The root locus method: application to linear stability analysis and design of cooperative car-following models

A global framework for linear stability analyses of traffic models, based on the dispersion relation root locus method, is presented and is applied taking the example of a broad class of car-following (CF) models. This approach is able to analyse all aspects of the dynamics: long waves and short wave behaviours, phase velocities and stability features. The methodology is applied to investigate the potential benefits of connected vehicles, i.e. V2V communication enabling a vehicle to send and receive information to and from surrounding vehicles. We choose to focus on the design of the coefficients of cooperation which weights the information from downstream vehicles. The coefficients tuning is performed and different ways of implementing an efficient cooperative strategy are discussed. Hence, this paper brings design methods in order to obtain robust stability of traffic models, with application on cooperative CF models

Uniform surface growth of copper oxide nanowires in radiofrequency plasma discharge and limiting factors

The uniform growth of copper oxide nanowires on the top of copper plate has been investigated during the exposure to radiofrequency plasma discharge in respect to plasma properties and its localization. The copper samples of 10 mm radius and 1 mm in thickness were exposed to argon-oxygen plasma created at discharge power of 150 W. After 10 min, almost uniform growth of nanowires was achieved over large surface. There were significant distortions in nanowire length and shape near the edges. Based on the experimental results, we developed a theoretical model, which took into account a balance in heat released at the flow of the current to the nanowire and rejected from the nanowire. This model established a dependence of the maximal length of the nanowire at dependence on the plasma parameters, where the limiting factor for nanowire growth and distortions in distribution are ballistic effects of ions and their local fluxes. In contrast, the plasma heating by potential interactions of species has very little influence on the length and smaller deviations in flux are allowed for uniformity of growth

Temperature variation between neighboring days and mortality: a distributed lag non-linear analysis

Objectives To investigate whether a sudden temperature change between neighboring days has significant impact on mortality. Methods A Poisson generalized linear regression model combined with a distributed lag non-linear models was used to estimate the association of temperature change between neighboring days with mortality in a subtropical Chinese city during 2008–2012. Temperature change was calculated as the current day’s temperature minus the previous day’s temperature. Results A significant effect of temperature change between neighboring days on mortality was observed. Temperature increase was significantly associated with elevated mortality from non-accidental and cardiovascular diseases, while temperature decrease had a protective effect on non-accidental mortality and cardiovascular mortality. Males and people aged 65 years or older appeared to be more vulnerable to the impact of temperature change. Conclusions Temperature increase between neighboring days has a significant adverse impact on mortality. Further health mitigation strategies as a response to climate change should take into account temperature variation between neighboring days.

Multifunctional three-dimensional T-junction graphene micro-wells: Energy-efficient, plasma-enabled growth and instant water-based transfer for flexible device applications

The “third-generation” 3D graphene structures, T-junction graphene micro-wells (T-GMWs) are produced on cheap polycrystalline Cu foils in a single-step, low-temperature (270 °C), energy-efficient, and environment-friendly dry plasma-enabled process. T-GMWs comprise vertical graphene (VG) petal-like sheets that seemlessly integrate with each other and the underlying horizontal graphene sheets by forming T-junctions. The microwells have the pico-to-femto-liter storage capacity and precipitate compartmentalized PBS crystals. The T-GMW films are transferred from the Cu substrates, without damage to the both, in de-ionized or tap water, at room temperature, and without commonly used sacrificial materials or hazardous chemicals. The Cu substrates are then re-used to produce similar-quality T-GMWs after a simple plasma conditioning. The isolated T-GMW films are transferred to diverse substrates and devices and show remarkable recovery of their electrical, optical, and hazardous NO2 gas sensing properties upon repeated bending (down to 1 mm radius) and release of flexible trasparent display plastic substrates. The plasma-enabled mechanism of T-GMW isolation in water is proposed and supported by the Cu plasma surface modification analysis. Our GMWs are suitable for various optoelectronic, sesning, energy, and biomedical applications while the growth approach is potentially scalable for future pilot-scale industrial production.

