Self-dual supersymmetric nonlinear sigma models

In four-dimensional N=1 Minkowski superspace, general nonlinear sigma models with four-dimensional target spaces may be realised in term of CCL (chiral and complex linear) dynamical variables which consist of a chiral scalar, a complex linear scalar and their conjugate superfields. Here we introduce CCL sigma models that are invariant under U(1) "duality rotations" exchanging the dynamical variables and their equations of motion. The Lagrangians of such sigma models prove to obey a partial differential equation that is analogous to the self-duality equation obeyed by U(1) duality invariant models for nonlinear electrodynamics. These sigma models are self-dual under a Legendre transformation that simultaneously dualises (i) the chiral multiplet into a complex linear one; and (ii) the complex linear multiplet into a chiral one. Any CCL sigma model possesses a dual formulation given in terms of two chiral multiplets. The U(1) duality invariance of the CCL sigma model proves to be equivalent, in the dual chiral formulation, to a manifest U(1) invariance rotating the two chiral scalars. Since the target space has a holomorphic Killing vector, the sigma model possesses a third formulation realised in terms of a chiral multiplet and a tensor multiplet. The family of U(1) duality invariant CCL sigma models includes a subset of N=2 supersymmetric theories. Their target spaces are hyper Kahler manifolds with a non-zero Killing vector field. In the case that the Killing vector field is triholomorphic, the sigma model admits a dual formulation in terms of a self-interacting off-shell N=2 tensor multiplet. We also identify a subset of CCL sigma models which are in a one-to-one correspondence with the U(1) duality invariant models for nonlinear electrodynamics. The target space isometry group for these sigma models contains a subgroup U(1) x U(1).Comment: 22 page

Peripheral vs. Central Sex Steroid Hormones in Experimental Parkinson’s Disease

The nigrostriatal dopaminergic (NSDA) pathway degenerates in Parkinson’s disease (PD), which occurs with approximately twice the incidence in men than women. Studies of the influence of systemic estrogens in females suggest sex hormones contribute to these differences. In this review we analyze the evidence revealing great complexity in the response of the healthy and injured NSDA system to hormonal influences, and emphasize the importance of centrally generated estrogens. At physiological levels, circulating estrogen (in females) or estrogen precursors (testosterone in males, aromatized to estrogen centrally) have negligible effects on dopaminergic neuron survival in experimental PD, but can modify striatal dopamine levels via actions on the activity or adaptive responses of surviving cells. However, these effects are sexually dimorphic. In females, estradiol promotes adaptive responses in the partially injured NSDA pathway, preserving striatal dopamine, whereas in males gonadal steroids and exogenous estradiol have a negligible or even suppressive effect, effectively exacerbating dopamine loss. On balance, the different effects of gonadal factors in males and females contribute to sex differences in experimental PD. Fundamental sex differences in brain organization, including the sexually dimorphic networks regulating NSDA activity are likely to underpin these responses. In contrast, estrogen generated locally appears to preserve striatal dopamine in both sexes. The available data therefore highlight the need to understand the biological basis of sex-specific responses of the NSDA system to peripheral hormones, so as to realize the potential for sex-specific, hormone-based therapies in PD. Furthermore, they suggest that targeting central steroid generation could be equally effective in preserving striatal dopamine in both sexes. Clarification of the relative roles of peripheral and central sex steroid hormones is thus an important challenge for future studies

The role of circumstance monitoring on the diagnostic interpretation of condition monitoring data

Circumstance monitoring, a recently coined termed defines the collection of data reflecting the real network working environment of in-service equipment. This ideally complete data set should reflect the elements of the electrical, mechanical, thermal, chemical and environmental stress factors present on the network. This must be distinguished from condition monitoring, which is the collection of data reflecting the status of in-service equipment. This contribution investigates the significance of considering circumstance monitoring on diagnostic interpretation of condition monitoring data. Electrical treeing partial discharge activity from various harmonic polluted waveforms have been recorded and subjected to a series of machine learning techniques. The outcome provides a platform for improved interpretation of the harmonic influenced partial discharge patterns. The main conclusion of this exercise suggests that any diagnostic interpretation is dependent on the immunity of condition monitoring measurements to the stress factors influencing the operational conditions. This enables the asset manager to have an improved holistic view of an asset's health

