‘Because it’s our culture!’ (Re)negotiating the meaning of lobola in Southern African secondary schools

Payment of bridewealth or lobola is a significant element of marriage among the Basotho of Lesotho and the Shona of Zimbabwe. However, the functions and meanings attached to the practice are constantly changing. In order to gauge the interpretations attached to lobola by young people today, this paper analyses a series of focus group discussions conducted among senior students at two rural secondary schools. It compares the interpretations attached by the students to the practice of lobola with academic interpretations (both historical and contemporary). Among young people the meanings and functions of lobola are hotly contested, but differ markedly from those set out in the academic literature. While many students see lobola as a valued part of ‘African culture’, most also view it as a financial transaction which necessarily disadvantages women. The paper then seeks to explain the young people’s interpretations by reference to discourses of ‘equal rights’ and ‘culture’ prevalent in secondary schools. Young people make use of these discourses in (re)negotiating the meaning of lobola, but the limitations of the discourses restrict the interpretations of lobola available to them

A Combined Offline and Online Algorithm for Real-Time and Long-Term Classification of Sheep Behaviour: Novel Approach for Precision Livestock Farming

Real-time and long-term behavioural monitoring systems in precision livestock farming have huge potential to improve welfare and productivity for the better health of farm animals. However, some of the biggest challenges for long-term monitoring systems relate to “concept drift”, which occurs when systems are presented with challenging new or changing conditions, and/or in scenarios where training data is not accurately reflective of live sensed data. This study presents a combined offline algorithm and online learning algorithm which deals with concept drift and is deemed by the authors as a useful mechanism for long-term in-the-field monitoring systems. The proposed algorithm classifies three relevant sheep behaviours using information from an embedded edge device that includes tri-axial accelerometer and tri-axial gyroscope sensors. The proposed approach is for the first time reported in precision livestock behavior monitoring and demonstrates improvement in classifying relevant behaviour in sheep, in real-time, under dynamically changing conditions

Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network.

PurposeTo assess feasibility of training a convolutional neural network (CNN) to automate liver segmentation across different imaging modalities and techniques used in clinical practice and apply this to enable automation of liver biometry.MethodsWe trained a 2D U-Net CNN for liver segmentation in two stages using 330 abdominal MRI and CT exams acquired at our institution. First, we trained the neural network with non-contrast multi-echo spoiled-gradient-echo (SGPR)images with 300 MRI exams to provide multiple signal-weightings. Then, we used transfer learning to generalize the CNN with additional images from 30 contrast-enhanced MRI and CT exams.We assessed the performance of the CNN using a distinct multi-institutional data set curated from multiple sources (n = 498 subjects). Segmentation accuracy was evaluated by computing Dice scores. Utilizing these segmentations, we computed liver volume from CT and T1-weighted (T1w) MRI exams, and estimated hepatic proton- density-fat-fraction (PDFF) from multi-echo T2*w MRI exams. We compared quantitative volumetry and PDFF estimates between automated and manual segmentation using Pearson correlation and Bland-Altman statistics.ResultsDice scores were 0.94 ± 0.06 for CT (n = 230), 0.95 ± 0.03 (n = 100) for T1w MR, and 0.92 ± 0.05 for T2*w MR (n = 169). Liver volume measured by manual and automated segmentation agreed closely for CT (95% limit-of-agreement (LoA) = [-298 mL, 180 mL]) and T1w MR (LoA = [-358 mL, 180 mL]). Hepatic PDFF measured by the two segmentations also agreed closely (LoA = [-0.62%, 0.80%]).ConclusionsUtilizing a transfer-learning strategy, we have demonstrated the feasibility of a CNN to be generalized to perform liver segmentations across different imaging techniques and modalities. With further refinement and validation, CNNs may have broad applicability for multimodal liver volumetry and hepatic tissue characterization

First measurement of the Head-Tail directional nuclear recoil signature at energies relevant to WIMP dark matter searches

We present first evidence for the so-called Head-Tail asymmetry signature of neutron-induced nuclear recoil tracks at energies down to 1.5 keV/amu using the 1m^3 DRIFT-IIc dark matter detector. This regime is appropriate for recoils induced by Weakly Interacting Massive Particle (WIMPs) but one where the differential ionization is poorly understood. We show that the distribution of recoil energies and directions induced here by Cf-252 neutrons matches well that expected from massive WIMPs. The results open a powerful new means of searching for a galactic signature from WIMPs.Comment: 4 pages, 6 figures, 1 tabl

Identifying nonalcoholic fatty liver disease patients with active fibrosis by measuring extracellular matrix remodeling rates in tissue and blood.

Excess collagen synthesis (fibrogenesis) in the liver plays a causal role in the progression of nonalcoholic fatty liver disease (NAFLD). Methods are needed to identify patients with more rapidly progressing disease and to demonstrate early response to treatment. We describe here a novel method to quantify hepatic fibrogenesis flux rates both directly in liver tissue and noninvasively in blood. Twenty-one patients with suspected NAFLD ingested heavy water (2 H2 O, 50-mL aliquots) two to three times daily for 3-5 weeks prior to a clinically indicated liver biopsy. Liver collagen fractional synthesis rate (FSR) and plasma lumican FSR were measured based on 2 H labeling using tandem mass spectrometry. Patients were classified by histology for fibrosis stage (F0-F4) and as having nonalcoholic fatty liver or nonalcoholic steatohepatitis (NASH). Magnetic resonance elastography measurements of liver stiffness were also performed. Hepatic collagen FSR in NAFLD increased with advancing disease stage (e.g., higher in NASH than nonalcoholic fatty liver, positive correlation with fibrosis score and liver stiffness) and correlated with hemoglobin A1C. In addition, plasma lumican FSR demonstrated a significant correlation with hepatic collagen FSR.ConclusionUsing a well-characterized cohort of patients with biopsy-proven NAFLD, this study demonstrates that hepatic scar in NASH is actively remodeled even in advanced fibrosis, a disease that is generally regarded as static and slowly progressive. Moreover, hepatic collagen FSR correlates with established risks for fibrotic disease progression in NASH, and plasma lumican FSR correlates with hepatic collagen FSR, suggesting applications as direct or surrogate markers, respectively, of hepatic fibrogenesis in humans. (Hepatology 2017;65:78-88)