Resting costs too: the relative importance of active and resting energy expenditure in a sub-arctic seabird

Breeding is costly for many animals, including birds that must deliver food to a central place (i.e. nest). Measuring energy expenditure throughout the breeding season can provide valuable insights on physiological limitations by highlighting periods of high demands, and ultimately allows to improve conservation strategies. However, quantifying energy expenditure in wildlife can be challenging, as existing methods do not measure both active (e.g. foraging) and resting energy costs across short and long time scales. Here, we develop a novel method for comparing active and resting costs in 66 pre-breeding and breeding seabirds (black-legged kittiwakes; Rissa tridactyla) by combining accelerometry and triiodothyronine (T3), as proxies for active and resting costs, respectively. Activity energy costs were higher during incubation (p=0.0004) and chick-rearing (p<0.0001) compared to pre-laying, due to an increase in time spent in flight of 11% (p=0.0005) and 15% (p<0.0001), respectively. Levels of T3, reflecting resting costs, peaked marginally during incubation with an average concentration of 4.71±1.97 pg mL−1 in comparison to 2.66±1.30 pg mL−1 in pre-laying (p=0.05), and 3.16±2.85 pg mL−1 in chick-rearing (p=11). Thus, although chick-rearing is often assumed to be the costliest breeding stage by multiple studies, our results suggest that incubation could be more costly due to high resting costs. We highlight the importance of accounting for both active and resting costs when assessing energy expenditure.

Energy-aware and Carbon-efficient VM Placement Optimization in Cloud Datacenters Using Evolutionary Computing Methods

One of the most important concerns of cloud service providers is balancing renewable and fossil energy consumption. On the other hand, the policy of organizations and governments is to reduce energy consumption and greenhouse gas emissions in cloud data centers. Recently, a lot of research has been conducted to optimize the Virtual Machine (VM) placement on physical machines to minimize energy consumption. Many previous studies have not considered the deadline and scheduling of IoT tasks. Therefore, the previous modelings are mainly not well-suited to the IoT environments where requests are time-constraint. Unfortunately, both the sub-problems of energy consumption minimization and scheduling fall into the category of NP-hard issues. In this study, we propose a multi-objective VM placement to joint minimizing energy costs and scheduling. After presenting a modified memetic algorithm, we compare its performance with baseline methods as well as state-of-the-art ones. The simulation results on the CloudSim platform show that the proposed method can reduce energy costs, carbon footprints, SLA violations, and the total response time of IoT requests.

An optical neural network using less than 1 photon per multiplication

Deep learning has become a widespread tool in both science and industry. However, continued progress is hampered by the rapid growth in energy costs of ever-larger deep neural networks. Optical neural networks provide a potential means to solve the energy-cost problem faced by deep learning. Here, we experimentally demonstrate an optical neural network based on optical dot products that achieves 99% accuracy on handwritten-digit classification using ~3.1 detected photons per weight multiplication and ~90% accuracy using ~0.66 photons (~2.5 × 10−19 J of optical energy) per weight multiplication. The fundamental principle enabling our sub-photon-per-multiplication demonstration—noise reduction from the accumulation of scalar multiplications in dot-product sums—is applicable to many different optical-neural-network architectures. Our work shows that optical neural networks can achieve accurate results using extremely low optical energies.

Mathematical Modeling of Knowledge-Intensive Products Export Energy Costs

This article presents the mathematical modeling of export energy costs. The knowledge-intensive products export energy costs are a set of financial, material, labor costs and resources consumption. Export costs are a multilevel system of indicators. The author sets out the order of mathematical modeling. At the first stage, the main trends in reducing export energy costs are identified. A set of integrated logistics support measures is modeled. The modeling of knowledge-intensive products export energy costs is a system of technical and economic indices and a cost value dependance: Maintenance and Repair, Material and Technical Maintenance, Business Model of After-Sales Service, Formation of the Cost of Insurance and Investment Management Strategy. Formulas, practical calculation examples and graphs are presented. The Ishikawa systematic analysis method is used to visualize data and dependence relations. The author's mathematical modeling of knowledge-intensive products export costs includes the calculation of integrated logistic support costs. Exporting countries require a high level of technical products efficiency. It has been established that "the more complex a knowledge-intensive products is, the higher the reliability of systems is". Reliability indices are basic. The author's scientific study confirms a hypothesis of the knowledge-intensive products export feasibility only with high reliability and efficiency factors. The author developed a set of integrated logistical support measures for knowledge-intensive products.

