The complete mitochondrial genome of a planarian flatworm Girardia tigrina (Tricladida: Dugesiidae).

Girardia tigrina, a freshwater planarian species native to America and introduced to other continents, has been usually used as model organism in many research fields of biology. In this study, we determined the complete mitochondrial genome of G. tigrina using next-generation sequencing (NGS). The complete mitogenome was 15,938 bp in length, with 36 genes, including 12 protein-coding genes, 2 ribosomal RNAs and 22 transfer RNAs, and ATP8 was absent in the mitogenome of G. tigrina as in the mitogenomes of some other flatworms. The maximum-likelihood phylogenetic tree suggested that G. tigrina was closely related to genus Dugesia in the clade of Tricladida.

QuickCash: Secure Transfer Payment Systems.

Payment systems play a significant role in our daily lives. They are an important driver of economic activities and a vital part of the banking infrastructure of any country. Several current payment systems focus on security and reliability but pay less attention to users' needs and behaviors. For example, people may share their bankcards with friends or relatives to withdraw money for various reasons. This behavior can lead to a variety of privacy and security issues since the cardholder has to share a bankcard and other sensitive information such as a personal identification number (PIN). In addition, it is commonplace that cardholders may lose their cards, and may not be able to access their accounts due to various reasons. Furthermore, transferring money to an individual who has lost their bankcard and identification information is not a straightforward task. A user-friendly person-to-person payment system is urgently needed to perform secure and reliable transactions that benefit from current technological advancements. In this paper, we propose two secure fund transfer methods termed QuickCash Online and QuickCash Offline to transfer money from peer to peer using the existing banking infrastructure. Our methods provide a convenient way to transfer money quickly, and they do not require using bank cards or any identification card. Unlike other person-to-person payment systems, the proposed methods do not require the receiving entity to have a bank account, or to perform any registration procedure. We implement our QuickCash payment systems and analyze their security strengths and properties.

Social Welfare Control in Mobile Crowdsensing Using Zero-Determinant Strategy.

As a promising paradigm, mobile crowdsensing exerts the potential of widespread sensors embedded in mobile devices. The greedy nature of workers brings the problem of low-quality sensing data, which poses threats to the overall performance of a crowdsensing system. Existing works often tackle this problem with additional function components. In this paper, we systematically formulate the problem into a crowdsensing interaction process between a requestor and a worker, which can be modeled by two types of iterated games with different strategy spaces. Considering that the low-quality data submitted by the workers can reduce the requestor's payoff and further decrease the global income, we turn to controlling the social welfare in the games. To that aim, we take advantage of zero-determinant strategy, based on which we propose two social welfare control mechanisms under both game models. Specifically, we consider the requestor as the controller of the games and, with proper parameter settings for the to-be-adopted zero-determinant strategy, social welfare can be optimized to the desired level no matter what strategy the worker adopts. Simulation results demonstrate that the requestor can achieve the maximized social welfare and keep it stable by using our proposed mechanisms.

On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks.

Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs). In this paper, we focus on the connected target k-coverage (CTC k) problem in heterogeneous wireless sensor networks (HWSNs). A centralized connected target k-coverage algorithm (CCTC k) and a distributed connected target k-coverage algorithm (DCTC k) are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

Wireless Relay Selection in Pocket Switched Networks Based on Spatial Regularity of Human Mobility.

Pocket switched networks (PSNs) take advantage of human mobility to deliver data. Investigations on real-world trace data indicate that human mobility shows an obvious spatial regularity: a human being usually visits a few places at high frequencies. These most frequently visited places form the home of a node, which is exploited in this paper to design two HomE based Relay selectiOn (HERO) algorithms. Both algorithms input single data copy into the network at any time. In the basic HERO, only the first node encountered by the source and whose home overlaps a destination's home is selected as a relay while the enhanced HERO keeps finding more optimal relay that visits the destination's home with higher probability. The two proposed algorithms only require the relays to exchange the information of their home and/or the visiting frequencies to their home when two nodes meet. As a result, the information update is reduced and there is no global status information that needs to be maintained. This causes light loads on relays because of the low communication cost and storage requirements. Additionally, only simple operations are needed in the two proposed algorithms, resulting in little computation overhead at relays. At last, a theoretical analysis is performed on some key metrics and then the real-world based simulations indicate that the two HERO algorithms are efficient and effective through employing only one or a few relays.

Developing prognostic systems of cancer patients by ensemble clustering.

Accurate prediction of survival rates of cancer patients is often key to stratify patients for prognosis and treatment. Survival prediction is often accomplished by the TNM system that involves only three factors: tumor extent, lymph node involvement, and metastasis. This prediction from the TNM has been limited, because other potential prognostic factors are not used in the system. Based on availability of large cancer datasets, it is possible to establish powerful prediction systems by using machine learning procedures and statistical methods. In this paper, we present an ensemble clustering-based approach to develop prognostic systems of cancer patients. Our method starts with grouping combinations that are formed using levels of factors recorded in the data. The dissimilarity measure between combinations is obtained through a sequence of data partitions produced by multiple use of PAM algorithm. This dissimilarity measure is then used with a hierarchical clustering method in order to find clusters of combinations. Prediction of survival is made simply by using the survival function derived from each cluster. Our approach admits multiple factors and provides a practical and useful tool in outcome prediction of cancer patients. A demonstration of use of the proposed method is given for lung cancer patients.