Visual Analytics of Tuberculosis Detection Rat Performance

The diagnosis of tuberculosis (TB) disease remains a global challenge, and the need for innovative diagnostic approaches is inevitable. Trained African giant pouched rats are the scent TB detection technology for operational research. The adoption of this technology is beneficial to countries with a high TB burden due to its cost-effectiveness and speed than microscopy. However, rats with some factors perform better. Thus, more insights on factors that may affect performance is important to increase rats’ TB detection performance. This paper intends to provide understanding on the factors that influence rats TB detection performance using visual analytics approach. Visual analytics provide insight of data through the combination of computational predictive models and interactive visualizations. Three algorithms such as Decision tree, Random Forest and Naive Bayes were used to predict the factors that influence rats TB detection performance. Hence, our study found that age is the most significant factor, and rats of ages between 3.1 to 6 years portrayed potentiality. The algorithms were validated using the same test data to check their prediction accuracy. The accuracy check showed that the random forest outperforms with an accuracy of 78.82% than the two. However, their accuracies difference is small. The study findings may help rats TB trainers, researchers in rats TB and Information system, and decision makers to improve detection performance. This study recommends further research that incorporates gender factors and a large sample size.

Full optimization and validation of an HPLC method for the quantitative analysis of total sugars in a soft drink

Five HPLC methods were employed for the quantitative analysis of three natural sugars namely fructose, glucose and sucrose in soft drinks. HPLC-refractive index detector (RID)-AMINO proved to be the most suitable HPLC method to carry out the latter task. For the optimum separation and response of the natural sugars the best conditions employed were column oven temperature 30 oC, flow rate 0.1 mL/min, mobile phase ratio acetonitrile:water 75:25 and they were determined by studying all possible interactions among these three parameters. Full validation of HPLC-RID-AMINO was performed in terms of system suitability test, precision check, accuracy check and robustness. KEY WORDS: Sugar, Soft drink, Experimental design, Validation, HPLC, System suitability Bull. Chem. Soc. Ethiop. 2020, 34(2), 419-426 DOI: https://dx.doi.org/10.4314/bcse.v34i2.17

Effects of Land Use Change on the Ecosystem Services Value in an Agro-Pastoral Ecotone

Human activities and the demand for biomass and biobased energy can lead to changes in land use. Songyuan City is a typical farming-pastoral ecotone in northeast China, to investigate the land use change in this area, the Landsat TM/OLI remote sensing images in 2000, 2010 and 2019 were analyzed. The land use in the ecotone in 2030 was predicted, as well as the changing characteristic of its ecosystem services value (ESV). The results showed that paddy field has had the highest annual growth rate and the ESV has increased by 338.6 million Chinese Yuan (CNY) in the past 19 years. The areas of dry field, paddy field, water bodies, wetland, and building land showed an upward trend with the dry field having the most growth of 49,596 hm2, whereas the areas of forestland, meadowland, and unused land showed a downward trend; and ESV increases from 3.5714 billion CNY in 2010 to 3.6236 billion CNY in 2030. Accuracy check and sensitivity analysis indicated a reliable result, which could provide reference to the ecologically sustainable development.

Feasibility study of a verification method for proton and carbon ion radiotherapy plan delivery accuracy check

Background All plan verification systems available for particle therapy are designed for pre-treatment verification. The plan delivery accuracy during treatment are unknown. The purpose of this study is to introduce a verification method and develop a software for proton and carbon ion plan delivery accuracy check. Methods A program was developed using Matlab to reconstruct dose from beam parameters recorded in log files and compare the dose reconstructed with the dose calculated by treatment planning system (TPS). Ten carbon ion plans and ten proton plans were enrolled in this study for algorithm validation, sensitivity analysis and plan delivery verification. The dose reconstruction algorithm was validated by comparing the dose calculated by TPS with reconstructed dose using the same beam parameters. The sensitivity of gamma pass rate to spot size deviation, position deviation and particle number deviation were analyzed by comparing dose reconstructed from pseudo plans which have manually added errors with original plan dose. Then plan delivery verification using homemade software were done for the 20 actual treated plans. Results A program for plan delivery verification was developed. For the validation of dose reconstruction algorithm, the mean dose difference between reconstructed dose and plan dose were 0.70% ± 0.24% and 0.51% ± 0.25% for carbon ion and proton plans, respectively. According to our simulation, the Gamma pass rate of carbon ion beam is more sensitive to spot position deviation and particle number deviation, and the Gamma pass rate of proton beam is more sensitive to spot size deviation. For the actual plan delivery verification using homemade software, the mean gamma pass rate were 99.47% ± 0.48%, 99.36% ± 0.50% and 99.48% ± 0.50% for carbon ion beams and 99.92% ± 0.13%, 99.96% ±0.06% and 99.89% ±0.13% for proton beams at three different depth of high dose region using 3mm/3% criteria. Conclusions A software was programed and the algorithm was verified. The method we introduced and the software we made for plan delivery verification is feasible and reliable. The verification method presented in this study can be easily repeated in other hospital.

Accuracy checking of dispensed medications by a pharmacy technician: a hospital case study

Medication order accuracy checking is an integral and time-consuming component of the current Australian pharmacist’s role. However, the pharmacy profession internationally has moved towards separating the checking task into two parts: a clinical check performed by the registered pharmacist and a technical accuracy check delegated to an appropriately trained pharmacy technician. This case study demonstrates that in an Australian hospital pharmacy context, appropriately trained pharmacy technicians have the potential to be more proficient and time efficient than pharmacists when undertaking accuracy checking of dispensed medications. What is known about the topic?International data have shown that appropriately trained pharmacy technicians can be more precise than pharmacists when performing accuracy checking. What does this paper add?This paper reports the findings of an Australian case study reallocating the accuracy checking task to trained pharmacy technicians and evaluating the time efficiency data, which has not previously been reported. What are the implications for practitioners?These findings provide support for the potential to safely delegate checking tasks to an appropriately trained accuracy checking pharmacy technician.

The Care Quality Commission's factual accuracy check guidance: an update

The 10-day period allowed to providers for comment on the factual accuracy of draft reports is a critical phase. The recent changes to this process are easily missed, but may mean a difference between ratings. Anna Hart clarifies these small yet crucial updates to the regulatory guidance

FCM Approach of Similarity and Dissimilarity Measures with α-Cut for Handling Mixed Pixels

In this paper, the fuzzy c-means (FCM) classifier has been studied with 12 similarity and dissimilarity measures: Manhattan distance, chessboard distance, Bray–Curtis distance, Canberra, Cosine distance, correlation distance, mean absolute difference, median absolute difference, Euclidean, Mahalanobis, diagonal Mahalanobis and normalised squared Euclidean distance. Both single and composite modes were used with a varying weight constant (m*) and also at different α-cuts. The two best single measures obtained were combined to study the effect of composite measures on the datasets used. An image-to-image accuracy check was conducted to assess the accuracy of the classified images. Fuzzy error matrix (FERM) was applied to measure the accuracy assessment outcomes for a Landsat-8 dataset with respect to the Formosat-2 dataset. To conclude, FCM classifier with Cosine measure performed better than the conventional Euclidean measure. But, due to the incapability of the FCM classifier to handle noise properly, the classification accuracy was around 75%.