Displaying publications 101 - 120 of 365 in total

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  1. Fulltext 3D Transparent Object Detection and Reconstruction Based on Passive Mode Single-Pixel Imaging
    Mathai A, Guo N, Liu D, Wang X
    Sensors (Basel), 2020 Jul 29;20(15).
    PMID: 32751165 DOI: 10.3390/s20154211
    Transparent object detection and reconstruction are significant, due to their practical applications. The appearance and characteristics of light in these objects make reconstruction methods tailored for Lambertian surfaces fail disgracefully. In this paper, we introduce a fixed multi-viewpoint approach to ascertain the shape of transparent objects, thereby avoiding the rotation or movement of the object during imaging. In addition, a simple and cost-effective experimental setup is presented, which employs two single-pixel detectors and a digital micromirror device, for imaging transparent objects by projecting binary patterns. In the system setup, a dark framework is implemented around the object, to create shades at the boundaries of the object. By triangulating the light path from the object, the surface shape is recovered, neither considering the reflections nor the number of refractions. It can, therefore, handle transparent objects with a relatively complex shape with the unknown refractive index. The implementation of compressive sensing in this technique further simplifies the acquisition process, by reducing the number of measurements. The experimental results show that 2D images obtained from the single-pixel detectors are better in quality with a resolution of 32×32. Additionally, the obtained disparity and error map indicate the feasibility and accuracy of the proposed method. This work provides a new insight into 3D transparent object detection and reconstruction, based on single-pixel imaging at an affordable cost, with the implementation of a few numbers of detectors.
    Matched MeSH terms: Data Collection
  2. Fulltext A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models
    Mohammadi A, Karimzadeh S, Jalal SJ, Kamran KV, Shahabi H, Homayouni S, et al.
    Sensors (Basel), 2020 Dec 16;20(24).
    PMID: 33339435 DOI: 10.3390/s20247214
    Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs' performance, such as 90-meters' TanDEM-X and 30-meters' SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).
    Matched MeSH terms: Data Collection
  3. Fulltext Triple Flat-Type Inductive-Based Oil Palm Fruit Maturity Sensor
    Aliteh NA, Misron N, Aris I, Mohd Sidek R, Tashiro K, Wakiwaka H
    Sensors (Basel), 2018 Aug 01;18(8).
    PMID: 30071614 DOI: 10.3390/s18082496
    This paper aims to study a triple flat-type air coil inductive sensor that can identify two maturity stages of oil palm fruits, ripe and unripe, based on the resonance frequency and fruitlet capacitance changes. There are two types of triple structure that have been tested, namely Triple I and II. Triple I is a triple series coil with a fixed number of turns (n = 200) with different length, and Triple II is a coil with fixed length (l = 5 mm) and a different number of turns. The peak comparison between Triple I and II is using the coefficient of variation cv, which is defined as the ratio of the standard deviation to the mean to express the precision and repeatability of data. As the fruit ripens, the resonance frequency peaks from an inductance⁻frequency curve and shifts closer to the peak curve of the air, and the fruitlet capacitance decreases. The coefficient of the variation of the inductive oil palm fruit sensor shows that Triple I is smaller and more consistent in comparison with Triple II, for both resonance frequency and fruitlet capacitance. The development of this sensor proves the capability of an inductive element such as a coil, to be used as a sensor so as to determine the ripeness of the oil palm fresh fruit bunch sample.
    Matched MeSH terms: Data Collection
  4. 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
  5. Fulltext Tree Alignment Based on Needleman-Wunsch Algorithm for Sensor Selection in Smart Homes
    Chua SL, Foo LK
    Sensors (Basel), 2017 Aug 18;17(8).
    PMID: 28820438 DOI: 10.3390/s17081902
    Activity recognition in smart homes aims to infer the particular activities of the inhabitant, the aim being to monitor their activities and identify any abnormalities, especially for those living alone. In order for a smart home to support its inhabitant, the recognition system needs to learn from observations acquired through sensors. One question that often arises is which sensors are useful and how many sensors are required to accurately recognise the inhabitant's activities? Many wrapper methods have been proposed and remain one of the popular evaluators for sensor selection due to its superior accuracy performance. However, they are prohibitively slow during the evaluation process and may run into the risk of overfitting due to the extent of the search. Motivated by this characteristic, this paper attempts to reduce the cost of the evaluation process and overfitting through tree alignment. The performance of our method is evaluated on two public datasets obtained in two distinct smart home environments.
    Matched MeSH terms: Data Collection
  6. Fulltext Adaptive Indoor Positioning Model Based on WLAN-Fingerprinting for Dynamic and Multi-Floor Environments
    Alshami IH, Ahmad NA, Sahibuddin S, Firdaus F
    Sensors (Basel), 2017 Aug 05;17(8).
    PMID: 28783047 DOI: 10.3390/s17081789
    The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS) differently, and peoples' presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS) based on: a dynamic radio map generator, RSS certainty technique and peoples' presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples' presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.
    Matched MeSH terms: Data Collection
  7. Fulltext Underwater Turbulence Detection Using Gated Wavefront Sensing Technique
    Bi Y, Xu X, Chua SY, Chow EMT, Wang X
    Sensors (Basel), 2018 Mar 07;18(3).
    PMID: 29518889 DOI: 10.3390/s18030798
    Laser sensing has been applied in various underwater applications, ranging from underwater detection to laser underwater communications. However, there are several great challenges when profiling underwater turbulence effects. Underwater detection is greatly affected by the turbulence effect, where the acquired image suffers excessive noise, blurring, and deformation. In this paper, we propose a novel underwater turbulence detection method based on a gated wavefront sensing technique. First, we elaborate on the operating principle of gated wavefront sensing and wavefront reconstruction. We then setup an experimental system in order to validate the feasibility of our proposed method. The effect of underwater turbulence on detection is examined at different distances, and under different turbulence levels. The experimental results obtained from our gated wavefront sensing system indicate that underwater turbulence can be detected and analyzed. The proposed gated wavefront sensing system has the advantage of a simple structure and high detection efficiency for underwater environments.
    Matched MeSH terms: Data Collection
  8. Fulltext The Effect of Dataset Imbalance on the Performance of SCADA Intrusion Detection Systems
    Balla A, Habaebi MH, Elsheikh EAA, Islam MR, Suliman FM
    Sensors (Basel), 2023 Jan 09;23(2).
    PMID: 36679553 DOI: 10.3390/s23020758
    Integrating IoT devices in SCADA systems has provided efficient and improved data collection and transmission technologies. This enhancement comes with significant security challenges, exposing traditionally isolated systems to the public internet. Effective and highly reliable security devices, such as intrusion detection system (IDSs) and intrusion prevention systems (IPS), are critical. Countless studies used deep learning algorithms to design an efficient IDS; however, the fundamental issue of imbalanced datasets was not fully addressed. In our research, we examined the impact of data imbalance on developing an effective SCADA-based IDS. To investigate the impact of various data balancing techniques, we chose two unbalanced datasets, the Morris power dataset, and CICIDS2017 dataset, including random sampling, one-sided selection (OSS), near-miss, SMOTE, and ADASYN. For binary classification, convolutional neural networks were coupled with long short-term memory (CNN-LSTM). The system's effectiveness was determined by the confusion matrix, which includes evaluation metrics, such as accuracy, precision, detection rate, and F1-score. Four experiments on the two datasets demonstrate the impact of the data imbalance. This research aims to help security researchers in understanding imbalanced datasets and their impact on DL SCADA-IDS.
    Matched MeSH terms: Data Collection
  9. Fulltext Variable-Length Multiobjective Social Class Optimization for Trust-Aware Data Gathering in Wireless Sensor Networks
    Saad MA, Jaafar R, Chellappan K
    Sensors (Basel), 2023 Jun 12;23(12).
