Weakly holomorphic modular forms in prime power levels of genus zero

Let $M_k^\sharp(N)$ be the space of weight $k$, level $N$ weakly holomorphic modular forms with poles only at the cusp at $\infty$. We explicitly construct a canonical basis for $M_k^\sharp(N)$ for $N\in\{8,9,16,25\}$, and show that many of the Fourier coefficients of the basis elements in $M_0^\sharp(N)$ are divisible by high powers of the prime dividing the level $N$. Additionally, we show that these basis elements satisfy a Zagier duality property, and extend Griffin's results on congruences in level 1 to levels 2, 3, 4, 5, 7, 8, 9, 16, and 25

Verbal Behavior Analysis as a Supervisory Technique with Student Teachers of Music

The purpose of the study was to determine the differential influence of a supervisory process based on constructs derived from the Withall Social-Emotional Climate Index on verbal behavior patterns exhibited by student teachers of music, their ability to engage in objective self-assessment, and the effect of such activity on the students' percepts of teacher-role ideology. The results indicated that: (1) student teachers of music appear not to be predisposed to the employment of learner-centered instructional behavior; (2) student teachers of music can be sensitized to the employment of both learner-centered and teacher-centered verbal patterns in accordance with the purpose and nature of the instruction being provided; and (3) verbal behavior analysis supervision tends to encourage objective self-assessment and provides a functional and commonly defined basis for the systematic improvement of teaching performance.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

The redoxomics of PTEN: walking a fine line between damage and signaling:mass spectrometry-based approaches to study the effect of oxidation on PTEN function, structure, and protein-protein interactions

The research described in this PhD thesis focuses on proteomics approaches to study the effect of oxidation on the modification status and protein-protein interactions of PTEN, a redox-sensitive phosphatase involved in a number of cellular processes including metabolism, apoptosis, cell proliferation, and survival. While direct evidence of a redox regulation of PTEN and its downstream signaling has been reported, the effect of cellular oxidative stress or direct PTEN oxidation on PTEN structure and interactome is still poorly defined. In a first study, GST-tagged PTEN was directly oxidized over a range of hypochlorous acid (HOCl) concentration, assayed for phosphatase activity, and oxidative post-translational modifications (oxPTMs) were quantified using LC-MS/MS-based label-free methods. In a second study, GSTtagged PTEN was prepared in a reduced and reversibly H2O2-oxidized form, immobilized on a resin support and incubated with HCT116 cell lysate to capture PTEN interacting proteins, which were analyzed by LC-MS/MS and comparatively quantified using label-free methods. In parallel experiments, HCT116 cells transfected with a GFP-tagged PTEN were treated with H2O2 and PTENinteracting proteins immunoprecipitated using standard methods. Several high abundance HOCl-induced oxPTMs were mapped, including those taking place at amino acids known to be important for PTEN phosphatase activity and protein-protein interactions, such as Met35, Tyr155, Tyr240 and Tyr315. A PTEN redox interactome was also characterized, which identified a number of PTEN-interacting proteins that vary with the reversible inactivation of PTEN caused by H2O2 oxidation. These included new PTEN interactors as well as the redox proteins peroxiredoxin-1 (Prdx1) and thioredoxin (Trx), which are known to be involved in the recycling of PTEN active site following H2O2-induced reversible inactivation. The results suggest that the oxidative modification of PTEN causes functional alterations in PTEN structure and interactome, with fundamental implications for the PTEN signaling role in many cellular processes, such as those involved in the pathophysiology of disease and ageing

Modelagem de abundância com drones : detectabilidade, desenho amostral e revisão automática de imagens em um estudo com cervos-do-pantanal

