Showing papers by "Boise State University published in 2023"
01 Jan 2023
TL;DR: In the 2020 assembly election campaign, Kejriwal publicized his temple visits, signaling to the Hindus that he was one of them and avoided appearing pro-Muslim by disregarding the anti-Citizenship Amendment Act protests as discussed by the authors .
Abstract: During the 2020 assembly election campaign, Kejriwal publicized his temple visits, signaling to the Hindus that he was one of them. Additionally, he avoided appearing pro-Muslim by disregarding the anti-Citizenship Amendment Act protests. The CAA discriminated against Muslims by providing non-Muslim immigrants an easier path to Indian citizenship. The prevalent narrative about the Delhi voters suggests that the bread-and-butter issues matter more to them than religion and culture. Considering the AAP’s administrative record, the party could have won the election whether or not they appeared pro-Muslim. Nevertheless, Kejriwal’s campaign strategy suggests that he believed that offending the Hindus or appearing pro-Muslim would have hurt the AAP electorally despite the party’s exemplary administrative record. Supporting or opposing the protestors would have emphasized the Hindu-Muslim divide, pushing the undecided Hindu voters toward the BJP.
17 Mar 2023
TL;DR: In this paper , a mesh-free geometric multilevel (MGM) method for solving linear systems associated with meshfree discretizations of elliptic PDEs on surfaces represented by point clouds is presented.
Abstract: This dissertation focuses on meshfree methods for solving surface partial differential equations (PDEs). These PDEs arise in many areas of science and engineering where they are used to model phenomena ranging from atmospheric dynamics on earth to chemical signaling on cell membranes. Meshfree methods have been shown to be effective for solving surface PDEs and are attractive alternatives to mesh-based methods such as finite differences/elements since they do not require a mesh and can be used for surfaces represented only by a point cloud. The dissertation is subdivided into two papers and software. In the first paper, we examine the performance and accuracy of two popular meshfree methods for surface PDEs:generalized moving least squares (GMLS) and radial basis function-finite differences (RBF-FD). While these methods are computationally efficient and can give high orders of accuracy for smooth problems, there are no published works that have systematically compared their benefits and shortcomings. We perform such a comparison by examining their convergence rates for approximating the surface gradient, divergence, and Laplacian on the sphere and a torus as the resolution of the discretization increases. We investigate these convergence rates also as the various parameters of the methods are changed. We also compare the overall efficiencies of the methods in terms of accuracy per computation cost. The second paper is focused on developing a novel meshfree geometric multilevel (MGM) method for solving linear systems associated with meshfree discretizations of elliptic PDEs on surfaces represented by point clouds. Multilevel (or multigrid) methods are efficient iterative methods for solving linear systems that arise in numerical PDEs. The key components for multilevel methods: \grid" coarsening, restriction/ interpolation operators coarsening, and smoothing. The first three components present challenges for meshfree methods since there are no grids or mesh structures, only point clouds. To overcome these challenges, we develop a geometric point cloud coarsening method based on Poisson disk sampling, interpolation/ restriction operators based on RBF-FD, and apply Galerkin projections to coarsen the operator. We test MGM as a standalone solver and preconditioner for Krylov subspace methods on various test problems using RBF-FD and GMLS discretizations, and numerically analyze convergence rates, scaling, and efficiency with increasing point cloud resolution. We finish with several application problems. We conclude the dissertation with a description of two new software packages. The first one is our MGM framework for solving elliptic surface PDEs. This package is built in Python and utilizes NumPy and SciPy for the data structures (arrays and sparse matrices), solvers (Krylov subspace methods, Sparse LU), and C++ for the smoothers and point cloud coarsening. The other package is the RBFToolkit which has a Python version and a C++ version. The latter uses the performance library Kokkos, which allows for the abstraction of parallelism and data management for shared memory computing architectures. The code utilizes OpenMP for CPU parallelism and can be extended to GPU architectures.
17 Mar 2023
TL;DR: This article explored the intersection of recreation and wildlife conservation at Grand Canyon National Park through the lens of long-term occupancy of a threatened species, and evaluated the potential for autonomous recording units (ARUs) to complement current survey protocols.
Abstract: National Parks across America play an important role in protecting natural resources and providing access to recreation for visitors. However, these goals may come into conflict as visitation rates rise. Grand Canyon National Park in Northern Arizona is one of the most highly visited parks in the United States, with over 6 million visitors a year. Backcountry hiking and camping are popular activities in the park, and many highly visited hiking trails and campgrounds overlap with known breeding areas of a threatened species, Mexican Spotted Owl. In this thesis, I explore the intersection of recreation and wildlife conservation at this popular park through the lens of long-term occupancy of a threatened species. My aims are to (1) assess the potential impact of visitor use on long-term occupancy (2001 to 2021) of Mexican Spotted Owls at the Grand Canyon, and (2) evaluate the potential for autonomous recording units (ARUs) to complement current survey protocols. To assess long-term occupancy, I ran a multi-season occupancy model using 20-years of call-back survey data conducted in protected activity centers (PACs), along with measures of visitor use and habitat characteristics. To assess the use of ARUs, I ran a single-season occupancy model using three years of data, which was collected using autonomous recording units in PACs from 2019 to 2021. I found that visitor use in the Grand Canyon had no effect on owl occupancy, which remained stable across PACs over the 20-year study period. Owl occupancy remained high across the 20-year survey period and was strongly informed by habitat characteristics. Specifically, Mexican Spotted Owls occupied PACs with higher proportions of mixed shrubland habitat and Supai formation. Conversely, owl occupancy decreased in PACs with more pinyon-juniper woodland habitat and Redwall Limestone. Assessing the use of ARUs as a complement to current protocol, ARUs were found to be a useful tool for supplementing traditional call-back surveys, particularly at PACs with extremely limited access. In particular, ARUs detected Mexican Spotted Owls with high probability early in the breeding season prior to the official call-back survey period, which allows managers to extend their monitoring period. In highly remote PACs, ARUs were more suitable than call-backs because they could collect more data with less effort. Incorporating this method into Spotted Owl survey protocol may be essential for improving monitoring of under-sampled locations, which is a critical component for assessing long-term trends for this species across its range.
