Evaluation of the undergraduate family medicine programme of Faculty of Medicine, University of Kelaniya : quantitative and qualitative student feedback

Background: Worldwide there is an increasing emphasis on the importance of primary care. The ministry of health Sri Lanka issued a directive in 2016 that training of doctors in primary care should be strengthened. Medical students of the Faculty of Medicine, University of Kelaniya follow a 1 month long clinical appointment in family medicine in their fourth year of study. Methods: Feedback is taken from students on completion of the appointment. Half the students from each group complete a pre tested structured feedback questionnaire that consists of answers to questions based on a likert scale with a space for free comments. The other half provide qualitative feedback. In this evaluation data were gathered from 185 (98%) students from all eight clinical groups throughout the year 2016. Quantitative data were analysed using SPSS version 22. Inductive thematic analysis was used to analyse the qualitative data from the Round Robin activity and free comments from the questionnaire. Results: The qualitative feedback provided a richer indepth overview of student ideas on the appointment compared to the quantitative data. In reflection of a desire for learning to be of relevance students wanted clinically oriented teaching focused on management. They preferred active teaching learning methods such as the opportunity to conduct consultations and receive immediate feedback. Students had a high regard for the teaching sessions by general practitioners at their clinics. The appointment had created an interest in the discipline of family medicine which could have an impact on future choice of career. There were indications to suggest that student attitudes towards patients may have evolved to be more patient centred. Students appreciated the inclusive and low stress ambience of the learning environment. Conclusions and recommendations: Regular evaluation of teaching programmes helps maintain accountability of faculty and paves the way for more student centred teaching through the incorporation of students’ views in devising teaching methods. This evaluation found that qualitative feedback provided more descriptive material to reflect on and therefore improve teaching on the programme. It is recommended that more use should be made of qualitative methodologies in programme evaluations

Frequency Domain Measurements for Diagnosis of Power Transformers: Experiences from Australia, Malaysia, Sri Lanka and UK

This is the author accepted manuscript. The final version is available from CIGRE via the link in this recordPower transformers and their performance and reliability in electric power networks are important research issues of power systems. Much information has already been collected and reported; however, it is rare to report comparisons of transformer service performance under different geographical locations and working conditions. CIGRE Working Group A2.37 collected information on 964 transformer failures from 58 utilities and 21 countries covering the period from 1996 to 2009. The main failure modes included failures in windings, tap changers, bushings, insulation, and core. As estimated, based on available literature, nearly 50% of the failures could be related to transformer windings and insulation. This collective paper summarizes experiences from the use of diagnostic tools based on frequency domain measurements at different geographical regions of the world. It starts with a short introduction to response measurements in frequency domain for condition assessment of transformers; then theoretical backgrounds of the two widely used response measurements, namely Frequency Dielectric Spectroscopy (FDS) and Frequency Response Analysis (FRA), are presented. Afterward details of tested transformers and measurement procedures are described for which selected set of FDS and FRA measurement results are analysed for respectively elucidating their potential in assessment of moisture content, ageing degree and fault identi cation

Host-mediated beneficial effects of phytochemicals for prevention of avian coccidiosis

