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Pattern of biopsy-proven renal disease in Sabah: A retrospective cross-sectional study over 3.5 years

Lee AV, Pang HC, Linus Lojikip S, Wong KW, Goh KW, Chan FS

Med J Malaysia, 2020 03;75(2):152-157.
PMID: 32281597

OBJECTIVES: To explore the epidemiological and histopathological patterns of glomerular diseases in Sabah.
METHODS: A state-wide cross-sectional study was conducted. There were 336 native renal biopsies in 296 eligible patients from 1st January 2013 to 30th June 2016. All patients aged ≥12 years with sufficient sampling (≥8 glomeruli) for histopathological assessment were included. Graft kidney biopsies, protocol-based biopsies and patients with uncertain demographics were excluded. Demographics of patients, clinical data, laboratory parameters prior to biopsy, and histology findings of renal biopsies were collected from local unit database and recorded into a standardised data collection form. Descriptive statistical analyses were employed and factors associated with Lupus nephritis (LN) were explored using logistic regression.
RESULTS: The mean age during biopsy was 34.53 years (Standard Deviation 0.759). Primary glomerulonephritis (PGN) accounted for 42.6% (126) of all native renal biopsies. The commonest cause of PGN was minimal change disease (38.9%, 49) followed by focal segmental glomerulosclerosis (33.3%, 42) and IgA nephropathy (14.3%, 18). LN is the leading cause for secondary glomerulonephritis (SGN) (87.2%, 136). Younger age (Odds Ratio, OR 0.978; 95% Confidence Interval, 95%CI 0.960, 0.996); female gender (OR 17.53; p<0.001); significant proteinuria (OR 132.0; p<0.001); creatinine level at biopsy (OR 11.26; p=0.004); positive antinuclear antibody (ANA) (OR 46.7; p<0.001); and ANA patterns (OR 8.038; p=0.018) were significant in predicting the odds of having LN.
CONCLUSION: This is the first epidemiology study of glomerular diseases in Sabah. The predominance of LN suggests lower threshold for renal biopsy in patients with suspected glomerular disorders. We have identified significant predictors for early detection and treatment of LN.

Matched MeSH terms: Data Collection
Fulltext Fruit Battery Method for Oil Palm Fruit Ripeness Sensor and Comparison with Computer Vision Method

Aliteh NA, Minakata K, Tashiro K, Wakiwaka H, Kobayashi K, Nagata H, et al.

Sensors (Basel), 2020 Jan 23;20(3).
PMID: 31979252 DOI: 10.3390/s20030637

Oil palm ripeness' main evaluation procedure is traditionally accomplished by human vision. However, the dependency on human evaluators to grade the ripeness of oil palm fresh fruit bunches (FFBs) by traditional means could lead to inaccuracy that can cause a reduction in oil palm fruit oil extraction rate (OER). This paper emphasizes the fruit battery method to distinguish oil palm fruit FFB ripeness stages by determining the value of load resistance voltage and its moisture content resolution. In addition, computer vision using a color feature is tested on the same samples to compare the accuracy score using support vector machine (SVM). The accuracy score results of the fruit battery, computer vision, and a combination of both methods' accuracy scores are evaluated and compared. When the ripe and unripe samples were tested for load resistance voltage ranging from 10 Ω to 10 kΩ, three resistance values were shortlisted and tested for moisture content resolution evaluation. A 1 kΩ load resistance showed the best moisture content resolution, and the results were used for accuracy score evaluation comparison with computer vision. From the results obtained, the accuracy scores for the combination method are the highest, followed by the fruit battery and computer vision methods.

Matched MeSH terms: Data Collection
Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods

Chen W, Li Y, Xue W, Shahabi H, Li S, Hong H, et al.

