Exercise-induced muscle damage is reduced in resistance-trained males by branched chain amino acids: a randomized, double-blind, placebo controlled study

Background: It is well documented that exercise-induced muscle damage (EIMD) decreases muscle function and causes soreness and discomfort. Branched-chain amino acid (BCAA) supplementation has been shown to increase protein synthesis and decrease muscle protein breakdown, however, the effects of BCAAs on recovery from damaging resistance training are unclear. Therefore, the aim of this study was to examine the effects of a BCAA supplementation on markers of muscle damage elicited via a sport specific bout of damaging exercise in trained volunteers. Methods: Twelve males (mean ± SD age, 23 ± 2 y; stature, 178.3 ± 3.6 cm and body mass, 79.6 ± 8.4 kg) were randomly assigned to a supplement (n = 6) or placebo (n = 6) group. The damaging exercise consisted of 100 consecutive drop-jumps. Creatine kinase (CK), maximal voluntary contraction (MVC), muscle soreness (DOMS), vertical jump (VJ), thigh circumference (TC) and calf circumference (CC) were measured as markers of muscle damage. All variables were measured immediately before the damaging exercise and at 24, 48, 72 and 96 h post-exercise. Results: A significant time effect was seen for all variables. There were significant group effects showing a reduction in CK efflux and muscle soreness in the BCAA group compared to the placebo (P < 0.05). Furthermore, the recovery of MVC was greater in the BCAA group (P < 0.05). The VJ, TC and CC were not different between groups. Conclusion: The present study has shown that BCAA administered before and following damaging resistance exercise reduces indices of muscle damage and accelerates recovery in resistance-trained males. It seems likely that BCAA provided greater bioavailablity of substrate to improve protein synthesis and thereby the extent of secondary muscle damage associated with strenuous resistance exercise. Clinical Trial Registration Number: NCT01529281

A Newly Discovered Large and Significant Population of Castela emoryi (Emory’s Crucifixion Thorn, Simaroubaceae) in California

Castela emoryi is an understudied species, and recent visits to populations across California have shed new light on its distribution and biology, including recruitment, natural history, and herbivory. Field exploration in Rice Valley in Riverside County revealed what is considered to be the largest population of C. emoryi in California. Possible threats and conservation needs of this species are discussed

Evaluation of 3D Printed Immobilisation Shells for Head and Neck IMRT

This paper presents the preclinical evaluation of a novel immobilization system for patients undergoing external beam radiation treatment of head and neck tumors. An immobilization mask is manufactured directly from a 3-D model, built using the CT data routinely acquired for treatment planning so there is no need to take plaster of Paris moulds. Research suggests that many patients find the mould room visit distressing and so rapid prototyping could potentially improve the overall patient experience. Evaluation of a computer model of the immobilization system using an anthropomorphic phantom shows that >99% of vertices are within a tolerance of ±0.2 mm. Hausdorff distance was used to analyze CT slices obtained by rescanning the phantom with a printed mask in position. These results show that for >80% of the slices the median “worse-case” tolerance is approximately 4 mm. These measurements suggest that printed masks can achieve similar levels of immobilization to those of systems currently in clinical use

A New Species of Linanthus (Polemoniaceae) from San Bernardino County, California

Linanthus bernardinus is described as new from San Bernardino County, California. It is morphologically similar to L. killipii and L. orcuttii subsp. pacificus but differs from plants of these taxa in height, corolla length, seed morphology, and habitat. Linanthus bernardinus can be found growing in vernally moist areas within Joshua tree woodland, often in shallow depressions, or on gentle slopes, in decomposed granite sand that is surrounded by large granite boulder fields

Adoption of Computer Science in NZ schools

In 2011, Programming and Computer Science standards were made available as part of NCEA in New Zealand high schools. Because little guidance and professional development was available initially, teachers have found it challenging to present the content effectively to their students. In response to this, several resources and professional development opportunities have been made available, including the widely used Computer Science Field Guide for Computer Science, and several programming resources specific to the new standards. In this paper we outline the deployment of the new standards and supporting material, and look at the uptake of the new standards over the first three years that they were phased in. This reveals increasing participation at schools, and higher enrolments at university as a flow-on effect. The introduction of Computer Science has also helped to address perception and stereotypes about the industry, with high achievement by female students, although participation rates are not ideal

Presenting Computer Science Concepts to High School Students

Computer science at high school often focusses on programming, but a broader view of other areas of computer science has key benefits for both writing programs that are more efficient and making more theoretical concepts more accessible to those who do not find programming intrinsically interesting. With the introduction of computer science at high schools, a lack of coherent resources for teachers and students prompted the development of the NZ Computer Science Field Guide, an open-source, on-line textbook. This paper describes the design of the Field Guide, which has fourteen chapters about various topics of computer science. The design includes written text, videos, classroom activities and interactive applications. The need for a broad view of computer science is discussed, and programming exercises to go with the topics are suggested

J. G. Ballard’s Surrealist Liberalism

J. G. Ballard was one of the most original writers of the postwar era. Although he has drawn considerable attention from scholars across various fields, the character of his political thinking remains a puzzle. He has been claimed as both a radical and a conservative, while others suggest that his work expresses no distinct political stance. Drawing on a wide range of source materials, I argue that from the 1960s to the early years of the twenty-first century Ballard developed a bold and intriguing account of liberalism grounded in insights drawn from surrealism and Freudian psychoanalysis. This was an idiosyncratic version of the liberalism of fear. The essay analyzes Ballard’s sociopolitical vision, focusing in particular on his account of human nature, social reality, totalitarianism, and the power of the imagination

Fast classification of drones and birds with an LSTM network applied to 1D phase data

Funding: Science and Technology Facilities Council under grant ST/N006569/1.This study investigates a new type of drone classifier based on Long Short-Term Memory (LSTM) networks. As a real-time surveillance system, the classification time of a drone detection radar is crucial. The motivation for this work is to develop a classification framework which has low latency in terms of data processing for the algorithm input. Theoretical modeling of a rotary wing drone and a bird wing flapping returns were done first to exhibit the difference in the patterns of the respective phase progressions. Then, 94 GHzexperimental trial data containing 4800 sequences of drones, birds, noise and clutter were used to create a diverse training dataset of 1D phase data for supervised learning. A stackedLSTM network with tuned hyperparameters was generated to reduce the possible overfitting from a simple LSTM model. Validation accuracy of 98.1% was achieved for 2-class classification of drone and non-drone. Further performance assessment was then done with 30 unseen test data, where the network was able to correctly classify all the sequences. It is ascertained that this method can be ~10 times faster than a spectrogram based classification model, which requires additional Fast Fourier Transform (FFT) operations