Entender como a abundância de uma espécie se distribui no espaço e/ou no tempo é uma questão fundamental em ecologia e conservação e ajuda, por exemplo, a elucidar relações entre a heterogeneidade de paisagens e populações ou compreender influência de predação na distribuição de indivíduos. Informações de tamanho populacional também são essenciais para avaliar risco de extinção, monitorar populações ameaçadas e planejar ações de conservação. Modelar a abundância de cervos-do-pantanal (Blastocerus dichotomus), sendo um grande herbívoro da América do Sul, pode ser importante para entender relações da espécie com a variação espacial da produtividade primária, das áreas úmidas que a espécie ocupa e do seu principal predador, a onça- pintada. Além disso, por estar ameaçado de extinção, estimar a abundância de cervos pode contribuir para avaliar populações relictuais da espécie, assim como monitorar populações após grandes eventos, como os incêndios de 2020 no Pantanal. Porém, acessar estimativas de abundância confiáveis de maneira eficiente requer métodos robustos que levem em conta os possíveis erros nas contagens e que forneçam as estimativas em tempo hábil, além de um desenho amostral otimizado para aproveitar os recursos geralmente escassos. Os drones tem aparecido como uma ferramenta versátil e custo-efetiva para amostragem de populações animais e vêm sendo aplicados para várias espécies diferentes nos mais variados contextos ecológicos. Como um método emergente, o uso de drones na ecologia fornece oportunidades para explorar novas possibilidades de amostragem e análise de dados, ao mesmo tempo em que pode apresentar novos desafios. Nesta tese, i) exploro oportunidade e desafios na utilização de drones para modelagem de abundância de animais, abordando questões de erros de detecção, desenho amostral e como lidar com os grandes bancos de imagens gerados; e ii) aplico os métodos desenvolvidos para estudar a variação na abundância de cervo-do- pantanal, assim como estabelecer uma abordagem para monitoramento robusto e efetivo dessa espécie. Assim, no primeiro capítulo, conduzo uma revisão na literatura descrevendo os potenciais erros de detecção que podem enviesar estimativas de abundância com drones, buscando soluções atuais para lidar com esses erros e identificando lacunas que precisam de desenvolvimento. Nessa revisão, destaco o potencial dos modelos hierárquicos para estimar abundância em amostragens com drone. No segundo capítulo, aplico amostragens espaço-temporalmente replicadas com drone, analisadas com modelos hierárquicos N-mixture, para entender o efeito de processos topo-base (distribuição de onças-pintadas) e base-topo (disponibilidade de forragem de qualidade e corpos d’água) na distribuição da abundância de cervos-do- pantanal. Nesse estudo, encontrei que, na época seca, os cervos se concentram em áreas de alta qualidade (maior disponibilidade de forragem e próximas a corpos d’água), mesmo sendo a região em que é esperado maior efeito da predação. No capítulo 3, em um estudo com simulações, avalio o desempenho de modelos N-mixture para estimativas de abundância a partir de amostragens espaço-temporalmente replicadas, explorando otimização de esforço amostral e o impacto de um protocolo com observadores duplos na acurácia das estimativas. No capítulo 4, desenvolvo uma abordagem para estimar abundância com drone usando observadores múltiplos na revisão das imagens, sendo um dos observadores baseado em um processamento semiautomático usando algoritmos de inteligência artificial. Nesse estudo, exploro técnicas de aprendizado profundo de máquina, com redes neurais convolucionais, acessíveis para ecólogos, treinando algoritmos para detectar cervos nas imagens de drone. Além de ajudar a elucidar questões sobre as relações do cervo-do-pantanal com aspectos diferentes da paisagem do Pantanal, as abordagens exploradas e desenvolvidas aqui têm um grande potencial de aplicação, ajudando a estabelecer os drones como uma ferramenta eficiente para modelagem e monitoramento populacional de diversas espécies animais, e particularmente de cervos.Understanding how abundance distributes in space and/or time is a fundamental question in ecology and conservation, and it helps, for example, to elucidate relationships between landscape heterogeneity or predation and populations. Information on the population size also is essential to evaluate extinction risk, monitor threatened species and plan conservation actions. Abundance modeling of marsh deer (Blastocerus dichotomus), as a large herbivore of South America, may be important to understand the relationships of this species with spatial variation in primary productivity, in the availability of wetlands that the species inhabits, and in the distribution of its main predator, the jaguar. Moreover, since marsh deer threatened to extinction, estimating its abundance can be contribute in assessments of relictual populations, as well as in monitoring the species after big events, such as the Pantanal 2020 megafires. However, efficiently assessing reliable abundance estimates require robust methods that account for possible sources of error in counts while providing the estimates timely. An optimized sampling design is also important, in order to make the best use of the usual scarce resources. Drones have raised as a versatile and cost- effective tool for sampling animal populations, and they have been applied for several species in a wide variety of ecological contexts. As being an emergent method, the use of drones in ecology provides opportunities to explore novel possibilities of sampling and analyzing data, while potentially presenting new challenges. In this thesis I: i) explore opportunities and challenges in the use of drones for animal abundance modeling, approaching issues about detection errors, sampling design and how to deal with the huge image sets generated from drone flights; and ii) apply the developed methods to study the spatial variation in marsh deer abundance and to establish an approach to monitor this species robustly and efficiently. Thus, in the first chapter, I carry on a literature review describing potential sources of errors that may bias abundance estimation with drones and the current solutions to address them, identifying gaps that need development. In this review, I highlight the potential of hierarchical models for abundance estimations from drone-based surveys. In the second chapter, I apply spatiotemporally replicated drone surveys, analyzed with N-mixture models, to understand the influence of bottom-up (forage and water) and top-down (jaguar density) variables on the spatial variation of marsh deer local abundance. In such study, I found that, in the dry season, the deer concentrate in high quality areas (high-quality forage available and close to water bodies), even these regions being expected to present higher predation risks. In chapter 3, in a simulation study, I evaluate the performance of N- mixture models for abundance estimation from spatiotemporally replicated surveys, exploring optimization of sampling effort and the impact of a double-observer protocol on estimation accuracy. In chapter 4, I develop a pipeline to estimate abundance from drone-based surveys using a multiple-observer protocol in which one of the observer is a semiautomated procedure based on deep learning algorithms. In such study, I explore deep learning techniques with convolutional neural networks that are accessible for ecologists, and train algorithms to detect marsh deer in drone imagery. Besides helping to elucidate questions about the relationships of marsh deer with landscape variables in Pantanal, the approaches explored and developed here have a great potential of application in order to establish drones as an efficient technique for population modeling and monitoring of several wildlife species, and particularly the marsh deer