Sci Total Environ, 2020 Jan 20;701:134979.
PMID: 31733400 DOI: 10.1016/j.scitotenv.2019.134979

Floods are one of the most devastating types of disasters that cause loss of lives and property worldwide each year. This study aimed to evaluate and compare the prediction capability of the naïve Bayes tree (NBTree), alternating decision tree (ADTree), and random forest (RF) methods for the spatial prediction of flood occurrence in the Quannan area, China. A flood inventory map with 363 flood locations was produced and partitioned into training and validation datasets through random selection with a ratio of 70/30. The spatial flood database was constructed using thirteen flood explanatory factors. The probability certainty factor (PCF) method was used to analyze the correlation between the factors and flood occurrences. Consequently, three flood susceptibility maps were produced using the NBTree, ADTree, and RF methods. Finally, the area under the curve (AUC) and statistical measures were used to validate the flood susceptibility models. The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rate, sensitivity, specificity, and accuracy for the training (0.951, 0.892, 0.941, 0.945, 0.886, and 0.915, respectively) and validation (0.925, 0.851, 0.938, 0.945, 0.835, and 0.890, respectively) datasets.

Matched MeSH terms: Data Collection
Fulltext Towards health monitoring using remote heart rate measurement using digital camera: A feasibility study

Hassan MA, Malik AS, Fofi D, Karasfi B, Meriaudeau F

Measurement : journal of the International Measurement Confederation, 2020 Jan;149:106804.
PMID: 32287815 DOI: 10.1016/j.measurement.2019.07.032

The paper presents a feasibility study for heart rate measurement using a digital camera to perform health monitoring. The feasibility study investigates the reliability of the state of the art heart rate measuring methods in realistic situations. Therefore, an experiment was designed and carried out on 45 subjects to investigate the effects caused by illumination, motion, skin tone, and distance variance. The experiment was conducted for two main scenarios; human-computer interaction scenario and health monitoring scenario. The human-computer scenario investigated the effects caused by illumination variance, motion variance, and skin tone variance. The health monitoring scenario investigates the feasibility of health monitoring at public spaces (i.e. airports, subways, malls). Five state of the art heart rate measuring methods were re-implemented and tested with the feasibility study database. The results were compared with ground truth to estimate the heart rate measurement error. The heart rate measurement error was analyzed using mean error, standard deviation; root means square error and Pearson correlation coefficient. The findings of this experiment inferred promising results for health monitoring of subjects standing at a distance of 500 cm.

Matched MeSH terms: Data Collection
Fulltext Disease risk analysis in sea turtles: A baseline study to inform conservation efforts

Mashkour N, Jones K, Kophamel S, Hipolito T, Ahasan S, Walker G, et al.

PLoS One, 2020;15(10):e0230760.
PMID: 33095793 DOI: 10.1371/journal.pone.0230760

The impact of a range of different threats has resulted in the listing of six out of seven sea turtle species on the IUCN Red List of endangered species. Disease risk analysis (DRA) tools are designed to provide objective, repeatable and documented assessment of the disease risks for a population and measures to reduce these risks through management options. To the best of our knowledge, DRAs have not previously been published for sea turtles, although disease is reported to contribute to sea turtle population decline. Here, a comprehensive list of health hazards is provided for all seven species of sea turtles. The possible risk these hazards pose to the health of sea turtles were assessed and "One Health" aspects of interacting with sea turtles were also investigated. The risk assessment was undertaken in collaboration with more than 30 experts in the field including veterinarians, microbiologists, social scientists, epidemiologists and stakeholders, in the form of two international workshops and one local workshop. The general finding of the DRA was the distinct lack of knowledge regarding a link between the presence of pathogens and diseases manifestation in sea turtles. A higher rate of disease in immunocompromised individuals was repeatedly reported and a possible link between immunosuppression and environmental contaminants as a result of anthropogenic influences was suggested. Society based conservation initiatives and as a result the cultural and social aspect of interacting with sea turtles appeared to need more attention and research. A risk management workshop was carried out to acquire the insights of local policy makers about management options for the risks relevant to Queensland and the options were evaluated considering their feasibility and effectiveness. The sea turtle DRA presented here, is a structured guide for future risk assessments to be used in specific scenarios such as translocation and head-starting programs.

