Search

The spatial time series generated by city sensors allow us to observe urban phenomena like environmental pollution and traffic congestion at an unprecedented scale. However, recovering causal relations from these observations to explain the sources of urban phenomena remains a challenging task because these causal relations tend to be time-varying and demand proper time series partitioning for effective analyses. The prior approaches extract one causal graph given long-time observations, which cannot be directly applied to capturing, interpreting, and validating dynamic urban causality. This paper presents Compass, a novel visual analytics approach for in-depth analyses of the dynamic causality in urban time series. To develop Compass, we identify and address three challenges: detecting urban causality, interpreting dynamic causal relations, and unveiling suspicious causal relations. First, multiple causal graphs over time among urban time series are obtained with a causal detection framework extended from the Granger causality test. Then, a dynamic causal graph visualization is designed to reveal the time-varying causal relations across these causal graphs and facilitate the exploration of the graphs along the time. Finally, a tailored multi-dimensional visualization is developed to support the identification of spurious causal relations, thereby improving the reliability of causal analyses. The effectiveness of Compass is evaluated with two case studies conducted on the real-world urban datasets, including the air pollution and traffic speed datasets, and positive feedback was received from domain experts.

The value of the high-resolution data lies in the high-precision information discovery. The fine-detailed landform element extraction is thus the basis of high-fidelity application of the high-resolution digital elevation models (DEMs). However, the results of landform element extraction generated by classical methods might be ungrounded on high-resolution DEMs. This paper presents our research on using the aspect to reinforce the applicability and robustness of the classical approaches in landform element extraction. First, according to the research of pattern recognition, we assume that aspect-enhanced landform representation is robust to rotation, scaling and affine variance. To testify the role of aspect, we respectively integrated the aspect into three classical approaches: mean curvature-based fuzzy classification, elevation-based feature descriptor, and object-based segmentation. In the experiment, based on four types of high-resolution DEMs (1 m, 2 m, 4 m and 8 m), we compare each classical approaches and their corresponding aspect-enhanced approaches based on extracting the rims of two craters having different landforms, and the ridgelines and valleylines of a region covered by few vegetables and man-made buildings. In comparison to the results generated by curvature-based fuzzy classification, the aspect enhanced curvature-based fuzzy classification can effectively filter a number of noises outperforms the curvature-based one. Otherwise, the aspect-enhanced feature descriptor can detect more landform elements than the elevation-based feature descriptor. Moreover, the aspect-based segmentation can detect the main structure of landform, while the boundaries segmented by classical approaches are messing and meaningless. The systematic experiments on meter-level resolution DEMs proved that the aspect in topography could effectively to improve the classical method-system, including fuzzy-based classification, feature descriptors-based detection and object-based segmentation. The value of aspect is significantly great to be worthy of attentions in landform representation.

The COVID-19 pandemic has demonstrated the need for real-time, open-access epidemiological information to inform public health decision-making and outbreak control efforts. In Canada, authority for healthcare delivery primarily lies at the provincial and territorial level; however, at the outset of the pandemic no definitive pan-Canadian COVID-19 datasets were available. The COVID-19 Canada Open Data Working Group was created to fill this crucial data gap. As a team of volunteer contributors, we collect daily COVID-19 data from a variety of governmental and non-governmental sources and curate a line-list of cases and mortality for all provinces and territories of Canada, including information on location, age, sex, travel history, and exposure, where available. We also curate time series of COVID-19 recoveries, testing, and vaccine doses administered and distributed. Data are recorded systematically at a fine sub-national scale, which can be used to support robust understanding of COVID-19 hotspots. We continue to maintain this dataset, and an accompanying online dashboard, to provide a reliable pan-Canadian COVID-19 resource to researchers, journalists, and the general public., Measurement(s) COVID-19 Cases • COVID-19 Mortalities • COVID-19 vaccination Technology Type(s) digital curation Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location Canada Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14331311

The rational allocation of functional areas is the foundation for addressing the sustainable development of cities. Efficient and accurate identification methods of urban functional areas are of great significance to the adjustment and testing of urban planning and industrial layout optimization. Firstly, by employing multisource geographic data, an identification method of urban functional areas was developed. A quantitative measurement approach of the urban functional area was then established considering the comprehensive effects of human-land, space-time, and thematic information to present the covering area of ground objects, public awareness, and empirical research. Finally, the Zhengzhou city, which locates in Henan province of central China, was used to test the method. The results show that the developed method is efficient, accurate, and universal and can identify urban functional areas quickly and accurately. We found that the overall distribution of Zhengzhou’s functional areas presents a spatial pattern of single and multimixed coordinated development. The city’s commercial functional areas and commercial-based mixed functional areas are located in the city’s central area. The green square’s function area occupies relatively low and is mainly distributed in the city’s fringe.

Using causal relations to guide decision making has become an essential analytical task across various domains, from marketing and medicine to education and social science. While powerful statistical models have been developed for inferring causal relations from data, domain practitioners still lack effective visual interface for interpreting the causal relations and applying them in their decision-making process. Through interview studies with domain experts, we characterize their current decision-making workflows, challenges, and needs. Through an iterative design process, we developed a visualization tool that allows analysts to explore, validate, and apply causal relations in real-world decision-making scenarios. The tool provides an uncertainty-aware causal graph visualization for presenting a large set of causal relations inferred from high-dimensional data. On top of the causal graph, it supports a set of intuitive user controls for performing what-if analyses and making action plans. We report on two case studies in marketing and student advising to demonstrate that users can effectively explore causal relations and design action plans for reaching their goals.

This article is focused on a challenging topic emerging from the registration of point clouds, specifically the registration of dynamic objects with low overlapping ratio. This problem is especially difficult when the static scanner is installed on a floating platform, and the objects it scans are also floating. These issues make most of the automatic registration methods and software solutions invalid. To solve this problem, explicit exploration of the static region is necessary for both the coarse and fine registration steps. Fortunately, determining the corresponding regions can be eased by the intuitive realization that in urban environments, natural objects neither present straight boundaries nor stack vertically. This intuition has guided the authors to develop a robust approach for the detection of static regions using planar structures. Then, silhouettes of the objects are extracted from the planar structures, which assist in the determination of an SE(2) transformation in the horizontal direction by a novel line matching method. The silhouettes also enable identification of the correspondences of planes in the step of fine registration using a variant of the iterative closest point method. Experimental evaluations using point clouds of cargo ships with different sizes and shapes reveal the robustness and efficiency of the proposed method, which gives 100% success and reasonable accuracy in rapid time, suitable for an online system. In addition, the proposed method is evaluated systematically with regard to several practical situations caused by the floating platform, and it demonstrates good robustness to limited scanning time and noise.

