Making scenes : Reggae, punk, and death metal in 1990s Bali

In 1996, Emma Baulch went to live in Bali to do research on youth culture. Her chats with young people led her to an enormously popular regular outdoor show dominated by local reggae, punk, and death metal bands. In this rich ethnography, she takes readers inside each scene: hanging out in the death metal scene among unemployed university graduates clad in black T-shirts and ragged jeans; in the punk scene among young men sporting mohawks, leather jackets, and hefty jackboots; and among the remnants of the local reggae scene in Kuta Beach, the island’s most renowned tourist area. Baulch tracks how each music scene arrived and grew in Bali, looking at such influences as the global extreme metal underground, MTV Asia, and the internationalization of Indonesia’s music industry. Making Scenes is an exploration of the subtle politics of identity that took place within and among these scenes throughout the course of the 1990s. Participants in the different scenes often explained their interest in death metal, punk, or reggae in relation to broader ideas about what it meant to be Balinese, which reflected views about Bali’s tourism industry and the cultural dominance of Jakarta, Indonesia’s capital and largest city. Through dance, dress, claims to public spaces, and onstage performances, participants and enthusiasts reworked “Balinese-ness” by synthesizing global media, ideas of national belonging, and local identity politics. Making Scenes chronicles the creation of subcultures at a historical moment when media globalization and the gradual demise of the authoritarian Suharto regime coincided with revitalized, essentialist formulations of the Balinese self.

Combining genetic algorithm and simulated annealing: A molecular geometry optimization study

We introduce a new hybrid approach to determine the ground state geometry of molecular systems. Firstly, we compared the ability of genetic algorithm (GA) and simulated annealing (SA) to find the lowest energy geometry of silicon clusters with six and 10 atoms. This comparison showed that GA exhibits fast initial convergence, but its performance deteriorates as it approaches the desired global extreme. Interestingly, SA showed a complementary convergence pattern, in addition to high accuracy. Our new procedure combines selected features from GA and SA to achieve weak dependence on initial parameters, parallel search strategy, fast convergence and high accuracy. This hybrid algorithm outperforms GA and SA by one order of magnitude for small silicon clusters (Si6 and Si10). Next, we applied the hybrid method to study the geometry of a 20-atom silicon cluster. It was able to find an original geometry, apparently lower in energy than those previously described in literature. In principle, our procedure can be applied successfully to any molecular system. © 1998 Elsevier Science B.V.

Finding the Relationship between a Search Algorithm and a Class of Functions on Discrete Space by Exhaustive Search

* The work is supported by RFBR, grant 04-01-00858-a.

The effect of horizontal resolution on simulation of very extreme US precipitation events in a global atmosphere model

We investigate the ability of a global atmospheric general circulation model (AGCM) to reproduce observed 20 year return values of the annual maximum daily precipitation totals over the continental United States as a function of horizontal resolution. We find that at the high resolutions enabled by contemporary supercomputers, the AGCM can produce values of comparable magnitude to high quality observations. However, at the resolutions typical of the coupled general circulation models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, the precipitation return values are severely underestimated.

Challenging Indifference to Extreme Poverty: Considering Southern Perspectives on Global Citizenship and Change

Canadian universities are expanding opportunities for students to travel, study, volunteer and work abroad for academic credit, especially in regions of the global south often called “developing countries.” It is widely assumed that exposure to extreme poverty through shortterm placements overseas will make young Canadians and other Northerners into “global citizens” who would by definition be incapable of indifference to the lack of freedom that accompanies extreme poverty. This paper asks whether it is warranted for Northerners to attain a claim to global citizenship via this mechanism, especially in light of the burdens falling upon Southern organizations that host young people from Canada and elsewhere.

A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates

The intensity and distribution of daily precipitation is predicted to change under scenarios of increased greenhouse gases (GHGs). In this paper, we analyse the ability of HadCM2, a general circulation model (GCM), and a high-resolution regional climate model (RCM), both developed at the Met Office's Hadley Centre, to simulate extreme daily precipitation by reference to observations. A detailed analysis of daily precipitation is made at two UK grid boxes, where probabilities of reaching daily thresholds in the GCM and RCM are compared with observations. We find that the RCM generally overpredicts probabilities of extreme daily precipitation but that, when the GCM and RCM simulated values are scaled to have the same mean as the observations, the RCM captures the upper-tail distribution more realistically. To compare regional changes in daily precipitation in the GHG-forced period 2080-2100 in the GCM and the RCM, we develop two methods. The first considers the fractional changes in probability of local daily precipitation reaching or exceeding a fixed 15 mm threshold in the anomaly climate compared with the control. The second method uses the upper one-percentile of the control at each point as the threshold. Agreement between the models is better in both seasons with the latter method, which we suggest may be more useful when considering larger scale spatial changes. On average, the probability of precipitation exceeding the 1% threshold increases by a factor of 2.5 (GCM and RCM) in winter and by I .7 (GCM) or 1.3 (RCM) in summer.