Interpersonal and intrapersonal differences among adolescent nonsmokers, ex-smokers, and smokers

Background: A large body of research has traced tobacco dependence among adolescents to a series of intrapersonal and interpersonal factors. However, there are remaining questions regarding the differences on these factors related to tobacco use. Objectives: We sought to investigate intrapersonal and interpersonal differences among adolescent nonsmokers, ex-smokers, and smokers. Methods: We used data from a 3-year project designed to investigate and address tobacco dependence among 1071 students (Mage = 15.76, SD = 1.52; girls = 51.54%) who were recruited from 11 high schools. Participants, filling out a survey, provided information on tobacco use (nonsmoker, ex-smoker, and smoker), tobacco-related experiences (smoking-related risk perception, parental smoking, number of friends who smoke, resisting peer pressure to smoke), cognitive variables (metacognitive skills), and personality traits (disinhibition and impulsivity). Results: Results from a discriminant function analysis showed that smokers and ex-smokers reported more disinhibition, impulsivity, number of friends who smoke and less self-control under peer pressure to smoke compared to nonsmokers. Ex-smokers reported less metacognitive processes, more smoking-related risk perception and were less likely to have parents who smoke. Conclusions/Importance: Interventions and campaigns aimed to persuade adolescents to stop smoking should work to develop adaptive metacognitive skills and an accurate risk perception of tobacco use. © 2017 Taylor & Francis Group, LL

Personal and family correlates to happiness amongst Italian children and pre-adolescents

This study examines how family functioning, the parent-child relationship and personal factors are related to happiness in 1549 children aged 7 to 14 years old (53% females) in Italy. Children and pre-adolescents completed a set of questionnaires on self-rated happiness, self-concept and loneliness. At least one of their parents filled in questionnaires on family functioning, attachment and their child’s happiness level. No gender differences were found in the direct measure of happiness, but younger participants were happier than older participants, according to both the children’s and parents’ evaluations. Happiness is influenced by positive self-concept, self-esteem and low levels of satisfaction but family functioning does not seem to play a major role. The clinical and social implications of the study are discussed.peer-reviewe

Binge Drinking and Internalised Sexual Stigma among Italian Lesbian, Gay and Bisexual Young Adults

BACKGROUND - Literature has studied the relation between youth alcohol consumption and sexual orientation, showing that lesbian, gay and bisexual (LGB) young people are at increased risk to develop alcohol-related problems compared to heterosexuals. AIM - Our study aims to describe alcohol use patterns in relation to alcohol expectancies, internalised sexual stigma and sensation seeking and to highlight the specific risk factors that sexual minority subgroups face. DESIGN - A survey was administered in order to examine drinking habits, background information and levels of internalised sexual stigma and of sensation seeking in 468 LGB youths. According to the alcohol consumption, the sample was divided into three groups: social, binge and heavy drinkers. RESULTS - Data showed that bisexual youths were at most risk of heavy drinking compared to lesbian and gay participants. Moreover, LGB heavy drinkers reported higher levels of sensation seeking, earlier age of first alcohol consumption and more positive drinking expectancies compared to binge and social drinkers. Bisexual male heavy drinkers also showed more social confidence alcohol expectancies while bisexual female heavy drinkers showed more sensation seeking. CONCLUSION - Bisexual youths are at most risk of alcohol abuse. It is conceivable that these findings are related to the peculiar discrimination to which bisexual people are subject. Practical implications for the present study are discussed. \ua9 2016 Valera Verrastro et al., published by De Gruyter Open 2016