A step-wise approach to a national hepatitis C screening strategy in Malaysia to meet the WHO 2030 targets: proposed strategy, coverage, and costs

In Malaysia, more than 330 000 individuals are estimated to be chronically infected with hepatitis C virus (HCV), but less than 2% have been treated to date. To estimate the required coverage and costs of a national screening strategy to inform the launch of an HCV elimination program. We designed an HCV screening strategy based on a "stepwise" approach. This approach relied on targeting of people who inject drugs in the early years, with delayed onset of widespread general population screening. Annual coverage requirements and associated costs were estimated to ensure that the World Health Organization elimination treatment targets were met. In total, 6 million individuals would have to be screened between 2018 and 2030. Targeting of people who inject drugs in the early years would limit annual screening coverage to less than 1 million individuals from 2018 to 2026. General population screening would have to be launched by 2026. Total costs were estimated at MYR 222 million ($58 million). Proportional to coverage targets, 60% of program costs would fall from 2026 to 2030

Alleviation of soil acidity improves the performance of oil palm progenies planted on an acid Ultisol

Soil acidity is one of the main factors that limit profitable and sustained agricultural production. Oil palm (Elaeis guineensis Jacq.) is mainly planted in acidic soils. In the last years, there has been a stagnated yield and increases in disease incidence and severity worldwide that could be attributed in some extent to soil acidity. This study was conducted to determine the effects of soil acidity alleviation on oil palm seedlings. The effects of ground magnesium limestone or dolomite and magnesium carbonate (0, 1.1, 2.2, 3.3 and 4.4 t ha -1) applied to an Ultisol dominated by kaolinite (pH in water 4.4) were evaluated on selected morphological, physiological and nutritional characteristics of hybrid (Deli dura-AVROS pisifera) and clonal (clone 366) oil palm progenies under nursery conditions for 8 months. Increasing rates of ground magnesium limestone and magnesium carbonate showed a significant effect on improving soil pH and lowering exchangeable aluminium. The hybrid oil palm showed significant either linear or quadratic trends for most of the parameters evaluated, indicating that the best responses for morphological and physiological traits were achieved from 2.5 to 4.23 t ha -1 with ground magnesium limestone and 2.87 to 3.45 t ha -1 with magnesium carbonate. Positive effects of increasing rates of ground magnesium limestone and magnesium carbonate were observed on nitrogen and magnesium uptake. Aluminium concentration in the third frond decreased significantly with increasing ground magnesium limestone rate. A significant reduction of manganese uptake was also observed with increasing rates of both ameliorants. The clonal oil palm progeny exhibited a better performance on un-amended treatment. This may be explained by the significant higher root growth of this progeny. Soil acidity alleviation improved the oil palm seedling growth. These results are important for the oil palm industry and could be applied in the nursery stage as well as extended to the immature stage

Variations in oil palm (Elaeis guineensis Jacq.) progeny response to high aluminium concentrations in solution culture

Aluminium (Al) phytotoxicity is an important soil constraint that limits crop yield. The objectives of this study were to investigate how growth, physiology, nutrient content and organic acid concentration is affected by Al, and to assess the degree of Al tolerance in different oil palm progeny (OPP). Four OPPs [‘A’ (Angola dura × Angola dura), ‘B’ (Nigerian dura × Nigerian dura), ‘C’ (Deli dura × AVROS pisifera) and ‘D’ (Deli dura × Dumpy AVROS pisifera)] were grown in different Al concentrations (0, 100 and 200 μm) in aerated Hoagland solution, pH 4.4, for 80 days. We observed a severe reduction (57.5%) in shoot dry weight, and root tips were reduced by 46.5% in 200 μm Al. In ‘B’ and ‘C’, the majority of macro- and micronutrients in plants were reduced significantly by 200 μm Al, with Mg being lowered by more than 50% in roots and shoots. The 200 μm Al treatment resulted in a 56.50% reduction in total leaf area, a 20% reduction in net photosynthesis and a 17% reduction in SPAD chlorophyll value in the third leaf. Root tips (0–5 mm) showed a significant increase in oxalic acid content with increasing Al concentration (∼5.86-fold); progeny ‘A’ had the highest concentration of oxalic acid. There was a significant interaction between Al concentration × OPP on total leaf number, root volume, lateral root length, Mg and K in root and shoot tissues, and Ca and N in shoots. The OPPs could be ranked in their tolerance to Al as: ‘A’ > ‘D’ > ‘B’ > ‘C’