Matched MeSH terms: Data Collection
Fulltext Effectiveness of strip footing with geogrid reinforcement for different types of soils in Mosul, Iraq

Hasan NI, Mohd Taib A, Muhammad NS, Mat Yazid MR, Mutalib AA, Abang Hasbollah DZ

PLoS One, 2020;15(12):e0243293.
PMID: 33332375 DOI: 10.1371/journal.pone.0243293

The main cause of problematic soil failure under a certain load is due to low bearing capacity and excessive settlement. With a growing interest in employing shallow foundation to support heavy structures, it is important to study the soil improvement techniques. The technique of using geosynthetic reinforcement is commonly applied over the last few decades. This paper aims to determine the effect of using geogrid Tensar BX1500 on the bearing capacity and settlement of strip footing for different types of soils, namely Al-Hamedat, Ba'shiqah, and Al-Rashidia in Mosul, Iraq. The analysis of reinforced and unreinforced soil foundations was conducted numerically and analytically. A series of conditions were tested by varying the number (N) and the width (b) of the geogrid layers. The results showed that the geogrid could improve the footing's bearing capacity and reduce settlement. The soil of the Al-Rashidia site was sandy and indicated better improvement than the other two sites' soils (clayey soils). The optimum geogrid width (b) was five times the footing width (B), while no optimum geogrid number (N) was obtained. Finally, the numerical results of the ultimate bearing capacity were compared with the analytical results, and the comparison showed good agreement between both the analyses and the optimum range published in the literature. The significant findings reveal that the geogrid reinforcement may induce improvement to the soil foundation, however, not directly subject to the width and number of the geogrid alone. The varying soil properties and footing size also contribute to both BCR and SRR values supported by the improvement factor calculations. Hence, the output complemented the benefit of applying reinforced soil foundations effectively.

Matched MeSH terms: Data Collection
Fulltext Personal Injury Claims (PIC) database modelling in Malaysia

Syadatul Syaeda Mat Saleh, Najihan Awang @ Ali, Nik Ruslawati Nik Mustapa, Nurul Husna Jamian, Hussin bin Abdul Hamid

Jurnal Inovasi Malaysia, 2020;3(2):75-86.
MyJurnal

Road accident is not stranger matter in Malaysia. Subsequently, often leads to a claim for personal injury by the persecuted party. In Malaysia, the method for calculating claims applies a multiplier-multiplicand approach. This approach is no longer relevant and unfair to the claimant as it excludes personal status in the quantum calculation of damages. Hence, this study uses the Ogden Table as introduced in the United Kingdom as benchmarking guidelines, by taking into account of all aspect of claimant's personal condition for the purpose of such calculation. This study is built upon a proposed framework of data modelling system known as Entity Relationship Diagram (ERD) and the created process modelling known as data flow diagram (DFD). Doing so, the claimants will insert their input data, run it through the first process, and store the information in the claim injury part database. They can also edit and store to claim injury part database on their own. This will generate a report with the information in claim injury part database and can be viewed by claimant, court and lawyer as target users. It is hoped that it will facilitate the calculation of injury claim which would serve justice and accuracy of personal injury in road accidents

Matched MeSH terms: Data Collection
Fulltext Pre-processing methods for vehicle lane detection

Muhammad Naim Mazani, Shuzlina Abdul-Rahman, Sofianita Mutalib

ESTEEM Academic Journal, 2020;16(1):74-85.
MyJurnal

This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. Standard image processing methods are not suitable for complicated roads with various sign on the ground. Thus, determining the right techniques for pre-processing such data would be a challenge. The objectives of this study are to pre-process the scanned images and apply the image recognition algorithm for lane detection. The study employed Canny Edge Detection and Hough Transform algorithms on several sets of images. A different region of interest was experimented to find the optimal one. The experimental results showed that the proposed algorithms could be practical in terms of effectively detecting road lines and generate lane detection.

Matched MeSH terms: Data Collection
Fulltext Sinensetin: An Insight on Its Pharmacological Activities, Mechanisms of Action and Toxicity

