Network interactions and performance of a multi-function IEC 61850 process bus

New substation technology, such as non-conventional instrument transformers,and a need to reduce design and construction costs, are driving the adoption of Ethernet based digital process bus networks for high voltage substations. Protection and control applications can share a process bus, making more efficient use of the network infrastructure. This paper classifies and defines performance requirements for the protocols used in a process bus on the basis of application. These include GOOSE, SNMP and IEC 61850-9-2 sampled values. A method, based on the Multiple Spanning Tree Protocol (MSTP) and virtual local area networks, is presented that separates management and monitoring traffic from the rest of the process bus. A quantitative investigation of the interaction between various protocols used in a process bus is described. These tests also validate the effectiveness of the MSTP based traffic segregation method. While this paper focusses on a substation automation network, the results are applicable to other real-time industrial networks that implement multiple protocols. High volume sampled value data and time-critical circuit breaker tripping commands do not interact on a full duplex switched Ethernet network, even under very high network load conditions. This enables an efficient digital network to replace a large number of conventional analog connections between control rooms and high voltage switchyards.

Executive function development and stress effects on driving performance : preliminary findings from a young adult sample.

This chapter presents a pilot study examining the interactive contributions of executive function development/impairment and psychosocial stress to young adults’ (17-30 years old) driving behaviour in a simulator city scenario.

A home-based progressive resistance exercise programme for patients with venous leg ulcers : a feasibility study

This study aimed to assess the feasibility of a home-based exercise program and examine the effects on the healing rates of venous leg ulcers. A 12 –week randomised controlled trial was conducted investigating the effects of an exercise intervention compared to a usual care group. Participants in both groups (n = 13) had active venous ulceration and were treated in a metropolitan hospital outpatients clinic in Australia. Data were collected on recruitment from medical records, clinical assessment and questionnaires. Follow-up data on progress in healing and treatments were collected fortnightly for 12 weeks. Calf muscle pump function data were collected at baseline and 12 weeks from recruitment. Range of ankle motion data were collected at baseline, 6 and 12 weeks from recruitment. This pilot study indicated that the intervention was feasible. Clinical significance was observed in the intervention group with a 32% greater decrease in ulcer size (p=0.34) than the control group, and a 10% (p=0.74) improvement in the number of participants healed in the intervention group compared to the control group. Significant differences between groups over time were observed in calf muscle pump function parameters; (ejection fraction [p = 0.05]; residual volume fraction [p = 0.04]) and range of ankle motion (p = 0.01). This pilot study is one of the first studies to examine and measure clinical healing rates for participants involved in a home-based progressive resistance exercise program. Further research is warranted with a larger multi-site study.

Why renal nurses cope so well with their workplace stressors

Background: Previous studies have found significant stressors experienced by nurses working in haemodialysis units yet renal nurses appear to report less burnout than other nurses. Objectives: This study aims to undertake an inductive process to better understand the stressors and the coping strategies used by renal nurses that may lead to resilience. Method: Sixteen haemodialysis nurses from a metropolitan Australian hospital and two satellite units participated in open-ended interviews. Data were analysed from a grounded theory methodology. Measures of burnout and resilience were also obtained. Results: Two major categories of stressors emerged. First, due to prolonged patient contact, family-like relationships developed that lead to the blurring of boundaries. Second, participants experienced discrimination from both patients and staff. Despite these stressors, the majority of participants reported low burnout and moderately high-to-high levels of resilience. The major coping strategy that appeared to promote resilience was emotional distancing, while emotional detachment appeared to promote burn-out. Conclusion: Assisting nurses to use emotional distancing, rather than emotional detachment strategies to engender a sense of personal achievement may promote resilience.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

On the probability density function of the product of Rayleigh distributed random variables

In this paper we investigate the distribution of the product of Rayleigh distributed random variables. Considering the Mellin-Barnes inversion formula and using the saddle point approach we obtain an upper bound for the product distribution. The accuracy of this tail-approximation increases as the number of random variables in the product increase.

