A genetic programming system with an epigenetic mechanism for traffic signal control

Traffic congestion is an increasing problem in most cities around the world. It impacts businesses as well as commuters, small cities and large ones in developing as well as developed economies. One approach to decrease urban traffic congestion is to optimize the traffic signal behaviour in order to be adaptive to changes in the traffic conditions. From the perspective of intelligent transportation systems, this optimization problem is called the traffic signal control problem and is considered a large combinatorial problem with high complexity and uncertainty. A novel approach to the traffic signal control problem is proposed in this thesis. The approach includes a new mechanism for Genetic Programming inspired by Epigenetics. Epigenetic mechanisms play an important role in biological processes such as phenotype differentiation, memory consolidation within generations and environmentally induced epigenetic modification of behaviour. These properties lead us to consider the implementation of epigenetic mechanisms as a way to improve the performance of Evolutionary Algorithms in solution to real-world problems with dynamic environmental changes, such as the traffic control signal problem. The epigenetic mechanism proposed was evaluated in four traffic scenarios with different properties and traffic conditions using two microscopic simulators. The results of these experiments indicate that Genetic Programming was able to generate competitive actuated traffic signal controllers for all the scenarios tested. Furthermore, the use of the epigenetic mechanism improved the performance of Genetic Programming in all the scenarios. The evolved controllers adapt to modifications in the traffic density and require less monitoring and less human interaction than other solutions because they dynamically adjust the signal behaviour depending on the local traffic conditions at each intersection

Residential Proximity to Major Roadways at Birth, DNA Methylation at Birth and Midchildhood, and Childhood Cognitive Test Scores: Project Viva(Massachusetts, USA).

BackgroundEpigenetic variability is hypothesized as a regulatory pathway through which prenatal exposures may influence child development and health.ObjectiveWe sought to examine the associations of residential proximity to roadways at birth and epigenome-wide DNA methylation. We also assessed associations of differential methylation with child cognitive outcomes.MethodsWe estimated residential proximity to roadways at birth using a geographic information system (GIS) and cord blood methylation using Illumina's HumanMethylation450-array in 482 mother-child pairs in Project Viva. We identified individual CpGs associated with residential-proximity-to-roadways at birth using robust linear regression [[Formula: see text]]. We also estimated association between proximity-to-roadways at birth and methylation of the same sites in blood samples collected at age 7-11 y ([Formula: see text]). We ran the same analyses in the Generation R Study for replication ([Formula: see text]). In Project Viva, we investigated associations of differential methylation at birth with midchildhood cognition using linear regression.ResultsLiving closer to major roadways at birth was associated with higher cord blood (and-more weakly-midchildhood blood) methylation of four sites in LAMB2. For each halving of residential-proximity-to-major-roadways, we observed a 0.82% increase in DNA methylation at cg05654765 [95% confidence interval (CI): (0.54%, 1.10%)], 0.88% at cg14099457 [95% CI: (0.56%, 1.19%)], 0.19% at cg03732535 [95% CI: (0.11%, 0.28)], and 1.08% at cg02954987 [95% CI: (0.65%, 1.51%)]. Higher cord blood methylation of these sites was associated with lower midchildhood nonverbal cognitive scores. Our results did not replicate in the Generation R Study.ConclusionsOur discovery results must be interpreted with caution, given that they were not replicated in a separate cohort. However, living close to major roadways at birth was associated with cord blood methylation of sites in LAMB2-a gene known to be linked to axonal development-in our U.S. cohort. Higher methylation of these sites associated with lower nonverbal cognitive scores at age 7-11 y in the same children. https://doi.org/10.1289/EHP2034

Metaheuristics for Traffic Control and Optimization: Current Challenges and Prospects

