Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

Dynamic robot path planning using an enhanced simulated annealing approach

Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

Genome-wide association study identifies a possible susceptibility locus for endometrial cancer

Background: Genome-wide association studies (GWAS) have identified more than 100 genetic loci for various cancers. However, only one is for endometrial cancer. Methods: We conducted a three-stage GWAS including 8,492 endometrial cancer cases and 16,596 controls. After analyzing 585,963 single-nucleotide polymorphisms (SNP) in 832 cases and 2,682 controls (stage I) from the Shanghai Endometrial Cancer Genetics Study, we selected the top 106 SNPs for in silico replication among 1,265 cases and 5,190 controls from the Australian/British Endometrial Cancer GWAS (stage II). Nine SNPs showed results consistent in direction with stage I with P < 0.1. These nine SNPs were investigated among 459 cases and 558 controls (stage IIIa) and six SNPs showed a direction of association consistent with stages I and II. These six SNPs, plus two additional SNPs selected on the basis of linkage disequilibrium and P values in stage II, were investigated among 5,936 cases and 8,166 controls from an additional 11 studies (stage IIIb). Results: SNP rs1202524, near the CAPN9 gene on chromosome 1q42.2, showed a consistent association with endometrial cancer risk across all three stages, with ORs of 1.09 [95% confidence interval (CI), 1.03–1.16] for the A/G genotype and 1.17 (95% CI, 1.05–1.30) for the G/G genotype (P = 1.6 × 10−4 in combined analyses of all samples). The association was stronger when limited to the endometrioid subtype, with ORs (95% CI) of 1.11 (1.04–1.18) and 1.21 (1.08–1.35), respectively (P = 2.4 × 10−5). Conclusions: Chromosome 1q42.2 may host an endometrial cancer susceptibility locus. Impact: This study identified a potential genetic locus for endometrial cancer risk

Algorithm clustering for multi-algorithm processor design

An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.

Fracture analysis of wind turbine main shaft

Shaft fracture at an early stage of operation is a common problem for a certain type of wind turbine. To determine the cause of shaft failure a series of experimental tests were conducted to evaluate the chemical composition and mechanical properties. A detail analysis involving macroscopic feature and microstructure analysis of the material of the shaft was also performed to have an in depth knowledge of the cause of fracture. The experimental tests and analysis results show that there are no significant differences in the material property of the main shaft when comparing it with the Standard, EN10083-3:2006. The results show that stress concentration on the shaft surface close to the critical section of the shaft due to rubbing of the annular ring and coupled with high stress concentration caused by the change of inner diameter of the main shaft are the main reasons that result in fracture of the main shaft. In addition, inhomogeneity of the main shaft micro-structure also accelerates up the fracture process of the main shaft. In addition, the theoretical calculation of equivalent stress at the end of the shaft was performed, which demonstrate that cracks can easily occur under the action of impact loads. The contribution of this paper is to provide a reference in fracture analysis of similar main shaft of wind turbines.

Mussel-inspired bioceramics with self-assembled Ca-P/polydopamine composite nanolayer : preparation, formation mechanism, improved cellular bioactivity and osteogenic differentiation of bone marrow stromal cells

