Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods

In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.

Corporate-cooperative management of fisheries: A potential alternative governance structure for low value small fisheries?

While the economic and environmental benefits of fisheries management are well accepted, the costs of effective management in low value fisheries, including the research necessary to underpin such management, may be considerable relative to the total economic benefits they may generate. Co-management is often seen as a panacea in low value fisheries. Increasing fisher participation increases legitimacy of management decision in the absence of detailed scientific input. However, where only a small number of operators exist, the potential benefits of co-management are negated by the high transaction cost to the individual fishers engaging in the management process. From an economic perspective, sole ownership has been identified as the management structure which can best achieve biological and economic sustainability. Moving low value fisheries with a small number of participants to a corporate-cooperative management model may come close to achieving these sole ownership benefits, with lower transaction costs. In this paper we look at the applicability of different management models with industry involvement to low value fisheries with a small number of participants. We provide an illustration as to how a fishery could be transitioned to a corporate-cooperative management model that captures the key benefits of sole management at a low cost and is consistent with societal objectives.

Unlocking the learning potential of incarcerated Indigenous and low SES young people; Mathematics outcomes for future success: a discussion paper

This presentation provides a beginning discussion about what the literature reports about incarcerated young people. Incarcerated Indigenous and low SES young people typically have very low literacy and mathematics skills which precludes them from future education and or employment opportunities, thus continuing the cycle of disadvantage, exclusion and despair(Payne, 2007). Being locked out of learning, they are stuck in a cycle of underachievement, a scenario which contributes to unacceptably high levels of recidivism(ACER, 2014). Success at education is considered an important protective factor against delinquent behaviours such as offending, substance abuse and truancy. Youth education and training centres provide educational opportunities for the incarcerated Indigenous youth but achievement continues to be lower than expected, particularly in mathematics. This presentation provides an introductory literature review focusing on incarcerated young people and education. It is also the preliminary writing for a small pilot project currently being conducted in one Youth Education and Training Centre in Australia.

Voltage balance improvement in urban low voltage distribution networks

This project is a step forward in developing effective methods to mitigate voltage unbalance in urban residential networks. The method is proposed to reduce energy losses and improve quality of service in strongly unbalanced low-voltage networks. The method is based on phase swapping as well as optimal placement and sizing of Distribution Static Synchronous Compensator (D-STATCOM) using a Particle Swarm Optimisation method.

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.

Enhanced cortisol suppression following administration of low-dose dexamethasone in first-episode psychosis patients

OBJECTIVE Impaired regulation of the hypothalamic-pituitary-adrenal (HPA) axis and hyper-activity of this system have been described in patients with psychosis. Conversely, some psychiatric disorders such as post-traumatic stress disorder (PTSD) are characterised by HPA hypo-activity, which could be related to prior exposure to trauma. This study examined the cortisol response to the administration of low-dose dexamethasone in first-episode psychosis (FEP) patients and its relationship to childhood trauma. METHOD The low-dose (0.25 mg) Dexamethasone Suppression Test (DST) was performed in 21 neuroleptic-naive or minimally treated FEP patients and 20 healthy control participants. Childhood traumatic events were assessed in all participants using the Childhood Trauma Questionnaire (CTQ) and psychiatric symptoms were assessed in patients using standard rating scales. RESULTS FEP patients reported significantly higher rates of childhood trauma compared to controls (p = 0.001) and exhibited lower basal (a.m.) cortisol (p = 0.04) and an increased rate of cortisol hyper-suppression following dexamethasone administration compared to controls (33% (7/21) vs 5% (1/20), respectively; p = 0.04). There were no significant group differences in mean cortisol decline or percent cortisol suppression following the 0.25 mg DST. This study shows for the first time that a subset of patients experiencing their first episode of psychosis display enhanced cortisol suppression. CONCLUSIONS These findings suggest there may be distinct profiles of HPA axis dysfunction in psychosis which should be further explored.

A low-cost attack on branch-based software watermarking schemes

In 2005, Ginger Myles and Hongxia Jin proposed a software watermarking scheme based on converting jump instructions or unconditional branch statements (UBSs) by calls to a fingerprint branch function (FBF) that computes the correct target address of the UBS as a function of the generated fingerprint and integrity check. If the program is tampered with, the fingerprint and integrity checks change and the target address will not be computed correctly. In this paper, we present an attack based on tracking stack pointer modifications to break the scheme and provide implementation details. The key element of the attack is to remove the fingerprint and integrity check generating code from the program after disassociating the target address from the fingerprint and integrity value. Using the debugging tools that give vast control to the attacker to track stack pointer operations, we perform both subtractive and watermark replacement attacks. The major steps in the attack are automated resulting in a fast and low-cost attack.