GDP dissociation inhibitor (GDI) regulates the GDP/GTP exchange reaction of most Rab proteins by inhibiting GDP dissociation. This study evaluated the potential prognostic and predictive value of GDI1 in colorectal cancer (CRC). To address the prognostic power of GDI1, we performed individual and pooled survival analyses on six independent CRC microarray gene expression datasets. GDI1-enriched signatures were also analyzed. Kaplan–Meier and Cox proportional analyses were employed for survival analysis. An immunohistochemistry (IHC) analysis was performed to validate the clinical relevance and prognostic significance of the GDI1 protein level in CRC tissue samples. The results revealed that GDI1 mRNA level was significantly linked with the aggressiveness of CRC, which is compatible with gene set enrichment analysis. A meta-analysis and pooled analysis demonstrated that a higher mRNA GDI1 expression was dramatically correlated with a worse survival in a dose-dependent manner in CRC patients. Further IHC analysis validated that the protein expression of GDI1 in both cytoplasm and membrane also significantly impacted the outcome of CRC patients. In CRC patients with stage III, chemotherapy significantly reduced the relative risk of death in low-GDI1 subgroup (hazard ratio (HR) = 0.22; 95% confidence interval (95% CI) 0.09–0.56, p = 0.0003), but not in high-GDI1 subgroup (HR = 0.63; 95% CI 0.35–1.14, p = 0.1137). Therefore, both high mRNA and protein levels of GDI1 were significantly related to poor outcomes in CRC patients. GD11 may serve as a prognostic biomarker for CRC.

Although previous works have proposed sophisticatedly probabilistic models that has strong capability of extracting features from remote sensing data (e.g., convolutional neural networks, CNN), the efforts that focus on exploring the human’s semantics on the object to be recognized are required more explorations. Moreover, interpretability of feature extraction becomes a major disadvantage of the state-of-the-art CNN. Especially for the complex urban objects, which varies in geometrical shapes, functional structures, environmental contexts, etc, due to the heterogeneity between low-level data features and high-level semantics, the features derived from remote sensing data alone are limited to facilitate an accurate recognition. In this paper, we present an ontology-based methodology framework for enabling object recognition through rules extracted from the high-level semantics, rather than unexplainable features extracted from a CNN. Firstly, we semantically organize the descriptions and definitions of the object as semantics (RDF-triple rules) through our developed domain ontology. Secondly, we exploit semantic web rule language to propose an encoder model for decomposing the RDF-triple rules based on a multilayer strategy. Then, we map the low-level data features, which are defined from optical satellite image and LiDAR height, to the decomposed parts of RDF-triple rules. Eventually, we apply a probabilistic belief network (PBN) to probabilistically represent the relationships between low-level data features and high-level semantics, as well as a modified TanH function is used to optimize the recognition result. The experimental results on lacking of the training process based on data samples show that our proposed approach can reach an accurate recognition with high-level semantics. This work is conducive to the development of complex urban object recognition toward the fields including multilayer learning algorithms and knowledge graph-based relational reinforcement learning.

Since December 2019, the coronavirus disease 2019 (COVID-19) has become a public health emergency. COVID-19 has already been classified as a category B infectious disease according to the Law of the People's Republic of China on the Prevention and Treatment of Infectious Diseases, and control measures for category A infectious diseases have been adopted. The National Health Commission has also published diagnosis and treatment protocols to guide the clinical diagnosis and treatment. With the accumulating experience of treating COVID-19 patients, particularly severely and critically ill patients, in clinical practice, our understanding of COVID-19 has continuously deepened. With regard to varying degrees of respiratory, physical, and psychological dysfunction in patients,[1] it is vital to standardize respiratory rehabilitation techniques and procedures for respiratory rehabilitation in various regions. Hence, we combined the opinions of frontline epidemic control experts and reviewed the evidence in relevant literature. Based on the “Coronavirus Disease 2019 Respiratory Rehabilitation Guidelines (First Edition),”[2] we organized experts in evidence-based medicine, respiratory and critical care medicine, and rehabilitation medicine in China, and invited some experts at the frontline of epidemic control in Wuhan and other cities in Hubei province to jointly draft these recommendations.

Circular glyphs are used across disparate fields to represent multidimensional data. However, although these glyphs are extremely effective, creating them is often laborious, even for those with professional design skills. This paper presents GlyphCreator, an interactive tool for the example-based generation of circular glyphs. Given an example circular glyph and multidimensional input data, GlyphCreator promptly generates a list of design candidates, any of which can be edited to satisfy the requirements of a particular representation. To develop GlyphCreator, we first derive a design space of circular glyphs by summarizing relationships between different visual elements. With this design space, we build a circular glyph dataset and develop a deep learning model for glyph parsing. The model can deconstruct a circular glyph bitmap into a series of visual elements. Next, we introduce an interface that helps users bind the input data attributes to visual elements and customize visual styles. We evaluate the parsing model through a quantitative experiment, demonstrate the use of GlyphCreator through two use scenarios, and validate its effectiveness through user interviews.

A landslide susceptibility map (LSM) is of vital importance for risk recognition and prevention. In the last decade, statistical methods have gradually exerted their impact on mapping the landslide susceptibility to locate the high-risk places of landslide. However, due to the complexity of getting full access to the thematic information in large scenarios, most of these statistical methods generally suffer from overfitting, inadequate representative power, and the inability to transfer the learned representation to other places. To solve these challenges, this study designed an unsupervised representation learning module, which features independence, compactness, robustness, and transferability. Specifically, we first stack restricted Boltzmann machines and denoising autoencoder to unsupervised discover the underlying representations embedded in the thematic maps. Then, we applied the transferring strategy in an adversarial manner to generalize the learned representations to the sample-scarce area. Experimental results and analyses using data in different regions have revealed that the proposed method can be generalized well between different LSM scenarios. In terms of precision, it outperforms other methods by a large margin, e.g., by around 7% compared to multilayer perceptrons with the same configuration, and by 3%-4% to the state of art algorithm random forest. Besides, compared to other methods, the landslide susceptibility map that is predicted by the proposed method featuring smoothness and stableness seems more reliable, and is more according to some prior knowledge that, for example, distance to the drainage, slope, and stratum, should exert dominant effects on the occurrence of a landslide.

Robotic-assisted resection of ovarian tumors in children: A case report and review of literature

The wireless video transmission environment of unmanned aerial vehicles (UAVs) is complex and unstable given the high mobility and changeable working conditions of UAVs, which lead to burst and consecutive errors and high error rates. A compressed video stream is extremely sensitive to transmission errors, such that even a single bit error sharply degrades the video quality. Hence, we propose an intraframe pixel-row-interleaved error concealment algorithm that interleaves pixel rows to generate high similarity in different parts of a frame, thereby achieving intraframe error resilience. Subsequently, we suggest an interframe time-field-interleaved alternative motion-compensated prediction that allows for automatic error elimination and recovers at least four consecutive frames in wireless video communications. The experiments demonstrate that the proposed algorithms recover frames with excellent subjective and objective effects. Moreover, these algorithms can provide reliable and robust video transmission for UAVs.

Stroke evaluation is critical for coaches to evaluate players' performance in table tennis matches. However, current methods highly demand proficient knowledge in table tennis and are time-consuming. We collaborate with the Chinese national table tennis team and propose Tac-Valuer, an automatic stroke evaluation framework for analysts in table tennis teams. In particular, to integrate analysts' knowledge into the machine learning model, we employ the latest effective framework named abductive learning, showing promising performance. Based on abductive learning, Tac-Valuer combines the state-of-the-art computer vision algorithms to extract and embed stroke features for evaluation. We evaluate the design choices of the approach and present Tac-Valuer's usability through use cases that analyze the performance of the top table tennis players in world-class events.

