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Creating an effective and efficient distribution plan is a considerable challenge owing to urgency, incomplete information, and surging demands. In this study, a planning method based on a sliding time window series is designed to solve the problem of drug distribution in earthquake responses. First, this study presents a method designed to generate a series of sliding time windows considering time-varying demands. Second, a method is proposed to determine the effectiveness of the drug distribution plan according to its evaluation standards. Third, a dynamic planning model is established considering the sliding time window series and group information updates. Fourth, a simulation study is conducted to test the models and algorithms. Simulation results show that specific drug distribution plans should be provided to emergency planners in the event of an earthquake. The sliding time window series and group information updates are key factors in creating an effective drug distribution plan as part of an earthquake response.

Hemoptysis is a common clinical emergency, bronchial arterial embolization is considered to be an effective treatment. The presence of coronary artery-bronchial artery fistula (CBF) may lead to recurrence of hemoptysis after treatment. It is necessary to investigate the imaging characteristics of a CBF and its correlation with the severity of pulmonary disease. With the development of multi-detector computed tomography, our study used the 320-slice CT bronchial artery angiography technology to observe and visualize blood vessels. The image and clinical data of 2015 hemoptysis patients with 320-slice CT bronchial artery angiography were retrospectively reviewed from January 2015 to December 2019. The axial and three-dimensional CT images were analyzed. The incidence, anatomical characteristics of CBF and pulmonary disease severity score were evaluated. A total of 12 CBF vessels were detected in 11 patients. We found that the incidence of CBF in this group was 0.55% (11/2015). Mean CBF diameter was 1.9 mm (1.2-2.5 mm). The course of CBF usually was relatively fixed. The proportions of CBF originated from the left circumflex artery, right coronary artery, and left anterior descending artery were 75%, 16.7% and 8.3%, respectively. Preliminarily analysis of the correlation between the trend of CBF and the pulmonary diseases severity score showed that CBF was more likely to communicate with a bronchial artery on the side with a higher severity score. CBF may occur in patients with chronic pulmonary disease and hemoptysis, and its origin, course and trend are characteristic. Detailed and comprehensive computed tomography angiography image analysis is helpful to improve the clinical treatment of hemoptysis with CBF.

People talk with diversified styles. For one piece of speech, different talking styles exhibit significant differences in the facial and head pose movements. For example, the "excited" style usually talks with the mouth wide open, while the "solemn" style is more standardized and seldomly exhibits exaggerated motions. Due to such huge differences between different styles, it is necessary to incorporate the talking style into audio-driven talking face synthesis framework. In this paper, we propose to inject style into the talking face synthesis framework through imitating arbitrary talking style of the particular reference video. Specifically, we systematically investigate talking styles with our collected \textit{Ted-HD} dataset and construct style codes as several statistics of 3D morphable model~(3DMM) parameters. Afterwards, we devise a latent-style-fusion~(LSF) model to synthesize stylized talking faces by imitating talking styles from the style codes. We emphasize the following novel characteristics of our framework: (1) It doesn't require any annotation of the style, the talking style is learned in an unsupervised manner from talking videos in the wild. (2) It can imitate arbitrary styles from arbitrary videos, and the style codes can also be interpolated to generate new styles. Extensive experiments demonstrate that the proposed framework has the ability to synthesize more natural and expressive talking styles compared with baseline methods., Comment: Accepted by MM2021, code available at https://github.com/wuhaozhe/style_avatar

The text classification task is the most basic and essential in natural language processing. It can find the rules about documents and distinguish the categories of different papers. Nowadays, graph convolutional neural network is widely used in text classification task because of its scalability and high efficiency. However, the GCN model has the best effect at layer 2. As the number of network layers increases, problems such as over smoothing will occur. This paper proposes a semi-supervised text classification model based on a graph attention neural network, which makes full use of the characteristics of information transmission along with the graph by adding residual connections to deepen the number of network layers. Simultaneously, the attention mechanism can be used to give different weights according to the importance of neighboring nodes to target nodes. A dual-layer attention mechanism at the topic level and node level is proposed to learn the importance of different neighboring nodes and extra neighboring node information to target nodes. Experimental results show that this model is superior to other methods on four benchmark datasets.

