Developing a transdisciplinary approach to improve urban traffic congestion based on Product Ecosystem theory

Product Ecosystem theory is an emerging theory that shows that disruptive “game changing” innovation is only possible when the entire ecosystem is considered. When environmental variables change faster than products or services can adapt, disruptive innovation is required to keep pace. This has many parallels with natural ecosystems where species that cannot keep up with changes to the environment will struggle or become extinct. In this case the environment is the city, the environmental pressures are pollution and congestion, the product is the car and the product ecosystem is comprised of roads, bridges, traffic lights, legislation, refuelling facilities etc. Each one of these components is the responsibility of a different organisation and so any change that affects the whole ecosystem requires a transdisciplinary approach. As a simple example, cars that communicate wirelessly with traffic lights are only of value if wireless-enabled traffic lights exist and vice versa. Cars that drive themselves are technically possible but legislation in most places doesn’t allow their use. According to innovation theory, incremental innovation tends to chase ever diminishing returns and becomes increasingly unable to tackle the “big issues.” Eventually “game changing” disruptive innovation comes along and solves the “big issues” and/or provides new opportunities. Seen through this lens, the environmental pressures of urban traffic congestion and pollution are the “big issues.” It can be argued that the design of cars and the other components of the product ecosystem follow an incremental innovation approach. That is why the “big issues” remain unresolved. This paper explores the problems of pollution and congestion in urban environments from a Product Ecosystem perspective. From this a strategy will be proposed for a transdisciplinary approach to develop and implement solutions.

Score-level multibiometric fusion based on Dempster-Shafer theory incorporating uncertainty factors

While existing multi-biometic Dempster-Shafer the- ory fusion approaches have demonstrated promising perfor- mance, they do not model the uncertainty appropriately, sug- gesting that further improvement can be achieved. This research seeks to develop a unified framework for multimodal biometric fusion to take advantage of the uncertainty concept of Dempster- Shafer theory, improving the performance of multi-biometric authentication systems. Modeling uncertainty as a function of uncertainty factors affecting the recognition performance of the biometric systems helps to address the uncertainty of the data and the confidence of the fusion outcome. A weighted combination of quality measures and classifiers performance (Equal Error Rate) are proposed to encode the uncertainty concept to improve the fusion. We also found that quality measures contribute unequally to the recognition performance, thus selecting only significant factors and fusing them with a Dempster-Shafer approach to generate an overall quality score play an important role in the success of uncertainty modeling. The proposed approach achieved a competitive performance (approximate 1% EER) in comparison with other Dempster-Shafer based approaches and other conventional fusion approaches.

A novel manoeuvering model based on low-aspect-ratio lift theory and Lagrangian mechanics

This paper proposes a physically motivated reappraisal of manoeuvring models for ships and presents a new model developed from first principles by application of low aspect-ratio aerodynamic theory and Lagrangian mechanics. The coefficients of the model are shown to be related to physical processes, and validation is presented using the results from a planar motion mechanism dataset.

Co-movements in commodity prices : a note based on network analysis

This article analyses co-movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co-movement during the sampled period.

Synonymization of key pest species within the Bactrocera dorsalis species complex (Diptera: Tephritidae): Taxonomic changes based on a review of 20 years of integrative morphological, molecular, cytogenetic, behavioural and chemoecological data

Bactrocera papayae Drew & Hancock, Bactrocera philippinensis Drew & Hancock, Bactrocera carambolae Drew & Hancock, and Bactrocera invadens Drew, Tsuruta & White are four horticultural pest tephritid fruit fly species that are highly similar, morphologically and genetically, to the destructive pest, the Oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae). This similarity has rendered the discovery of reliable diagnostic characters problematic, which, in view of the economic importance of these taxa and the international trade implications, has resulted in ongoing difficulties for many areas of plant protection and food security. Consequently, a major international collaborative and integrated multidisciplinary research effort was initiated in 2009 to build upon existing literature with the specific aim of resolving biological species limits among B. papayae, B. philippinensis, B. carambolae, B. invadens and B. dorsalis to overcome constraints to pest management and international trade. Bactrocera philippinensis has recently been synonymized with B. papayae as a result of this initiative and this review corroborates that finding; however, the other names remain in use. While consistent characters have been found to reliably distinguish B. carambolae from B. dorsalis, B. invadens and B. papayae, no such characters have been found to differentiate the latter three putative species. We conclude that B. carambolae is a valid species and that the remaining taxa, B. dorsalis, B. invadens and B. papayae, represent the same species. Thus, we consider B. dorsalis (Hendel) as the senior synonym of B. papayae Drew and Hancock syn.n. and B. invadens Drew, Tsuruta & White syn.n. A redescription of B. dorsalis is provided. Given the agricultural importance of B. dorsalis, this taxonomic decision will have significant global plant biosecurity implications, affecting pest management, quarantine, international trade, postharvest treatment and basic research. Throughout the paper, we emphasize the value of independent and multidisciplinary tools in delimiting species, particularly in complicated cases involving morphologically cryptic taxa.

