For H.R. II and S. II to Strengthen the Robinson-Patman Act and Amend the Antitrust Law Prohibiting Price Discrimination

H. R. 11 and S. 11 are modest and simple legislative proposals.\u27They provide for no change in our antitrust laws prohibiting price discrimination except to limit somewhat the use of the good faith defense. The extent of this limitation goes no further than to assist the Act by providing that the good faith defense shall not operate as an absolute and complete bar to a proceeding by the Government against the practices of destructive price discrimination: In other words, those discriminations which would have the effect of substantially lessening competition and tending to create a monopoly may not be defended by showing that they were practiced in good faith. It appears that those opposing H. R. 11 and S. 11 want to insure legality of price discriminations, even at the cost of lessening competition and creation of monopoly. Actually, they are arguing for those ugly results, with the concession that the ugliness my be covered with the veil of good faith meeting of competition. Therefore, the naked issue over whether H. R. 11 and S. 11 should be enacted into law is, like the bill, quite simple. It is this: Shall we tolerate practices which destroy competition and create monopoly, even when those practices are based upon good intentions? It should not be difficult for us to resolve that issue, especially in the light of our national anti-monopoly public policy. Certainly, no practice destructive of competition and creative of monopoly can be said to be consonant with our antimonopoly public policy, even though the architect of such practices had some good, though misguided, purposes in mind. For ex-ample, mergers of corporations which destroy competition violate the antimerger law even though based on good intentions and for good purposes. In criminal causes, to be sure, evidence of intent is relevant to the issue. Here, we are not discussing proposals for amending the Criminal Code. Instead, we are discussing legislative proposals out of which only civil actions may arise

Science for the Next Century: Deep Phenotyping

Our ability to unravel the mysteries of human health and disease have changed dramatically over the past 2 decades. Decoding health and disease has been facilitated by the recent availability of high-throughput genomics and multi-omics analyses and the companion tools of advanced informatics and computational science. Understanding of the human genome and its influence on phenotype continues to advance through genotyping large populations and using “light phenotyping” approaches in combination with smaller subsets of the population being evaluated using “deep phenotyping” approaches. Using our capability to integrate and jointly analyze genomic data with other multi-omic data, the knowledge of genotype-phenotype relationships and associated genetic pathways and functions is being advanced. Understanding genotype-phenotype relationships that discriminate human health from disease is speculated to facilitate predictive, precision health care and change modes of health care delivery. The American Association for Dental Research Fall Focused Symposium assembled experts to discuss how studies of genotype-phenotype relationships are illuminating the pathophysiology of craniofacial diseases and developmental biology. Although the breadth of the topic did not allow all areas of dental, oral, and craniofacial research to be addressed (e.g., cancer), the importance and power of integrating genomic, phenomic, and other -omic data are illustrated using a variety of examples. The 8 Fall Focused talks presented different methodological approaches for ascertaining study populations and evaluating population variance and phenotyping approaches. These advances are reviewed in this summary

Kernel density classification and boosting: an L2 sub analysis

Kernel density estimation is a commonly used approach to classification. However, most of the theoretical results for kernel methods apply to estimation per se and not necessarily to classification. In this paper we show that when estimating the difference between two densities, the optimal smoothing parameters are increasing functions of the sample size of the complementary group, and we provide a small simluation study which examines the relative performance of kernel density methods when the final goal is classification. A relative newcomer to the classification portfolio is “boosting”, and this paper proposes an algorithm for boosting kernel density classifiers. We note that boosting is closely linked to a previously proposed method of bias reduction in kernel density estimation and indicate how it will enjoy similar properties for classification. We show that boosting kernel classifiers reduces the bias whilst only slightly increasing the variance, with an overall reduction in error. Numerical examples and simulations are used to illustrate the findings, and we also suggest further areas of research

Predicting evolution and visualizing high-dimensional fitness landscapes

The tempo and mode of an adaptive process is strongly determined by the structure of the fitness landscape that underlies it. In order to be able to predict evolutionary outcomes (even on the short term), we must know more about the nature of realistic fitness landscapes than we do today. For example, in order to know whether evolution is predominantly taking paths that move upwards in fitness and along neutral ridges, or else entails a significant number of valley crossings, we need to be able to visualize these landscapes: we must determine whether there are peaks in the landscape, where these peaks are located with respect to one another, and whether evolutionary paths can connect them. This is a difficult task because genetic fitness landscapes (as opposed to those based on traits) are high-dimensional, and tools for visualizing such landscapes are lacking. In this contribution, we focus on the predictability of evolution on rugged genetic fitness landscapes, and determine that peaks in such landscapes are highly clustered: high peaks are predominantly close to other high peaks. As a consequence, the valleys separating such peaks are shallow and narrow, such that evolutionary trajectories towards the highest peak in the landscape can be achieved via a series of valley crossingsComment: 12 pages, 7 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (A. Engelbrecht and H. Richter, eds.). Springer Series in Emergence, Complexity, and Computation, 201