    PMID: 37420692 DOI: 10.3390/s23125526
    Data gathering in wireless sensor networks (WSNs) is vital for deploying and enabling WSNs with the Internet of Things (IoTs). In various applications, the network is deployed in a large-scale area, which affects the efficiency of the data collection, and the network is subject to multiple attacks that impact the reliability of the collected data. Hence, data collection should consider trust in sources and routing nodes. This makes trust an additional optimization objective of the data gathering in addition to energy consumption, traveling time, and cost. Joint optimization of the goals requires conducting multiobjective optimization. This article proposes a modified social class multiobjective particle swarm optimization (SC-MOPSO) method. The modified SC-MOPSO method is featured by application-dependent operators named interclass operators. In addition, it includes solution generation, adding and deleting rendezvous points, and moving to the upper and lower class. Considering that SC-MOPSO provides a set of nondominated solutions as a Pareto front, we employed one of the multicriteria decision-making (MCDM) methods, i.e., simple additive sum (SAW), for selecting one of the solutions from the Pareto front. The results show that both SC-MOPSO and SAW are superior in terms of domination. The set coverage of SC-MOPSO is 0.06 dominant over NSGA-II compared with only a mastery of 0.04 of NSGA-II over SC-MOPSO. At the same time, it showed competitive performance with NSGA-III.
    Matched MeSH terms: Data Collection
  10. Fulltext Awareness, knowledge and attitudes towards epilepsy among rural populations in East Coast Peninsular Malaysia: a preliminary exploration
    Neni SW, Latif AZ, Wong SY, Lua PL
    Seizure, 2010 Jun;19(5):280-90.
    PMID: 20466567 DOI: 10.1016/j.seizure.2010.04.006
    This study was carried out to gauge the preliminary insight regarding epilepsy among the rural society. The purposes of this study were: (1) to determine general level of awareness, knowledge and attitudes (AKA) towards epilepsy among rural communities, (2) to compare the AKA level based on socio-demographic characteristics and (3) to investigate rural cohort's perception of the best epilepsy treatment, preference for epilepsy information delivery and preference for mode of transportation to seek medical treatment. This prospective, cross sectional study included a sample of 615 rural residents enrolled via cluster sampling in East Coast region of Peninsular Malaysia (mean age=41.6+/-18.02, female=56.6%, married=65.5%, Malay=94.0%, monthly income < or = RM 500=56.9%). The Total AKA level was generally low (2.66+/-0.7). Gender-wise no significant difference was shown regarding AKA level (p>0.05). However, respondents with higher education significantly possessed better attitudes and higher Total AKA level compared to those with lower education level (p<0.001). Employed respondents reported significantly more favourable attitudes than unemployed respondents (p=0.011). Additionally, higher income rural cohorts possessed both significantly better attitudes and better AKA. These rural communities perceived modern medicine as the best epilepsy treatment (56.60%), preferred to obtain direct epilepsy-related information from health personnel (60.4%) and chose to use their own car to seek medical treatment in hospital (76.30%). The outcomes of this preliminary study signified the need to devise a dedicated epilepsy education program for implementation among rural residents. Increased AKA level in the society could enhance the people's acceptance, reduce stigmatisation and improve health-related quality of life (HRQoL) for epilepsy patients and their family.
    Matched MeSH terms: Data Collection
  11. Fulltext Systematical study of multi-walled carbon nanotube nanofluids based disposed transformer oil
    Suhaimi NS, Md Din MF, Ishak MT, Abdul Rahman AR, Mohd Ariffin M, Hashim N', et al.
    Sci Rep, 2020 Dec 02;10(1):20984.
    PMID: 33268816 DOI: 10.1038/s41598-020-77810-8
    In this paper, the electrical, dielectric, Raman and small angle X-ray scattering (SAXS) structure behavior of disposed transformer oil in the presence of multi-walled carbon nanotube (MWCNT) were systematically tested to verify their versatility for preparing better alternative transformer oil in future. MWCNT nanofluids are prepared using a two-step method with concentrations ranging from 0.00 to 0.02 g/L. The test results reveal that 0.005 g/L concentration possesses the most optimum performance based on the electrical (AC breakdown and lightning impulse) and dielectric (permittivity, dissipation factor and resistivity) behavior. According to the trend of AC breakdown strength and lightning impulse pattern, there were 212.58% and 40.01% enhancement indicated for 0.005 g/L concentration compared to the disposed transformer oil. The presence of MWCNT also yielding to the decrement of dissipation factor, increased on permittivity and resistivity behavior of disposed transformer oil which reflected to the performance of electrical properties. Furthermore, it is found that these features correlated to the structural properties as systematically verify by Raman and SAXS analysis study.
    Matched MeSH terms: Data Collection
  12. Fulltext Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques
    Hannan MA, Lipu MSH, Hussain A, Ker PJ, Mahlia TMI, Mansor M, et al.
    Sci Rep, 2020 Mar 13;10(1):4687.
    PMID: 32170100 DOI: 10.1038/s41598-020-61464-7
    State of charge (SOC) is a crucial index used in the assessment of electric vehicle (EV) battery storage systems. Thus, SOC estimation of lithium-ion batteries has been widely investigated because of their fast charging, long-life cycle, and high energy density characteristics. However, precise SOC assessment of lithium-ion batteries remains challenging because of their varying characteristics under different working environments. Machine learning techniques have been widely used to design an advanced SOC estimation method without the information of battery chemical reactions, battery models, internal properties, and additional filters. Here, the capacity of optimized machine learning techniques are presented toward enhanced SOC estimation in terms of learning capability, accuracy, generalization performance, and convergence speed. We validate the proposed method through lithium-ion battery experiments, EV drive cycles, temperature, noise, and aging effects. We show that the proposed method outperforms several state-of-the-art approaches in terms of accuracy, adaptability, and robustness under diverse operating conditions.
    Matched MeSH terms: Data Collection
  13. Fulltext Real Time Microwave Biochemical Sensor Based on Circular SIW Approach for Aqueous Dielectric Detection
    Mohd Bahar AA, Zakaria Z, Md Arshad MK, Isa AAM, Dasril Y, Alahnomi RA
    Sci Rep, 2019 04 02;9(1):5467.
    PMID: 30940843 DOI: 10.1038/s41598-019-41702-3
    In this study, a critical evaluation of analyte dielectric properties in a microvolume was undertaken, using a microwave biochemical sensor based on a circular substrate integrated waveguide (CSIW) topology. These dielectric properties were numerically investigated based on the resonant perturbation method, as this method provides the best sensing performance as a real-time biochemical detector. To validate these findings, shifts of the resonant frequency in the presence of aqueous solvents were compared with an ideal permittivity. The sensor prototype required a 2.5 µL volume of the liquid sample each time, which still offered an overall accuracy of better than 99.06%, with an average error measurement of ±0.44%, compared with the commercial and ideal permittivity values. The unloaded Qu factor of the circular substrate-integrated waveguide (CSIW) sensor achieved more than 400 to ensure a precise measurement. At 4.4 GHz, a good agreement was observed between simulated and measured results within a broad frequency range, from 1 to 6 GHz. The proposed sensor, therefore, offers high sensitivity detection, a simple structural design, a fast-sensing response, and cost-effectiveness. The proposed sensor in this study will facilitate real improvements in any material characterization applications such as pharmaceutical, bio-sensing, and food processing applications.
    Matched MeSH terms: Data Collection
  14. Fulltext Electrochemical Performance of Supercapacitor with Stacked Copper Foils Coated with Graphene Nanoplatelets
    Chiam SL, Lim HN, Hafiz SM, Pandikumar A, Huang NM
    Sci Rep, 2018 02 15;8(1):3093.
    PMID: 29449631 DOI: 10.1038/s41598-018-21572-x
    The energy density of conventional supercapacitors is in the range of 6-10 Wh kg-1, which has restricted them from many applications that require devices with long durations. Herein, we report a method for enhancing the energy density of a device through the parallel stacking of five copper foils coated on each side with graphene nanoplatelets. Microporous papers immersed in 2 M aqueous sodium sulphate were used as separators. With a low contact resistance of 0.05 Ω, the supercapacitor yielded an optimum specific energy density and a specific power density of 24.64 Wh kg-1 and 402 W kg-1 at 0.8 V, respectively. The working potential was increased to 2.4 V when three of the supercapacitors were connected in series, forming a tandem device. Its potential for real applications was manifested by the ability to light up a light-emitting diode for 40 s after charging for 60 s.
    Matched MeSH terms: Data Collection
  15. Teaching engineering ethics using BLOCKS game
    Lau SW, Tan TP, Goh SM
    Sci Eng Ethics, 2013 Sep;19(3):1357-73.