1.1 Background Slug as a member of the epithelial-mesenchymal transition(EMT) leads to the decrease of adhesion between cancer cells and the increase of cell migration. Many studies have been reported the relationship between prognosis and slug expression in patients with breast cancer, yet the results are controversial. Therefore, it is necessary to conclude the relationship between slug and breast cancer by a meta-analysis. 1.2 Methods We looked for studies on breast cancer and slug via PubMed, Scopus and Web of Science .A total of 1458 patients from the final eight studies were included in this meta-analysis. Overall survival (OS) and Disease-free survival (DFS) were the primary endpoints. Pooled hazard ratio (HR), pooled odds ratio (OR), and 95% confidence interval (CI) were calculated to assess the association between slug, prognosis, and clinicopathological parameters (age, tumor size, histological grade, axillary lymph nodes status(LN),TNM stage, ER(estrogen receptor) status, PR(progesterone receptor) status, HER-2(human epidermal growth factor receptor 2)status). Data analysis was carried out by using STATA version 14.0. (Stata Corporation, TX, USA)software. 1.3 Results This meta-analysis included 1458 patients from eight studies. The final results show that high slug expression leads to poor OS（pooled HR = 2.21;95%CI=1.47-3.33;p＜0.001) and DFS （pooled HR = 2.03;95%CI=1.26-3.28; P=0.004) in breast cancer. In terms of clinicopathological parameters, the results show that breast cancer patients with high slug expression have higher TNM stage(I-II/III-IV; pooled OR=0.42;95%CI=0.25-0.70;P=0.001), more prone to axillary lymph node metastasis(N+/N0;pooled OR =2.16; 95%CI =1.31-3.56; P=0.003) and more severe ER deficiency (positive /negative; pooled OR=0.67;95%CI=0.45-0.99; P=0.042).However, slug is not related to age, histological grade, tumor size, PR status and Her-2 status. 1.4 Conclusion This meta-analysis results show that high slug expression in breast cancer is associated with poor OS, DFS and axillary lymph node status, TNM stage and ER status, but not related to age, histological grade, tumor size, PR status and Her-2 status.

BackgroundConsidering that current peritoneal dialysis has its own shortcomings, In this study, the Seldinger technique was modified to explore the relationship between different catheter placement methods of peritoneal dialysis and short-term postoperative complications.MethodsWe retrospectively analyzed the data of 157 patients who received peritoneal dialysis in the Department of Nephrology of our hospital from January 2017 to December 2019. According to different catheter placement methods, the patients were divided into three groups: 111 cases of open surgery technique, 23 cases of Seldinger technique, and 23 cases of modified Seldinger technique (ultrasound-guided Veress needle puncture). The general data, laboratory indexes, and abdominal infection and catheter-related complications within one month postoperatively were collected.ResultsThere were 48 (31.0 %) cases of complications in 157 patients within one month postoperatively, which were mainly catheter-related complications (45 cases, 29.0 %). The incidence of catheter tip peritoneal drift (catheter migration) in the three groups was 27.3 %, 39.1 %, and 9.1 %, respectively, with no significant difference between groups (P = 0.069). Univariate logistic regression analysis showed that the systolic blood pressure, history of abdominal and pelvic surgery, creatinine, and modified Seldinger technique were possible impact factors of catheter migration (P P = 0.045); However, the difference between the Seldinger method group and the open surgery group was not significant, with an OR of 1.061 (95 % confidence interval: 0.308–3.649,P = 0.926). Curve fitting showed that the average incidence of catheter migration in the three groups was 27.3 % (95% CI: 15.9-42.7 %), 28.5 % (95% CI: 10.7-56.9 %), and 5.7 % (95% CI: 1.0-27.0 %); the modified Seldinger method has the lowest average incidence of catheter migration.ConclusionsModified Seldinger technique can significantly reduce catheter-related short-term complications after peritoneal dialysis, and it is especially effective in reducing the incidence of catheter migration. Modified Seldinger technique is a safe and feasible method for the placement of a peritoneal dialysis catheter.

Objective To investigate the factors involved in early and mid-term complications after catheter insertion for peritoneal dialysis and to establish prediction models. Methods A total of 158 patients with peritoneal dialysis in the Department of Nephrology of our hospital were retrospectively analyzed. General information, laboratory indices, early complications (within 1 month after the operation), mid-term complications (1–6 months after the operation), and other relevant data were recorded. Multivariate logistic regression analysis was performed to establish a prediction model of complications and generate a nomogram. Receiver operating characteristic (ROC) curve analysis was used to evaluate the efficacy of the model. Results Among the patients, 48 (30.8%) had early complications, which were mainly catheter-related complications, and 29 (18.4%) had mid-term complications, which were mainly abdominal infection and catheter migration. We constructed a prediction model for early complications (area under the curve = 0.697, 95% confidence interval: 0.609–0.785) and mid-term complications (area under the curve = 0.730, 95% confidence interval: 0.622–0.839). The sensitivity was 0.750 and 0.607, and the specificity was 0.589 and 0.765, respectively. Conclusions Our prediction model has clinical significance for risk assessment of early and mid-term complications and prevention of complications after catheterization for peritoneal dialysis.

Objective Currently, many studies have found that RFC4 was up‐regulated in various cancers, and related to the progression and development. While the effects of RFC4 in oral tongue squamous cell carcinoma remain unclear, the main purpose of this research is to explore the role of RFC4 in oral tongue squamous cell carcinoma. Methods The expression of RFC4 in various cancers was analyzed in GEPIA database, and the results were further verified by IHC assay. The relationship between RFC4 and several clinical parameters was analyzed; the proliferation was further observed by knockdown RFC4 in vitro. Finally, we constructed related nude mouse models by planting cells subcutaneous of nude mice, and the discrepancy was observed. Results Based on GEPIA database, RFC4 was up‐regulated in various cancers, including colorectal cancer, breast cancer, prostate cancer, lung cancer, and liver cancer. RFC4 was up‐regulated in oral tongue squamous cell carcinoma compared with the normal tissue from GEPIA online database; we further found that the expression of RFC4 was tightly associated with TNM stage (p = 0.005), but not with age, gender, and differentiation (p > 0.05). We further found that the proliferation of oral tongue squamous cell carcinoma was obviously restrained in vitro, and the carcinogenesis was also inhibited in vivo. Conclusions We found that RFC4 was up‐regulated and related to the progression of oral tongue squamous cell carcinoma, and knockdown RFC4 could restrain the proliferation and progression. RFC4 might serve a potential biomarker and provide a new treatment strategy for lots of patients with oral tongue squamous cell carcinoma., Figure 1. RFC4 was up‐regulated in various cancers. The expression of RFC4 in several cancers, including colorectal cancer, breast cancer, prostate cancer, lung cancer and liver cancer.Figure 2. The expression of RFC4 in oral tongue squamous cell carcinoma. Left panel: The expression of RFC4 in oral tongue squamous cell carcinoma (IHC), tissues were classified as low expression and high expression. Right panel: The expression of RFC4in normal tissues was used as normal control group. The expression of rfc4 in normal tissue is low and stain is weakly or negative.Table 1. Relationships of RFC4 and clinicopathological characteristics in 64 patients with tongue squamous cell carcinomaFigure 3. Knockdown RFC4 could restrain the proliferation of oral tongue squamous cell carcinoma CAL27 and TCA8113 cells. A. The mRNA expression of RFC4 in CAL27 and TCA8113 cells transfected with RFC4 shRNA. B. The protein expression of RFC4 in CAL27 and TCA8113 cells transfected with RFC4 shRNA. C. The CCK‐8 assay of CAL27 and TCA8113 cells transfected with RFC4 shRNA. D. The colony forming assay of CAL27 and TCA8113 cells transfected with RFC4 shRNA.Figure 4. Knockdown RFC4 inhibited the growth of oral tongue squamous cell carcinoma in vivo. A, B. CAL27 cell transfected with RFC4 shRNA was transplanted subcutaneously in nude mice, the tumor volume was measured with a caliper. C. IHC staining with RFC4 was performed in these tumors from nude mice.

