorithm together with AdaBoost algorithm, we adjust the parameters (centers, widths, shape parameters and connection weights) of GRBF and present a novel hybrid EDIW-PSO-AdaBoost-GRBF model. Two application examples are given on the proposed model. The results obtained show that the proposed model is effective and feasible for prediction problems. [ABSTRACT FROM AUTHOR]

Since COVID-19 pneumonia broke out, the Chinese government has taken a series of measures to control the spread of the epidemic, which has made the air quality of Taiyuan in February 2020 significantly better than during the same period in previous years. In this paper, the Gray Relational Analysis (GRA) method was first applied to evaluate and analyze the influence of six major pollutants on air quality. Then, the improved seagull optimization algorithm (ISOA) was proposed and combined with Support Vector Regression (SVR) to establish a hybrid predicted model ISOA-SVR. Finally, the proposed ISOA-SVR was utilized to predict air quality index (AQI). The experimental results on two kinds of different data showed that the proposed ISOA-SVR had the better generalization ability and robustness compared with other predicted models. Further, the proposed ISOA-SVR is suitable for the prediction of AQI. [ABSTRACT FROM AUTHOR]

• Phenotype of Tph17 cells is activated and proliferative in psoriasis vulgaris. • Tph17 cells and plasma CXCL13 could be biomarkers for evaluating the severity of psoriasis vulgaris. • Tph17 cells and the CXCL13/CXCR5 axis might represent new immunotherapeutic targets for psoriasis vulgaris. Recently, a new subgroup of T cells, named peripheral helper T (Tph) cells, has been implicated in autoimmune pathogenesis. An imbalance of Tph cell subsets influences the severity of immune-related diseases. However, the characteristics and roles of Tph cell subsets in psoriasis remain unknown. Programmed cell death 1-positive, chemokine C-X-C receptor (CXCR) 5-negative Tph cells can be divided into 3 subgroups based on differential expression of chemokine CXCR3 and chemokine C-C receptor (CCR) 6. CXCR3+CCR6− Tph cells are classified as Tph1, CXCR3−CCR6− Tph cells are classified as Tph2, and CXCR3−CCR6+ Tph cells are classified as Tph17. In this study, conditions of circulating Tph cell subsets and CD4+CXCR5+ follicular helper T (Tfh) cells in 27 patients with psoriasis and 13 healthy individuals were detected by flow cytometry. The level of plasma chemokine C-X-C ligand (CXCL) 13 was measured by enzyme-linked immunosorbent assay. The correlations between the above indexes and disease severity were explored. In the peripheral blood of patients with psoriasis, Tph17 cells had an activated, proliferative phenotype; the quantity of the cells correlated with disease severity. Plasma CXCL13 levels were elevated in psoriasis and associated with disease severity and the frequency of Tph17 cells. CD4+CXCR5+ Tfh cells were increased in patients and positively correlated with disease severity, the frequency of Tph17 cells, and plasma CXCL13 levels. Our results suggest that Tph17 cells and the CXCL13/CXCR5 axis may be involved in the pathogenesis of psoriasis and represent new immunotherapeutic targets for treating psoriasis. [ABSTRACT FROM AUTHOR]

The outbreak of Corona Virus Disease 2019 (COVID-19) in Wuhan has significantly impacted the economy and society globally. Countries are in a strict state of prevention and control of this pandemic. In this study, the development trend analysis of the cumulative confirmed cases, cumulative deaths, and cumulative cured cases was conducted based on data from Wuhan, Hubei Province, China from January 23, 2020 to April 6, 2020 using an Elman neural network, long short-term memory (LSTM), and support vector machine (SVM). A SVM with fuzzy granulation was used to predict the growth range of confirmed new cases, new deaths, and new cured cases. The experimental results showed that the Elman neural network and SVM used in this study can predict the development trend of cumulative confirmed cases, deaths, and cured cases, whereas LSTM is more suitable for the prediction of the cumulative confirmed cases. The SVM with fuzzy granulation can successfully predict the growth range of confirmed new cases and new cured cases, although the average predicted values are slightly large. Currently, the United States is the epicenter of the COVID-19 pandemic. We also used data modeling from the United States to further verify the validity of the proposed models. [ABSTRACT FROM AUTHOR]

