Currency attack/defense with two-sided private information

A currency attack fails on its own when the speculator suffers from her financial problem. This paper extends the existing models and argues that the monetary authority?s willingness to peg and the speculator?s cost of attack are private information. Our model thus accounts for the duration of currency attack/defense, and more importantly, allows for failed attack. We employ an asymmetric war of attrition and gauge the time when the speculator stops attacking, or when the monetary authority de-pegs. Comparative static results throw light on the interest rate policy amidst the Exchange Rate Mechanism Crisis and the Asian Currency CrisisAsymmetric war of attrition; Credibility of policymakers; Failed speculative attack; Persistent effect; Two-sided private information

An evaluation of cement manufacture options for sustainable infrastructure

Sustainable production and use of cement, including limiting additional environmental protection costs, efficiently producing cement and minimising natural resources used, are significant global industrial objectives. One of the major challenges facing the cement manufacturing industry is that ordinary Portland cement production emits approximately 5% of the world’s carbon dioxide, and each kilogram of Portland cement produces 0.85 kg of carbon dioxide. High energy levels are also needed to produce cement, which requires heavy carbon dioxide emissions and accelerates the consumption of natural resources, which in turn affects climate change. One solution is to mix a certain amount of supplementary cementitious materials within ordinary Portland cement production. This outcome alleviates energy intensive production, reduces carbon dioxide emissions and slows natural resource consumption as well as decreasing production facility investment. Geopolymer based cement manufacturing is an alternative solution to improving this situation, as there is no carbonate content in the raw materials and less energy is required for production, which minimises carbon dioxide emission. Therefore, this is another method used to reduce the carbon footprint. In addition, fly ash is a by product of coal fired power stations and is now one of the major raw materials used to make fly ash based geopolymer cement, which slows abiotic depletion. The goal of this research is to optimise the three areas of maximising profit in manufacturing cement, minimising natural resources depletion and reducing carbon dioxide emissions in the manufacturing process. Selecting the right tools to measure these factors was achieved by using the proposed advanced framework, which integrated tools such as linear programming with the simplex method, and used traditional mathematical and spreadsheet based methods to seek optimal results. Six scenario based studies covered ordinary Portland cement; ordinary Portland cement with supplementary cementitious materials and fly ash based geopolymer cement in production under the same manufacturing conditions and the same boundaries in terms of the manufacturing process, seeking optimal solutions by using the linear programming equation method: Scenario 1 maximised the profit of mixed production ordinary Portland cement and ordinary Portland cement with supplementary cementitious materials. Scenario 2 maximised the profit of mixed production geopolymer based cement, including fly ash based and metakaolin based geopolymer cement. Scenario 3 maximised the profit of fly ash based geopolymer and ordinary Portland cement. Scenario 4 minimised carbon dioxide emissions from transport using the Carbon Dioxide Equivalent method. Scenario 5 minimised carbon dioxide emissions from transport using the Australian National Greenhouse Accounts Factors method (2014 to 2016). Scenario 6 made optimal use of raw materials for cement using abiotic depletion for ordinary Portland cement production. Further, the linear programming equations consisted of ‘subject to function’ and ‘subject to constraints’, which played the vital roles in the scenario based studies. The sources of developing the ‘subject to function’ equations are found in Chapter 3 Methodology. For example, the Australian National Greenhouse Accounts Factors method (2014 to 2016) and the Carbon Dioxide Equivalent method acted as ‘subject to function’ to minimise carbon dioxide emissions from transport and to compare the benefits of the two methods. Optimal use of natural resources depletion was based on an abiotic depletion equation. The optimal mix production equation was derived from a typical cement plant operation, such as kiln, grinding, mix, machines hours, labour hours and so on. The ‘subject to constraint’ equations for scenario based studies were derived from the primary and secondary data. The primary data were collected based on well constructed interviews and questionnaire with assistance of a supplementary electronics survey if necessary. In addition, secondary data came from the literature, the annual financial reports of the target companies (2015), the Australian Bureau of Statistics (2014 to 2016), the Cement Industry Federation (2012 to 2013) and more. To solve tailor made, complex linear programming equation problems, traditional mathematical methods were used involving graphical and Gaussian Jordan Elimination methods and spreadsheet based methods with the assistance of the Solver®, which can produce answers, sensitivity analyses and limit reports to deliver optimal solutions. Here, one of the most important outcome of the research was a sensitivity analysis report, which reflected cement factory efficiency and profit performances. By adding to the analysis, the additional constraint that the supply of fly ash was likely to be reduced because of scheduled power station closures in Australia by 2022, it was found that the cost of the raw materials for fly ash based geopolymer cement could then be 17% higher than for ordinary Portland cement. Metakaolin or ground granulate blast slag based geopolymer cement, both of which would positively affect carbon dioxide emissions in production, could pose potential solutions to this shortage. To probe further domestic material consumption in Australia, the time series for the regression model were developed using statistical methods, including ratio indices tools and XLminer Analysis ToolPak® to calculate raw materials consumption and forecast cement production. It also examined the status of further raw material reserves based on Chapter 3’s assigned equation. However, this equation needed to carefully analyse curve characteristics based on the trend of domestic material consumption in Australia in the outcome of results. The solution in this study was the polynomial equation, including the linear equation, instead of the original exponential equation used in the French region. Here, one of the results was that the calcium carbonate and sand would be in short supply within five to 10 years based on 9.1 to 11.1 million tonnes cement production each year. The whole life cycle method based on 20 years of producing fly ash based geopolymer cement, ordinary Portland cement and ordinary Portland cement with supplementary cementitious materials was also used to intensively examine each raw material’s abiotic depletion and reserve status. These outcomes would send earlier messages to cement entrepreneurs organising cement manufacturing for sustainable infrastructure and provide them with optimal solutions as a result of expert, validated knowledge and opinion and optimisation of the proposed methodology

