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Change detection of high-resolution remote sensing images is an important task in earth observation and was extensively investigated. Recently, deep learning has shown to be very successful in plenty of remote sensing tasks. The current deep learning-based change detection method is mainly based on conventional long short-term memory (Conv-LSTM), which does not have spatial characteristics. Since change detection is a process with both spatiality and temporality, it is necessary to propose an end-to-end spatiotemporal network. To achieve this, Conv-LSTM, an extension of the Conv-LSTM structure, is introduced. Since it shares similar spatial characteristics with the convolutional layer, L-UNet, which substitutes partial convolution layers of UNet-to-Conv-LSTM and Atrous L-UNet (AL-UNet), which further using Atrous structure to multiscale spatial information is proposed. Experiments on two data sets are conducted and the proposed methods show the advantages both in quantity and quality when compared with some other methods.

Detecting the evolutionary stages of social media events such as Twitter and Sina Weibo is beneficial for enterprises and governments to take necessary actions before emergent phenomena become uncontrollable. Prior work on event extraction from microblogs mostly focused on extracting event summary. However, the evolutionary stages of an event can provide more details about the evolution of the event, which are more critical to predict the future trend of the event. On the other hand, many events have a lifecycle-like evolutionary property, i.e., beginning, developing, climax, descending, and disappearing. Such a feature is helpful to detect the evolutionary stages of events. Thus, we propose a graph-based approach to represent and extract the evolutionary stages of events from microblogs based on this consideration. The contributions of this study are threefold. First, differing from existing methods that use a keyword set or a microblog set to represent an event, we propose a Keyword Popularity Information Graph (KPIG) to represent the keywords and the statistical information of events using a graph. With this mechanism, we can capture both the textual information and the statistical information of an event. Second, based on the KPIG graph, we present a graph-kernel-based approach to measure the similarity among events. Third, we conduct extensive experiments on a real dataset and compare our proposal with several competitor algorithms. The results show that our approach outperforms other competitors in terms of various metrics.

Purpose To explore the clinical significance of plasma pyruvate kinase M2 (PKM2) in assessing the incidence and prognosis of acute leukemia. Methods Plasma samples from 56 acute myeloid leukemia (AML) patients, 40 acute lymphoblastic leukemia (ALL) patients, and 66 plasma samples from healthy individuals were collected. The level of plasma PKM2 was detected by enzyme-linked immunosorbent assay. The clinical significance of PKM2 in acute leukemia was assessed by analyzing receiver operating characteristic and survival curves. Results The plasma levels of PKM2 in AML or ALL patients were significantly higher than those in healthy individuals, respectively. PKM2 can be used as a potential diagnostic index with the AUC of 0.827 for AML and 0.837 for ALL. The level of plasma PKM2 in ALL patients with a BCR/ABL-positive genotype was significantly higher than that in patients with a BCR/ABL-negative genotype (p

BACKGROUND The brain is the most complex organ in the human body. Treatment for a glioma always involves a multi-disciplinary team. Nursing care in fast-track surgery or enhanced recovery after surgery is such kind of work implemented by an interdisciplinary team to provide services to patients to improve their outcomes. AIM To explore the effects of nursing care in fast-track surgery on postoperative pain, psychological state, and patient satisfaction with nursing for glioma. METHODS From June 2018 to June 2020, 138 patients who underwent operation for glioma at Cancer Hospital Affiliated to Chongqing University were selected. They were categorized into groups according to different nursing care that they received. Of them, 69 patients receiving nursing care in fast-track surgery were included in an experimental group, and 69 patients receiving conventional postoperative nursing were included in a control group. Visual analogue scale was used to evaluate postoperative pain in the two groups immediately after the operation and at 3 d after the operation. Self-rating anxiety scale (SAS) and self-rating depression scale (SDS) were used to evaluate the psychological status of patients immediately after operation and on the 3rd postoperative day. A self-made satisfaction scale for patient satisfaction with nursing was used to evaluate and compare patient satisfaction with nursing between the two groups. RESULTS Time to excretion, time to out-of-bed activities, and length of hospital stay were significantly shorter in the observation group than in the control group (P < 0.05). There was no significant difference in duration of operative time or intraoperative bleeding between the two groups (P > 0.05). There was no significant difference in postoperative pain score between the two groups (P > 0.05). The pain score was significantly lower in the observation group than in the control group at 3 d after the operation (P < 0.05). There was no significant difference in postoperative SAS or SDS score between the two groups (P > 0.05). SAS and SDS scores were significantly lower in the observation group than in the control group at 3 d after operation (P < 0.05). The rate of patient satisfaction with nursing was 94.2% in the observation group, which was significantly higher than that (81.2%) of the control group (P < 0.05). CONCLUSION Nursing care in fast-track surgery can relieve postoperative pain, anxiety, and depression, and improve patient satisfaction with nursing in patients with glioma, which is worthy of clinical application.

In this paper, conventional thermogravimetric analysis and a new congruent–mass thermogravimetric analysis were used to study the reaction mechanism of the co-pyrolysis process of coal and biomass in the thermogravimetric analyzer, the effects of heating rate and carrier gas flow rate on co-pyrolysis were investigated, and kinetic analysis was conducted for the major pyrolysis stages to explore whether there was a synergistic effect in the co-pyrolysis process. The surface morphology of pyrolytic coke was evaluated by the fractal dimension method. The results show that congruent–mass thermogravimetric analysis can compare the interactions in the co-pyrolysis process more intuitively and reduce the influence of initial mass on the determination of interaction relationship. Synergistic effect appears in co-pyrolysis of coal and biomass. With the increase of heating rate, the thermogravimetric hysteresis appeared and the thermogravimetric curve gradually moved to the high temperature region. With the increase of carrier gas flow rate, the synergistic effect weakens. The kinetics of different reaction stages was analyzed by Coats–Redfern method; the results show that the activation energy required in the main co-pyrolysis stage of the mixture is lower than that in the pyrolysis stage alone. The micromorphology shows that biomass coke has a more developed pore structure than coal, and the box dimension indicates that co-pyrolysis increases the surface irregularity of coke. It is of great significance to judge the interaction mechanism of two or even multiple mixed samples in the process of co-pyrolysis.

This study evaluated age-associated morphology changes in the cranial base, facial development, and upper airway of patients with Treacher Collins syndrome (TCS). A total of 33 preoperative computed tomographic images (TCS, n = 14; control, n = 19) were included in the study and divided into three age-related subgroups (2-6 years, 7-18 years, and older than 18 years). Linear, angular cephalometric measurements and upper airway volumes were collected. All measurements were analyzed using ProPlan CMF software (version 3.0; Materialize, Leuven, Belgium). The association between aging and upper airway morphology was analyzed. Compared to control subjects, TCS patients had a smaller cranial base, maxilla, and nose; they also had reduced upper airway volume compared to control subjects. The observed differences were most significant in patients between the ages of 7 and 18 years. This study used computed tomography-based three-dimensional analyses to provide a detailed description of age-related changes that occur in craniofacial measurements and upper airway volumes in children, adolescents, and young adult patients with TCS in China. These data can be used to evaluate individual patients with TCS and to select treatment to improve the growth of the craniofacial region.