Abstract: Colla corii asini hydrolysates (ACCH) and ginkgo biloba extracts (EGb) possess more potent antioxidant effects when used in combination than when used alone. The mixture of ACCH and EGb at a dose ratio of 20:4(w:w) showed the highest radical scavenging activity with IC50 of 0.17 ± 0.01, 0.43 ± 0.02 and 1.52 ± 0.07 mg/ml against DPPH, ABTS and HO· free radicals, respectively. Furthermore, the inhibition of breast cancer cells MCF‐7 and MDA‐MB‐231 proliferation increased when these cell lines were treated with a combination of ACCH and EGb for 72 hr, with IC50 of 4.32 ± 0.12 mg/ml and 0.39 ± 0.01 mg/ml, respectively. The findings indicated that the mixtures of ACCH and EGb could be used to prevent and treat some diseases caused by the excessive free radicals, especially cancer. Therefore, the mixtures of ACCH and EGb might serve as a natural source of desirable antioxidant and anticancer agents for the nutraceutical and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

Objective: The aim of the research is to obtain the relative influences of some critical electro-thermal parameters on the ablation temperature and lesion volume during temperature-controlled radiofrequency ablation (RFA) of liver tumor by parameter sensitivity analysis.Methods: The finite element method (FEM) has been used to establish the simulation model of RFA temperature field, and the sensitivity of the tissue parameters has been analyzed. The effects of six parameters have been taken into account, including the thermal specific capacity (Cp), the thermal conductivity (k), the electrical conductivity (Sigma), the density (rho), the dielectric constant (Epsilon) and the resistance (R). The simulation processes based on different parameter values have been accomplished with Comsol Multiphysics software, and the sensitivity parameters have been obtained utilizing the variance contribution rate (SS%) or the main effects.Results: It was found that the ablation temperature and lesion volume increased with increasing the values of Rand Sigma, but was a reverse situation for Cp and rho. Besides, the influence of k on ablation volume was relatively small and Epsilon had a negligible effect on ablation temperature.Conclusions: It is concluded that these parameter sensitivity results can provide scientific and reliable reference for the specificity analysis of the RF ablation models. [ABSTRACT FROM AUTHOR]

Psoriasis (PS) and rheumatoid arthritis (RA) are immune-mediated inflammatory diseases. Previous studies showed that these two diseases had a common pathogenesis, but the precise molecular mechanism remains unclear. In this study, RNA sequencing of peripheral blood mononuclear cells was employed to explore both the differentially expressed genes (DEGs) of 10 PS and 10 RA patients compared with those of 10 healthy volunteers and the shared DEGs between these two diseases. Bioinformatics network analysis was used to reveal the connections among the shared DEGs and the corresponding molecular mechanism. In total, 120 and 212 DEGs were identified in PS and RA, respectively, and 31 shared DEGs were identified. Bioinformatics analysis indicated that the cytokine imbalance relevant to key molecules (such as extracellular signal-regulated kinase 1/2 (ERK1/2), p38 mitogen-activated protein kinase (MAPK), tumor necrosis factor (TNF), colony-stimulating factor 3 (CSF3), interleukin- (IL-) 6, and interferon gene (IFNG)) and canonical signaling pathways (such as the complement system, antigen presentation, macropinocytosis signaling, nuclear factor-kappa B (NF-κB) signaling, and IL-17 signaling) was responsible for the common comprehensive mechanism of PS and RA. Our findings provide a better understanding of the pathogenesis of PS and RA, suggesting potential strategies for treating and preventing both diseases. This study may also provide a new paradigm for illuminating the common pathogenesis of different diseases. [ABSTRACT FROM AUTHOR]

