26400 research outputs found
Sort by
Investigating the roles of plants, fungi, and biocrusts in nutrient movement within dryland ecosystems
Get PDFIn dryland ecosystems, plant productivity and microbial decomposition are often separated in space and time due to the asynchronous availability of soil moisture and organic matter inputs. It has been proposed that fungi play a key functional role in connecting these cycles by facilitating movement of water, carbon (C), and nitrogen (N) through a network of shared hyphae between plant roots and biological soil crust (biocrust) communities at the soil surface. This connection, also known as the â??fungal loop,â?? effectively re-couples processes of nutrient release and uptake between primary producers and minimizes ecosystem N losses due to leaching, erosion, and gaseous pathways. However, direct support for the existence of these nutrient exchanges and for the importance of fungal networks in dryland biogeochemical cycles remains scarce. In this dissertation, I addressed several direct and indirect lines of evidence underlying the fungal loop hypothesis, described in the following chapters: Ch. 2 presents a greenhouse study comparing foliar recovery and uptake of inorganic and organic N forms applied to roots of three dryland plant species and summarizes our current ecological understanding of dryland plant N uptake rates and methods of quantification; Ch. 3 identifies the abundance, composition and similarity of fungal communities in both biocrust soils and roots of black grama (Bouteloua eriopoda) and compares the responses of biocrust and root-associated fungi to different global change factors; and Ch. 4 attempts to isolate the role of fungi in nutrient translocation of N between biocrust soils and plants by impeding fungal connections to plant roots and evaluating the conditions affecting N uptake from biocrust soils to plant leaves. My findings from Ch. 2 demonstrate that dryland plants with different growth requirements can take up both inorganic and organic soil N within 12-48 hours, and there is little evidence for N niche specialization among nutrient-limited plants in this habitat. Results from Ch. 3 illustrate the relative dissimilarity of biocrust and root-associated fungal communities, the potential sensitivity of root fungal diversity to N fertilization, and the reordering of biocrust fungal communities under increased precipitation variability and combined inputs of water and N inputs. Findings from Ch. 4 did not support the central importance of fungal connections to rapid N transfer through surface soils, as we found that plant 15N uptake was not inhibited by neither fungal exclusion mesh treatments nor surface soil barriers, and significant movement was only observed after 3-10 days. We conclude that (i) nutrient uptake can occur rapidly (\u3c 24 h) in co-occurring dryland plant species following application of water and N to the roots, (ii) there are taxonomically diverse and abundant saprotrophic fungi in biocrust soils, and functionally distinct, symbiotrophic taxa in plant roots that may have differential responses to fluctuations in N and water inputs in this system, and (iii) N transfers from surface biocrusts to plant leaves are fairly rare at the ~0.5 m2 scales we tested, and relatively slower rates of nutrient movement into plants could be driven by soil diffusion and plant root uptake processes, rather than active fungal facilitation. Overall, I did not find strong direct or indirect evidence supporting the occurrence of fungal-mediated nutrient exchanges in this semiarid grassland; however, I did gain a clearer picture of the diversity, composition, abundance and potential trophic roles of dryland fungi and the potential mechanisms underlying N translocation through soils and biotic pools. Cultivating a better understanding of the relationships between short-term nutrient uptake, soil and plant microbes, and soil nutrient movement in dryland has important implications for understanding patterns and mechanisms of nutrient cycling and retention in these globally important ecosystems
The New Management Accounting Ecosystem: A Retrospective View and Path to the Future
Get PDFIn this paper we argue that management accounting research should seek to expand to examine the broader ecosystem of information sources that influence organizational performance. We introduce the concept of the management accounting ecosystem as a means of linking discrete management accounting research topics to the broader environment in which organizations operate. By doing this, we can better bridge the gap between management accounting research and management accounting practice. Our goal is to encourage more cross-disciplinary research that provides a better understanding of the ecosystem in which management accounting practitioners operate. We encourage researchers to submit studies to “Advances in Management Accounting” that evaluate the effectiveness of new management accounting information sources and the techniques used to analyze them in the broader ecosystem to enhance the effectiveness of management accounting practices. By exploring the wider information sources within the management accounting ecosystem, future management accounting research can become more innovative and better address the decision-making needs of organizational members
Regional Commercial Bank Lending to Small Businesses in the Wake of the Great Recession
Get PDFThe purpose of this paper is to document and explain the state by state variation in commercial bank lending to small businesses during the Great Recession. To accomplish this purpose will require several steps. These steps include showing the evidence of the variation in lending across states, the theoretical causes and the empirical findings of a capital supply gap based on market imperfections and employing OLS estimation method on carefully selected economic variables. The empirical results indicate that economic conditions, borrower characteristics and lender characteristics influence lending variation where these results can help in policy formulation
