The purpose of the following study is to examine how reading is influenced by the use of easy-to-read adaptations of literary classics compared to the original works in an educational context. The novels forming the basis of the analysis are Charlotte Brontë's Jane Eyre (1847) and the adaptation written by Malin Lindroth, as well as Hjalmar Söderberg's Doktor Glas (1905) and the adaptation written by Tomas Dömstedt. In our study, we focus on how complex motifs and themes transition from the original works to the adaptations. The motifs that emerge in Jane Eyre are class affiliation, violence, gender oppression and religious oppression, which together constitute the overarching theme of female emancipation. The motifs that emerge in Doktor Glas are superhuman ideal, desire and disgust and doubt which together constitute the theme of moral guilt. Using an adaptation theoretical perspective based on Linda Hutcheon's and Brian McFarlane's respective theory descriptions, and a comparative method, we analyze how the motifs and themes transfer. The results show that class affiliation, violence, and gender oppression in Jane Eyre and superhuman ideal and some aspects of desire and disgust in Doktor Glas are transferred while maintaining fidelity to the essence. Furthermore, the results of the study show that there are opportunities to use the easy-to-read fiction for a didactic purpose, but that the easy-to-read literature must be supplemented with parts from the original work in some cases.

Plant pathogens are one of the biggest threats to plant health and food security worldwide. To effectively contain plant disease outbreaks, classification and precise identification of pathogens is crucial to determine treatment and preventive measurements. Conventional methods of detection such as PCR may not be sufficient when the pathogen in question is unknown. Advances in sequencing technology have made it possible to sequence entire genomes and metagenomes in real-time and at a relatively low cost, opening an opportunity for the development of alternative methods for detection of novel and unknown plant pathogens. Within this dissertation, an integrated approach is used to reclassify a high-impact group of plant pathogens. Additionally, the application of metagenomics and nanopore sequencing using the Oxford Nanopore Technologies (ONT) MinION for fungal and bacterial plant pathogen detection and precise identification are demonstrated. To improve the classification of the strains belonging to the Ralstonia solanacearum species complex (RSSC), we performed a meta-analysis using a comparative genomics and a reverse ecology approach to accurately portray and refine the understanding of the diversity and evolution of the RSSC. The groups identified by these approaches were circumscribed and made publicly available through the LINbase web server so future isolates can be properly classified. To develop a culture-free detection method of plant pathogens, we used metagenomes of various plants and long-read nanopore sequencing to precisely identify plant pathogens to the strain-level and performed phylogenetic analysis with SNP resolution. In the first paper, we used tomato plants to demonstrate the detection power of bacterial plant pathogens. We compared bioinformatics tools for detection at the strain-level using reads and assemblies. In the second paper, we used a read-based approach to test the feasibility of the methodology to precisely detect the fungal pathogen causing boxwood blight. Lastly, with the improvement in nanopore sequencing, we used grapevine petioles to investigate whether we can go beyond detection and identification and do a phylogenetic analysis. We assembled a metagenome-assembled genome (MAG) of almost the same quality as the genomes obtained from cultured isolates and did a phylogenetic analysis with SNP resolution. Finally, for the cases where there may be no related genome in the database like the pathogen in question, we used machine learning and metagenomics to develop a reference-free approach to detection of plant diseases. We trained eight different machine learning models with reads from healthy and infected plant metagenomes and compared the classification accuracy of reads as belonging to a healthy or infected plant. From the comparison, random forest was the best model in terms of computational resources needed while maintaining a high accuracy (> 0.90). / Doctor of Philosophy / Microbes are present in every environment on the planet and have been on Earth for billions of years. While some microbes are beneficial, others can cause diseases. To differentiate the ones causing diseases from those who do not, looking into the evolutionary forces making them different is crucial to classify and identify them correctly. Although microorganisms cause diseases in humans and animals, the ones causing diseases in plants are one of the biggest threats to plant health and food security worldwide. In a perfect world, plant diseases would be diagnosed by eye or simple procedures. However, when a plant disease is present, it is not always obvious which organism, if any, is causing the disease making it hard for outbreaks to be detected and contained promptly. With technological advances, it is now possible to obtain all the genetic information of not only one organism but all the organisms living in an environment at a time. This genetic information can then be used to precisely identify what organism is causing a disease in a plant for faster disease diagnosis and, consequently, more efficient disease prevention and control. In this dissertation, we used the bacterial group, called Ralstonia solanacearum species complex, which can cause different diseases in more than 200 crops, to investigate and understand the evolution and diversity of the members of this group. We also used newly developed technologies to obtain the genetic material of all the organisms living in multiple important plants including tomato, grapevine, and the ornamental bush, boxwood. Using this genetic material, we developed a methodology for the detection of bacteria and a fungus causing plant diseases. While this works well when the suspected organism or a similar one is available for comparison, the detection of plant diseases in cases where this information is not available is challenging. Machine learning models, where computers can learn complex patterns from data, have the potential to detect pathogens without the need to compare the sequences to sequences of other pathogens. Here we also used the genetic material to train and compare different machine learning models to classify plants as either being infected or healthy.