In this paper, a novel small-decentralized desalination device is presented for increasing the temperature difference between brackish water and glass cover, so as to enhance the solar still’s freshwater productivity. This novel solar still device is based on installing a lens in front of the single slope solar still, and two lenses on still’s both sides, and a reflector over the back side of the solar still. The main objective of such novel still is to concentrate sunrays at the still’s bottom basin, through the refraction function of Fresnel lens. Furthermore, this novel still makes the reflector transferring its reflected sunrays to the solar still’s basin. Experiments are conducted under the climate conditions in Hangzhou city, China, for testing the novel still’s operational performance, and internal heat and mass transfer characteristics. Assessment of the novel still’s feasibility is performed based on energy, exergy, exergoeconomic, and enviroeconomic methodologies, as well as energy payback time. Results show that the productivity of novel still is 32% higher than that of conventional still, and novel solar still enhances the average hourly energy efficiency by 97.73%, compared to conventional solar still. While, the corresponding value of hourly exergy efficiency is also enhanced by 43.713%. Due to the higher energy and exergy outputs of novel still throughout its lifetime, the novel solar still proposed in this study mitigates more CO2 compared to the conventional still. Overall, incorporation three lenses and one reflector with the still is found promising in terms of freshwater yield, cost, and energy payback time compared to conventional one. Exergoeconomic and environmental parameters of the novel solar still are found more effective compared to the conventional one.

Background Diabetic nephropathy (DN) is a primary complication of diabetes mellitus (DM). The pathology of DN is still vague, and diagnostic accuracy is not enough. This study was performed to identify miRNAs and genes that have possibilities of being used as therapeutic targets for DN in type 2 DM. Methods Human miRNA data GSE51674 and gene data GSE111154 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) in the kidney between control and DN patients were screened out. The competing endogenous RNA (ceRNA) network was constructed, and key lncRNA-miRNA-mRNA pairs were selected accordingly. Potential drugs targeting DEGs were screened out and validated using PCR analysis. Results Totally, 83 DEmiRNAs and 293 DEGs were identified in GSE51674 and GSE111154, respectively. Thirteen of the top 20 DEmiRNAs (10 up and 10 down) targeted to 47 DEGs. In the ceRNA network, RP11-363E7.4/TTN-AS1/HOTAIRM1-hsa-miR-106b-5p-PTGER3 and LINC00960-hsa-miR-1237-3p-MMP-2 interaction pairs were identified as the key ceRNA network. Interestingly, PTGER3 and hsa-miR-1237-3p were downregulated, and MMP-2 and hsa-miR-106b-5p were upregulated in the kidney of patients with DN compared with normal controls, respectively. PTGER3 and MMP-2 were targeted by drugs including iloprost, treprostinil, or captopril, and the deregulation of the two genes was confirmed in the plasma samples from patients with DN as compared with controls. Conclusions We speculated that the RP11-363E7.4/TTN-AS1/HOTAIRM1-hsa-miR-106b-5p-PTGER3 and LINC00960-hsa-miR-1237-3p-MMP-2 networks were associated with diabetic renal injury.

In this study, we aim to provide a deep convolutional network based femoral neck fracture detection system on radiographs for emergency patients. We retrospectively collected 1,491 frontal pelvic radiographs from three institutions and assigned them to the following data sets: primary dataset (710 radiographs, to fine-tune and validate the initial model called the Digital Radiography Fracture Detection System [DR-FDS]), internal test set 1 (189 radiographs) and 2 (235 radiographs), and external test set 1 (189 radiographs) and 2 (168 radiographs). Per-bounding box recall and precision and per-image sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were computed. We randomly extracted 300 radiographs from the above test sets and compared their effect on the diagnostic accuracy and efficiency of fine-tuned model-assisted and unassisted clinicians. The fine-tuned DR-FDS showed a better overall performance in detecting femoral neck fractures than did the initial DR-FDS. The fine-tuned DR-FDS achieved AUC values of 0.9526 (95%CI, 0.9048–0.9767) and 0.9633(95%CI, 0.9346-0.9797) in internal test sets 1 and 2. In external test sets 1 and 2, this model also achieved promising results with AUC values of 0.9231 (95%CI, 0.8779–0.9520), and 0.9937 (95%CI 0.9739–0.9985), respectively. The clinicians showed a statistically significant increase in specificity, sensitivity, and accuracy for the identification of minimal/undisplaced fracture and a decrease in the average reading time. The object detection model that is fine-tuned has high sensitivity and specificity and the universal ability to detect and locate femoral neck fractures on pelvic radiographs.

Objective: To investigate the correlation between high-risk human papillomavirus (HR HPV)-negative cervical lesions and cervical microenvironment in Inner Mongolia, China, and to find the pathogenic factors of HR HPV-negative cervical lesions. Materials and methods: 74 cases of HR HPV-negative healthy women and 80 cases of patients with cervical lesions (28 cases of LSIL, 49 cases of HSIL and 3 cases of CSCC) were selected as the study group; 26 cases of HPV-positive women and 352 cases of patients with cervical lesions (108 cases of LSIL, 214 cases of HSIL and 30 cases of CSCC) were control group. Questionnaires were collected from the study group and the control group and specimens were collected. Gram staining, hematoxylin and eosin staining microscopy, and substrate colorimetry method were used to detect vaginal micro-ecological indicators; ELISA was used to detect the concentration of SIgA, IgG, IL-2 and IL-10 in vaginal lavage fluid. Genetic testing was used to detect HPV, mycoplasma, and chlamydia infection. The changes of vaginal micro-ecology evaluation index and local immune factor concentration in healthy women and cervical lesions of all grades in the study group and the control group were compared. Results: Patients with cervical lesions, compared with healthy women, had a decrease in dominant lactobacilli and dysbacteriosis (P

Background The aim of this study was to clarify the characteristics of gene mutation related to multidrug-resistance (MDR) of tuberculosis (TB) and diabetes in Zunyi. Methods A total 763 patients with TB were screened for TB-DNA, TB-RNA, and acid-fast staining (all were positive). They were divided into the tuberculosis (TB) group and the diabetes mellitus-tuberculosis (DM-TB) group. We compared and analyzed the MDR gene rpoB, KatG, and inhA characteristics of gene mutations in the two groups by polymerase chain reaction (PCR)-reverse dot hybridization, and collected relevant clinical data to explore its correlation with the occurrence of multidrug resistance. Results Multidrug resistance occurred in 32 of the 525 patients in the TB group, and extensive drug resistance occurred in 15 of the 207 patients in the DM-TB group. In the DM-TB group, the mutation rates of ropBS531L and ropB531 (both 53.33%) were lower than those of the TB group (both 59.38%) in rifampicin resistance mutations. Most of the mutations were at the KatG315N site, conferring isoniazid resistance. Conclusions The mutation sites of multidrug-resistant patients in Zunyi are mainly ropB531 and ropBS531L mutations, which are prone to co-occurrence; patients with MDR-TB alone are prone to mutations at the KatG315N site, while patients with diabetes and MDR-TB are more likely to have inhA15M site mutations.