Skilling up for a low-carbon future: Vocational education and training

Given the need for both short and long-term training for sustainability discussed in the first of this three-part series (ECOS 158, pp 22–24), it is clear that the vocational education and training sector will play a major role in building capacity for our nation over the next five years.

Skilling up for a low carbon future

A lack of appropriate skills and qualifications in the professions over the next decade may see Australian businesses forego significant opportunities in the global shift to sustainable development. What is the extent of the broader capacity building challenge facing our education sector, and how quickly will we need to respond?

Ability to discriminate between healthy and low back pain sufferers using ultrasound during maximum lumbar extension

Objective To analyze the ability to discriminate between healthy individuals and individuals with chronic nonspecific low back pain (CNLBP) by measuring the relation between patient-reported outcomes and objective clinical outcome measures of the erector spinae (ES) muscles using an ultrasound during maximal isometric lumbar extension. Design Cross-sectional study with screening and diagnostic tests with no blinded comparison. Setting University laboratory. Participants Healthy individuals (n=33) and individuals with CNLBP (n=33). Interventions Each subject performed an isometric lumbar extension. With the variables measured, a discriminate analysis was performed using a value ≥6 in the Roland and Morris disability questionnaire (RMDQ) as the grouping variable. Then, a logistic regression with the functional and architectural variables was performed. A new index was obtained from each subject value input in the discriminate multivariate analysis. Main Outcome Measures Morphologic muscle variables of the ES muscle were measured through ultrasound images. The reliability of the measures was calculated through intraclass correlation coefficients (ICCs). The relation between patient-reported outcomes and objective clinical outcome measures was analyzed using a discriminate function from standardized values of the variables and an analysis of the reliability of the ultrasound measurement. Results The reliability tests show an ICC value >.95 for morphologic and functional variables. The independent variables included in the analysis explained 42% (P=.003) of the dependent variable variance. Conclusions The relation between objective variables (electromyography, thickness, pennation angle) and a subjective variable (RMDQ ≥6) and the capacity of this relation to identify CNLBP within a group of healthy subjects is moderate. These results should be considered by clinicians when treating this type of patient in clinical practice.

High-temperature, low-H₂O silicic magmas of the Yellowstone Hotspot: an experimental study of Rhyolite from the Bruneau-Jarbidge eruptive center, Central Snake River Plain, USA

The phase relations have been investigated experimentally at 200 and 500 MPa as a function of water activity for one of the least evolved (Indian Batt Rhyolite) and of a more evolved rhyolite composition (Cougar Point Tuff XV) from the 12·8-8·1 Ma Bruneau-Jarbidge eruptive center of the Yellowstone hotspot. Particular priority was given to accurate determination of the water content of the quenched glasses using infrared spectroscopic techniques. Comparison of the composition of natural and experimentally synthesized phases confirms that high temperatures (>900°C) and extremely low melt water contents (<1·5 wt % H₂O) are required to reproduce the natural mineral assemblages. In melts containing 0·5-1·5 wt % H₂O, the liquidus phase is clinopyroxene (excluding Fe-Ti oxides, which are strongly dependent on fO₂), and the liquidus temperature of the more evolved Cougar Point Tuff sample (BJR; 940-1000°C) is at least 30°C lower than that of the Indian Batt Rhyolite lava sample (IBR2; 970-1030°C). For the composition BJR, the comparison of the compositions of the natural and experimental glasses indicates a pre-eruptive temperature of at least 900°C. The composition of clinopyroxene and pigeonite pairs can be reproduced only for water contents below 1·5 wt % H₂O at 900°C, or lower water contents if the temperature is higher. For the composition IBR2, a minimum temperature of 920°C is necessary to reproduce the main phases at 200 and 500 MPa. At 200 MPa, the pre-eruptive water content of the melt is constrained in the range 0·7-1·3 wt % at 950°C and 0·3-1·0 wt % at 1000°C. At 500 MPa, the pre-eruptive temperatures are slightly higher (by 30-50°C) for the same ranges of water concentration. The experimental results are used to explore possible proxies to constrain the depth of magma storage. The crystallization sequence of tectosilicates is strongly dependent on pressure between 200 and 500 MPa. In addition, the normative Qtz-Ab-Or contents of glasses quenched from melts coexisting with quartz, sanidine and plagioclase depend on pressure and melt water content, assuming that the normative Qtz and Ab/Or content of such melts is mainly dependent on pressure and water activity, respectively. The combination of results from the phase equilibria and from the composition of glasses indicates that the depth of magma storage for the IBR2 and BJR compositions may be in the range 300-400 MPa (13 km) and 200-300 MPa (10 km), respectively.

