Smart transport: A comparative analysis using the most used indicators in the literature juxtaposed with interventions in English metropolitan areas

The development of smart transport technologies, methods, strategies and infrastructures has drawn much attention in recent years, owing to the rise of smart cities paradigms and the rapid technological advancements in the transport sector. New transport technologies create opportunities and challenges for English cities to move towards a more sustainable and integrated future. Smart governance and interventions in the English metropolitan areas are reviewed to provide a background of the smart city and transport development in the UK. Despite the increasing commercial and political attention, there is still a lack of understanding and proposals for a robust framework to evaluate the smart transport system. It is challenging to build a toolbox that suits both academics and practitioners when developing transport interventions and investments. This paper proposes a comprehensive and up-to-date framework to assess smart transport development in cities. A systematic literature review is conducted to identify the most used indicators and important indices. New indicators that illustrate trending themes are added to the existing toolbox. In total, 49 indicators are listed in this study, including five new ones. We also show several aspects and the overall performance in the new evaluation framework by aggregating indicators into indices in the following groups: 1) private, public and emergency transport indices; 2) accessibility, sustainability and innovation indices; and 3) a composite index. The new evaluation framework is applied in eleven English metropolitan areas. The empirical results show that Greater London has the best development in smart transport, followed by West Midlands and West of England. The findings can provide useful insights for metropolitan authorities and their transport authorities when key devolution strategies are in place and substantial investment packages are considered

Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis

Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for disease diagnosis, where discriminating subjects with mild cognitive impairment (MCI) from normal controls (NC) is still one of the most challenging problems. Dynamic functional connectivity (dFC), consisting of time-varying spatiotemporal dynamics, may characterize "chronnectome" diagnostic information for improving MCI classification. However, most of the current dFC studies are based on detecting discrete major brain status via spatial clustering, which ignores rich spatiotemporal dynamics contained in such chronnectome. We propose Deep Chronnectome Learning for exhaustively mining the comprehensive information, especially the hidden higher-level features, i.e., the dFC time series that may add critical diagnostic power for MCI classification. To this end, we devise a new Fully-connected Bidirectional Long Short-Term Memory Network (Full-BiLSTM) to effectively learn the periodic brain status changes using both past and future information for each brief time segment and then fuse them to form the final output. We have applied our method to a rigorously built large-scale multi-site database (i.e., with 164 data from NCs and 330 from MCIs, which can be further augmented by 25 folds). Our method outperforms other state-of-the-art approaches with an accuracy of 73.6% under solid cross-validations. We also made extensive comparisons among multiple variants of LSTM models. The results suggest high feasibility of our method with promising value also for other brain disorder diagnoses.Comment: The paper has been accepted by MICCAI201

Computing a rectilinear shortest path amid splinegons in plane

We reduce the problem of computing a rectilinear shortest path between two given points s and t in the splinegonal domain \calS to the problem of computing a rectilinear shortest path between two points in the polygonal domain. As part of this, we define a polygonal domain \calP from \calS and transform a rectilinear shortest path computed in \calP to a path between s and t amid splinegon obstacles in \calS. When \calS comprises of h pairwise disjoint splinegons with a total of n vertices, excluding the time to compute a rectilinear shortest path amid polygons in \calP, our reduction algorithm takes O(n + h \lg{n}) time. For the special case of \calS comprising of concave-in splinegons, we have devised another algorithm in which the reduction procedure does not rely on the structures used in the algorithm to compute a rectilinear shortest path in polygonal domain. As part of these, we have characterized few of the properties of rectilinear shortest paths amid splinegons which could be of independent interest

Enabling Thin and Flexible Solid-State Composite Electrolytes by the Scalable Solution Process

All solid-state batteries (ASSBs) have the potential to deliver higher energy densities, wider operating temperature range, and improved safety compared with today's liquid-electrolyte-based batteries. However, of the various solid-state electrolyte (SSE) classes - polymers, sulfides, or oxides - none alone can deliver the combined properties of ionic conductivity, mechanical, and chemical stability needed to address scalability and commercialization challenges. While promising strategies to overcome these include the use of polymer/oxide or sulfide composites, there is still a lack of fundamental understanding between different SSE-polymer-solvent systems and its selection criteria. Here, we isolate various SSE-polymer-solvent systems and study their molecular level interactions by combining various characterization tools. With these findings, we introduce a suitable Li7P3S11SSE-SEBS polymer-xylene solvent combination that significantly reduces SSE thickness (∼50 μm). The SSE-polymer composite displays high room temperature conductivity (0.7 mS cm-1) and good stability with lithium metal by plating and stripping over 2000 h at 1.1 mAh cm-2. This study suggests the importance of understanding fundamental SSE-polymer-solvent interactions and provides a design strategy for scalable production of ASSBs

Extra gauge symmetries in BHT gravity

We study the canonical structure of the Bergshoeff-Hohm-Townsend massive gravity, linearized around a maximally symmetric background. At the critical point in the space of parameters, defined by $\Lambda_0/m^2=-1$, we discover an extra gauge symmetry, which reflects the existence of the partially massless mode. The number of the Lagrangian degrees of freedom is found to be 1. We show that the canonical structure of the theory at the critical point is unstable under linearization.Comment: LATEX, 12 page