Circulating T follicular helper (Tfh) cells in the blood are counterparts to conventional Tfh cells in germinal centres. Similarly to conventional Tfh cells, circulating Tfh cells provide helpful signals for B cells. Circulating Tfh cells can be divided into three subpopulations, including Tfh17 (CXCR3-CCR6+), Tfh1 (CXCR3 + CCR6-), and Tfh2 (CXCR3-CCR6-) cells, based on differences in CXCR3 and CCR6 expression. Recent studies have demonstrated that alterations in circulating Tfh cell subsets have significant effects on the progression of numerous autoimmune diseases. To address the role of circulating Tfh cells in psoriasis, we used flow cytometry to analyse frequencies of circulating Tfh cell subsets and levels of IL-21 receptor (IL-21R) expression on B cells in 32 patients with psoriasis vulgaris and 13 sex- and age-matched healthy controls. We observed dynamic changes in Tfh17 cell frequency and disease severity in 10 psoriasis patients during a 6-month treatment. Our results demonstrate that the frequency of Tfh17 cells was significantly increased in psoriasis patients and was positively correlated with psoriasis area and severity index (PASI) score, a marker of disease severity ( P < 0.05). During the follow-up period, the frequencies of Tfh17 cells decreased, and reductions in PASI scores were observed. Moreover, IL-21R expression on B cells was significantly increased in patients with psoriasis vulgaris ( P < 0.05). Interestingly, IL-21R levels on B cells were correlated with both PASI score and the frequency of Tfh17 cells ( P < 0.05). In conclusion, this study is the first investigation of the distribution of circulating Tfh subsets in psoriasis. These results deepen our understanding of the immune state of psoriasis patients. Our data also indicate that Tfh17 cells may not be good biomarkers for diagnosing psoriasis but may be potential biomarkers of disease severity in psoriasis. [ABSTRACT FROM AUTHOR]

Rationale With the amounts and types of new psychoactive substances (NPSs) increasing rapidly in recent years, an excellent high-throughput method for the analysis of these compounds is urgently needed. In this article, a rapid screening method and a quantitative analysis method for 11 NPSs are described and compared, respectively. Method A simple direct analysis in real time mass spectrometry (DART-MS) method was developed for the analysis of 11 NPSs including three categories of these substances present on the global market such as four cathinones, one phenylethylamine, and six synthetic cannabinoids. In order to analyze these compounds quantitatively with better accuracy and sensitivity, another rapid analytical method with a low limit of detection (LOD) was also developed using liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (LC/QTOFMS). Results The 11 NPSs could be determined within 0.5 min by DART-MS. Furthermore, they could also be separated and determined within 5 min by the LC/QTOFMS method. The two methods both showed good linearity with correlation coefficients ( r2) higher than 0.99. The LODs for all these target NPSs by DART-MS and LC/QTOFMS ranged from 5 to 40 ng mL−1 and 0.1 to 1 ng mL−1, respectively. Confiscated samples, named as 'music vanilla' and 'bath salt', and 11 spiked samples were firstly screened by DART-MS and then determined by LC/QTOFMS. Conclusions The identification of NPSs in confiscated materials was successfully achieved, and the proposed analytical methodology could offer rapid screening and accurate analysis results. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An effective two-level self-organizing map (SOM) neural network for direction of arrival (DOA) of sound signals estimation is proposed. The approach is based on the distance difference of arrival (DDOA) and a uniform linear sensor array in a 2D plane; it performs a nonlinear mapping between the DDOA vectors and angles of arrival (AOA). We found that the topological order of DDOA vectors and AOAs of same signals is uniform; thus, the topological order preserving of SOM network makes it valid to estimate AOA through DDOA. From the results of simulations and lake experiments, it is shown that the network has the advantage of accuracy and robustness, can be trained in advance, and is easy to implement. [ABSTRACT FROM AUTHOR]