We sought to determine whether high-density lipoprotein (HDL) function was altered in gout patients.The study included 95 gout patients and 68 healthy controls. The concentrations of interleukin (IL)-1β and IL-9 were measured by ELISA, and indicators such as blood uric acid, liver and kidney function, blood glucose, and blood lipids were detected. To test for the anti-inflammatory and reverse cholesterol transport (RCT) function of HDL, 11 gout patients and 11 healthy controls were randomly selected for the BioVision cholesterol efflux test, which detects the RCT activity of HDL. To assess the anti-inflammatory function of HDL, cells in co-culture with HDL were treated with inflammatory stimuli such as tumor necrosis factor-α (TNF-α), and then, the cells were assayed for the expression of intercellular adhesion molecules (ICAMs) and vascular cell adhesion molecule-1 (VCAM-1).In total, this study enrolled 163 participants, including 95 non-hyperlipidemic gout patients and 68 healthy controls. IL-1β and IL-9 levels were significantly higher in the gout group than in the control group (85.26 ± 23.16 vs. 41.47 ± 6.48 and 33.77 ± 12.68 vs. 23.66 ± 4.53, respectively, P0.001). Additionally, plasma IL-1β and IL-9 levels were increased along with those of blood uric acid (RThe anti-inflammatory activities of HDLs are impaired in gout patients. Key Points • Gout patients show chronic inflammation. • The anti-inflammatory activity of high-density lipoprotein is impaired in gout patients.

Background This study aimed to investigate the correlation between the level of HPV16 and HPV18 in patients with cervical lesions and the local vaginal immunity after receiving treatment with different degrees of cervical intraepithelial neoplasia (CIN) and cervical squamous cell carcinoma (CSCC). Methods One hundred and thirty-six patients with LSIL (grade 1 CIN or CIN 1), 263 patients with HSIL (grade 2 and 3 CIN or CIN 2 and 3), and 33 patients with CSCC pathologically confirmed between November 2012 and September 2016 were assigned to the test group and 100 healthy women in the same period were assigned to the control group. ELISA was used to determine the levels of SIgA, IgG, IL-2, and IL-10 and the IL-2/IL-10 ratio in vaginal lavage fluid in the test group (before treatment and 3, 6, and 12 months after treatment) and the control group, respectively. Gene chip technology was adopted to test the HPV infection in the test group (before treatment and 3, 6, and 12 months after treatment) and the control group, respectively. Results The results showed that the levels of SIgA, IgG, and IL-10 were positively correlated with the degree of cervical lesions and IL-2/IL-10 was negatively correlated with the degree in all patients before treatment. The levels of SIgA, IgG, and IL-10 were positively correlated with the degree of cervical lesions and IL-2/IL-10 was negatively correlated with the degree in HPV16 and HPV18-infected patients before receiving the treatment. Conclusions The recovery after the treatment of HPV infection is time-dependent and the immune system of patients with CIN starts to recover in the 6th month after treatment, early intervention is not recommended. However, the immune system is approximately in a normal sate at 12 months after treatment, at which time the efficacy can be evaluated, and clinical intervention can be initiated if necessary. The level of local immune factors in the vagina can be monitored to determine the progression and prognosis of patients’ cervical lesions.

Major depressive disorder (MDD) is a highly prevalent debilitating psychiatric disease and a serious public health problem worldwide. Brain structural MRI and postmortem studies on patients with depression have revealed changes in the anatomy and functionality in various brain regions, including the amygdala, thalamus, hippocampus, and prefrontal cortex (PFC). The alterations in these brain regions could be a result, in part, of the dysregulation of the neurotrophic factors. Neuregulin1 (NRG1) is one of the neurotrophic factors, and our previous study showed that the NRG1-ErbB4 signaling pathway plays a critical role in epilepsy. In this study, we established a chronic social defeat stress (CSDS) model to investigate the role of the NRG1-ErbB4 signaling pathway in depression-like behaviors. In CSDS mice, we found that the NRG1 protein expression levels were significantly decreased both in the medial prefrontal cortex (mPFC) and hippocampus, while phosphorylated ErbB4 only decreased in the mPFC. In addition, lateral ventricle NRG1 administration significantly rescued depression-like behaviors in the susceptible group. The current study suggests that the NRG1-ErbB4 signaling pathway may exert a protective role in MDD.

This paper explores the diagnosis of deep invasive endometriosis through retrospective data analysis, including deep infiltration and magnetic resonance imaging. The literature retrospectively collected data from 21 patients with deep invasive endometriosis who were admitted from 2012 to 2018. The patients were confirmed to have pain and nerve growth factor (NGF) receptor expression levels after operation and underwent vaginal color ultrasound and magnetic resonance imaging before surgery. The diagnostic results of color Doppler ultrasound and magnetic resonance imaging were retrospectively analyzed and compared with the surgical results, and the cumulative site and anatomic abnormalities of the diagnosis of deep invasive endometriosis were analyzed to determine the NGF receptor table. Through research it has been found that deep invasive endometriosis mainly involves the uterine fibula ligament, vagina, uterus rectum, rectum, ureter, and so forth. Patient pain is related to the expression level of NGF receptor, and its magnetic resonance mainly manifests as signals and structural obstacles, irregular thickening of the affected area, or nodular formation and deformation of adjacent tissues and organs. Through research and demonstration of deep invasive endometriosis, transvaginal color ultrasound and magnetic resonance imaging can not only accurately locate the expression levels of pain and NGF receptors, but also show the extent of the lesions, thereby studying pain and NGF receptor expression, which is an important method for preoperative examination and postoperative follow-up.