Rationale: Adenomyoepithelioma (AME) is a rare biphasic tumor consisting of epithelial and Myoepithelial cell. Most of the AME is benign, and only a few will progress to malignancy, Here, we report a case of low-grade malignant adenomyoepithelioma, and review the related literature, in a bid to investigate its clinical and pathological features and thus, enhance our understanding of this tumor. Patient concerns: A 64-year-old woman visited our hospital with a 1-year history of a painless mass in her left breast. Physical examination revealed a palpable painless mass, measuring approximately 4.5 cm, in the left breast. Diagnosis: Histological examination confirmed the diagnosis of malignant adenomyoepithelioma Interventions: The patient underwent local excision of the mass, with frozen section analysis revealing ductal carcinoma in situ. Mastectomy and sentinel lymph node biopsy were then performed. Outcomes: We conducted a one-year follow-up, and relapse was not observed. Lessons: Treatment of AME remains controversial owing to the lack of high volume data and absence of prospective studies. Simple mastectomy is an acceptable treatment of this tumor.

How to achieve academic career success has been a long-standing research question in social science research. With the growing availability of large-scale well-documented academic profiles and career trajectories, scholarly interest in career success has been reinvigorated, which has emerged to be an active research domain called the Science of Science (i.e., SciSci). In this study, we adopt an innovative dynamic perspective to examine how individual and social factors will influence career success over time. We propose ACSeeker, an interactive visual analytics approach to explore the potential factors of success and how the influence of multiple factors changes at different stages of academic careers. We first applied a Multi-factor Impact Analysis framework to estimate the effect of different factors on academic career success over time. We then developed a visual analytics system to understand the dynamic effects interactively. A novel timeline is designed to reveal and compare the factor impacts based on the whole population. A customized career line showing the individual career development is provided to allow a detailed inspection. To validate the effectiveness and usability of ACSeeker, we report two case studies and interviews with a social scientist and general researchers.

The drug response sensitivity and related prognosis of prostate cancer varied from races, while the original mechanism remains rarely understood. In this study, the comprehensive signature including transcriptomics, epigenome and single nucleotide polymorphisms (SNPs) of 485 PCa cases- including 415 Whites, 58 Blacks and 12 Asians from the TCGA database were analyzed to investigate the drug metabolism differences between races. We found that Blacks and Whites had a more prominent drug metabolism, cytotoxic therapy resistance, and endocrine therapy resistance than Asians, while Whites were more prominent in drug metabolism, cytotoxic therapy resistance and endocrine therapy resistance than Blacks. Subsequently, the targeted regulation analysis indicated that the racial differences in cytotoxic therapy resistance, endocrine therapy resistance, might originate from drug metabolisms, and 19 drug metabolism-related core genes were confirmed in the multi-omics network for subsequent analysis. Furthermore, we verified that CYP1A1, CYP3A4, CYP2B6, UGT2B17, UGT2B7, UGT1A8, UGT2B11, GAS5, SNHG6, XIST significantly affected antineoplastic drugs sensitivities in PCa cell lines, and these genes also showed good predictive efficiency of drug response and treatment outcomes for PCa in this cohort of patients. These findings revealed a comprehensive signature of drug metabolism differences for the Whites, Blacks and Asians, and it may provide some evidence for making individualized treatment strategies.

In soccer, passing is the most frequent interaction between players and plays a significant role in creating scoring chances. Experts are interested in analyzing players' passing behavior to learn passing tactics, i.e., how players build up an attack with passing. Various approaches have been proposed to facilitate the analysis of passing tactics. However, the dynamic changes of a team's employed tactics over a match have not been comprehensively investigated. To address the problem, we closely collaborate with domain experts and characterize requirements to analyze the dynamic changes of a team's passing tactics. To characterize the passing tactic employed for each attack, we propose a topic-based approach that provides a high-level abstraction of complex passing behaviors. Based on the model, we propose a glyph-based design to reveal the multi-variate information of passing tactics within different phases of attacks, including player identity, spatial context, and formation. We further design and develop PassVizor, a visual analytics system, to support the comprehensive analysis of passing dynamics. With the system, users can detect the changing patterns of passing tactics and examine the detailed passing process for evaluating passing tactics. We invite experts to conduct analysis with PassVizor and demonstrate the usability of the system through an expert interview.

Artificial breeding of small yellow croaker (Larimichthys polyactis) was recently achieved, providing a bright future for its commercial farming. In May 2019, a disease outbreak occurred among small yellow croakers in an aquaculture farm near Xiangshan Bay, charactering by white spots spotted on the surface of fish skin, gills and fins. The parasite was preliminarily identified as Cryptocaryon irritans based on morphological feature of the parasite and the symptoms on fish. However, the previously published specific primer pairs failed to confirm the existence of C. iriitans. Six nucleotides mismatches were discovered after mapping specific forward primer back to targeted gene. Therefore, an updated PCR specific primer was developed within the 9th highly variable region of 18S rRNA gene and conserved in all C. irritans sequences available in GenBank database. The specificity was verified in silico by Primer-BLAST against GenBank nucleotide. Laboratory cultured ciliates (Mesanophrys, Pseudokeronopsis and Uronema) as well as natural microbial community samples collected from sea water and river water was used as negative control to verify the specificity of the primer in situ. Besides, tank transfer method was used to evaluate the treatment of the parasite infection. By tank transfer method, 2.00 ± 0.61 out of 10 fish that already sever infected were successfully survived after 8 days treatment, meanwhile the control group died out at d 6. More loss to the treatment group during first five days was observed and may attribute to the combined effect from infection and stress the recent domesticated fish suffered during rotation. Therefore, tank transfer method was also effective to prevent small yellow croaker from further infection, however the loss of the small yellow croaker suffered from stress during rotation also needs to be carefully concerned. In conclusion, this study reported the first diagnose of C. irritans infection on small yellow croaker, provided updated specific primer to detect C. irritans infection on fish body and reported the effect of tank transfer on small yellow croaker treatment.