On unitary subsectors of polycritical gravities

We study higher-derivative gravity theories in arbitrary space-time dimension d with a cosmological constant at their maximally critical points where the masses of all linearized perturbations vanish. These theories have been conjectured to be dual to logarithmic conformal field theories in the (d-1)-dimensional boundary of an AdS solution. We determine the structure of the linearized perturbations and their boundary fall-off behaviour. The linearized modes exhibit the expected Jordan block structure and their inner products are shown to be those of a non-unitary theory. We demonstrate the existence of consistent unitary truncations of the polycritical gravity theory at the linearized level for odd rank.Comment: 22 pages. Added references, rephrased introduction slightly. Published versio

Variability of mitochondrial energy balance across brain regions

Brain is not homogenous and neurons from various brain regions are known to have different vulnerabilities to mitochondrial mutations and mitochondrial toxins. However, it is not clear if this vulnerability is connected to different energy metabolism in specific brain regions. Here, using live‐cell imaging, we compared mitochondrial membrane potential and nicotinamide adenine dinucleotide (NADH) redox balance in acute rat brain slices in different brain regions and further detailed the mitochondrial metabolism in primary neurons and astrocytes from rat cortex, midbrain and cerebellum. We have found that mitochondrial membrane potential is higher in brain slices from the hippocampus and brain stem. In primary co‐cultures, mitochondrial membrane potential in astrocytes was lower than in neurons, whereas in midbrain cells it was higher than in cortex and cerebellum. The rate of NADH production and mitochondrial NADH pool were highest in acute slices from midbrain and midbrain primary neurons and astrocytes. Although the level of adenosine tri phosphate (ATP) was similar among primary neurons and astrocytes from cortex, midbrain and cerebellum, the rate of ATP consumption was highest in midbrain cells that lead to faster neuronal and astrocytic collapse in response to inhibitors of ATP production. Thus, midbrain neurons and astrocytes have a higher metabolic rate and ATP consumption that makes them more vulnerable to energy deprivation

Propensity score analysis in the Genetic Analysis Workshop 17 simulated data set on independent individuals

Genetic Analysis Workshop 17 provided simulated phenotypes and exome sequence data for 697 independent individuals (209 case subjects and 488 control subjects). The disease liability in these data was influenced by multiple quantitative traits. We addressed the lack of statistical power in this small data set by limiting the genomic variants included in the study to those with potential disease-causing effect, thereby reducing the problem of multiple testing. After this adjustment, we could readily detect two common variants that were strongly associated with the quantitative trait Q1 (C13S523 and C13S522). However, we found no significant associations with the affected status or with any of the other quantitative traits, and the relationship between disease status and genomic variants remained obscure. To address the challenge of the multivariate phenotype, we used propensity scores to combine covariates with genetic risk factors into a single risk factor and created a new phenotype variable, the probability of being affected given the covariates. Using the propensity score as a quantitative trait in the case-control analysis, we again could identify the two common single-nucleotide polymorphisms (C13S523 and C13S522). In addition, this analysis captured the correlation between Q1 and the affected status and reduced the problem of multiple testing. Although the propensity score was useful for capturing and clarifying the genetic contributions of common variants to the disease phenotype and the mediating role of the quantitative trait Q1, the analysis did not increase power to detect rare variants

Warped black holes in 3D general massive gravity

We study regular spacelike warped black holes in the three dimensional general massive gravity model, which contains both the gravitational Chern-Simons term and the linear combination of curvature squared terms characterizing the new massive gravity besides the Einstein-Hilbert term. The parameters of the metric are found by solving a quartic equation constrained by an inequality that imposes the absence of closed timelike curves. Explicit expressions for the central charges are suggested by exploiting the fact that these black holes are discrete quotients of spacelike warped AdS(3) and a known formula for the entropy. Previous results obtained separately in topological massive gravity and in new massive gravity are recovered as special cases.Comment: 38 pages, 7 figures. v2: minor changes, added refs and an appendix on self-dual and null z-warped black hole

Willingness to Pay for Genetic Testing for Alzheimer's Disease: A Measure of Personal Utility

Background: The increased availability of genetic tests for common, complex diseases, such as Alzheimer's disease (AD), raises questions about what people are willing to pay for these services. Methods: We studied willingness-to-pay for genetic testing in a study of AD risk assessment that included APOE genotype disclosure among 276 first-degree relatives of persons with AD. Results: Seventy-one percent reported that they would ask for such testing from their doctor if it were covered by health insurance, and 60% would ask for it even if it required self-pay. Forty-one percent were willing to pay more than $100 for testing, and more than half would have been willing to pay for the test out of pocket. Participants who learned that they were APOE -4 positive and those who had higher education were less likely to want testing if covered by insurance, possibly to avoid discrimination. Conclusion: This is the first report to examine willingness to pay for susceptibility genetic testing in a sample of participants who had actually undergone such testing. These findings reveal that some participants find valuable personal utility in genetic risk information even when such information does not have proven clinical utility.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90504/1/gtmb-2E2011-2E0028.pd