The impact of childhood symptoms of conduct disorder on driver aggression in adulthood

Background

Despite limited empirical investigation, existing scientific literature suggests that individuals with a history or current diagnosis of conduct disorder (CD) may be more likely to demonstrate reckless and aggressive driving. Much of the limited research in this field examines the impact of childhood CD on driver behaviour and collision risk in young adults. Few if any, studies assess the impact of this disorder on driver behaviour beyond age 21 years. The current research is a population-based study of the impact of CD symptoms during childhood on the risk of engaging in driver aggression during adulthood.

Methods

Data are based on telephone interviews with 5230 respondents who reported having driven in the past year. Data are derived from the 2011–2013 cycles of the CAMH Monitor, an ongoing cross-sectional survey of adults in Ontario, Canada aged 18 years and older. A binary logistic regression analysis of self-reported driver aggression in the previous 12 months was conducted, consisting of measures of demographic characteristics, driving exposure, problem substance use, alcohol- and drug-impaired driving, symptoms of attention deficit hyperactivity disorder, and childhood (before age 15) symptoms of CD.

Results

When entered with demographic characteristics, driving exposure, and other potential confounders, childhood symptoms of CD increased the odds of reporting driver aggression more than two-fold (adjusted OR = 2.12). Exploratory analyses of the interaction between childhood symptoms of CD and age was not a significant predictor of driver aggression.

Conclusions

Results suggest that symptoms of CD during childhood are associated with significantly increased odds of self-reported driver aggression during adulthood. Limitations and future directions of the research are discussed.     

Low‐level PGAS computing on many‐core processors with TSHMEM

Diminishing returns from increased clock frequencies and instruction‐level parallelism have forced computer architects to adopt architectures that exploit wider parallelism through multiple processor cores. While emerging many‐core architectures have progressed at a remarkable rate, concerns arise regarding the performance and productivity of numerous parallel‐programming tools for application development. Development of parallel applications on many‐core processors often requires developers to familiarize themselves with unique characteristics of a target platform while attempting to maximize performance and maintain correctness of their applications. The family of partitioned global address space (PGAS) programming models comprises the current state of the art in balancing performance and programmability. One such PGAS approach is SHMEM, a lightweight, shared‐memory programming library that has demonstrated high performance and productivity potential for parallel‐computing systems with distributed‐memory architectures. In the paper, we present research, design, and analysis of a new SHMEM infrastructure specifically crafted for low‐level PGAS on modern and emerging many‐core processors featuring dozens of cores and more. Our approach (with a new library known as TSHMEM) is investigated and evaluated atop two generations of Tilera architectures, which are among the most sophisticated and scalable many‐core processors to date, and is intended to enable similar libraries atop other architectures now emerging. In developing TSHMEM, we explore design decisions and their impact on parallel performance for the Tilera TILE‐Gx and TILEPro many‐core architectures, and then evaluate the designs and algorithms within TSHMEM through microbenchmarking and applications studies with other communication libraries. Our results with barrier primitives provided by the Tilera libraries show dissimilar performance between the TILE‐Gx and TILEPro; therefore, TSHMEM's barrier design takes an alternative approach and leverages the on‐chip mesh network to provide consistent low‐latency performance. In addition, our experiments with TSHMEM show that naive collective algorithms consistently outperformed linear distributed collective algorithms when executed in an SMP‐centric environment. In leveraging these insights for the design of TSHMEM, our approach outperforms the OpenSHMEM reference implementation, achieves similar to positive performance over OpenMP and OSHMPI atop MPICH, and supports similar libraries in delivering high‐performance parallel computing to emerging many‐core systems. Copyright © 2015 John Wiley & Sons, Ltd.     

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

In financial decision‐making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi‐structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium‐size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision‐maker to analyse the financial options.     

CD26 Induces Colorectal Cancer Angiogenesis and Metastasis through CAV1/MMP1 Signaling

CD26 has been reported as a marker for colorectal cancer stem cells endowed with tumor-initiating properties and capable of colorectal cancer (CRC) metastasis. In this study, we investigated the functional effect of CD26 on CRC angiogenesis and metastasis, and the potential underlying mechanism. The functional effects of CD26 overexpression or repression were determined by a wound healing experiment, and cell migration and invasion assays in vitro and in mouse models. Differentially expressed genes regulated by CD26 were identified by genome-wide mRNA expression array and validated by quantitative PCR. CD26 functionally regulated CRC cell migration and invasion in vitro and angiogenesis and metastasis in vivo. Genome-wide mRNA expression array and qPCR showed that MMP1 was up-regulated in CD26+ subpopulation, and a subsequent experiment demonstrated the regulatory effect of CD26 on MMP1 in CRC cell lines with CD26 repression or overexpression. Furthermore, overexpression of CAV1 abrogated the CD26-regulated MMP1 induction in CRC cell lines. This study demonstrated the functional roles of CD26 in inducing CRC migration, invasion, angiogenesis and metastasis and identified the potential involvement of MMP1 and CAV1 in such process. CD26 is an attractive therapeutic target for combating tumor progression to improve the prognosis of CRC patients.     

Comparison and Characterization of Compounds with Antioxidant Activity in Lycium barbarum Using High‐Performance Thin Layer Chromatography Coupled with DPPH Bioautography and Tandem Mass Spectrometry

Methanol extracts from 50 batches of Lycium barbarum (L. barbarum, wolfberry) in China were compared and characterized using high‐performance thin‐layer chromatography coupled with 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) bioautography (HPTLC‐DPPH) and electrospray ionization quadrupole time‐of‐flight tandem mass spectrometry (ESI‐Q‐TOF‐MS/MS), respectively. Results showed that similar components occupying the major antioxidant activity existed in L. barbarum collected from different origins. However, the average antioxidant capacities of methanol extracts of L. barbarum collected in Ningxia were significantly higher than those of Qinghai, Xinjiang, Inner Mongolia, and Gansu, which may contribute to rational use of L. barbarum in China. Furthermore, the chemical structure of compound with the highest antioxidant capacity was tentatively identified as 2‐O‐β‐d ‐glucopyranosyl‐l ‐ascorbic acid using ESI‐Q‐TOF‐MS/MS analysis, which possessed high potentials to be used as an antioxidant biomarker for the quality control of L. barbarum. Results are helpful for the bioactivity‐based quality control of L. barbarum, and beneficial for the improvement of their performance in functional/health foods area, suggesting that HPTLC‐DPPH bioautography with ESI‐Q‐TOF‐MS/MS could be used as a routine approach for quality control of antioxidant components in L. barbarum.