Effect of cold water immersion after exercise in the heat on muscle function, body temperatures, and vessel diameter

Cold water immersion (CWI) is a popular recovery modality, but actual physiological responses to CWI after exercise in the heat have not been well documented. The purpose of this study was to examine effects of 20-min CWI (14 degrees C) on neuromuscular function, rectal (T(re)) and skin temperature (T(sk)), and femoral venous diameter after exercise in the heat. Ten well-trained male cyclists completed two bouts of exercise consisting of 90-min cycling at a constant power output (216+/-12W) followed by a 16.1km time trial (TT) in the heat (32 degrees C). Twenty-five minutes post-TT, participants were assigned to either CWI or control (CON) recovery conditions in a counterbalanced order. T(re) and T(sk) were recorded continuously, and maximal voluntary isometric contraction torque of the knee extensors (MVIC), MVIC with superimposed electrical stimulation (SMVIC), and femoral venous diameters were measured prior to exercise, 0, 45, and 90min post-TT. T(re) was significantly lower in CWI beginning 50min post-TT compared with CON, and T(sk) was significantly lower in CWI beginning 25min post-TT compared with CON. Decreases in MVIC, and SMVIC torque after the TT were significantly greater for CWI compared with CON; differences persisted 90min post-TT. Femoral vein diameter was approximately 9% smaller for CWI compared with CON at 45min post-TT. These results suggest that CWI decreases T(re), but has a negative effect on neuromuscular function.

Detecting Symbian OS malware through static function call analysis

Smartphones become very critical part of our lives as they offer advanced capabilities with PC-like functionalities. They are getting widely deployed while not only being used for classical voice-centric communication. New smartphone malwares keep emerging where most of them still target Symbian OS. In the case of Symbian OS, application signing seemed to be an appropriate measure for slowing down malware appearance. Unfortunately, latest examples showed that signing can be bypassed resulting in new malware outbreak. In this paper, we present a novel approach to static malware detection in resource-limited mobile environments. This approach can be used to extend currently used third-party application signing mechanisms for increasing malware detection capabilities. In our work, we extract function calls from binaries in order to apply our clustering mechanism, called centroid. This method is capable of detecting unknown malwares. Our results are promising where the employed mechanism might find application at distribution channels, like online application stores. Additionally, it seems suitable for directly being used on smartphones for (pre-)checking installed applications.

Extracorporeal lessons from sheep

Background: Extracorporeal circulation (ECC), the diversion of blood flow through a circuit located outside of the body, has been one of the major advances in modern medicine. Cardio-pulmonary bypass (CPB), renal dialysis, apheresis and extracorporeal membrane oxygenation (ECMO) are all different forms of ECC. Despite its major benefits, when blood comes into contact with foreign material, both the coagulation and inflammation cascades are activated simultaneously. Short periods of exposure to ECC e.g. CPB (�2 h duration), are known to be associated with haemolysis, coagulopathies, bleeding and inflammation which demand blood product support. Therefore, it is not unexpected that these complications would be exaggerated with prolonged periods of ECC such as in ECMO (days to weeks duration). The variability and complexities of the underlying pathologies of patients requiring ECC makes it difficult to study the cause and effect of these complications. To overcome this problem we developed an ovine (sheep) model of ECC. Method: Healthy female sheep (1–3 y.o.) weighing 40–50 kg were fasted overnight, anaesthetised, intubated and ventilated [1]. Half the group received smoke induced acute lung injury (S-ALI group) (n = 8) and the other half did not (healthy group) (n = 8). Sheep were subsequently cannulated (Medtronic Inc, Minneapolis, MN, USA) and veno-venous ECMO commenced using PLS ECMO circuit and Quadrox D oxygenator (Maquet Cardiopulmonary AG, Hechinger Straße, Germany). There was continuous physiological monitoring and blood was collected at specified time intervals for full blood counts, platelet function analysis (by Multiplate®), routine coagulation and assessment of clot formation and lysis (by ROTEM®). Preliminary results Full blood counts and routine coagulation results from normal healthy sheep were comparable to those of normal human adults. Within 15 min of initiating of ECMO, PT, PTT and EXTEM clot formation time increased, whilst EXTEM maximum clot firmness decreased in both cohorts. Discussion & Conclusions: Preliminary results of sheep from both 2 h ECMO cohorts showed that the anatomy, haematology and coagulation parameters of an adult sheep are comparable to that a human adult. Experiments are currently underway with healthy (n = 8) and S-ALI (n = 8) sheep on ECMO for 24 h. In addition to characterising how ECMO alters haematology and coagulation parameters, we hope that it will also define which blood components will be most effective to correct bleeding or clotting complications during ECMO support.