Background Metformin, which is cheap and easy to get, is a first-line anti-hyperglycemia drug. Recently, its anti-tumor effect has been revealed. Here we performed a meta-analysis to summarize previous studies and a narrative review to gather the mechanisms involved in the potential relationship. Methods We searched related articles in database of Pubmed, EMbase, Web of science, the Cochrane Library, China National Knowledge Infrastructure (CNKI), the Wanfang and Sinomed and obtained 8 clinic trials that investigated the connection between metformin and breast cancer metastasis, containing 2 randomized controlled trials (RCTs) and 6 retrospective cohort studies. We evaluated each retrospective cohort study by Newcastle-Ottawa Scale (NOS), while RCT by Chcorane Risk of Bias tool. Pooled hazard ratios (HRs), risk ratios (RRs) and we calculated associated 95% confidence intervals (CIs) with a random-effect, generic inverse variance method. We also collected the possible mechanisms of cancer metastasis inhibition from metformin. Results A total of 8 studies containing 13919 breast cancer patients without distant metastasis before they got anticancer treatment. The result showed that adjuvant metformin in treatment of local breast cancer facilitated to suppress metastasis (HR = 0.69, 95% CI = 0.57–0.82, p I2 = 0%), and the result was consistent with the subgroup of breast cancer patients with type 2 diabetes mellitus (T2DM) (HR = 0.68, 95% CI = 0.57–0.82, p I2 = 0%). Conclusion The meta-analysis suggested metformin might repress the metastasis and be benefit to distant metastasis-free survival (DMFS) when added to systemic breast cancer therapy, supporting anti-tumor effects of metformin on breast cancer.

Massive spatiotemporal data scheduling in a cloud environment play a significant role in real-time visualization. Existing methods focus on preloading, prefetching, multithread processing and multilevel cache collaboration, which waste hardware resources and cannot fully meet the different scheduling requirements of diversified tasks. This paper proposes an optimized spatiotemporal data scheduling method based on maximum flow for multilevel visualization tasks. First, the spatiotemporal data scheduling framework is designed based on the analysis of three levels of visualization tasks. Second, the maximum flow model is introduced to construct the spatiotemporal data scheduling topological network, and the calculation algorithm of the maximum data flow is presented in detail. Third, according to the change in the data access hotspot, the adaptive caching algorithm and maximum flow model parameter switching strategy are devised to achieve task-driven spatiotemporal data optimization scheduling. Compared with two typical methods of first come first serve (FCFS) and priority scheduling algorithm (PSA) by simulating visualization tasks at three levels, the proposed maximum flow scheduling (MFS) method has been proven to be more flexible and efficient in adjusting each spatiotemporal data flow type as needed, and the method realizes spatiotemporal data flow global optimization under limited hardware resources in the cloud environment.

Background Non-small cell lung cancer (NSCLC) accounts for a significant proportion of cancer-related deaths and lacks an effective treatment strategy. NSCLC tissues are generally found in a low oxygen environment. The NDUFA4L2 protein, located in the mitochondria, is encoded by the nucleus genome and is considered a crucial mediator that regulates cell survival. A better understanding of the mechanism of NDUFA4L2 in NSCLC survival in hypoxic environments is essential to design new therapeutic methods. Methods Twenty NSCLC and corresponding paired non-tumorous lung tissue samples were collected. NSCLC cell lines were cultured in hypoxic conditions to investigate the mechanism of NDUFA4L2 in NSCLC. The role of NDUFA4L2 was confirmed by using Western blotting, reactive oxygen species measurement, flow cytometry, immunofluorescence analysis, and wound healing and colony formation assays. Results The expression of HIF-1α and mitochondrial NDUFA4L2 increased in NSCLC cell lines cultured in hypoxic conditions (1% O2 ). NDUFA4L2 was drastically overexpressed in human NSCLC tissues and cell lines cultured in hypoxic conditions. HIF-1α regulated the expression of NDUFA4L2. Knockdown of NDUFA4L2 notably increased mitochondrial reactive oxygen species production, which suppressed the viability of NSCLC. Conclusion In conclusion, overexpression of NDUFA4L2 is a key factor for maintaining NSCLC growth, suggesting that mitochondrial NDUFA4L2 may be a potential target for the treatment of lung cancer.

Regarded as a high-level tactic in soccer, a team formation assigns players different tasks and indicates their active regions on the pitch, thereby influencing the team performance significantly. Analysis of formations in soccer has become particularly indispensable for soccer analysts. However, formations of a team are intrinsically time-varying and contain inherent spatial information. The spatio-temporal nature of formations and other characteristics of soccer data, such as multivariate features, make analysis of formations in soccer a challenging problem. In this study, we closely worked with domain experts to characterize domain problems of formation analysis in soccer and formulated several design goals. We design a novel spatio-temporal visual representation of changes in team formation, allowing analysts to visually analyze the evolution of formations and track the spatial flow of players within formations over time. Based on the new design, we further design and develop ForVizor, a visual analytics system, which empowers users to track the spatio-temporal changes in formation and understand how and why such changes occur. With ForVizor, domain experts conduct formation analysis of two games. Analysis results with insights and useful feedback are summarized in two case studies.

Individual tree detection and crown delineation (ITDD) are critical in forest inventory management and remote sensing based forest surveys are largely carried out through satellite images. However, most of these surveys only use 2D spectral information which normally has not enough clues for ITDD. To fully explore the satellite images, we propose a ITDD method using the orthophoto and digital surface model (DSM) derived from the multi-view satellite data. Our algorithm utilizes the top-hat morphological operation to efficiently extract the local maxima from DSM as treetops, and then feed them to a modified superpixel segmentation that combines both 2D and 3D information for tree crown delineation. In subsequent steps, our method incorporates the biological characteristics of the crowns through plant allometric equation to falsify potential outliers. Experiments against manually marked tree plots on three representative regions have demonstrated promising results – the best overall detection accuracy can be 89%.

Rationale: Breast metastasis from serous borderline tumor with micro-invasive carcinoma of ovary is a very rare condition. The breast lump as the only clinical presentation is rarely seen in ovarian carcinoma, which may lead to be misdiagnosed, and the mechanism of breast metastasis from ovarian tumors in early stage still needs to be explored. Differentiation from primary breast cancer and extramammary malignancy is crucial because the treatment and prognosis are significantly different. Patient concerns: A 33-year-old female presented with a painless, movable, 1.0 × 1.0 cm lump in the upper outer quadrant of the right breast for a month. Diagnoses: Breast metastasis of serous borderline tumor with micro-invasive ovarian carcinoma confirmed by pathology and immunohistochemistry. Interventions: The patient underwent lumpectomy, bilateral ovarian tumor stripping operation and prophylactic chemotherapy. Outcomes: No signs of recurrence have been detected in 1.5 years of follow-up. Lessons: Distant metastasis may occur in early stage of ovarian carcinoma. It is important to determine the origin of the primary tumor and develop an effective treatment strategy for patients. Imaging findings and pathological diagnostic criteria are important to accurately differentiate between metastasis and primary breast lesions, which may improve the patient's outcomes.

