The impact of anti-diabetic drugs on colorectal cancer risk in a large cohort of women with diabetes

No Abstrac

On the Patent Claim Eligibility Prediction Using Text Mining Techniques

With the widespread of computer software in recent decades, software patent has become controversial for the patent system. Of the many patentability requirements, patentable subject matter serves as a gatekeeping function to prevent a patent from preempting future innovation. Software patents may easily fall into the gray area of abstract ideas, whose allowance may hinder future innovation. However, without a clear definition of abstract ideas, determining the patent claim subject matter eligibility is a challenging task for examiners and applicants. In this research, in order to solve the software patent eligibility issues, we propose an effective model to determine patent claim eligibility by text-mining and machine learning techniques. Drawing upon USPTO issued guidelines, we identify 66 patent cases to design domain knowledge features, including abstractness features and distinguishable word features, as well as other textual features, to develop the claim eligibility prediction model. The experiment results show our proposed model reaches the accuracy of more than 80%, and domain knowledge features play a crucial role in our prediction model

Multi-Hop Routing Mechanism for Reliable Sensor Computing

Current research on routing in wireless sensor computing concentrates on increasing the service lifetime, enabling scalability for large number of sensors and supporting fault tolerance for battery exhaustion and broken nodes. A sensor node is naturally exposed to various sources of unreliable communication channels and node failures. Sensor nodes have many failure modes, and each failure degrades the network performance. This work develops a novel mechanism, called Reliable Routing Mechanism (RRM), based on a hybrid cluster-based routing protocol to specify the best reliable routing path for sensor computing. Table-driven intra-cluster routing and on-demand inter-cluster routing are combined by changing the relationship between clusters for sensor computing. Applying a reliable routing mechanism in sensor computing can improve routing reliability, maintain low packet loss, minimize management overhead and save energy consumption. Simulation results indicate that the reliability of the proposed RRM mechanism is around 25% higher than that of the Dynamic Source Routing (DSR) and ad hoc On-demand Distance Vector routing (AODV) mechanisms

A Shallow Ritz Method for Elliptic Problems with Singular Sources

In this paper, a shallow Ritz-type neural network for solving elliptic equations with delta function singular sources on an interface is developed. There are three novel features in the present work; namely, (i) the delta function singularity is naturally removed, (ii) level set function is introduced as a feature input, (iii) it is completely shallow, comprising only one hidden layer. We first introduce the energy functional of the problem and then transform the contribution of singular sources to a regular surface integral along the interface. In such a way, the delta function singularity can be naturally removed without introducing a discrete one that is commonly used in traditional regularization methods, such as the well-known immersed boundary method. The original problem is then reformulated as a minimization problem. We propose a shallow Ritz-type neural network with one hidden layer to approximate the global minimizer of the energy functional. As a result, the network is trained by minimizing the loss function that is a discrete version of the energy. In addition, we include the level set function of the interface as a feature input of the network and find that it significantly improves the training efficiency and accuracy. We perform a series of numerical tests to show the accuracy of the present method and its capability for problems in irregular domains and higher dimensions

Rapid identification of Mycobacterium tuberculosis infection by a new array format-based surface plasmon resonance method

Tubercle bacillus [TB] is one of the most important chronic infectious diseases that cause millions of deaths annually. While conventional smear microscopy and culture methods are widely used for diagnosis of TB, the former is insensitive, and the latter takes up to 6 to 8 weeks to provide a result, limiting the value of these methods in aiding diagnosis and intermediate decisions on treatment. Therefore, a rapid detection method is essential for the diagnosis, prognosis assessment, and recurrence monitoring. A new surface plasmon resonance [SPR] biosensor based on an array format, which allowed immobilizing nine TB antigens onto the sensor chip, was constructed. Simultaneous determination of multiple TB antibodies in serum had been accomplished with this array-based SPR system. The results were compared with enzyme-linked immunosorbent assay, a conventional immunological method. Array-based SPR showed more advantages in providing label-free and real-time detection. Additionally, the high sensitivity and specificity for the detection of TB infection showed its potential for future development of biosensor arrays for TB diagnosis

Interference-Aware Deployment for Maximizing User Satisfaction in Multi-UAV Wireless Networks

In this letter, we study the deployment of Unmanned Aerial Vehicle mounted Base Stations (UAV-BSs) in multi-UAV cellular networks. We model the multi-UAV deployment problem as a user satisfaction maximization problem, that is, maximizing the proportion of served ground users (GUs) that meet a given minimum data rate requirement. We propose an interference-aware deployment (IAD) algorithm for serving arbitrarily distributed outdoor GUs. The proposed algorithm can alleviate the problem of overlapping coverage between adjacent UAV-BSs to minimize inter-cell interference. Therefore, reducing co-channel interference between UAV-BSs will improve user satisfaction and ensure that most GUs can achieve the minimum data rate requirement. Simulation results show that our proposed IAD outperforms comparative methods by more than 10% in user satisfaction in high-density environments.Comment: 5 pages, 3 figures, to appear in IEEE Wireless Communications Letter