Viruses have huge impact on controlling diseases and regulating many key ecosystem processes. As metagenomic data can contain many microbiomes including many viruses, by analyzing metagenomic data we can analyze many viruses at the same time. The first step towards analyzing metagenomic data is to identify and quantify viruses present in the data. In order to answer this question, we developed a computational pipeline, FastViromeExplorer. FastViromeExplorer leverages a pseudoalignment based approach, which is faster than the traditional alignment based approach to quickly align millions/billions of reads. Application of FastViromeExplorer on both human gut samples and environmental samples shows that our tool can successfully identify viruses and quantify the abundances of viruses quickly and accurately even for a large data set. As viruses are getting increased attention in recent times, most of the viruses are still unknown or uncategorized. To discover novel viruses from metagenomic data, we developed a computational pipeline named FVE-novel. FVE-novel leverages a hybrid of both reference based and de novo assembly approach to recover novel viruses from metagenomic data. By applying FVE-novel to an ocean metagenome sample, we successfully recovered two novel viruses and two different strains of known phages. Analysis of viral assemblies from metagenomic data reveals that viral assemblies often contain assembly errors like chimeric sequences which means more than one viral genomes are incorrectly assembled together. In order to identify and fix these types of assembly errors, we developed a computational tool called VirChecker. Our tool can identify and fix assembly errors due to chimeric assembly. VirChecker also extends the assembly as much as possible to complete it and then annotates the extended and improved assembly. Application of VirChecker to viral scaffolds collected from an ocean meatgenome sample shows that our tool successfully fixes the assembly errors and extends two novel virus genomes and two strains of known phage genomes. / Doctor of Philosophy / Virus, the most abundant micro-organism on earth has a profound impact on human health and environment. Analyzing metagenomic data for viruses has the beneFIt of analyzing many viruses at a time without the need of cultivating them in the lab environment. Here, in this dissertation, we addressed three research problems of analyzing viruses from metagenomic data. To analyze viruses in metagenomic data, the first question needs to answer is what viruses are there and at what quantity. To answer this question, we developed a computational pipeline, FastViromeExplorer. Our tool can identify viruses from metagenomic data and quantify the abundances of viruses present in the data quickly and accurately even for a large data set. To recover novel virus genomes from metagenomic data, we developed a computational pipeline named FVE-novel. By applying FVE-novel to an ocean metagenome sample, we successfully recovered two novel viruses and two strains of known phages. Examination of viral assemblies from metagenomic data reveals that due to the complex nature of metagenome data, viral assemblies often contain assembly errors and are incomplete. To solve this problem, we developed a computational pipeline, named VirChecker, to polish, extend and annotate viral assemblies. Application of VirChecker to virus genomes recovered from an ocean metagenome sample shows that our tool successfully extended and completed those virus genomes.

The purpose of this study is to develop a readiness program which will be an aid in eliminating many failures in reading and to help the children be happy while learning to read.