01 Jan 2023
TL;DR: Shiv Sena as discussed by the authors was the first political party to politicize religious and cultural identities in Maharashtra, which polarized Hindus and Muslims to beat the BJP at its own game by raising the pitch of its anti-minority rhetoric to show that it was more aggressive in protecting the Hindus than its ally and rival.
Abstract: If the AAP and TMC countered the BJP’s divisive propaganda by downplaying the Hindu-Muslim divide, then Shiv Sena polarized Hindus and Muslims to beat the BJP at its own game. Maharashtra has a long history of Hindu-Muslim composite culture, which prevented social polarization even as Hindu nationalism emerged in the region. Hindu-Muslim riots occurred in Maharashtra long before Shiv Sena’s rise. However, Shiv Sena was the first political party to politicize religious and cultural identities in Maharashtra. Shiv Sena pronounced its anti-Muslim stance as it tried to spread beyond Mumbai. Most importantly, Shiv Sena raised the pitch of its anti-minority rhetoric to show that it was more aggressive in protecting the Hindus than its ally and rival, the BJP.
17 Mar 2023
TL;DR: In this article , the authors combine textual features with user features to improve the state-of-the-art hate speech detection technique using BERT embeddings and linguistic features.
Abstract: Social media platforms provide users with a powerful platform to share their ideas. Using one’s right to expression to incite hatred toward a particular group of people is inappropriate. However, hate speech is pervasive in our society. Spreading hate through online social networks like Facebook, Twitter, Tiktok, and Instagram is commonplace in today’s milieu. One such case is the unprecedented COVID-19 pandemic, which engendered anti-Asian hate. In current literature, there is limited study on using user features in conjunction with textual features to detect hate. This thesis aims to combine textual features with user features to improve the state-of-the-art hate speech detection technique. To test our approach, we used four different datasets available in the public domain. We have used various tools to access Twitter APIs to extract required user information, either to use directly or further compute other features using that information. We have represented the textual features in the form of BERT embeddings and linguistic features. The 97 linguistic measures computed with a Linguistic Inquiry and Word Count (LIWC) tool quantify the text’s cognitive, affective, and grammatical processes. The user feature consisted of demographic, behavioral-based, emotion-based, personality, readability, and writing style features. Our experimental evaluation over three datasets shows that the top twenty linguistic features and the top twenty user features are the best combinations for hate speech detection. Hate speech is mostly emotionally charged. We further analyzed these user and linguistic features. Among the most intuitive and prominent results was that features like anger, negative emotion, swearing, fear, and annoyance were high in hate speech, while the happiness feature was low. We compared multiple approaches along with the existing state-of-the-art. We found that the best approach with textual features was combining LIWC features with BERT embeddings. This combination gave us the F1 of 0.82 and 0.79 on Crowd-sourced (DS1) and Kaggle (DS3), respectively. Followed by this, we identified the top LIWC and user features for hate speech detection. We found that features representing negative emotions like anger, fear, sadness, and annoyance were prominently high in hate speech. Happiness is lower in hate speech. After this, we analyzed the F1 scores with standalone LIWC and user features. We also used their combinations. We found that the combination of the top twenty LIWC and top twenty user features gives the best F1 scores of 0.74, 0.90, and 0.64 on DS1, NAACL (DS2), and anti-Asian Covid hate (DS4) dataset. Finally, we used traditional machine learning algorithms combining BERT embeddings with the top twenty linguistic features and the top twenty user features. We obtained the F1 scores of 0.78, 0.92, and 0.84 on DS1, DS2, and DS4 respectively. We also compared our approach with other studies using user and textual features.
TL;DR: In this article , the authors generalize Kauffman's famous formula defining the Jones polynomial of an oriented link in [Formula: see text]-space from his bracket and the writhe of a oriented diagram, and define an epimorphism between skein modules of tangles in compact connected oriented manifold with markings in the boundary.
Abstract: We generalize Kauffman’s famous formula defining the Jones polynomial of an oriented link in [Formula: see text]-space from his bracket and the writhe of an oriented diagram [L. Kauffman, State models and the Jones polynomial, Topology 26(3) (1987) 395–407]. Our generalization is an epimorphism between skein modules of tangles in compact connected oriented [Formula: see text]-manifolds with markings in the boundary. Besides the usual Jones polynomial of oriented tangles we will consider graded quotients of the bracket skein module and Przytycki’s [Formula: see text]-analog of the first homology group of a [Formula: see text]-manifold [J. Przytycki, A [Formula: see text]-analogue of the first homology group of a [Formula: see text]-manifold, in Contemporary Mathematics, Vol. 214 (American Mathematical Society, 1998), pp. 135–144]. In certain cases, e.g., for links in submanifolds of rational homology [Formula: see text]-spheres, we will be able to define an epimorphism from the Jones module onto the Kauffman bracket module. For the general case we define suitably graded quotients of the bracket module, which are graded by homology. The kernels define new skein modules measuring the difference between Jones and bracket skein modules. We also discuss gluing in this setting.
17 Mar 2023
TL;DR: In this paper , the authors describe the experience of 12 local leaders implementing an oral curriculum over 13 months in Karnataka, India, where they created audio materials referred to as content in their group's mother tongue: In a Kannada-Telegu mix for the Madiga group, in Vaagri Booli for the Hakkipikki group (a Scheduled Tribe), and in Kannadi for the Kannadiga group.
Abstract: This research documents the experience of 12 local leaders implementing an oral curriculum over 13 months in Karnataka, India. These leaders were Change Agents interested in influencing a community with new information. They created audio materials referred to as “content” in their group’s mother tongue: In a Kannada-Telegu mix for the Madiga group (a Scheduled Caste); in Vaagri Booli for the Hakkipikki group (a Scheduled Tribe); and in Kannada for the Kannadiga group. The first two languages are unwritten. The Kannada language is the official language of Karnataka state. The oral curriculum followed the Spoken Worldwide® model. Each team of local leaders designed their content by combining a topic, a local proverb, and an informative resource in story form. Next, the individual leaders facilitated discussion groups in their community centered on the content. Eighteen men were interviewed; this included six community discussion group members. The Connected Learning Framework was the conceptual lens for this research. It consists of four constructs—relationship, relevance, oral modes of communication, and mutual respect. Relationships played a primary role because the learners preferred to work with individuals they knew, or with individuals who were approved by the community’s leaders. Content that centered on what was relevant to community members was well-received by the listeners. The leaders used modes of communication that were familiar to community members by presenting content in the mother tongue and including local proverbs. By facilitating discussion after presenting the content, the leaders demonstrated mutual respect ensuring a multidirectional flow of information. This informed how the leaders created subsequent content. This research found that introducing new ideas, specifically Christian Scripture as a source of wisdom, was received positively by almost all audiences. In addition, the Team Leaders who had more experience using oral modes of communication, specifically telling Bible stories, and facilitating discussion were more consistent in implementing the Spoken process and principles and modeled the process during the content creation sessions with their Local Leaders or in presenting the content in their Leader’s gatherings. These leaders who had more experience with Connect Learning strategies were able to navigate further in the oral learning paradigm.
17 Mar 2023
TL;DR: In this paper , a commercial direct ink writing system (nScrypt microdispenser) was used to additively manufacture PVDF-trFE force sensors, and the resulting force sensors are used to measure the mechanical force with the resulting electrical charges or voltages.
Abstract: Piezoelectric poly(vinylidene fluoride-co-trifluoroethylene), or PVDF-trFE, builds up significant electrical charges on its surface when stressed. By correlating the mechanical force with the resulting electrical charges or voltages, researchers have developed flexible, broadband, and biocompatible force sensors. PVDF-trFE force sensors are traditionally fabricated via spin coating or solvent casting, which result in large waste production and experience difficulties in forming complex geometries. To tackle these challenges, I leveraged a commercial direct ink writing system (nScrypt microdispenser) to additively manufacture PVDF-trFE force sensors. I first synthesized an unprecedented piezoelectric ink that is compatible with a commercial ink writing system at Boise State University, specifically the nScrypt microdispenser, by dissolving PVDF-trFE powders into a cosolvent system consisting of methyl ethyl ketone and dimethyl sulfoxide. The ink composition and substrate surface properties were optimized simultaneously to ensure consistent and uniform printing. Postprocessing procedures, including air-drying, thermal curing, electrical poling and non-contact corona poling were then investigated to facilitate polymerization and beta phase transformation in the printed PVDF-trFE films. With the knowledge acquired from these investigations, I prototyped a piezoelectric force sensor consisting of printed PVDF-trFE films and printed silver electrodes. From justifying the methods for sensor fabrication, unprecedented prototypes of PVDF-trFE sensor arrays were investigated.
17 Mar 2023
TL;DR: The Book of Ela or Apokalypsis in Five acts as mentioned in this paper explores the layers of mental abstraction in which the human mind engages when thinking, and by extension, when writing.
