Editorial of "International Journal of Critical Indigenous Studies Volume 4, Number 1, 2011"

This special edition of the International Journal of Critical Indigenous Studies highlights the work of emerging scholars in the field of Indigenous Studies. The five featured authors were all finalists for the prize awarded by the Native American and Indigenous Studies Association (NAISA) to the best post-graduate student paper at the NAISA meeting held in 2010 in Tucson, Arizona. While the breadth of scholarship encompassed by the term ‘Indigenous Studies’ and the global representation of Indigenous peoples at NAISA mean that the topics and approaches vary widely, a common thematic of fraught post-colonial relations can be discerned within all five articles.

Critical Indigenous Studies: Engagements in First World Locations

With increasing speed, the emerging discipline of critical Indigenous studies is expanding and demarcating its territory from Indigenous studies through the work of a new generation of Indigenous scholars. Critical Indigenous Studies makes an important contribution to this expansion, disrupting the certainty of disciplinary knowledge produced in the twentieth century, when studying Indigenous peoples was primarily the domain of non-Indigenous scholars. Aileen Moreton-Robinson's introductory essay provides a context for the emerging discipline. The volume is organized into three sections: the first includes essays that interrogate the embedded nature of Indigenous studies within academic institutions; the second explores the epistemology of the discipline; and the third section is devoted to understanding the locales of critical inquiry and practice. Each essay places and contemplates critical Indigenous studies within the context of First World nations, which continue to occupy Indigenous lands in the twenty-first century. The contributors include Aboriginal, Metis, Maori, Kanaka Maoli, Filipino-Pohnpeian, and Native American scholars working and writing through a shared legacy born of British and later U.S. imperialism. In these countries, critical Indigenous studies is flourishing and transitioning into a discipline, a knowledge/power domain where distinct work is produced, taught, researched, and disseminated by Indigenous scholars.

The Science and Art of Light

Architecture today often is praised for its tectonics, floating volumes, and sensational, gravity-defying stunts of “starchitecture.” Yet, very so often there is a building that inspires descriptions of the sublime, the experiential, and the power of light and architecture to transcend our expectations. The new Meinel Optical Sciences Research Building, designed by Phoenix-based Richärd+Bauer for the University of Arizona, Tucson, is one of these architectural rarities. Already drawing comparisons to Louis Kahn's 1965 Salk Institute for Biological Studies in La Jolla, California, the indescribable quality of light that characterizes the best of Kahn's work also resonates in Richärd+Bauer's new building. Both an expansion and renovation of the existing College of Optical Sciences facilities, the Meinel building includes teaching and research laboratories, six floors of offices, discussion areas, conference rooms, and an auditorium. The new 47,000 square-foot cast-in-place concrete structure, wrapped on three-sides in copper-alloy panels, harmonizes with the largely brick vocabulary of the campus while reflecting the ethereal quality of the wide Arizona sky. The façade, however, is merely a prelude for what awaits inside—where light and architecture seamlessly combine to create moments of pure awe.

Long time, no see? (DIY walking)

Building on the launch of an early prototype at Balance Unbalance 2013, we now offer a fully realised experience of the ‘Long Time, No See?’ site specific walking/visualisation project for conference users to engage with on a do it yourself basis, either before, during or after the event. ‘Long Time, No See?’ is a new form of participatory, environmental futures project, designed for individuals and groups. It uses a smartphone APP to guide processes of individual or group walking at any chosen location—encouraging walkers to think in radical new ways about how to best prepare for ‘stormy’ environmental futures ahead. As part of their personal journeys participants’ contribute site-specific micro narratives in the form of texts, images and sounds, captured via the APP during the loosely ‘guided’ walk. These responses are then uploaded and synthesised into an ever-building audiovisual and generative artwork/‘map’ of future-thinking affinities, viewable both online at long-time-no-see.org (in Chrome) (and at the same time on a large screen visualisations at QUT’s Cube Centre in Brisbane Australia). The artwork therefore spans both participants’ mobile devices and laptops. If desired outcomes can also be presented publicly in large screen format at the conference. ‘Long Time, No See?’ has been developed over the past two years by a team of leading Australian artists, designers, urban/environmental planners and programmers.