After an earthquake, affected areas have insufficient medicinal supplies, thereby necessitating substantial distribution of first-aid medicine from other supply centers. To make a proper distribution schedule, we considered the timing of supply and demand. In the present study, a “sequential time window” is used to describe the time to generate of supply and demand and the time of supply delivery. Then, considering the sequential time window, we proposed two multiobjective scheduling models with the consideration of demand uncertainty; two multiobjective stochastic programming models were also proposed to solve the scheduling models. Moreover, this paper describes a simulation that was performed based on a first-aid medicine distribution problem during a Wenchuan earthquake response. The simulation results show that the methodologies proposed in this paper provide effective schedules for the distribution of first-aid medicine. The developed distribution schedule enables some supplies in the former time windows to be used in latter time windows. This schedule increases the utility of limited stocks and avoids the risk that all the supplies are used in the short-term, leaving no supplies for long-term use.

Progesterone is often used to protect the endometrium and prevent endometrial cancer. An intensive study on its molecular mechanism in endometrial cancer would contribute to the development of more promising therapies. Relevant lncRNAs and mRNAs expression data in endometrial cancer cell line Ishikawa pretreated and post-treated with progesterone were derived from Gene Expression Omnibus (accession no. GSE29435), and then we analyzed long noncoding RNAs and mRNAs with differential expressions in two different conditions. The Cytoscape software, TargetScan, miRanda, and Human microRNA Disease Database (HMDD) websites were employed. Gene set enrichment analysis (GSEA) was used to determine related Kyoto Encyclopedia of Genes and Genomes pathways alteration in Ishikawa cells treated with progesterone. In addition to bioinformatics analysis, Reverse Transcription-Polymerase Chain Reaction (RT-PCR), Western blot, and dual-luciferase reporter assays were performed. The impact of progesterone on cell propagation and cell cycle was testified by colony formation and flow cytometry analysis. LncRNA nuclear enriched abundant transcript 1 (NEAT1) was the most significantly downregulated lncRNA in endometrial cancer cells treated with progesterone. Lymphoid enhancing factor 1 (LEF1) was positively associated with NEAT1, and eventually hsa_miR-146b-5p was validated to target both LEF1 and NEAT1. Wnt/β-catenin signaling pathway was identified to involve in endometrial cancer. NEAT1 or LEF1 was overexpressed in endometrial cancer cells while downregulated following post-treatment with progesterone. Conversely, miR-146b-5p was notably decreased in Ishikawa cells while upregulated after treatment with progesterone. Downstream gene c-myc or MMP9 regulated by upstream gene LEF1 in Wnt/β-catenin signaling pathway was remarkably increased in Ishikawa cells and positively related with NEAT1. Progesterone inhibited cell cycle and viability through regulating NEAT1/miR-146b-5p axis via Wnt/β-catenin signaling pathway. Progesterone exerted suppressive influence on endometrial cancer progression via regulation of lncRNA NEAT1/miR-146b-5p-mediated Wnt/β-catenin signaling pathway, which might reveal new strategies for developing more effective therapeutics. © 2018 IUBMB Life, 71(1):223-234, 2019.

Rationale: It is extremely rare for an intrauterine contraception device (IUD) to cause uterine perforation and Sigmoid perforation for a long time without being detected. Patient concerns: We present a case of a patient who has suffered from abdominal pain after 4 years of placement of an IUD, and found that the IUD was incarcerated by ultrasound. Diagnoses: Laparoscopic and hysteroscopic examination revealed that the incarcerated IUD caused uterine perforation and sigmoid perforation for a long time. One end of the intrauterine device completely penetrated the anterior wall muscle layer of the uterus and the full layer of the sigmoid colon, located in the intestinal lumen, and the perforated portion of the sigmoid colon formed a chronic nodule. Interventions: We extended the sigmoid colon perforation and uterine perforation by laparoscopy, removed the incarcerated IUD from the uterus through the vagina, trimmed the chronic nodules of the sigmoid perforation, repaired the sigmoid colon, and repaired the uterine perforation. Outcomes: The patient was cured and discharged 22 days after surgery. The patient was naturally pregnant 3 months after surgery and delivered by cesarean section 12 months after surgery. We saw a good recovery of the uterus and sigmoid colon during cesarean section. Lessons: The patient was placed with an intrauterine device made of a special material and was not monitored after placement, causing the uterus and sigmoid perforation to be undetected for a long time. The IUD placed in the patient should be monitored regularly. If the IUD is found to be incarcerated or displaced, attention should be paid to uterine perforation and intestinal perforation.

