Kinematic dynamo in spherical Couette flow

We investigate numerically kinematic dynamos driven by flow of electrically conducting fluid in the shell between two concentric differentially rotating spheres, a configuration normally referred to as spherical Couette flow. We compare between axisymmetric (2D) and fully three dimensional flows, between low and high global rotation rates, between prograde and retrograde differential rotations, between weak and strong nonlinear inertial forces, between insulating and conducting boundaries, and between two aspect ratios. The main results are as follows. Azimuthally drifting Rossby waves arising from the destabilisation of the Stewartson shear layer are crucial to dynamo action. Differential rotation and helical Rossby waves combine to contribute to the spherical Couette dynamo. At a slow global rotation rate, the direction of differential rotation plays an important role in the dynamo because of different patterns of Rossby waves in prograde and retrograde flows. At a rapid global rotation rate, stronger flow supercriticality (namely the difference between the differential rotation rate of the flow and its critical value for the onset of nonaxisymmetric instability) facilitates the onset of dynamo action. A conducting magnetic boundary condition and a larger aspect ratio both favour dynamo action

Assessing the removal of organic micro-pollutants from anaerobic membrane bioreactor effluent by fertilizer-drawn forward osmosis

© 2017 Elsevier B.V. In this study, the behavior of organic micro-pollutants (OMPs) transport including membrane fouling was assessed in fertilizer-drawn forward osmosis (FDFO) during treatment of the anaerobic membrane bioreactor (AnMBR) effluent. The flux decline was negligible when the FO membrane was oriented with active layer facing feed solution (AL-FS) while severe flux decline was observed with active layer facing draw solution (AL-DS) with di-ammonium phosphate (DAP) fertilizer as DS due to struvite scaling inside the membrane support layer. DAP DS however exhibited the lowest OMPs forward flux or higher OMPs rejection rate compared to other two fertilizers (i.e., mono-ammonium phosphate (MAP) and KCl). MAP and KCl fertilizer DS had higher water fluxes that induced higher external concentration polarization (ECP) and enhanced OMPs flux through the FO membrane. Under the AL-DS mode of membrane orientation, OMPs transport was further increased with MAP and KCl as DS due to enhanced concentrative internal concentration polarization while with DAP the internal scaling enhanced mass transfer resistance thereby lowering OMPs flux. Physical or hydraulic cleaning could successfully recover water flux for FO membranes operated under the AL-FS mode but only partial flux recovery was observed for membranes operated under AL-DS mode because of internal scaling and fouling in the support layer. Osmotic backwashing could however significantly improve the cleaning efficiency

Microscopics of Extremal Kerr from Spinning M5 Branes

We show that the spinning magnetic one-brane in minimal five-dimensional supergravity admits a decoupling limit that interpolates smoothly between a self-dual null orbifold of AdS_3 \times S^2 and the near-horizon limit of the extremal Kerr black hole times a circle. We use this interpolating solution to understand the field theory dual to spinning M5 branes as a deformation of the Discrete Light Cone Quantized (DLCQ) Maldacena-Stominger-Witten (MSW) CFT. In particular, the conformal weights of the operators dual to the deformation around AdS_3 \times S^2 are calculated. We present pieces of evidence showing that a CFT dual to the four-dimensional extremal Kerr can be obtained from the deformed MSW CFT.Comment: 5 page

A new fault diagnosis and fault-tolerant control method for mechanical and aeronautical systems with neural estimators

A new method of fault detection and fault tolerant control is proposed in this paper for mechanical systems and aeronautical systems. The faults to be estimated and diagnosed are malfunctions occurred within the control loops of the systems, rather than some static faults, such as gearbox fault, component cracks, etc. In the proposed method two neural networks are used as on-line estimators, the fault will be accurately estimated when the estimators are adapted on-line with the post fault dynamic information. Furthermore, the estimated value of faults are used to compensate for the impact of the faults, so that the stability and performance of the system with the faults are maintained until the faulty components to be repaired. The sliding mode control is used to maintain system stability under the post fault dynamics. The control law and the neural network learning algorithms are derived using the Lyapunov method, so that the neural estimators are guaranteed to converge to the fault to be diagnosed, while the entire closed-loop system stability is guaranteed with all variables bounded. The main contribution of this paper to the knowledge in this field is that the proposed method cannot only diagnose and tolerant with constant fault, also diagnose and tolerant with the time-varying faults. This is very important because most faults occurred in industrial systems are time-varying in nature. A simulation example is used to demonstrate the design procedure and the effectiveness of the method. The simulation results are compared with two existing methods that can cope with constant faults only, and the superiority is demonstrated

The Incremental Cooperative Design of Preventive Healthcare Networks

This document is the Accepted Manuscript version of the following article: Soheil Davari, 'The incremental cooperative design of preventive healthcare networks', Annals of Operations Research, first published online 27 June 2017. Under embargo. Embargo end date: 27 June 2018. The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-017-2569-1.In the Preventive Healthcare Network Design Problem (PHNDP), one seeks to locate facilities in a way that the uptake of services is maximised given certain constraints such as congestion considerations. We introduce the incremental and cooperative version of the problem, IC-PHNDP for short, in which facilities are added incrementally to the network (one at a time), contributing to the service levels. We first develop a general non-linear model of this problem and then present a method to make it linear. As the problem is of a combinatorial nature, an efficient Variable Neighbourhood Search (VNS) algorithm is proposed to solve it. In order to gain insight into the problem, the computational studies were performed with randomly generated instances of different settings. Results clearly show that VNS performs well in solving IC-PHNDP with errors not more than 1.54%.Peer reviewe

Building resilience in contemporary nursing practice

YesThe nursing profession is being threatened by staff shortages. Catherine Best explains why building resilience from within the profession is vital to safeguarding its future, by keeping newly qualified nurses in the job and preventing emotional ‘burnout’ across disciplines Resilience in nursing has been critiqued and challenged throughout the nursing literature. Trends in nursing have led to many nurses leaving the profession early in their career, often due to the immense pressures that they work under. There are many opinions on how nurses can develop the resilience needed to maintain professional integrity and continue to provide safe and effective care, while attempting to shoulder the considerable impact of political and professional drivers. This not only leaves nurses exhausted but often without hope. By taking collective action, this article argues that nurses may benefit from sharing ideas and learning from others, and in so doing rekindle hope and a belief that things can change

Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring

Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)–mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia