1,017 research outputs found
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 Districtâs 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 studentsâ experiences with inclusion as âbad examples of a good idea.â 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 Leveâs 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 âmindset of a more inclusive philosophy.â 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 schoolâs 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 automåtica
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 SetĂșbal,
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; SumĂĄrio: Os acidentes de trĂąnsito sĂŁo uma grande preocupação a nĂvel mundial, uma vez que resultam em grandes
nĂșmeros de vĂtimas, feridos e mortes por ano, como tambĂ©m perdas econĂłmicas significativas. Existem
vĂĄrios fatores responsĂĄveis por causar acidentes rodoviĂĄrios. Se pudermos compreender e prever melhor
estes fatores, talvez seja possĂvel tomar medidas para mitigar os danos e a sua gravidade. O objetivo desta
dissertação Ă© identificar estes fatores utilizando dados de acidentes de 2016 a 2019 do distrito de SetĂșbal,
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 anålise aos dados de acidentes. Além disso, este estudo também propÔe um modelo de previsão
para futuros acidentes rodoviĂĄrios com base em dados do passado. VĂĄrias abordagens de aprendizagem
automĂĄtica sĂŁo usadas para criar esses modelos. MĂ©todos de aprendizagem supervisionada, como ĂĄrvores
de decisĂŁo (DT), random forest (RF), regressĂŁo logĂstica (LR) e naive bayes (NB), sĂŁo usados, bem como
técnicas de aprendizagem automåtica não supervisionada, incluindo DBSCAN e clustering hierårquico. Os
resultados mostram que um modelo baseado em regras usando o algoritmo C5.0 Ă© 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 Ăștil para a previsĂŁo 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
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