Ongoing marine development has drawn considerable attentions on reinforcing the construction of marine engineering. A high ferrite Portland clinker (HFPC) with 47% C3S, 27% C2S, 6% C3A, and 20% C4AF was designed in this study. Compared with traditional Portland cement, there is larger amount of C4AF and hydration products like AH3 and FH3 that can absorb Cl−, SO42−, Mg2+ from seawater in the high ferrite cement. The activities of C4AF and C3S could be changed by adding Cu2+ under first-Principle calculation. The hydration activity of the high ferrite Portland clinker (HFPC) can be significantly enhanced by doping with Cu2+ because Cu2+ solidifies better in C4AF. This study aims to explore the mechanism of CuO-doping on the hydration performance and chloride-binding capacity of HFPC by using different microscopic analysis methods, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and nuclear magnetic resonance (NMR). The results show that C4AF has the better hydration activity when it is incorporated with 1.0% CuO. According to our calculations by Density Functional Theory and our experimental results, C4AF was easily influenced by the doping Cu2+. As for C4AF, the site of ferrite element can be replaced by copper element, accounting for the improvement of the hydration activity of it when the moderate amount of CuO was doped. As for C3S, it had the less influence of CuO-doping on it when few amounts of CuO was doped into the clinker. The polymorph of C3S was transferred from R to MIII, when the CuO amount was up to 0.8% which made a has unsatisfactory hydration activity under this condition. Taking all the results into consideration, HFPC has the better hydration activity and chloride-binding capacity when 0.2%CuO is doped into the clinker.

Progesterone is often used to protect the endometrium and prevent endometrial cancer. An intensive study on its molecular mechanism in endometrial cancer would contribute to the development of more promising therapies. Relevant lncRNAs and mRNAs expression data in endometrial cancer cell line Ishikawa pretreated and post-treated with progesterone were derived from Gene Expression Omnibus (accession no. GSE29435), and then we analyzed long noncoding RNAs and mRNAs with differential expressions in two different conditions. The Cytoscape software, TargetScan, miRanda, and Human microRNA Disease Database (HMDD) websites were employed. Gene set enrichment analysis (GSEA) was used to determine related Kyoto Encyclopedia of Genes and Genomes pathways alteration in Ishikawa cells treated with progesterone. In addition to bioinformatics analysis, Reverse Transcription-Polymerase Chain Reaction (RT-PCR), Western blot, and dual-luciferase reporter assays were performed. The impact of progesterone on cell propagation and cell cycle was testified by colony formation and flow cytometry analysis. LncRNA nuclear enriched abundant transcript 1 (NEAT1) was the most significantly downregulated lncRNA in endometrial cancer cells treated with progesterone. Lymphoid enhancing factor 1 (LEF1) was positively associated with NEAT1, and eventually hsa_miR-146b-5p was validated to target both LEF1 and NEAT1. Wnt/β-catenin signaling pathway was identified to involve in endometrial cancer. NEAT1 or LEF1 was overexpressed in endometrial cancer cells while downregulated following post-treatment with progesterone. Conversely, miR-146b-5p was notably decreased in Ishikawa cells while upregulated after treatment with progesterone. Downstream gene c-myc or MMP9 regulated by upstream gene LEF1 in Wnt/β-catenin signaling pathway was remarkably increased in Ishikawa cells and positively related with NEAT1. Progesterone inhibited cell cycle and viability through regulating NEAT1/miR-146b-5p axis via Wnt/β-catenin signaling pathway. Progesterone exerted suppressive influence on endometrial cancer progression via regulation of lncRNA NEAT1/miR-146b-5p-mediated Wnt/β-catenin signaling pathway, which might reveal new strategies for developing more effective therapeutics. © 2018 IUBMB Life, 71(1):223-234, 2019.

