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Teacher Perceptions of Science Pedagogical Content Knowledge Obtained in an Educator Preparation Programs at a Middle Tennessee State University
No full textResearch states that elementary educators do not possess the adequate pedagogical content knowledge necessary to teach science effectively (Baumgartner, 2010; Lewis, 2017) The purpose of this mixed method study that took place at a public land-grant university in a large metropolitan city in the southern area of the United States was to gather the perceptions of both preservice (PST) and in-service educators on the pedagogical science content knowledge they received from the university. This study aimed to discover which aspects of the elementary educator preparation program, if any, needs to be modified to cultivate adequate pedagogical content knowledge needed to teach science effectively. The participants of this study answered survey questions that provided both quantitative and qualitative data. The results of the study suggest that less than 70% of participants felt prepared to teach science in the elementary classroom
Wildlife and Tick Responses to Forest Management: Prevalence of Tick-Borne Pathogens and Implications for One Health
No full textIn the United States human cases of tick-borne diseases have more than doubled over the past 15 years. This trend is expected to increase as medically important tick species and their host(s) expand in geographic range largely mediated by anthropogenic environmental disturbance, particularly land use change. The goal of this study was to evaluate the effects of land use change as it relates to forest management in the forms of prescribed fire and thinning on tick and small mammal communities, their associated microhabitat(s), and prevalence of tick-borne pathogens within a mixed hardwood/pine forest ecosystem. I also surveyed Sus scrofa for ticks and their associated pathogens to determine the role of a nonnative invasive wildlife host in influencing tick-borne disease risk within the study area evaluated. This project consisted of a control-impact, complete block design with a 2 x 3 factorial arrangement with three thinning levels applied (no thin, heavy thin, and light thin) and two burn applications (burn and no burn) resulting in six treatments with controls included (no thin and no burn) replicated three times resulting in a total of 18 research stands. From 1 June to 30 August, 2016–2019, I collected 50,736 ticks via drag sampling, 893 ticks from 54 hunter harvested Sus scrofa, and one tick from 269 live trapped small mammals at the William B. Bankhead National Forest, Alabama, US. Tick samples were comprised primarily of Amblyomma americanum, followed by Dermacentor variabilis, Amblyomma maculatum, Ixodes scapularis, and Rhipicephalus sanguineus. Using molecular methods, I identified presence of Rickettsia spp., Rickettsia amblyommatis, Rickettsia montanensis, Rickettsia parkeri, Candidatus Rickettsia andeanae, Ehrlichia chaffeensis, and Heartland Virus. I detected a significant interaction effect of burn with thin on A. americanum abundance with total adult counts decreasing in light thin with burn stands and total nymph counts decreasing in heavy thin with burn as well as light thin with burn stands. In addition, I found lower prevalence of Rickettsia spp. in ticks collected from light thin with burn stands as compared to ticks from heavy thin with burn and control stands. This study shows that prescribed burning in combination with thinning is not only an effective tool for managing A. americanum populations, but also potentially infection prevalence of Rickettsia spp. within mixed pine/hardwood forests in the southeastern US and therefore, has significant implications for human, animal, and forest healt
Robust feature space separation for deep convolutional neural network training
Get PDFThis paper introduces two deep convolutional neural network training techniques that lead to more robust feature subspace separation in comparison to traditional training. Assume that dataset has M labels. The first method creates M deep convolutional neural networks called {DCNNi}M i=1 . Each of the networks DCNNi is composed of a convolutional neural network ( CNNi ) and a fully connected neural network ( FCNNi ). In training, a set of projection matrices are created and adaptively updated as representations for feature subspaces {S i}M i=1 . A rejection value is computed for each training based on its projections on feature subspaces. Each FCNNi acts as a binary classifier with a cost function whose main parameter is rejection values. A threshold value ti is determined for ith network DCNNi . A testing strategy utilizing {ti}M i=1 is also introduced. The second method creates a single DCNN and it computes a cost function whose parameters depend on subspace separations using the geodesic distance on the Grasmannian manifold of subspaces S i and the sum of all remaining subspaces {S j}M j=1,j≠i . The proposed methods are tested using multiple network topologies. It is shown that while the first method works better for smaller networks, the second method performs better for complex architectures
Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review
Get PDFDisease diagnosis is one of the major tasks for increasing food production in agriculture. Although precision agriculture (PA) takes less time and provides a more precise application of agricultural activities, the detection of disease using an Unmanned Aerial System (UAS) is a challenging task. Several Unmanned Aerial Vehicles (UAVs) and sensors have been used for this purpose. The UAVs’ platforms and their peripherals have their own limitations in accurately diagnosing plant diseases. Several types of image processing software are available for vignetting and orthorectification. The training and validation of datasets are important characteristics of data analysis. Currently, different algorithms and architectures of machine learning models are used to classify and detect plant diseases. These models help in image segmentation and feature extractions to interpret results. Researchers also use the values of vegetative indices, such as Normalized Difference Vegetative Index (NDVI), Crop Water Stress Index (CWSI), etc., acquired from different multispectral and hyperspectral sensors to fit into the statistical models to deliver results. There are still various drifts in the automatic detection of plant diseases as imaging sensors are limited by their own spectral bandwidth, resolution, background noise of the image, etc. The future of crop health monitoring using UAVs should include a gimble consisting of multiple sensors, large datasets for training and validation, the development of site-specific irradiance systems, and so on. This review briefly highlights the advantages of automatic detection of plant diseases to the growers
Ex Vivo High Salt Activated Tumor-Primed CD4+T Lymphocytes Exert a Potent Anti-Cancer Response
Get PDFCell based immunotherapy is rapidly emerging as a promising cancer treatment. A modest increase in salt (sodium chloride) concentration in immune cell cultures is known to induce inflammatory phenotypic differentiation. In our current study, we analyzed the ability of salt treatment to induce ex vivo expansion of tumor-primed CD4 (cluster of differentiation 4)+T cells to an effector phenotype. CD4+T cells were isolated using immunomagnetic beads from draining lymph nodes and spleens from tumor bearing C57Bl/6 mice, 28 days post-injection of Py230 syngeneic breast cancer cells. CD4+T cells from non-tumor bearing mice were isolated from splenocytes of 12-week-old C57Bl/6 mice. These CD4+T cells were expanded ex vivo with five stimulation cycles, and each cycle comprised of treatment with high salt (Δ0.035 M NaCl) or equimolar mannitol controls along with anti-CD3/CD28 monoclonal antibodies for the first 3 days, followed by the addition of interleukin (IL)-2/IL-7 cytokines and heat killed Py230 for 4 days. Ex vivo high salt treatment induced a two-fold higher Th1 (T helper type 1) expansion and four-fold higher Th17 expansion compared to equimolar mannitol treatment. Importantly, the high salt expanded CD4+T cells retained tumor-specificity, as demonstrated by higher in vitro cytotoxicity against Py230 breast cancer cells and reduced in vivo syngeneic tumor growth. Metabolic studies revealed that high salt treatment enhanced the glycolytic reserve and basal mitochondrial oxidation of CD4+T cells, suggesting a role of high salt in enhanced pro-growth anabolic metabolism needed for inflammatory differentiation. Mechanistic studies demonstrated that the high salt induced switch to the effector phenotype was mediated by tonicity-dependent transcription factor, TonEBP/NFAT5. Using a transgenic murine model, we demonstrated that CD4 specific TonEBP/NFAT5 knock out (CD4cre/creNFAT5flox/flox) abrogated the induction of the effector phenotype and anti-tumor efficiency of CD4+T cells following high salt treatment. Taken together, our data suggest that high salt-mediated ex vivo expansion of tumor-primed CD4+T cells could induce effective tumor specific anti-cancer responses, which may have a novel cell-based cancer immunotherapeutic application
A Data Analytics Study for Adverse Reactions of Blood Donors by Age, Gender, and Donation Type
Get PDFThe blood donation process is usually very safe, and blood donors are comfortable during the blood donation procedure; however, blood donors occasionally experience various types of adverse reactions during or at the end of blood donation. Some of these reactions are very minor while blood donors sometimes experience serious reactions as well. This study aims to analyze the various types of adverse reactions experienced by the blood donors. The study conducts detailed analysis on a significant amount of real data collected through a blood organization in the southern part of the United States and provides the results regarding the frequency and types of adverse reactions based on multiple attributes such as age, gender, and donation type