Most of the data referenced by sequential and parallel applications running in current chip multiprocessors are referenced by a single thread, i.e., private. Recent proposals leverage this observation to improve many aspects of chip multiprocessors, such as reducing coherence overhead or the access latency to distributed caches. The effectiveness of those proposals depends to a large extent on the amount of detected private data. However, the mechanisms proposed so far either do not consider either thread migration or the private use of data within different application phases, or do entail high overhead. As a result, a considerable amount of private data is not detected. In order to increase the detection of private data, this thesis proposes a TLB-based mechanism that is able to account for both thread migration and private application phases with low overhead. Classification status in the proposed TLB-based classification mechanisms is determined by the presence of the page translation stored in other core's TLBs. The classification schemes are analyzed in multilevel TLB hierarchies, for systems with both private and distributed shared last-level TLBs. This thesis introduces a page classification approach based on inspecting other core's TLBs upon every TLB miss. In particular, the proposed classification approach is based on exchange and count of tokens. Token counting on TLBs is a natural and efficient way for classifying memory pages. It does not require the use of complex and undesirable persistent requests or arbitration, since when two ormore TLBs race for accessing a page, tokens are appropriately distributed classifying the page as shared. However, TLB-based ability to classify private pages is strongly dependent on TLB size, as it relies on the presence of a page translation in the system TLBs. To overcome that, different TLB usage predictors (UP) have been proposed, which allow a page classification unaffected by TLB size. Specifically, this thesis introduces a predictor that obtains system-wide page usage information by either employing a shared last-level TLB structure (SUP) or cooperative TLBs working together (CUP). / La mayor parte de los datos referenciados por aplicaciones paralelas y secuenciales que se ejecutan enCMPs actuales son referenciadas por un único hilo, es decir, son privados. Recientemente, algunas propuestas aprovechan esta observación para mejorar muchos aspectos de los CMPs, como por ejemplo reducir el sobrecoste de la coherencia o la latencia de los accesos a cachés distribuidas. La efectividad de estas propuestas depende en gran medida de la cantidad de datos que son considerados privados. Sin embargo, los mecanismos propuestos hasta la fecha no consideran la migración de hilos de ejecución ni las fases de una aplicación. Por tanto, una cantidad considerable de datos privados no se detecta apropiadamente. Con el fin de aumentar la detección de datos privados, proponemos un mecanismo basado en las TLBs, capaz de reclasificar los datos a privado, y que detecta la migración de los hilos de ejecución sin añadir complejidad al sistema. Los mecanismos de clasificación en las TLBs se han analizado en estructuras de varios niveles, incluyendo TLBs privadas y con un último nivel de TLB compartido y distribuido. Esta tesis también presenta un mecanismo de clasificación de páginas basado en la inspección de las TLBs de otros núcleos tras cada fallo de TLB. De forma particular, el mecanismo propuesto se basa en el intercambio y el cuenteo de tokens (testigos). Contar tokens en las TLBs supone una forma natural y eficiente para la clasificación de páginas de memoria. Además, evita el uso de solicitudes persistentes o arbitraje alguno, ya que si dos o más TLBs compiten para acceder a una página, los tokens se distribuyen apropiadamente y la clasifican como compartida. Sin embargo, la habilidad de los mecanismos basados en TLB para clasificar páginas privadas depende del tamaño de las TLBs. La clasificación basada en las TLBs se basa en la presencia de una traducción en las TLBs del sistema. Para evitarlo, se han propuesto diversos predictores de uso en las TLBs (UP), los cuales permiten una clasificación independiente del tamaño de las TLBs. En concreto, esta tesis presenta un sistema mediante el que se obtiene información de uso de página a nivel de sistema con la ayuda de un nivel de TLB compartida (SUP) o mediante TLBs cooperando juntas (CUP). / La major part de les dades referenciades per aplicacions paral·leles i seqüencials que s'executen en CMPs actuals són referenciades per un sol fil, és a dir, són privades. Recentment, algunes propostes aprofiten aquesta observació per a millorar molts aspectes dels CMPs, com és reduir el sobrecost de la coherència o la latència d'accés a memòries cau distribuïdes. L'efectivitat d'aquestes