HIV diagnosis and disclosure

For those we interviewed the knowledge that either they or their partner had diagnosed HIV needed to be managed on both an individual and collective level. It impacted on how each partner saw themselves and also how they perceived the future of their relationship. This report begins by exploring how participants with diagnosed HIV became aware of their HIV status, and how they have tried to come to terms with it, before describing their decision making about sharing this status with their partner and their means of doing so. The thoughts and experiences of participants who had not disclosed their status are described. Finally it explores the reactions of the HIV negative or untested partners to disclosure, its impact on a personal level and how they sought to come to terms with this news

Relación entre conocimientos y prácticas de las medidas de bioseguridad en el personal expuesto a material biológico y punzocortantes. Hospital Metropolitano Vivian Pellas, Agosto 2012 a Mayo 2013.

Estudio descriptivo tipo relacional. Se encontró que el 86.2% del personal expuesto son asistenciales, predominando el sexo femenino cuyos años de antigüedad están entre 1-10 años. La medida que menos se cumple es el lavado de manos 66.6% y el uso de guantes 88.8%. Conocen las normas de bioseguridad; sin embargo, no las aplican en su totalidad. Se identificó que se tiene que fortalecer de forma particular en el manejo de las consecuencias post pinchazo y salpicadura por sangre y material biológico

Narrowing the Digital Divide: The Young Women Leaders Program HerStory Project

Research suggests that girls are at especial disadvantage in the field of informational technology and are less likely than boys to take courses or seek out careers in this area. The Young Women Leaders Program (YWLP), a mentoring program at the University of Virginia that pairs at-risk middle school girls with college women for a year of mentoring, developed the YWLP HerStory project to engage middle school girls in informational technology through their development of technology projects focused on psychosocial issues of importance to them. This study reviewed an early version of the YWLP HerStory’s technology curriculum and training for mentors, the revisions made to both, and evaluated the effectiveness of the revisions with a sample of 27 eighth grade girls and their mentors. Findings indicated that participating in the revised curriculum improved girls’ engagement in technology projects, including an 83% completion rate, and modifications to mentor training improved mentor’s grasp of relevant technology and confidence in teaching it to their mentees. Notably, participating eighth grade girls reported that the technology curriculum was fun and expressed an interest in further engagement in using technology platforms to tell their stories

Single Cell Analysis of Transcriptional Activation Dynamics

Gene activation is thought to occur through a series of temporally defined regulatory steps. However, this process has not been completely evaluated in single living mammalian cells.To investigate the timing and coordination of gene activation events, we tracked the recruitment of GCN5 (histone acetyltransferase), RNA polymerase II, Brd2 and Brd4 (acetyl-lysine binding proteins), in relation to a VP16-transcriptional activator, to a transcription site that can be visualized in single living cells. All accumulated rapidly with the VP16 activator as did the transcribed RNA. RNA was also detected at significantly more transcription sites in cells expressing the VP16-activator compared to a p53-activator. After alpha-amanitin pre-treatment, the VP16-activator, GCN5, and Brd2 are still recruited to the transcription site but the chromatin does not decondense.This study demonstrates that a strong activator can rapidly overcome the condensed chromatin structure of an inactive transcription site and supercede the expected requirement for regulatory events to proceed in a temporally defined order. Additionally, activator strength determines the number of cells in which transcription is induced as well as the extent of chromatin decondensation. As chromatin decondensation is significantly reduced after alpha-amanitin pre-treatment, despite the recruitment of transcriptional activation factors, this provides further evidence that transcription drives large-scale chromatin decondensation

Increased Incidence of Loco-Regional Recurrences Among African American Women with Terminal Stage Breast Cancer

A prospective analysis of women with terminal breast cancer admitted to CHNE from November 2006–August 2007 evaluated anecdotal observations that African American (AA) women are likelier than Caucasian women to evidence loco-regional recurrences (LRR). Women with terminal breast cancer who were admitted to CHNE, a not-for-profit hospice serving over 90% of Northeast Florida hospice patients, were eligible for participation. 134 terminal breast cancer patients were assessed by hospice nurses for LRR presence via chest wall examination. 80% of them (107) were Caucasian, 17% (23) were AA and 3% (4) were of other ethnicities. Evidence of LRR were noted in 13% of the women (17/134). The proportion of patients with LRR was higher in AA women than Caucasian women (26% vs. 10%, 6/23 vs. 11/107, respectively), although this difference was not statistically significant (p = 0.08). The majority of Caucasian women with LRR consented to a medical record review, but a minority of AA women consented (8/11 vs. 2/6, respectively, p = 0.16)

Extreme Rainfall Event Classification Using Machine Learning for Kikuletwa River Floods

