Private operators and time-of-day tolling on a congested road network

Private-sector involvement in the construction and operation of roads is growing around the world and private toll roads are seen as a useful tool in the battle against congestion. Yet serious concerns remain about exercise of monopoly power if private operators can set tolls freely. A number of theoretical studies have investigated private toll-road pricing strategies, and compared them with first-best and second-best public tolls. But most of the analyses have employed simple road networks and/or used static models that do not capture the temporal dimension of congestion or describe the impacts of tolling schemes that vary by time of day. This paper takes a fresh look at private toll road pricing using METROPOLIS: a dynamic traffic simulator that treats endogenously choices of transport mode, departure time and route at the level of individual travellers. Simulations are performed for the peak-period morning commute on a stylized urban road network with jobs concentrated towards the centre of the city. Tolling scenarios are defined in terms of what is tolled (traffic lanes, whole links, or toll rings) and how tolls are varied over time. Three administration regimes are compared. The first two are the standard polar cases: social surplus maximization by a public-sector operator, and unconstrained profit maximization by a private-sector operator. The third regime entails varying tolls in steps to eliminate queuing on the tolled links. It is a form of third-best tolling that could be implemented either by a public operator or by the private sector under quality-of-service regulation. Amongst the results it is found that the no-queue tolling regime performs favourably compared to public step tolling, and invariably better than private tolling. Another provisional finding is that a private operator has less incentive than does a public operator to implement time-of-day congestion pricing.

Projected Density Matrix Embedding Theory with Applications to the Two-Dimensional Hubbard Model

Density matrix embedding theory (DMET) is a quantum embedding theory for strongly correlated systems. From a computational perspective, one bottleneck in DMET is the optimization of the correlation potential to achieve self-consistency, especially for heterogeneous systems of large size. We propose a new method, called projected density matrix embedding theory (p-DMET), which achieves self-consistency without needing to optimize a correlation potential. We demonstrate the performance of p-DMET on the two-dimensional Hubbard model.Comment: 25 pages, 8 figure

Opioids for Dyspnea End of Life Review

Objective: The objective of this systematic review is to consolidate the existing evidence on opioid use, including administration, dosing and efficacy, for the relief of dyspnea at end-of-life. The overarching goal is to optimize clinical management of dyspnea by identifying patterns in opioid use, improving opioid management of dyspnea, and to prioritize future research. Background: Opioids are commonly used in the management of dyspnea at end of life; yet specific administration guidelines are limited. A greater understanding of the effectiveness of opioids in relieving end-of-life dyspnea with consideration of study design, patients, and opioids, including dyspnea evaluation tools and outcomes, will leverage development of standardized administration and dosing. Methods: A PRISMA guided systematic review using six databases identified quality studies of opioid management for patients with dyspnea at end of life. Results: Twenty-three references met review inclusion criteria which included terminally ill cancer and non-cancer patients with various diagnoses. Studies included two randomized controlled trials, three non-randomized experimental, three prospective observational, one cross-sectional, and one case series. Thirteen retrospective chart reviews were also included due to the limited rigorous studies rendered by the search. Thirteen studies evaluated morphine, followed by fentanyl (6), oxycodone (5), general opioid use (4), and hydromorphone (2). Routes of administration were parenteral, oral, combination, and nebulization. Dyspnea was evaluated using self-reporting and non-self-reporting evaluation tools. Sedation was the most reported opioid related adverse effect. Discussion: Challenges persist in conducting end of life research preventing consensus on standardization of opioid treatment for dyspnea within this specific palliative timeframe. Future robust prospective trials using specific, accurate assessment with re-assessment of dyspnea/respiratory distress, and consideration of opioid tolerance, polypharmacy, and comorbidities are require

Functional dimension of feedforward ReLU neural networks

It is well-known that the parameterized family of functions representable by fully-connected feedforward neural networks with ReLU activation function is precisely the class of piecewise linear functions with finitely many pieces. It is less well-known that for every fixed architecture of ReLU neural network, the parameter space admits positive-dimensional spaces of symmetries, and hence the local functional dimension near any given parameter is lower than the parametric dimension. In this work we carefully define the notion of functional dimension, show that it is inhomogeneous across the parameter space of ReLU neural network functions, and continue an investigation - initiated in [14] and [5] - into when the functional dimension achieves its theoretical maximum. We also study the quotient space and fibers of the realization map from parameter space to function space, supplying examples of fibers that are disconnected, fibers upon which functional dimension is non-constant, and fibers upon which the symmetry group acts non-transitively.Comment: 51 pages, 1 figur

First Steps towards Parameter Optimization of Bioelectrochemical Systems using a Microsystems Engineering Approach

There is a growing interest in exploiting bioelectrochemical systems (BESs), such as microbial fuel cells, as an alternative energy source for sustainable living. Certain species of microorganisms, such as Pseudomonas aeruginosa 14 (PA14) wild type, produce electron carriers, Phenazines, which transfers electrons to the anode in the system and produce digital output signal. The electric current generation of BESs is influenced by many biophysical and biochemical parameters in the system, such as glucose level, cell culture community, cell density, PH, and oxygen level. The existing MFCs are at macroscale, and not suitable for parameter optimization; and as a result they are not yet cost effective. Here, we present our first effort in parameter optimization of BESs using a microfluidic device. Microfluidic device affords us an ability to quickly define a physical and chemical environment for PA14, and its compatibility with microscope allows us a real time observation of the responses. We will present experimental results on the roles of carbon sources in PA14 motility and promising results of Phenazines being a chemoattractant to PA14. We will discuss the relation between PA14 motility and biofilm formation, and subsequently electric current generation

Establishing Pteridine Metabolism in a Progressive Isogenic Breast Cancer Cell Model – Part II

Introduction: Determining the biological significance of pteridines in cancer development and progression remains an important step in understanding the altered levels of urinary pteridines seen in certain cancers. Our companion study revealed that several folate-derived pteridines and lumazines correlated with tumorigenicity in an isogenic, progressive breast cancer cell model, providing direct evidence for the tumorigenic origin of pteridines. Objectives: This study sought to elucidate the pteridine biosynthetic pathway in a progressive breast cancer model via direct pteridine dosing to determine how pteridine metabolism changes with tumorigenicity. Methods: First, MCF10AT breast cancer cells were dosed individually with 15 pteridines to determine which pteridines were being metabolized and what metabolic products were being produced. Second, pteridines that were significantly metabolized were dosed individually across the progressive breast cancer cell model (MCF10A, MCF10AT, and MCF10ACA1a) to determine the relationship between each metabolic reaction and breast cancer tumorigenicity. Results: Several pteridines were found to have altered metabolism in breast cancer cell lines, including pterin, isoxanthopterin, xanthopterin, sepiapterin, 6-biopterin, lumazine, and 7-hydroxylumazine (p \u3c 0.05). In particular, isoxanthopterin and 6-biopterin concentrations were differentially expressed (p \u3c 0.05) with respect to tumorigenicity following dosing with pterin and sepiapterin, respectively. Finally, the pteridine biosynthetic pathway in breast cancer cells was proposed based on these findings. Conclusions: This study, along with its companion study, demonstrates that pteridine metabolism becomes disrupted in breast cancer tumor cells. This work highlights several key metabolic reactions within the pteridine biosynthetic pathway that may be targeted for further investigation and clinical applications