Supporting and Retaining Early Career Mathematics Teachers Using an Online Community of Practice

This study reports on efforts over several years to design and implement a yearlong intervention intended to support secondary mathematics teachers in their early years of teaching. The intervention is designed to retain early career mathematics teachers in the professions by engaging them in the development of meaningful professional relationships with a school-based mentors, and by creating an online community of practice for support with other professionals. The intervention itself consists of early career teachers and their mentors participating in monthly professional learning activities such as online meetings, videoconferencing panels with experts, and collaborative reading and discussing timely, purposeful, and relevant content. The intervention is designed to not over burden the participants and to be feasible for national implementation with little to no funding. This article presents the purpose, design, and implementations of the intervention, as well as a discussion of challenges faced and potential next steps and future directions for similar work

Supporting and Retaining Early Career Mathematics Teachers Using an Online Community of Practice

This study reports on efforts over several years to design and implement a yearlong intervention intended to support secondary mathematics teachers in their early years of teaching. The intervention is designed to retain early career mathematics teachers in the professions by engaging them in the development of meaningful professional relationships with a school-based mentors, and by creating an online community of practice for support with other professionals. The intervention itself consists of early career teachers and their mentors participating in monthly professional learning activities such as online meetings, videoconferencing panels with experts, and collaborative reading and discussing timely, purposeful, and relevant content. The intervention is designed to not over burden the participants and to be feasible for national implementation with little to no funding. This article presents the purpose, design, and implementations of the intervention, as well as a discussion of challenges faced and potential next steps and future directions for similar work

THE DESIGN AND IMPLEMENTATION OF AN INTERVENTION TO SUPPORT AND RETAIN EARLY CAREER MATHEMATICS TEACHERS

This study reports on efforts over several years to design and implement a yearlong intervention intended to support secondary mathematics teachers in their early years of teaching. The intervention is designed to support these teachers’ development of meaningful professional relationships with a school-based mentor and to create an online community of practice for support with other professionals. The intervention itself consists of early career teachers and their mentors participating in monthly professional development sessions such as online meetings, Zoom panels with experts, and collaboratively reading and discussing timely, purposeful, and relevant content. The intervention is designed to not over burden the participants and to be feasible for national implementation with little funding. The goal of the intervention is to try to retain secondary mathematics teachers in the profession by providing them with meaningful and targeted support Half of all teachers leave the profession within the first five years, and this rate is highest for mathematics positions in high poverty schools (Fantilli & McDougall, 2009; Goldring et al., 2014). Furthermore, half of all current teachers in the U.S. retiring in the next five years (Foster, 2010), enrollment in teacher preparation programs declining, and teacher turnover is costing America $7.3 billion annually (National Math + Science Initiative, 2013), which represents a crisis for public education in the U.S. These conditions lead to classrooms staffed with underprepared/unqualified teachers, which profoundly affects the mathematical preparation of students in high school, college, and beyond. Experts agree that addressing the mathematics-teaching crisis meaningfully will require building a more cohesive system of teacher preparation, support, and development (Mehta, TheisenHomer, Braslow, & Lopatin 2015). The purpose of this study is to report on the design and implementation of a cost effective, easily replicable intervention for early career secondary mathematics teachers with the goal of positively impacting teacher retention. We also present lessons learned over two years of implementing the intervention and provide suggestions for future research

A sensitive one-step real-time PCR for detection of avian influenza viruses using a MGB probe and an internal positive control

BACKGROUND: Avian influenza viruses (AIVs) are endemic in wild birds and their introduction and conversion to highly pathogenic avian influenza virus in domestic poultry is a cause of serious economic losses as well as a risk for potential transmission to humans. The ability to rapidly recognise AIVs in biological specimens is critical for limiting further spread of the disease in poultry. The advent of molecular methods such as real time polymerase chain reaction has allowed improvement of detection methods currently used in laboratories, although not all of these methods include an Internal Positive Control (IPC) to monitor for false negative results. Therefore we developed a one-step reverse transcription real time PCR (RRT-PCR) with a Minor Groove Binder (MGB) probe for the detection of different subtypes of AIVs. This technique also includes an IPC. METHODS: RRT-PCR was developed using an improved TaqMan technology with a MGB probe to detect AI from reference viruses. Primers and probe were designed based on the matrix gene sequences from most animal and human A influenza virus subtypes. The specificity of RRT-PCR was assessed by detecting influenza A virus isolates belonging to subtypes from H1–H13 isolated in avian, human, swine and equine hosts. The analytical sensitivity of the RRT-PCR assay was determined using serial dilutions of in vitro transcribed matrix gene RNA. The use of a rodent RNA as an IPC in order not to reduce the efficiency of the assay was adopted. RESULTS: The RRT-PCR assay is capable to detect all tested influenza A viruses. The detection limit of the assay was shown to be between 5 and 50 RNA copies per reaction and the standard curve demonstrated a linear range from 5 to 5 × 10(8 )copies as well as excellent reproducibility. The analytical sensitivity of the assay is 10–100 times higher than conventional RT-PCR. CONCLUSION: The high sensitivity, rapidity, reproducibility and specificity of the AIV RRT-PCR with the use of IPC to monitor for false negative results can make this method suitable for diagnosis and for the evaluation of viral load in field specimens