Identifying harmonic attributes from online partial discharge data

Partial discharge (PD) monitoring is a key method of tracking fault progression and degradation of insulation systems. Recent research discovered that the harmonic regime experienced by the plant also affects the PD pattern, questioning the conclusions about equipment health drawn from PD data. This paper presents the design and creation of an online system for harmonic circumstance monitoring of distribution cables, using only PD data. Based on machine learning techniques, the system can assess the prevalence of the 5th and 7th harmonic orders over the monitoring period. This information is key for asset managers to draw correct conclusions about the remaining life of polymeric cable insulation, and prevent overestimation of the degradation trend

Interpretation of partial discharge activity in the presence of harmonics

Recent work has identified that circumstances of equipment operation can radically change condition monitoring data. This contribution investigates the significance of considering circumstance monitoring on the diagnostic interpretation of such condition monitoring data. Electrical treeing partial discharge data have been subjected to a data mining investigation, providing a platform for classification of harmonic influenced partial discharge patterns. The Total Harmonic Distortion (THD) index was varied to a maximum of 40%. The results show progressive development for interpretation of condition monitoring data, improving the asset manager's holistic view of an asset's health

Assessing the effects of power quality on partial discharge behaviour through machine learning

Partial discharge (PD) is commonly used as an indicator of insulation health in high voltage equipment, but research has indicated that power quality, particularly harmonics, can strongly influence the discharge behaviour and the corresponding pattern observed. Unacknowledged variation in harmonics of the excitation voltage waveform can influence the insulation's degradation, leading to possible misinterpretation of diagnostic data and erroneous estimates of the insulation's ageing state, thus resulting in inappropriate asset management decisions. This paper reports on a suite of classifiers for identifying pertinent harmonic attributes from PD data, and presents results of techniques for improving their accuracy. Aspects of PD field monitoring are used to design a practical system for on-line monitoring of voltage harmonics. This system yields a report on the harmonics experienced during the monitoring period

Biochemical changes in athletes during marathon and ultra-marathon races, with special reference to the incidence and prevention of hypoglycaemia

Fats and carbohydrates are the major fuels utilized during exercise and it has been suggested that carbohydrate depletion is the cause of exhaustion during prolonged exercise lasting more than two hours. However, there is some disagreement in the literature as to whether this exhaustion is due either to muscle glycogen depletion or to hypoglycaemia secondary to liver glycogen depletion. I therefore undertook three studies to determine the roles of hypoglycaemia in explaining fatigue in marathon and ultra-marathon runners

Astroglial Plasticity Is Implicated in Hippocampal Remodelling in Adult Rats Exposed to Antenatal Dexamethasone

The long-term effects of antenatal dexamethasone treatment on brain remodelling in 3-months old male Sprague-Dawley rats whose mothers had been treated with dexamethasone were investigated in the present study. Dorsal hippocampus, basolateral amygdala and nucleus accumbens volume, cell numbers and GFAP-immunoreactive astroglial cell morphology were analysed using stereology. Total brain volume as assessed by microCT was not affected by the treatment. The relative volume of the dorsal hippocampus (% of total brain volume) showed a moderate, by 8%, but significant reduction in dexamethasone-treated vs control animals. Dexamethasone had no effect on the total and GFAP-positive cell numbers in the hippocampal sub-regions, basolateral amygdala and nucleus accumbens. Morphological analysis indicated that numbers of astroglial primary processes were not affected in any of the hippocampal sub-regions analysed but significant reductions in the total primary process length were observed in CA1 by 32%, CA3 by 50% and DG by 25%. Mean primary process length values were also significantly decreased in CA1 by 25%, CA3 by 45% and DG by 25%. No significant astroglial morphological changes were found in basolateral amygdala and nucleus accumbens. We propose that the dexamethasone-dependent impoverishment of hippocampal astroglial morphology is the case of maladaptive glial plasticity induced prenatally