OBJECTIVE This retrospective study aimed to evaluate the diagnostic efficiency of simultaneous positron emission tomography/magnetic resonance imaging (PET/MR) in differentiating the benign and malignant of pancreatic tumors as well as the differentiation of pancreatic cancer. METHODS A total of 62 patients with suspected pancreatic tumors, diagnosed by PET/MR examinations, were collected in this study. These patients were divided into benign group and malignant group. The characteristics of the morphological MR, apparent diffusion coefficient (ADC), the mean of standardized uptake value (SUVmean), maximum values of standardized uptake value (SUVmax), in lesions were measured, and the novel parameters SUVpeak/ADC and SUVmax/ADC were constructed. The diagnostic efficiency for differentiating the benign and malignant lesions was analyzed by receiver operating characteristic (ROC) curve, and the diagnosis efficiency for the differentiation of pancreatic cancer was analyzed by Spearman correlation analysis. RESULTS In differentiating the benign and malignant of pancreatic tumors, the diagnostic efficiency increased in the order of SUVpeak (AUROC: 0.760), SUVmax (AUROC: 0.774), T1T2 (AUROC: 0.789), ADC (AUROC: 0.817), SUVpeak/ADC (AUROC: 0.836), SUVmax/ADC (AUROC: 0.847). There was no significant correlation for SUVmax, SUVpeak, ADC, SUVpeak/ADC, and SUVmax/ADC with the differentiation of pancreatic cancer (P > 0.05). Besides, T1T2 was not significantly correlated to the differentiation of pancreatic cancer (P = 0.026, r = -0.406). CONCLUSION The integration of PET/MR imaging could be used to efficiently diagnose whether the pancreatic tumor was benign or malignant. The SUVmax/ADC was the most efficient metric, while it could not help in the differentiation of pancreatic cancer.

Mandibular angle osteotomy with outer cortex grinding has become the preferred cosmetic procedure for correcting square faces. After surgery, bone hyperplasia at the mandibular angle affects the operation result. This study evaluated the effect of the masticatory muscles on bone repair. From January 2016 to January 2019, patients who underwent mandibular angle osteotomy with outer cortex grinding were retrospectively reviewed. Computed tomography data of these patients were collected, and the bone volume of the mandibular angle changes and its correlation with masticatory muscle morphology were analyzed. Computed tomography data measurement results showed that a large amount of bone in the mandibular angle area was removed by the operation; however, the long-term follow-up results showed that there was bone hyperplasia in the mandibular angle areas. Compared with the immediate postoperative bone volume, the difference was statistically significant (P

The coastal zone is one of the most important features on the earth’s surface; therefore, it is imperative to extract the coastline, a representative coastal zone feature with high quality. Previou...

Background: Repetitive transcranial magnetic stimulation (rTMS) has therapeutic effects on craving in methamphetamine (METH) use disorder (MUD). The chronic abuse of METH causes impairments in executive function, and improving executive function reduces relapse and improves treatment outcomes for drug use disorder. The purpose of this study was to determine whether executive function helped predict patients' responses to rTMS treatment.Methods: This study employed intermittent theta burst stimulation (iTBS) rTMS modalities and observed their therapeutic effects on executive function and craving in MUD patients. MUD patients from an isolated Drug Rehabilitation Institute in China were chosen and randomly allocated to the iTBS group and sham-stimulation group. All participants underwent the Behavior Rating Inventory of Executive Function - Adult Version Scale (BRIEF-A) and Visual Analog Scales (VAS) measurements. Sixty-five healthy adults matched to the general condition of MUD patients were also recruited as healthy controls.Findings: Patients with MUD had significantly worse executive function. iTBS groups had better treatment effects on the MUD group than the sham-stimulation group. Further Spearman rank correlation and stepwise multivariate regression analysis revealed that reduction rates of the total score of the BRIEF-A and subscale scores of the inhibition factor and working memory factor in the iTBS group positively correlated with improvements in craving. ROC curve analysis showed that working memory (AUC = 87.4%; 95% CI = 0.220, 0.631) and GEC (AUC = 0.761%; 95% CI = 0.209, 0.659) had predictive power to iTBS therapeutic efficacy. The cutoff values are 13.393 and 59.804, respectively.Conclusions: The iTBS rTMS had a better therapeutic effect on the executive function of patients with MUD, and the improved executive function had the potential to become a predictor for the efficacy of iTBS modality for MUD treatment.Clinical Trial Registration:ClinicalTrials.gov, identifier: ChiCTR2100046954.

Due to the irregularity of colorectal tumor contours, it is a challenging task for clinicians to segment colorectal tumors manually in CT scans. To solve this problem, a novel algorithm based on a convolutional neural network with an attention mechanism is proposed to automatically achieve tumor segmentation. The proposed network consists of three major modules: an encoder module, which is fed CT scans to attain the feature map; a dual attention module, which includes a channel attention module and a position attention module to obtain more contextual information in the deep layer of the network; and a decoder module, which restores the feature map to the original size of the input images. We used 1131 CT slices of colorectal tumors to train and test the proposed network. Compared with U-Net and CE-Net, the Dice coefficient increased by 1.46% and 0.66% respectively, for our model. The comprehensive results show that the proposed network performs more effectively in colorectal tumor segmentation than the other methods.

The most important motivation for streamflow forecasts is flood prediction and longtime continuous prediction in hydrological research. As for many traditional statistical models, forecasting flood peak discharge is nearly impossible. They can only get acceptable results in normal year. On the other hand, the numerical methods including physics mechanisms and rainfall-atmospherics could provide a better performance when floods coming, but the minima prediction period of them is about one month ahead, which is too short to be used in hydrological application. In this study, a deep neural network was employed to predict the streamflow of the Hankou Hydrological Station on the Yangtze River. This method combined the Empirical Mode Decomposition (EMD) algorithm and Encoder Decoder Long Short-Term Memory (En-De-LSTM) architecture. Owing to the hydrological series prediction problem usually contains several different frequency components, which will affect the precision of the longtime prediction. The EMD technique could read and decomposes the original data into several different frequency components. It will help the model to make longtime predictions more efficiently. The LSTM based En-De-LSTM neural network could make the forecasting closer to the observed in peak flow value through reading, training, remembering the valuable information and forgetting the useless data. Monthly streamflow data (from January 1952 to December 2008) from Hankou Hydrological Station on the Yangtze River was selected to train the model, and predictions were made in two years with catastrophic flood events and ten years rolling forecast. Furthermore, the Root Mean Square Error (RMSE), Coefficient of Determination (R2), Willmott's Index of agreement (WI) and the Legates-McCabe's Index (LMI) were used to evaluate the goodness-of-fit and performance of this model. The results showed the reliability of this method in catastrophic flood years and longtime continuous rolling forecasting.

