Predator cue studies reveal strong trait-mediated effects in communities despite variation in experimental designs

Nonconsumptive or trait-mediated effects of predators on their prey often outweigh density-mediated interactions where predators consume prey. For instance, predator presence can alter prey behaviour, physiology, morphology and/or development. Despite a burgeoning literature, our ability to identify general patterns in prey behavioural responses may be influenced by the inconsistent methodologies of predator cue experiments used to assess trait-mediated effects. We therefore conducted a meta-analysis to highlight variables (e.g. water type, predator husbandry, exposure time) that may influence invertebrate prey's behavioural responses to fish predator cues. This revealed that changes in prey activity and refuge use were remarkably consistent overall, despite wide differences in experimental methodologies. Our meta-analysis shows that invertebrates altered their behaviour to predator cues of both fish that were fed the focal invertebrate and those that were fed other prey types, which suggests that invertebrates were not responding to specific diet information in the fish cues. Invertebrates also altered their behaviour regardless of predator cue addition regimes and fish satiation levels. Cue intensity and exposure time did not have significant effects on invertebrate behaviour. We also highlight that potentially confounding factors, such as parasitism, were rarely recorded in sufficient detail to assess the magnitude of their effects. By examining the likelihood of detecting trait-mediated effects under large variations in experimental design, our study demonstrates that trait-mediated effects are likely to have pervasive and powerful influences in nature.

Lovastatin biosynthesis depends on the carbon-nitrogen proportion: model development and controller design

Lovastatin biosynthesis depends on the relative concentrations of dissolved oxygen and the carbon and nitrogen resources. An elucidation of the underlying relationship would facilitate the derivation of a controller for the improvement of lovastatin yield in bioprocesses. To achieve this goal, batch submerged cultivation experiments of lovastatin production by Aspergillus flavipus BICC 5174, using both lactose and glucose as carbon sources, were performed in a 7 liter bioreactor and the data used to determine how the relative concentrations of lactose, glucose, glutamine and oxygen affected lovastatin yield. A model was developed based on these results and its prediction was validated using an independent set of batch data obtained from a 15-liter bioreactor using five statistical measures, including the Willmott index of agreement. A nonlinear controller was designed considering that dissolved oxygen and lactose concentrations could be measured online, and using the lactose feed rate and airflow rate as process inputs. Simulation experiments were performed to demonstrate that a practical implementation of the nonlinear controller would result in satisfactory outcomes. This is the first model that correlates lovastatin biosynthesis to carbon-nitrogen proportion and possesses a structure suitable for implementing a strategy for controlling lovastatin production.

A scaling method for modelling the crashworthiness of novel roadside barrier designs

In this paper, a novel method for modelling a scaled vehicle–barrier crash test similar to the 20◦ angled barrier test specified in EN 1317 is reported. The intended application is for proof-of-concept evaluation of novel roadside barrier designs, and as a cost-effective precursor to full-scale testing or detailed computational modelling. The method is based on the combination of the conservation of energy law and the equation of motion of a spring mass system representing the impact, and shows, for the first time, the feasibility of applying classical scaling theories to evaluation of roadside barrier design. The scaling method is used to set the initial velocity of the vehicle in the scaled test and to provide scaling factors to convert the measured vehicle accelerations in the scaled test to predicted full-scale accelerations. These values can then be used to calculate the Acceleration Severity Index score of the barrier for a full-scale test. The theoretical validity of the method is demonstrated by comparison to numerical simulations of scaled and full-scale angled barrier impacts using multibody analysis implemented in the crash simulation software MADYMO. Results show a maximum error of 0.3% ascribable to the scaling method.

OperationCheckpoint: SDN Application Control

One of the core properties of Software Defined Networking (SDN) is the ability for third parties to develop network applications. This introduces increased potential for innovation in networking from performance-enhanced to energy-efficient designs. In SDN, the application connects with the network via the SDN controller. A specific concern relating to this communication channel is whether an application can be trusted or not. For example, what information about the network state is gathered by the application? Is this information necessary for the application to execute or is it gathered for malicious intent? In this paper we present an approach to secure the northbound interface by introducing a permissions system that ensures that controller operations are available to trusted applications only. Implementation of this permissions system with our Operation Checkpoint adds negligible overhead and illustrates successful defense against unauthorized control function access attempts.