Estimation of the time of a linear trend in monitoring survival time

Change point estimation is recognized as an essential tool of root cause analyses within quality control programs as it enables clinical experts to search for potential causes of change in hospital outcomes more effectively. In this paper, we consider estimation of the time when a linear trend disturbance has occurred in survival time following an in-control clinical intervention in the presence of variable patient mix. To model the process and change point, a linear trend in the survival time of patients who underwent cardiac surgery is formulated using hierarchical models in a Bayesian framework. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. We use Markov Chain Monte Carlo to obtain posterior distributions of the change point parameters including the location and the slope size of the trend and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time cumulative sum control chart (CUSUM) control charts for different trend scenarios. In comparison with the alternatives, step change point model and built-in CUSUM estimator, more accurate and precise estimates are obtained by the proposed Bayesian estimator over linear trends. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Modeling meat yield based on measurements of body traits in genetically improved giant freshwater prawn (GFP) Macrobrachium rosenbergii

A single-generation dataset consisting of 1,730 records from a selection program for high growth rate in giant freshwater prawn (GFP, Macrobrachium rosenbergii) was used to derive prediction equations for meat weight and meat yield. Models were based on body traits [body weight, total length and abdominal width (AW)] and carcass measurements (tail weight and exoskeleton-off weight). Lengths and width were adjusted for the systematic effects of selection line, male morphotypes and female reproductive status, and for the covariables of age at slaughter within sex and body weight. Body and meat weights adjusted for the same effects (except body weight) were used to calculate meat yield (expressed as percentage of tail weight/body weight and exoskeleton-off weight/body weight). The edible meat weight and yield in this GFP population ranged from 12 to 15 g and 37 to 45 %, respectively. The simple (Pearson) correlation coefficients between body traits (body weight, total length and AW) and meat weight were moderate to very high and positive (0.75–0.94), but the correlations between body traits and meat yield were negative (−0.47 to −0.74). There were strong linear positive relationships between measurements of body traits and meat weight, whereas relationships of body traits with meat yield were moderate and negative. Step-wise multiple regression analysis showed that the best model to predict meat weight included all body traits, with a coefficient of determination (R 2) of 0.99 and a correlation between observed and predicted values of meat weight of 0.99. The corresponding figures for meat yield were 0.91 and 0.95, respectively. Body weight or length was the best predictor of meat weight, explaining 91–94 % of observed variance when it was fitted alone in the model. By contrast, tail width explained a lower proportion (69–82 %) of total variance in the single trait models. It is concluded that in practical breeding programs, improvement of meat weight can be easily made through indirect selection for body trait combinations. The improvement of meat yield, albeit being more difficult, is possible by genetic means, with 91 % of the variation in the trait explained by the body and carcass traits examined in this study.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Linear and weakly nonlinear stability analyses of cooperative car-following models

Stability analyses have been widely used to better understand the mechanism of traffic jam formation. In this paper, we consider the impact of cooperative systems (a.k.a. connected vehicles) on traffic dynamics and, more precisely, on flow stability. Cooperative systems are emerging technologies enabling communication between vehicles and/or with the infrastructure. In a distributed communication framework, equipped vehicles are able to send and receive information to/from other equipped vehicles. Here, the effects of cooperative traffic are modeled through a general bilateral multianticipative car-following law that improves cooperative drivers' perception of their surrounding traffic conditions within a given communication range. Linear stability analyses are performed for a broad class of car-following models. They point out different stability conditions in both multianticipative and nonmultianticipative situations. To better understand what happens in unstable conditions, information on the shock wave structure is studied in the weakly nonlinear regime by the mean of the reductive perturbation method. The shock wave equation is obtained for generic car-following models by deriving the Korteweg de Vries equations. We then derive traffic-state-dependent conditions for the sign of the solitary wave (soliton) amplitude. This analytical result is verified through simulations. Simulation results confirm the validity of the speed estimate. The variation of the soliton amplitude as a function of the communication range is provided. The performed linear and weakly nonlinear analyses help justify the potential benefits of vehicle-integrated communication systems and provide new insights supporting the future implementation of cooperative systems.