propostes depen en gran mesura de la quantitat de dades detectades com a privades. No obstant això, els mecanismes proposats fins a la data no consideren la migració de fils d'execució ni les fases d'una aplicació. Per tant, una quantitat considerable de dades privades no es detecta apropiadament. A fi d'augmentar la detecció de dades privades, aquesta tesi proposa un mecanisme basat en les TLBs, capaç de reclassificar les dades com a privades, i que detecta la migració dels fils d'execució sense afegir complexitat al sistema. Els mecanismes de classificació en les TLBs s'han analitzat en estructures de diversos nivells, incloent-hi sistemes amb TLBs d'últimnivell compartides i distribuïdes. Aquesta tesi presenta un mecanisme de classificació de pàgines basat en inspeccionar les TLBs d'altres nuclis després de cada fallada de TLB. Concretament, el mecanisme proposat es basa en l'intercanvi i el compte de tokens. Comptar tokens en les TLBs suposa una forma natural i eficient per a la classificació de pàgines de memòria. A més, evita l'ús de sol·licituds persistents o arbitratge, ja que si dues o més TLBs competeixen per a accedir a una pàgina, els tokens es distribueixen apropiadament i la classifiquen com a compartida. No obstant això, l'habilitat dels mecanismes basats en TLB per a classificar pàgines privades depenen de la grandària de les TLBs. La classificació basada en les TLBs resta en la presència d'una traducció en les TLBs del sistema. Per a evitar-ho, s'han proposat diversos predictors d'ús en les TLBs (UP), els quals permeten una classificació independent de la grandària de les TLBs. Específicament, aquesta tesi introdueix un predictor que obté informació d'ús de la pàgina a escala de sistema mitjançant un nivell de TLB compartida (SUP) or mitjançant TLBs cooperant juntes (CUP). / Esteve García, A. (2017). Design of Efficient TLB-based Data Classification Mechanisms in Chip Multiprocessors [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86136

Many children in the United States struggle with mental health issues. The increase in mental health difficulties for children and adolescents has increased so greatly after the COVID19 pandemic that it has been declared a national mental health emergency by the American Academy of Pediatrics, the American Academy of Child and Adolescent Psychiatry and the Children’s Hospital Association (AAP et al., 2021). The burden to provide children with socialemotional learning, opportunities, access, and support often falls on teachers, and this burden can be particularly acute in rural communities, stemming from the limited availability of resources. Using picturebooks through means such as developmental bibliotherapy is one way for educators to address the increasing need to care for children’s social and emotional wellness in schools. This self-study explored my lived experience reading and connecting with award-winning Mo Willems picturebooks for emotional literacy content and considering the possibility of using them in interactive read-aloud sessions. Analyses revealed four overarching themes: (a) my personal journey, (b) discovering emotions in characters, (c) the importance of relationships, and (d) nurturing and recognizing positivity. These findings highlight important implications for supporting young children’s emotional literacy through interactive read-alouds, emphasizing the idea that teaching is a personal act, the potential for interactive read-alouds to provide hope or positivity, and the opportunities afforded to foster meaningful interactions with text through developmental bibliotherapy. This study may inform future work regarding teaching and supporting social-emotional learning concepts for young children, specifically applying insights related to pedagogy, teacher perspective, and student learning.

Epigenetics are stable heritable traits that are not a result of the DNA sequence. Epigenetic modification of DNA cytosine plays a role in development and disease. The covalent bonding of a methyl group or a hydroxymethyl group to the 5-carbon of cytosine epigenetically modifies cytosine to 5-methylcytosine or 5-hydroxymethylcytosine. Upon PCR amplification, the bisulfite treatment of DNA converts unmethylated cytosine to thymine, while 5-methylcytosine, 5-hydroxymethylcytosine, and other bases remain unchanged. The resulting sequences can be mapped to a reference genome; however, this can be challenging due to sequencing technology complexity, low sequence complexity, and biases and errors introduced with bisulfite treatment. Once the short read is mapped, the identity of 5-methylcytosine or 5-hydroxymethylcytosine can be determined by comparing the mapped read to the aligned reference genome. Bisulfite DNA read mapping is characterized by mapping performance as low as 40%. This research