Clinical trial designs for rare diseases: Studies developed and discussed by the International Rare Cancers Initiative

BACKGROUND: The past three decades have seen rapid improvements in the diagnosis and treatment of most cancers and the most important contributor has been research. Progress in rare cancers has been slower, not least because of the challenges of undertaking research.

SETTINGS: The International Rare Cancers Initiative (IRCI) is a partnership which aims to stimulate and facilitate the development of international clinical trials for patients with rare cancers. It is focused on interventional--usually randomized--clinical trials with the clear goal of improving outcomes for patients. The key challenges are organisational and methodological. A multi-disciplinary workshop to review the methods used in ICRI portfolio trials was held in Amsterdam in September 2013. Other as-yet unrealised methods were also discussed.

RESULTS: The IRCI trials are each presented to exemplify possible approaches to designing credible trials in rare cancers. Researchers may consider these for use in future trials and understand the choices made for each design.

INTERPRETATION: Trials can be designed using a wide array of possibilities. There is no 'one size fits all' solution. In order to make progress in the rare diseases, decisions to change practice will have to be based on less direct evidence from clinical trials than in more common diseases.

A First Step Towards Cost Functions for Quantum-dot Cellular Automata Designs

Quantum-dot cellular automata (QCA) is potentially a very attractive alternative to CMOS for future digital designs. Circuit designs in QCA have been extensively studied. However, how to properly evaluate the QCA circuits has not been carefully considered. To date, metrics and area-delay cost functions directly mapped from CMOS technology have been used to compare QCA designs, which is inappropriate due to the differences between these two technologies. In this paper, several cost metrics specifically aimed at QCA circuits are studied. It is found that delay, the number of QCA logic gates, and the number and type of crossovers, are important metrics that should be considered when comparing QCA designs. A family of new cost functions for QCA circuits is proposed. As fundamental components in QCA computing arithmetic, QCA adders are reviewed and evaluated with the proposed cost functions. By taking the new cost metrics into account, previous best adders become unattractive and it has been shown that different optimization goals lead to different “best” adders.

Adaptive backstepping droop controller design for multi-terminal high-voltage direct current systems

Wind power is one of the most developed renewable energy resources worldwide. To integrate offshore wind farms to onshore grids, the high-voltage direct current (HVDC) transmission cables interfaced with voltage source converters (VSCs) are considered to be a better solution than conventional approaches. Proper DC voltage indicates successive power transfer. To connect more than one onshore grid, the DC voltage droop control is one of the most popular methods to share the control burden between different terminals. However, the challenges are that small droop gains will cause voltage deviations, while higher droop gain settings will cause large oscillations. This study aims to enhance the performance of the traditional droop controller by considering the DC cable dynamics. Based on the backstepping control concept, DC cables are modelled with a series of capacitors and inductors. The final droop control law is deduced step-by-step from the original remote side. At each step the control error from the previous step is considered. Simulation results show that both the voltage deviations and oscillations can be effectively reduced using the proposed method. Further, power sharing between different terminals can be effectively simplified such that it correlates linearly with the droop gains, thus enabling simple yet accurate system operation and control.

HpMC: An Energy- Aware Management System for Multi-Level Memory Architectures

DRAM technology faces density and power challenges to increase capacity because of limitations of physical cell design. To overcome these limitations, system designers are exploring alternative solutions that combine DRAM and emerging NVRAM technologies. Previous work on heterogeneous memories focuses, mainly, on two system designs: PCache, a hierarchical, inclusive memory system, and HRank, a flat, non-inclusive memory system. We demonstrate that neither of these designs can universally achieve high performance and energy efficiency across a suite of HPC workloads. In this work, we investigate the impact of a number of multilevel memory designs on the performance, power, and energy consumption of applications. To achieve this goal and overcome the limited number of available tools to study heterogeneous memories, we created HMsim, an infrastructure that enables n-level, heterogeneous memory studies by leveraging existing memory simulators. We, then, propose HpMC, a new memory controller design that combines the best aspects of existing management policies to improve performance and energy. Our energy-aware memory management system dynamically switches between PCache and HRank based on the temporal locality of applications. Our results show that HpMC reduces energy consumption from 13% to 45% compared to PCache and HRank, while providing the same bandwidth and higher capacity than a conventional DRAM system.