Han Jie L, Jantan I, Yusoff SD, Jalil J, Husain K

Front Pharmacol, 2020;11:553404.
PMID: 33628166 DOI: 10.3389/fphar.2020.553404

Sinensetin, a plant-derived polymethoxylated flavonoid found in Orthosiphon aristatus var. aristatus and several citrus fruits, has been found to possess strong anticancer activities and a variety of other pharmacological benefits and promising potency in intended activities with minimal toxicity. This review aims to compile an up-to-date reports of published scientific information on sinensetin pharmacological activities, mechanisms of action and toxicity. The present findings about the compound are critically analyzed and its prospect as a lead molecule for drug discovery is highlighted. The databases employed for data collection are mainly through Google Scholar, PubMed, Scopus and Science Direct. In-vitro and in-vivo studies showed that sinensetin possessed strong anticancer activities and a wide range of pharmacological activities such as anti-inflammatory, antioxidant, antimicrobial, anti-obesity, anti-dementia and vasorelaxant activities. The studies provided some insights on its several mechanisms of action in cancer and other disease states. However, more detail mechanistic studies are needed to understand its pharmacological effects. More in vivo studies in various animal models including toxicity, pharmacokinetic, pharmacodynamic and bioavailability studies are required to assess its efficacy and safety before submission to clinical studies. In this review, an insight on sinensetin pharmacological activities and mechanisms of action serves as a useful resource for a more thorough and comprehensive understanding of sinensetin as a potential lead candidate for drug discovery.

Matched MeSH terms: Data Collection
Binary Particle Swarm Optimization for Variables Selection Optimization in Taguchi’s T-Method

Khairur Rijal Jamaludin, Nolia Harudin, Faizir Ramlie, Mohd Nabil Muhtazaruddin, Che Munira Che Razali, Wan Zuki Azman Wan Muhamad

MATEMATIKA, 2020;36(1):69-84.
MyJurnal

Prediction analysis has drawn significant interest in numerous field. Taguchi’s T-Method is a prediction tool that developed practically but not limited to small sample analysis. It was developed explicitly for multidimensional system prediction by relying on historical data as the baseline model and adapting the signal to noise ratio (SNR) as well as zero proportional concepts in strengthening its robustness. Orthogonal array (OA) in T-Method is a variable selection optimization technique in improving the prediction accuracy as well as help in eliminating variables that may deteriorate the overall performance. However, the limitation of OA in dealing with higher multidimensionality restraint the optimization accuracy. Binary particle swarm optimization used in this study helps to cater to the limitation of OA as well as optimizing the variable selection process to better prediction accuracy. The results show that if the historical data consist of samples with higher correlation of determination (R2) value for the model creation, the optimization process in reducing the number of variables would be much reliable and accurate. Comparing between T-Method+OA and T-Method+BPSO in four different case study, it shows that T-Method+BPSO performing better with greater R2 and means relative error (MRE) value compared to T-Method+OA.

Matched MeSH terms: Data Collection
Fulltext Logic mining in league of legends

Liew, Ching Kho, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor, Sathasivam, Saratha

Pertanika Journal of Science & Technology, 2020;28(1):211-225.
MyJurnal

Since its debut in 2009, League of Legends (LoL) has been on a rise in becoming an extremely favoured multiplayer online battle arena (MOBA) game. This paper presented a logic mining technique to model the results (Win / Lose) of the LoL games played in 3 regions, namely South Korea, North America and Europe. In this research, a method named k satisfiability based reverse analysis method (kSATRA) was brought forward to obtain the logical relationship among the gameplays and objectives in the game. The logical rule obtained from the LoL games was used to categorize the results of future games. kSATRA made use of the advantages of Hopfield Neural Network and k Satisfiability representation. The data set used in this study included the data of all 10 teams from each region, which composed of all games from Spring Season 2018. The effectiveness of kSATRA in obtaining logical rule in LoL games was tested based on root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and CPU time. Results acquired from the computer simulation showed the robustness of kSATRA in exhibiting the performance of the LoL teams.

Matched MeSH terms: Data Collection
Fulltext Hybrid discrete hopfield neural network based modified clonal selection algorithm for VLSI circuit verification

Sathasivam, Saratha, Mustafa Mamat, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor

Pertanika Journal of Science & Technology, 2020;28(1):227-243.
MyJurnal

Clonal selection algorithm and discrete Hopfield neural network are extensively employed for solving higher-order optimization problems ranging from the constraint satisfaction problem to complex pattern recognition. The modified clonal selection algorithm is a comprehensive and less iterative immune-inspired searching algorithm, utilized to search for the correct combination of instances for Very large-scale integrated (VLSI) circuit structure. In this research, the VLSI circuit framework consists of Boolean 3-Satisfiability instances with the different complexities and number of transistors are considered. Hence, a hybrid modified clonal selection algorithm with discrete Hopfield neural network is well developed to optimize the configuration of VLSI circuits with different number of electronic components such as transistors as the instances. Therefore, the performance of the developed hybrid model was assessed experimentally with the standard models, HNNVLSI-3SATES and HNNVLSI-3SATGA in term of circuit accuracy, sensitivity, robustness and runtime to complete the verification process. The results have demonstrated the developed model, HNNVLSI-3SATCSA produced a minimum error (consistently approaching 0), better accuracy (more than 80%) and faster computational time (less than 125 seconds) against changes in the complexity in term of the number of transistors. Furthermore, the developed hybrid model is able to minimize the computational burden and configurational noises for the variant of VLSI circuits.

Matched MeSH terms: Data Collection
Fulltext Factors associated with falls among the elderly attending a government clinic in Kuala Lumpur

Leong Joyce W.S, Intan Nadia Mohd Zukri, Siew Mooi Ching, Navin Kumar Devaraj

Malaysian Journal of Medicine and Health Sciences, 2020;16(1):183-190.
MyJurnal

Introduction: Falls among the elderly can be associated with serious complications such as fractures, injuries and death. This study aims to ascertain the factors associated with falls among the elderly patients attending a government clinic located in Kuala Lumpur. Method: This was a cross-sectional study using a convenience sampling method. Data collection in 2017 from 322 elderly who attended the above clinic. A modified assisted self-administered ques- tionnaire was used that contained the socio-demographic data, falls profile as well as extrinsic and intrinsic factors associated with falls. Analysis was done with SPSS v20.0. Results: 120 (37.27%) elderly reported falls in the past one year. The majority who had falls were females (n=76, 41.8%) and between the age of 80-89 years old (n=29, 44.6%). Malay ethnicity group, reported more falls compared to other ethnicities (n=93,44.5%). Significant associations were found between age, ethnicity and history of falls with falling (p

Matched MeSH terms: Data Collection
Fulltext Timbre spectrum of gamelan instruments from four Malay gamelan ensembles

Hamdan, Sinin, Ahmad Faudzi Musib, Musoddiq, Iran Amri, Marini Sawawi

Pertanika Journal of Science & Technology, 2020;28(2):459-476.
MyJurnal

Gamelan in general is categorized as a group of gongs. This traditional Malay gamelan ensemble is in a slendro scale i.e. five notes per octave. The rhythms, pitch, duration and loudness classify the various groups of gongs such as bonang, kenong, gender, peking and gambang. The cast bronze peking, kenong and bonang were chosen from a range of Malay gamelan ensemble from Universiti Malaysia Sarawak (UNIMAS), Universiti Putra Malaysia (UPM), Universiti Kebangsaan Malaysia (UKM) and Universiti Teknologi Mara (UiTM). The sounds were recorded by PicoScope Oscilloscope. The PicoScope software displays waveform and spectrum in time and frequency domain respectively. The peking lowest and highest frequencies from UiTM were 293 Hz and 1867 Hz, from UPM were 644 Hz and 1369 Hz, from UKM were 1064 Hz and 2131 Hz and from UNIMAS were 1072 Hz and 2105 Hz respectively. The kenong lowest and highest frequencies from UiTM were 259 Hz and 463 Hz, from UPM were 294 Hz and 543 Hz, from UKM were 300 Hz and 540 Hz and from UNIMAS were 293 Hz and 519 Hz respectively. The fundamental frequencies of bonang from UPM were higher than that of UKM, UiTM and UNIMAS. The harmonics were not successive but interrupted by another frequency. The harmonics of each bonang was similar except for gamelan from UKM.

