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PARTICIPATION OF DIPSHIKHA BENEFICIARIES IN SOCIO-ECONOMIC DEVELOPMENT ACTIVITIES
Full text linkA Thesis
Submitted to the Faculty of Agriculture,
Sher-e-Bangla Agricultural University, Dhaka,
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
IN
AGRICULTURAL EXTENSION AND INFORMATION SYSTEMThe main purpose of the study was to ascertain the extent of participation by the Dipshikha
beneliciaries in different development activities. Attempts were also made to describe some
of the selected characteristics of the respondents and to explore the relationships between
selected characteristics of the respondents and their participation in overall Dipshikha
activities. The study
was
conducted in three unions consisting eleven villages under Birganj
upazila of Dinajpur district. Out of 479 beneficiary families, 120 member families of
Dipshikha were selected randomly and proportionately. Data were collected by using
interview schedule during
2nd
October to 31
"
October, 2007. Participation of the respondents
in three major activities was ascertained through a four point rating scale. Then overall
activities was measured by adding the obtained scores of three dimensions activities such as
income generating activities, 'health, hygiene & sanitation activities' and women
development activities. Coefficient of correlation (r) was computed in order to explore the
relationships between selected characteristics of the respondents and their participation in
overall Dipshikha activities. Participation Index (P1) was computed which ranged from 0 to
300. 'Use of tube well water' and 'Taking iodized salt' had the same rank as 1.5 and
obtained P1 is 300, where 'Candle marketing' and Soap marketing' had the same rank as
33.5 and obtained P1 is 0. The possible participation score in overall activities ranged from 0
to 102. where the observed participation score was found 28-68 with an average 51.93 and
standard deviation 8.69. It was observed that majority of the respondents (64.17 percent) had
medium participation, 15.83 percent had low participation and 20 percent of them had high
participation in overall Dipshikha activities. The findings revealed that level of education,
farm size, annual income, training exposure, savings, credit availability, implementation of
family development plan and attitude towards Dipshikha of the respondents had significant
positive relationships with their participation in overall Dipshikha activities. Age,
involvement with Dipshikha, family size and acceptance of loan received conditions by the
respondents had no statistically significant relationships with their participation in overall
Dipshikha activities
Peuplement d'une base de connaissance fondé sur l'exploitation d'un graphe d'entités
No full textKnowledge Base Population (KBP) is an important and challenging task specially when it has to be done automatically. The objective of KBP task is to make a collection of facts of the world. A Knowledge Base (KB) contains different entities, relationships among them and various properties of the entities. Relation extraction (RE) between a pair of entity mentions from text plays a vital role in KBP task. RE is also a challenging task specially for open domain relations. Generally, relations are extracted based on the lexical and syntactical information at the sentence level. However, global information about known entities has not been explored yet for RE task. We propose to extract a graph of entities from the overall corpus and to compute features on this graph that are able to capture some evidence of holding relationships between a pair of entities. In order to evaluate the relevance of the proposed features, we tested them on a task of relation validation which examines the correctness of relations that are extracted by different RE systems. Experimental results show that the proposed features lead to outperforming the state-of-the-art system.Le peuplement de base de connaissance (KBP) est une tâche importante qui présente de nombreux défis pour le traitement automatique des langues. L'objectif de cette tâche est d'extraire des connaissances de textes et de les structurer afin de compléter une base de connaissances. Nous nous sommes intéressés à la reconnaissance de relations entre entités. L'extraction de relations (RE) entre une paire de mentions d'entités est une tâche difficile en particulier pour les relations en domaine ouvert. Généralement, ces relations sont extraites en fonction des informations lexicales et syntaxiques au niveau de la phrase. Cependant, l'exploitation d'informations globales sur les entités n'a pas encore été explorée. Nous proposons d'extraire un graphe d'entités du corpus global et de calculer des caractéristiques sur ce graphe afin de capturer des indices des relations entre paires d'entités. Pour évaluer la pertinence des fonctionnalités proposées, nous les avons testées sur une tâche de validation de relation dont le but est de décider l'exactitude de relations extraites par différents systèmes. Les résultats expérimentaux montrent que les caractéristiques proposées conduisent à améliorer les résultats de l'état de l'art
