Culturally responsive teaching professional development for special educators in rural areas via digital learning technology.

This study examined how participants perceived the experience of receiving culturally responsive teaching (CRT) professional development (PD) for special education teachers via short message service (SMS) in a rural area. Six teachers received the CRT PD non-formal learning course. To establish experimental control, the researcher used a convergent parallel mixed-methods design to analyze survey data and interviews, perform social network analysis, and incorporate data triangularization. The findings showed that participants perceived the experience of receiving CRT PD via SMS as good or excellent. Results also showed more advantages than disadvantages of receiving CRT PD via SMS in a rural area. The learner’s device may have affected learner-instructor connectivity rates during the study. Learners affected interconnectivity rates either at a lower or higher level based on the amount of learner-learner and learner-instructor connectivity that occurred. However, the practice of delivering PD via a mobile device exclusively through SMS is a new practice in the field of mobile learning

Women on the bus: transit experiences in Flagstaff

In 2001, the Mountain Line bus system began operations in Flagstaff, AZ, after voters approved a tax increase for transit funding. This political decision impacted Flagstaff’s historical and geographic movement, embodied experiences, and everyday practices —or “constellations of mobility” (Cresswell, 2010) of older women of color and other groups at the social margins. In the United States, women are the social sector that uses transit the most (Lee et al., 2017). Yet social scientists in Northern Arizona have overlooked the Mountain Line bus as an epistemic space worth attention over two decades. A gap exists in analyzing the bus from a gender perspective. This gap highlights hidden structures of oppression and violence toward older women in urban settings. This study is grounded in a sociological framework combining Marxism, Constructivist Structuralism, and Decolonial Feminism to explore public transportation-related mobility experiences of older women of color in Flagstaff. Participant observations on all Mountain Line routes and semi-structured interviews with four female riders who identify as Hispanic and Navajo, two transit officers, and one driver indicate that older women of color in Flagstaff suffer social exclusion due to the transportation disadvantages they face. This exclusion amplifies the gender data gap on their transit needs, reinforces stigmas imposed on the bus in the United States, and results in a non-universal infrastructure characterized by racist, ageist, and misogynistic social dynamics. In this oppressive context, older women of color develop sophisticated strategies to navigate transit systems in the city, facing time control, infrastructure conditions, and safety burdens that constitute issues that impact their transit experiences

Efficient Euclidean distance calculations and distance similarity searches: an examination of heterogeneous CPU, GPU, and Tensor Core architectures

The Euclidean distance is a measure frequently used in numerous applications, including data-analysis algorithms, to determine the similarity between objects, as a function of the distance between them. Given a set of objects, performing a distance similarity search consists of finding objects that are considered similar, i.e., finding objects within a threshold search distance of a given object, where the distance measure often employs the Euclidean distance formula. Distance similarity searches can be used as a building block for other algorithms, including the distance similarity join, k-Nearest Neighbors (kNN), k-Means, or the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithms. As such, optimizing the computation of Euclidean distances will improve the performance of distance similarity searches, and improving distance similarity searches will improve the performance of numerous other algorithms. Consequently, optimizing both Euclidean distance calculations and distance similarity searches is critical to improve the performance of many data-analysis algorithms, including the ones mentioned above, in addition to applications in other domains such as fields that require modeling and simulation. The literature is rich with methods to improve the performance of Euclidean distance calculations and distance similarity searches, particularly using Central Processing Units (CPUs). While multicore CPUs can offer great parallel performance, they are outclassed by the higher computational throughput of Graphics Processing Units (GPUs). Using GPUs for these problems is relatively recent and there are, consequently, significantly fewer proposed work that use the GPU instead of the CPU. However, the design space for GPU algorithms is large, thus some algorithm designs have been neglected, including those that carefully exploit GPU resources. Furthermore, while both CPUs and GPUs have been extensively studied on their own, very little work has been conducted where both architectures are leveraged concurrently. Tensor Cores (TCs) are a recent addition to certain GPU architectures. As an Application-Specific Integrated Circuit (ASIC), TCs are designed to compute Matrix Multiply-Accumulate (MMA) operations, at a higher throughput than other general-purpose cores. In the literature, TCs are primarily used for machine learning and other related fields involving linear algebra, yielding great performance improvements. Despite their specificity, TCs can be leveraged for any algorithm where the computation can be expressed using MMA operations. Nevertheless, leveraging TCs for general-purpose scientific algorithms remains an open problem. We propose in this dissertation to optimize the performance of Euclidean distance calculations and more generally distance similarity searches, by examining: (i) GPU resource utilization; (ii) the joint use of both CPUs and GPUs for computation; (iii) the use of TCs to compute Euclidean distances; (iv) the joint use of general-purpose GPU cores and TCs to compute Euclidean distances