improves bisulfite short read mapping quality. First, reads generated from the bisulfite hairpin PCR protocol are used to study mapping failure and solutions. A read may not map to the genome; it may map uniquely, or it may map to multiple locations. Sequence complexity correlates with these mapping categories. The hairpin protocol allows for a recovery, in some cases, of the original untreated read, and mapping this read with the regular read mapper Bowtie2 improved mapper performance by 10%. New bisulfite read mapping software called BisPin was created that calls BFAST (BLAT-like Fast Accurate Search Tool) for mapping. BisPin resolves ambiguously mapped reads with a rescoring strategy, which yields a statistically significant improvement. BFAST-Gap for Ion Torrent reads was developed, since Ion Torrent machines are less expensive than Illumina machines and since Ion Torrent reads are longer. There are few mappers for Ion Torrent data. BFAST-Gap uses homopolymer run length for contextual gap penalty functions, since homopolymer runs cause errors in Ion Torrent reads. In conjunction with BisPin, this software performed well on real and simulated bisulfite Ion Torrent data and Illumina data. InfoTrim, a read trimmer with an entropy term, was developed with competitive results. / Ph. D. / DNA, deoxyribonucleic acid, is a large molecule comprised of four molecular bases: adenine, cytosine, thymine, and guanine, and it determines heritable traits in living organisms. Sequencing DNA determines the sequential arrangement of bases. A read is a small sequence of DNA bases. Epigenetics are stable heritable traits that are not a result of the DNA sequence. Chemical groups called methyl and hydroxymethyl can be attached to cytosine. These groups are an epigenetic modification of cytosine, and they play a role in disease and development. The chemical bisulfite is used to discover these chemical groups. The bisulfite sequencing of DNA is a process where bisulfite is introduced to DNA, and then the DNA is sequenced. Bisulfite treatment converts cytosines without the methyl and hydroxymethyl chemical groups into thymine. Software is then used to align and match the resulting DNA strands to a large reference DNA strand called a reference genome to distinguish between cytosines that have these chemical groups. This process is called mapping or alignment, and its performance can be as low as 40% for bisulfite data. This research improves this performance. The hairpin protocol is a known bisulfite sequencing method that sequences two opposing DNA strands, where the original untreated strand can sometimes be recovered. Mapping the recovered strands improved performance by 10%. Using hairpin data, sequence complexity, a measure of DNA sequence randomness, correlated with mapping performance. BisPin mapping software was created that implements the hairpin recovery approach. BisPin rescores DNA strands that map to multiple locations on the reference genome, and it supports multiple sequencing technologies. BFAST-Gap, a modified mapping program callable by BisPin, uses a context sensitive function to better align Ion Torrent reads, which tend to have errors in regions of repeated bases. BFAST-Gap was developed, since Ion Torrent sequencing machines are less expensive than Illumina machines and since Ion Torrent reads tend to be longer and have more information. The read trimmer InfoTrim was developed to trim the lengths of short DNA sequences to improve the quality of alignments. These programs were validated on real and simulated DNA data and performed well.

This is a study of how four teachers work with pupils’ early literacy learning. Interviews were conducted with two teachers who chose to use a specific method, Writing to Read (WTR), for teaching pupils to read, and with two teachers who had not chosen a specific method. The aim of the study was to compare how the teachers worked, their motives for their choice of method, and the ideas the teachers have about early literacy learning. To see whether the teachers’ choice of method was related to the individualization of the teaching and their views of pupils’ learning in interaction, Vygotsky’s theories about children’s learning have been used. The result shows that there are both similarities and differences in the teachers’ reasons for their choice of method. Those who use WTR say that they do so to be able to individualize the teaching, while the teachers who do not use a specific method use the same arguments. There is a difference in whether the teachers aim for structured or unstructured teaching, regardless of the choice of method. Several parallels to Vygotsky’s theories were found, in that all four teachers, irrespective of method, think that their teaching should be characterized by interaction and individualization.