How Difficult Is It to Comprehend a Program That Has Significant Repetitions: Fuzzy-Related Explanations of Empirical Results
No full textIn teaching computing and in gauging the programmers\u27 productivity, it is important to property estimate how much time it will take to comprehend a program. There are techniques for estimating this time, but these techniques do not take into account that some program segments are similar, and this similarity decreases the time needed to comprehend the second segment. Recently, experiments were performed to describe this decrease. These experiments found an empirical formula for the corresponding decrease. In this paper, we use fuzzy-related ideas to provide commonsense-based theoretical explanation for this empirical formula
Number Representation With Varying Number of Bits
No full textIn a computer, usually, all real numbers are stored by using the same number of bits: usually, 8 bytes, i.e., 64 bits. This amount of bits enables us to represent numbers with high accuracy -- up to 19 decimal digits. However, in most cases -- whether we process measurement results or whether we process expert-generated membership degrees -- we do not need that accuracy, so most bits are wasted. To save space, it is therefore reasonable to consider representations with varying number of bits. This would save space used for representing numbers themselves, but we would also need to store information about the length of each number. In view of this, the first natural question is whether a varying-length representation can lead to a drastic decrease in needed computer space. Another natural question is related to the fact that while potentially, allowing number of bits which is not proportional to 8 bits per byte will save even more space, this would require a drastic change in computer architecture, since the current architecture is based on bytes. So will going from bytes to bits be worth it -- will it save much space? In this paper, we provide answers to both questions
Assessing Nordihydroguaiaretic Acid Properties and Its Potential Therapeutic Effect for Glioblastoma
No full textThis study employs a combination of theoretical and experimental analysis to spectroscopically investigate the biomechanistic structure relationship and therapeutic effects of the Nordihydroguaiaretic Acid (NDGA) chemical derived from the Larrea Tridentata plant. These relationships are crucial for understanding NDGA\u27s efficacy in disease prevention, treatment, and potential toxicological effects. While the medicinal and antiviral properties of the NDGA have been studied extensively, there remains a gap in optically identifying and reporting its structural changes. The current research successfully reveals evident trends in NDGA\u27s vibrational signatures, particularly highlighting the absence of the Raman feature at 780 cm-1 as indicative of a fully oxidized structural form contributing to its bio-toxicity alongside ortho-quinone accumulation. Additional characteristic signatures of these toxic forms include the Raman lines at 1582 and 1698 cm-1 and the IR vibrational line at 1680 cm-1. By elucidating these morphological changes, this study offers valuable insights for the development and implementation of new drugs. Connecting evidence in supporting this statement is the second part of the study, where the NDGA was used for glioblastoma (GBM) treatment. Again, combined experimental Raman and statistical analyses were implemented to detect the drug effect on GBM-treated human cells.As a potential therapeutic agent, NDGA is a reactive oxygen species (ROS) scavenger and antioxidant. This phenolic lignan had positive effects on multi-organ malignant tumor reduction and inhibition. Although the drug concentrations were beyond the Raman capability limit of their detection, the results show a decrease in altered protein content and ROS-damaged phenylalanine upon NDGA administration. The use of phenylalanine as a biomarker for differentiating across samples and evaluating NDGA\u27s effectiveness is a new finding discussed here. The creation of lipid droplets and a decline in the altered protein content indicate that treatment with a low dosage of NDGA over long periods reduces abnormal lipid-protein metabolism. The knowledge acquired via this research is significant for comprehending both the positive and negative bio-effects of NDGA as a potential treatment for brain cancer
El testimonio de los niños de el parque: Discipline Practices and the Impact on Public High School Students
No full textWhat happens to our students when they do not complete their studies and drop out of school? Perhaps this question is probably not something that we reflect on as educators. This study seeks to amplify three students’ voices and explore their unique experiences and the challenges they faced after they did not complete their high school studies. The interviews that I conducted tell the story of three minority students from lower-income families. Their stories highlight the overall purpose of this study, which is how students who find themselves involved in disciplinary issues are pushed out of school. The interviews capture the lived experiences as well as the resilience of these individuals. My research question focuses on understanding the personal and systemic challenges that marginalized youth face and how they navigate and make sense of the obstacles in their daily lives. I used qualitative and Testimonio methodology involving semi-structured interviews. The students’ lives are similar in that they are affected by socio-economic disadvantages and racial and ethnic marginalization. The interview protocol was designed to offer a safe and respectful environment to ensure that the participants shared their stories and perspectives openly. These interviews provided a rich collection of narratives that revealed significant insights into the adversities faced by these students, such as discrimination, limited access to resources, and social exclusion. The findings from my study not only shed light on the needs and challenges of these kids but also highlight the need for the development of all-encompassing strategies and supportive policies that can support students’ well-being and provide opportunities for them to complete their studies at the secondary level. My research contributes to a broader understanding of the intersectionality of disadvantage and resilience, offering guidance to educators, policymakers, and community stakeholders to better support vulnerable populations
