Nonrivalry and Price Discrimination in Copyright Economics

The literature on the economics of copyright proceeds from the premise that copyrightable works constitute pure public goods, which is generally modeled by assuming that such works are nonexcludable and that the marginal cost of making additional copies is essentially zero. A close examination of the foundational literature on public goods theory reveals that the defining characteristic of public goods is instead the optimality criterion known as the “Samuelson condition,” which implies that the systematic bias toward underproduction is the result of the inability to induce consumers to reveal their preferences rather than the inability to exclude or price at marginal cost. Reframing the analysis in terms of the Samuelson condition also contradicts the hostility toward price discrimination reflected in much of the literature by implying that price discrimination is a necessary condition for optimality. At the same time, it implies that the producer need only appropriate the marginal benefits created by the public good, which in turn provides a basis for determining an optimal level of price discrimination that still permits consumers to retain some of the surplus. Moreover, broadening public good models to reflect the fact that copyrighted works often serve as imperfect substitutes for one another allows the number of works to be determined endogenously. In such impure public goods models, the systematic bias toward underproduction disappears, and price discrimination once again may (but need not necessarily) promote optimality

Depressed clad hollow optical fiber with fundamental LP01 mode cut-off

We propose a depressed clad hollow optical fiber with fundamental (LP01) mode cut-off suitable for high power short-wavelength, especially three-level, fiber laser operation by introducing highly wavelength dependent losses at longer wavelengths. The cut-off characteristic of such fiber structure was investigated. A Yb-doped depressed clad hollow optical fiber laser generating 59.1W of output power at 1046nm with 86% of slope efficiency with respect to the absorbed pump power was realised by placing the LP01 mode cut-off at ~1100nm

Complex imaging of phase domains by deep neural networks

The reconstruction of a single-particle image from the modulus of its Fourier transform, by phase-retrieval methods, has been extensively applied in X-ray structural science. Particularly for strong-phase objects, such as the phase domains found inside crystals by Bragg coherent diffraction imaging (BCDI), conventional iteration methods are time consuming and sensitive to their initial guess because of their iterative nature. Here, a deep-neural-network model is presented which gives a fast and accurate estimate of the complex single-particle image in the form of a universal approximator learned from synthetic data. A way to combine the deep-neural-network model with conventional iterative methods is then presented to refine the accuracy of the reconstructed results from the proposed deep-neural-network model. Improved convergence is also demonstrated with experimental BCDI data

Isolation and characterization of cellulose degrading ability in Paenibacillus isolates from landfill leachate

Aims: Cellulases are enzymes that convert cellulose into glucose molecules, and are produced by various microorganisms in the environment. Due to their importance to the biofuel industry, there is a need to screen for more efficient varieties of cellulases. In this study, leachate samples from a landfill site were screened for cellulolytic bacteria. Methodology and results: Leachate samples obtained from a landfill collection pond were cultured in an enriched cellulose medium. Two cellulolytic isolates, designated MAEPY1 and MAEPY2, were isolated and further characterized. Phenotypic profiles and phylogenetic analyses using sequences of 16S rRNA, gyrB and whole genome suggested that these isolates are new strains of the Paenibacillus genera. The crude enzyme extracts from both isolates have cellulose degradation activity at approximately 0.1-0.2 IU/mg under working conditions of pH 6 and 55 °C. Assays using other lignocellulosic substrates showed that the crude enzyme extracts also have high xylan degradation activity. Conclusion, significance and impact of study: Paenibacillus sp. are known to produce multiple enzymes for lignocellulolytic degradation and the present results suggest that isolates described in this study, MAEPY1 and MAEPY2, are excellent candidates deserving further study as potential producers of efficient cellulases for use in industries associated with cellulosic biomass

Municipal Fiber in the United States: A Financial Assessment

Despite growing interest in broadband provided by municipally owned and operated fiber-to-the-home networks, the academic literature has yet to undertake a systematic assessment of these projects’ financial performance. To fill this gap, we utilize municipalities’ official reports to offer an empirical evaluation of the financial performance of every municipal fiber project in the U.S. operating in 2010 through 2019. An analysis of the actual performance of the resulting fifteen-project panel dataset reveals that none of the projects generated sufficient nominal cash flow in the short run to maintain solvency without infusions of additional cash from outside sources or debt relief. Similarly, 87% have not actually generated sufficient nominal cash flow to put them on track to achieve long-run solvency. In addition, 73% generated negative nominal cash flow over the past three fiscal years, leaving them poorly positioned to make up their deficits and causing them to fall farther into debt. An assessment based on the net present value of these projects’ operating cash flow indicates that 53% of projects would not be on track to breakeven even assuming the theoretical best-case performance in terms of capital expenditures and debt service. Close analysis of these projects’ performance reveals that revenue generation likely plays a more important role in generating cash flow than efficiency in construction costs or operating efficiency

The Oracle Problem in Software Testing: A Survey

Testing involves examining the behaviour of a system in order to discover potential faults. Given an input for a system, the challenge of distinguishing the corresponding desired, correct behaviour from potentially incorrect behavior is called the “test oracle problem”. Test oracle automation is important to remove a current bottleneck that inhibits greater overall test automation. Without test oracle automation, the human has to determine whether observed behaviour is correct. The literature on test oracles has introduced techniques for oracle automation, including modelling, specifications, contract-driven development and metamorphic testing. When none of these is completely adequate, the final source of test oracle information remains the human, who may be aware of informal specifications, expectations, norms and domain specific information that provide informal oracle guidance. All forms of test oracles, even the humble human, involve challenges of reducing cost and increasing benefit. This paper provides a comprehensive survey of current approaches to the test oracle problem and an analysis of trends in this important area of software testing research and practice

Control of carbon nanotube morphology by change of applied bias field during growth

Carbon nanotube morphology has been engineered via simple control of applied voltage during dc plasma chemical vapor deposition growth. Below a critical applied voltage, a nanotube configuration of vertically aligned tubes with a constant diameter is obtained. Above the critical voltage, a nanocone-type configuration is obtained. The strongly field-dependent transition in morphology is attributed primarily to the plasma etching and decrease in the size of nanotube-nucleating catalyst particles. A two-step control of applied voltage allows a creation of dual-structured nanotube morphology consisting of a broad base nanocone (~200 nm dia.) with a small diameter nanotube (~7 nm) vertically emanating from the apex of the nanocone, which may be useful for atomic force microscopy

The Complexity of Codiagnosability for Discrete Event and Timed Systems

In this paper we study the fault codiagnosis problem for discrete event systems given by finite automata (FA) and timed systems given by timed automata (TA). We provide a uniform characterization of codiagnosability for FA and TA which extends the necessary and sufficient condition that characterizes diagnosability. We also settle the complexity of the codiagnosability problems both for FA and TA and show that codiagnosability is PSPACE-complete in both cases. For FA this improves on the previously known bound (EXPTIME) and for TA it is a new result. Finally we address the codiagnosis problem for TA under bounded resources and show it is 2EXPTIME-complete.Comment: 24 pages