A non-fullerene electron acceptor based on fluorene and diketopyrrolopyrrole building blocks for solution-processable organic solar cells with an impressive open-circuit voltage

A novel solution-processable non-fullerene electron acceptor 6,6′-(5,5′-(9,9-dioctyl-9H-fluorene-2,7-diyl)bis(thiophene-5,2-diyl))bis(2,5-bis(2-ethylhexyl)-3-(thiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione) (DPP1) based on fluorene and diketopyrrolopyrrole conjugated moieties was designed, synthesized and fully characterized. DPP1 exhibited excellent solubility and high thermal stability which are essential for easy processing. Upon using DPP1 as an acceptor with the classical electron donor poly(3-hexylthiophene), solution processable bulk-heterojunction solar cells afforded a power conversion efficiency of 1.2% with a high open-circuit voltage (1.1 V). As per our knowledge, this value of open circuit voltage is one of the highest values reported so far for a bulk-heterojunction device using DPP1 as a non-fullerene acceptor.

Design and implementation of unified communications as a service based on the OpenStack cloud environment

Cloud Computing, based on early virtual computer concepts and technologies, is now itself a maturing technology in the marketplace and it has revolutionized the IT industry, being the powerful platform that many businesses are choosing to migrate their in-premises IT services onto. Cloud solution has the potential to reduce the capital and operational expenses associated with deploying IT services on their own. In this study, we have implemented our own private cloud solution, infrastructure as a service (IaaS), using the OpenStack platform with high availability and a dynamic resource allocation mechanism. Besides, we have hosted unified communication as a service (UCaaS) in the underlying IaaS and successfully tested voice over IP (VoIP), video conferencing, voice mail and instant messaging (IM) with clients located at the remote site. The proposed solution has been developed in order to give advice to bussinesses that want to build their own cloud environment, IaaS and host cloud services and applicatons in the cloud. This paper also aims at providing an alternate option for proprietary cloud solutions for service providers to consider.

A new study on binder performance and formulation modification of anti-corrosive primer based on ethyl silicate resin

Zinc-rich ethyl silicate coatings are quite successful in protecting steel against corrosion under severe exposing conditions. In spite of providing excellent cathodic protection to steel structure after film curing, two-component zinc-rich ethyl silicate coatings have some limitations, one of which is inadequate shelf life as a result of in-can binder gelation. In this work, the preparation steps of ethyl silicate such as pre-hydrolysis, dehydration and organometallic reactions were surveyed and herein an approach towards understanding the cause and effect relationship of the use of ingredients is presented. The effects of water and catalytic acid dosages on gel time under accelerated conditions and the effect of alcoholic solvent order on the rate of the hydrolysis and dehydration reactions were studied via Karl-Fischer test determining the water content of hydrolysate. A thriving optimization in shelf life without any loss in physical–mechanical characteristics of the final film (e.g. hardness, adhesion, solvent and salt spray resistance) was obtained.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

Phylogenetics of small horseshoe bats from east Asia based on mitochondrial DNA sequence variation

We undertook analyses of mitochondrial DNA gene sequences and echolocation calls to resolve phylogenetic relationships among the related bat taxa Rhinolophus pusillus (sampled across China), R. monoceros (Taiwan), R. cornutus (main islands of Japan), and R. c. pumilus (Okinawa, Japan), Phylogenetic trees and genetic divergence analyses were constructed by combining new complete mitochondrial cytochrome-b gene sequences and partial mitochondrial control region sequences with published sequences. Our work showed that these 4 taxa formed monophyletic groups in the phylogenetic tree. However, low levels of sequence divergence among the taxa, together with similarities in body size and overlapping echolocation call frequencies, point to a lack of taxonomic distinctiveness. We therefore suggest that these taxa are better considered as geographical subspecies rather than distinct species, although this should not diminish the conservation importance of these island populations, which are important evolutionarily significant units. Based on our findings, we suggest that the similarities in body size and echolocation call frequency in these rhinolophids result from their recent common ancestry, whereas similarities in body size and call frequency with R. hipposideros of Europe are the result of convergent evolution.

A clarion call for action based on refined DALY estimates for South Africa

Initial estimates of the burden of disease in South Africa in 20001 have been revised on the basis of additional data to estimate the disability-adjusted life-years (DALYs) for single causes for the first time in South Africa. The findings highlight the fact that despite uncertainty in the estimates, they provide important information to guide public health responses to improve the health of the nation...

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

Some comparison on whole-proteome phylogeny of large dsDNA viruses based on dynamical language approach and feature frequency profiles method

There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among them, CVTree method, feature frequency profiles method and dynamical language approach were used to investigate the whole-proteome phylogeny of large dsDNA viruses. Using the data set of large dsDNA viruses from Gao and Qi (BMC Evol. Biol. 2007), the phylogenetic results based on the CVTree method and the dynamical language approach were compared in Yu et al. (BMC Evol. Biol. 2010). In this paper, we first apply dynamical language approach to the data set of large dsDNA viruses from Wu et al. (Proc. Natl. Acad. Sci. USA 2009) and compare our phylogenetic results with those based on the feature frequency profiles method. Then we construct the whole-proteome phylogeny of the larger dataset combining the above two data sets. According to the report of The International Committee on the Taxonomy of Viruses (ICTV), the trees from our analyses are in good agreement to the latest classification of large dsDNA viruses.