Assessment of neuroretinal function in a group of functional amblyopes with documented LGN deficits

Purpose In this study we examine neuroretinal function in five amblyopes, who had been shown in previous functional MRI (fMRI) studies to have compromised function of the lateral geniculate nucleus (LGN), to determine if the fMRI deficit in amblyopia may have its origin at the retinal level. Methods We used slow flash multifocal ERG (mfERG) and compared averaged five ring responses of the amblyopic and fellow eyes across a 35 deg field. Central responses were also assessed over a field which was about 6.3 deg in diameter. We measured central retinal thickness using optical coherence tomography. Central fields were measured using the MP1-Microperimeter which also assesses ocular fixation during perimetry. MfERG data were compared with fMRI results from a previous study. Results Amblyopic eyes had reduced response density amplitudes (first major negative to first positive (N1-P1) responses) for the central and paracentral retina (up to 18 deg diameter) but not for the mid-periphery (from 18 to 35 deg). Retinal thickness was within normal limits for all eyes, and not different between amblyopic and fellow eyes. Fixation was maintained within the central 4° more than 80% of the time by four of the five participants; fixation assessed using bivariate contour ellipse areas (BCEA) gave rankings similar to those of the MP-1 system. There was no significant relationship between BCEA and mfERG response for either amblyopic or fellow eye. There was no significant relationship between the central mfERG eye response difference and the selective blood oxygen level dependent (BOLD) LGN eye response difference previously seen in these participants. Conclusions Retinal responses in amblyopes can be reduced within the central field without an obvious anatomical basis. Additionally, this retinal deficit may not be the reason why the LGN BOLD (blood oxygen level dependent) responses are reduced for amblyopic eye stimulation.

The relationship between CFH and ARMS2 genotypes and neuroretinal function in persons without age-related macular degeneration

Purpose: To determine whether neuroretinal function differs in healthy persons with and without common risk gene variants for age- related macular degeneration (AMD) and no ophthalmoscopic signs of AMD, and to compare those findings in persons with manifest early AMD. Methods and Participants: Neuroretinal function was assessed with the multifocal electroretinogram (mfERG) (VERIS, Redwood City, CA,) in 32 participants (22 healthy persons with no clinical signs of AMD and 10 early AMD patients). The 22 healthy participants with no AMD were risk genotypes for either the CFH (rs380390) and/or ARMS2 (rs10490920). We used a slow flash mfERG paradigm (3 inserted frames) and a 103 hexagon stimulus array. Recordings were made with DTL electrodes; fixation and eye movements were monitored online. Trough N1 to peak P1 (N1P1) response densities and P1-implicit times (IT) were analysed in 5 concentric rings. Results: N1P1 response densities (mean ± SD) for concentric rings 1-3 were on average significantly higher in at-risk genotypes (ring 1: 17.97 nV/deg2 ± 1.9, ring 2: 11.7 nV/deg2 ±1.3, ring 3: 8.7 nV/deg2 ± 0.7) compared to those without risk (ring 1: 13.7 nV/deg2 ± 1.9, ring 2: 9.2 nV/deg2 ±0.8, ring 3: 7.3 nV/deg2 ± 1.1) and compared to persons with early AMD (ring 1: 15.3 nV/deg2 ± 4.8, ring 2: 9.1 nV/deg2 ±2.3, ring 3 nV/deg2: 7.3± 1.3) (p<0.5). The group implicit times, P1-ITs for ring 1 were on average delayed in the early AMD patients (36.4 ms ± 1.0) compared to healthy participants with (35.1 ms ± 1.1) or without risk genotypes (34.8 ms ±1.3), although these differences were not significant. Conclusion: Neuroretinal function in persons with normal fundi can be differentiated into subgroups based on their genetics. Increased neuroretinal activity in persons who carry AMD risk genotypes may be due to genetically determined subclinical inflammatory and/or histological changes in the retina. Assessment of neuroretinal function in healthy persons genetically susceptible to AMD may be a useful early biomarker before there is clinical manifestation of AMD.

