Displaying publications 81 - 100 of 2040 in total

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  1. Dahiru AT, Daud D, Tan CW, Jagun ZT, Samsudin S, Dobi AM
    Environ Sci Pollut Res Int, 2023 Jul;30(34):81984-82013.
    PMID: 36652076 DOI: 10.1007/s11356-023-25146-x
    A major challenge in renewable energy planning and integration with existing systems is the management of intermittence of the resources and customer demand uncertainties that are attributed to climates. In emerging distributed grids, state-of-the-art optimization techniques were used for cost and reliability objectives. In the existing literature, power dispatch and demand side management schemes were implemented for various techno-economic objectives. In renewable energy-based distributed grids, power dispatch is strategic to system operations. However, demand side management is preferred, as it allows more options for customer participation and active management of energy in buildings. Moreover, the demand side management can simply follow supplies. This paper investigates the implications of demand side management as it affects planning and operations in renewable energy-based distributed grids. Integration of demand side management in customer-oriented plans such as the time-of-use and real-time-pricing on residential and commercial demands is conceptualised to ensure effective customer participation which maintains the valued comforts. Moreover, the optimised tariff integrated demand side management implementations based on the utility-initiated demand response programmes are envisaged to offset conflicting objectives of the economy and customer comforts within residential and commercial demands and are also viewed as a step towards efficient management of energy in buildings.
    Matched MeSH terms: Reproducibility of Results
  2. Leung HK, Mahadeva S, Rajaram RB, Lai PSM
    Eur J Gastroenterol Hepatol, 2023 Mar 01;35(3):333-341.
    PMID: 36708305 DOI: 10.1097/MEG.0000000000002493
    BACKGROUND: Assessing a patient's knowledge regarding liver cirrhosis is important to improve patient outcomes. This study aimed to develop and validate the Adult cirrhosiS Knowledge Questionnaire (ASK-Q) to assess patients' knowledge regarding liver cirrhosis from multiple aspects.

    METHODS: A 24-item ASK-Q with four domains: self-understanding (5 items), aetiology (5 items), complications (5 items) and management (9 items) of liver cirrhosis was developed based on literature review and expert panel input. It was then piloted in five English-speaking patients with liver cirrhosis. These patients commented that the font size was too small. Hence, the font was enlarged and the final version of the ASK-Q was administered to English-speaking patients with liver cirrhosis, aged ≥18 years, with or without decompensation, at a tertiary hospital, from September 2020 to November 2021, at baseline and fortnight later. Patients with encephalopathy were excluded.

    RESULTS: 120/135 patients agreed to participate (response rate = 88.9%). The overall median score was 59.1 (45.6-68.2). A total of 7/22 (31.8%) items were "easy", 14/22 (63.6%) items were "moderately easy" and 1/22 (4.5%) items were "difficult". Exploratory factor analysis extracted nine factors, and two items were omitted. The ASK-Q was able to discriminate the knowledge level of patients with and without tertiary education [59.1 (50.0-72.7) vs. 54.5 (36.4-63.6); P 

    Matched MeSH terms: Reproducibility of Results
  3. Er HM, Wong PS, Nadarajah VD
    BMC Med Educ, 2023 Jun 02;23(1):397.
    PMID: 37268906 DOI: 10.1186/s12909-023-04368-0
    BACKGROUND: Open book examinations have been used to assess students' higher order cognitive skills. These examinations can be conducted online remotely with the advancement of technology. However, there are concerns regarding its validity and reliability particularly if the examinations are not proctored. The objective of this study was to explore the perceptions of faculty and students in health professions programmes about remote online open book examinations (ROOBE).

    METHODS: Semi-structured interviews were conducted among 22 faculty staff who were involved in ROOBE in health professions programmes. All interviews were audio recorded, transcribed verbatim and analysed using a thematic analysis approach. The perceptions of 249 medical students were obtained using an online questionnaire after they completed ROOBE.

    RESULTS: The faculty agreed that open book examinations could promote students' higher order cognitive skills and reduce students' stress. However, they were concerned about students' academic integrity during non-invigilated ROOBE which could affect recognition by accreditation and professional bodies. The shift from traditional practice of closed-book examinations to ROOBE required change management with the support of guidelines and faculty training.  Majority of the students claimed that the examinations were challenging as they assessed their ability to apply knowledge in real world problems. Nevertheless, they preferred ROOBE due to less anxiety and memorisation, and more emphasis on problem solving skills. The shortcomings were insufficient time for information searching during examinations and uncertainty in preparedness for future practice as they focused less on memorisation of factual knowledge during examination preparation. Cheating among peers and internet instability during non-invigilated ROOBE were the concerns highlighted by some students.

    CONCLUSIONS: Faculty and students expressed favourable views about ROOBE in promoting higher order cognitive skills. Adequate technological support was essential during ROOBE. While there was a need to address issues related to academic integrity, ROOBE could be included as an authentic assessment within the systems of assessment.

    Matched MeSH terms: Reproducibility of Results
  4. Devan PAM, Ibrahim R, Omar M, Bingi K, Abdulrab H
    Sensors (Basel), 2023 Jul 07;23(13).
    PMID: 37448072 DOI: 10.3390/s23136224
    A novel hybrid Harris Hawk-Arithmetic Optimization Algorithm (HHAOA) for optimizing the Industrial Wireless Mesh Networks (WMNs) and real-time pressure process control was proposed in this research article. The proposed algorithm uses inspiration from Harris Hawk Optimization and the Arithmetic Optimization Algorithm to improve position relocation problems, premature convergence, and the poor accuracy the existing techniques face. The HHAOA algorithm was evaluated on various benchmark functions and compared with other optimization algorithms, namely Arithmetic Optimization Algorithm, Moth Flame Optimization, Sine Cosine Algorithm, Grey Wolf Optimization, and Harris Hawk Optimization. The proposed algorithm was also applied to a real-world industrial wireless mesh network simulation and experimentation on the real-time pressure process control system. All the results demonstrate that the HHAOA algorithm outperforms different algorithms regarding mean, standard deviation, convergence speed, accuracy, and robustness and improves client router connectivity and network congestion with a 31.7% reduction in Wireless Mesh Network routers. In the real-time pressure process, the HHAOA optimized Fractional-order Predictive PI (FOPPI) Controller produced a robust and smoother control signal leading to minimal peak overshoot and an average of a 53.244% faster settling. Based on the results, the algorithm enhanced the efficiency and reliability of industrial wireless networks and real-time pressure process control systems, which are critical for industrial automation and control applications.
    Matched MeSH terms: Reproducibility of Results
  5. Yin T, Xu L, Gil B, Merali N, Sokolikova MS, Gaboriau DCA, et al.
    ACS Nano, 2023 Aug 08;17(15):14619-14631.
    PMID: 37470391 DOI: 10.1021/acsnano.3c01812
    Biosensors based on graphene field effect transistors (GFETs) have the potential to enable the development of point-of-care diagnostic tools for early stage disease detection. However, issues with reproducibility and manufacturing yields of graphene sensors, but also with Debye screening and unwanted detection of nonspecific species, have prevented the wider clinical use of graphene technology. Here, we demonstrate that our wafer-scalable GFETs array platform enables meaningful clinical results. As a case study of high clinical relevance, we demonstrate an accurate and robust portable GFET array biosensor platform for the detection of pancreatic ductal adenocarcinoma (PDAC) in patients' plasma through specific exosomes (GPC-1 expression) within 45 min. In order to facilitate reproducible detection in blood plasma, we optimized the analytical performance of GFET biosensors via the application of an internal control channel and the development of an optimized test protocol. Based on samples from 18 PDAC patients and 8 healthy controls, the GFET biosensor arrays could accurately discriminate between the two groups while being able to detect early cancer stages including stages 1 and 2. Furthermore, we confirmed the higher expression of GPC-1 and found that the concentration in PDAC plasma was on average more than 1 order of magnitude higher than in healthy samples. We found that these characteristics of GPC-1 cancerous exosomes are responsible for an increase in the number of target exosomes on the surface of graphene, leading to an improved signal response of the GFET biosensors. This GFET biosensor platform holds great promise for the development of an accurate tool for the rapid diagnosis of pancreatic cancer.
    Matched MeSH terms: Reproducibility of Results
  6. Haarindraprasad RP, Thurga Devi N, Thevendran R, Maheswaran S
    Biotechnol J, 2023 Aug;18(8):e2300092.