Abstract: The Book of Ela or Apokalypsis in Five acts seeks first and foremost to investigate the layers of mental abstraction in which the human mind engages when thinking, and by extension, when writing. Writing and thinking do not end at the boundaries of genre. As such, I felt the styles therein should not stop at those boundaries either. Making use of influences such as Samuel Beckett, Virginia Woolf, Renee Gladman and Rosemarie Waldrop, I have endeavored to use narrative as a to form more fully and poetically explore the contours of language, and by extension, the contours of the mind. The project began with the investigation of character appearing in the text, known as the cartographer. The cartographer is strictly atemporal, and thus supersedes human consciousness. And yet, the cartographer’s existence presented itself as an ideal jumping off point from which to explore the many layers of consciousness that one immersed in such a continuum could never survey in full. Around the same time I was working on this character, I came across an article that reimagined Schrodinger’s famous thought experiment of the cat and the box with an additional layer. Now it was not only the cat, the box and the person opening the box that combined to collapse the wave function. This new configuration required a second observer watching from outside the room, observing not only cat and box, but observer. The question was: when in this scenario does the wave function collapse? This was endlessly fascinating to me, and I found myself thinking that since we are so many selves, this sort of dynamic unfolds within the bounds of consciousness in every decision we make.
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TL;DR: In this article , the authors trace the historical roots of the AAP's cultural posturing and examine the Aam Aadmi Party, TMC, and Shiv Sena to understand better how regional parties compete with the BJP's cultural nationalism.
Abstract: Historically, the overlaps between Hinduism and Islam bolstered the narrative that the Muslims were outsiders and culturally inferior to the Hindus and that Hinduism was India’s unifying tradition. The perspective described above still holds sway over many Hindus. As a result, for a large portion of the Hindu population, emphasizing the separateness of a minority group represents a threat to the nation’s integrity. With the rise of the Bharatiya Janata Party (BJP), Aam Aadmi Party (AAP), and Trinamool Congress (TMC), we witness a tussle between two variants of Hindu nativism. The BJP attempts to consolidate the Hindu vote by heightening the differences between Hindus and Muslims and portraying itself as the protector of national integrity. The AAP and the TMC revive a much older form of cultural nativism by downplaying the separateness of the Muslims, indicating that India is already a Hindu nation and that there is no need to persecute religious minorities. Although we examine the AAP, TMC, and Shiv Sena to understand better how regional parties compete with the BJP’s cultural nationalism, our primary goal is to trace the historical roots of the AAP’s cultural posturing.
TL;DR: In this article , the authors used infrasound sensors to detect the approach of hazardous volcanic mudflows, known as lahars, tens of minutes before their flow fronts arrive.
Abstract: Abstract Infrasound may be used to detect the approach of hazardous volcanic mudflows, known as lahars, tens of minutes before their flow fronts arrive. We have analyzed signals from more than 20 secondary lahars caused by precipitation events at Fuego Volcano during Guatemala’s rainy season in May through October of 2022. We are able to quantify the capabilities of infrasound monitoring through comparison with seismic data, time lapse camera imagery, and high-resolution video of a well-recorded event on August 17. We determine that infrasound sensors, deployed adjacent to the lahar path and in small-aperture (10 s of meters) arrays, are particularly sensitive to remote detection of lahars, including small-sized events, at distances of at least 5 km. At Fuego Volcano these detections could be used to provide timely alerts of up to 30 min before lahars arrive at a downstream monitoring site, such as in the frequently impacted Ceniza drainage. We propose that continuous infrasound monitoring, from locations adjacent to a drainage, may complement seismic monitoring and serve as a valuable tool to help identify approaching hazards. On the other hand, infrasound arrays located a kilometer or more from the lahar path can be effectively used to track a lahar’s progression.
17 Mar 2023
TL;DR: In this article , the authors examined how altruistic behavior toward different people (family, friends, strangers, or general altruistic acts) is preferred when considering potential short-term and long-term mates.
Abstract: Prior studies have attempted to establish how human altruism has evolved, including theories of kin selection, reciprocal altruism, and costly signaling. Recent investigations have explored the evolution of altruism as the result of sexual selection, where individuals may exhibit altruistic behavior because it is preferred by potential mates. In this study, I examine how altruistic behavior toward different people (family, friends, strangers, or general altruistic acts) is preferred when considering potential short-term and long-term mates. While previous research has examined this question using college-aged heterosexual participants, this study uses a more diverse sample, including individuals who identify as LGBTQ, those of varying ages, and those who identify as childfree. Seven hypotheses were tested to understand how preferences for altruistic behavior vary based on individual characteristics. An on-line survey was conducted and over 500 participants responded. Results show that women prefer potential mates who behave altruistically toward strangers more so than men; when examining long-term relationships, people prefer potential mates who behave altruistically toward family; and that an individual’s self-reported altruistic behavior is positively correlated with an individual’s preference for altruistic behavior in a mate. Surprisingly, some hypotheses were not confirmed. For instance, there is no difference between preferences for altruistic behavior in potential mates based on sexual orientation. When examining women’s preferences for altruistic behavior in potential mates based on reproductive status, I found that post-reproductive women have a greater preference for altruistic behavior that is directed toward strangers or general altruistic behavior as compared to reproductive aged women. The results of this thesis provide insights into the evolution of human altruism.
26 May 2023
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TL;DR: In this paper , the authors argue that moderate Hindus rejected Nehruvian secularism because it did not acknowledge Hindu supremacy and conclude that moderate Indians are ready to experiment with a decentralized, regional form of political Hinduism.