The tensile behavior, fracture, and power harvesting potential of nickel-manganese-gallium magnetic shape memory alloys

The shape memory effect in Ni2MnGa MSMAs is driven by the magnetic field-induced or stress-induced motion of twin boundaries. The Ni2MnGa microstructure consists of tetragonal martensite variants with magnetic easy axis aligned with the short axis (of the unit cell), which aligns in either the direction of the applied magnetic field or mechanical stress causing a reorientation of the microstructure. The reorientation strain and the change in the material’s magnetization during variant reorientation, drive the development of MSMA-based applications. The overarching objective of this dissertation study is to inform the development of new MSMA-based applications and to improve the efficiency and reliability of current MSMA-based applications by studying the tensile behavior, fracture mechanics, and power harvesting potential of Ni2MnGa MSMAs. Historically, MSMAs have been studied extensively under combined compressive and/or magnetic loads, and applications only use MSMAs in compression. The tensile study investigates the strain fields developed in Ni2MnGa samples, with fine and coarse twin structures when loaded in tension and/or with a magnetic field. The strain fields are recorded using digital image correlation, which allowed for the observation of the evolution of the strain field over the entire sample, concurrent with the evolution of the sample’s twin microstructure. The results show that the twin density, the uniformity of the magneto-mechanical loading along the sample, and the presence of pinning sites are all contributing to the profile of the tensile strain field; the presence of pinning sites along the sample inhibits variant reorientation and recovery. Both samples showed no visible signs of damage during tensile testing, and the magneto-mechanical response in tension was found to be comparable to that in compression for both sample types. The fracture mechanics study involves the experimental research of the fracture mechanisms in MSMAs and the development of an MSMA fracture mechanics modeling framework; the brittle nature of Ni2MnGa MSMAs causes cracks to develop in them hampering their function in MSMA-based applications. The phase-field method is proposed for the modeling framework since this method is able to capture complex crack patterns, and Vickers microindentation is used for the experimental study to determine the fracture energy of the material and study crack evolution characteristics under magneto-mechanical loading. The Vickers microindentation results suggest that transverse magnetic fields facilitate crack growth and decrease the fracture energy of the MSMA, while the axial compressive stress impedes crack growth and increases the fracture energy. Lastly, the power harvesting study reports new power harvesting data generated with a biaxial magnetic field and a surrounding coil, and full strain field data for an MSMA subject to load similar to what is seen during power harvesting, then compares theperformance of MSMA-based power harvesters with different designs to determine which give the best output. For this comparison, a framework for evaluating the performance of (side coil and surrounding coil type) MSMA-based power harvesters reported in the literature is developed. This framework involves normalizing the results to the design characteristics of the respective harvesters. The strain maps reveal the potential for perpendicular twin boundaries that limit variant reorientation and correspondingly the harvester’s power. The power harvesting study concludes that the largest change in magnetic flux density, which is the driver for power harvesting, occurs in the side coil setup with an optimized magnetic circuit and it recommends using this configuration for future MSMA-based power harvesters for maximum power

