Going through the rites of passage: timing and transition of menarche, childhood sexual abuse, and anxiety symptoms in girls.

Menarche is a discrete, transitional event that holds considerable personal, social, biological, and developmental significance. The present longitudinal study examined both the transition and timing of menarche on the trajectory of anxiety in girls with histories of childhood maltreatment (N = 93; 63% European American, 14% multiracial, 10% Latino, 9% African American, and 4% Native American). We hypothesized that because menarche is a novel, unfamiliar experience, girls would show greater anxiety around the time of menarche. The anxiety-provoking nature of menarche may be accentuated among earlier-maturing girls and girls with histories of childhood sexual abuse. Results indicated that earlier-maturing girls were more anxious in the pre- and peri-menarche periods than their later-maturing peers; however, their anxiety declined after menarche. Childhood sexual abuse was associated with heightened anxiety throughout this transition. The developmental significance of the timing and transition of menarche in relation to childhood sexual abuse and anxiety is discussed

Ground-water records of Flagler, Putnam, and St. Johns Counties, Florida

An investigation of the geology] and ground-water resources of Flagler, Putnam, and St. Johns counties, Florida, was made during the period November 1955 through 1958 by the U. S. Geological Survey in cooperation with the Florida Geological Survey. The results of this investigation have been published by the Florida Geological Survey in the following reports: Information Circular 13 entitled, "Interim Report on the Ground-Water Resources of Flagler County, Florida," by Boris J. Bermes; Information Circular 14 entitled, "Interim Report on the Ground- Water Resources of St. Johns County, Florida," by George R. Tarver; Information Circular 15 entitled, "Interim Report on the Ground-Water Resources of Putnam County, Florida," by Gilbert W. Leve; and Report of Investigations 32 entitled, "Geology and Ground-Water Resources of Flagler, Putnam, and St. Johns counties, Florida," by B. J. Bermes, G. W. Leve, and George R. Tarver. Report of Investigations 32 includes most of the information contained in the interim reports and in addition includes the results of the full period of investigation covering the entire area. The tabular material presented herewith contains all of the records that were not included in Report of Investigations 32. (Document contains 97 pages.

Reconnaissance of the ground-water resources of the Fernandina area, Nassau County, Florida

Practically all water for municipal and industrial use in the Fernandina area is supplied by artesian wells. In recent years, the use of artesian water in the area has increased to meet the needs of expanding industry and increasing population. The total industrial and municipal pumpage has increased from approximately 35 million gallons per day in 1941 to approximately 50 million gallons per day in 1959. Correlated with the increase in water use is the constant decline in the artesian pressure in the area. In many other areas in Florida, such a decline in artesian pressure has resulted in salt-water intrusion into the fresh-water supply.An intrusion of salt water in the Fernandina area would contaminate the existing fresh-water supply and would result in a hardship for the population and seriously injure the economy. Recognizing the threat to the fresh-water supplies of this area, the U. S. Geological Survey in cooperation with the Florida Geological Surveymade a reconnaissance to determineif there has been any intrusion of salt water into the fresh-water supply or if there is any danger of future intrusion. (PDF contains 28 pages.

A Commitment to Change: One District’s Journey Toward Inclusion

Introduction by: Ellen Contopidis, PhD Associate Professor, Nazareth College As a teacher educator preparing future inclusive educators, I often find myself responding to my students’ experiences with inclusion as “bad examples of a good idea.” The common element of these bad examples is that they are often the description of a place, a classroom, a service, a teacher or a child. Never do these bad examples reflect a philosophy or a culture within a system. Dr. Harold Leve’s leadership of transforming his school to an inclusive instructional environment is founded in a strong vision of social justice. The tools of collaboration, coteaching, consultant models, common planning and quality professional development were all used along the journey. Yet, tools they were and would have been ineffective if not grounded in a vision that allowed a transformation to a “mindset of a more inclusive philosophy.” Hildenbrand and Leve are very pragmatic in their description of the journey. They provide specific details that can be replicated or morphed to be used in other school systems. They also clearly demonstrate that leadership is key to transforming a school’s culture. Active leadership is an important catalyst for system change

De pedagogische professional van de toekomst:21st. Century Skills Professionals 0- tot 6-jarigen

De ambitie van kindcentra is om interdisciplinair samen te werken: onderwijs, kinderopvang en zorg samen. Dat vraagt om nieuwe vaardigheden van pedagogische professionals (leraren, pedagogisch medewerkers en zorgprofessionals). In dit rapport wordt geschetst om welke vaardigheden het gaat, van individuele professionals en van interdisciplinaire teams

