Balls to the wall: How acoustic information from a ball in motion guides interceptive movement in people with Parkinson’s disease

Previous research has shown that Parkinson's disease (PD) patients can increase the speed of their movement when catching a moving ball compared to when reaching for a static ball (Majsak et al., 1998). A recent model proposed by Redgrave et al. (2010) explains this phenomenon with regard to the dichotomic organization of motor loops in the basal ganglia circuitry and the role of sensory micro-circuitries in the control of goal-directed actions. According to this model, external visual information that is relevant to the required movement can induce a switch from a habitual control of movement toward an externally-paced, goal-directed form of guidance, resulting in augmented motor performance (Bienkiewicz et al., 2013). In the current study, we investigated whether continuous acoustic information generated by an object in motion can enhance motor performance in an arm reaching task in a similar way to that observed in the studies of Majsak et al. (1998, 2008). In addition, we explored whether the kinematic aspects of the movement are regulated in accordance with time to arrival information generated by the ball's motion as it reaches the catching zone. A group of 7 idiopathic PD (6 male, 1 female) patients performed a ball-catching task where the acceleration (and hence ball velocity) was manipulated by adjusting the angle of the ramp. The type of sensory information (visual and/or auditory) specifying the ball's arrival at the catching zone was also manipulated. Our results showed that patients with PD demonstrate improved motor performance when reaching for a ball in motion, compared to when stationary. We observed how PD patients can adjust their movement kinematics in accordance with the speed of a moving target, even if vision of the target is occluded and patients have to rely solely on auditory information. We demonstrate that the availability of dynamic temporal information is crucial for eliciting motor improvements in PD. Furthermore, these effects appear independent from the sensory modality through-which the information is conveyed. 

Rapid quantification of microRNAs in plasma using a fast real time PCR system

The ability to rapidly detect circulating small RNAs, in particular microRNAs (miRNAs), would further increase their already established potential as biomarkers in a range of conditions. One rate-limiting factor is the time taken to perform quantitative real time PCR amplification. We therefore evaluated the ability of a novel thermal cycler to perform this step in less than 10 minutes. Quantitative PCR was performed on an xxpress® thermal cycler (BJS Biotechnologies, Perivale, UK), which employs a resistive heating system and forced air cooling to achieve thermal ramp rates of 10 °C/s, and a conventional peltier-controlled LightCycler 480 system (Roche, Basel, Switzerland) ramping at 4.8 °C/s. The threshold cycle (Ct) for detection of 18S rDNA from a standard genomic DNA sample was significantly more variable across the block (F-test, p=2.4x10-25) for the xxpress (20.01±0.47SD) than the LightCycler (19.87±0.04SD). RNA was extracted from human plasma, reverse transcribed and a panel of miRNAs amplified and detected using SYBR green (Kapa Biosystems, Wilmington, Ma, USA). The sensitivity of both systems was broadly comparable and both detected a panel of miRNAs reliably and indicated similar relative abundances. The xxpress thermal cycler facilitates rapid qPCR detection of small RNAs and brings point-of care diagnostics based upon circulating miRNAs a step closer to reality.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

A hybrid harmony search with arithmetic crossover operation for economic dispatch

Economic dispatch (ED) problems often exhibit non-linear, non-convex characteristics due to the valve point effects. Further, various constraints and factors, such as prohibited operation zones, ramp rate limits and security constraints imposed by the generating units, and power loss in transmission make it even more challenging to obtain the global optimum using conventional mathematical methods. Meta-heuristic approaches are capable of solving non-linear, non-continuous and non-convex problems effectively as they impose no requirements on the optimization problems. However, most methods reported so far mainly focus on a specific type of ED problems, such as static or dynamic ED problems. This paper proposes a hybrid harmony search with arithmetic crossover operation, namely ACHS, for solving five different types of ED problems, including static ED with valve point effects, ED with prohibited operating zones, ED considering multiple fuel cells, combined heat and power ED, and dynamic ED. In this proposed ACHS, the global best information and arithmetic crossover are used to update the newly generated solution and speed up the convergence, which contributes to the algorithm exploitation capability. To balance the exploitation and exploration capabilities, the opposition based learning (OBL) strategy is employed to enhance the diversity of solutions. Further, four commonly used crossover operators are also investigated, and the arithmetic crossover shows its efficiency than the others when they are incorporated into HS. To make a comprehensive study on its scalability, ACHS is first tested on a group of benchmark functions with a 100 dimensions and compared with several state-of-the-art methods. Then it is used to solve seven different ED cases and compared with the results reported in literatures. All the results confirm the superiority of the ACHS for different optimization problems.