Abstract: We end the book by asking if Kejriwal and Banerjee’s victories indicate the rise of a new political perspective. Historians argue that the Hindus rejected Nehruvian secularism because it did not acknowledge Hindu supremacy. Could the Hindus have begun to move away from the BJP because the party’s attempts at creating a Hindu Rashtra smothers the regional variants of Hindutva? Do Kejriwal’s rise and Banerjee’s recent victory mean that the two experiments—Nehruvian secularism and cultural nationalism—have failed and that moderate Hindus are ready to experiment with a decentralized, regional form of political Hinduism? We intend to examine these questions in the next phase of our research.
17 Mar 2023
TL;DR: In this article , a qualitative phenomenological study investigated the experiences of a purposive sample of eight Learning and Development executives to understand the circumstances leading to, as well as the experiences implementing Digital Business Simulation Games (DBSG) in a corporate learning environment, specifically related to the financial service industry.
Abstract: This qualitative phenomenological study investigated the experiences of a purposive sample of eight Learning and Development executives to understand the circumstances leading to, as well as the experiences implementing Digital Business Simulation Games (DBSG) in a corporate learning environment, specifically related to the financial service industry. Their perception of the organizational needs, decision-making process of those involved, as well as the experience in design, development, and implementation may contribute to a better understanding of the circumstances within an organization where a DBSG would be an effective solution to achieve the development goals of learners within that organization. This study will also investigate the impact the implementation of the DBSG had on the organization, as well as provide further insight into best practices and critical success factors for future implementations. The research technique employed was a modified van Kaam method as described by Moustakas (1994) based upon transcribed interviews using semi-structured questions to capture the organizational needs, decision-making, and implementation experiences as well as perceptions of the participants. Five significant themes with two subthemes that emerged are prevalent from within the collected data from the participants: 1) needs intake and leadership support, 2) safe space to practice, 3) innovation on current curricula, 4) higher degrees of engagement, and 5) positive measurement results. The resulting analysis also led to considerable collection of best practices and critical success factors in deciding to undertake a DBSG program, and the design, development and implementation of a DBSG
01 Jan 2023
TL;DR: The political and cultural streams of Hindu nationalism had much in common; both embraced the unity in diversity doctrine as mentioned in this paper , however, because of their involvement in electoral politics, nationalist political parties, such as the Bharatiya Jana Sangh and Bharatiy Janata Janata Party, oscillated between valorizing India's unity and pursuing a divisive populist agenda.
Abstract: The political and cultural streams of Hindu nationalism had much in common; both embraced the unity in diversity doctrine. However, because of their involvement in electoral politics, nationalist political parties, such as the Bharatiya Jana Sangh and Bharatiya Janata Party, oscillated between valorizing India’s unity and pursuing a divisive populist agenda. For example, during the 2014 Lok Sabha election campaign, Narendra Modi rarely spoke of Hindu nationalism. Eager to distance himself from the 2002 communal riots in Gujarat, which took place under his watch, Modi focused on attacking the economic failures of the Congress government. In the 2019 election campaign, Modi relied on sowing communal divisions because he had very little to show on the economic front from his last term. Promising to protect India’s integrity from Muslims worked in BJP’s favor; the BJP won a majority in the Lok Sabha despite its poor performance.
01 Jan 2023
TL;DR: This paper examined the lived experiences of parents/guardians of teenagers who were recovering from a concussion and whose symptoms were persistent, and found that difficulties enforcing cognitive and physical rest, concerns about depression and isolation, observing struggles with athletic identity, feelings of frustration, helplessness, and stress, decisions about returning to sport, being lied to about symptoms, and offering strategies and practical advice.
Abstract: Sport-related concussions (SRCs) occur at alarming rates among adolescents and evidence suggests that adolescents experience more severe and longer-lasting symptoms compared to other age groups. Developmentally, adolescence is a time when youth become less reliant on their parents, establish their personal identity, and rely more on other social support networks (e.g., peers, teammates). However, previous studies show that parents play a prominent role in the recovery process from an SRC, especially in situations where recovery is prolonged. The purpose of this study was to examine the lived experiences of parents/guardians of teens who were recovering from a concussion and whose symptoms were persistent. Participants ( N = 12) were individually interviewed to better understand how they navigated and advocated for their teen during their prolonged recovery. An inductive content analysis revealed eight thematic categories that were interpreted with a developmental lens: (a) difficulties enforcing cognitive and physical rest, (b) concerns about depression and isolation, (c) observing struggles with athletic identity, (d) feelings of frustration, helplessness, and stress, (e) challenges of a hidden injury, (f) decisions about returning to sport, (g) being lied to about symptoms, and (h) offering strategies and practical advice. The themes illustrate how challenging and complicated the recovery process can be for parents of teenagers in particular, which is supported in previous concussion studies and the broader developmental literature. These results reinforce the idea that taking a biopsychosocial approach to care is best in order to adequately support parents/guardians and adolescents during the SRC recovery process.
TL;DR: The Streamflow Data Catalog as discussed by the authors is a streamflow catalog for the United States Pacific Northwest that includes current and historical streamflow monitoring location information obtained from 32 organizations (other than the U.S. Geological Survey), which includes 2661 continuous streamflow gaging locations and 30,557 discrete streamflow measurements.