The urban sustainable development becomes an essential goal presented in “2030 Agenda for Sustainable development” by the United Nations. Urban land use and land cover (LULC) change prediction, which is a significant indicator to evaluate urban construction strategy, urges to be solved. Remote sensing technique and neural network, are two practical tools widely utilized in urban LULC change prediction. Because of the rapid improvement of remote sensing technique, urban data can be periodically captured in a short time interval. A large amount of data cause the conventional neural networks method having bad efficiency in dealing with it. Moreover, as human activities are in high intensity in the urban area, society related factors require to be taken into consideration in urban land change trend prediction. In this article, a self-adaptive cellular-based deep learning analysis method by utilizing the multisourced data is proposed for urban LULC change prediction. Multisourced data, including weather related data, economy related data, construction related data, and remote sensing data, are normalized and formalized by the proposed self-adaptive cellular-based method. Deep learning long short term memory neural network, which is an advanced model of recurrent neural network and has a strong ability in dealing with sequence data, is utilized to urban LULC change prediction. Remote sensing data captured from 1984 to 2016 are utilized to conduct experiments. Experiment results illustrate that the proposed method can effectively and efficiently make LULC change prediction, and the accuracy is up to $\text{93.1}\%$ .

BACKGROUND Sepsis is a devastating medical condition. In the USA, about 745 000 people are diagnosed with sepsis annually. Although many anti-inflammatory drugs have been used to manage sepsis, the treatment success rate is very low. This study was undertaken to examine the protective effects of naringenin on sepsis-induced kidney injury in rats. MATERIAL AND METHODS Sepsis was induced in Wistar albino rats by cecal ligation and puncture methods. Histological analysis was performed with hematoxylin and eosin (HE) staining. Reactive oxygen species (ROS) levels were determined by flow cytometery. TUNEL assay was used to demonstrate apoptosis. Sandwich ELISA method was used for the determination of urinary angiotensinogen, and protein expression was determined by Western blot analysis. RESULTS We found that naringenin decreased atrophy in the glomerulus and enabled maintenance of the capsule area and normal tubular cavity of the septic rats. Admistration of naringenin at the dosage of 10 and 20 mg/kg to sepsis rats caused significant reduction in the sepsis-induced apoptosis of kidney cells, accompanied by decrease in Bax and increase in Bcl-2 expression. Moreover, naringenin also decreased the ROS levels in septic rats and downregulated the expression of SOD, CAT, and APX. The effects of naringenin were also examined on the levels of urinary angiotensinogen in sepsis rats. We found that naringenin caused a significant decrease in urinary angiotensinogen levels of septic rats. CONCLUSIONS Naringenin appears to have potential in the treatment of sepsis.

Submarine piggyback pipeline is an important tool for oil and gas transport, especially, in the marginal oil field. When the scour happens in the seabed, the pipeline slides easily, which may cause...

Supplemental Digital Content is available in the text., Background: China has seen a burgeoning epidemic of obesity in recent decades, but few studies reported nationally on obesity across socio-demographic subgroups. We sought to assess the prevalence and socio-demographic associations of obesity nationwide. Methods: We assessed the prevalence of overall obesity (body mass index ≥28 kg/m2) and abdominal obesity (waist circumference ≥85/90 cm for women/men) among 2.7 million community-dwelling adults aged 35 to 75 years in the China PEACE Million Persons Project from 2014 to 2018 and quantified the socio-demographic associations of obesity using multivariable mixed models. Results: Age-standardized rates of overall and abdominal obesity were 14.4% (95% CI, 14.3%–14.4%) and 32.7% (32.6%–32.8%) in women and 16.0% (15.9%–16.1%) and 36.6% (36.5%–36.8%) in men. Obesity varied considerably across socio-demographic subgroups. Older women were at higher risk for obesity (eg, adjusted relative risk [95% CI] of women aged 65–75 versus 35–44 years: 1.29 [1.27–1.31] for overall obesity, 1.76 [1.74–1.77] for abdominal obesity) while older men were not. Higher education was associated with lower risk in women (eg, adjusted relative risk [95% CI] of those with college or university education versus below primary school: 0.47 [0.46–0.48] for overall obesity, 0.61 [0.60–0.62] for abdominal obesity) but higher risk in men (1.07 [1.05–1.10], 1.17 [1.16–1.19]). Conclusions: In China, over 1 in 7 individuals meet criteria for overall obesity, and 1 in 3 for abdominal obesity. Wide variation exists across socio-demographic subgroups. The associations of age and education with obesity are significant and differ by sex. Understanding obesity in contemporary China has broad domestic policy implications and provides a valuable international reference.

To describe and advise on management protocols and infection-protection experience of the radiology department in makeshift hospitals in Wuhan during the coronavirus disease 2019 (COVID-19) outbreak. Based on the literature review and the experience in the frontline, we retrospectively reviewed the configuration of the radiology department, human resource, personal protection, examination procedures for patients confirmed with COVID-19 in Wuhan fangcang shelter hospital. From February 11, 2020 to March 10, 2020, 2730 and 510 CT examinations were performed in the Hanjiang shelter hospital and Hanyang Sports School shelter hospital, respectively, including initial examinations and re-examinations. The maximum number of daily CT examinations reached 289. The CT scanned a patient approximately once every 13 mins. Fangcang shelter radiology department could be powerful components of both global and national responses to the COVID-19 pandemic.

Objective. Driver gene mutation in lung adenocarcinoma patients in Zunyi and its relationship with clinical features were probed in this investigation. Methods. In total, with 244 patients with lung adenocarcinoma as study subjects, including 141 males and 103 females, amplification-refractory mutation system-polymerase chain reaction (ARMS-PCR) was utilized for detecting multigene mutations. Subsequently, the relationship between gene mutation and clinical characteristics was analyzed. Results. The total mutation rate of driver genes was 65.17%, including 48.36% EGFR, 6.15% KRAS, 5.74% ALK, 2.05% HER-2, 1.23% ROS1, 0.82% RET, 0.41% NRAS, and 0.41% BRAF. Among EGFR mutations, 47.46% were EGFR-19-deletion, 42.37% EGFR-21-L858R mutation, 4.24% EGFR-20-T790M mutation, 2.54% EGFR-21-L861Q mutation, 2.54% EGFR-20-insertion, and 0.85% EGFR-18-G719X mutation. Both female patients and nonsmoking patients with lung adenocarcinoma had a higher rate of EGFR mutation. Additionally, 15 patients with multiple mutations in EGFR, including 13 patients with 2 mutations in EGFR and 2 patients with 3 mutations in EGFR, were found. Conclusion. Among driver gene mutations in patients with lung adenocarcinoma in Zunyi, EGFR mutation has the highest incidence, followed by ALK fusion and KRAS mutation. Although both mutations and multisite mutations in the other driver genes account for a low proportion, they still have great clinical significance. Multigene mutation detection contributes to the rapid screening of patients with lung adenocarcinoma who respond to targeted therapy.