The nanostructured surface of biomaterials plays an important role in improving their in vitro cellular bioactivity as well as stimulating in vivo tissue regeneration. Inspired by the mussel’s adhesive versatility, which is thought to be due to the plaque–substrate interface being rich in 3,4-dihydroxy-L-phenylalamine (DOPA) and lysine amino acids, in this study we developed a self-assembly method to prepare a uniform calcium phosphate (Ca-P)/polydopamine composite nanolayer on the surface of b-tricalcium phosphate (b-TCP) bioceramics by soaking b-TCP bioceramics in Tris–dopamine solution. It was found that the addition of dopamine, reaction temperature and reaction time are three key factors inducing the formation of a uniform Ca-P/polydopamine composite nanolayer. The formation mechanism of a Ca-P/polydopamine composite nanolayer involved two important steps: (i) the addition of dopamine to Tris–HCl solution decreases the pH value and accelerates Ca and P ionic dissolution from the crystal boundaries of b-TCP ceramics; (ii) dopamine is polymerized to form self-assembled polydopamine film and, at the same time, nanosized Ca-P particles are mineralized with the assistance of polydopamine, in which the formation of polydopamine occurs simultaneously with Ca-P mineralization (formation of nanosized microparticles composed of calcium phosphate-based materials), and finally a self-assembled Ca-P/polydopamine composite nanolayer forms on the surface of the b-TCP ceramics. Furthermore, the formed self-assembled Ca-P/polydopamine composite nanolayer significantly enhances the surface roughness and hydrophilicity of b-TCP ceramics, and stimulates the attachment, proliferation, alkaline phosphate (ALP) activity and bone-related gene expression (ALP, OCN, COL1 and Runx2) of human bone marrow stromal cells. Our results suggest that the preparation of self-assembled Ca-P/polydopamine composite nanolayers is a viable method to modify the surface of biomaterials by significantly improving their surface physicochemical properties and cellular bioactivity for bone regeneration application.

Market turbulence, temporal orientation and firm performance

This study investigates the role of environmental dynamics (i.e., market turbulence) as a factor influencing an organisation’s top management temporal orientation, and the impact of temporal orientation on innovative and financial performance. Results show that firm’s operating in highly turbulent markets exhibit higher degrees of future orientation, as opposed to present orientation. Future-oriented (rather than present-oriented) firms also experience higher levels of both incremental and radical innovations, which in turn generate financial performance. The study highlights the important role of shared strategic mindset (which is contextually influenced) as a driving factor behind the firm innovative and financial performance.

The Tarim picrite-basalt-rhyolite suite, a Permian flood basalt from Northwest China with contrasting rhyolites produced by fractional crystallization and anatexis

We report major and trace element composition, Sr–Nd isotopic and seismological data for a picrite–basalt–rhyolite suite from the northern Tarim uplift (NTU), northwest China. The samples were recovered from 13 boreholes at depths between 5,166 and 6,333 m. The picritic samples have high MgO (14.5–16.8 wt%, volatiles included) enriched in incompatible element and have high 87Sr/86Sr and low 143Nd/144Nd isotopic ratios (εNd (t) = −5.3; Sri = 0.707), resembling the Karoo high-Ti picrites. All the basaltic samples are enriched in TiO2 (2.1–3.2 wt%, volatiles free), have high FeOt abundances (11.27–15.75 wt%, volatiles free), are enriched in incompatible elements and have high Sr and low Nd isotopic ratios (Sri = 0.7049–0.7065; εNd (t) = −4.1 to −0.4). High Nb/La ratios (0.91–1.34) of basalts attest that they are mantle-derived magma with negligible crustal contamination. The rhyolite samples can be subdivided into two coeval groups with overlapping U–Pb zircon ages between 291 ± 4 and 272 ± 2 Ma. Group 1 rhyolites are enriched in Nb and Ta, have similar Nb/La, Nb/U, and Sr–Nd isotopic compositions to the associated basalts, implying that they are formed by fractional crystallization of the basalts. Group 2 rhyolites are depleted in Nb and Ta, have low Nb/La ratios, and have very high Sr and low Nd isotopic ratios, implying that crustal materials have been extensively, if not exclusively, involved in their source. The picrite–basalt–rhyolite suite from the NTU, together with Permian volcanic rocks from elsewhere Tarim basin, constitute a Large Igneous Province (LIP) that is characterized by large areal extent, rapid eruption, OIB-type chemical composition, and eruption of high temperature picritic magma. The Early Permian magmatism, which covered an area >300,000 km2, is therefore named the Tarim Flood Basalt.