A research article was submitted to Water 2023, volume 15Advancements in machine learning techniques, availability of more data sets, and increased computing power have enabled a significant growth in a number of research areas. Predicting, detecting, and classifying complex events in earth systems which by nature are difficult to model is one such area. In this work, we investigate the application of different machine learning techniques for detecting and classifying extreme rainfall events in a sub-catchment within the Pangani River Basin, found in Northern Tanzania. Identification and classification of extreme rainfall event is a preliminary crucial task towards success in predicting rainfall-induced river floods. To identify a rain condition in the selected sub-catchment, we use data from five weather stations that have been labeled for the whole sub-catchment. In order to assess which machine learning technique is better suited for rainfall classification, we apply five different algorithms in a historical dataset for the period of 1979 to 2014. We evaluate the performance of the models in terms of precision and recall, reporting random forest and XGBoost as having the best overall performances. However, because the class distribution is imbalanced, a generic multi-layer perceptron performs best when identifying heavy rainfall events, which are eventually the main cause of rainfall-induced river floods in the Pangani River Basi

Estimates of Genetic Variability for Seedling Traits in Fluted Pumpkin (Telfairia occidentalis Hook. F)

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT An experiment was conducted to evaluate genetic variation among twenty-one fluted pumpkin genotypes for seedling traits. The seeds of the fluted pumpkin were germinated in nursery bags filled with saw dust at the Federal University of Agriculture, Abeokuta and the Federal University of Technology, Akure, Nigeria between July and August, 2013. The experiment was laid out in completely randomized design with three replications. Characters evaluated were emergence percentage (E%), emergence index, emergence index rate, vine length (cm), leaf area (cm 2 ), number of leaves, shoot dry weight (g), and seedling vigour index (SVI). Significant (P≤0.05) differences were observed among the fluted pumpkin genotypes for the evaluated characters. High E% was observed for genotypes Ftn45 (94.80%), Ftn43 (93.30%), Ftn57 (93.30%), Fte41 (90.0%), Ftn61 (86.70%), and Ftm11 (83.30%). Also, these genotypes had above average values for SVI. High phenotypic coefficients of variation and genotypic coefficients of variation were observed for leaf area (75.44%) and dry shoot weight (55.85%), respectively while heritability estimates above 50% was observed for leaf area (82.0%), dry weight (77.78%), E% (70.84%), and SVI (51.98%). The genetic advance was high for E% (38.37), SVI (38.09), and leaf area. SVI, E%, vine length, and leaf area had significant positive correlation with most of the traits therefore, they can be used as selection criteria in fluted pumpkin. Therefore, genetic improvement of early seedling can be used for selection programme in fluted pumpkin

Sensor-Based River Monitoring System: A Case for Kikuletwa River Floods in Tanzania

A research was submitted to computer science and mathematics volume 2, 2023Reliable and accurate flood prediction is a challenging task in poorly gauged basins due 1 to data scarcity. Data is an essential component of any AI/ML model today, and the performance 2 of such models hugely depends on the availability of sufficient amount of trusted, representative 3 data. However, unlike a few well-studied rivers, most of the rivers in developing countries are still 4 insufficiently monitored, which significantly hinges the design and development of advanced flood 5 prediction models and early warning systems. This paper presents a multi-modal, sensor-based and 6near-real time river monitoring system to produce a mul ti-feature data set for the Kikuletwa river in 7 Northern Tanzania, an area that heavily suffers from frequent floods. Our deployed system, which 8 gather information about river depth levels and weather at several locations, aims at widening the 9 ground truth of the river characteristics and eventually improve the accuracy of flood predictions. We 10 provide details on the monitoring system used to gather the data as well as report on the methodology 11 and the nature of the data. Finally, we present the relevance of the data set in the context of flood 12 prediction, discussing the most suitable AI/ML-based forecasting approaches, while also highlighting 13 some applications of the data set beyond flood warning systems

Extreme Rainfall Events Classification Using Machine Learning for Kikuletwa River Floods

A research article was submitted by artificial intelligence and machine learningAdvancements in Machine Learning techniques, availability of more data-sets, and 1 increased computing power have enabled a significant growth in a number research areas. Predicting, 2 detecting and classifying complex events in earth systems which by nature are difficult to model 3 is one of such areas. In this work, we investigate the application of different machine learning 4 techniques for detecting and classifying extreme rainfall events in a sub-catchment within Pangani 5 River Basin, found in Northern Tanzania. Identification and classification of extreme rainfall event 6is a preliminary crucial task towards success in predicting rainfall-induced river floods. To identify 7 a rain condition in the selected sub-catchment, we use data from five weather stations which have 8 been labeled for the whole sub-catchment. In order to assess which Machine Learning technique 9 suits better for rainfall classification, we apply five different algorithms in a historical dataset for the 10 period of 1979 to 2014. We evaluate the performance of the models in terms of precision and recall, 11 reporting Random Forest and XGBoost as the ones with best overall performance. However, since the 12 class distribution is imbalanced, the generic Multi-layer Perceptron performs best when identifying 13 the heavy rainfall events, which are eventually the main cause of rainfall-induced river floods in the 14 Pangani River Basin

Letters of Comment

Letters from readers in The Mythic Circle #