Aluminium speciation of amended acid tropical soil and its effects on plant root growth

Exchangeable and soluble soil aluminum (Al) is limiting plant growth in many soils worldwide. This study evaluated the effects of increasing rates of dolomite and magnesium carbonate (MgCO3) on Al3+, pH, dissolved organic carbon, cations, anions, and Al speciation on oil palm Deli dura × AVROS pisifera root growth. Dolomite and MgCO3 additions significantly raised linearly soil solution pH, magnesium (Mg2+), nitrate (NO3 −) and chlorine (Cl−) concentrations; exponentially decreased the activity of phytotoxic Al species [aluminum (Al3+), aluminum sulfate (Al2SO4), and aluminum fluoride (AlF3)]; and reduced manganese (Mn) concentration and activity. High activity of those species exponentially reduced root dry weight. Optimum oil palm growth was achieved at: <50 μM monomeric Al, < 30 μM Mn, and <0.20 unit of the ratio Al+Mn to calcium (Ca)+Mg. High activity of Al species and Mn in acidic soil solution cause significant reduction of the root growth. Soil acidity alleviation either with dolomite or MgCO3 mitigates the toxic effect of Al and Mn

VIRTUAL SCREENING OF HETEROCYCLIC COMPOUNDS AGAINST ANGIOTENSIN-CONVERTING ENZYME FOR POTENTIAL ANTIHYPERTENSIVE INHIBITORS

Objective: The objective of this study was to investigate the antihypertensive activity of heterocyclic compounds against angiotensin-converting enzyme (ACE) through molecular docking studies. Methods: The X-ray crystal three-dimensional (3D) structure of human ACE complexed with lisinopril (PDB ID: 1O86) was retrieved from protein databank. The two-dimensional structures of 10 selected heterocyclic compounds were drawn in ACD-Chemsketch and converted into 3D structures. The 3D structures of compounds were virtually screened in the binding pockets of ACE using FlexX docking program. Further, the chemical entities revealing the molecular electronic structures of the best docked compound (Compound-4) were explored through density functional theory studies. Results: The Compound-4 showed the highest docking score of −26.6290 kJ/mol with ACE. The Hbond and non-bonded interactions are favored by phenylalanine, leucine, and arginine. The energy gap of 1.60 eV between highest occupied molecular orbital and lowest unoccupied molecular orbitals explained the presence of strong electron-acceptor group. Furthermore, the molecular electrostatic potential studies clearly envisaged the requirement of electropositive and electronegative groups are crucial for the ACE inhibitor activities. Conclusion: The identification of good ACE inhibitors requires the understanding of the current ACE inhibitors. Thus, the docking interactions of Compound-4 and its molecular electronic structure significantly imply its potential as antihypertensive agent. However, further clinical studies are required to ascertain its potential toxic effects

Al-Quran learning using mobile speech recognition:an overview

The usage of mobile application in various aspects has been worldwide accepted and there are variety of mobile applications which developed to cater the usage of different background of the user. In this paper, a short survey which includes questionnaire is distributed to find the interest of user whom using application for learning Quran and concept of mobile speech apps. The main interest of this survey is to find the acceptance of user and explanation on the proposed usage of mobile speech recognition with feature of learning apps. Factors of mobile speech recognition and mobile learning are listed to support the results from the short survey

Enhanced Secure Multi Keyword Top-K Retrieval in Cloud

This research is capable to do cryptography with multi keywords search. This research is target to provide search files from cloud network using multi keywords. This paper is target to provide a security at the maximum level by includes encryption and decryption. The administrator has control of authorization and allowing files to move more secured. Encryption and decryption of files and file names which is used symmetric and asymmetric algorithm respectively. The unique key is generated for every users to protect other user cannot access the files. While implementing this project the user can understand very simple environment. The user can reduce incapable systems in server side process to hold most of the processes. The client side system has used less work for the corresponding task to perform the necessary role like arranging and ranking the files from requested order. This project can apply in various applications for this user friendly

Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging

The transition to Electric Vehicles (EV) in place of traditional internal combustion engines is increasing societal demand for electricity. The ability to integrate the additional demand from EV charging into forecasting electricity demand is critical for maintaining the reliability of electricity generation and distribution. Load forecasting studies typically exclude households with home EV charging, focusing on offices, schools, and public charging stations. Moreover, they provide point forecasts which do not offer information about prediction uncertainty. Consequently, this paper proposes the Long Short-Term Memory Bayesian Neural Networks (LSTM-BNNs) for household load forecasting in presence of EV charging. The approach takes advantage of the LSTM model to capture the time dependencies and uses the dropout layer with Bayesian inference to generate prediction intervals. Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals. Moreover, the impact of lockdowns related to the COVID-19 pandemic on the load forecasting model is examined, and the analysis shows that there is no major change in the model performance as, for the considered households, the randomness of the EV charging outweighs the change due to pandemic

The cost of radiology procedures using Activity Based Costing (ABC) for development of cost weights in implementation of casemix system in Malaysia

Presently there is a gross lack of information on cost and cost weights in many developing countries that implement casemix system. Furthermore, studies that employed Activity Based Costing method (ABC) to estimate the costs of radiology procedures were rarely done in developing countries, including Malaysia. The main objective of this study is to determine the costs of radiology procedures for each group in casemix system, in order to develop cost weights to be used in the implementation of the casemix system. An economic evaluation study was conducted in all units in the Department of Radiology in the first teaching hospital using the casemix system in Malaysia. From the 25,754 cases, 16,173 (62.8%) of them were from medical discipline. Low One Third and High One Third (L3H3) method was employed to trim the outlier cases. Output from the trimming, 15,387 cases were included in the study. The results revealed that the total inpatients’ charges of all the radiology procedures was RM1,820,533.00 while the cost imputed using ABC method was RM2,970,505.54. The biggest cost component were human resources in Radiology Unit (Mobile) (57.5%), consumables (78.5%) of Endovascular Interventional Radiology (EIR) Unit, equipment (81.4%) of Magnetic Resonance Imaging (MRI) Unit, reagents (68.1%) of Medical Nuclear Unit. The one highest radiology cost weight, was for Malaysia Diagnosis Related Group (MY-DRG®) B-4-11-II (Hepatobiliary and Pancreas Neoplasms with severity level II, 2.8301). The method of calculation of the cost of procedures need to be revised by the hospital as findings from this study showed that the cost imposed to patient is lower than the actual cost

Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification

Echoed parts of Quranic accent (Qiraat) signals are exposed to reverberation of signals especially if they are listened to in a conference room or the Quranic recordings found in different media such as the web. Quranic verse rules identification/Tajweed are prone to additive noise and may reduce classification results. This research work aims to present our work towards Quranic accents (Qiraat) identification, which emphasizes on acoustic echo cancellation (AEC) of all echoed Quranic signals during the preprocessing phase of the system development. In order to conduct the AEC, three adaptive algorithms known as affine projection (AP), least mean square (LMS), and recursive least squares (RLS) are used during the preprocessing phase. Once clean Quranic signals are produced, they undergo feature extraction and pattern classification phases. The Mel Frequency Cepstral Coefficients is the most widely used technique for feature extraction and is adopted in this research work, whereas probabilities principal component analysis (PPCA), K-nearest neighbor (KNN) and gaussian mixture model (GMM) are used for pattern classification. In order to verify our methodology, audio files have been collected for Surat Ad-Duhaa for five different Quranic accents (Qiraat), namely: (1) Ad-Duri, (2) Al-Kisaie, (3) Hafs an A’asem, (4) IbnWardan, and (5) Warsh. Based on our experimental results, the AP algorithm achieved 93.9 % accuracy rate against all pattern classification techniques including PPCA, KNN, and GMM. For LMS and RLS, the achieved accuracy rates are different for PPCA, KNN, and GMM, whereby LMS with PPCA and GMM achieved the same accuracy rate of 96.9 %; however, LMS with KNN achieved 84.8 %. In addition, RLS with PPCA and GMM achieved the same accuracy rate of 90.9 %; however, RLS with KNN achieved 78.8 %. Therefore, the AP adaptive algorithm is able to reduce the echo of Quranic accents (Qiraat) signals in a consistent manner against all pattern classification techniques