Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research.

The quality of the constructed social infrastructure project has been considered a necessary measure for the sustainability of projects. Studies on factors affecting project quality have used various techniques and methods to explain the relationships between particular variables. Unexpectedly, Structural Equation Modeling (SEM) has acquired very little concern in factors affecting project quality studies. To address this limitation in the body of knowledge, the objective of this study was to apply the SEM approach and build a model that explained and identified the critical factors affecting quality in social infrastructure projects. The authors developed a quantitative approach using smart-PLS version 3.2.7. This study shed light on the views of different experts based on their experience in public construction projects in Pakistan. Particularly, the authors aimed to find out the relationships between construction, stakeholders, materials, design, and external factors, and how these relate to project quality. The findings of this study revealed that the R 2 value of the model was scored at 0.749, which meant that the five exogenous latent constructs collectively explained 74.9% of the variance in project quality. The Goodness-of-Fit of the model was 0.458. The construction related factor was the most important out of the five constructs. This study determined that better planning and monitoring and evaluation should be developed to better address and control the quality defects by decision-makers, project managers as well as contractors. These findings might support practitioners and decision makers to focus on quality related problems that might occur in their current or future projects.

Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are used to help diagnose heart disease by recording the heart’s activity. However, automated medical-aided diagnosis with computers usually requires a large volume of labeled clinical data without patients' privacy to train the model, which is an empirical problem that still needs to be solved. To address this problem, we propose a generative adversarial network (GAN), which is composed of a bidirectional long short-term memory(LSTM) and convolutional neural network(CNN), referred as BiLSTM-CNN,to generate synthetic ECG data that agree with existing clinical data so that the features of patients with heart disease can be retained. The model includes a generator and a discriminator, where the generator employs the two layers of the BiLSTM networks and the discriminator is based on convolutional neural networks. The 48 ECG records from individuals of the MIT-BIH database were used to train the model. We compared the performance of our model with two other generative models, the recurrent neural network autoencoder(RNN-AE) and the recurrent neural network variational autoencoder (RNN-VAE). The results showed that the loss function of our model converged to zero the fastest. We also evaluated the loss of the discriminator of GANs with different combinations of generator and discriminator. The results indicated that BiLSTM-CNN GAN could generate ECG data with high morphological similarity to real ECG recordings.

Purpose Silencing behavior among project team members (PTM) poses a potential threat to project results. Hence, breaking silence in projects is critical to motivate team members and beneficial for project outcomes. The purpose of this paper is to examine the relationship between transformational leadership (TL) of project manager (PM) and silence behavior of PTMs. It proposes a mediating role of feeling trusted (FT) to fill this gap by conducting an empirical research. Design/methodology/approach A theoretical model was developed and a series of hypotheses were proposed based on existing literature. Then, regression analysis was conducted on a sample of 219 team members of a diverse set of projects in China. Findings The paper empirically shows that TL of PM is significantly negatively related to team members’ defensive and prosocial silence (PS), but not with their acquiescence silence. In addition, the study also discovered that team members’ FT mediates the effects of TL on team members’ defensive and PS. Research limitations/implications This study contributed to the project management literature by showing that feeling trusted link the relationship between TL of PM and PTMs’ silence. The studies’ findings also contribute to the silence theory in project context through discussions of the rationale behind the main effects. Practical implication is provided for PMs that making the most of TL can reduce the silence of PTM, through building trusted feelings. The limitation to this study is the research setting regarding culture-related issues that focused only on projects in China. Originality/value This research is one of the early studies that address the issue of silence behavior in project context, which is a contribution to the coordination and communication in project management.

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Purpose Due to the increasing risk and uncertainty of construction projects, contractual flexibility has been considered as an effective tool to cope with emergences and to promote cooperation between owners and contractors. However, in practice, owners often failed to build an efficient cooperative relationship via contracts, resulting in a lacking of appropriate justice. Furthermore, due to a lack of available empirical research, the influence of contractual flexibility on the cooperative behavior of contractors requires further investigation. The purpose of this paper is to fill this gap by conducting empirical research from the perspective of justice perception. Design/methodology/approach A theoretical model was developed and a series of hypotheses were proposed. Then, partial least squares structural equation modeling analyses were conducted on a sample of 188 respondents. Findings The results show that contractual content and executing flexibility both have a positive influence on the cooperative behavior of a contractor, which was partially mediated by distribution, procedural, and interactional justice perceptions. Moreover, content flexibility has a significant impact on all three types of justice perception, and the execution of flexibility has more impact on interactional justice compared to other justice perceptions. Originality/value The findings contribute to an improved understanding of how contractual flexibility affects the cooperative behavior of contractors, indicating that the owner could develop a fair exchange relationship through flexible contracting and motivation of the other party.

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