Features of the geomagnetic field during the Holocene and Proterozoic

The geomagnetic field is one of the most fundamental geophysical properties of the Earth and has significantly contributed to our understanding of the internal structure of the Earth and its evolution. Paleomagnetic and paleointensity data have been crucial in shaping concepts like continental drift, magnetic reversals, as well as estimating the time when the Earth's core and associated geodynamo processes begun. The work of this dissertation is based on reliable Proterozoic and Holocene geomagnetic field intensity data obtained from rocks and archeological artifacts. New archeomagnetic field intensity results are presented for Finland, Estonia, Bulgaria, Italy and Switzerland. The data were obtained using sophisticated laboratory setups as well as various reliability checks and corrections. Inter-laboratory comparisons between three laboratories (Helsinki, Sofia and Liverpool) were performed in order to check the reliability of different paleointensity methods. The new intensity results fill up considerable gaps in the master curves for each region investigated. In order to interpret the paleointensity data of the Holocene period, a novel and user-friendly database (GEOMAGIA50) was constructed. This provided a new tool to independently test the reliability of various techniques and materials used in paleointensity determinations. The results show that archeological artifacts, if well fired, are the most suitable materials. Also lavas yield reliable paleointensity results, although they appear more scattered. This study also shows that reliable estimates are obtained using the Thellier methodology (and its modifications) with reliability checks. Global paleointensity curves during Paleozoic and Proterozoic have several time gaps with few or no intensity data. To define the global intensity behavior of the Earth's magnetic field during these times new rock types (meteorite impact rocks) were investigated. Two case histories are presented. The Ilyinets (Ukraine) impact melt rocks yielded a reliable paleointensity value at 440 Ma (Silurian), whereas the results from Jänisjärvi impact melts (Russian Karelia, ca. 700 Ma) might be biased towards high intensity values because of non-ideal magnetic mineralogy. The features of the geomagnetic field at 1.1 Ga are not well defined due to problems related to reversal asymmetries observed in Keweenawan data of the Lake Superior region. In this work new paleomagnetic, paleosecular variation and paleointensity results are reported from coeval diabases from Central Arizona and help understanding the asymmetry. The results confirm the earlier preliminary observations that the asymmetry is larger in Arizona than in Lake Superior area. Two of the mechanisms proposed to explain the asymmetry remain plausible: the plate motion and the non-dipole influence.

Deeper and wider fully convolutional network coupled with conditional random fields for scene labeling

Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.

Inhomogeneity of asteroid 2008 TC3 (Almahata Sitta meteorites) revealed through magnetic susceptibility measurements

Magnetic susceptibility measurements were performed on freshly fallen Almahata Sitta meteorites. Most recovered samples are polymict ureilites. Those found in the first four months since impact, before the meteorites were exposed to rain, have a magnetic susceptibility in the narrow range of 4.92 ± 0.08 log 10-9 Am2/kg close to the range of other ureilite falls 4.95 ± 0.14 log 10-9 Am2/kg reported by Rochette et al. (2009). The Almahata Sitta samples collected one year after the fall have similar values (4.90 ± 0.06 log 10-9 Am2/kg), revealing that the effect of one-year of terrestrial weathering was not severe yet. However, our reported values are higher than derived from polymict (brecciated) ureilites 4.38 ± 0.47 log 10-9 Am2/kg (Rochette et al. 2009) containing both falls and finds confirming that these are significantly weathered. Additionally other fresh-looking meteorites of non-ureilitic compositions were collected in the Almahata Sitta strewn field. Magnetic susceptibility measurements proved to be a convenient non-destructive method for identifying non-ureilitic meteorites among those collected in the Almahata Sitta strewn field, even among fully crusted. Three such meteorites, no. 16, 25, and 41, were analyzed and their composition determined as EH6, H5 and EL6 respectively (Zolensky et al., 2010). A high scatter of magnetic susceptibility values among small (< 5 g) samples revealed high inhomogeneity within the 2008 TC3 material at scales below 1-2 cm.

A k-epsilon model for turbulent weld pool convection in gas metal arc welding process

In this paper, we present a modified k - epsilon model capable of addressing turbulent weld-pool convection in a GMAW process, taking into account the morphology of the phase change interface during a Gas Metal Arc Welding (GMAW) process. A three-dimensional turbulence mathematical model has been developed to study the heat transfer and fluid flow within the weld pool by considering the combined effect of three driving forces, viz., buoyancy, Lorentz force and surface tension (Marangoni convection). Mass and energy transports by the droplets are considered through the thermal analysis of the electrode. The falling droplet's heat addition to the molten pool is considered to be a volumetric heat source distributed in an imaginary cylindrical cavity ("cavity model") within the weld pool. This nature of heat source distribution takes into account the momentum and the thermal, energy of the falling droplets. The numerically predicted weld pool dimensions both from turbulence and laminar models are then compared with the experimental post-weld results sectioned across the weld axis. The above comparison enables us to analyze the overall effects of turbulent convection on the nature of heat and fluid flow and hence on the weld pool shape/size during the arc welding processes.

Exploiting coherence for the simultaneous discovery of latent facets and associated sentiments

Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.

A sequential dual method for structural SVMs

In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to compu- tational biology or computer vision and have been tackled using algorithms, referred to as structured output learning algorithms. We consider the problem of structured classifi- cation. In the last few years, large margin classifiers like sup-port vector machines (SVMs) have shown much promise for structured output learning. The related optimization prob -lem is a convex quadratic program (QP) with a large num-ber of constraints, which makes the problem intractable for large data sets. This paper proposes a fast sequential dual method (SDM) for structural SVMs. The method makes re-peated passes over the training set and optimizes the dual variables associated with one example at a time. The use of additional heuristics makes the proposed method more efficient. We present an extensive empirical evaluation of the proposed method on several sequence learning problems.Our experiments on large data sets demonstrate that the proposed method is an order of magnitude faster than state of the art methods like cutting-plane method and stochastic gradient descent method (SGD). Further, SDM reaches steady state generalization performance faster than the SGD method. The proposed SDM is thus a useful alternative for large scale structured output learning.