Intelligent traffic control at signalized intersections in urban areas is vital for mitigating congestion and ensuring sustainable traffic operations. Poor traffic management at road intersections may lead to numerous issues such as increased fuel consumption, high emissions, low travel speeds, excessive delays, and vehicular stops. The methods employed for traffic signal control play a crucial role in evaluating the quality of traffic operations. Existing literature is abundant, with studies focusing on applying regression and probability-based methods for traffic light control. However, these methods have several shortcomings and can not be relied on for heterogeneous traffic conditions in complex urban networks. With rapid advances in communication and information technologies in recent years, various metaheuristics-based techniques have emerged on the horizon of signal control optimization for real-time intelligent traffic management. This study critically reviews the latest advancements in swarm intelligence and evolutionary techniques applied to traffic control and optimization in urban networks. The surveyed literature is classified according to the nature of the metaheuristic used, considered optimization objectives, and signal control parameters. The pros and cons of each method are also highlighted. The study provides current challenges, prospects, and outlook for future research based on gaps identified through a comprehensive literature review

Bio-inspired Computing and Smart Mobility

Por último, se aborda la predicción de plazas libres de aparcamiento utilizando técnicas de aprendizaje automático, tales como series temporales, agrupamiento, etc., incluyendo un prototipo de aplicación web. La tercera parte de esta tesis doctoral se enfoca en el diseño y evaluación de un nuevo algoritmo inspirado en la epigénesis, el Algoritmo Epigenético. Luego de la descripción del modelo en el que se basa y de sus partes, se utiliza este nuevo algoritmo para la resolución del problema de la mochila multidimensional y se comparan sus resultados con los de otros algoritmos del estado de arte. Por último se emplea también el Algoritmo Epigenético para la optimización de la arquitectura Yellow Swarm, un problema de movilidad inteligente resuelto por un nuevo algoritmo bioinspirado. A lo largo de esta tesis doctoral se han descrito los problemas de movilidad inteligente y propuesto nuevas herramientas para su optimización. A partir de los experimentos realizados se concluye que estas herramientas, basadas en algoritmos bioinspirados, son eficientes para abordar estos problemas, obteniendo resultados competitivos comparados con los del estado del arte, los cuales han sido validados estadísticamente. Esto representa un aporte científico pero también una serie de mejoras para la sociedad toda, tanto en su salud como en el aprovechamiento de su tiempo libre. Fecha de lectura de Tesis: 01 octubre 2018.Esta tesis doctoral propone soluciones a problemas de movilidad inteligente, concretamente la reducción de los tiempos de viajes en las vías urbanas, las emisiones de gases de efecto invernadero y el consumo de combustible, mediante el diseño y uso de nuevos algoritmos bioinspirados. Estos algoritmos se utilizan para la optimización de escenarios realistas, cuyo trazado urbano se obtiene desde OpenStreetMap, y que son luego evaluados en el microsimulador SUMO. Primero se describen las bases científicas y tecnológicas, incluyendo la definición y estado del arte de los problemas a abordar, las metaheurísticas que se utilizarán durante el desarrollo de los experimentos, así como las correspondientes validaciones estadísticas. A continuación se describen los simuladores de movilidad como principal herramienta para construir y evaluar los escenarios urbanos. Por último se presenta una propuesta para generar tráfico vehicular realista a partir de datos de sensores que cuentan el número de vehículos en la ciudad, utilizando herramientas incluidas en SUMO combinadas con algoritmos evolutivos. En la segunda parte se modelan y resuelven problemas de movilidad inteligente utilizando las nuevas arquitecturas Red Swarm y Green Swarm para sugerir nuevas rutas a los vehículos utilizando nodos con conectividad Wi-Fi. Red Swarm se centra en la reducción de tiempos de viajes evitando la congestión de las calles, mientras que Green Swarm está enfocado en la reducción de emisiones y consumo de combustible. Luego se propone la arquitectura Yellow Swarm que utiliza una serie de paneles LED para indicar desvíos que los vehículos pueden seguir en lugar de nodos Wi-Fi haciendo esta propuesta más accesible. Además se propone un método para genera rutas alternativas para los navegadores GPS de modo que se aprovechen mejor las calles secundarias de las ciudades, reduciendo los atascos

Adolescent idiopathic scoliosis (AIS), environment, exposome and epigenetics: a molecular perspective of postnatal normal spinal growth and the etiopathogenesis of AIS with consideration of a network approach and possible implications for medical therapy