Glass fiber-reinforced polymers (GFRPs) have received increasing attention in recent years due to their overall performance of light weight, low cost and corrosion resistance, and they are increasingly used as reinforcement in concrete structures. However, GFRP material has low elastic modulus and linear elastic properties compared with steel bars, which introduces different bonding characteristics between bars and concrete. Therefore, a reliable monitoring method is urgently needed to detect the bond slip in GFRP-reinforced concrete structures. In this paper, a piezoceramic-based active sensing approach is proposed and developed to find the debonding between a GFRP bar and the concrete structure. In the proposed method, we utilize PZT (lead zirconate titanate) as two transducers. One acts as an actuator which is buried in the concrete structure, and the other acts as a sensor which is attached to the GFRP bar by taking advantage of machinability of the GRRP material. Both transducers are strategically placed to face each other across from the interface between the GFRP bar and the concrete. The actuator provokes a stress wave that travels through the interface. Meanwhile, the PZT patch that is attached to the GFRP bar is used to detect the propagating stress wave. The bonding condition determines how difficult it is for the stress wave traveling through the interface. The occurrence of a bond slip leads to cracks between the bar and the concrete, which dramatically reduces the energy carried by the stress wave through the interface. In this research, two specimens equipped with the PZT transducers are fabricated, and pull-out tests are conducted. To analyze the active sensing data, we use wavelet packet analysis to compute the energy transferred to the sensing PZT patch throughout the process of debonding. Experimental results illustrate that the proposed method can accurately capture the bond slip between the GFRP bar and the concrete.

Some of the most severe structural loadings come in the form of blast loads, which may be caused by severe accidents or even terrorist activities. Most commonly after exposure to explosive forces, a structure will suffer from different degrees of damage, and even progress towards a state of collapse. Therefore, damage detection of a structure subject to explosive loads is of importance. This paper proposes a new approach to damage detection of a concrete column structure subjected to blast loads using embedded piezoceramic smart aggregates (SAs). Since the sensors are embedded in the structure, the proposed active-sensing based approach is more sensitive to internal or through cracks than surface damage. In the active sensing approach, the embedded SAs act as actuators and sensors, that can respectively generate and detect stress waves. If the stress wave propagates across a crack, the energy of the wave attenuates, and the reduction of the energy compared to the healthy baseline is indicative of a damage. With a damage index matrix constructed by signals obtained from an array of SAs, cracks caused by blast loads can be detected throughout the structure. Conventional sensing methods such as the measurement of dynamic strain and acceleration were included in the experiment. Since columns are critical elements needed to prevent structural collapse, knowledge of their integrity and damage conditions is essential for safety after exposure to blast loads. In this research, a concrete column with embedded SAs was chosen as the specimen, and a series of explosive tests were conducted on the column. Experimental results reveal that surface damages, though appear severe, cause minor changes in the damage index, and through cracks result in significant increase of the damage index, demonstrating the effectiveness of the active sensing, enabled by embedded SAs, in damage monitoring of the column under blast loads, and thus providing a reliable indication of structural integrity in the event of blast loads.

In some data stream applications, the information embedded in the data arriving in the most recent time period is of particular interest. This paper proposes a method for efficiently mining the frequent patterns in a varying-size sliding window of online data streams. To highlight recent frequent patterns in the data stream, a time decay model is used to differentiate the patterns of recently generated transactions from historical transactions. The derived concrete bounds of the decay factor can achieve either 100% recall or 100% precision. A summary data structure, named SWP-tree, is proposed for capturing the content of the transactions in the sliding window by scanning the stream only once. In order to speed up online processing of new transactions, the information of frequent patterns recorded in the SWP-tree is updated in an incrementally way. To make the mining operation efficient, the SWP-tree is periodically pruned by identifying insignificant patterns, which include two kinds of obsolete pattern and two kinds of infrequent pattern. Since the sliding window can change its size, the effect of window size is examined. The performance of the proposed technique is evaluated via simulation experiments. The results show that the proposed method is both efficient and scalable, and that it outperforms comparable algorithms.

The Chinese yew (Taxus chinensis) is catalogued as an endangered species in China because of the small size and senescent status of most populations. Its lack of natural regeneration is the most important reason for its endangered status. We investigated the regeneration of an ex-situ conservation population, which was introduced into the Nanjing Botanical Garden Memorial Sun Yat-Sen in the 1950s, and evaluated the role of frugivorous birds on the establishment of this regenerating population. Two hundred and thirteen individual yew seedlings and saplings were found on the hillside in 2006, and the nearest seedling was found more than 10 m away from mother trees. The spatial pattern of all seedlings and saplings occurred as a clumped distribution, which is typical for vertebrate-dispersed plants. Six bird species were seen ingesting whole "fruits" at yew trees in the present study and 745 visits by avian frugivores were recorded. Red-billed blue magpie (Urocissa erythrorhyncha), Chinese bulbul (Pycnonotus sinensis) and azure-winged magpie (Cyanopica cyana) were the most frequent visitors over the two years of the study. Comparing the flights of departure and perching habitats of the three main bird species, we inferred that U. erythrorhyncha would be the most important disperser. This regeneration population has had good development over the past 20 or more years; frugivorous birds have removed seeds to the hillside every year until now, and seed germination and seedling growth continue to develop well under natural conditions. We suggest that the conservation system of the Chinese yew should be composed of yews, avian dispersers and habitats for seed germination and seedling growth.

