Transitioning to a Personalized Learning Environment Leveraging One-to-One Devices

Today’s educational blueprint is evolving from the traditional teacher-directed model into a student-driven curriculum approach. Specifically, education is experiencing a paradigm shift from the long-established one-size-fits-all model to a customized learning process known as personalized learning. Personalized learning aims at engaging students in more relevant and rigorous learning and turns them into co-designers as the curriculum becomes tailored to their individual learning needs, skills, and interests. Additionally, when coupled with educational technology, personalized learning will provide the teacher with the tools to individualize, differentiate, and accommodate multiple student learning styles and preferences. Indeed, as personalized learning increases in popularity the need to effectively implement the new instructional model also increases. Moreover, it is imperative to understand how the roles of teachers and administrators change as schools’ transition from a traditional learning paradigm to a personalized learning approach influenced by one-to-one devices, and how these changes affect implementation. Therefore, the aim of this research was to explore the perceptions of administrators and teachers as they transition from a traditional learning paradigm to a personalized learning model influenced by one-to-one devices

Potential for tsunami detection and early-warning using space-based passive microwave radiometry

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 141-150).The threat of a tsunami in coastal communities is considerable, especially in the Pacific and Indian Oceans. Current warning systems consist of two networks: (1) a network of seismometers, and (2) a network of sea level gauges and bottom pressure recorders. Bottom pressure recorders communicate with ocean surface buoys, which send the data to processing centers through satellite communication uplinks. The ability to quickly and accurately detect a tsunami in the deep ocean is proposed using a new space-based passive microwave radiometer system. Passive microwave radiometry can detect oceanic parameters such as sea-surface temperature and sea surface roughness to contribute to earlier tsunami detection, when the tsunami is farther from shore, which will increase the reaction time for at-risk coastal communities. This thesis will outline a physics based approach to manipulating brightness temperature data from the ocean's surface through the variation as a result of the satellite platform, the sensor, its location, the antenna, and other considerations. The thesis will give a description of how each component of the overall system will change the surface data because the observations are space-based. The thesis will also outline how the current detection system can be compared to the new space-based system. In the future, the comparison method can be used to make an argument to support the system with the best capability to serve as an efficient and accurate tsunami early-warning system.by Rebecca G. Myers.S.M

Appropriate Inhibition of Orexigenic Hypothalamic Arcuate Nucleus Neurons Independently of Leptin Receptor/STAT3 Signaling

Leptin directly suppresses the activity of orexigenic neurons in the hypothalamic arcuate nucleus (ARC). We examined c-Fos-like immunoreactivity (CFLIR) as a marker of ARC neuronal activity in db/db mice devoid of the signaling form of the leptin receptor (LRb) and s/s mice that express LRbS1138 [which is defective for STAT3 (signal transducer and activator of transcription) signaling]. Both db/db and s/s animals are hyperphagic and obese. This analysis revealed that CFLIR in agouti related peptide-expressing orexigenic ARC neurons is basally elevated in db/db but not s/s mice. Consistent with these observations, electrophysiologic evaluation of a small number of neurons in s/s animals suggested that leptin appropriately suppresses the frequency of IPSCs on ARC proopiomelanocortin (POMC) neurons that are mediated by the release of GABA from orexigenic ARC neurons. CFLIR in POMC neurons of s/s mice was also increased compared with db/db animals. Thus, these data suggest that, although LRb→STAT3 signaling is crucial for the regulation of feeding, it is not required for the acute or chronic regulation of orexigenic ARC neurons, and the activation of STAT3-mediated transcription by leptin is not required for the appropriate development of leptin responsiveness in these neurons

Decreased Serologic Response in Vaccinated Military Recruits during 2011 Correspond to Genetic Drift in Concurrent Circulating Pandemic A/H1N1 Viruses

Population-based febrile respiratory illness surveillance conducted by the Department of Defense contributes to an estimate of vaccine effectiveness. Between January and March 2011, 64 cases of 2009 A/H1N1 (pH1N1), including one fatality, were confirmed in immunized recruits at Fort Jackson, South Carolina, suggesting insufficient efficacy for the pH1N1 component of the live attenuated influenza vaccine (LAIV).To test serologic protection, serum samples were collected at least 30 days post-vaccination from recruits at Fort Jackson (LAIV), Parris Island (LAIV and trivalent inactivated vaccine [TIV]) at Cape May, New Jersey (TIV) and responses measured against pre-vaccination sera. A subset of 78 LAIV and 64 TIV sera pairs from recruits who reported neither influenza vaccination in the prior year nor fever during training were tested by microneutralization (MN) and hemagglutination inhibition (HI) assays. MN results demonstrated that seroconversion in paired sera was greater in those who received TIV versus LAIV (74% and 37%). Additionally, the fold change associated with TIV vaccination was significantly different between circulating (2011) versus the vaccine strain (2009) of pH1N1 viruses (ANOVA p value = 0.0006). HI analyses revealed similar trends. Surface plasmon resonance (SPR) analysis revealed that the quantity, IgG/IgM ratios, and affinity of anti-HA antibodies were significantly greater in TIV vaccinees. Finally, sequence analysis of the HA1 gene in concurrent circulating 2011 pH1N1 isolates from Fort Jackson exhibited modest amino acid divergence from the vaccine strain.Among military recruits in 2011, serum antibody response differed by vaccine type (LAIV vs. TIV) and pH1N1 virus year (2009 vs. 2011). We hypothesize that antigen drift in circulating pH1N1 viruses contributed to reduce vaccine effectiveness at Fort Jackson. Our findings have wider implications regarding vaccine protection from circulating pH1N1 viruses in 2011-2012