Accretion-induced Collapse of Dark Matter-admixed Rotating White Dwarfs: Dynamics and Gravitational-wave Signals

We present two-dimensional hydrodynamic simulations of the accretion-induced collapse (AIC) of rotating white dwarfs admixed with an extended component of dark matter (DM) comprising of sub-GeV degenerate fermionic DM particles. We find that the DM component would follow the collapse of the normal matter (NM) component to become a bound DM core. Thus, we demonstrate how a DM-admixed neutron star could form through DM-admixed AIC (DMAIC) for the first time, with the dynamics of DM taken into account. The gravitational-wave (GW) signature from the DMAIC shows distinctive features. In the diffusive DM limit, the DM admixture indirectly suppresses the post-bounce spectral peak of the NM GWs. In the compact DM limit, the collapse dynamics of the DM in a Milky Way event generate GWs that are strong enough to be detectable by Advanced LIGO as continuous low-frequency ($< 1000$ Hz) signals after the NM core bounce. Our study not only is the first-ever computation of GW from a collapsing DM object but also provides the key features to identify DM in AIC events through future GW detections.Comment: 14 pages, 13 figure

Can the Testing Effect for General Knowledge Facts Be Influenced by Distraction due to Divided Attention or Experimentally Induced Anxious Mood?

Studies on testing effect have showed that a practice test on study materials leads to better performance in a final test than restudying the materials for the same amount of time. Two experiments were conducted to test how distraction, as triggered by divided attention or experimentally induced anxious mood in the practice phase, could modulate the benefit of testing (vs. restudying) on the learning of interesting and boring general knowledge facts. Two individual difference factors (trait test anxiety and working memory (WM) capacity) were measured. Under divided attention, participants restudied or recalled the missing information in visually presented general knowledge facts, while judging whether auditorily presented items were from a pre-specified category. To experimentally induce anxious mood, we instructed participants to view and interpret negative pictures with anxious music background before and during the practice phase. Immediate and two-day delayed tests were given. Regardless of item type (interesting or boring) or retention interval, the testing effect was not significantly affected by divided (vs. full) attention or anxious (vs. neutral) mood. These results remained unchanged after taking into account the influences of participants’ trait test anxiety and WM capacity. However, when analyses were restricted to the study materials that had been learnt in the divided attention condition while participants accurately responded to the concurrent distracting task, the testing effect was stronger in the divided attention condition than in the full attention condition. Contrary to previous studies (e.g., Tse and Pu, 2012), there was no WM capacity × trait test anxiety interaction in the overall testing effect. Theoretical and practical implications of these findings are discussed

Comparison of virtual patient simulation with Mannequin-based simulation for improving clinical performances in assessing and managing clinical deterioration: Randomized controlled trial

10.2196/jmir.3322Journal of Medical Internet Research169e21

A targeted gene panel that covers coding, non-coding and short tandem repeat regions improves the diagnosis of patients with neurodegenerative diseases