Matched MeSH terms: Data Collection
Fulltext Latent based temporal optimization approach for improving the performance of collaborative filtering

Al-Hadi IAA, Sharef NM, Sulaiman MN, Mustapha N, Nilashi M

PeerJ Comput Sci, 2020;6:e331.
PMID: 33816980 DOI: 10.7717/peerj-cs.331

Recommendation systems suggest peculiar products to customers based on their past ratings, preferences, and interests. These systems typically utilize collaborative filtering (CF) to analyze customers' ratings for products within the rating matrix. CF suffers from the sparsity problem because a large number of rating grades are not accurately determined. Various prediction approaches have been used to solve this problem by learning its latent and temporal factors. A few other challenges such as latent feedback learning, customers' drifting interests, overfitting, and the popularity decay of products over time have also been addressed. Existing works have typically deployed either short or long temporal representation for addressing the recommendation system issues. Although each effort improves on the accuracy of its respective benchmark, an integrative solution that could address all the problems without trading off its accuracy is needed. Thus, this paper presents a Latent-based Temporal Optimization (LTO) approach to improve the prediction accuracy of CF by learning the past attitudes of users and their interests over time. Experimental results show that the LTO approach efficiently improves the prediction accuracy of CF compared to the benchmark schemes.

Matched MeSH terms: Data Collection
Fulltext An evaluation on pharmacokinetics parameters of phenytoin in adult epileptic patients: a single centre study from Malaysia

Tan, Kenny, Luen, Leong Wei, Ong, Yi Ping, Khai, H’ng Kee, Tan, Li May, Siti Nur Fatihah Abd Rahman, et al.

Malaysian Journal of Pharmaceutical Science, 2020;18(1):77-83.
MyJurnal

Phenytoin follows Michaelis-Menten, a non-linear pharmacokinetics that occurs when drug molecules saturates the enzymes ability to metabolise the drug. When this occurs, steady state phenytoin serum concentration increases in a disproportionate manner after a dosage increase. General population data are usually used for the phenytoin dose calculation. However, many studies show that population pharmacokinetic parameters of phenytoin have high variations. Thus, use of specific local pharmacokinetic parameters for each population group in estimating individualised phenytoin dose can reduce phenytoin toxicity cases. This prospective, observational study was conducted to estimate a local Vmax and Km of phenytoin for adult epileptic patients in neurological ward and clinic at Hospital Pulau Pinang, Malaysia. All therapeutic drug monitoring of oral capsule phenytoin were studied in a three-month data collection period. Out of the 17 subjects in our study, there are 13 male subjects (76.47%) and 4 female subjects (23.53%). A total 11 Malay subjects (64.71%), 4 Chinese subjects (23.53%) and 2 Indian subjects (11.76%) were included. Median Vmax and Km were found to be 8.25 mg/kg/day and 3.80 mg/l. Male subjects have a higher Vmax (8.30 mg/kg/day) but a lower Km (3.3 mg/l). Chinese population has the highest Vmax (8.80 mg/kg/day). For Km, Indian population is the highest, with a value of 5.5 mg/l. From our study, gender does not correlate with Vmax and Km of phenytoin (p-value > 0.05). Ethnicity was also found to have no association with Vmax and Km (p-value > 0.05). Local Vmax (8.25 mg/kg/day) is higher and Km (3.8 mg/l) is lower when compared with standard Vmax (7 mg/kg/day) and Km (4 mg/l) obtained from Caucasian population.

Matched MeSH terms: Data Collection
Fulltext PeskAAS: A near-real-time, open-source monitoring and analytics system for small-scale fisheries

Tilley A, Dos Reis Lopes J, Wilkinson SP

PLoS One, 2020;15(11):e0234760.
PMID: 33186386 DOI: 10.1371/journal.pone.0234760

Small-scale fisheries are responsible for landing half of the world's fish catch, yet there are very sparse data on these fishing activities and associated fisheries production in time and space. Fisheries-dependent data underpin scientific guidance of management and conservation of fisheries systems, but it is inherently difficult to generate robust and comprehensive data for small-scale fisheries, particularly given their dispersed and diverse nature. In tackling this challenge, we use open source software components including the Shiny R package to build PeskAAS; an adaptable and scalable digital application that enables the collation, classification, analysis and visualisation of small-scale fisheries catch and effort data. We piloted and refined this system in Timor-Leste; a small island developing nation. The features that make PeskAAS fit for purpose are that it is: (i) fully open-source and free to use (ii) component-based, flexible and able to integrate vessel tracking data with catch records; (iii) able to perform spatial and temporal filtering of fishing productivity by fishing method and habitat; (iv) integrated with species-specific length-weight parameters from FishBase; (v) controlled through a click-button dashboard, that was co-designed with fisheries scientists and government managers, that enables easy to read data summaries and interpretation of context-specific fisheries data. With limited training and code adaptation, the PeskAAS workflow has been used as a framework on which to build and adapt systematic, standardised data collection for small-scale fisheries in other contexts. Automated analytics of these data can provide fishers, managers and researchers with insights into a fisher's experience of fishing efforts, fisheries status, catch rates, economic efficiency and geographic preferences and limits that can potentially guide management and livelihood investments.