    PMID: 37139895 DOI: 10.1002/biot.202300092
    The creation of nanostructure is profound for the generation of nanobiosensors in several medical diagnosis. Here, we employed an aqueous hydrothermal route using Zinc-oxide (ZnO) and Gold (Au), which under optimal conditions formed an ultra-crystalline rose-like nanostructure textured with nanowires on the surface, coined as "spiked nanorosette." The spiked nanorosette structures was further characterized to possess crystallites of ZnO and Au grains with average sizes of 27.60 and 32.33 nm, respectively. The intensity for both ZnO (002) and Au (111) planes of the nanocomposite was inferred to be controlled by fine-tuning the percentage of Au nanoparticles doped in the ZnO/Au matrix, as referred by X-ray diffraction analysis. The formation of ZnO/Au-hybrid nanorosettes were additionally verified by the distinct corresponding peaks from photoluminescence and X-ray photoelectron spectroscopy, supported by electrical validations. The biorecognition properties of the spiked nanorosettes were also examined using custom targeted and non-target DNA sequences. The DNA targeting capabilities of the nanostructures were analyzed by Fourier Transform Infrared and electrochemical impedance spectroscopy. The fabricated nanowire-embedded nanorosette exhibited a detection limit at the lower picomolar range of 1 × 10-12 M, with high selectivity, stability and reproducibility and good linearity, under optimal conditions. Impedance-based techniques are more sensitive to the detection of nucleic acid molecule whereas this novel spiked nanorosette demonstrate promising attributes as excellent nanostructures for nanobiosensor developments and their potential future application for nucleic-acids or disease diagnostics.
    Matched MeSH terms: Reproducibility of Results
  7. Mohamed NA, Zulkifley MA, Ibrahim AA, Aouache M
    Sensors (Basel), 2021 Sep 28;21(19).
    PMID: 34640803 DOI: 10.3390/s21196485
    In recent years, there has been an immense amount of research into fall event detection. Generally, a fall event is defined as a situation in which a person unintentionally drops down onto a lower surface. It is crucial to detect the occurrence of fall events as early as possible so that any severe fall consequences can be minimized. Nonetheless, a fall event is a sporadic incidence that occurs seldomly that is falsely detected due to a wide range of fall conditions and situations. Therefore, an automated fall frame detection system, which is referred to as the SmartConvFall is proposed to detect the exact fall frame in a video sequence. It is crucial to know the exact fall frame as it dictates the response time of the system to administer an early treatment to reduce the fall's negative consequences and related injuries. Henceforth, searching for the optimal training configurations is imperative to ensure the main goal of the SmartConvFall is achieved. The proposed SmartConvFall consists of two parts, which are object tracking and instantaneous fall frame detection modules that rely on deep learning representations. The first stage will track the object of interest using a fully convolutional neural network (CNN) tracker. Various training configurations such as optimizer, learning rate, mini-batch size, number of training samples, and region of interest are individually evaluated to determine the best configuration to produce the best tracker model. Meanwhile, the second module goal is to determine the exact instantaneous fall frame by modeling the continuous object trajectories using the Long Short-Term Memory (LSTM) network. Similarly, the LSTM model will undergo various training configurations that cover different types of features selection and the number of stacked layers. The exact instantaneous fall frame is determined using an assumption that a large movement difference with respect to the ground level along the vertical axis can be observed if a fall incident happened. The proposed SmartConvFall is a novel technique as most of the existing methods still relying on detection rather than the tracking module. The SmartConvFall outperforms the state-of-the-art trackers, namely TCNN and MDNET-N trackers, with the highest expected average overlap, robustness, and reliability metrics of 0.1619, 0.6323, and 0.7958, respectively. The SmartConvFall also managed to produce the lowest number of tracking failures with only 43 occasions. Moreover, a three-stack LSTM delivers the lowest mean error with approximately one second delay time in locating the exact instantaneous fall frame. Therefore, the proposed SmartConvFall has demonstrated its potential and suitability to be implemented for a real-time application that could help to avoid any crucial fall consequences such as death and internal bleeding if the early treatment can be administered.
    Matched MeSH terms: Reproducibility of Results
  8. Nazar NSBM, Ramanathan A, Ghani WMN, Rokhani FB, Jacob PS, Sabri NEB, et al.
    Clin Oral Investig, 2024 Jan 16;28(1):98.
    PMID: 38225483 DOI: 10.1007/s00784-023-05481-6
    OBJECTIVES: The aim of this systematic review and meta-analysis is to assess the diagnostic potential of salivary metabolomics in the detection of oral potentially malignant disorders (OPMDs) and oral cancer (OC).