Both in vitro and in vivo studies were conducted to evaluate the beneficial effects of green tea extract (GT), cinnamon oil (CO), and pomegranate extract (PO) on avian coccidiosis. In experiment (EXP) 1, an in vitro culture system was used to investigate the individual effects of GT, CO, and PO on the proinflammatory cytokine response and integrity of tight junction (TJ) in chicken intestinal epithelial cells (IEC), on the differentiation of quail muscle cells and primary chicken embryonic muscle cells, and anticoccidial and antibacterial activities against Eimeria tenella sporozoites and Clostridium perfringens bacteria, respectively. In EXP 2 and 3, in vivo trials were carried out to study the dose-dependent effect of blended phytochemicals (GT, CO, PO) on coccidiosis in broiler chickens infected with E. maxima. For EXP 2, one hundred male broiler chickens (0-day-old) were allocated into the following five treatment groups: Control group for non-infected chickens (NC), Basal diet group for E. maxima-infected chickens (PC), PC group supplemented with phytochemicals at 50 (Phy 50), 100 (Phy 100), and 200 (Phy 200) mg/kg feed diets for E. maxima-infected chickens. For EXP 3, one hundred twenty male broiler chickens (0-day-old) were allocated into the following six treatment groups: NC, PC, PC supplemented with phytochemicals at 10 (Phy 10), 20 (Phy 20), 30 (Phy 30), and 100 (Phy 100) mg/kg feed for E. maxima-infected chickens. Body weights (BW) were measured on days 0, 7, 14, 20, and 22, and jejunum samples were used to measure cytokine, TJ protein, and antioxidant enzyme responses at 8 days post-infection (dpi). Fecal samples for oocyst enumeration were collected from 6 to 8 dpi. In vitro, CO and PO reduced LPS-induced IL-1β and IL-8 in IEC, respectively, and GT enhanced the gene expression of occludin in IEC. PO at 1.0 and 5.0 mg/mL exerted antimicrobial effect against E. tenella sporozoites and C. perfringens bacteria, respectively. In vivo, chickens fed a diet supplemented with phytochemicals showed enhanced BW, reduced oocyst shedding, and decreased proinflammatory cytokines following E. maxima challenge. In conclusion, the combination of GT, CO, and PO in the diet of broiler chickens infected with E. maxima induced enhanced host disease resistance including innate immunity and gut health, which contributed to improved growth and reduced disease responses. These findings provide scientific support for the development of a novel phytogenic feed additive formula that enhances the growth and intestinal health of broiler chickens infected with coccidiosis

Cost minimization analysis of different growth hormone pen devices based on time-and-motion simulations

<p>Abstract</p> <p>Background</p> <p>Numerous pen devices are available to administer recombinant Human Growth Hormone (rhGH), and both patients and health plans have varying issues to consider when selecting a particular product and device for daily use. Therefore, the present study utilized multi-dimensional product analysis to assess potential time involvement, required weekly administration steps, and utilization costs relative to daily rhGH administration.</p> <p>Methods</p> <p>Study objectives were to conduct 1) Time-and-Motion (TM) simulations in a randomized block design that allowed time and steps comparisons related to rhGH preparation, administration and storage, and 2) a Cost Minimization Analysis (CMA) relative to opportunity and supply costs. Nurses naïve to rhGH administration and devices were recruited to evaluate four rhGH pen devices (2 in liquid form, 2 requiring reconstitution) via TM simulations. Five videotaped and timed trials for each product were evaluated based on: 1) Learning (initial use instructions), 2) Preparation (arrange device for use), 3) Administration (actual simulation manikin injection), and 4) Storage (maintain product viability between doses), in addition to assessment of steps required for weekly use. The CMA applied micro-costing techniques related to opportunity costs for caregivers (categorized as wages), non-drug medical supplies, and drug product costs.</p> <p>Results</p> <p>Norditropin^®NordiFlex and Norditropin^®NordiPen (NNF and NNP, Novo Nordisk, Inc., Bagsværd, Denmark) took less weekly Total Time (p < 0.05) to use than either of the comparator products, Genotropin^®Pen (GTP, Pfizer, Inc, New York, New York) or HumatroPen^®(HTP, Eli Lilly and Company, Indianapolis, Indiana). Time savings were directly related to differences in new package Preparation times (NNF (1.35 minutes), NNP (2.48 minutes) GTP (4.11 minutes), HTP (8.64 minutes), p < 0.05)). Administration and Storage times were not statistically different. NNF (15.8 minutes) and NNP (16.2 minutes) also took less time to Learn than HTP (24.0 minutes) and GTP (26.0 minutes), p < 0.05). The number of weekly required administration steps was also least with NNF and NNP. Opportunity cost savings were greater in devices that were easier to prepare for use; GTP represented an 11.8% drug product savings over NNF, NNP and HTP at time of study. Overall supply costs represented <1% of drug costs for all devices.</p> <p>Conclusions</p> <p>Time-and-motion simulation data used to support a micro-cost analysis demonstrated that the pen device with the greater time demand has highest net costs.</p