Dynamic Storytelling Algorithms Using Contextual Aspects of a Large Language Model
No full textStorytelling is a set of algorithms used to create narratives by connecting documents in a sequence that accurately reflects the evolution of events and entities within a particular topic or theme. Early storytelling algorithms face challenges in encoding the progression and interconnections of information between consecutive texts, given that the conventional approaches rely primarily on connecting document pairs based on content overlap. They often neglect critical linguistic features, such as word contexts, semantics, the roles words play across different documents, and attention to the historical contexts of the underlying documents. Many existing storytelling models frequently produce story chains that, while connected by keywords, lack meaningful coherence in the chains. My dissertation introduces innovative LLM-driven storytelling algorithms to overcome the challenges traditional storytelling algorithms face and significantly enhance downstream tasks.In my research, I propose a role-based contextual embedding algorithm using a large language model that provides a rich understanding of text in a document by considering the different roles of the same word in other documents. I also employ a generative diffusion model to seamlessly link documents within a narrative, even with gaps in the data, to ensure a smoother and more logical story progression. In my dissertation, I introduce a novel distributed attention similarity mechanism designed to control the narrative output of storytelling algorithms locally and globally. The techniques I have designed ensure that the generated stories are not merely connected by keywords but are also coherent and meaningfully sequenced. The experiments in my dissertation indicate that the proposed storytelling models generate more coherent, cohesive, and contextually rich narratives than existing approaches. In addition, I demonstrate that my proposed storytelling model has immense potential in vector data preparation for conventional machine-learning tasks
Biofabrication of Human Tissue-on-a-Chip Models Using Engineered Biocompatible Electrospun Scaffolds
No full textThis study explored the adoption of furfuryl gelatin (F-gelatin) based electrospun scaffolds compared with poly-caprolactone (PCL) as promising biomaterials for tissue engineering applications. Tissue-on-a-chip models, incorporating F-gelatin and PCL electrospun scaffolds, offer promising avenues for healthy and disease-in-vitro tissue models that can be explored to investigate underlying physiological mechanisms involved in disease development. Previous research has demonstrated the cytocompatibility of F-gelatin when used for modifying implant surfaces and tissue repair applications. Our earlier published works have also successfully utilized F-gelatin for in-vitro cardiac tissue engineering. We designed F-gelatin and PCL electrospun scaffolds to replicate the native tissue extracellular matrix (NT-ECM) environment. Additionally, we hypothesized that blending the hydrophilic F-gelatin with hydrophobic PCL would result in mechanically robust scaffolds capable of supporting the retention and viability of cells, essential for establishing a successful in-vitro tissue model. Since the electrospinning method offers versatility in controlling fiber alignment and composition, allowing for the generation of scaffolds that closely resemble the NT-ECM, we aim to optimize the electrospinning parameters to yield scaffolds that possess excellent mechanical fidelity, biocompatibility as well as the ability to sustain long-term culture periods. Specifically, we will study the effects of optimizing electrospinning parameters such as rotational speed, deposition distance, and voltage to evaluate their impact on the resultant scaffolds. Two collection speeds, static (0 RPM) and dynamic (\u3e100 RPM), will be compared to assess their effects on scaffold fiber alignment as well as orientation and its correlation with the scaffold’s biological properties.To facilitate these experiments, we have developed an in-house electrospinning system capable of recording the various electrospinning parameters via an Arduino setup, which has led to reliable and reproducible results for tissue engineering applications. Samples will be characterized for mechanical fidelity via SEM (Scanning Electron Microscopy), FTIR-ATR (Fourier-Transform Infrared – Attenuated Total Reflectance), and DMA (Dynamic Mechanical Analysis). Finally, three different applications will be developed using these scaffolds, including their use in 1) seeding and differentiation of neural progenitor cells for studying neurodegenerative diseases, 2) for the development of cardiac cell models to study the onset of diabetes, and 3) adoption in tissue on-a-chip models to be tested under microgravity and other extreme environmental conditions. Overall, this project contributes to developing novel NT-ECM for biocompatible human tissue-on-a-chip models via the biofabrication of electrospun scaffolds