Improved linear cryptanalysis of reduced-round SIMON-32 and SIMON-48

In this paper we analyse two variants of SIMON family of light-weight block ciphers against variants of linear cryptanalysis and present the best linear cryptanalytic results on these variants of reduced-round SIMON to date. We propose a time-memory trade-off method that finds differential/linear trails for any permutation allowing low Hamming weight differential/linear trails. Our method combines low Hamming weight trails found by the correlation matrix representing the target permutation with heavy Hamming weight trails found using a Mixed Integer Programming model representing the target differential/linear trail. Our method enables us to find a 17-round linear approximation for SIMON-48 which is the best current linear approximation for SIMON-48. Using only the correlation matrix method, we are able to find a 14-round linear approximation for SIMON-32 which is also the current best linear approximation for SIMON-32. The presented linear approximations allow us to mount a 23-round key recovery attack on SIMON-32 and a 24-round Key recovery attack on SIMON-48/96 which are the current best results on SIMON-32 and SIMON-48. In addition we have an attack on 24 rounds of SIMON-32 with marginal complexity.

Exploring the role of energy, trade and financial development in explaining economic growth in South Africa: A revisit

South Africa is an emerging and industrializing economy which is experiencing remarkable progress. We contend that amidst the developments in the economy, the role of energy, trade openness and financial development are critical. In this article, we revisit the pivotal role of these factors. We use the ARDL bounds [72], the Bayer and Hanck [11] cointegration techniques, and an extended Cobb–Douglas framework, to examine the long-run association with output per worker over the sample period 1971–2011. The results support long-run association between output per worker, capital per worker and the shift parameters. The short-run elasticity coefficients are as follows: energy (0.24), trade (0.07), financial development (−0.03). In the long-run, the elasticity coefficients are: trade openness (0.05), energy (0.29), and financial development (−0.04). In both the short-run and the long-run, we note the post-2000 period has a marginal positive effect on the economy. The Toda and Yamamoto [91] Granger causality results show that a unidirectional causality from capital stock and energy consumption to output; and from capital stock to trade openness; a bidirectional causality between trade openness and output; and absence (neutrality) of any causality between financial development and output thus indicating that these two variables evolve independent of each other.

Long-term growth and anthropometry after childhood liver transplantation

Objectives: To describe longitudinal height, weight, and body mass index changes up to 15 years after childhood liver transplantation. Study design: Retrospective chart review of patients who underwent liver transplant from 1985-2004 was performed. Subjects were age <18 years at transplant, survived ≥5 years, with at least 2 recorded measurements, of which one was ≥5 years post-transplant. Measurements were recorded pre-transplant, 1, 5, 10, and 15 years later. Results: Height and weight data were available in 98 and 104 patients, respectively; 47% were age <2 years at transplant; 58% were Australian, and the rest were from Japan. Height recovery continued for at least 10 years to reach the 26th percentile (Z-score -0.67) 15 years after transplant. Australians had better growth recovery and attained 47th percentile (Z-score -0.06) at 15 years. Weight recovery was most marked in the first year and continued for 15 years even in well-nourished children. Growth impaired and malnourished children at transplant exhibited the best growth, but remained significantly shorter and lighter even 15 years later. No effect of sex or age at transplant was noted on height or weight recovery. Post-transplant factors significantly impact growth recovery and likely caused the dichotomous growth recovery between Australian and Japanese children; 9% (9/98) of patients were overweight on body mass index calculations at 10-15 years but none were obese. Conclusions: After liver transplant, children can expect ongoing height and weight recovery for at least 10-15 years. Growth impairment at transplant and post-transplant care significantly impact long-term growth recovery. Copyright © 2013 Mosby Inc. All rights reserved.