An efficient harmony search with new pitch adjustment for dynamic economic dispatch

A simple yet efficient harmony search (HS) method with a new pitch adjustment rule (NPAHS) is proposed for dynamic economic dispatch (DED) of electrical power systems, a large-scale non-linear real time optimization problem imposed by a number of complex constraints. The new pitch adjustment rule is based on the perturbation information and the mean value of the harmony memory, which is simple to implement and helps to enhance solution quality and convergence speed. A new constraint handling technique is also developed to effectively handle various constraints in the DED problem, and the violation of ramp rate limits between the first and last scheduling intervals that is often ignored by existing approaches for DED problems is effectively eliminated. To validate the effectiveness, the NPAHS is first tested on 10 popular benchmark functions with 100 dimensions, in comparison with four HS variants and five state-of-the-art evolutionary algorithms. Then, NPAHS is used to solve three 24-h DED systems with 5, 15 and 54 units, which consider the valve point effects, transmission loss, emission and prohibited operating zones. Simulation results on all these systems show the scalability and superiority of the proposed NPAHS on various large scale problems.

Influence of testing on permeability of compacted fine soils

The British standard constant-head triaxial test for measuring the permeability of fine-grained soils takes a relatively long time. A quicker test could provide savings to the construction industry, particularly for checking the quality of landfill clay liners. An accelerated permeability test has been developed, but the method often underestimates the permeability values compared owing to structural changes in the soil sample. This paper reports on an investigation
into the accelerated test to discover if the changes can be limited by using a revised procedure. The accelerated test is assessed and compared with the standard test and a ramp-accelerated permeability test. Four different finegrained materials are compacted at various water contents to produce analogous samples for testing using the three different methods. Fabric analysis is carried out on specimens derived from post-test samples using mercury intrusion porosimetry and scanning electron microscopy to assess the effects of testing on soil structure. The results show that accelerated testing in general underestimates permeability compared with values derived from the standard test, owing to changes in soil structure caused by testing. The ramp-accelerated test is shown to provide an improvement in terms of these structural changes.

A tool for the evaluation of slaughter horse welfare during unloading

This study aimed to develop a scientific and practical tool to be used to assess horse welfare after commercial transport over long journeys. A set of physical, behavioural and environmental measures was selected, covering welfare aspects of both transport and unloading procedures. The protocol was field-tested on 51 intra-EU commercial transports arriving at different sites in Italy. Univariate analysis was implemented to look for associations between the input variables (environmental hazards potentially affecting the animal well-being during long transports) and the outcome variables (direct evaluation of the animal condition). No severe welfare impairments were recorded (ie dead on arrival, severe injuries, non-ambulatory animals), while milder ones were more frequent at unloading (eg slipping; 36.7%, reluctance to move; 9.6%). Correlations emerged between ramp slope and falling; type of ramp floor and slipping; fast gait and the presence of gaps between the ramp and the floor. The horses' behaviour was also related to the type of handling procedure used. The measures were repeatable and practical to apply and score during real-time unloading. This work provides a sound basis for a new and practical welfare assessment tool for horses travelling over long journeys. Careful and constant application of this protocol would provide stakeholders with the opportunity to track and monitor changes in the industry over time, as well as to identify high risk areas in transport routines.

Work Fluctuations in Bosonic Josephson Junctions

We calculate the first two moments and full probability distribution of the work performed on a system of bosonic particles in a two-mode Bose-Hubbard Hamiltonian when the self-interaction term is varied instantaneously or with a finite-time ramp. In the instantaneous case, we show how the irreversible work scales differently depending on whether the system is driven to the Josephson or Fock regime of the bosonic Josephson junction. In the finite-time case, we use optimal control techniques to substantially decrease the irreversible work to negligible values. Our analysis can be implemented in present-day experiments with ultracold atoms and we show how to relate the work statistics to that of the population imbalance of the two modes.

Early warning systems for cyber defence

Cybercriminals ramp up their efforts with sophisticated techniques while defenders gradually update their typical security measures. Attackers often have a long-term interest in their targets. Due to a number of factors such as scale, architecture and nonproductive traffic however it makes difficult to detect them using typical intrusion detection techniques. Cyber early warning systems (CEWS) aim at alerting such attempts in their nascent stages using preliminary indicators. Design and implementation of such systems involves numerous research challenges such as generic set of indicators, intelligence gathering, uncertainty reasoning and information fusion. This paper discusses such challenges and presents the reader with compelling motivation. A carefully deployed empirical analysis using a real world attack scenario and a real network traffic capture is also presented.