Analysis Of Semi-Distributed And Global Hydrological Models In The Central Tropical Basins Of The Gulf Of Mexico To The Effects Of Extreme Hydrometeorological Phenomena

In the last years extreme hydrometeorological phenomena have increased in number and intensity affecting the inhabitants of various regions, an example of these effects are the central basins of the Gulf of Mexico (CBGM) that they have been affected by 55.2% with floods and especially the state of Veracruz (1999-2013), leaving economic, social and environmental losses. Mexico currently lacks sufficient hydrological studies for the measurement of volumes in rivers, since is convenient to create a hydrological model (HM) suited to the quality and quantity of the geographic and climatic information that is reliable and affordable. Therefore this research compares the semi-distributed hydrological model (SHM) and the global hydrological model (GHM), with respect to the volumes of runoff and achieve to predict flood areas, furthermore, were analyzed extreme hydrometeorological phenomena in the CBGM, by modeling the Hydrologic Modeling System (HEC-HMS) which is a SHM and the Modèle Hydrologique Simplifié à I'Extrême (MOHYSE) which is a GHM, to evaluate the results and compare which model is suitable for tropical conditions to propose public policies for integrated basins management and flood prevention. Thus it was determined the temporal and spatial framework of the analyzed basins according to hurricanes and floods. It were developed the SHM and GHM models, which were calibrated, validated and compared the results to identify the sensitivity to the real model. It was concluded that both models conform to tropical conditions of the CBGM, having MOHYSE further approximation to the real model. Worth mentioning that in Mexico there is not enough information, besides there are no records of MOHYSE use in Mexico, so it can be a useful tool for determining runoff volumes. Finally, with the SHM and the GHM were generated climate change scenarios to develop risk studies creating a risk map for urban planning, agro-hydrological and territorial organization.

Paleoproterozoic snowball Earth: Extreme climatic and geochemical global change and its biological consequences

Geological, geophysical, and geochemical data support a theory that Earth experienced several intervals of intense, global glaciation (“snowball Earth” conditions) during Precambrian time. This snowball model predicts that postglacial, greenhouse-induced warming would lead to the deposition of banded iron formations and cap carbonates. Although global glaciation would have drastically curtailed biological productivity, melting of the oceanic ice would also have induced a cyanobacterial bloom, leading to an oxygen spike in the euphotic zone and to the oxidative precipitation of iron and manganese. A Paleoproterozoic snowball Earth at 2.4 Giga-annum before present (Ga) immediately precedes the Kalahari Manganese Field in southern Africa, suggesting that this rapid and massive change in global climate was responsible for its deposition. As large quantities of O2 are needed to precipitate this Mn, photosystem II and oxygen radical protection mechanisms must have evolved before 2.4 Ga. This geochemical event may have triggered a compensatory evolutionary branching in the Fe/Mn superoxide dismutase enzyme, providing a Paleoproterozoic calibration point for studies of molecular evolution.

Moomba - A collaborative environment for supporting distributed extreme programming in global software development

Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.

Towards convection-resolving, global atmospheric simulations with the Model for Prediction Across Scales (MPAS) v3.1: an extreme scaling experiment, links to sourcecode of model and grides

The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This concept allows one to include the feedback of regional land use information on weather and climate at local and global scales in a consistent way, which is impossible to achieve with traditional limited area modelling approaches. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different high-performance computing (HPC) sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African monsoon (WAM) and its associated precipitation in a pilot study. Constrained by available computational resources, we compare 11-month runs for two meshes with observations and a reference simulation from the Weather Research and Forecasting (WRF) model. We show that MPAS can reproduce the atmospheric dynamics on global and local scales in this experiment, but identify a precipitation excess for the West African region. Finally, we conduct extreme scaling tests on a global 3?km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70?% parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3?km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.

Climate change and financial regulation : challenges for the financial sector post the Global Financial Crisis

Regulation has played a significant role in shaping the financial services sector in Australia over the past few decades. Regulatory changes have included the establishment of the Australian Prudential Regulation Authority (APRA), floating the Australian dollar, allowing foreign financial institutions to operate domestically, the introduction of the superannuation guarantee charge, and the removal of interest rate controls. As the economy emerges from the worst financial crisis since the great depression, a new force of change that is recognised as one of the most significant sources of risk and opportunity facing the business community in the foreseeable future is that of climate change. Climate change is expected to be a significant change agent in the financial services sector as extreme weather patterns, sea level rises, and atmospheric changes impact on asset values (both investment and lending), project finance, and risk products. The financial services industry will be particularly affected by these developments, both as a provider of financial products (capital, credit, investment, advice, and insurance), and also through its powerful influence on the economy in terms of capital allocation. In addition, industry constituents will be heavily impacted by government regulation in this area (reporting, emissions trading and environmental policies), with respect to their own business practices and also those of their clients. This study reports the results of interviews conducted with senior members of the finance sector working in the sustainability area to gauge their perceptions of the challenges facing the sector with respect to climate change. Our results confirm that that regulatory intervention will be critical to climate change response gaining traction and momentum. In particular, regulatory certainty will promote engagement, particularly in relation to the Carbon Pollution Reduction Scheme (CPRS), with other developments needed in terms of information disclosure, performance and remuneration, and incentive programs. Accordingly, the significant potential risks and opportunities that climate change presents to the sector, and the broader economy, will in part be managed/realised only if a swift and significant regulatory response is achieved.

Estimating present day extreme water level exceedance probabilities around the coastline of Australia : tides, extra-tropical storm surges and mean sea level

The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical applications.