Cryptic Variation in the Human Mutation Rate

The mutation rate is known to vary between adjacent sites within the human genome as a consequence of context, the most well-studied example being the influence of CpG dinucelotides. We investigated whether there is additional variation by testing whether there is an excess of sites at which both humans and chimpanzees have a single-nucleotide polymorphism ( SNP). We found a highly significant excess of such sites, and we demonstrated that this excess is not due to neighbouring nucleotide effects, ancestral polymorphism, or natural selection. We therefore infer that there is cryptic variation in the mutation rate. However, although this variation in the mutation rate is not associated with the adjacent nucleotides, we show that there are highly nonrandom patterns of nucleotides that extend similar to 80 base pairs on either side of sites with coincident SNPs, suggesting that there are extensive and complex context effects. Finally, we estimate the level of variation needed to produce the excess of coincident SNPs and show that there is a similar, or higher, level of variation in the mutation rate associated with this cryptic process than there is associated with adjacent nucleotides, including the CpG effect. We conclude that there is substantial variation in the mutation that has, until now, been hidden from view

The Cost of Coexistence between Bt Maize and Open Pollinated Maize Varieties in Lowland Coastal Kenya

Kenya is currently in the process of introducing genetically modified maize (Bt maize). A major concern is that the Bt gene might cross into local varieties through cross pollination. Current regulatory strategies to ensure coexistence of the two cropping systems at the farm level rely on spatial isolation measures-separation distances and/or buffer zones. However, the interaction of practical measures and costs of spatial isolation with the farmer’s economic incentive to plant a Bt maize crop have not been studied in Kenya. The purpose of this study was to analyze the technical and economic feasibility of the implementation of spatial coexistence measures. Using spatial geo-referenced data from the actual agricultural landscape in lowland coastal Kenya, the study finds that flexible separation distances hold the possibility of ensuring coexistence in the region, but will be difficult to implement. Rigid buffer strips on the other hand are not consistent with the producers’ economic incentive to plant a Bt maize crop.Coexistence, Regulatory, Spatial, Agro-ecological zone, GM crops, Resource /Energy Economics and Policy,

Positionnement des systèmes multi-agents pour les systèmes de transport intelligents

National audienceThe use of new information and communication technologies has become a central solution to improve transport systems. What has led to which is called the Intelligent Transport Systems (ITS). Societal challenges for ensuring their effective implementations are crucial both to respond to users needs, and to design sustainable transport systems. In this paper, we argue that multi-agent paradigm can address the needs of this domain. We introduce ITS, and we emphasize three main issues of ITS which are how to ensure its functionality, how to render it more "intelligent" despite constraints in scalability, and the ethical implications. Some selected research works are provided to illustrate these issuesL’utilisation des nouvelles technologies de l’information et de la communication pour l’amélioration des systèmes de transport est une solution devenue centrale dans le domaine du transport. Le résultat est ce que l’on appelle les systèmes de transport intelligents (STI). Les enjeux sociétaux de leur mise en œuvre sont cruciaux en termes de réponse aux besoins des usagers mais également pour la conception de systèmes de transports durables. Dans ce papier, nous défendons l’idée que le paradigme multi-agent peut répondre aux besoins de ce domaine. Nous proposons ainsi de présenter le domaine des STI et de focaliser notre attention sur trois problématiques : la manière d’assurer sa fonctionnalité, la manière de le rendre plus « intelligent » malgré des contraintes de passage à l’échelle, et enfin ses conséquences éthiques. Quelques travaux de recherche illustrent notre propos

Validity of purchasing power parity in BRICS under a DFA Approach

Objectives This study tests the validity of the purchasing power parity (PPP) theory in Brazil, Russia, India, Macao-China and South Africa. We examine real exchange rates of these countries for mean reversion. Approach The Hurst exponent is our mean reversion measure which is evaluated by the Detrended Fluctuation Analysis (DFA) in a rolling window to determine the validity of the PPP theory amongst these countries through time. Results Our results show persistence in real exchange rates; an indication not supporting the PPP theory in the five countries. Value The study contributes to the extant literature of the PPP theory in BRICS using the DFA approach in a rolling window through&nbsp

Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution

Nowadays, systems are becoming increasingly complex, mainly due to an exponential increase in the number of entities and their interconnections. Examples of these complex systems can be found in manufacturing, smart-grids, traffic control, logistics, economics and biology, among others. Due to this complexity, particularly in manufacturing, a lack of responsiveness in coping with demand for higher quality products, the drastic reduction in product lifecycles and the increasing need for product customization are being observed. Traditional solutions, based on central monolithic control structures, are becoming obsolete as they are not suitable for reacting and adapting to these perturbations. The decentralization of the complexity problem through simple, intelligent and autonomous entities, such as those found in multi-agent systems, is seen as a suitable methodology for tackling this challenge in industrial scenarios. Additionally, the use of biologically inspired self-organization concepts has proved to be suitable for being embedded in these approaches enabling better performances to be achieved. According to these principals, several approaches have been proposed but none can be truly embedded and extract all the potential of self-organization mechanisms. This paper proposes an evolution to the ADACOR holonic control architecture inspired by biological and evolutionary theories. In particular, a two-dimension al self-organization mechanism was designed taking the behavioural and structural vectors into consideration, thus allowing truly evolutionary and reconfigurable systems to be achieved that can cope with emergent requirements. The approach proposed is validated with two simulation use cases.info:eu-repo/semantics/publishedVersio

Improving the ADACOR2 supervisor holon scheduling mechanism with genetic algorithms

Manufacturing companies are being pushed to their limits due to an increase of production complexity guided by a growing standards demand by the costumers. To respond properly to this, manufacturing companies must adopt innovative control architectures that are able to handle better the occurrence of disturbances at shop-floor level (e.g. workstation breakdown, orders cancellation or modification). Additionally, the selection of a proper scheduling algorithms assumes a crucial point, in the sense that the increase of optimization levels depend on this. This paper presents a Genetic Algorithm (GA) based technique to be embedded into the supervisor entity present at the ADACOR2 aiming to improve the existing fast and non-optimal scheduling technique, improving the overall system processing execution. The main requirements of the GA is to be fast enough to be usable in demanding environments improving the optimization output. The proposed algorithm is tested using a Flexible Manufacturing System using different configurations of transportation and batch sizes. Results show that despite the presented GA technique increased the optimization calculation time it performs better considering the sum of this time with the gain in the optimization output.info:eu-repo/semantics/publishedVersio

Masking Kernel for Learning Energy-Efficient Representations for Speaker Recognition and Mobile Health

Modern smartphones possess hardware for audio acquisition and to perform speech processing tasks such as speaker recognition and health assessment. However, energy consumption remains a concern, especially for resource-intensive DNNs. Prior work has improved the DNN energy efficiency by utilizing a compact model or reducing the dimensions of speech features. Both approaches reduced energy consumption during DNN inference but not during speech acquisition. This paper proposes using a masking kernel integrated into gradient descent during DNN training to learn the most energy-efficient speech length and sampling rate for windowing, a common step for sample construction. To determine the most energy-optimal parameters, a masking function with non-zero derivatives was combined with a low-pass filter. The proposed approach minimizes the energy consumption of both data collection and inference by 57%, and is competitive with speaker recognition and traumatic brain injury detection baselines

Design optimization of a short-term duty electrical machine for extreme environment

This paper presents design optimisation of a short term duty electrical machine for extreme environments of high temperature and high altitudes. For such extreme environmental conditions of above 80⁰C and altitudes of 30km, thermal loading limits are a critical consideration in machines, especially if high power density and high efficiency are to be achieved. The influence of different material on the performance of such machines is investigated. Also the effect of different slot and pole combinations are studied for machines used for such extreme operating conditions but with short duty. In the research, A Non-dominated Sorting Genetic Algorithm (NSGAII) considering an analytical electromagnetic model, structural and thermal model together with Finite Element (FE) methods are used to optimise the design of the machine for such environments achieving high efficiencies and high power density with relatively minimal computational time. The adopted thermal model is then validated through experiments and then implemented within the Genetic Algorithm (GA). It is shown that, generally, the designs are thermally limited where the pole numbers are limited by volt-amps drawn from the converter. The design consisting of a high slot number allows for improving the current loading and thus, significant weight reduction can be achieved

Poster Abstract: Interconnecting Low-Power Wireless and Power-Line Communications using IPv6

Wireless sensor networks for building automation and energy management has made great progress in recent years, but the inherent indoor radio range limitations can make communication unpredictable and system deployments difficult. Low-power radio can be combined with low-power Power-Line Communication (PLC) to extend the range and predictability of indoor communication for building management and automation systems. We take the first steps towards exploring the system implications for integration of low-power wireless and PLC in the same network. We leverage IPv6, which allow networks to exist over multiple physical communication media as well as the RPL routing protocol for low-power lossy networks