It is well known that hydrostatic pressure (HP) is a physical parameter that is now regarded as an important variable for life. High hydrostatic pressure (HHP) technology has influenced biological systems for more than 100 years. Food and bioscience researchers have shown great interest in HHP technology over the past few decades. The development of knowledge related to this area can better facilitate the application of HHP in the life sciences. Furthermore, new applications for HHP may come from these current studies, particularly in tumor vaccines. Currently, cancer recurrence and metastasis continue to pose a serious threat to human health. The limited efficacy of conventional treatments has led to the need for breakthroughs in immunotherapy and other related areas. Research into tumor vaccines is providing new insights for cancer treatment. The purpose of this review is to present the main findings reported thus far in the relevant scientific literature, focusing on knowledge related to HHP technology and tumor vaccines, and to demonstrate the potential of applying HHP technology to tumor vaccine development.

Accurate long-term streamflow and flood forecasting has always been an important research direction in hydrology research. Nowadays, with climate change, floods, and other anomalies occurring more and more frequently and bringing great losses to society. The prediction of streamflow, especially flood prediction, is important for disaster prevention. Current hydrological models based on physical mechanisms can give accurate predictions of streamflow, but the effective prediction period is only about one month in advance, which is too short for decision making. Previous studies have shown a link between the El Niño–Southern Oscillation (ENSO) and the streamflow of the Yangtze River. In this paper, we use ENSO and the monthly streamflow data of the Yangtze River from 1952 to 2016 to predict the monthly streamflow of the Yangtze River in two extreme flood years by using deep neural networks. In this paper, three deep neural network frameworks are used: Stacked LSTM, Conv LSTM Encoder-Decoder LSTM and Conv LSTM Encoder-Decoder GRU. Experiments have shown that the months of flood occurrence and peak flows predicted by these four models become more accurate after the introduction of ENSO. And the best results were obtained on the Convolutional LSTM + Encoder Decoder Gate Recurrent Unit model.

Accurate long-term streamflow and flood forecasting have always been an important research direction in hydrology research. Nowadays, climate change, floods, and other anomalies occurring more and more frequently and bringing great losses to society. The prediction of streamflow, especially flood prediction, is important for disaster prevention. Current hydrological models based on physical mechanisms can give accurate predictions of streamflow, but the effective prediction period is only about 1 month in advance, which is too short for decision making. The artificial neural network (ANN) has great potential for predicting runoff and is not only good at handling non-linear data but can also make long-period forecasts. However, most of ANN models are unstable in their predictions when faced with raw flow data, and have excessive errors in predicting extreme flows. Previous studies have shown a link between the El Niño–Southern Oscillation (ENSO) and the streamflow of the Yangtze River. In this paper, we use ENSO and the monthly streamflow data of the Yangtze River from 1952 to 2018 to predict the monthly streamflow of the Yangtze River in two extreme flood years and a small flood year by using deep neural networks. In this paper, three deep neural network frameworks are used: stacked long short-term memory, Conv long short-term memory encoder–decoder long short-term memory and Conv long short-term memory encoder–decoder gate recurrent unit. The results show that the use of ConvLSTM improves the stability of the model and increases the accuracy of the flood prediction. Besides, the introduction of ENSO to the experimental data resulted in a more accurate prediction of the time of the occurrence of flood peaks and flood flows. Furthermore, the best results were obtained on the convolutional long short-term memory + encoder–decoder gate recurrent unit model.

Objective. To investigate the effect of matrine on rats with collagen-induced arthritis (CIA) and its regulatory effect on receptor activator of nuclear factor-κB ligand (RANKL) and osteoprotegerin (OPG) expression. Methods. Wistar rats ( n = 6 ) and CIA rats ( n = 30 ) were randomly divided into six groups: healthy, CIA control, low/medium/high matrine (25, 50, or 100 mg/kg, once per day for six weeks), and methotrexate (MTX) (2 mg/kg, once per week for six weeks). The degree of joint damage was evaluated by X-ray and HE staining. Bone marrow suppression was assessed by routine blood analysis. In addition, the levels of serum RANKL and OPG in the rats were measured by ELISA. Results. The level of joint swelling and degree of joint damage assessed by ankle swelling measurements, AI score, X-ray, and HE staining were alleviated in the CIA rats treated with MTX or different doses of matrine. Furthermore, no obvious inhibitory effect was observed on the bone marrow of the CIA rats, regardless of the dose of matrine or treatment with 2 mg/kg MTX ( P > 0.05 ). The levels of OPG in serum and the ratio of OPG/RANKL were higher, and RANKL expression was lower in the low/medium/high matrine group compared with that of the CIA control group. The serum levels of OPG and OPG/RANKL ratio increased with the matrine dose, while the opposite was observed for RANKL expression. Conclusion. Matrine treatment was associated with a lower degree of bone destruction, increased OPG expression and OPG/RANKL ratio, and decreased RANKL expression in CIA rats. Thus, matrine may represent a novel drug candidate for the treatment of RA.

In this paper, we study linear transport model by adopting deep learning method, in particular deep neural network (DNN) approach. While the interest of using DNN to study partial differential equations is arising, here we adapt it to study kinetic models, in particular the linear transport model. Moreover, theoretical analysis on the convergence of neural network and its approximated solution towards analytic solution is shown. We demonstrate the accuracy and effectiveness of the proposed DNN method in numerical experiments.

We examine the impact of religious traditions and social trust on corporate cash holdings from 2007 to 2015 with the listed companies in China as the research sample. The empirical results show that in the areas where the traditional religion and social trust are higher, the cash holding of listed companies is lower, and social trust has the interaction enhancing effect on the impact of religious traditions on corporate cash holdings. Compared with the state-owned listed companies, the traditional religion and social trust have a negative impact on cash holdings in non-state-owned listed companies. Further research shows that the influence of traditional religion and social trust on the cash holdings of enterprises is mainly manifested as an over-curbing effect on the holding of cash. Traditional religion and social trust both as informal institutional factors, have complementary effect on formal institutional factors, such as the marketization process, the level of government governance and the level of legalization. A series of robustness tests prove the reliability of the above conclusion. This article provides empirical evidence that religious traditions and social trust influence the cash holdings of firms.

Among numerous emergency responses to maritime emergencies, the most critical part is the search and rescue (SAR) for victims in distress on the sea. Maritime search and rescue missions are usually divided into two: search and rescue, and the most complex and difficult part is searching for targets in distress at sea. Traditional numerical models can provide accurate drift trajectories of targets in distress. However, owing to the mathematical mechanism, even with high-performance computing technology, the searching time is still far from meeting the real-time requirements of sea rescue missions. In view of this situation, in this paper, a parallel intelligent system is proposed for SAR targets in distress at sea based on a deep residual neural network. A large amount of natural system observation data is utilized to train the proposed ResNet network with the advantages of high-performance computing technique which can accelerate the training process. Furthermore, mathematical model simulation results are used to tune the parameters and optimize the results of the neural network. The precision, recall, and F1 scores of the predictions for drifting of the targets in distress can reach more than 90%. Moreover, the ResNet network-based parallel intelligent system combined with high-performance parallel computing technology reduces the time by about 1%. When compared with traditional numerical model systems in predicting target drifting results, the proposed system can enhance the timeliness of the maritime search and rescue process.