In situ SANS study of the surface and pore filling adsorption of subcritical and supercritical CO2 in porous silica as a function of pore size

We applied small-angle neutron scattering (SANS) and ultra small-angle neutron scattering (USANS) to monitor evolution of the CO2 adsorption in porous silica as a function of CO2 pressure and temperature in pores of different sizes. The range of pressures (0 < P < 345 bar) and temperatures (T=18 OC, 35 OC and 60 OC) corresponded to subcritical, near critical and supercritical conditions of bulk fluid. We observed that the adsorption behavior of CO2 is fundamentally different in large and small pores with the sizes D > 100 Å and D < 30 Å, respectively. Scattering data from large pores indicate formation of a dense adsorbed film of CO2 on pore walls with the liquid-like density (ρCO2)ads≈0.8 g/cm3. The adsorbed film coexists with unadsorbed fluid in the inner pore volume. The density of unadsorbed fluid in large pores is temperature and pressure dependent: it is initially lower than (ρCO2)ads and gradually approaches it with pressure. In small pores compressed CO2 gas completely fills the pore volume. At the lowest pressures of the order of 10 bar and T=18 OC, the fluid density in smallest pores available in the matrix with D ~ 10 Å exceeds bulk fluid density by a factor of ~ 8. As pressure increases, progressively larger pores become filled with the condensed CO2. Fluid densification is only observed in pores with sizes less than ~ 25 – 30 Å. As the density of the invading fluid reaches (ρCO2)bulk~ 0.8 g/cm3, pores of all sizes become uniformly filled with CO2 and the confinement effects disappear. At higher densities the fluid in small pores appears to follow the equation of state of bulk CO2 although there is an indication that the fluid density in the inner volume of large pores may exceed the density of the adsorbed layer. The equivalent internal pressure (Pint) in the smallest pores exceeds the external pressure (Pext) by a factor of ~ 5 for both sub- and supercritical CO2. Pint gradually approaches Pext as D → 25 – 30 Å and is independent of temperature in the studied range of 18 OC ≤ T ≤ 60 OC. The obtained results demonstrate certain similarity as well as differences between adsorption of subcritical and supercritical CO2 in disordered porous silica. High pressure small angle scattering experiments open new opportunities for in situ studies of the fluid adsorption in porous media of interest to CO2 sequestration, energy storage, and heterogeneous catalysis.

Prediction of age at menopause from assessment of ovarian reserve may be improved by using body mass index and smoking status

Objective: Menopause is the consequence of exhaustion of the ovarian follicular pool. AMH, an indirect hormonal marker of ovarian reserve, has been recently proposed as a predictor for age at menopause. Since BMI and smoking status are relevant independent factors associated with age at menopause we evaluated whether a model including all three of these variables could improve AMH-based prediction of age at menopause. Methods: In the present cohort study, participants were 375 eumenorrheic women aged 19–44 years and a sample of 2,635 Italian menopausal women. AMH values were obtained from the eumenorrheic women. Results: Regression analysis of the AMH data showed that a quadratic function of age provided a good description of these data plotted on a logarithmic scale, with a distribution of residual deviates that was not normal but showed significant leftskewness. Under the hypothesis that menopause can be predicted by AMH dropping below a critical threshold, a model predicting menopausal age was constructed from the AMH regression model and applied to the data on menopause. With the AMH threshold dependent on the covariates BMI and smoking status, the effects of these covariates were shown to be highly significant. Conclusions: In the present study we confirmed the good level of conformity between the distributions of observed and AMH-predicted ages at menopause, and showed that using BMI and smoking status as additional variables improves AMH-based prediction of age at menopause.

The impact of legislation on divorce : a hazard function approach

The paper examines the impact of the introduction of no-fault divorce legislation in Australia. The approach used is rather novel, a hazard model of the divorce rate is estimated with the role of legislation captured via a time-varying covariate. The paper concludes that contrary to US empirical evidence, no-fault divorce legislation appears to have had a positive impact upon the divorce rate in Australia.

Towards a Dynamic IS Function

With the growing importance of IS for organizations and the continuous stream of new IT developments, the IS function in organizations becomes more critical but is also more challenged. For example, how should the IS function deal with the consumerization of IT or what is the added value of the IS function when it comes to SaaS and the Cloud? In this paper we argue that IS research is in need of a dynamic perspective on the IS function. The IS function has to become more focused on building and adapting IS capabilities in a changing environment. We discuss that there has been an overreliance on the Resource Based View so far for understanding the IS function and capabilities and introduce Dynamic Capabilities Theory as an additional theoretical perspective, which has only been limitedly addressed in IS literature yet. We present a first conceptualization of the dynamic IS function and discuss IS capabilities frameworks and individual IS capabilities from a dynamic perspective. These initial insights demonstrate the contribution of a dynamic perspective on the IS function itself.