Hello everyone, 

A few months ago we started a project of cleaning up our electronic thesis 
and dissertation records from DSpace. We exported our data from Dspace as a 
csv file and after the cleanup we are ready to import the data back into 
Dspace. But we noticed that some of the names (accent marks and quotes) in 
our data are not showing correctly (I am assuming the encoding is not set 
correctly in the very beginning after we export). But since we have already 
done our clean up in our file, it will be really painful to go back and re 
export the file from Dspace (so we can set the encoding correctly this 
time) and redo all the editing. I wonder is there any way we can correct 
the encoding after we import the data back into Dspace? Or any suggestions 
to solve this problem? I have attached a small sample of our data. 

Your help is greatly appreicated. 

Xiping 


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id,collection,dc.contributor.advisor,dc.contributor.author,dc.contributor.committeeMember,dc.title,dc.description.abstract
969,10657/2,"Gustafsson, Jan-�ke",,"Ström, Anders  M||Schwartz, Robert||Webb, Paul||Wang, Yuhong",Antiproliferative and pro-­apoptotic actions of Estrogen receptor β in prostate cancer,"High Gleason grade prostate cancers are aggressive. Currently, the major target for treatment is the androgen receptor. Recent literature points towards a tumor suppressive role of estrogen receptor β (ERβ), which has a potential to be exploited as a target for novel therapeutics used for treatment of prostate cancer. 
In Chapter 2 of the thesis, we showed that ERβ-selective agonists elicited an increase in apoptosis and this was accompanied by an increase in expression of the pro-apoptotic factor PUMA. Induction of PUMA was dependent on the presence of the transcription factor FOXO3 but was independent of p53. In the ventral prostates of ERβ-/- mice, expression of FOXO3a is lower than that in WT littermates demonstrating a relationship between ERβ and FOXO3a expression found in PC3 and LNCaP cells. Furthermore, in prostate cancers of Gleason grade 4 or higher there was a marked reduction of both ERβ and FOXO3a, while both genes were well expressed in BPH sections. 
In Chapter 3 of the thesis, we investigated whether the loss of ERβ (also called as ERβ1) and/or expression of its splice variant ERβ2 affected signaling pathways involved in proliferation and bone metastasis of prostate cancer. We found repressed expression of the bone metastasis regulator Runx2 and its target gene, Slug by ERβ1. In addition, the expression of Twist1, a factor whose expression strongly correlates with high Gleason grade prostate cancer, was increased by ERβ2. In terms of cell cycle modification, of the two receptors, ERβ1, but not ERβ2, inhibited proliferation and expression of the proliferation markers Cyclin E, c-Myc, and p45Skp2. Xenograft studies using athymic nude mice confirmed the proliferative effect of ERβ2, as tumors in mice bearing PC3-ERβ2 cells were substantially larger than tumors in mice bearing PC3-control and PC3-ERβ1 cells."
482,10657/2,"Josić , Krešimir",,"Ott, William||Török, Andrew||Dabaghian, Yuri",The Interplay of Architecture and Correlated Variability in Neuronal Networks,"This much is certain: neurons are coupled, and they exhibit covariations in their output. The extent of each does not have
a single answer. Moreover, 
the strength of neuronal
correlations, in particular, has been a subject of hot debate within the neuroscience community
over the past decade, as advancing recording techniques have made available a lot of new,
sometimes seemingly conflicting, datasets. 
The impact of connectivity and the resulting correlations on the ability of animals to perform
necessary tasks is even less well understood.
In order to answer
relevant questions in these categories, novel approaches must be developed.
This work focuses  on three somewhat distinct, but inseparably coupled,
crucial avenues of research within the broader field of computational neuroscience.
First, there is a need for tools which can be applied, both by experimentalists and theorists,
to understand how networks transform their inputs. In turn, these tools will allow neuroscientists to tease apart the structure which
underlies network activity. The Generalized Thinning and Shift framework, presented in
Chapter 4, addresses this need.
Next, taking for granted a general understanding of network
architecture as well as some grasp of the behavior of its individual units, we must be able to reverse the activity to structure relationship, and understand instead how network structure
determines dynamics. 
We achieve this in Chapters 5 through 7 where we present an application of linear response theory yielding an explicit approximation of correlations in integrate--and--fire neuronal
networks. This approximation
reveals the explicit relationship between correlations, structure, and marginal dynamics.
Finally, we must strive to understand the functional impact of network dynamics and
architecture on the tasks that a neural network performs. This need
motivates our analysis of a biophysically detailed model of the blow fly visual system in Chapter 8. 
Our hope is that the work presented here represents significant advances in multiple directions within the field of computational neuroscience."
168,10657/2,"Mountain, Lee",,"Abrahamson, Richard||Craig, Cheryl||Horn, Catherine",Parental Perceptions of the Effects of the high-Stakes TAKS Test on the Home Lives of At-Risk Fifth Grade Students,"Westfall, Dawn. “Parental Perceptions of the Effects of the High-Stakes TAKS Test on the 
Home Lives of At-Risk Fifth Grade Students.”  Doctor of Education Dissertation, December 2010.

ABSTRACT

In Texas, fifth grade students are required to pass both the reading and math sections of the Texas Assessment of Knowledge and Skills, or TAKS test, in order to be promoted to the next grade level.  The purpose of this study is to describe parents’ perceptions of the influence of the high-stakes TAKS test on the family lives of at-risk fifth grade students.  Parents of students identified as at-risk for failure on the TAKS test by their schools were given a 12-item survey with three components: the effects of TAKS on the student and family, the effects of TAKS on how students spend time outside of school, and parent attitudes about TAKS as a fair measure of achievement. 
A series of three one-way ANOVAS was used, comparing each independent variable (family, time, and fairness) to a series of dependent variables (gender, race, and attendance at a Title I school) to look for variability between these groups in their attitudes towards the independent variables.  The results indicated that many parents perceive that the TAKS affects their families by causing their child and other family members to express concerns about passing the test and by causing the parent to worry about how their child is reacting to the pressures of the test.  Parents perceived that the TAKS test affects how much time students spend playing with friends as well as watching television or movies.  Many parents did not agree that TAKS is a fair measure of student achievement for their child or other children. The ANOVAs indicated statistically significant findings among race groups and their scores on “family” and “fairness.”  Asian/Pacific Islander parents indicated significantly less effect of TAKS on their student and family than did white parents.  Asian/Pacific Islander parents also perceived TAKS as fairer measure of student achievement than did white parents.  As well, Hispanic parents also perceived TAKS as a fairer measure of student achievement than did both white and Black/African American parents.  
Findings indicate that perhaps schools and teachers would be surprised to discover the amount of stress TAKS is causing families and students, particularly those at risk for failure as well as those groups that might not have previously been thought to “care” about school.  The level of negativity caused by TAKS appears to be an undesirable unintended consequence of the assessment system, so educators may want to reconsider their policies and practices for TAKS-related parent engagement, homework, and test preparation."

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