Background With demographic and epidemiologic transitions, China has become home to the greatest number of obese individuals in the world. Effective policy intervention requires a contemporary assessment of obesity across broad socio-demographic subgroups. Purpose We aim to assess the prevalence of overall and abdominal obesity by socio-demographic characteristics and the associations of these characteristics with obesity in China. Methods Using the data of 2.7-million community-dwelling participants aged 35–75 years in the China PEACE Million Persons Project, a nationwide cross-sectional screening project from 2014 to 2018, we calculated the prevalence of overall and abdominal obesity based on national guideline definitions (body mass index ≥28 kg/m2, waist circumference ≥85/90 cm for women/men). We examined 12 available socio-demographic variables that are potentially associated with obesity, in addition to self-reported co-morbidities, and quantified the associations of these socio-demographic characteristics with obesity using multivariable mixed models. Results The prevalence of overall and abdominal obesity were 15.8% and 37.6% in women and 15.0% and 36.3% in men (Figure). Compared to individuals with normal weight, those with overall obesity had a higher prevalence of hypertension, dyslipidemia, and diabetes (in women: by 30.4, 16.1, and 6.0 percent points; in men, by 29.9, 31.2, and 5.8 percent points). A similar pattern was observed with abdominal obesity. In women, those aged 55–64 years constituted the largest age group with overall and abdominal obesity (33.7% and 35.0%), while in men, those aged 45–54 and 55–64 years constituted the largest age group with overall obesity (30.4%) and abdominal obesity (30.5%), respectively. Older women were at substantially higher risk for obesity (e.g., adjusted relative risk [95% CI] of women aged 65–75 vs. 35–44 years: 1.29 [1.27–1.31] for overall obesity and 1.76 [1.74–1.77] for abdominal obesity) while older men were not. Higher education was associated with lower risk in women (e.g., those with college or university education vs. less than primary school: 0.47 [0.46–0.48] for overall obesity and 0.61 [0.60–0.62] for abdominal obesity) but higher risk in men (1.07 [1.05–1.10] and 1.17 [1.16–1.19]). In both women and men, current smoking was associated with lower risk for obesity, and current drinking was associated with higher risk, but the magnitude of associations was smaller in women than men. Conclusions In China, over one in seven individuals meet criteria for overall obesity, and one in three for abdominal obesity. Wide variation exists across socio-demographic subgroups. The associations of age and education with obesity are significant and differ by sex. Understanding obesity in contemporary China has broad domestic policy implications and provides a valuable international reference. Figure 1 Funding Acknowledgement Type of funding source: Other. Main funding source(s): The National Key Research and Development Program from the Ministry of Science and Technology of China, the CAMS Innovation Fund for Medical Science

Given the difficulties faced in real-time monitoring of slope deformation and the low degree of automation of the traditional monitoring methods, a BDS/GPS based geological deformation monitoring system was designed. This system uses carrier phase differential technology to achieve BDS/GPS high-precision positioning, transmits data through the NB-IoT wireless network, and transmits slope deformation monitoring data and environmental-based data to a cloud server, achieving automatic and real-time data collection and transmission. In order to study the function and accuracy of the BDS / GPS integrated system in deformation monitoring, experiments are designed to test the stability of the system and collected environmental factors. The feasibility of BDS / GPS in deformation monitoring is analyzed from the constellation distribution and satellite system. The test results show that long-term continuous observation is the prerequisite for obtaining high-precision positioning data. Under the same conditions, the BDS / GPS integrated system's measured accuracy is better than that of the BDS single system.

Storm surge is a natural disaster, often causing economic damage and loss of human life in the coastal communities. In recent decades, with more people attracted to coastal areas, the potential economic losses resulted from storm surges are increasing. Therefore, it is important to make risk assessments to identify areas at risk and design risk reduction strategies. However, the quantitative risk assessment of storm surge for coastal cities in China is often difficult due to the lack of adequate data regarding the building footprint and vulnerability curves. This paper aims to provide a methodology for conducting the quantitative risk assessment of storm surge, estimating direct tangible damage, by using Geographical Information System (GIS) techniques and open data. The proposed methodology was applied to a coastal area with a high concentration of petroleum industries in the Daya Bay zone. At first, five individual typhoon scenarios with different return periods (1000, 100, 50, 20, and 10 years) were defined. Then, the Advanced Circulation model and the Simulating Waves Nearshore model were utilized to simulate storm surge. The model outputs were imported into GIS software, transformed into inundation area and inundation depth. Subsequently, the building footprint data were extracted by the use of GIS techniques, including spatial analysis and image analysis. The layer containing building footprints was superimposed on the inundation area layer to identify and quantify the exposed elements to storm surge hazard. Combining the exposed elements with their related depth–damage functions, the quantitative risk assessment translates the spatial extent and depth of storm surge into the estimation of economic losses. The quantitative risk assessment and zonation maps for sub-zones in the study area can help local decision-makers to prioritize the sub-zones that are more likely to be affected by storm surge, make risk mitigation strategies, and develop long-term urban plans.

Since the reform and opening to the world, the development of science and technology has made great progress. A large amount of scientific and technological resources has been accumulated in China, the storage forms of which can be divided into two categories: structured data and unstructured data. SOLR playing an important role in this field is a means for us to obtain information and data fast and precisely. In this paper, we import the stored data to SOLR, and establish the index of relevant content. Then the retrieval results data could be presented quickly on the basis of index.

Based on the needs of the wireless system of the National Engineering and Technology Library, according to the latest requirements of the Cyber Security Law of the People's Republic of China, and combined with the latest achievements of wireless technology development, the wireless network of the National Engineering and Technology Library has been redesigned and constructed. The new wireless network has greatly improved the transmission rate, security, unified management convenience and wireless network authentication access convenience, which provides a guarantee for providing better network service.