Matched MeSH terms: Data Collection
Fulltext Cube polygon: a new modified Euler method to improve electric circuit efficiency

Nurhafizah Moziyana Mohd Yusop, Nooraida Samsudin, Nooraida Samsudin, Anis Shahida Mokhta, Siti Rohaidah Ahmad, Mohd Fahmi Mohammad Amran, et al.

ZULFAQAR International Journal of Defence Science, Engineering & Technology, 2020;3(1):8-14.
MyJurnal

Euler method is a numerical order process for solving problems with the Ordinary Differential Equation (ODE). It is a fast and easy way. While Euler offers a simple procedure for solving ODEs, problems such as complexity, processing time and accuracy have driven others to use more sophisticated methods. Improvements to the Euler method have attracted much attention resulting in numerous modified Euler methods. This paper proposes Cube Polygon, a modified Euler method with improved accuracy and complexity. In order to demonstrate the accuracy and easy implementation of the proposed method, several examples are presented. Cube Polygon’s performance was compared to Polygon’s scheme and evaluated against exact solutions using SCILAB. Results indicate that not only Cube Polygon has produced solutions that are close to identical solutions for small step sizes, but also for higher step sizes, thus generating more accurate results and decrease complexity. Also known in this paper is the general of the RL circuit due to the ODE problem.

Matched MeSH terms: Data Collection
Fulltext The knowledge and self-management educational needs of older adults with knee osteoarthritis: A qualitative study

Kamsan SS, Singh DKA, Tan MP, Kumar S

PLoS One, 2020;15(3):e0230318.
PMID: 32226047 DOI: 10.1371/journal.pone.0230318

Knee osteoarthritis (KOA) is closely related with ageing, physical disability and functional dependency. The course of KOA is considered progressive and irreversible. Engagement with self-management may, however, minimize the impact of KOA. To be fully engaged with self-management activities, knowledge about KOA is a prerequisite. There is limited empirical data on older adults' understanding on KOA and their information needs about KOA. Therefore, the aims of this study were to explore older adults' knowledge about KOA and their perspectives on the information required to enable self-management. Three focus groups were conducted with 16 older adults with KOA. The sample consisted of three men and thirteen women with the mean age 73.2 years (range from 61 to 89). Thematic content analysis revealed two themes which were understanding about KOA and information needed about KOA. Participants' knowledge about KOA varied between individuals with many expressing that they needed more information about KOA. A targeted strategy is needed to educate older adults about KOA in order to support and prepare them for self-management.

Matched MeSH terms: Data Collection
Sudden cardiac death and kidney health related problems among Nepali migrant workers in Malaysia

Aryal N, Regmi PR, Faller EM, van Teijlingen E, Khoon CC, Pereira A, et al.

Nepal J Epidemiol, 2019 Sep;9(3):788-791.
PMID: 31687253 DOI: 10.3126/nje.v9i3.25805

This paper reports on a consultation meeting that discussed two emerging health issues of Nepali migrant workers in Malaysia and the ways they can be addressed. Primarily, it focused on the issue of sudden cardiac deaths of Nepali migrant workers in Malaysia. This issue has been raised internationally by both scientific and media in the recent years. Secondly, it discussed kidney health related problem among Nepali migrant workers which has caught the attention of Nepali media recently. The meeting was organized in Kuala Lumpur, Malaysia on 19th April, 2019 where twenty people including health researchers, representatives of migrant related national and international organizations, and Nepali migrant workers participated. The meeting concluded that three types of data collection are needed: (1) good record of deaths, if at possible proper post-mortems; (2) a verbal autopsy tool to help identify underlying causes ; and qualitative research into kidney related problems.

Matched MeSH terms: Data Collection

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