Product feature taxonomy learning based on user reviews

In recent years, the Web 2.0 has provided considerable facilities for people to create, share and exchange information and ideas. Upon this, the user generated content, such as reviews, has exploded. Such data provide a rich source to exploit in order to identify the information associated with specific reviewed items. Opinion mining has been widely used to identify the significant features of items (e.g., cameras) based upon user reviews. Feature extraction is the most critical step to identify useful information from texts. Most existing approaches only find individual features about a product without revealing the structural relationships between the features which usually exist. In this paper, we propose an approach to extract features and feature relationships, represented as a tree structure called feature taxonomy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature taxonomy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that our proposed approach is able to capture the product features and relations effectively.

Structured feature extraction using association rules

As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

An efficient proactive route maintenance process for reliable data transmissions in sensor networks

For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

Denial predicts outcome in anxiety following group cognitive behavioral therapy

This study aimed to explore whether participants' pretherapy coping strategies predicted the outcome of group cognitive behavioral therapy (CBT) for anxiety and depression. It was hypothesized that adaptive coping strategies such as the use of active planning and acceptance would be associated with higher reductions, whereas maladaptive coping strategies such as denial and disengagement would be associated with lower reductions in anxious and depressed symptoms following psychotherapy. There were 144 participants who completed group CBT for anxiety and depression. Measures of coping strategies were administered prior to therapy, whereas measures of depression and anxiety were completed both prior to and following therapy. The results showed that higher levels of denial were associated with a poorer outcome, in terms of change in anxiety but not depression, following therapy. These findings suggest the usefulness of using the Denial subscale from the revised Coping Orientation to Problems Experienced (COPE) as a predictor of outcome in group CBT for anxiety.

Social engineering in social networking sites : affect-based model

While social engineering represents a real and ominous threat to many organizations, companies, governments, and individuals, social networking sites (SNSs), have been identified as among the most common means of social engineering attacks. Owing to factors that reduce the ability of users to detect social engineering tricks and increase the ability of attackers to launch them, SNSs seem to be perfect breeding ground for exploiting the vulnerabilities of people, and the weakest link in security. This work will contribute to the knowledge of social engineering by identifying different entities and subentities that affect social engineering based attacks in SNSs. Moreover, this paper includes an intensive and comprehensive overview of different aspects of social engineering threats in SNSs.

Toward understanding social engineering

There is no doubt that social engineering plays a vital role in compromising most security defenses, and in attacks on people, organizations, companies, or even governments. It is the art of deceiving and tricking people to reveal critical information or to perform an action that benefits the attacker in some way. Fraudulent and deceptive people have been using social engineering traps and tactics using information technology such as e-mails, social networks, web sites, and applications to trick victims into obeying them, accepting threats, and falling victim to various crimes and attacks such as phishing, sexual abuse, financial abuse, identity theft, impersonation, physical crime, and many other forms of attack. Although organizations, researchers, practitioners, and lawyers recognize the severe risk of social engineering-based threats, there is a severe lack of understanding and controlling of such threats. One side of the problem is perhaps the unclear concept of social engineering as well as the complexity of understand human behaviors in behaving toward, approaching, accepting, and failing to recognize threats or the deception behind them. The aim of this paper is to explain the definition of social engineering based on the related theories of the many related disciplines such as psychology, sociology, information technology, marketing, and behaviourism. We hope, by this work, to help researchers, practitioners, lawyers, and other decision makers to get a fuller picture of social engineering and, therefore, to open new directions of collaboration toward detecting and controlling it.

Cross-layer design for traffic management in wireless networked control systems

Wireless networked control systems (WNCSs) have been increasingly deployed in industrial applications. As they require timely data packet transmissions, it is difficult to make efficient use of the limited channel resources, particularly in contention based wireless networks in the layered network architecture. Aiming to maintain the WNCSs under critical real-time traffic condition at which the WNCSs marginally meet the real-time requirements, a cross-layer design (CLD) approach is presented in this paper to adaptively adjust the control period to achieve improved channel utilization while still maintaining effective and timely packet transmissions. The effectiveness of the proposed approach is demonstrated through simulation studies.