Abstract: Streamflow data are critical for monitoring and managing water resources, yet there are significant spatial gaps in our federal monitoring networks with biases toward large perennial rivers. In some cases, streamflow monitoring exists in these spatial gaps, but information about these monitoring locations is challenging to obtain. Here, we present a streamflow catalog for the United States Pacific Northwest that includes current and historical streamflow monitoring location information obtained from 32 organizations (other than the U.S. Geological Survey), which includes 2661 continuous streamflow gaging locations (22% are currently active) and 30,557 discrete streamflow measurements. A stakeholder advisory board with representatives from organizations that operate streamflow monitoring networks identified metadata requirements and provided feedback on the Streamflow Data Catalog user interface. Engagement with the water resources community through this effort highlighted challenges that water professionals face in collecting and managing streamflow data so that data are findable, accessible, interoperable, and reusable (FAIR). Over 60% of the streamflow monitoring locations in the Streamflow Data Catalog are not available online and are thus not findable through web search engines. Providing organizations technical assistance with standard measurement procedures, metadata collection, and web accessibility could substantially increase the availability and utility of streamflow information to water resources communities.
TL;DR: This paper examined the influence of individual characteristics and organizational attributes in predicting burnout and turnover intent of federal probation officers across eight offices in a southern state, using survey data of federal POs (N = 80).
Abstract: In recent years, Western and non-Western countries have experience increased reliance on probation services. However, prior research indicates that high job demands and ambiguous role responsibilities invoke feelings of stress and suggest the importance of understanding the relationship between stress and burnout and turnover. While past efforts largely focused on correctional officers (COs), less is known about how probation officers (POs) experience burnout and how organizational attributes may influence this relationship. Using survey data of federal POs (N = 80) across eight offices in a southern state, the current study examines the influence of individual characteristics and organizational attributes in predicting burnout and turnover intent. To answer our research questions, we perform a series of linear regression models. Findings suggest the importance of affective commitment for reducing POs' feelings of burnout and turnover intent. Implications of these findings and directions of future research are discussed.
TL;DR: In this paper , the authors explore the possibility of making coherent exciton information processing devices, including quantum computers, and describe the chromophore arrangements needed to implement a complete set of gates that would enable universal quantum computation.
Abstract: Abstract DNA-based self-assembly enables the programmable arrangement of matter on a molecular scale. It holds promise as a means with which to fabricate high technology products. DNA-based self-assembly has been used to arrange chromophores (dye molecules) covalently linked to DNA to form Förster resonant energy transfer and exciton-based devices. Here we explore the possibility of making coherent exciton information processing devices, including quantum computers. The focus will be on describing the chromophore arrangements needed to implement a complete set of gates that would enable universal quantum computation.
TL;DR: This paper investigated the long-term impact on earnings of attending a tuition-free, top-quality university in Brazil and identified the causal effect through a sharp discontinuity in an admission process based on test scores.
17 Mar 2023
TL;DR: In this article , a deep learning approach is proposed to predict the chemistry and processing history of a material by reading the morphological distribution of one element, and the predicted chemistry and heat treatment temperature were in good agreement with the ground truth.
Abstract: The internal structure of materials also called the microstructure plays a critical role in the properties and performance of materials. The chemical element composition is one of the most critical factors in changing the structure of materials. However, the chemical composition alone is not the determining factor, and a change in the production process can also significantly alter the materials' structure. Therefore, many efforts have been made to discover and improve production methods to optimize the functional properties of materials. The most critical challenge in finding materials with enhanced properties is to understand and define the salient features of the structure of materials that have the most significant impact on the desired property. In other words, by process, structure, and property (PSP) linkages, the effect of changing process variables on material structure and, consequently, the property can be examined and used as a powerful tool in material design with desirable characteristics. In particular, forward PSP linkages construction has received considerable attention thanks to the sophisticated physics-based models. Recently, machine learning (ML), and data science have also been used as powerful tools to find PSP linkages in materials science. One key advantage of the ML-based models is their ability to construct both forward and inverse PSP linkages. Early ML models in materials science were primarily focused on process-property linkages construction. Recently, more microstructures are included in the materials design ML models. However, the inverse design of microstructures, i.e., the prediction of vii process and chemistry from a microstructure morphology image have received limited attention. This is a critical knowledge gap to address specifically for the problems that the ideal microstructure or morphology with the specific chemistry associated with the morphological domains are known, but the chemistry and processing which would lead to that ideal morphology are unknown. In this study, first, we propose a framework based on a deep learning approach that enables us to predict the chemistry and processing history just by reading the morphological distribution of one element. As a case study, we used a dataset from spinodal decomposition simulation of Fe-Cr-Co alloy created by the phase-field method. The mixed dataset, which includes both images, i.e., the morphology of Fe distribution, and continuous data, i.e., the Fe minimum and maximum concentration in the microstructures, are used as input data, and the spinodal temperature and initial chemical composition are utilized as the output data to train the proposed deep neural network. The proposed convolutional layers were compared with pretrained EfficientNet convolutional layers as transfer learning in microstructure feature extraction. The results show that the trained shallow network is effective for chemistry prediction. However, accurate prediction of processing temperature requires more complex feature extraction from the morphology of the microstructure. We benchmarked the model predictive accuracy for real alloy systems with a Fe-Cr-Co transmission electron microscopy micrograph. The predicted chemistry and heat treatment temperature were in good agreement with the ground truth. The treatment time was considered to be constant in the first study. In the second work, we propose a fused-data deep learning framework that can predict the heat treatment time as well as temperature and initial chemical compositions by reading the morphology of Fe distribution and its concentration. The results show that the trained deep neural network has the highest accuracy for chemistry and then time and temperature. We identified two scenarios for inaccurate predictions; 1) There are several paths for an identical microstructure, and 2) Microstructures reach steady-state morphologies after a long time of aging. The error analysis shows that most of the wrong predictions are not wrong, but the other right answers. We validated the model successfully with an experimental Fe-Cr-Co transmission electron microscopy micrograph. Finally, since the data generation by simulation is computationally expensive, we propose a quick and accurate Predictive Recurrent Neural Network (PredRNN) model for the microstructure evolution prediction. Essentially, microstructure evolution prediction is a spatiotemporal sequence prediction problem, where the prediction of material microstructure is difficult due to different process histories and chemistry. As a case study, we used a dataset from spinodal decomposition simulation of Fe-Cr-Co alloy created by the phase-field method for training and predicting future microstructures by previous observations. The results show that the trained network is capable of efficient prediction of microstructure evolution.