    MATERIALS AND METHODS: A systematic review was performed in accordance with the 3rd edition of the Centre for Reviews and Dissemination (CRD) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Electronic searches for articles were carried out in the PubMed, Web of Science, and Scopus databases. The quality assessment of the included studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS) and the new version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. The effect size was presented using the Forest plot, whereas the presence of publication bias was examined through Begg's funnel plot.

    RESULTS: A total of nine studies were included in the systematic review. The metabolite profiling was heterogeneous across all the studies. The expression of several salivary metabolites was found to be significantly altered in OPMDs and OCs as compared to healthy controls. Meta-analysis was able to be conducted only for N-acetylglucosamine. There was no significant difference (SMD = 0.15; 95% CI - 0.25-0.56) in the level of N-acetylglucosamine between OPMDs, OC, and the control group.

    CONCLUSION: Evidence for N-acetylglucosamine as a salivary biomarker for oral cancer is lacking. Although several salivary metabolites show changes between healthy, OPMDs, and OC, their diagnostic potential cannot be assessed in this review due to a lack of data. Therefore, further high-quality studies with detailed analysis and reporting are required to establish the diagnostic potential of the salivary metabolites in OPMDs and OC.

    CLINICAL RELEVANCE: While some salivary metabolites exhibit significant changes in oral potentially malignant disorders (OPMDs) and oral cancer (OC) compared to healthy controls, the current evidence, especially for N-acetylglucosamine, is inadequate to confirm their reliability as diagnostic biomarkers. Additional high-quality studies are needed for a more conclusive assessment of salivary metabolites in oral disease diagnosis.

    Matched MeSH terms: Reproducibility of Results
  9. Fan CW, Chang YL, Huang PC, Fung XCC, Chen JK, Bevan N, et al.
    BMC Psychol, 2023 Nov 04;11(1):369.
    PMID: 37925470 DOI: 10.1186/s40359-023-01377-y
    BACKGROUND: The benefits of physical activity are well-known to prevent multiple long-term health conditions. Physical appearance and weight-related stigma may influence individuals' decision to engage in physical activity and sport. Therefore, the present study examined the psychometric properties of a newly developed instrument, the Tendency to Avoid Physical Activity and Sport Scale (TAPAS), using modern test theory.

    METHODS: A total of 2319 university students were recruited from mainland China and they completed the TAPAS. Rasch analysis was used to examine the TAPAS' rating scaling functioning, test unidimensionality, item hierarchy, ceiling and floor effects, and differential item functioning (DIF). Moreover, the concurrent validity of the TAPAS was examined using the Weight Self-Stigma Questionnaire (WSSQ), Weight Bias Internalization Scale (WBIS), and body mass index (BMI).

    RESULTS: Unidimensionality was confirmed except for one item. Items corresponding to attitude toward physical activity were more easily adopted compared to items corresponding to actual behavioral aspects. No ceiling and floor effects were found. No DIF existed in the TAPAS items. The TAPAS was strongly correlated with both the WSSQ and WBIS, but not BMI.