Comparison of thigh muscle activations in single leg exercises: bench squat, step-up, airborne lunge

Background and Study Aim. Single leg exercises have some advantages in terms of time, practice and energy costs. However, the activation values that occur in different single leg exercises can be used for training planning. The aim of this research was to examine the thigh muscle activation values during three different single leg exercises. Materials and Methods. Ten healthy male volunteers who were students of the faculty of sports sciences participated in the study. In the study, the EMG ampilitude values of the vastus medialis (VM), vastus lateralis (VL), semitendinosus (SEM) and biceps femoris (BF) muscles were examined during Step-up, Bench Squat and Airborne Lunge exercises. At the same time, Quadriceps (VM+VL): Hamstring (SEM+BF) ratios were determined. Results. Significant differences were detected in all thigh muscles in the ascent and descent phases (p<0.05). While the greatest activation for the quadriceps group was seen in the airborne lunge, the greatest activation for the hamstring group was detected in the bench squat. A statistically significant difference was found in terms of exercise practices in the quadriceps: hamstring (Q:H) ratio (F(2,18)=12.282, p=.003). It was seen that the most balanced exercise was bench squat (Q:H=2.55), and the most unbalanced exercise (agonist dominant) was airborne lunge (Q:H=5.51). Conclusions. The findings show that the exercises examined can be selected depending on the purpose of the training. While bench squats can be preferred for more balanced co-activation the airborne lunge can be preferred for dominant knee extensors.

Development of a mathematical model of functioning system communications spacecraft

The paper discusses a mathematical model of the functioning of communication spacecraft, using systems of differential equations for translational and rotational motion, as well as the process of distributing problems in a constellation of three satellites. The model is implemented by means of the python 3.6 language and the computational method library numpy1.19. A series of computational experiments was carried out in order to estimate the energy costs for the operation of grouping with various orbital parameters and external impact models. The presented results of the experiments suggest the possibility of increasing the life of spacecraft by improving the operating system.

EFFICIENCY OF ANTHROPOGENIC ENERGY COSTS IN THE CREATION AND LONG-TERM USE OF DIFFERENT-RIPENING CEREAL HAYFIELDS

The results of the agro-energy assessment of the creation and long-term haymaking use (for 27 years) of different-ripening cereal grasses are presented. The total costs of anthropogenic energy were recouped by the collection of metabolic energy by 2,8–3,3 times. In the structure of metabolic energy production, renewable natural factors accounted for 64–70%.

Robert McNeill Alexander. 7 July 1934—21 March 2016

Neill Alexander graduated in natural sciences at the University of Cambridge in 1955. After a PhD at Cambridge and a lecturership at the University College of North Wales in Bangor, he was appointed to the chair of the Department of Pure and Applied Zoology at the University of Leeds in 1969. At that stage, he switched his research interests abruptly from fishes to the mechanics of legged locomotion. He conducted experiments with a variety of mammals, calculating forces, stresses and strains in muscle fibres, bones and tendons. His speciality became the application of mathematical models to animal locomotion, including repurposing the Froude number, devised by the Victorian engineer William Froude (FRS 1870) for use with ships, to estimate the speed of dinosaurs based on the spacing of their fossil footprints. Subsequent work included modelling the optimization of mammal performance and the minimization of energy costs. In 1992, following an announcement that London Zoo would have to close as a result of shortage of funds, Neill was appointed secretary of the Zoological Society of London. During the period of his secretaryship, the Society's finances recovered, with both its zoos (London and Whipsnade) breaking even in 1993 and the Society returning a surplus in each subsequent year. Neill was awarded the CBE in 2000. The National Portrait Gallery holds his portrait by John Arnison.