    PMID: 23065541 DOI: 10.1007/s11948-012-9406-3
    The aim of this study was to investigate the use of a newly developed design game called BLOCKS to stimulate awareness of ethical responsibilities amongst engineering students. The design game was played by seventeen teams of chemical engineering students, with each team having to arrange pieces of colored paper to produce two letters each. Before the end of the game, additional constraints were introduced to the teams such that they faced similar ambiguity in the technical facts that the engineers involved in the Challenger disaster had faced prior to the space shuttle launch. At this stage, the teams had to decide whether to continue with their original design or to develop alternative solutions. After the teams had made their decisions, a video of the Challenger explosion was shown followed by a post-game discussion. The students' opinion on five Statements on ethics was tracked via a Five-Item Likert survey which was administered three times, before and after the ethical scenario was introduced, and after the video and post-game discussion. The results from this study indicated that the combination of the game and the real-life incident from the video had generally strengthened the students' opinions of the Statements.
    Matched MeSH terms: Data Collection
  16. Fulltext Translation and validation of the Arabic version of the General Medication Adherence Scale (GMAS) in Saudi patients with chronic illnesses
    Naqvi AA, Mahmoud MA, AlShayban DM, Alharbi FA, Alolayan SO, Althagfan S, et al.
    Saudi Pharm J, 2020 Sep;28(9):1055-1061.
    PMID: 32922135 DOI: 10.1016/j.jsps.2020.07.005
    Purpose: The study aimed to translate and validate the Arabic version of General Medication Adherence Scale (GMAS) in Saudi patients with chronic diseases.

    Methods: A multi-center cross sectional study was conducted for a month in out-patient wards of hospitals in Khobar, Dammam, Makkah, and Madinah, Saudi Arabia. Patients were randomly selected from a registered patient pools at hospitals and the item-subject ratio was kept at 1:20. The tool was assessed for factorial, construct, convergent, known group and predictive validities as well as, reliability and internal consistency of scale were also evaluated. Sensitivity, specificity, and accuracy were also evaluated. Data were analyzed using SPSS v24 and MedCalc v19.2. The study was approved by concerned ethics committees (IRB-129-25/6/1439) and (IRB-2019-05-002).

    Results: A total of 282 responses were received. The values for normed fit index (NFI), comparative fit index (CFI), Tucker Lewis index (TLI) and incremental fit index (IFI) were 0.960, 0.979, 0.954 and 0.980. All values were >0.95. The value for root mean square error of approximation (RMSEA) was 0.059, i.e., <0.06. Hence, factorial validity was established. The average factor loading of the scale was 0.725, i.e., >0.7, that established convergent validity. Known group validity was established by obtaining significant p-value <0.05, for the associations based on hypotheses. Cronbach's α was 0.865, i.e., >0.7. Predictive validity was established by evaluating odds ratios (OR) of demographic factors with adherence score using logistic regression. Sensitivity was 78.16%, specificity was 76.85% and, accuracy of the tool was 77.66%, i.e., >70%.

    Conclusion: The Arabic version of GMAS achieved all required statistical parameters and was validated in Saudi patients with chronic diseases.

    Matched MeSH terms: Data Collection
  17. Analisis Data Panel ke Atas Fungsi Pengeluaran Sektor Pembuatan Makanan di Malaysia
    Abu Hassan Shaari Mohd Nor, Fauziah Maarof
    Sains Malaysiana, 2004;33.
    The main purpose of this article is to introduce the technique of panel data analysis in econometrics modeling. The elasticity of labour, capital and economic of scale for twenty two food manufacturing firms covering from 1989 to 1993 is estimated using the Cobb-Douglas model. The three main techniques of panel data analysis discussed are least square dummy variables (LSDV), analysis of covariance (ANCOVA) and generalized least square (GLS). Ordinary Least Square (OLS) method is included as the basis of comparison.
    Matched MeSH terms: Data Collection
  18. Fulltext SMART-SLE: serology monitoring and repeat testing in systemic lupus erythematosus-an analysis of anti-double-stranded DNA monitoring
    Yeo AL, Kandane-Rathnayake R, Koelmeyer R, Golder V, Louthrenoo W, Chen YH, et al.
    Rheumatology (Oxford), 2024 Feb 01;63(2):525-533.