The epidemiology of postpartum malaria: a systematic review

Pregnant women are more susceptible to malaria than their non-pregnant counterparts. Less is known about the risk of malaria in the postpartum period. The epidemiology of postpartum malaria was systematically reviewed. Eleven articles fitted the inclusion criteria. Of the 10 studies that compared malaria data from the postpartum period with pregnancy data, nine studies suggested that the risk for malaria infection decreased after delivery. All three studies that compared postpartum data with non-pregnant non-postpartum women concluded that the risk did not return to pre-pregnancy levels immediately after delivery. The results of this review have to be carefully interpreted, as the majority of studies were not designed to study postpartum malaria, and there was large variability in study designs and reported outcomes. Current evidence suggests an effort should be made to detect and radically cure malaria during pregnancy so that women do not enter the postpartum period with residual parasites

Role of Physiology, Immunity, Microbiota, and Infectious Diseases in the Gut Health of Poultry

&ldquo;Gut health&rdquo; refers to the physical state and physiological function of the gastrointestinal tract and in the livestock system; this topic is often focused on the complex interacting components of the intestinal system that influence animal growth performance and host-microbial homeostasis. Regardless, there is an increasing need to better understand the complexity of the intestinal system and the various factors that influence gut health, since the intestine is the largest immune and neuroendocrine organ that interacts with the most complex microbiome population. As we face the post-antibiotic growth promoters (AGP) era in many countries of the world, livestock need more options to deal with food security, food safety, and antibiotic resilience to maintain agricultural sustainability to feed the increasing human population. Furthermore, developing novel antibiotic alternative strategies needs a comprehensive understanding of how this complex system maintains homeostasis as we face unpredictable changes in external factors like antibiotic-resistant microbes, farming practices, climate changes, and consumers&rsquo; preferences for food. In this review, we attempt to assemble and summarize all the relevant information on chicken gut health to provide deeper insights into various aspects of gut health. Due to the broad and complex nature of the concept of &ldquo;gut health&rdquo;, we have highlighted the most pertinent factors related to the field performance of broiler chickens

Predictive Analytics in Cardiac Healthcare and 5G Cellular Networks

This thesis proposes the use of Machine Learning (ML) to two very distinct, yet compelling, applications – predicting cardiac arrhythmia episodes and predicting base station association in 5G networks comprising of virtual cells. In the first scenario, Support Vector Machines (SVMs) are used to classify features extracted from electrocardiogram (EKG) signals. The second problem requires a different formulation departing from traditional ML classification where the objective is to partition feature space into constituent class regions. Instead, the intention here is to identify temporal patterns in unequal-length sequences. Using Recurrent Neural Networks (RNNs), it is demonstrated that accurate predictions can be made as to the base station most likely to provide connectivity for a mobile device as it moves. Atrial Fibrillation (AF) is a common cardiac arrhythmia affecting several million people in the United States. It is a condition in which the upper chambers of the heart are unable to contract effectively leading to inhibited blood flow to the ventricles. The stagnation of blood is one of the major risk factors for stroke. The Computers in Cardiology Challenge 2001 was organized to further research into the prediction of episodes of AF. This research revisits the problem with some modifications. Patient-specific classifiers are developed for AF prediction using a different dataset and employing shorter EKG signal epochs. SVM classification yielded an average accuracy of just above 95% in identifying EKG epochs appearing just prior to fibrillatory rhythms. 5G cellular networks were envisaged to provide enhanced data rates for mobile broadband, support low-latency communication, and enable the Internet of Things (IoT). Handovers contribute to latency as mobile devices are switched between base stations due to movements. Given that customers may not be willing to continuously share their exact locations due to privacy concerns and the establishment of a mobile network architecture with dynamically created virtual cells, this research presents a solution for proactive mobility management using RNNs. A RNN is trained to identify patterns in variable-length sequences of Received Signal Strength (RSS) values, where a mobile device is permitted to connect to more than a single base station at a time. A classification accuracy of over 98% was achieved in a simulation model that was set up emulating an urban environment