Risk factors for lower urinary tract injury at the time of hysterectomy for benign reasons

None of the authors has any conflicts of interest to report except for Dr. Rebecca G. Rogers, who is DSMB chair for American Medical Systems Transform Trial, UptoDate royalties, ACOG royalties, and is on the executive board of the ACOG. Dr. Gena Dunivan is a member of the AUGS Education Committee

Representing the function and sensitivity of coastal interfaces in earth system models

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ward, N. D., Megonigal, J. P., Bond-Lamberty, B., Bailey, V. L., Butman, D., Canuel, E. A., Diefenderfer, H., Ganju, N. K., Goni, M. A., Graham, E. B., Hopkinson, C. S., Khangaonkar, T., Langley, J. A., McDowell, N. G., Myers-Pigg, A. N., Neumann, R. B., Osburn, C. L., Price, R. M., Rowland, J., Sengupta, A., Simard, M., Thornton, P. E., Tzortziou, M., Vargas, R., Weisenhorn, P. B., & Windham-Myers, L. Representing the function and sensitivity of coastal interfaces in earth system models. Nature Communications, 11(1), (2020): 2458, doi:10.1038/s41467-020-16236-2.Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth’s climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface.Funding for this work was provided by Pacific Northwest National Laboratory (PNNL) Laboratory Directed Research & Development (LDRD) as part of the Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) Initiative. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. Additional support to J.P.M. was provided by the NSF-LTREB program (DEB-0950080, DEB-1457100, DEB-1557009), DOE-TES Program (DE-SC0008339), and the Smithsonian Institution. This manuscript was motivated by discussions held by co-authors during a three-day workshop at PNNL in Richland, WA: The System for Terrestrial Aquatic Research (STAR) Workshop: Terrestrial-Aquatic Research in Coastal Systems. The authors thank PNNL artist Nathan Johnson for preparing the figures in this manuscript and Terry Clark, Dr. Charlette Geffen, and Dr. Nancy Hess for their aid in organizing the STAR workshop. The authors thank all workshop participants not listed as authors for their valuable insight: Lihini Aluwihare (contributed to biogeochemistry discussions and development of concept for Fig. 3), Gautam Bisht (contributed to modeling discussion), Emmett Duffy (contributed to observational network discussions), Yilin Fang (contributed to modeling discussion), Jeremy Jones (contributed to biogeochemistry discussions), Roser Matamala (contributed to biogeochemistry discussions), James Morris (contributed to biogeochemistry discussions), Robert Twilley (contributed to biogeochemistry discussions), and Jesse Vance (contributed to observational network discussions). A full report on the workshop discussions can be found at https://www.pnnl.gov/publications/star-workshop-terrestrial-aquatic-research-coastal-systems

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants

BACKGROUND: Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. METHODS: A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. RESULTS: CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. CONCLUSION: State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide

Mental toughness and transitions to high school and to undergraduate study

Mental toughness can be conceptualised as a set of attributes that allow people to deal effectively with challenges, stressors and pressure. Recent work has suggested that it may be a valuable construct to consider within educational settings. The current studies explored the associations between mental toughness and educational transitions. Study 1 examined the relationships between mental toughness and concerns about moving to a new school in 105 children aged 12–13 years of age. The results revealed significant relationships between several aspects of mental toughness, but particularly confidence in abilities, and children’s concerns. Study 2 examined the relationships between mental toughness and adjustment to university in 200 undergraduate students at various stages of their course. The results revealed a role for several aspects of mental toughness; commitment, control of life, control of emotion, confidence in abilities and interpersonal confidence. The results are discussed in terms of implications for educational practice. It is suggested that measures of mental toughness could be used to identify individuals who may benefit from additional support during transition to a new school or to university, and that future research should explore the potential benefits of mental toughness training. © 2016 Informa UK Limited, trading as Taylor & Francis Group

Leptin Does Not Directly Affect CNS Serotonin Neurons to Influence Appetite

Serotonin (5-HT) and leptin play important roles in the modulation of energy balance. Here we investigated mechanisms by which leptin might interact with CNS 5-HT pathways to influence appetite. Although some leptin receptor (LepRb) neurons lie close to 5-HT neurons in the dorsal raphe (DR), 5-HT neurons do not express LepRb. Indeed, while leptin hyperpolarizes some non-5-HT DR neurons, leptin does not alter the activity of DR 5-HT neurons. Furthermore, 5-HT depletion does not impair the anorectic effects of leptin. The serotonin transporter-cre allele (Sert(cre)) is expressed in 5-HT (and developmentally in some non-5-HT) neurons. While Sert(cre) promotes LepRb excision in a few LepRb neurons in the hypothalamus, it is not active in DR LepRb neurons, and neuron-specific Sert(cre)-mediated LepRb inactivation in mice does not alter body weight or adiposity. Thus, leptin does not directly influence 5-HT neurons and does not meaningfully modulate important appetite-related determinants via 5-HT neuron function