17 Mar 2023
TL;DR: ArtAB as discussed by the authors is an AB-type multimeric structure consisting of an enzymatically active subunit non-covalently situated atop of a non-toxic pentamer.
Abstract: Bacterial mono-ADP-ribosyltransferases (ARTs) catalyze the singular transfer of an ADP-ribose moiety from an NAD+ molecule onto a target molecule. ARTs contain an ancient and highly conserved tertiary structure and have a wide variety of intracellular targets and effects. Some, but not all, bacterial ARTs have an AB5-type multimeric structure consisting of an enzymatically active subunit non-covalently situated atop of a non-toxic pentamer. The active, or A, subunit of AB5-type toxins has a catalytic action that contributes to bacterial pathogenicity, and it is sometimes, but not always, an ART. ArtAB is an ART with AB5-type structure from the virulent and highly antibiotic resistant Salmonella Typhimurium DT104. In the studies described here, we tested the hypothesis that the active subunit of ArtAB is structurally and enzymatically homologous to that of the well-characterized AB5-type ART pertussis toxin. ArtAB was purified from E. coli and was used to characterize ArtAB’s cellular effects, predicted structure, and biophysical properties. In addition, a set of single-residue mutants was constructed and purified to probe ArtAB’s active site. AB5-type toxins have long been studied for their immunogenic properties, and some of these bacterial munitions have been harnessed and repurposed as vaccines or vaccine adjuvants to prevent infectious disease. Their receptor-binding pentamer, abbreviated as B5, binds to, and facilitates entry into, host cells. In additional work presented here, we tested the hypothesis that the B5 subunit of cholera toxin (CTB) from Vibrio cholerae could be used to construct a safe and effective mucosal vaccine against Staphylococcus aureus -caused mastitis. We constructed a bovine vaccine by conjugating Staphylococcus aureus antigens to the CTB-based adjuvant platform, and the immunogenicity of the vaccine was characterized in a bovine clinical trial. Finally, clinical isolates of caprine S. aureus were screened for the presence of surface antigens that could be use in a caprine version of the vaccine against mastitis. The work on bacterial AB5-type ARTs presented here contributes to a growing global understanding of the bacterial ART family, lays a foundation for the potential incorporation of ArtAB in a vaccine against Salmonella , and advances the development of bovine and caprine vaccines against S. aureus -caused mastitis.
17 Mar 2023
TL;DR: In this paper , the authors adopt the construct of tinkering, which is usually applied to the development of tangible artifacts and consider how this activity might apply to the developing of novel models and theoretical objects in science education.
Abstract: Tinkering and modeling have increasingly gained traction within science education. For this study, I adopt the construct of tinkering, which is usually applied to the development of tangible artifacts and consider how this activity might apply to the development of novel models and theoretical objects in science. Data was collected from student artifacts and coding of transcripts was performed to identify how students design models in science, with a focus on how students engage in tinkering when doing so. Using a multiple case study approach, I examined two cases of undergraduate pre-service science teachers’ development of models of light and color. The data shows that students can invent theoretical objects to productively model complex abstract scientific ideas. Examining these models revealed that students use many of the same tinkering processes-iteration, improvisation, playfulness, and shifting of emergent goals- as seen in tinkering in engineering, but students use theoretical objects (ideas) instead of tangible objects. Coding of student discussion further showed that students can tinker with theoretical objects in an iterative, playful, improvisational manner with shifting goals to refine and improve their models. Overall, including tinkering and modeling in the science classrooms creates a space where students can richly develop scientific ideas and novel models of scientific phenomena.
17 Mar 2023
TL;DR: In this article , the authors present a literature review on accessible and inclusive online course design in higher education and a qualitative study focusing on instructional designers' experiences, perceptions, and knowledge and skills related to accessibility and inclusion in online learning.
