Developing Zero-Emission Bus and Truck Markets Will Require a Mix of Financial Incentives, Sale Mandates, and Demonstration Projects

California has a number of programs intended to encourage the introduction of zero- and near-zero emission vehicle (ZEV) technologies into the medium- and heavy-duty truck markets. Meeting the goals of these programs will require the sale of large numbers of battery-electric and hydrogen fuel cell transit buses and trucks by 2025 and beyond. However, several barriers to widespread adoption of these technologies will need to be addressed, including their purchase price, utility, durability and reliability, as well as the cost of energy and the availability of refueling infrastructure. Policies such as mandates or incentives will likely be necessary to overcome these barriers and the uncertainty of adopting a new, unproven technology. These policies must make economic sense to both the bus and truck manufacturers and the vehicle purchasers if they are to be successful in the long term. To gain a better understanding of the financial barriers for ZEV bus and truck adoption, researchers at UC Davis conducted technology and cost assessments for batteryelectric and fuel cell vehicles in the medium- and heavy-duty truck sector. High-level findings and the policy implications of this research are summarized in this brief

A heuristic approach for big bucket multi-level production planning problems

Multi-level production planning problems in which multiple items compete for the same resources frequently occur in practice, yet remain daunting in their difficulty to solve. In this paper, we propose a heuristic framework that can generate high quality feasible solutions quickly for various kinds of lot-sizing problems. In addition, unlike many other heuristics, it generates high quality lower bounds using strong formulations, and its simple scheme allows it to be easily implemented in the Xpress-Mosel modeling language. Extensive computational results from widely used test sets that include a variety of problems demonstrate the efficiency of the heuristic, particularly for challenging problems

Governance: public governance to social innovation?

ArticleThis paper reviews governance and public governance related to an emerging area of policy interest – social innovation. The European Commission’s White Paper on European Governance (2001) focused on openness, participation, accountability, effectiveness and coherence in public policy as characteristics of good governance. The EC has prioritised social innovation to address policy problems. Yet, the extant literature and research on social innovation is sparse. The paper questions whether it is a new mode of governance which contributes to good governance or a continuum of neoliberal reforms of the state which alters the relationship between the state, market and civil society

Zero-Emission Medium- and Heavy-duty Truck Technology, Markets, and Policy Assessments for California

This report assesses zero emissions medium- and heavy-duty vehicle technologies, their associated costs, projected market share, and possible policy mandates and incentives to support their adoption. Cost comparisons indicate that battery-electric transit buses and city delivery trucks are the most economically attractive of the zero-emission vehicles (ZEVs) based on their break-even mileage being a small fraction of the expected total mileage. These ZEVs using fuel cells are also attractive for a hydrogen cost of $5/kg. The most economically unattractive vehicle types for ZEV adoption are long-haul trucks and inter-city buses. Developing mandates for buses and trucks will be more difficult than for passenger cars for several reasons, including the large differences in the size and cost of the vehicles and the ways they are used in commercial, profit-oriented fleets. The best approach will be to develop separate mandates for classes of vehicles that have similar sizes, cost characteristics, use patterns, and ownership/business models. These mandates should be coupled to incentives that vary by vehicle type/class and by year or accumulated sales volume, to account for the effects of expected price reductions with time

Nominal Abstraction

Recursive relational specifications are commonly used to describe the computational structure of formal systems. Recent research in proof theory has identified two features that facilitate direct, logic-based reasoning about such descriptions: the interpretation of atomic judgments through recursive definitions and an encoding of binding constructs via generic judgments. However, logics encompassing these two features do not currently allow for the definition of relations that embody dynamic aspects related to binding, a capability needed in many reasoning tasks. We propose a new relation between terms called nominal abstraction as a means for overcoming this deficiency. We incorporate nominal abstraction into a rich logic also including definitions, generic quantification, induction, and co-induction that we then prove to be consistent. We present examples to show that this logic can provide elegant treatments of binding contexts that appear in many proofs, such as those establishing properties of typing calculi and of arbitrarily cascading substitutions that play a role in reducibility arguments.Comment: To appear in the Journal of Information and Computatio

Prudent banks and creative mimics : can we tell the difference?

The recent financial crisis has forced a rethink of banking regulation and supervision and the role of financial innovation. We develop a model where prudent banks may signal their type through high capital ratios. Capital regulation may ensure separation in equilibrium but deposit insurance will tend to increase the level of capital required. If supervision detects risky behaviour ex ante then it is complementary to capital regulation. However, financial innovation may erode supervisors' ability to detect risk and capital levels should then be higher. But regulators may not be aware their capacities have been undermined. We argue for a four-prong policy response with higher bank capital ratios, enhanced supervision, limits to the use of complex financial instruments and Coco's. Our results may support the institutional arrangements proposed recently in the UK

A Comparison of Patient History- and EKG-based Cardiac Risk Scores.

Patient-specific risk scores are used to identify individuals at elevated risk for cardiovascular disease. Typically, risk scores are based on patient habits and medical history - age, sex, race, smoking behavior, and prior vital signs and diagnoses. We explore an alternative source of information, a patient's raw electrocardiogram recording, and develop a score of patient risk for various outcomes. We compare models that predict adverse cardiac outcomes following an emergency department visit, and show that a learned representation (e.g. deep neural network) of raw EKG waveforms can improve prediction over traditional risk factors. Further, we show that a simple model based on segmented heart beats performs as well or better than a complex convolutional network recently shown to reliably automate arrhythmia detection in EKGs. We analyze a large cohort of emergency department patients and show evidence that EKG-derived scores can be more robust to patient heterogeneity