The architecture and parameter initialization of wavelet neural network are discussed and a novel initialization method is proposed. The new approach can be regarded as a dynamic clustering procedure which will derive the neuron number as well as the initial value of translation and dilation parameters according to the input patterns and the activating wavelets functions. Three simulation examples are given to examine the performance of our method as well as Zhang's heuristic initialization approach. The results show that the new approach not only can decide the WNN structure automatically, but also provides superior initial parameter values that make the optimization process more stable and quickly. [ABSTRACT FROM AUTHOR]

The Guposhan- Huashan district is an important W- Sn- Sb- Zn-( Cu) metallogenic area in South China. It is located in the middle-west segment of the Nanling Range. Granitoids in the Guposhan- Huashan district possess certain properties of A-type or I-type granites. The W- Sn- Sb- Zn mineralization in the district is closely associated with magma emplacement. Two igneous biotite and seven hydrothermal muscovite samples from skarn, veins and greisenization ores were analyzed by Ar- Ar methods. Two igneous biotite samples from fine-grained quartz monzodiorite and fine-grained biotite granite show plateau ages of 168.7 ± 1.9 Ma and 165.0 ± 1.1 Ma, respectively. Seven hydrothermal muscovite samples from ores yield plateau ages as two groups: 165 Ma to 160 Ma and 104 Ma to 100 Ma. These data suggest that the emplacement of fine-grained granitoids in this district is coeval with the main phase magma emplacement, different from previous studies. The W- Sn- Sb- Zn mineralization took place in two stages, i.e. the Middle- Late Jurassic and early Cretaceous. W- Sn mineralization in the Guposhan- Huashan district is closely related to the magmatism, which was strongly influenced by underplating of asthenospheric mantle along trans-lithospheric deep faults and related fractures. [ABSTRACT FROM AUTHOR]

Rationale: With the development of various imaging techniques, the deformation-based morphometry (DBM) method provides an objective automatic examination of the whole brain. Objectives: This study aims to assess the abnormalities in the brains of first-episode schizophrenia (FES) patients treated with quetiapine using another advanced nonrigid registration method, hierarchical attribute matching mechanism for elastic registration, through the application of DBM in the entire brain. Methods: Thirty FES patients and 30 normal controls were grouped by age and handedness and subjected to magnetic resonance imaging examination. The patients had relatively short durations of untreated psychosis (DUP; 6.4 ± 5.2 months), and only a single antipsychotic drug, quetiapine (dosage, 200 ± 75 mg), was used for treatment. Statistically significant changes in regional volume were analyzed via DBM. In addition, a voxel-wise analysis of correlations between the duration of treatment or dosage and volume was also performed. Results: Compared with control subjects, FES patients showed contracted regions located in Brodmann area (BA) 42 and BA 19. By contrast, expanded regions were observed in BA 38, BA 21, BA 6 and 8, and left cerebellum. A negative correlation was observed between dosage and volume in the hippocampus, while a positive correlation was found in the caudate. Meanwhile, a negative correlation was observed between duration of treatment and volume in BA 38. Conclusion: Both regional volume reductions and increases were detected in the brains of FES patients treated with quetiapine compared with healthy control subjects. Such differences may be partially relevant to dosage and treatment duration in clinic. [ABSTRACT FROM AUTHOR]

Abstract: West Junggar is featured with a wide spread of Late Carboniferous–Early Permian A-type granites. Systematic comparison of the Yangzhuang granite porphyry and the regional coeval A-type granites (RCAG) shows that: (1) all the Late Carboniferous–Early Permian A-type granites are of the A2 group except the Yangzhuang granite porphyry; (2) the Nb and Ta contents of the Yangzhuang granite porphyry are nearly 10 times that of the RCAG while Ti content is more depleted; (3) εNd (t) of the Yangzhuang granite porphyry is slightly lower and the Sr isotope has a wider range relative to the RCAG. Previous research revealed that highly incompatible elements including Nb and Ta can be transferred into the mantle wedge by precipitation of amphibole from the ascending fluids generated by dehydration of subducted slab. It is inferred that enhanced heat flux brought by the Late Carboniferous ridge subduction decomposed amphibole in the mantle wedge to generate Nb and Ta-rich melt and finally produced the Yangzhuang granite porphyry. [Copyright &y& Elsevier]