Analyzing social streams is important for many applications, such as crisis management. However, the considerable diversity, increasing volume, and high dynamics of social streams of large events continue to be significant challenges that must be overcome to ensure effective exploration. We propose a novel framework by which to handle complex social streams on a budget PC. This framework features two components: 1) an online method to detect important time periods (i.e., subevents), and 2) a tailored GPU-assisted Self-Organizing Map (SOM) method, which clusters the tweets of subevents stably and efficiently. Based on the framework, we present StreamExplorer to facilitate the visual analysis, tracking, and comparison of a social stream at three levels. At a macroscopic level, StreamExplorer uses a new glyph-based timeline visualization, which presents a quick multi-faceted overview of the ebb and flow of a social stream. At a mesoscopic level, a map visualization is employed to visually summarize the social stream from either a topical or geographical aspect. At a microscopic level, users can employ interactive lenses to visually examine and explore the social stream from different perspectives. Two case studies and a task-based evaluation are used to demonstrate the effectiveness and usefulness of StreamExplorer.Analyzing social streams is important for many applications, such as crisis management. However, the considerable diversity, increasing volume, and high dynamics of social streams of large events continue to be significant challenges that must be overcome to ensure effective exploration. We propose a novel framework by which to handle complex social streams on a budget PC. This framework features two components: 1) an online method to detect important time periods (i.e., subevents), and 2) a tailored GPU-assisted Self-Organizing Map (SOM) method, which clusters the tweets of subevents stably and efficiently. Based on the framework, we present StreamExplorer to facilitate the visual analysis, tracking, and comparison of a social stream at three levels. At a macroscopic level, StreamExplorer uses a new glyph-based timeline visualization, which presents a quick multi-faceted overview of the ebb and flow of a social stream. At a mesoscopic level, a map visualization is employed to visually summarize the social stream from either a topical or geographical aspect. At a microscopic level, users can employ interactive lenses to visually examine and explore the social stream from different perspectives. Two case studies and a task-based evaluation are used to demonstrate the effectiveness and usefulness of StreamExplorer.

Gap exists in the interface of cement asphalt emulsion mortar and CRTS I track slab universally, which is more severe at four corners than other parts of the track slab. In this work, the temperature and elevation of CRTS I slab track with and without rail were measured continuously to study the influence mechanism of rail on the gap. The results show that the alternating temperature gradient of track slab is the main reason that causes the gap, and laying rail can efficiently decrease the gap size in the slab track without rail. Compared with the slab track without rail, the maximum elevation occurred at the corner, the maximum gap width and the maximum gap depth of the slab track with rail laid were decreased by 0.45 mm (25.7%), 0.75 mm (46.6%) and 9.5 mm (59.4%), respectively; meanwhile, the disqualification ratio at corners was reduced to 5.9%, which is 50% less than that of the track without rail. When elevation mismatch occurs in adjacent track slabs, a gasket should be placed at rail-bearing bed below the track slab in order to avoid the lower slab being dragged up by the higher slab and the further occurrence of new gap.

We report the design and fabrication of high speed evanescently coupled InGaAs/InP uni-traveling-carrier-photodiodes (UTC-PDs). A self-aligned passive waveguide is integrated with the PDs by a simple fabrication procedure. Open eye diagrams at 32 Gb/s under zero bias are demonstrated for the first time, to the best of our knowledge, from evanescently or edge coupled InP based PDs, which are easier to be integrated with other optical components than surface illuminated PDs. When used for photonic integrated circuits (PICs) applications, our PDs help to lower the electrical cross talk and power consumption of PICs chips.

AlGaInAs electroabsorption-modulated lasers (EMLs) fabricated by identical epitaxial layer technique are demonstrated. The EML device shows an infinite characteristic temperature when the temperature ranges from 20 o C to 30 o C. The integrated modulator has static extinction ratios of larger than 20 dB at a reverse bias voltage of − 2 V. The small signal modulation bandwidth of the modulator is larger than 11 GHz. At 10 Gb/s data modulation, the dynamic extinction ratio is about 9.5 dB in a back to back test configuration. Because only a simple fabrication procedure is needed, our EMLs are promising low cost light sources for optical fiber transmission applications.

We present electroabsorption modulators integrated with distributed feedback lasers (EMLs) fabricated by a simple method, which combines the advantages of the selective area growth and double stack active layer techniques. The obtained EML device has a threshold current as low as 16 mA and optical power of larger than 10 mW at 85 mA laser current. Quite low chirp parameter of the fabricated EMLs is obtained. Negative chirp parameters can be obtained at only about 0.5 V reverse bias voltage. Open eye diagrams are demonstrated from the EML at both 10 and 20 Gb/s modulations with the driving voltage of only 0.65 V while securing high dynamic extinction ratio. The exhibited performance makes our device a very promising candidate as a simple light source in long distance and cost sensitive applications.

We present data transmission using a directly modulated distributed Bragg reflector (DBR) laser having an integrated Ti thin film heater in the DBR section and butt-jointed InGaAsP as DBR material. By combining DBR current tuning and thermal tuning effects, an over 16 nm wavelength tuning range is obtained. 5 Gb/s data transmissions are conducted at up to 25 km distance and different wavelengths. In the fabricated device, the butt-jointed InGaAsP material is also used for the formation of an integrated photodiode for monitoring the light power of the device.

Efficient electrocatalytic hydrogen evolution reaction (HER) is one of the most promising ways to low-cost hydrogen production in the future. However, it is still a challenge to develop efficient, durable, and affordable catalysts. In this paper, we choose ultrasmall Pt nanoclusters, metallic MoO2 semiconductor, and conductive material with ultralow Pt loadings as an active and durable catalyst for HER in acid media. The obtained 0.5 wt % Pt–MoO2/MWCNTs catalyst with ultralow Pt loadings exhibits high-efficiency electrocatalytic activity and excellent stability. Benefiting from the space confinement effect and good electric conductivity of metallic MoO2 and MWCNTs, the HER activity of as-made 0.5 wt % Pt–MoO2/MWCNTs catalyst is comparable to that of commercial 20 wt % Pt/C catalyst. Remarkably, the strong interaction between metallic Pt and MoO2 support can prevent the aggregation of Pt species; the 0.5 wt % Pt–MoO2/MWCNTs sample shows better stability than 0.5 wt % Pt–MWCNTs and commercial 20 wt % Pt/C. ...

Compressed sensing changes the conventional image processing model of full collection-sampling-compression-transmission-reconstruction and provides a more feasible way to the UAV wireless transmission. Existing matching pursuit algorithms cannot simultaneously meet the requirements of reconstruction accuracy and reconstruction efficiency in UAV wireless transmission, especially when the images are polluted by some noise. Hence, we propose an effective noisy image reconstruction algorithm based on low-rank which introduces the low-rank matrix decomposition and the Augmented Lagrange Multiplier to realize the tradeoff between reconstruction accuracy and reconstruction efficiency. Experimental results verify that the proposed LR algorithm has a superior and stable reconstruction performance on noisy image reconstruction compared with the matching pursuit algorithms.

