Primaquine is the only widely used drug that prevents Plasmodium vivax malaria relapses, but adherence to the standard 14-day regimen is poor. We aimed to assess the efficacy of a shorter course (7 days) of primaquine for radical cure of vivax malaria. We did a randomised, double-blind, placebo-controlled, non-inferiority trial in eight health-care clinics (two each in Afghanistan, Ethiopia, Indonesia, and Vietnam). Patients (aged ≥6 months) with normal glucose-6-phosphate dehydrogenase (G6PD) and presenting with uncomplicated vivax malaria were enrolled. Patients were given standard blood schizontocidal treatment and randomly assigned (2:2:1) to receive 7 days of supervised primaquine (1·0 mg/kg per day), 14 days of supervised primaquine (0·5 mg/kg per day), or placebo. The primary endpoint was the incidence rate of symptomatic P vivax parasitaemia during the 12-month follow-up period, assessed in the intention-to-treat population. A margin of 0·07 recurrences per person-year was used to establish non-inferiority of the 7-day regimen compared with the 14-day regimen. This trial is registered at ClinicalTrials.gov (NCT01814683). Between July 20, 2014, and Nov 25, 2017, 2336 patients were enrolled. The incidence rate of symptomatic recurrent P vivax malaria was 0·18 (95% CI 0·15 to 0·21) recurrences per person-year for 935 patients in the 7-day primaquine group and 0·16 (0·13 to 0·18) for 937 patients in the 14-day primaquine group, a difference of 0·02 (-0·02 to 0·05, p=0·3405). The incidence rate for 464 patients in the placebo group was 0·96 (95% CI 0·83 to 1·08) recurrences per person-year. Potentially drug-related serious adverse events within 42 days of starting treatment were reported in nine (1·0%) of 935 patients in the 7-day group, one (0·1%) of 937 in the 14-day group and none of 464 in the control arm. Four of the serious adverse events were significant haemolysis (three in the 7-day group and one in the 14-day group). In patients with normal G6PD, 7-day primaquine was well tolerated and non-inferior to 14-day primaquine. The short-course regimen might improve adherence and therefore the effectiveness of primaquine for radical cure of P vivax malaria. UK Department for International Development, UK Medical Research Council, UK National Institute for Health Research, and the Wellcome Trust through the Joint Global Health Trials Scheme (MR/K007424/1) and the Bill & Melinda Gates Foundation (OPP1054404).

BACKGROUND AND PURPOSE: Although CT perfusion is a promising tool to support treatment decisions for patients with acute ischemic stroke, it still lacks a standardized method for CTP analysis. The purpose of this study was to assess the variability of the area of infarct core and penumbra as presented in summary maps produced by 2 different software packages. MATERIALS AND METHODS: Forty-one CTP image datasets of 26 consecutive patients who presented with acute ischemic stroke were retrospectively evaluated. Identical image datasets were analyzed by using 2 different commercially available CTP analysis software packages, each representing a mainstream of widely used algorithms: delay-sensitive and delay-insensitive. Bland-Altman analyses were performed to evaluate the level of agreement between the 2 methods in determining the area of infarct core and penumbra area in the summary maps. RESULTS: There was a statistically significant difference in infarct core area (−23.6 ± 25.6 cm²) and penumbra area (15.8 ± 25.3 cm²) between the 2 software packages. For all the areas presented in the summary maps, the Bland-Altman interval limit of agreement was larger than 100 cm². CONCLUSIONS: The infarct core and penumbra area of CTP summary maps generated by 2 commonly used software packages were significantly different, emphasizing the need for standardization and validation of CTP analysis before it can be applied to patient management in clinical practice.

The continuous monitoring of pollution level in urban areas is important for a smart city. There are several parameters changes that indicate the pollution: dust particle density in the air, humidity, light intensity, and the level of sound noise. A technology that can be developed for an integrated pollution monitoring system is wireless sensor network (WSN) utilizing waspmote smart cities device, connected with several sensors, such as dust sensor PM-10 (GPY21010AU0F), humidity sensor (808H5V5), luminosity sensor (LDR), and microphone (dBA). As a communication protocol we used 3G connectivity to store the data to cloud system. Prototype of this system had been tested in controlled laboratory environment and the performance of developed system was as expected. Result of this system can be used by government and policy makers as basic information to take further actions reducing pollution level.

This paper proposed a simple but highly accurate feature extraction method for epilepsy detection from electroencephalogram (EEG) signals. Based on the combination of Discrete Wavelet Transform (DWT) and the newly proposed features Local Binary Pattern Transition Histogram (LBPTH) and Local Binary Pattern Mean Absolute Deviation (LBPMAD), our proposed feature extraction method can efficiently extract features from EEG signals for machine learning classification of epilepsy, achieving high classification accuracy with a feature size of only 18 for each signal. Tested on the publicly available University of Bonn Epilepsy EEG Dataset using a signal length of 4097 data points (23.61 seconds), the proposed method achieved larger than 99.6% accuracy results for Support Vector Machine (SVM) and k-Nearest Neighbor (KNN) classification of ictal (set E) against any non-ictal (set A, B, C, or D) or combinations of non-ictal (set $\text{A}+\text{B}$ , set $\text{C}+\text{D}$ , or set $\text{A}+\text{B}+\text{C}+\text{D}$ ) EEG signals, which is among the best of currently published works. Our method can maintain high classification accuracy even with short input signals, achieving more than 99.1% SVM classification accuracy when input signal length is reduced to 512 data points (2.95 seconds). The high accuracy, small feature size, ability to work with short input signals and low computing requirements made the proposed method suitable for mobile, low power, and low-cost wearable medical devices.

Palm oil has important role for the plantation subsector. Forecasting of the real palm oil production in certain period is needed by plantation companies to maintain their strategic management. This study compared several methods based on exponential smoothing (ES) technique such as single ES, double exponential smoothing holt, triple exponential smoothing, triple exponential smoothing additive and multiplicative to predict the palm oil production. We examined the accuracy of forecasting models of production data and analyzed the characteristics of the models. Programming language R was used with selected constants for double ES (α and β) and triple ES (α, β, and γ) evaluated by the technique of minimizing the root mean squared prediction error (RMSE). Our result showed that triple ES additives had lowest error rate compared to the other models with RMSE of 0.10 with a combination of parameters α = 0.6, β = 0.02, and γ = 0.02.