Genetic testing for neurodegenerative diseases (NDs) is highly challenging because of genetic heterogeneity and overlapping manifestations. Targeted-gene panels (TGPs), coupled with next-generation sequencing (NGS), can facilitate the profiling of a large repertoire of ND-related genes. Due to the technical limitations inherent in NGS and TGPs, short tandem repeat (STR) variations are often ignored. However, STR expansions are known to cause such NDs as Huntington\u27s disease and spinocerebellar ataxias type 3 (SCA3). Here, we studied the clinical utility of a custom-made TGP that targets 199 NDs and 311 ND-associated genes on 118 undiagnosed patients. At least one known or likely pathogenic variation was found in 54 patients; 27 patients demonstrated clinical profiles that matched the variants; and 16 patients whose original diagnosis were refined. A high concordance of variant calling were observed when comparing the results from TGP and whole-exome sequencing of four patients. Our in-house STR detection algorithm has reached a specificity of 0.88 and a sensitivity of 0.82 in our SCA3 cohort. This study also uncovered a trove of novel and recurrent variants that may enrich the repertoire of ND-related genetic markers. We propose that a combined comprehensive TGPs-bioinformatics pipeline can improve the clinical diagnosis of NDs

Computational aberration correction of VIS-NIR multispectral imaging microscopy based on Fourier ptychography

Due to the chromatic dispersion properties inherent in all optical materials, even the best-designed multispectral objective will exhibit residual chromatic aberration. Here, we demonstrate a multispectral microscope with a computational scheme based on the Fourier ptychographic microscopy (FPM) to correct these effects in order to render undistorted, in-focus images. The microscope consists of 4 spectral channels ranging from 405 nm to 1552 nm. After the computational aberration correction, it can achieve isotropic resolution enhancement as verified with the Siemens star sample. We image a flip-chip to show the promise of our system to conduct fault detection on silicon chips. This computational approach provides a cost-efficient strategy for high quality multispectral imaging over a broad spectral range

Extending the wavelength range of multi-spectral microscope systems with Fourier ptychography

Due to the chromatic dispersion properties inherent in all optical materials, even the best designed multi-spectral objective will exhibit residual chromatic aberration effect. Here we show that the aberration correction ability of Fourier Ptychographic Microscopy (FPM) is well matched and well suited for post-image acquisition correction of these effects to render in-focus images. We show that an objective with significant spectral focal shift (up to 0.02 μm/nm) and spectral field curvature (up to 0.05 μm/nm drift at off-axis position of 800μm) can be computationally corrected to render images with effectively null spectral defocus and field curvature. This approach of combining optical objective design and computational microscopy provides a good strategy for high quality multi-spectral imaging over a broad spectral range, and eliminating the need for mechanical actuation solutions

Relationship between anxiety sensitivity and post-traumatic stress symptoms in trauma-exposed adults: A meta-analysis

Given the high rate of trauma exposure among the general population, it is important to delineate the risk factors for post-traumatic stress disorder (PTSD). While historically implicated in panic disorder, anxiety sensitivity is increasingly found to play a role in PTSD. The present review investigated the size of the relationship between anxiety sensitivity and PTSD symptoms among trauma exposed adults. A systematic search on multiple electronic databases (PTSDpubs, CINAHL, MEDLINE and PsycINFO) generated a total of 1025 records, among which 52 (n = 15173) met study inclusion criteria and were included in our random effects meta-analysis. Our results indicated a medium effect size (r =.46, 95% CI =.41,.50) for the relationship between anxiety sensitivity and PTSD symptoms. There was significant between-study heterogeneity. Furthermore, sub-group analyses revealed that study design (cross-sectional vs. longitudinal) may significantly moderate the association between anxiety sensitivity and PTSD severity. No moderation effect was found for assessment of PTSD through interview versus questionnaire, interpersonal versus non-interpersonal trauma, or low versus high study quality. Such patterns of results are consistent with cognitive models of PTSD. Clinical implications, strengths and limitations of the review were discussed

Computational aberration correction of VIS-NIR multispectral imaging microscopy based on Fourier ptychography

Due to the chromatic dispersion properties inherent in all optical materials, even the best-designed multispectral objective will exhibit residual chromatic aberration. Here, we demonstrate a multispectral microscope with a computational scheme based on the Fourier ptychographic microscopy (FPM) to correct these effects in order to render undistorted, in-focus images. The microscope consists of 4 spectral channels ranging from 405 nm to 1552 nm. After the computational aberration correction, it can achieve isotropic resolution enhancement as verified with the Siemens star sample. We image a flip-chip to show the promise of our system to conduct fault detection on silicon chips. This computational approach provides a cost-efficient strategy for high quality multispectral imaging over a broad spectral range