The design and fabrication of an evanescently coupled waveguide InGaAs unitraveling-carrier photodiode (PD) are presented. Through doping the InGaAs absorption layer gradedly, a large built-in electric field can be obtained. As a result, a 4- $\mu \text{m}$ -wide 15- $\mu \text{m}$ -long PD has a bandwidth larger than 21 GHz at zero bias. Passive input waveguide is integrated monolithically with the PD by a simple process, which eases the integration of PD with other optical components.

// Tingting Liu 1 , Lika’a Fasih Y. Al-Kzayer 2 , Xiao Xie 3 , Hua Fan 4 , Shamil Naji Sarsam 5 , Yozo Nakazawa 2 and Lei Chen 6 1 Department of Pediatric Hematology/Oncology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China 2 Department of Pediatrics, Shinshu University School of Medicine, Matsumoto, Japan 3 Department of Thoracic Cardiovascular Surgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China 4 Department of Radiology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China 5 Department of Radiology, Ibn Al-Nafees Hospital, Manama, Kingdom of Bahrain 6 Department of Pathology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China Correspondence to: Lei Chen, email: chenlei021@sina.com Keywords: mediastinal lesions, age distribution, histopathological distribution, the mediastinum Received: January 30, 2017 Accepted: April 06, 2017 Published: April 18, 2017 ABSTRACT The objective of this study was to identify the differences in histopathological distribution and clinical features of mediastinal lesions (MLs) across the age spectrum in Chinese series of patients and to compare with the available literature. A total of 409 cases of MLs, including 137 pediatric and 272 adult patients from a single institution, was reviewed and categorized into groups according to age. Among the 409 cases, the age showed a bimodal distribution with an increased incidence of MLs among (< 10 year) and (60–< 70 year) age groups. Thymic lesions, neurogenic tumors, and cysts made up 57% of MLs among the 409 cases. A significantly higher frequency was found for neurogenic tumors, germ cell tumors, mesenchymal tumors, and lymphatic lesions, ( p < 0.01) for all, in pediatric population compared to adults. On the contrary, frequencies of thymic lesions and metastatic carcinomas were significantly higher in adults compared to pediatric category, ( p < 0.01) for both. Overall, 41.6% were asymptomatic, however, pediatric patients showed a significantly higher incidence of cough and fever, ( p < 0.01) for both, and dyspnea ( p = 0.02), than adults. Whereas adult subset showed a significantly higher incidence of chest pain ( p = 0.02), or oppression ( p < 0.01), than pediatric counterpart. In conclusion, the age spectrum was the factor that influenced the histopathological distribution and the clinical presentation of MLs in Chinese series of patients. Such differences might be considered in the differential diagnosis and therapeutic approach for adult as well as pediatric patients with MLs. Furthermore, our study was comparable to the literature in terms of MLs frequencies.

AIM To assess the value of quantitative analysis of sound touch elastography of tissues around breast lesions to facilitate the evaluation of malignancy of the lesions. MATERIALS AND METHODS With the permission of the Ethics Committee, every patient signed informed consent forms before the study. One hundred and eighty-two solid breast lesions were analysed retrospectively. Postoperative histopathology proved that 63 lesions were malignant and 119 were benign. All lesions were examined by two-dimensional ultrasonography, colour Doppler ultrasonography and ultrasound elastography including sound touch elastography (STE) and strain elastography. Using pathological diagnosis as the reference, the correlation between each ultrasound marker and the malignancy of the solid breast masses was evaluated by chi-square test, and the logistic regression model was constructed to determine the best diagnostic model with multiple markers. RESULTS The areas under the receiver operating characteristic (ROC) curve (AUCs) of various elastography markers were compared and the markers with the largest AUC values, including quantitative, semi-quantitative, and distance markers were identified. Logistic regression analysis showed that the combination of accuracy of Breast Imaging Reporting and Data System (BI-RADS) classification + age + maximum elasticity value of the tissue around the lesion (EMax_shell) in predicting malignant lesions was higher than that of the other combinations. The prediction model verified that the sensitivity of diagnosis of the mammary lump was 94.12% and the specificity was 84.13%. CONCLUSIONS EMax_shell in the elasticity is the most valuable marker for the diagnosis of breast cancer, and age combined with EMax_shell can effectively improve the diagnostic efficacy of the BI-RADS classification in breast cancer.

Carry trade refers to a risky arbitrage in interest rate differentials between two currencies. Persistent excess carry trade returns pose a challenge to foreign exchange market efficiency. Using a data set of ten currencies between 1990 and 2017, we find: (i) a machine learning model, long short-term memory (LSTM) networks, forecast carry trade returns better than linear and threshold regressions based on economic fundamentals; and (ii) excess carry trade returns deteriorate after the 2007--2008 global financial crisis in LSTM networks and other model forecasts, indicating that the uncovered interest rate parity may still hold in the long run.

Simulative analysis in competitive sports can provide prospective insights, which can help improve the performance of players in future matches. However, adequately simulating the complex competition process and effectively explaining the simulation result to domain experts are typically challenging. This work presents a design study to address these challenges in table tennis. We propose a well-established hybrid second-order Markov chain model to characterize and simulate the competition process in table tennis. Compared with existing methods, our approach is the first to support the effective simulation of tactics, which represent high-level competition strategies in table tennis. Furthermore, we introduce a visual analytics system called Tac-Simur based on the proposed model for simulative visual analytics. Tac-Simur enables users to easily navigate different players and their tactics based on their respective performance in matches to identify the player and the tactics of interest for further analysis. Then, users can utilize the system to interactively explore diverse simulation tasks and visually explain the simulation results. The effectiveness and usefulness of this work are demonstrated by two case studies, in which domain experts utilize Tac-Simur to find interesting and valuable insights. The domain experts also provide positive feedback on the usability of Tac-Simur. Our work can be extended to other similar sports such as tennis and badminton.

Uterine arteriovenous malformation (AVM) is an extremely rare condition characterized by abnormal connections between veins and arteries. The atypical clinical manifestations and relatively low morbidity of AVM are conducive to missed diagnosis. The present study describes a case of a 47-year-old female patient with congenital uterine AVM followed by iatrogenic AVM. The diagnosis was established by contrast-enhanced ultrasound combined with contrast-enhanced CT (CECT). Because the symptom of vaginal bleeding was severe, trophoblastic disease or neoplasia could be preferred. The manifestations on various imaging examinations were carefully assessed, and the relevant literature was also reviewed.