Growth patterns in preterm infants born appropriate for gestational age

Aim: This study aimed to document the growth patterns of a contemporary cohort of preterm infants born appropriate for gestational age (AGA). It was hypothesised that preterm AGA (PT-AGA) infants would display poorer growth than full-term AGA (FT-AGA) infants. Methods: Sixty-four PT-AGA infants and 64 FT-AGA infants were assessed at 0, 4, 8 and 12 months of corrected age (CA). Measurements of weight and length were recorded at each of the specified ages. Centers for Disease Control and Prevention growth data were used to calculate Z-scores for weight and length based on CA. Results: The mean length and weight Z-scores of PT-AGA infants were found to be significantly less than those of FT-AGA infants at term, 4, 8 and 12 months of CA (P < 0.001). The mean weight Z-score of PT-AGA infants was found to be less than their mean length Z-score at each time point, though the differences were not significant. Conclusions: The results of this study suggest that PT-AGA infants are likely to display poorer growth than FT-AGA infants until at least 1 year of CA. Long-term growth monitoring in this population is recommended. © 2008 The Authors.

Common variants in the region around Osterix are associated with bone mineral density and growth in childhood

Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 × 10-4; Australia: P = 3.7 × 10-4). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 × 10-11). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 × 10-5). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.

The ascidian natural product eusynstyelamide B is a novel topoisomerase II poison that induces DNA damage and growth arrest in prostate and breast cancer cells

As part of an anti-cancer natural product drug discovery program, we recently identified eusynstyelamide B (EB), which displayed cytotoxicity against MDA-MB-231 breast cancer cells (IC50 = 5 μM) and induced apoptosis. Here, we investigated the mechanism of action of EB in cancer cell lines of the prostate (LNCaP) and breast (MDA-MB-231). EB inhibited cell growth (IC50 = 5 μM) and induced a G2 cell cycle arrest, as shown by a significant increase in the G2/M cell population in the absence of elevated levels of the mitotic marker phospho-histone H3. In contrast to MDA-MB-231 cells, EB did not induce cell death in LNCaP cells when treated for up to 10 days. Transcript profiling and Ingenuity Pathway Analysis suggested that EB activated DNA damage pathways in LNCaP cells. Consistent with this, CHK2 phosphorylation was increased, p21CIP1/WAF1 was up-regulated and CDC2 expression strongly reduced by EB. Importantly, EB caused DNA double-strand breaks, yet did not directly interact with DNA. Analysis of topoisomerase II-mediated decatenation discovered that EB is a novel topoisomerase II poison.

The effect of transforming growth factor β1 gene polymorphisms in ankylosing spondylitis

Objectives. To determine whether genetic polymorphisms in or near the transforming growth factor β1 (TGFB1) locus were associated d with susceptibility to or severity of ankylosing spondylitis (AS). Methods. Five intragenic single-nucleotide polymorphisms (SNP) and three microsatellite markers flanking the TGFB1 locus were genotyped. Seven hundred and sixty-two individuals from 184 multiplex families were genotyped for the microsatellite markers and two of the promoter SNPs. One thousand and two individuals from 212 English and 170 Finnish families with AS were genotyped for all five intragenic SNPs. A structured questionnaire was used to assess the age of symptom onset, disease duration and disease severity scores, including the BASDAI (Bath Ankylosing Spondylitis Disease Activity Index) and BASFI (Bath Ankylosing Spondylitis Functional Index). Results. A weak association was noted between the rare TGFB1 + 1632 T allele and AS in the Finnish population (P = 0.04) and in the combined data set (P = 0.03). No association was noted between any other SNPs or SNP haplotype and AS, even among those families with positive non-parametric linkage scores. The TGFB1 +1632 polymorphism was also associated with a younger age of symptom onset (English population, allele 2 associated with age of onset greater by 4.2 yr, P = 0.05; combined data set, allele 2 associated with age of onset greater by 3.2 yr, P = 0.02). A haplotype of coding region SNPs (TGFB1 +869/ +915+1632 alleles 2/1/2) was associated with age of symptom onset in both the English parent-case trios and the combined data set (English data set, haplotype 2/1/2 associated with age of onset greater by 4.9 yr, P = 0.03; combined data set, haplotype 2/1/2 associated with greater age of onset by 4.2 yr, P = 0.006). Weak linkage with AS susceptibility was noted and the peak LOD score was 1.3 at distance 2 cM centromeric to the TGFB1 gene. No other linkage or association was found between quantitative traits and the markers. Conclusion. This study suggests that the polymorphisms within the TGFB1 gene play at most a small role in AS and that other genes encoded on chromosome 19 are involved in susceptibility to the disease.