Steady-state sludge digestion model with auto-calibration

Anaerobic digestion is a wastewater treatment technology used to treat sludge. One of the main benefits of this technology is the production of biogas that can be used as fuel for energy production. This process is extremely complex with many different steps and parallel reactions occurring simultaneously. These steps require highly specific environmental conditions that must be maintained for anaerobic digestion to occur. Modeling for anaerobic digestion began in the late 1960s to better understand and streamline the anaerobic digestion process. Many years of research were combined by the International Water Association to develop the Anaerobic Digestion Model No. 1 (ADM1), which was published in 2002 and no widely accepted updates have been published since. This model has repeatedly been proven to be a complete and accurate model for anaerobic digestion, but it is extremely complex and requires many estimated parameters. This complexity results in the model not being used by currently operating wastewater treatment plants due to the lack of data that is required for the ADM1. Creating a simple steady-state model to predict the concentration of methane in the biogas produced that does not require as many parameters would be beneficial for wastewater treatment plants to repurpose the biogas. Using full-scale solids data, a steady-state model that auto-calibrates to a specific wastewater treatment was developed by creating simple relationships between volatile solids, metabolism factors, and hydraulic retention times. This resulted in methane concentrations ranging from 55 – 71% of the biogas. These values are within expected ranges for mesophilic operations, but due to lack of measured methane data from wastewater treatment plants, it is not possible to know if this is accurate for the specific plant. This poses the need for wastewater treatment plants to routinely monitor methane concentrations to successfully develop a steady-state anaerobic digestion model. Despite its limitations, the steady-state model is successful in terms of providing a way for wastewater treatment plants to easily predict the methane concentration within the biogas

How will global warming affect decomposition and element cycling of native and invasive leaf litter in streams?

Global warming and introduced species have the potential to alter the functioning and structure of headwater streams. Testing how temperature affects detrital food webs is challenging because it is difficult to manipulate temperature in a field setting. Here, we evaluate how microbes and shredders decompose two morphologically distinct, riparian tree species, Populus fremontii (native) and Tamarix sp. (nonnative). We built an artificial stream facility to manipulate temperature while maintaining natural diurnal and seasonal patterns of most stream variables (light, nutrients, dissolved oxygen). We employed a factorial design that included 3 temperature treatments (ambient, + 3.7°C, and + 6.6°C), 2 leaf types and 2 decomposition mediators (microbes and shredders + microbes). Decomposition rate and microbial biomass were influenced by leaf type and temperature, with P. fremontii decomposing more rapidly and supporting almost twice the microbial biomass found in Tamarix sp. Temperature increased decomposition rate by 9.1 to 16.5% in the +3.7°C treatments relative to ambient temperatures. Additional increases in temperature did not accelerate decomposition rate for either species. Litter packs containing shredders decomposed more rapidly than litter packs with only microbes. However, shredder contribution to leaf litter decomposition was relatively low in both leaf types, ranging from 1.97% to 10.45%. A laboratory experiment measured leaching rates with 2 temperatures and 2 time periods (24h and 48h). P. fremontii leached significantly more DOC than Tamarix sp. and Tamarix sp. leached significantly more TN than P. fremontii. In both litter types, approximately 43% to 48% of initial mass was lost after 48 hours of leaching. Temperature did not affect mass loss due to leaching. These results show that increases in water temperature may lead to rapid depletion of labile leaf litter resources and that the disproportionately high leaching of TN found in Tamarix sp. leaf litter may prevent microbes and shredders from accessing compounds containing nitrogen