Quantitative Methods for the Analysis of Neuroglia in Micrographs
No full textAstrocytes are an important subclass of glial cells with an extremely intricate structure that play critical roles in maintaining or regulating a variety of functions within the Central Nervous System(CNS). These cells participate in a variety of CNS activities, from the maintenance of the blood-brain barrier and the regulation of blood flow to the modulation of synaptic activity and responsive changes after brain injury. However, despite their great importance, the mechanisms through which astrocytes work within the CNS remain not fully understood. One of the reasons lies in the complex morphological interactions that astrocytes have with other CNS cells, in particular with neurons and other glial cells. One major challenge to further understand the role of astrocytes comes from the limitations of available quantitative image analysis tools that are not very efficient at capturing their elaborated shapes, high heterogeneity and complex networks. This limits the possibility of studying in detail the alterations of astrocytes, their responses to various inputs and their interactions within the CNS. To help addressing these challenges, in this dissertation we developed a new deep learning framework that enables the automatic identification and analysis of GFAP-immunolabeled astrocytes directly from brightfield and fluorescent micrographs based on a state-of-the-art deep learning platform in object detection -You Only Look Once(YOLOv8). For this task, we have customized YOLOv8 to develop optimized models for astrocyte detection, improving its ability to accurately identify these cells even under a highly complex and challenging environment and introduced a novel automated counting method of those astrocytes. Our framework has been tested through a large collection of numerical experiments applied on different imaging modalities and conditions. These experiments have demonstrated that our approach is very competitive compared to traditional and state-of-the-art techniques. In particular, in cases of relatively dense packing of astrocytes, our approach seems quite effective. It is expected that our framework will facilitate studies on these critical CNS cells with a more accurate and efficient way to detect and analyze astrocytes
Identification of glycosylations affected by androgen-regulated process on the surface of extracellular vesicles derived from PCa cell lines
Full text linkIntroduction: Prostate cancer (PCa) is one of the leading death-causing cancers in males. Lack of sensitivity of the current diagnostic approach created an opportunity for a new diagnostic method. Altered glycosylation is a well-known phenomenon in cancer and can be used as an essential hint for identification of biomarkers of cancer. In this research, the aim is to identify glycosylation from PCa cell line on extracellular vesicles (EVs) which is regulated by the androgen hormone using a variety of lectins.
Methods: The LNCaP, a PCa cell line, was treated with androgen hormone agonist DHT (R1881) and antagonist enzalutamide (MDV3100). Then EVs were isolated from hormone-treated and untreated LNCaP cell culture medium. Then EVs were captured by biotinylated anti- CD9.C11 which was immobilized in a streptavidin-coated microtiter plate with EU+3-coated nanoparticles (NPs) conjugated with lectins was used to detect the surface glycan of EVs. To maintain an equal amount of EVs in each well, 800ng total protein was added.
Results: Among twenty-four screened lectins, UEA (Ulex europaeus Agglutinin) presents a considerable amount of fluorescence signal to the EVs from the LNCaP cell line. We noticed that fucosylation in EVs-derived from LNCaP cell was increased by R1881 and decreased by MDV3100 which is indicated by the fucose-binding lectin UEA. Antibodies against tetraspanins were conjugates with NPs which was used for normalizing signal. Our results give a hint for androgen hormone and EVs glycosylation for detecting PCa from the simple assay.
Conclusion: Influence of glycosylation and androgen in PCa is a well-studied phenomenon. Therefore, identification of glycosylation in the surface of EVs from the simple lectin-NPs technique would be a useful approach for EVs-based cancer diagnosis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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