The market of ERP management software has made great progress, which results in the huge demand of ERP talents. The problem of talents becomes the bottleneck of the development of ERP. Therefore it is necessary to train qualified compound ERP talents to meet the social requirements. This paper analyzes the problems existing in the training of ERP talents, sums up the ability requirements of compound ERP talents, and makes a design of teaching system of compound ERP talents including curriculum system, practical teaching system and teaching mode. Curriculum system includes four parts. The first part is basic theory and technology composed of management, finance and information technology. The second to fourth part are ERP theory, ERP application and professional qualities. The practical teaching system consists of three parts: experiments in the lab, extracurricular activities and internship in real enterprise. To train the compound ERP talents efficiently and effectively, school-enterprise cooperation is a good choice of teaching mode.

Auditing practices nowadays have to cope with an increasing number of fraudulent financial statements. Data mining techniques can facilitate auditors in accomplishing the task of detection of fraudulent financial statements (FFS). Considering the character of FFS, this paper designs a FFS detection model based on Naive Bayes classifier. To perform the experiment, we choose 44 FFS according to the auditing reports and 44 non-fraudulent financial statements(non-FFS) according to some specific standards from listed companies in China during 1999–2002 as training data set. Similarly, 73 FFS and 99 non-FFS during 2003–2006 are chosen as testing data set. We train the model using training data set and apply the trained model to the testing data set, good experimental results are obtained.

In order to solve the time over-consuming problem caused by max-min ant system (MMAS) for solving large scale permutation flow shop scheduling problem (PFSP), a hybrid ant colony algorithm is proposed by incorporating the MMAS with taboo search algorithm based on PFSP's block properties. The new algorithm can reduce neighborhood by eliminating quantity of inferior solutions and can enhance global optimization ability by applying taboo search algorithm. Results of experiments on larger scale PFSP instances show that TB-MMAS obviously reduces the calculation time and effectively eliminates the premature convergence compared with MMAS.

Auditing practices nowadays have to cope with an increasing number of fraudulent financial statements (FFS). Based on data mining techniques, researchers have made some studies and have found that the techniques can facilitate auditors in accomplishing the task of detection of FFS. However, most of the techniques used in the detection of FFS are supervised methods. Clustering, one kind of unsupervised data mining technique, has almost never been used. Therefore, considering the characteristics of FFS and self-organizing map(SOM), a model combining SOM and K-means clustering based on a clustering validity measure is designed. To carry out the experiment, 100 financial statements from Chinese listed companies during 1999–2006 are selected as experimental sample according to some specific standards. 47 financial ratios are chosen as variables. The model is applied to the data and good experimental results are obtained.

To make students have a deep understanding on ERP and to improve the students' practical ability, this paper designs a practical teaching framework of ERP Course. The framework consists of three parts: experiments in the lab, extracurricular activities and internship in a certain software company. Furthermore, there are three levels of experiments in the lab: business scenario simulation, business process and roles collaboration designed according to Zachman's enterprise architecture framework. Extracurricular activities include the research of ERP business game, the simulation of development and testing of some ERP modules, the implementation solution design of ERP. Students' jobs in internship may be system development, system testing, system implementation and customer service. The framework has been applied in real teaching environment and has gotten good results.

Auditing practices nowadays have to cope with an increasing number of fraudulent financial statements. Data mining techniques can facilitate auditors in accomplishing the task of detection of fraudulent financial statements (FFS). Considering the character of FFS, this paper designs a FFS detection model based on support vector machine. To perform the experiment, we choose 44 FFS according to the auditing reports and 44 non-fraudulent financial statements(non-FFS) according to some specific standards from listed companies in China during 1999–2002 as training data set. Similarly, 73 FFS and 99 non-FFS during 2003–2006 are chosen as testing data set. We train the model using training data set and apply the trained model to the testing data set, good experimental results are obtained.