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Metabolic Inhibitor Effects on Eyespot Formation in Regenerating Planaria
Get PDFPlanaria are flatworms known for their remarkable ability to regenerate. Glycolytic activity has been shown to increase during planarian regeneration (Osuma et al., 2017) and regeneration requires both an increase in mitotic activity and an increase in apoptotic activity to successfully regrow missing structures (Pellettieri et al., 2010; Wenemoser & Reddien, 2010). The objectives of this study are to determine if metabolic inhibitors affect the time needed to regenerate eyespots after head amputation as a measurement of regeneration and if there are any correlations between average numbers of mitotic and apoptotic cells in regenerating planaria in the presence or absence of metabolic inhibitors. Planaria (D. dorotocephala and D. tigrina) were exposed to non-lethal doses of metabolic inhibitors after amputation between the head and the pharynx to determine if metabolic inhibitors affect eyespot regeneration times. Mucus removal, fixation, and bleaching were used to prepare planaria for immunolabeling procedures. Mitotic cells were labeled to determine if metabolic inhibitors affect average numbers of mitotic cells in regenerating planaria. Immunolabelling procedures were used in an attempt to visualize apoptotic cells in planaria. Results from the exposure experiments suggest that the earlier planaria are exposed to metabolic inhibitors after amputation, the longer it takes to regrow eyespots. By comparing the average number of mitotic cells planaria in the presence or absence of metabolic inhibitors, it was determined that delays in eyespot formation are not associated with changes in the average number of mitotic cells. Further studies should be conducted to test for significant differences between apoptotic cells in inhibitor-treated and untreated planaria
The Impact of Using Trauma-Informed Practices in Public Schools in Early Childhood Education
Get PDFThis study is vital due to the need for trauma-informed practices to be incorporated holistically into early childhood education settings. Children who have experienced trauma frequently have behavioral, social emotional, and academic challenges. Providing trauma-informed practices within early childhood education would allow students who have experienced trauma to receive the support they need to benefit from the education system. This study examines the impact of childhood trauma on social emotional learning experiences and academic outcomes. This study further examines those trauma-informed practices being used in early childhood settings as well as their impact in mitigating retraumatization of young children. The results of this study will help early childhood educators create and apply appropriate learning environments designed to resist retraumatization for children who have experienced trauma so they can make academic and social emotional gains
Treasury Bond and Corporate Bond Spread as an Indicator of Economic Activity
Get PDFBonds spread has been recognized as a strong indicator of future economic growth. Forecasting economic growth with spread is simpler compared to other measures. This paper focuses to study the usefulness of the spread between Treasury Bonds and High-Quality Corporate Bonds in predicting US economic growth, its accuracy between the years 1999 and 2021, and comparison with the traditional yield curve. By analyzing the relationship between different spreads and Industrial production index frequently used for observing and analyzing current economic performance, the results indicate that the traditional spreads such as 10Year–3Month and 10Year–2Year are not very accurate predictors of economic activity, while the new spread between Treasury Bonds and High-Quality Corporate Bonds can predict the economy.
Keywords: Spread, Industrial Production, Economic Growth, Yield Curve
Comparing a Hybrid Multi-layered Machine Learning Intrusion Detection System to Single-layered and Deep Learning Models
Get PDFAdvancements in computing technology have created additional network attack surface, allowed the development of new attack types, and increased the impact caused by an attack. Researchers agree, current intrusion detection systems (IDSs) are not able to adapt to detect these new attack forms, so alternative IDS methods have been proposed. Among these methods are machine learning-based intrusion detection systems. This research explores the current relevant studies related to intrusion detection systems and machine learning models and proposes a new hybrid machine learning IDS model consisting of the Principal Component Analysis (PCA) and Support Vector Machine (SVM) learning algorithms. The NSL-KDD Dataset, benchmark dataset for IDSs, is used for comparing the models’ performance. The performance accuracy and false-positive rate of the hybrid model are compared to the results of the model’s individual algorithmic components to determine which components most impact attack prediction performance. The performance metrics of the hybrid model are also compared to two deep learning Autoencoder Neuro Network models and the results found that the complexity of the model does not add to the performance accuracy. The research showed that pre-processing and feature selection impact the predictive accuracy across models. Future research recommendations were to implement the proposed hybrid IDS model into a live network for testing and analysis, and to focus research into the pre-processing algorithms that improve performance accuracy, and lower false-positive rate. This research indicated that pre-processing and feature selection/feature extraction can increase model performance accuracy and decrease false-positive rate helping businesses to improve network security
Blight
Get PDFFractured relationships can spread as a different type of disease. This poem gives voice to a narrator entangled in relational strain following trauma.