Abstract: The growth of online learning has expanded the reach of higher education to more diverse students than ever before; however, students often face barriers to equitable access to online instructional materials, course activities, and assessments. The challenge of meeting the needs of diverse learners was both highlighted and exacerbated during the COVID-19 pandemic and the rapid shift to remote teaching and learning at many institutions. Disabled students were one group that was particularly affected. Research has explored faculty and students’ (with and without disabilities) perceptions of online learning; however, less is known about instructional designers’ and their team leaders’ roles and perceptions of inclusive online course design. We posit that instructional designers are well-positioned to lead the charge in designing accessible and inclusive online courses that will better serve disabled students. Thus, this article-based dissertation presents three studies focused on accessible and inclusive online learning. Chapter one will introduce the research space and elaborate on the issues of accessible and inclusive online course design in higher education and the role that instructional designers and their team leaders play. Chapter two will present a literature review on accessible and inclusive online course design in higher education. The themes and gaps that emerged from the literature review led to the proposal of two qualitative studies. Chapter three is a qualitative exploration of online learning leaders’ (i.e., those who lead teams of instructional designers) perceptions of accessible and inclusive online learning. Leaders provided insight into the institutional and systemic barriers impacting instructional designers’ ability to collaborate in the creation of accessible and inclusive online learning experiences. Chapter four is a qualitative study focusing on instructional designers’ experiences, perceptions, and knowledge and skills related to accessible and inclusive online course design. These studies, when taken together, are intended to fill the gap in the literature about instructional design teams’ current and potential role in ensuring that diverse learners can effectively access, participate, and feel a sense of belonging in online higher education. Chapter five provides a synthesis of the findings from the three studies, explores the scholarly significance, and presents areas for future research.
17 Mar 2023
TL;DR: In this paper , the interactions between PFTs and specific membrane moieties as mediators of binding, oligomerization, and lysis were investigated. And the use of liposomes as target decoys for SLO and lysenin, capable of diminishing hemolysis in a concentration-dependent manner, was investigated.
Abstract: The investigations described in this work are focused on better understanding the interactions between pore-forming toxins (PFTs) and lipid membranes. The necessity of these investigations is justified by the important role of PFTs in infectivity and their potential impact on the development of alternative strategies for mitigating the global burden presented by infectious diseases and the onset of antimicrobial resistance. To achieve our scientific goals, we employed Red Blood Cells (RBCs) as a model for assessing the lytic action of two PFTs, Streptolysin O (SLO), and lysenin. To address the interactions between PFTs and specific membrane moieties as mediators of binding, oligomerization, and lysis, we employed spectrophotometrical assessments of hemolysis in conjunction with affinity measurements by the Kinetics Exclusion Assay (KinExA). The observation that SLO-induced hemolysis was gradually diminished upon cholesterol depletion even when the affinity of SLO for target membranes increased led to the conclusion that a slight reduction in the cholesterol content promotes binding but affects oligomerization into functional pores. Sphingomyelin depletion also led to a reduced hemolytic activity of lysenin but significantly diminished the barrier function of RBC membranes. Prompted by these results, we investigated the use of liposomes as target decoys for SLO and lysenin, capable of diminishing hemolysis in a concentration-dependent manner, which may constitute a complementary or alternative therapeutic approach for infectious diseases in which PFTs act as virulence factors. A direct comparison between the inhibitory effectiveness of monoclonal antibodies and liposomes for SLO clearance indicates the tremendous potential therapeutic applications presented by custom-designed liposomes for aiding in the world-wide fight against bacterial infections.
23 Jan 2023
15 May 2023
TL;DR: In this article , the authors used geophysics-informed hydrologic modeling to study the effect of snow-to-rain transition on hydrology partitioning in a snow-dominated mountainous catchment in Idaho, USA.
Abstract: In snow-dominated regions, snowmelt water plays a critical role in recharging the subsurface and generating streamflow. With a changing climate, the fraction of annual precipitation that falls as snow will probably decline. Rainfall and snowmelt water have different interactions with the subsurface and potentially vegetation, thus affecting the partitioning of precipitation into subsurface storage and streamflow. Currently, our understanding of how snow-to-rain transition affects this hydrologic partitioning in mountainous catchments is still limited. To take the best management practices for climate change adaptation, it is of critical importance to study how a catchment responds to such environmental disturbances.In this study, we use the geophysics-informed hydrologic modeling to study the effect of snow-to-rain transition on hydrologic partitioning in a snow-dominated mountainous catchment in Idaho, USA. In the modeling, the subsurface structure was extracted from velocity map obtained from seismic refraction tests. Many studies has highlighted the importance of the heterogeneous subsurface in water partitioning in catchments, but accurate characterizations with traditional field techniques such as drilling are challenging. The hydrologic model developed from geophysical results is then calibrated with historical hydrometeorological measurements. Two climate change scenarios are designed to study the impact of warming on streamflow generation and water storage. In Scenario 1, a uniform warming is considered throughout the year, and an air temperature increase (+2.5 °C) is applied to change the phase of precipitation. In scenario 2, warming is only applied to the snow season (i.e., from December to April). The numerical modeling results show that a uniform warming (scenario 1) significantly promotes evapotranspiration (ET), and streamflow becomes less productive. Warming in the snow season only (scenario 2) induces an earlier, flashier streamflow but the partitioning of precipitation between storage and streamflow is not significantly changed. Compared to simulation results from traditional hydrologic modeling (without the heterogeneous deep subsurface), geophysics-informed hydrologic modeling reveals the importance of water storage in the fractured bedrock in response to the climate change.