ABSTRACT BACKGROUND AND PURPOSE This study aims to investigate the regional changes in the early onset of blindness using the deformation-based morphometry (DBM) method. METHODS A total of 15 early blindness and 30 gender- and age-matched sighted control subjects were recruited for the study. Statistically significant changes in regional volume were analyzed using DBM through HAMMER registration. Using this technique, changes in regional tissue volume can be detected on the basis of the deformation field derived from the warping subject to the template image. A voxelwise estimation of the morphological differences between the two groups can be acquired after applying a threshold ( P < .001, uncorrected) to the statistic maps. RESULTS Regions with enlarged volume in the brains of blind subjects are mainly localized in the left associated visual cortex, posterior cingulated cortex, and cerebellum, whereas volume reductions are primarily localized in the left early visual cortex. CONCLUSIONS DBM is an effective method for detecting entire brain structural changes in blindness. Visual deprivation actually alters the local structural organization during the early critical periods of neurodevelopment. Volume increases outside the occipital lobe detected with DBM may suggest compensatory adaptations. [ABSTRACT FROM AUTHOR]

The purpose of this research was to design and realize a real-time tele-monitoring system with multiphysiological parameters using the Internet. Both the ClientServer (CS) mode and Peer-to-Peer (P2P) mode were used in the system's network communication. The CS mode is used to upload, retrieve, and download physiological data. The P2P mode provides realtime tele-monitoring and video chatting between doctors and patients. Experiment results show that P2P technology could efficiently improve the transmission speed of the physiological parameters. This study demonstrates an effective method of remote monitoring of physiological parameters in real time. [ABSTRACT FROM AUTHOR]

Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimation method based on compressed sensing (CS) is a new method proposed in recent years. It has received widespread attention because it can realize the direction-of-arrival estimation under small snapshots. However, this method will cause serious distortion in a strong noise environment. To solve this problem, this paper proposes a DOA estimation algorithm based on the principle of CS and density-based spatial clustering (DBSCAN). First of all, in order to make the estimation accuracy higher, this paper selects a signal reconstruction strategy based on the basis pursuit de-noising (BPDN). In response to the challenge of the selection of regularization parameters in this strategy, the power spectrum entropy is proposed to characterize the noise intensity of the signal, so as to provide reasonable suggestions for the selection of regularization parameters; Then, this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis, so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate; Finally, calculate the cluster center value of each cluster, the number of clusters is the number of signal sources, and the cluster center value is the final DOA estimate. The proposed method is applied to the simulation experiment and the micro electro mechanical system (MEMS) vector hydrophone lake test experiment, and they are proved that the proposed method can obtain good results of DOA estimation under the conditions of small snapshots and low signal-to-noise ratio (SNR). [ABSTRACT FROM AUTHOR]

Background: Many previous studies have reported factors that contribute to health-related quality of life (HRQoL) for a single skin disease. However, little is known about generalized factors associated with HRQoL across skin diseases. The objective of this study was to investigate overall HRQoL, and to identify factors related to severely impaired HRQoL among patients with 16 different skin diseases.Methods: A cross-sectional study of 9845 patients with skin disease was conducted in 9 hospitals in China. HRQoL was assessed with the Chinese version of the Skindex-29 which measures dermatology-specific health along three domains (symptoms, emotions and functioning). With the published Skindex-29 cut-off scores for severely impaired HRQoL, logistic regression models assessed the relationship between severely impaired HRQoL and demographic/clinical characteristics, with adjustments for different skin diseases. To guarantee the models' convergence, 16 skin diseases with frequencies of at least 100 were included, and the sample size was 8789.Results: Emotions was the most impaired aspect of HRQoL. Co-existing chronic diseases, 3 years or longer duration, and more severity were identified as associated factors for severely impaired HRQoL for each Skindex-29 domain, and for the aggregate. Being female, under 45 years old, and consuming alcohol were associated with a severely impaired emotion domain; Lack of exercise and smoking were associated with severely impaired symptoms and function domains, respectively.Conclusions: Skin diseases can affect many facets of HRQoL, but the emotional impairment deserves more attention. In addition to skin disease severity, this study shows that other chronic diseases and long duration are correlated with severely impaired HRQoL for patients with 16 clinical common skin diseases. This suggests the need for increased awareness in treating skin disease as a chronic disease. It also suggests that disease management decisions should consider HRQoL improvement, especially emotional conditions, when making management decisions. [ABSTRACT FROM AUTHOR]