Financial Development and Income Inequality in the Selected Southern African Development Community Countries

Financial development is widely regarded as another conduit through which income inequality can be reduced. The study empirically examines the relationship between financial development and income inequality in selected Southern African Development Community (SADC) countries, employing the Generalised Method of Moments technique for the period 1980 to 2016. Based on the inequality-decreasing hypothesis, a model which links financial sector development and inequality was estimated. Empirical results revealed that financial sector development overall does have an impact on income inequality in the selected SADC countries. An interesting observation from the empirical results is that the actual dimension of financial development plays a significant role in determining the relationship between financial development and income inequality in the SADC region. The impact of financial depth on income inequality is not obvious in the study, depending on the variable used. On the relationship between financial system stability and income inequality, results reveal that a stable financial system is beneficial to the poor. Financial efficiency does not appear to have a significant role in reducing income inequality in the selected SADC countries. The findings imply that a specific approach to financial sector development rather than a blanket approach is desirable

Financial Sector Development and Poverty Alleviation in the SADC Region

Financial development is widely regarded as another conduit through which poverty can be reduced. The study empirically examines the relationship between financial sector development and poverty reduction in SADC countries utilising the Generalised Method of Moments technique for the period 1980 to 2017. The empirical results indicate that the effect of the different measures of financial sector development on poverty in the SADC region is mixed. Six out of nine financial development variables have a negative effect on poverty in the SADC region. In terms of financial depth, the empirical results reveal mixed outcomes. Results on financial system stability confirm the notion that a stable financial system is beneficial to the poor. The results also reveal that financial inclusion or access to financial services significantly reduces poverty in the SADC region. The results thus suggest that financial sector development is beneficial to the poor when it is inclusive and stable. The results imply that policies aimed at ensuring a stable financial system, which is also inclusive, should be pursued if the poor are to benefit from the financial system

Plataforma integrada de dados de acidentes de viação para suporte a processos de aprendizagem automática

Integrated road accident data platform to support machine learning techniques Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors can be better understood and predicted, it might be possible to take measures to mitigate the damages and its severity. The purpose of this dissertation is to identify these factors using accident data from 2016 to 2019 from the district of Setúbal, Portugal. This work aims at developing models that can select a set of influential factors that may be used to classify the severity of an accident, supporting an analysis on the accident data. In addition, this study also proposes a predictive model for future road accidents based on past data. Various machine learning approaches are used to create these models. Supervised machine learning methods such as decision trees (DT), random forests (RF), logistic regression (LR) and naive bayes (NB) are used, as well as unsupervised machine learning techniques including DBSCAN and hierarchical clustering. Results show that a rule-based model using C5.0 algorithm is capable of accurately detecting the most relevant factors describing a road accident severity. Furthermore, the results of the predictive model suggests the RF model could be a useful tool for forecasting accident hotspots; Sumário: Os acidentes de trânsito são uma grande preocupação a nível mundial, uma vez que resultam em grandes números de vítimas, feridos e mortes por ano, como também perdas económicas significativas. Existem vários fatores responsáveis por causar acidentes rodoviários. Se pudermos compreender e prever melhor estes fatores, talvez seja possível tomar medidas para mitigar os danos e a sua gravidade. O objetivo desta dissertação é identificar estes fatores utilizando dados de acidentes de 2016 a 2019 do distrito de Setúbal, Portugal. Este trabalho tem como objetivo desenvolver modelos capazes de selecionar um conjunto de fatores influentes e que possam vir a ser utilizados para classificar a gravidade de um acidente, suportando uma análise aos dados de acidentes. Além disso, este estudo também propõe um modelo de previsão para futuros acidentes rodoviários com base em dados do passado. Várias abordagens de aprendizagem automática são usadas para criar esses modelos. Métodos de aprendizagem supervisionada, como árvores de decisão (DT), random forest (RF), regressão logística (LR) e naive bayes (NB), são usados, bem como técnicas de aprendizagem automática não supervisionada, incluindo DBSCAN e clustering hierárquico. Os resultados mostram que um modelo baseado em regras usando o algoritmo C5.0 é capaz de detetar com precisão os fatores mais relevantes que descrevem a gravidade de um acidente de viação. Além disso, os resultados do modelo preditivo sugerem que o modelo RF pode ser uma ferramenta útil para a previsão de acidentes

Model Predictive Control of an Underactuated Spacecraft with Two Reaction Wheels

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143105/1/1.G000320.pd