Low voltage EPMA: Experiments on a new frontier in microanalysis—analytical spatial resolution

Field emission (FE) electron gun sources provide new capabilities for high lateral resolution EPMA. The determination of analytical lateral resolution is not as straightforward as that for electron microscopy imaging. Results from two sets of experiments to determine the actual lateral resolution for accurate EPMA are presented for Kα X-ray lines of Si and Al and Lα of Fe at 5 and 7 keV in a silicate glass. These results are compared to theoretical predictions and Monte Carlo simulations of analytical lateral resolution. The experiments suggest little is gained in lateral resolution by dropping from 7 to 5 keV in EPMA of this silicate glass.

Low δ18O zircons from the Bruneau-­Jarbidge eruptive center: A key to crustal anatexis along the track of the Yellowstone hotspot

The Bruneau-Jarbidge eruptive center (BJEC) in the central Snake River Plain, Idaho, USA consists of the Cougar Point Tuff (CPT), a series of ten, high-temperature (900-1000°C) voluminous ignimbrites produced over the explosive phase of volcanism (12.8-10.5 Ma) and more than a dozen equally high-temperature rhyolite lava flows produced during the effusive phase (10.5-8 Ma). Spot analyses by ion microprobe of oxygen isotope ratios in 210 zircons demonstrate that all of the eruptive units of the BJEC are characterized by zircon δ¹⁸O values ≤ 2.5‰, thus documenting the largest low δ¹⁸O silicic volcanic province known on Earth (>10⁴ km³). There is no evidence for voluminous normal δ¹⁸O magmatism at the BJEC that precedes generation of low δ¹⁸O magmas as there is at other volcanic centers that generate low δ¹⁸O magmas such as Heise and Yellowstone. At these younger volcanic centers of the hotspot track, such low δ¹⁸O magmas represent ~45 % and ~20% respectively of total eruptive volumes. Zircons in all BJEC tuffs and lavas studied (23 units) document strong δ¹⁸O depletion (median CPT δ¹⁸OZrc = 1.0‰, post-CPT lavas = 1.5‰) with the third member of the CPT recording an excursion to minimum δ¹⁸O values (δ¹⁸OZrc= -1.8‰) in a supereruption > 2‰ lower than other voluminous low δ¹⁸O rhyolites known worldwide (δ¹⁸OWR ≤0.9 vs. 3.4‰). Subsequent units of the CPT and lavas record a progressive recovery in δ¹⁸OZrc to ~2.5‰ over a ~ 4 m.y. interval (12 to 8 Ma). We present detailed evidence of unit-to-unit systematic patterns in O isotopic zoning in zircons (i.e. direction and magnitude of Δcore-rim), spectrum of δ¹⁸O in individual units, and zircon inheritance patterns established by re-analysis of spots for U-Th-Pb isotopes by LA-ICPMS and SHRIMP. In conjunction with mineral thermometry and magma compositions, these patterns are difficult to reconcile with the well-established model for "cannibalistic" low δ¹⁸O magma genesis at Heise and Yellowstone. We present an alternative model for the central Snake River Plain using the modeling results of Leeman et al. (2008) for ¹⁸O depletion as a function of depth in a mid-upper crustal protolith that was hydrothermally altered by infiltrating meteoric waters prior to the onset of silicic magmatism. The model proposes that BJEC silicic magmas were generated in response to the propagation of a melting front, driven by the incremental growth of a vast underlying mafic sill complex, over a ~5 m.y. interval through a crustal volume in which a vertically asymmetric δ¹⁸OWR gradient had previously developed that was sharply inflected from ~ -1 to 10‰ at mid-upper crustal depths. Within the context of the model, data from BJEC zircons are consistent with incremental melting and mixing events in roof zones of magma reservoirs that accompany surfaceward advance of the coupled mafic-silicic magmatic system.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.