Ammonia as a tool for removal of invasive crayfish

Several species of invasive crayfish have been introduced globally, impacting ecosystem functioning and biodiversity. The opportunistic feeding habits of nonnative crayfish have negatively affected native aquatic species in the Southwestern United States, and their ability to travel between isolated aquatic systems make them difficult to control once they become established. Efforts to manually remove crayfish from invaded habitats have met with limited success and few chemical tools are available. With increasing numbers of invasive species in aquatic systems comes a growing need for additional management methods. The use of ammonia has shown promise as a removal tool for introduced fish and has several advantages over other chemical removal methods. An ammonia-based tool could be a cost-effective way to eradicate invasive crayfish and support conservation of native aquatic species while utilizing the natural nitrogen cycle to remove the ammonia from the environment and return an ecosystem to baseline conditions. I used laboratory experiments to develop and test lethal concentrations of ammonia for Northern crayfish (Faxonius virilis) and Red Swamp crayfish (Procambarus clarkii). I used a formulation of ammonium sulfate to elevate ammonia concentrations to 50mg/l, sodium carbonate to increase pH to 9.5, and sodium sulfite to lower dissolved oxygen to 0mg/l. The formulation achieved 100% mortality of F. virilis in 24 hours in a laboratory setting, but only 90% mortality of P. clarkii. A field trial with P. clarkii achieved mortality of most of the crayfish exposed to the ammonia treatment; however, live crayfish were found around the pond after the treatment. These results suggest that an ammonia-based chemical tool could be utilized for invasive crayfish management. I recommend that additional laboratory and field trials focus on further exploring species differences and the effectiveness of ammonia treatments under diverse field conditions

March of the Aspen: poems and essays

March of the Aspen is a mixed collection of poetry and memoir that delves into the meaning of belonging to a place and the responsibility in having that place belong to you. Split between Red Lodge, Montana where I work as a Wilderness ranger for the Forest Service and the Idaho-Wyoming border where I grew up, March of the Aspen juxtaposes my connections to these lands with homesteaders, tourists, family, and those whose spaces we must share – the birds and bears and aspen’s steady spread into the meadow. In a world inundated with ever more alarming statistics about changing climates I write to the local side of change: that which is only noticeable when intimate with the land

Human perceptions of competing interests in springs ecosystems management on the Coconino and Kaibab national forests

Spring ecosystems provide vital services to humans and wildlife in Northern Arizona. Management of springs presents unique challenges due to the diversity of stakeholders and the multiple uses of springs. We employ two methods of data collection to understand the perceptions of springs ecosystem management: interviews and focus groups with stakeholders of springs in Coconino National Forest (CNF) and Kaibab National Forest (KNF) and a national survey aimed towards public perceptions. We analyze the human perceptions of springs to understand variations between stakeholders and how perceptions of stakeholders and the public vary. Our results indicate differences between human perceptions and current management practices. The main competing interests of springs management are cattle grazing, recreation, and Indigenous Nations’ cultural significance. The survey respondents, representative of public perceptions, indicate springs management for Indigenous Nations’ cultural significance is important. We see positive correlation between concern for threats to springs from grazing and management to prioritize cultural significance indicating respondents prefer springs to be managed for cultural significance. Cattle grazing and other high impact human uses are viewed less favorably than other management scenarios. Stakeholders’ perceptions varied and non-Indigenous stakeholders suggested management should be based on multiple uses and management focused on specific attributes of springs valuable to humans. Our results of the survey respondents’ perceptions for management of Indigenous culture and some support from stakeholders show a joint management concept might be beneficial for springs management in the CNF and KNF. Using the information we collected on the perceptions of spring ecosystems management, we discuss mechanisms for springs management to increase the ability for springs to provide cultural significance values to Indigenous Nations by potentially limiting high impact and degrading uses of springs. We provide results and examples of how all stakeholders can have the ability to benefit from the resources springs provide

Multilingual spoken word recognition: A megastudy approach

Bilingualism research has primarily focused on the perception and processing of individual sounds or word learning. Many studies have investigated how bilingual listeners perceive sound contrasts that don't create lexical distinctions in their native language. There is substantially less research that has investigated how word-level properties impact L2 auditory processing. The present study examines how auditory lexical processing differs between monolingual and bilingual listeners with different language backgrounds. We collected lexical decision accuracies and latencies for 26,793 words and 9600 pseudowords from the Massive Auditory Lexical Decision database from native and non-native listener responses. We compare the language backgrounds of our 1028 listeners and group them into four groups: native speakers, early, early-late, and late bilinguals. We report the findings of an analysis investigating how language background and proficiency modulate lexical effects to understand how language background influences spoken word recognition. We find differences in the effects of lexical frequency, phonological neighborhood density, and phonological uniqueness point between the different listener groups. We discuss the impact of bilingualism in a word recognition task and how these results inform models of spoken word recognition and second language acquisition