In this paper we proposed a wearable electrocardiogram (ECG) telemonitoring system for atrial fibrillation (AF) detection based on a smartphone and cloud computing. A wearable ECG patch was designed to collect ECG signals and send the signals to an Android smartphone via Bluetooth. An Android APP was developed to display the ECG waveforms in real time and transmit every 30 s ECG data to a remote cloud server. A machine learning (CatBoost)-based ECG classification method was proposed to detect AF in the cloud server. In case of detected AF, the cloud server pushed the ECG data and classification results to the web browser of a doctor. Finally, the Android APP displayed the doctor's diagnosis for the ECG signals. Experimental results showed the proposed CatBoost classifier trained with 17 selected features achieved an overall F1 score of 0.92 on the test set (n = 7270). The proposed wearable ECG monitoring system may potentially be useful for long-term ECG telemonitoring for AF detection. [ABSTRACT FROM AUTHOR]

Underwater acoustic technology is an important means of detecting the ocean. Due to the complex influence of the marine environment, there is a lot of noise and baseline drift in the signals collected by hydrophones. In order to solve this problem, this paper proposes a denoising and baseline drift removal algorithm for MEMS vector hydrophone based on whale-optimized variational mode decomposition (VMD) and correlation coefficient (CC). Firstly, the power spectrum entropy (PSE), which reflects the variation characteristics of the signal frequency is selected as the fitness function of the whale-optimization algorithm to find the parameters (K,α) of the VMD. It is easier to find the global optimal solution of the parameters by combining the whale-optimization algorithm. Then, using the VMD algorithm after obtaining the parameters, the original signal is decomposed to obtain the intrinsic mode functions (IMFs), and calculating the correlation coefficients (CCs) between the IMFs and the original signal. Finally, the CC threshold is used to remove the noise IMFs, and the rest of the useful IMFs are reconstructed to complete the denoising and baseline drift removal process of the original signals. In the simulation experiments, the algorithm proposed in this paper shows better performance by comparing conventional digital signal-processing methods and the related algorithms proposed recently. Applied in the experiments of a MEMS hydrophone, the effectiveness of the proposed algorithm is also verified. This algorithm can provide new ideas for signal denoising and baseline drift removal. [ABSTRACT FROM AUTHOR]

It is critical for microwave ablation (MWA) treatment planning to evaluate the changes of thermal coagulation zones. In MWA procedures, the shapes and sizes of thermal coagulation zones are gradually evolving over time. To this end, a novel characterization and mapping method of thermal coagulation zones is presented in this article. Firstly, finite element method (FEM) models of temperature distributions for 40, 45, 50, 55, and 60 W microwave ablations were built to derive thermal ablation data of ex vivo porcine livers and were compared with experimental results. Secondly, growth models of characteristic lengths were fitted. Finally, characterization functions of thermal coagulation zones were developed using these growth models. In addition, shape variation factors were incorporated to handle the minor shape variations of thermal coagulation zones. Experimental results showed that these characterization functions could accurately represent the changes of thermal coagulation zones. The standard deviations between prediction results and simulated values were less than 1 mm. The comparative results were statistically analyzed by paired t test (P > 0.05), indicating no significant differences. The proposed method can simply and effectively predict the changes of MWA coagulation zones with time, thus providing reliable coagulation dimensions for the thermal ablation therapies. [ABSTRACT FROM AUTHOR]