Genetic factors are believed to play an important role in the etiology of adolescent idiopathic scoliosis (AIS). Discordant findings for monozygotic (MZ) twins with AIS show that environmental factors including different intrauterine environments are important in etiology, but what these environmental factors may be is unknown. Recent evidence for common chronic non-communicable diseases suggests epigenetic differences may underlie MZ twin discordance, and be the link between environmental factors and phenotypic differences. DNA methylation is one important epigenetic mechanism operating at the interface between genome and environment to regulate phenotypic plasticity with a complex regulation across the genome during the first decade of life. The word exposome refers to the totality of environmental exposures from conception onwards, comprising factors in external and internal environments. The word exposome is used here also in relation to physiologic and etiopathogenetic factors that affect normal spinal growth and may induce the deformity of AIS. In normal postnatal spinal growth we propose a new term and concept, physiologic growth-plate exposome for the normal processes particularly of the internal environments that may have epigenetic effects on growth plates of vertebrae. In AIS, we propose a new term and concept pathophysiologic scoliogenic exposome for the abnormal processes in molecular pathways particularly of the internal environment currently expressed as etiopathogenetic hypotheses; these are suggested to have deforming effects on the growth plates of vertebrae at cell, tissue, structure and/or organ levels that are considered to be epigenetic. New research is required for chromatin modifications including DNA methylation in AIS subjects and vertebral growth plates excised at surgery. In addition, consideration is needed for a possible network approach to etiopathogenesis by constructing AIS diseasomes. These approaches may lead through screening, genetic, epigenetic, biochemical, metabolic phenotypes and pharmacogenomic research to identify susceptible individuals at risk and modulate abnormal molecular pathways of AIS. The potential of epigenetic-based medical therapy for AIS cannot be assessed at present, and must await new research derived from the evaluation of epigenetic concepts of spinal growth in health and deformity. The tenets outlined here for AIS are applicable to other musculoskeletal growth disorders including infantile and juvenile idiopathic scoliosis

Preserving Human Potential as Freedom: A Framework for Regulating Epigenetic Harms

Epigenetics is a rapidly evolving scientific field of inquiry examining how a wide range of environmental, social, and nutritional exposures can dramatically control how genes are expressed without changing the underlying DNA. Research has demonstrated that epigenetics plays a large role in human development and in disease causation. In a sense, epigenetics blurs the distinction between “nature” and “nurture” as experiences (nurture) become a part of intrinsic biology (nature). Remarkably, some epigenetic modifications are durable across generations, meaning that exposures from our grandparents’ generation might affect our health now, even if we have not experienced the same exposures. In the same vein, current exposures could affect the health of not only individuals currently living but also future generations. Given the relative novelty of epigenetics research and the multifactorial nature of human development and disease causation, it is unlikely that conclusive proof can be established showing that particular exposures lead to epigenetic risks that manifest into specific conditions. Using the Capabilities Approach (“CA”) developed by Amartya Sen and Martha Nussbaum, this article argues that epigenetic risk is not merely a medical issue, but that it more generally implicates the underlying fairness and justice of our social contract. For instance, how we develop mentally or physically has a tremendous impact upon our inherent capabilities and our set of life options. The CA prompts us to ask questions such as: (1) what impact do particular epigenetic risks have on our ability to exercise free choices; (2) are these risks avoidable; and (3) how are these risks distributed across society? Due to the complex nature of epigenetic risk, tort law is predictably incapable of addressing this harm. Further, while regulatory agencies possess the statutory authority to begin addressing epigenetic harms, currently these agencies are not attuned to measure or to respond to this type of harm. This article argues that it is imperative to initiate a regulatory framework to address epigenetic risk from specific substances even if conclusive proof of disease causation cannot be established. Shifting the burden of generating epigenetic risk data to producers of suspected harmful substances serves as a start. As information concerning epigenetic risks accrues, the regulatory response should evolve concurrently. As part of a dynamic policy-making approach our goals need to encompass the following: (i) promotion of knowledge in the scientific, legal, and public domains; (ii) assessment and modification of current regulations to address preventable risk; and (iii) an overarching commitment to protect human capabilities in an equitable manner