Narcolepsy and adjuvanted pandemic influenza A (H1N1) 2009 vaccines – Multi-country assessment

Background: In 2010, a safety signal was detected for narcolepsy following vaccination with Pandemrix, an AS03-adjuvanted monovalent pandemic H1N1 influenza (pH1N1) vaccine. To further assess a possible association and inform policy on future use of adjuvants, we conducted a multi-country study of narcolepsy and adjuvanted pH1N1 vaccines. Methods: We used electronic health databases to conduct a dynamic retrospective cohort study to assess narcolepsy incidence rates (IR) before and during pH1N1 virus circulation, and after pH1N1 vaccination campaigns in Canada, Denmark, Spain, Sweden, Taiwan, the Netherlands, and the United Kingdom. Using a case-control study design, we evaluated the risk of narcolepsy following AS03- and MF59-adjuvanted pH1N1 vaccines in Argentina, Canada, Spain, Switzerland, Taiwan, and the Netherlands. In the Netherlands, we also conducted a case-coverage study in children born between 2004 and 2009. Results: No changes in narcolepsy IRs were observed in any periods in single study sites except Sweden and Taiwan; in Taiwan incidence increased after wild-type pH1N1 virus circulation and in Sweden (a previously identified signaling country), incidence increased after the start of pH1N1 vaccination. No association was observed for Arepanrix-AS03 or Focetria-MF59 adjuvanted pH1N1 vaccines and narcolepsy in children or adults in the case-control study nor for children born between 2004 and 2009 in the Netherlands case-coverage study for Pandemrix-AS03. Conclusions: Other than elevated narcolepsy IRs in the period after vaccination campaigns in Sweden, we did not find an association between AS03- or MF59-adjuvanted pH1N1 vaccines and narcolepsy in children or adults in the sites studied, although power to evaluate the AS03-adjuvanted Pandemrix brand vaccine was limited in our study

La glutatione transferasi in Serratia marcescens

Dottorato di ricerca in enzimologia applicata alle scienze medicheConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7, Rome / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

Un Robot, affascinato, dipinge il mare

Introduce e modera Maria Campitelli, presidente associazione culturale Gruppo 78 Intervengono Paolo Gallina, docente di Meccanica applicata Università di Trieste Diego Borme, ricercatore Sezione di oceanografia, OGS Eric Medvet, docente di Machine Learning and Data Mining Università di Trieste A cura di Università di Trieste, in collaborazione con Università di Udine Può un qualcosa di meccanico produrre arte? Nella fattispecie, può un robot, dotato magari di intelligenza artificiale, produrre qualcosa che abbia una valenza artistica? Queste e altre domande sono lecite dato che viviamo in un’epoca nella quale l’automazione e le tecnologie digitali sono entrate così pervasivamente nella nostra vita da renderci uomini e donne diversi rispetto a dieci o vent’anni fa. In questa conferenza si parlerà proprio di questo: il connubio tra arte e robotica (compresa anche l’intelligenza artificiale). Lo si farà partendo da esempi pratici, lontani e vicini, precursori di riflessioni che coinvolgono la definizione stessa di arte. E lo si farà anche presentando punti ti vista all’apparenza antitetici. Nondimeno, verranno mostrati i risultati di un gruppo composto da artisti e ingegneri teso a creare suggestioni estetiche attraverso la programmazione di un “robot pittore”. Maria Campitelli curatrice di arte contemporanea, è presidente del Gruppo 78 associazione culturale di Trieste con cui ha realizzato oltre 500 eventi, incentrati sulla media-art, sul connubio arte/scienza. Cura scambi culturali con altri paesi, in particolare con il Messico e con la Svizzera. Nell’ambito del rapporto arte/scienza ha prodotto la mostra internazionale “Aurelia 1+Hz, Arte/Scienza/Biotecnologia” (2015), ora in Messico, “Arte/Scienza/La Robotica” (2016); ha in preparazione “Robotics2. Il Gruppo78, associazione culturale attestata sull’arte contemporanea, da qualche tempo si orienta sul rapporto arte/scienza/tecnologia, puntando, dal 2016, sulla specificità della robotica. Il legame arte/scienza si attua in vari modi, adottando i linguaggi tecnologici, al posto di quelli tradizionali, o inducendo il robot a produrre pittura, disegno. Attraverso una serie di video (di Flego, Rinaldo, Cocho, Kiessling) si proporranno delle ricerche dove arte e tecno-scienza tendono a fondersi. Paolo Gallina è Professore associato di Meccanica Applicata alle Macchine. È Coordinatore del corso di Ingegneria industriale. I suoi campi di ricerca riguardano le vibrazioni, le interfacce uomo macchina e la robotica. È autore del romanzo/saggio "La formula matematica della felicità", 2012, Mondadori Ed. e del saggio scientifico “L’anima delle Macchine”, 2015, Dedalo Ed., col quale ha vinto il premio Internazionale Galileo. Twitter @paolo_gallina Eric Medvet è ricercatore universitario presso il DIA dell’Università degli Studi di Trieste e professore aggregato di Machine Learning e Data Mining. È responsabile del Machine Learning Lab, che svolge attività di ricerca nei campi dell’apprendimento automatico e del calcolo evoluzionistico in collaborazione con aziende nazionali ed università e centri di ricerca internazionali. Twitter @EricMedvetT