Infinite push: a new support vector ranking algorithm that directly optimizes accuracy at the absolute top of the list

Ranking problems have become increasingly important in machine learning and data mining in recent years, with applications ranging from information retrieval and recommender systems to computational biology and drug discovery. In this paper, we describe a new ranking algorithm that directly maximizes the number of relevant objects retrieved at the absolute top of the list. The algorithm is a support vector style algorithm, but due to the different objective, it no longer leads to a quadratic programming problem. Instead, the dual optimization problem involves l1, ∞ constraints; we solve this dual problem using the recent l1, ∞ projection method of Quattoni et al (2009). Our algorithm can be viewed as an l∞-norm extreme of the lp-norm based algorithm of Rudin (2009) (albeit in a support vector setting rather than a boosting setting); thus we refer to the algorithm as the ‘Infinite Push’. Experiments on real-world data sets confirm the algorithm’s focus on accuracy at the absolute top of the list.

Fish inspired biomimetic ionic polymer metal composite pectoral fins using labriform propulsion

Ionic polymer metal composites (IPMC) are a new class of smart materials that have attractive characteristics such as muscle like softness, low voltage and power consumption, and good performance in aqueous environments. Thus, IPMC’s provide promising application for biomimetic fish like propulsion systems. In this paper, we design and analyze IPMC underwater propulsor inspired from swimming of Labriform fishes. Different fish species in nature are source of inspiration for different biomimetic flapping IPMC fin design. Here, three fish species with high performance flapping pectoral fin locomotion is chosen and performance analysis of each fin design is done to discover the better configurations for engineering applications. In order to describe the behavior of an active IPMC fin actuator in water, a complex hydrodynamic function is used and structural model of the IPMC fin is obtained by modifying the classical dynamic equation for a slender beam. A quasi-steady blade element model that accounts for unsteady phenomena such as added mass effects, dynamic stall, and the cumulative Wagner effect is used to estimate the hydrodynamic performance of the flapping rectangular shape fin. Dynamic characteristics of IPMC actuated flapping fins having the same size as the actual fins of three different fish species, Gomphosus varius, Scarus frenatus and Sthethojulis trilineata, are analyzed with numerical simulations. Finally, a comparative study is performed to analyze the performance of three different biomimetic IPMC flapping pectoral fins.

Evaluación de productos botánicos para el manejo del complejo mosca blanca (Bemisia tabaci, Gennadius)-Geminivirus y otros insectos plagas en el cultivo de tomate (Solanum lycopersicum L.), en Tisma, Masaya

La mosca blanca (Bemisia tabaci) y los Geminivirus son las principales plagas causantes de pérdidas económicas en el cultivo de tomate (Solanum lycopersicum, Mill) en el municipio de Tisma-Masaya. En base a esta situación se realizó un estudio para evaluar la efectividad que tiene para controlar plagas los tratamientos botánicos: Chile+Ajo+Jabón, Madero Negro, Crisantemo, Extracto alcohólico+Chile, Extracto alcohólico+ Chile+ Ajo y Testigo en el período comprendido entre Diciembre 2013 a Febrero 2014. Las variables evaluadas fueron: número de mosca blanca por planta, Incidencia del daño de virosis de mosca blanca por planta, severidad del daño de virosis de mosca blanca por planta, y otros organismos plagas en el rubro: Halticus sp por planta, áfidos (Aphis gossypii) por planta, y minador de la hoja (Liriomyza sp) por planta. De los tratamientos evaluados, el menor número de moscas blancas por planta y menor porcentaje de incidencia(47%) y severidad (51%) lo obtuvo el tratamiento Extracto Alcohólico + Chile+ Ajo. El tratamiento Madero Negro presentó la mayor efectividad en el manejo de poblaciones de Halticus sp. y Lyriomiza sp., mientras que el Extracto Alcohólico + Chile + Ajo presentó los mejores resultados para el manejo de Aphis gossypii. El análisis económico reveló que el mayor rendimiento lo obtuvo el Extracto Alcohólico+ Chile + Ajo con 34685.18 kg/ha seguido del tratamiento Chile+ Ajo+ Jabón (30614.28 kg/ha). En el análisis de retorno marginal resultó que el tratamiento Chile+ Ajo+ Jabón es el que obtuvo la mejor tasa de retorno marginal con 1476 %, es decir, 14.76 US$ por cada dólar invertido. El análisis realizado en la Universidad de Tucson Arizona en muestra de mosca blanca procedente de Tisma- Masaya determinó que de la muestra un 66.66% corresponde a la mosca blanca autóctona (biotipo A), y el 33.33% corresponde al biotipo B que es más agresivo que el A. Y el análisis de los begomovirus determinó: Enrollamiento severo de la hoja de tomate (ToSLCV) con 97.4% de identidad y el Virus del mosaico dorado de la chiltoma (PepGMV) con un 98% de identidad.