Research Lags Revisited: Concepts and Evidence from U.S. Agriculture

Many researchers and commentators underestimate the length and importance of the time lags between initial research investment and ultimate impacts on the development and adoption of technological innovations. In both econometric studies of productivity and ex post and ex ante benefit-cost evaluations of research investments, researchers typically impose untested assumptions about the R&D lag, which can have profound implications for the results. In this paper we present a range of evidence on agricultural R&D lags including both aggregative analysis of U.S. agricultural productivity using time series data, and some specific details on the timelines for the research, development, and adoption processes for particular mechanical and biological innovations in U.S. agriculture. The aggregative analysis makes use of a comparatively rich state-level data set on U.S. agriculture that makes it possible to test hypotheses about the R&D lag and to evaluate the implications for the specification of models of production and for findings regarding the rate of return to public research investments. The results support the use of a longer lag with a different shape than is typically imposed in studies of industrial R&D. These findings are supported by the timelines for specific technological innovations, including new crop varieties, as well as tractors and other mechanical innovations.Research and Development/Tech Change/Emerging Technologies,

Include medical ethics in the Research Excellence Framework

The Research Excellence Framework of the Higher Education Funding Council for England is taking place in 2013, its three key elements being outputs (65% of the profile), impact (20%), and “quality of the research environment” (15%). Impact will be assessed using case studies that “may include any social, economic or cultural impact or benefit beyond academia that has taken place during the assessment period.”1 Medical ethics in the UK still does not have its own cognate assessment panel—for example, bioethics or applied ethics—unlike in, for example, Australia. Several researchers in medical ethics have reported to the Institute of Medical Ethics that during the internal preliminary stage of the Research Excellence Framework several medical schools have decided to include only research that entails empirical data gathering. Thus, conceptual papers and ethical analysis will be excluded. The arbitrary exclusion of reasoned discussion of medical ethics issues as a proper subject for medical research unless it is based on empirical data gathering is conceptually mistaken. “Empirical ethics” is, of course, a legitimate component of medical ethics research, but to act as though it is the only legitimate component suggests, at best, a partial understanding of the nature of ethics in general and medical ethics in particular. It also mistakenly places medicine firmly on only one side of the science/humanities “two cultures” divide instead of in its rightful place bridging the divide. Given the emphasis by the General Medical Council on medical ethics in properly preparing “tomorrow’s doctors,” we urge medical schools to find a way of using the upcoming Research Excellence Framework to highlight the expertise residing in their ethicist colleagues. We are confident that appropriate assessment will reveal work of high quality that can be shown to have social and cultural impact and benefit beyond academia, as required by the framework

Tracking EEG changes to alpha and beta binaural beats

A binaural beat can be produced by presenting two tones of differing frequency, one to each ear. Such auditory stimulation has been suggested to influence behaviour and cognition via the process of cortical entrainment. However, research so far has only shown frequency following responses in the traditional EEG frequency ranges of delta, theta and gamma. Hence a primary aim of this research was to ascertain whether it would be possible to produce clear changes in the EEG in either the alpha or beta frequency ranges. Such changes, if possible, would have a number of important implications as well as potential applications. A secondary goal was to track any observable changes in EEG throughout the entrainment epoch to gain some insight into the nature of the entrainment effects any changes in an effort to identify more effective entrainment regimes. Twenty two healthy participants were recruited and randomly allocated to one of two groups, each of which was exposed to a distinct binaural beat frequency for ten 1-minute epochs. The first group listened to an alpha binaural beat of 10Hz and the second to a beta binaural beat of 20Hz. EEG was recorded from the left and right temporal regions during pre-exposure baselines, stimulus exposure epochs and post-exposure baselines. Analysis of changes in broad-band and narrow-band amplitude, and frequency showed no effect of either binaural beat frequency eliciting a frequency following effect in the EEG. Possible mediating factors are discussed and a number of recommendations are made regarding future studies, exploring entrainment effects from binaural beat presentation

Substitution Laws and Innovation in the Pharmaceutical Industry

When the sensors readings are perturbed by an unknown stochastic time jitter, classical system identification algorithms based on additive amplitude perturbations will give biased estimates. We here outline the maximum likelihood procedure, for the case of both time and amplitude noise, in the frequency domain, based on the measurement DFT. The method directly applies to output error continuous time models, while a simple sinusoid in noise example is used to illustrate the bias removal of the proposed method

Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time

This paper investigates how to utilize different forms of human interaction to safely train autonomous systems in real-time by learning from both human demonstrations and interventions. We implement two components of the Cycle-of-Learning for Autonomous Systems, which is our framework for combining multiple modalities of human interaction. The current effort employs human demonstrations to teach a desired behavior via imitation learning, then leverages intervention data to correct for undesired behaviors produced by the imitation learner to teach novel tasks to an autonomous agent safely, after only minutes of training. We demonstrate this method in an autonomous perching task using a quadrotor with continuous roll, pitch, yaw, and throttle commands and imagery captured from a downward-facing camera in a high-fidelity simulated environment. Our method improves task completion performance for the same amount of human interaction when compared to learning from demonstrations alone, while also requiring on average 32% less data to achieve that performance. This provides evidence that combining multiple modes of human interaction can increase both the training speed and overall performance of policies for autonomous systems.Comment: 9 pages, 6 figure

Automated fiber placement: Evolution and current demonstrations

The automated fiber placement process has been in development at Hercules since 1980. Fiber placement is being developed specifically for aircraft and other high performance structural applications. Several major milestones have been achieved during process development. These milestones are discussed in this paper. The automated fiber placement process is currently being demonstrated on the NASA ACT program. All demonstration projects to date have focused on fiber placement of transport aircraft fuselage structures. Hercules has worked closely with Boeing and Douglas on these demonstration projects. This paper gives a description of demonstration projects and results achieved

Migrating to Cloud-Native Architectures Using Microservices: An Experience Report

Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not ready to fully exploit the benefits of this environment, and adapting them to this environment is a non-trivial task. Microservices have appeared recently as novel architectural styles that are native to the cloud. These cloud-native architectures can facilitate migrating on-premise architectures to fully benefit from the cloud environments because non-functional attributes, like scalability, are inherent in this style. The existing approaches on cloud migration does not mostly consider cloud-native architectures as their first-class citizens. As a result, the final product may not meet its primary drivers for migration. In this paper, we intend to report our experience and lessons learned in an ongoing project on migrating a monolithic on-premise software architecture to microservices. We concluded that microservices is not a one-fit-all solution as it introduces new complexities to the system, and many factors, such as distribution complexities, should be considered before adopting this style. However, if adopted in a context that needs high flexibility in terms of scalability and availability, it can deliver its promised benefits

NASA Space applications of high-temperature superconductors

The application of superconducting technology in space has been limited by the requirement of cooling to near liquid helium temperatures. The only means of obtaining these temperatures has been with cryogenic fluids which severely limit mission lifetime. The development of materials with superconducting transition temperatures above 77 K has made superconducting technology more attractive and feasible for employment in aerospace systems. Here, potential applications of high temperature superconducting technology in cryocoolers, remote sensing, communications, and power systems are discussed

Day-to-Day Glycemic Variability Using Continuous Glucose Monitors in Endurance Athletes

Objectives: The application of continuous glucose monitors (CGMs) to measure interstitial glucose in athletic populations is limited by the lack of accepted athlete-specific reference values. The aim of this study was to develop athlete-specific reference ranges for glycemic variability under standardized diet and exercise conditions. Methods: A total of 12 elite racewalkers (n = 7 men, 22.4 ± 3.5 years, VO2max 61.6 ± 7.3 mL kg−1 min−1) completed two 4-d trials separated by 4-d. Athletes were provided a high-energy, high-carbohydrate diet (225 ± 1.6 kJ kg−1 day−1, 8.4 ± 0.3 g kg−1 day−1 carbohydrate) and completed standardized daily exercise. The timing of food consumed and exercise undertaken were matched each day across the 4-d trials. Interstitial glucose data were collected via Freestyle Libre 2 CGMs. Glycemic variability was calculated as the mean amplitude of glycemic excursions (MAGEs), mean of daily differences (MODD), and standard deviation (SD). Results: Twenty-four hour MODD, MAGE, and SD for interstitial glucose were 12.6 ± 1.8 mg/dL (0.7 ± 0.1 mmol/L), 36.0 ± 5.4 mg/dL (2.0 ± 0.3 mmol/L), and 16.2 ± 1.8 mg/dL (0.9 ± 0.1 mmol/L), respectively. Twenty-four hour mean glucose (MG; 102.6 ± 5.4 mg/dL [5.7 ± 0.3 mmol/L]) was higher than overnight (91.8 ± 5.4 mg/dL [5.1 ± 0.3 mmol/L]; P &lt;.0001) and was lower in women than men (99.0 ± 3.6 mg/dL [5.5 ± 0.2 mmol/L] vs 104.4 ± 3.6 mg/dL [5.8 ± 0.2 mmol/L]; P =.059, d = 1.4). Conclusions: This study provides reference indices under standardized diet and exercise conditions for glycemic variability derived from CGMs in endurance athletes which are similar than previously reported for healthy individuals, despite strenuous daily training and a high daily energy and carbohydrate diet.</p