The aim of this study was to observe the spatial distribution and dynamic changes of matrix metalloproteinase (MMP)-2, MMP-9, and collagen in in stent restenosis (ISR) and to explore their influence on ISR.Sixty Z type stents were implanted into the common iliac arteries of minipigs, which were divided into 10 groups (six in each group) according to euthanasia time (6 hours, and 1, 3, 7, 14, 28, 56, 84, 168, and 336 days). After the samples were harvested, haematoxylin and eosin staining, immunohistochemical staining, Western blotting, and Picrosirius red staining were performed for all groups.ISR occurred in all six minipigs in the 56 day group (percentage diameter stenosis range 71.6%-79.2%, mean ± standard deviation 75.6% ± 2.5%). The percentage diameter stenosis decreased to 38.3% ± 2.7% at 336 days (p .001). Immunohistochemical staining showed that MMP-2 and MMP-9 were strongly stained near the internal elastic lamina or in the damaged parts of the intima, around the struts and neointimal lumen surface in the ISR process. The expression of MMP-2 and MMP-9 at 56 days was significantly lower compared with their peaks (seven days and one day [p .001; p = .002], respectively). At 56 days, the collagen content reached its maximum (mean integrated optical density range 0.73-0.92, mean ± standard deviation 0.82 ± 0.09). From the 14 day group to the 336 day group, mature collagen in neointima was correlated negatively with MMP-2 (γ(36) = -0.816; p .001) and MMP-9 expression (γ(36) = -0.853; p .001). During the neointimal regression period, new collagen in neointima was positively correlated with MMP-2 (γ(24) = 0.683; p .001) and MMP-9 (γ(24) = 0.873; p .001).This study has demonstrated the spatial distribution of and dynamic changes in MMP-2, MMP-9, and collagen in ISR by simulating the process of neointima from generation to regression after stent implantation. When ISR occurred, MMP-2 and MMP-9 expression decreased and collagen content reached its maximum, which might contribute to ISR.

Objective: LncRNA-KAT7 is a recently identified tumor suppressor in colorectal cancer, whereas its roles in other malignancies remain unclear. This study aimed to investigate the roles of KAT7 in n...

The objective of the study was to investigate the value of anti-α-enolase antibody (Ab) combined with RDW in evaluating the activity of systemic lupus erythematosus (SLE). Levels of serum anti-α-enolase Ab and RDW were detected in 193 SLE patients and 98 healthy controls by ELISA and automatic blood cell counter (XN9000), respectively. Furthermore, the correlation between anti-α-enolase Ab and RDW in evaluating the activity of SLE was evaluated by correlation analysis. The level of anti-α-enolase Ab (9.16 ± 0.44 ng/mL in stable group and 10.26 ± 0.36 ng/mL in activity group) was significantly higher than that in the healthy control (7.05 ± 0.27 ng/mL). The level of RDW (12.92% ± 1.23% in stable group and 13.57% ± 2.12% in activity group) was significantly higher than that in the healthy control (12.46% ± 0.61%). The levels of anti-α-enolase Ab or RDW in SLE patients were positively correlated with SLEDAI-2 K score (r= 0.75, r = 0.73), respectively. Compared with the anti-α-enolase Ab (AUC: 78.0%) or RDW (AUC:80.0%) alone, anti-α-enolase Ab combined with RDW (AUC: 81.0%) had the best of the effectiveness of evaluating activity of SLE. These data suggested that combined anti-α-enolase Ab with RDW might be good biomarker to predict the activity of SLE in clinical.

In recent tsunami events like those happened in the Indian Ocean in 2004 and 2018 and in Japan in 2011, many ocean and coastal infrastructures have been damaged tremendously, revealing the need of the work to study the hydrodynamic interaction between real-world tsunami waves and offshore structures. Besides, the destructive energy of tsunami wave on the offshore structures should also be assessed. However, to study the impact of tsunami waves on offshore structures, solitary waves are used generally instead of real-world tsunami waves despite the vast differences in hydrodynamic characteristics. Using Computational Fluid Dynamics (CFD) approach, this paper investigates the hydrodynamic characteristics of the floating cylinders moored by chains, under the real-world tsunami-like waves (2011 Japan Tohoku tsunami). Comparisons of hydrodynamic characteristics between real-world tsunami-like wave and solitary wave propagating over the moored cylinders are analyzed and discussed, indicating that the flow fields, the tension forces of mooring chains, the impinging forces and the movement trajectories of the cylinder caused by the two types of waves are greatly different from each other. Moreover, the influences of single cylinder diameter and tandem cylinder spacing on the interaction between real-world tsunami-like waves and cylinders are considered through a series of simulation tests, while meaningful conclusions are drawn.

A new hyperspectral image denoising algorithm, called the dual deep convolutional neural network (DD-CNN), is proposed in this paper. In contrast to internal denoising methods that utilize only the features from the target noisy image, the DD-CNN extensively explores the similarities between the target noisy image and the clean reference image from other bands. As external data, the reference images are selected based on the structural similarity index metric (SSIM). The DD-CNN is composed of two CNNs: one is responsible for extracting the features of the target image, and the other is responsible for extracting features from the reference image. A new activation function is proposed that activates the two types of features in the DD-CNN. Based on the dual structure and the new activation function, the external features extracted from the reference images are thoroughly integrated into the internal features of the target noise image. We experimented on different datasets with different noise levels; we also tested special cases for reference images with extra or undesirable features. The DD-CNN algorithm can effectively utilize the similarity between the external image and the target image. When the noise level is high, the advantages of the DD-CNN are obvious.

BACKGROUND The aim of this study was to compare changes in the extracellular matrix after implantation of a stent that elutes a matrix metalloproteinase (MMP) inhibitor (GM6001); and to determine the effects of the GM6001-eluting stent upon prevention of in-stent restenosis (ISR). MATERIAL AND METHODS We included 48 Guangxi Bama mini-pigs in this study. A GM6001-eluting stent was placed in one iliac artery and a stent that did not elute GM6001 was placed in the contralateral iliac artery. The iliac arteries were removed at 6 hours as well as 1, 7, 14, 56, 84, and 336 days after stent placement. Arteries were analyzed for morphometry, gelatinase content, different phenotypes of vascular smooth muscle cells (VSMCs), collagen content, apoptotic rate, and cell density. RESULTS The vascular lumen areas of the GM6001 group were significantly increased and the neointimal areas were significantly reduced compared with the control group from the 7 days to the 336 days. In the 2 groups, expression of MMP-2 and MMP-9 peaked simultaneously, but GM6001-eluting stents inhibited expression of MMP-2 and MMP-9 in the vascular media and neointima (especially around the struts) significantly. In the GM6001 group, expression of tissue inhibitor of matrix metalloproteinase (TIMP)-1, TIMP-2, myosin heavy chain 10 (MYH-10, marker of the proliferative phenotype of VSMCs), collagen content, percentage of apoptotic cells, and cell density were also decreased significantly compared with those in the control group. CONCLUSIONS Use of GM6001-eluting stents resulted in persistent and potent inhibition of intimal hyperplasia, an increase in luminal area, and no obvious thrombosis in the arteries of the mini-pigs.