Intramural pregnancy is an uncommon type of ectopic pregnancy, where the gestational sac is completely encircled by myometrium and unconnected with endometrial cavity, fallopian tubes or round ligament. Owing to its potentially life-threatening hemorrhage and uterine rupture, early diagnosis and management are urgently required. We present a case of a woman undergoing zigzag medical procedures, which featured non-consensus preoperative diagnosis of intramural and interstitial pregnancy and an intramural ectopic pregnancy ultimately confirmed and successfully removed by emergency laparoscopy. Additionally, we present a review of the related literature and discuss its varied clinical features, imageological characters, diagnosis, differential diagnosis and multiple treatments. A comprehensive bibliographic search through PubMed, using keywords: intramural ectopic pregnancy. Relevant literatures published from January 2013 to April 2019 were reviewed. Twenty-four cases in total for intramural ectopic pregnancy including this report were reviewed. Diagnoses were mainly made by ultrasound images. Most patients had a history of uterine surgery or intrauterine operation and had been surgically resected. None of the mothers were in danger, but only one case had live birth at 37 weeks of gestation. Non-specific clinical presentation and non-uniform ultrasound criteria pose a challenge for us to make timely and accurate management. Integrated radiological examinations and communication and cooperation between sonographers and gynecologists play a vital role in diagnostic accuracy and selecting the optimal therapeutic method of an intramural pregnancy.

To accurately and formally represent the historical trajectory and present the current situation of land use/land cover (LULC), numerous types of classification standards for LULC have been developed by different nations, institutes, organizations, etc., however, these land cover classification systems and legends generate polysemy and ambiguity in integration and sharing. The approaches for dealing with semantic heterogeneity have been developed in terms of semantic similarity. Generally speaking, these approaches lack domain ontologies, which might be a significant barrier to implementing these approaches in terms of semantic similarity assessment. In this paper, we propose an ontological approach to assess the similarity of the domain of LULC classification systems and standards. We develop domain ontologies to explicitly define the descriptions and codes of different LULC classification systems and standards as semantic information, and formally organize this semantic information as rules for logical reasoning. Then, we utilize a Bayes algorithm to create a conditional probabilistic model for computing the semantic similarity of terms in two separate LULC land cover classification systems. The experiment shows that semantic similarity can be effectively measured by integrating a probabilistic model based on the content of ontology.

Although the clinical benefit of laparoscopic splenectomy and devascularization (LSD) has been elaborated in many studies, its application in massive splenomegaly remains controversial. We conducted a retrospective research to assess the curative efficacy of LSD for massive splenomegaly due to portal hypertension. Forty-seven patients with massive splenomegaly due to portal hypertension were enrolled in this study, and divided into two groups. Twenty-one patients underwent open splenectomy and devascularization (OSD) from June 2010 to October 2012 (OSD group). From March 2013 to February 2015, LSD was performed on 26 patients (LSD group). Perioperative variables were analyzed. Compared to OSD, LSD was associated with less blood loss (241.9±110.0 mL vs. 319.0±139.5 mL, P

Many studies have been published on the association between IFNL4 rs368234815 single-nucleotide polymorphism (SNP) and sustained virological response (SVR) in chronic hepatitis C (CHC) patients undergoing treatment with PEGylated interferon (PEG-IFN) plus ribavirin (RBV). Because of the variable and sometimes inconsistent results, we performed a meta-analysis to estimate the association between these factors.We conducted a search of the literature published prior to July 1, 2014. The pooled results were analyzed as the odds ratios (ORs) and corresponding 95% confidence intervals (CIs) using random-effect model.The pooled results revealed that the rs368234815 TT/TT genotype was significantly correlated with SVR in HCV-1/4-infected Caucasian patients (OR=4.65, 95% CI=3.36-6.42, P0.00001) but not in HCV-2/3-infected Caucasian patients (OR=1.44, 95% CI: 0.89-2.33, P=0.13). Conversely, the rs368234815 ΔG/ΔG genotype was significantly linked to treatment failure in Caucasian patients (OR=0.49, 95% CI: 0.38-0.64, P0.00001), regardless of the HCV genotype.The results of the meta-analysis suggest that IFNL4 rs368234815 polymorphism may be a predictor of SVR in Caucasian HCV-1/4-infected patients.

Automatic road extraction from remote-sensing imagery plays an important role in many applications. However, accurate and efficient extraction from very high-resolution (VHR) images remains difficult because of, for example, increased data size and superfluous details, the spatial and spectral diversity of road targets, disturbances (e.g., vehicles, shadows of trees, and buildings), the necessity of finding weak road edges while avoiding noise, and the fast-acquisition requirement of road information for crisis response. To solve these difficulties, a two-stage method combining edge information and region characteristics is presented. In the first stage, convolutions are executed by applying Gabor wavelets in the best scale to detect Gabor features with location and orientation information. The features are then merged into one response map for connection analysis. In the second stage, highly complete, connected Gabor features are used as edge constraints to facilitate stable object segmentation and limit region growing. Finally, segmented objects are evaluated by some fundamental shape features to eliminate nonroad objects. The results indicate the validity and superiority of the proposed method to efficiently extract accurate road targets from VHR remote-sensing images.

Targeted drugs have been widely used in the treatment of patients with lung cancer, particularly for those with non-small cell lung cancer (NSCLC). Plasma cell-free DNA is an emerging clinical tool for the detection of epidermal growth factor receptor (EGFR) gene mutation in patients with lung cancer. Detection of circulating tumor (ct) DNA by droplet digital PCR (ddPCR) is a highly sensitive and minimally invasive alternative for the assessment and management of cancer. In the present study, four ddPCR systems were developed to detect the 19DELs, L858R, T790M and C797S mutations of the EGFR gene in plasma ctDNA samples, and all exhibited higher sensitivity compared with the amplification refractory mutation system (ARMS)-PCR assays. The results revealed that the sensitivity of the ddPCR assays for the four major types of EGFR mutant reached 0.04%. In total, 50 plasma ctDNA samples were collected from patients with NSCLC to detect the 19DELs, L858R, T790M and C797S mutations by ddPCR and ARMS-PCR. All the mutations except for C797S were detected and the concordance rates between ddPCR and ARMS-PCR were 96% (19DELs), 98% (L858R) and 100% (T790M). The fraction of EGFR mutation ranged from 0.43 to 68.07% using the ddPCR method. Therefore, the present study suggests that the four ddPCR testing systems could be used for early detection of EGFR mutations in plasma samples, so that patients can better select the targeted drugs according to the EGFR mutation.

Interactive visualization of large image collections is important and useful in many applications, such as personal album management and user profiling on images. However, most prior studies focus on using low-level visual features of images, such as texture and color histogram, to create visualizations without considering the more important semantic information embedded in images. This paper proposes a novel visual analytic system to analyze images in a semantic-aware manner. The system mainly comprises two components: a semantic information extractor and a visual layout generator. The semantic information extractor employs an image captioning technique based on convolutional neural network (CNN) to produce descriptive captions for images, which can be transformed into semantic keywords. The layout generator employs a novel co-embedding model to project images and the associated semantic keywords to the same 2D space. Inspired by the galaxy metaphor, we further turn the projected 2D space to a galaxy visualization of images, in which semantic keywords and images are visually encoded as stars and planets. Our system naturally supports multi-scale visualization and navigation, in which users can immediately see a semantic overview of an image collection and drill down for detailed inspection of a certain group of images. Users can iteratively refine the visual layout by integrating their domain knowledge into the co-embedding process. Two task-based evaluations are conducted to demonstrate the effectiveness of our system.