Spatio-Temporal Short-Term Urban Traffic Volume Forecasting Using Genetically Optimized Modular Networks

Abstract:   Current interest in short-term traffic volume forecasting focuses on incorporating temporal and spatial volume characteristics in the forecasting process. This article addresses the problem of integrating and optimizing predictive information from multiple locations of an urban signalized arterial and proposes a modular neural predictor consisting of temporal genetically optimized structures of multilayer perceptrons (MLP) that are fed with volume data from sequential locations to improve the accuracy of short-term forecasts. The results show that the proposed methodology provides more accurate forecasts compared to the conventional statistical methodologies applied, as well as to the static forms of neural networks.     

Quality of manual data collection in Java software: an empirical investigation

Data collection, both automatic and manual, lies at the heart of all empirical studies. The quality of data collected from software informs decisions on maintenance, testing and wider issues such as the need for system re-engineering. While of the two types stated, automatic data collection is preferable, there are numerous occasions when manual data collection is unavoidable. Yet, very little evidence exists to assess the error-proneness of the latter. Herein, we investigate the extent to which manual data collection for Java software compared with its automatic counterpart for the same data. We investigate three hypotheses relating to the difference between automated and manual data collection. Five Java systems were used to support our investigation. Results showed that, as expected, manual data collection was error-prone, but nowhere near the extent we had initially envisaged. Key indicators of mistakes in manual data collection were found to be poor developer coding style, poor adherence to sound OO coding principles, and the existence of relatively large classes in some systems. Some interesting results were found relating to the collection of public class features and the types of error made during manual data collection. The study thus offers an insight into some of the typical problems associated with collecting data manually; more significantly, it highlights the problems that poorly written systems have on the quality of visually extracted data.     

The nearest neighbor and the bayes error rates

The (k, l) nearest neighbor method of pattern classification is compared to the Bayes method. If the two acceptance rates are equal then the asymptotic error rates satisfy the inequalities Ek,l + 1 ? E*(?) ? Ek,l dE*(?), where d is a function of k, l, and the number of pattern classes, and ? is the reject threshold for the Bayes method. An explicit expression for d is given which is optimal in the sense that for some probability distributions Ek,l and dE* (?) are equal.     

A Holistic Evolutionary and 3D Pharmacophore Modelling Study Provides Insights into the Metabolism,Function, and Substrate Selectivity of the Human Monocarboxylate Transporter 4 (hMCT4)

Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.     

The mechanical property and phase structures of wheat proteins/polyvinyl alcohol blends studied by high-resolution solid-state NMR

The phase structures of thermally processed wheat proteins (WP) and polyvinyl alcohol (PVOH) blends were studied by solid-state high-resolution NMR spectroscopy. The intermolecular interactions among the multi-component systems and the behavior of each component in the blends on scales of nanometers were examined. The mechanical properties of the blends were also measured and related to the phase structure studies. The results indicated that the polymer chains of WP could be homogeneously mobilized when thermally processed with glycerol and water as plasticisers, but the glycerol predominately associated with WP rather than PVOH in the blends. The intermolecular hydrogen bonding interactions between WP and PVOH caused some extent of miscibility in the system on scales of nanometers especially when the PVOH content was low. The tensile strength and modulus of the blends were improved as compared to WP. However, the intermolecular interactions were relatively weak and could not be further enhanced by increasing PVOH component in the blends. The particle miscible WP/PVOH blends contained plasticised WP and PVOH phases in conjunction with the miscible WP/PVOH phase. Increasing the PVOH content in the blends did not result in an increase of the percentage of the miscible phase and the blends tented to be immiscible while the elongation of the blends was reduced when increasing the PVOH content in the blends.     

Applying storm water management in Greek cities: learning from the European experience

This paper is based on the studies forming part of the European research project DayWater, which aims at the promotion of stormwater source control (participating countries: UK, France, Sweden, Denmark, Germany, The Netherlands and Greece). Source control techniques include all techniques (e.g. retention, infiltration, reuse) of stormwater treatment near its source, in contrast to end-of-pipe. In this paper we present: the different stormwater management issues across Europe; the specific stormwater management issues in Greece; source control techniques applied in European cities; Public policies for promoting source control techniques; Strategies of application of the aforementioned techniques and policies in Greek cities. In Greece, the question of stormwater treatment has not yet attracted a lot of attention. Wastewater management, flood prevention and fresh water scarcity issues are given priority instead. However source control stormwater management can contribute to the solution of all these problems. In many European cities source control techniques have been chosen for stormwater treatment because: a) they are less expensive than massive end-of-pipe treatment installations, b) they are more compatible with the natural water cycle, c) they reduce the overall stormwater flow and thus permit the expansion of cities without requesting reconstruction of the existing sewer networks. Different policy instruments (taxes, specific regulations and controls, information campaigns) have been applied in order to promote source control techniques. The main objective of this work is to discuss the possibility of applying similar techniques and policies in Greek cities.     

Density Functions for Navigation-Function-Based Systems

In this paper, we present a scheme for constructing density functions for systems that are almost globally asymptotically stable (i.e., systems for which all trajectories converge to an equilibrium except for a set of measure zero) using navigation functions (NFs). Although recently-proven converse theorems guarantee the existence of density functions for such systems, such results are only existential and the construction of a density function for almost globally asymptotically stable systems remains a challenging task. We show that for a specific class of dynamical systems that are defined based on an NF, a density function can be easily derived from the system's underlying NF.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.     

A well‐conditioned and optimally convergent XFEM for 3D linear elastic fracture

A variation of the extended finite element method for three‐dimensional fracture mechanics is proposed. It utilizes a novel form of enrichment and point‐wise and integral matching of displacements of the standard and enriched elements in order to achieve higher accuracy, optimal convergence rates, and improved conditioning for two‐dimensional and three‐dimensional crack problems. A bespoke benchmark problem is introduced to determine the method's accuracy in the general three‐dimensional case where it is demonstrated that the proposed approach improves the accuracy and reduces the number of iterations required for the iterative solution of the resulting system of equations by 40% for moderately refined meshes and topological enrichment. Moreover, when a fixed enrichment volume is used, the number of iterations required grows at a rate which is reduced by a factor of 2 compared with standard extended finite element method, diminishing the number of iterations by almost one order of magnitude. Copyright © 2015 John Wiley & Sons, Ltd.