Evaluation of the n-alkane technique for estimating herbage dry matter intake of dairy cows offered herbage harvested at two different stages of growth in summer and autumn

peer-reviewedThe n-alkane technique for estimating herbage dry matter intake (DMI) of dairy cows was investigated in this experiment. Eight Holstein-Friesian dairy cows were offered perennial ryegrass ad libitum that had been harvested at two different herbage masses and during two different seasons, in order to assess the effect of herbage mass and season on the accuracy of the n-alkane technique. Two pre-harvested herbage mass treatments (low, target 1500 kg DM/ha versus high, target 4000 kg DM/ha, measured above 4 cm), were investigated in a crossover factorial arrangement within each of two seasons (summer versus autumn), in Ireland. Each season consisted of two periods, each 12 days in length. Cows were housed in individual metabolism stalls to allow for accurate determination of measured DMI. Herbage DMI was estimated, with the n-alkane technique, by dosing cows twice daily with a C32 n-alkane. Pre-harvest herbage mass and season did not affect the n-alkane estimated DMI, although lack of season and herbage mass effects may have been masked by variation that occurred between swards within the same herbage mass and season. However, there were a number of differences between summer and autumn in the fecal recovery rates of a number of n-alkanes suggesting that the effect of season requires further investigation prior to the application of recovery rates from literature values when investigating diet selection and botanical composition. Overall, the n-alkane technique provided good estimates of DMI; the discrepancy had a standard deviation due to sward of 1.2 and 1.0 kg DM/cow per day, and hence potential bias of up to twice this, and a measurement error standard deviation of 1.3 and 1.0 kg DM/cow per day, for the C33/C32 and C31/C32 n-alkane pair methods respectively. Two n-alkane pairs were tested, and C33/C32 n-alkane provided the most precise estimates of DMI, compared with the C31/C32 n-alkane pair. This research provides some strong evidence for future use of the n-alkane technique including that the accuracy of the technique has not been influenced by contemporary changes to herbage management, is not affected by seasonal changes, and overall is an accurate and precise technique for estimating DMI.This research was funded by Teagasc Core Funding (Ireland) and the Irish Dairy Levy Research fund (Ireland). The Department of Economic Development, Jobs, Transport and Resources (Australia), Dairy Australia (Australia) and The University of Melbourne (Australia) supported the travel costs in order to conduct this research

Getting Better Hospital Alarm Sounds Into a Global Standard

The reserved set of audible alarm signals embodied within the global medical device safety standard, IEC 60601-1-8, is known to be problematic and in need of updating. The current alarm signals are not only suboptimal, but there is also little evidence beyond learnability (which is known to be poor) that demonstrates their performance in realistic and representative clinical environments. In this article, we describe the process of first designing and then testing potential replacement audible alarm signals for IEC 60601-1-8, starting with the design of several sets of candidate sounds and initial tests on learnability and localizability, followed by testing in simulated clinical environments. We demonstrate that in all tests, the alarm signals selected for further development significantly outperform the current alarm signals. We describe the process of collecting considerably more data on the performance of the new sounds than exists for the current sounds, which ultimately will be of use to end users. We also reflect on the process and practice of working with the relevant committees and other practical issues beyond the science, which also need constant attention if the alarms we have developed are to be included successfully in an updated version of the standard

Synthesis, biological profiling and mechanistic studies of 4-aminoquinoline-based heterodimeric compounds with dual trypanocidal–antiplasmodial activity.

YesDual submicromolar trypanocidal–antiplasmodial compounds have been identified by screening and chemical synthesis of 4-aminoquinoline-based heterodimeric compounds of three different structural classes. In Trypanosoma brucei, inhibition of the enzyme trypanothione reductase seems to be involved in the potent trypanocidal activity of these heterodimers, although it is probably not the main biological target. Regarding antiplasmodial activity, the heterodimers seem to share the mode of action of the antimalarial drug chloroquine, which involves inhibition of the haem detoxification process. Interestingly, all of these heterodimers display good brain permeabilities, thereby being potentially useful for late stage human African trypanosomiasis. Future optimization of these compounds should focus mainly on decreasing cytotoxicity and acetylcholinesterase inhibitory activity

Neurology

Contains reports on six research projects.U. S. Public Health Service (B-3055-4, B-3090-4, MH-06175-02)U. S. Air Force (AF49(638)-1313)U.S. Navy. Office of Naval Research (Nonr-1841(70)

Public perceptions of environmental friendliness of renewable energy power plants

Demanding EU targets for renewables create challenges for governmental decisions regarding energy sources and plant sitting. In this study we explore perceptions of the Portuguese general population regarding renewable energy power plants. In particular we study how these are affected by dimensions such as home distance to the power plant and its visibility, familiarity with the different energy sources, involvement in terms of employment, and socioeconomic characteristics. We find considerable differences in perception depending on familiarity and involvement with energy sources, environmental friendliness, and specific environmental impacts. Assessment of public perceptions of renewables should thus include these different dimensions.The authors gratefully acknowledge the financial support from FCT Fundacao para a Ciencia e Tecnologia with Grant Number PTDC/EGE-ECO/122402/2010