    PMID: 37208196 DOI: 10.1093/rheumatology/kead231
    OBJECTIVE: Disease activity monitoring in SLE includes serial measurement of anti-double stranded-DNA (dsDNA) antibodies, but in patients who are persistently anti-dsDNA positive, the utility of repeated measurement is unclear. We investigated the usefulness of serial anti-dsDNA testing in predicting flare in SLE patients who are persistently anti-dsDNA positive.

    METHODS: Data were analysed from patients in a multinational longitudinal cohort with known anti-dsDNA results from 2013 to 2021. Patients were categorized based on their anti-dsDNA results as persistently negative, fluctuating or persistently positive. Cox regression models were used to examine longitudinal associations of anti-dsDNA results with flare.

    RESULTS: Data from 37 582 visits of 3484 patients were analysed. Of the patients 1029 (29.5%) had persistently positive anti-dsDNA and 1195 (34.3%) had fluctuating results. Anti-dsDNA expressed as a ratio to the normal cut-off was associated with the risk of subsequent flare, including in the persistently positive cohort (adjusted hazard ratio [HR] 1.56; 95% CI: 1.30, 1.87; P 3. Both increases and decreases in anti-dsDNA more than 2-fold compared with the previous visit were associated with increased risk of flare in the fluctuating cohort (adjusted HR 1.33; 95% CI: 1.08, 1.65; P = 0.008) and the persistently positive cohort (adjusted HR 1.36; 95% CI: 1.08, 1.71; P = 0.009).

    CONCLUSION: Absolute value and change in anti-dsDNA titres predict flares, including in persistently anti-dsDNA positive patients. This indicates that repeat monitoring of dsDNA has value in routine testing.

    Matched MeSH terms: Data Collection
  19. Seroprevalence and risk factors of Trypanosoma evansi infection in horses in Peninsular Malaysia
    Elshafie EI, Sani RA, Hassan L, Sharma R, Bashir A, Abubakar IA
    Res Vet Sci, 2013 Apr;94(2):285-9.
    PMID: 23021152 DOI: 10.1016/j.rvsc.2012.09.004
    A cross-sectional study was designed to assess the seroprevalence and risk factors associated with Trypanosoma evansi infection among horses, using a total of 527 blood samples obtained from eight states in Peninsular Malaysia. A structured questionnaire was used to collect data on risk factors associated with T. evansi seroprevalence. The overall seroprevalence detected by card agglutination test for T. evansi (CATT/T. evansi) was 13.90% (73/527, CI: 11.2-17.1%). Female and exogenous horses showed a higher risk in association with the disease seroprevalence compared to other groups. The majority of the horse owners were not familiar with surra (85.30%). However, most of them were very cautious with the health of their animals. In conclusion, this study showed that T. evansi occurred in low frequency among horses in Peninsular Malaysia, and the good management system adopted by horse owners was probably responsible for the low T. evansi occurrence.
    Matched MeSH terms: Data Collection
  20. Consumer perception on generic medicines in Basrah, Iraq: preliminary findings from a qualitative study
    Sharrad AK, Hassali MA
    Res Social Adm Pharm, 2011 Mar;7(1):108-12.
    PMID: 21397885 DOI: 10.1016/j.sapharm.2009.12.003
    BACKGROUND: The use of generic medicines has been increasing steadily internationally, primarily because of cost concerns. Knowledge and use patterns of generic medicines in Iraq have not yet been measured.
    OBJECTIVE: This study aimed to explore consumers' perception and knowledge on issues relating to generic medicine use in Basrah, Iraq.
    METHODS: A qualitative approach was used to gather information from consumers in Basrah, Iraq. A purposive sample of 14 consumers in Basrah was interviewed face-to-face using a semistructured interview guide.
    RESULTS: Thematic analysis of the interviews identified 5 major themes: understanding of the term "generic medicine," preference for generic medicine, refusal of generic medicine, generic substitution, and education on the use of generic medicines. Not all the consumers were familiar with the term "generic medicine;" they were familiar with the term "commercial medicine." Most of the participants understood that generics cost less compared with their branded counterparts. Most of the consumers said that their physicians and pharmacists had given them information on generics.
    CONCLUSION: Knowledge of generic medicines may be lacking among consumers in Iraq. Development of consumer education on generics by health care providers is required to support the implementation of the policy on generic medicines in Iraq.
    Matched MeSH terms: Data Collection
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