Author bio: Rosanna M. Vail is the managing editor of a scientific journal and is pursuing a doctoral degree in technical communication and rhetoric from Texas Tech University
The Monsters Who Raise Us: Unearthing the Haunted Institution of Motherhood
Get PDFThis research examines the political, cultural and legal systems of the contemporary United States that turn mothers into monsters. Through the modes of embodied research and dance choreography, this research explores the incredibly powerful, conflicting emotions, desires and impulses that mothers are compelled to sanitize or repress to align with codes of civility. The lack of access to reproductive medical care, minimal maternity leave policies, and the constructs of default parenting demonstrate that little of the expectations of motherhood have changed over the past century. Using personal, embodied experience as a new mother alongside Adrienne Rich’s institution of motherhood, Eve Tuck’s conception of Monsters and Avery Gordon’s notions of Hauntings, Chin examines the ways in which anxiety, guilt, shame, trauma and unmet societal expectations haunt mothers and over time, create monsters. Using mass distributed American horror films as an additional point of departure, this research explores the impact of embedded cultural expectations of suppressing feminine rage and the lauding of unsustainable self-sacrifice of mothers in deference to their children. The research is synthesized through physical movement that explores the interplay between monstrous, uncanny movements and touches of comfort and support. The choreographic process draws on historical dance references of rageful, ghostly feminine figures, such as Petipa’s willis from Giselle, as well as the recollection of Chin’s first-hand experiences gestating, birthing and sustaining a small child. The performance iteration of this process was performed by a cast of 9 dancers at the University of Illinois Urbana-Champaign in January 2023 at the Krannert Center for Performing Arts
A Multicultural Approach to Education in Early Childhood Pedagogy
Get PDFThe focus point of this study is intended to determine the dimensions of a multicultural approach to curriculum and instruction specifically in early childhood education. Additionally, throughout this study, the ways that technology has enhanced education are looked at and compared in relation to the recent advances and changes in education. Incorporating any of the dimensions of multiculturalism, or any fundamental ideas serve various benefits for students both inside the classroom and out. Implementing appropriate strategies prepares students to live and survive in a diverse world. We are able to do this by teaching them essential life skills, starting with their ‘experiences’ inside the classroom, which in reality are the culturally dense lessons we present to our students
Use of an Interdependent Group Contingency to Decrease the Off-Task Behavior of a Special Education Student
Get PDFOff-task behavior of an individual student can impact the behavior of a class. Group contingencies are an effective behavior management procedure to reduce disruptive behavior and increase academic engagement of a classroom. This study investigated the effects of an interdependent group contingency on the off-task behavior of a special education student. A multiple-baseline design was used to examine whether the intervention could decrease the rate of inappropriate vocalizations and off-task technology use of an individual student as well as their class peers. The interdependent group contingency reduced inappropriate vocalizations by 60.49% for the target student and 62.52% for the class. Off-task technology use was decreased for the target student and their peers by 72.31% and 76.27% respectively. In addition, a correlated increase in academic engagement was observed for the target student and the class once the procedure was fully applied to both target behaviors. The findings suggest the interdependent group contingency reduced off-task behavior of a special education student and increased their academic engagement while further providing an overall reduction in disruptive behavior of the classroom
Candidates\u27 modification of global perspectives via international teaching: A case study
Get PDFI investigated U.S. elementary teacher candidates’ global perspectives before and after completing a student teaching experience in the People’s Republic of China (PRC). The samples, four elementary teacher candidates (TCs), purposely selected for the present study, completed student teaching in a Primary School in Xian, PRC, because they all come from Midwestern-culture family, complete teacher preparation course work, and are ready to do student teaching. I employed math lessons in this exploration of TCs’ global perceptions, looking for modifications; my primary interest was in potential changes from provincial to more refined perspec- tives. It is worth noting that the questions may have may have communicated expectations that such changes would occur. Interviews and class observations were collected from the four candidates and analyzed by means of an axial coding process across the four candidates. Results demonstrated that pre-service teachers change from what I termed a “local” (or what might be termed “parochial)” perspective to more “global” views of schooling and culture. The four teacher candidates evinced this new sophisticated understanding along three axes, (1) the global cognitive development, (2) the social strategies change under different physical environments, and (3) noticing and appreciating cultural divergence. An evolving sense of justice appeared to connect the three concepts. A tangentially connected issue that came up, as might be expected, was the vulnerability of candidates’ foreign communication skills. TCs’ effectively developed their global perspectives in teaching math lessons and suggest that math or STEM may be better for acquiring global perspectives than are either social studies or language arts
Modeling Brain Using Parameters of Passive Electrical Circuits
Get PDFBrain is the central and most complex organ in the human body. It controls most of the body functions, processing, integrating, and coordinating the information it receives from the organs, and sending decision instructions to the rest of the body. Brain injury may occur due to external environmental and/or internal influences. Timely diagnosing and differentiating the type of brain injury is critical. CT and MRI are often used for the diagnosis, which may not be available at a remote location or at an accident site or an emergency vehicle.
This thesis contributes to the modeling of the brain from the electrical point of view, considering the structural complexity of the head composed of biological tissues with different dielectric properties. The goal of the thesis is to develop electrical models of the brain using parameters of passive electrical circuits. The models are developed for a normal brain and a brain with pathological conditions such as edema (swelling) and hemorrhage (bleeding). The circuit models are simulated at a range of frequencies from 1 Hz to 200 kHz. The experiment data is collected on a sheep brain surrounded by phantom tissue using bioimpedance analyzer at a range of frequencies from 1 Hz to 200 kHz. The simulation results are compared with experiment data