How relative prices affect fuel use patterns in manufacturing : plant - level evidence from Chile

Some economists have urged reliance on fuel taxes and other fiscal incentives to reduce air pollution in semi-industrialized countries. They argue that policies that act on relative prices are easier to enforce than those based on emission monitoring, create less misallocation of resources, and are relatively free of the rent-seeking and corruption that accompany regulations administered at the plant level. To be effective, however, fuel specific taxes and subsidies must inspire manufacturers to significantly adjust their input use as relative prices change. Moreover, these policies must not create politically unacceptable income redistribution. The authors shed light on both issues by analyzing detailed panel data on Chilean manufacturing plants. Overall, their estimates suggest that there is substantial scope for fuel taxes to encourage fuel substitution, but that the response will be very uneven - not only across sectors but across producers of different sizes. Although others may be correct in arguing that fiscal incentives are easier to implement that are direct emission controls, the costs of adjustment are likely to be concentrated fairly narrowly for some fuels. The authors found bakeries, for example, to be very responsive to changes in the relative prices of alternative fuels. By contrast, energy demand in metal products plants appears to be very insensitive to relative prices, no matterwhat estimates are used. Meatpackers fall somewhere between the two - with little price responsiveness in electricity demand, but more in the demand for energy from other sources, especially if coherency-constrained figures are used. It seems that the effects of fuel taxes would depend in significant measure on the sectoral composition varies and some sectors have little flexibility.Energy and Environment,Economic Theory&Research,Transport and Environment,Access to Markets,Environmental Economics&Policies

Residential On-Site Carsharing and Off-Street Parking Policy in the San Francisco Bay Area, Research Report 11-28

In light of rising motorization, transportation planners have increasingly supported alternatives to the indiscriminate use of the car. Off-street parking policy and carsharing have emerged as credible alternatives for discouraging car ownership. This report explores an initiative that could connect these policy fields and build on their synergy: the provision of on-site carsharing service in residential developments. It evaluates the performance of on-site carsharing programs in the San Francisco Bay Area by interviewing developers, planners, and carsharing service providers. Interviews were conducted in four Bay Area cities that support the provision of carsharing as an alternative to the private automobile. Based on these interviews, this report identifies the principal factors contributing to the success or failure of on-site carsharing: the unbundling status of off-street parking in residential developments; ties to off-street parking standards; financial constraints; and the level of coordination among stakeholders. The interviews revealed that on-site carsharing has been accepted by developers, planners, and service providers, particularly in densely-populated, transit-rich communities. Nevertheless, there appears to be a gap between on-site carsharing programs and off-street parking standards, and between carsharing programs and carsharing business operations. The authors recommend that a few models for establishing carsharing policy be tested: a model designed to serve high-density cities with traditional carsharing; and another designed to serve moderately-dense communities, with new carsharing options (e.g., peer-to-peer). In the case of the latter, trip reduction can be achieved through the promotion of alternative modes along major corridors

Amenity or Necessity? Street Standards as Parking Policy, Research Report 11-23

This paper explores the rationales underlying the use of minimum street width requirements to mandate street parking. A survey of 97 cities reveals that this mandate is not a technical necessity based on safety concerns or an amenity reflecting market demand, two common beliefs held by decision-makers. Many residents are likely unwilling to pay for street parking if it is unbundled from housing. The hidden parking policies should be made transparent and subject to public oversight, the double standard between private and public streets should be eliminated, and parking on residential streets should be optional

Content Based Image Retrieval by Convolutional Neural Networks

Hamreras S., Benítez-Rochel R., Boucheham B., Molina-Cabello M.A., López-Rubio E. (2019) Content Based Image Retrieval by Convolutional Neural Networks. In: Ferrández Vicente J., Álvarez-Sánchez J., de la Paz López F., Toledo Moreo J., Adeli H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science, vol 11487. Springer.In this paper, we present a Convolutional Neural Network (CNN) for feature extraction in Content based Image Retrieval (CBIR). The proposed CNN aims at reducing the semantic gap between low level and high-level features. Thus, improving retrieval results. Our CNN is the result of a transfer learning technique using Alexnet pretrained network. It learns how to extract representative features from a learning database and then uses this knowledge in query feature extraction. Experimentations performed on Wang (Corel 1K) database show a significant improvement in terms of precision over the state of the art classic approaches.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Dynamic Leadership: Toolbox for the Values-Based Entrepreneur

Four entrepreneurship models are proposed which lend guidance in the development of a business, from birth to exit, each examining ways to maintain the business founder’s initial vision and to continue to infuse values and ethical decision-making at each stage of development

Explaining the Short- and Long-Term IPO Anomalies in the US by R&D

Financial scholars who research the initial underpricing and long-term underperformance of IPOs generally attribute these phenomena to information asymmetry and investors' misevaluations. Here, we identify, on a sample of 2,696 US IPOs issued during 1980-1995, a widespread source of information asymmetry and valuation uncertainty - the R&D activities of issuers - and document that these activities significantly affect both the initial underpricing of IPOs (R&D is positively correlated with underpricing) and their long-term performance (R&D is positively related to long-term performance). Given the pervasiveness and constant growth of firms' R&D activities in modern economies, our identification of R&D as a major factor affecting IPO's performance contributes to the understanding of this important economic and capital market phenomenon

Flow charts: visualization of vector fields on arbitrary surfaces

Journal ArticleWe introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme, the surface and its associated flow are segmented into overlapping patches, which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into hardware accelerated flow visualization techniques for interactive performance