Made available in DSpace on 2016-08-03T16:16:11Z (GMT). No. of bitstreams: 1 Maria Matilde Antonelli.pdf: 3019163 bytes, checksum: b1fa56e5a12288562365f215644e6ba2 (MD5) Previous issue date: 2009-03-19 / This work aims to investigate the knowledge present in the pedagogical practice of six teachers who during their professional career presented a successful practice in teaching how to read and write, always acting in the peripheral region of one city of Big São Paulo. In this study I used semi-structured interviews, participant observation and report of their life history with the intention to answer the following questions: What is there of significance in the well succeeded practice of these teachers? Which knowledge is mobilized with students in the process of reading and writing? How do the teachers deal with different knowledge of the students and with the situations that they face with a possible absence of knowledge? Initially I describe the historical context of the read and write process in 1983 with the implantation of the Basic Cycle (DURAN, 1995), period in which the target teachers of this research began their teaching career in the state web of schools and were challenged to face a new forms of thinking the read and write process within the psychogenesis of the written language (FERREIRO AND TEBEROSKY, 1979), which takes as basis the Piaget constructivism in a dialogic action with authors who prioritize the reflection on knowledge and pedagogical practice. (FREIRE, 1996, OLIVEIRA, 1997, ALARCÃO 2005 AND TARDIF, 2007). The results show that the construction of knowledge of the teachers in the conduct of the work in classrooms occur along with the trajectory of formation and pedagogical acting in different moments. In the dialogue with live experience with produced pedagogical material in the relation with the children they work with in the course of formation in which they take part in the partnership and exchanges with teachers. The creativity facing the challenges of read/write process make they reorganize the knowledge and look for knowledge in which the quality of their intervention and pedagogical actions attend the diversity which constitutes the classroom space. Because they believe in the capacity of children they present challenging activities which can make possible the reflection on the reading and writing processes. Always respecting the previous knowledge of the students who interact with them and constructing knowledge.(AU) / Objetivando investigar os saberes presentes na prática pedagógica de seis professoras que, ao longo de sua trajetória profissional, apresentaram uma prática bem-sucedida na alfabetização, sempre atuando em região periférica de uma cidade da Grande São Paulo, utilizei, neste estudo, entrevista semiestruturada, observação participante e relato de história de vida, no intuito de responder às questões: O que há de significativo nas práticas bem-sucedidas das professoras alfabetizadoras? Quais saberes são mobilizados com os educandos no processo de alfabetização? Como as professoras lidam com diferentes saberes dos alunos e com as situações em que se defrontam com um possível não saber? Inicialmente, descrevo o contexto histórico da alfabetização em 1983, com a implantação do Ciclo Básico de Alfabetização (DURAN, 1995), período em que as professoras-alvo da pesquisa iniciaram carreira no magistério na rede pública estadual e foram desafiadas a uma nova forma de pensar a alfabetização no âmbito da Psicogênese da Língua Escrita (FERREIRO e TEBEROSKY, 1979), embasadas no construtivismo piagetiano, numa ação dialógica com autores que priorizam a reflexão sobre saberes e prática pedagógica (FREIRE, 1996; OLIVEIRA, 1997; ALARCÃO, 2005 e TARDIF, 2007). Os resultados mostram que a constituição dos saberes das professoras na condução do trabalho em sala de aula ocorre ao longo da trajetória de formação e atuação pedagógica, em diferentes momentos: no diálogo com experiências vividas, com materiais pedagógicos produzidos; na relação com as crianças com quem convivem; nos cursos de formação de que participam; nas parcerias e trocas com professores. A criatividade diante dos desafios de alfabetizar faz com que reorganizem o saber e busquem conhecimentos para que a qualidade das intervenções e ações pedagógicas atenda a diversidade que compõe o espaço da sala de aula. Por acreditarem na capacidade das crianças, propiciam atividades desafiadoras que oportunizam a reflexão sobre a leitura e a escrita (FERREIRO, 1989, LERNER, 2002 & WEISZ, 2002), sempre respeitando os conhecimentos prévios do aprendiz que interage com elas e constrói conhecimentos.(AU)

I skolans tidigare åldrar fokuseras till stor del på läs- och skrivutveckling och vilka metoder som lämpar sig bäst för elevers lärande. Den här systematiska litteraturstudien handlar om elevers tidiga skrivutveckling med hjälp av digitala verktyg och att skriva sig till läsning (ASL-metoden). Syftet är att studera om digitala verktyg och ASL-metoden kan gynna elevers tidiga skrivande. Studiens syfte och frågeställning besvaras med en analys av flertalet vetenskapliga artiklar. Resultatet visar att digitala verktyg och ASL-metoden kan vara ett bra komplement till den mer traditionella skrivundervisningen med penna och papper. Dock visar ett resultat att bland det viktigaste, oavsett modell, är att skrivundervisningen behöver vara systematisk och tydligt strukturerad.