    CONCLUSION: The study showed that overall, the TAPAS has robust psychometric properties. However, future research needs to address the misfit item and explore the feasibility of applying the TAPAS to other populations including wider ethnic groups, age ranges, and life stages.

    Matched MeSH terms: Reproducibility of Results
  10. AlDahas A, Heneghan NR, Althobaiti S, Deane JA, Rushton A, Falla D
    BMC Musculoskelet Disord, 2024 Jan 10;25(1):44.
    PMID: 38200520 DOI: 10.1186/s12891-023-07111-4
    INTRODUCTION: Proprioception can be impaired in people with neck pain. The cervical joint position sense test, which measures joint position error (JPE), is the most common test used to assess neck proprioception. The aim of this systematic review was to assess the measurement properties of this test for the assessment of people with and without neck pain.

    METHODS: This systematic review was registered prospectively on Prospero (CRD42020188715). It was designed using the COSMIN guidelines and reported in line with the PRISMA checklist. Two reviewers independently searched Medline, Embase, SportDiscus, and CINAHL Plus databases from inception to the 24th July 2022 with an update of the search conducted until 14th of October 2023. The COSMIN risk of bias checklist was used to assess the risk of bias in each study. The updated criteria for good measurement properties were used to rate individual studies and then the overall pooled results. The level of evidence was rated by two reviewers independently using a modified GRADE approach.

    RESULTS: Fifteen studies were included in this review, 13 reporting absolute JPE and 2 reporting constant JPE. The measurement properties assessed were reliability, measurement error, and validity. The measurement of JPE showed sufficient reliability and validity, however, the level of evidence was low/very low for both measurement properties, apart from convergent validity of the constant JPE, which was high.

    CONCLUSION: The measure of cervical JPE showed sufficient reliability and validity but with low/very low levels of evidence. Further studies are required to investigate the reliability and validity of this test as well as the responsiveness of the measure.

    Matched MeSH terms: Reproducibility of Results
  11. Hui TX, Kasim S, Aziz IA, Fudzee MFM, Haron NS, Sutikno T, et al.
    BMC Bioinformatics, 2024 Jan 12;25(1):23.
    PMID: 38216898 DOI: 10.1186/s12859-024-05632-w
    BACKGROUND: With the exponential growth of high-throughput technologies, multiple pathway analysis methods have been proposed to estimate pathway activities from gene expression profiles. These pathway activity inference methods can be divided into two main categories: non-Topology-Based (non-TB) and Pathway Topology-Based (PTB) methods. Although some review and survey articles discussed the topic from different aspects, there is a lack of systematic assessment and comparisons on the robustness of these approaches.

    RESULTS: Thus, this study presents comprehensive robustness evaluations of seven widely used pathway activity inference methods using six cancer datasets based on two assessments. The first assessment seeks to investigate the robustness of pathway activity in pathway activity inference methods, while the second assessment aims to assess the robustness of risk-active pathways and genes predicted by these methods. The mean reproducibility power and total number of identified informative pathways and genes were evaluated. Based on the first assessment, the mean reproducibility power of pathway activity inference methods generally decreased as the number of pathway selections increased. Entropy-based Directed Random Walk (e-DRW) distinctly outperformed other methods in exhibiting the greatest reproducibility power across all cancer datasets. On the other hand, the second assessment shows that no methods provide satisfactory results across datasets.

    CONCLUSION: However, PTB methods generally appear to perform better in producing greater reproducibility power and identifying potential cancer markers compared to non-TB methods.

    Matched MeSH terms: Reproducibility of Results
  12. Jovanović V, Rudnev M, Abdelrahman M, Abdul Kadir NB, Adebayo DF, Akaliyski P, et al.
    Psychol Assess, 2024 Jan;36(1):14-29.
    PMID: 38010780 DOI: 10.1037/pas0001270
    Coronavirus Anxiety Scale (CAS) is a widely used measure that captures somatic symptoms of coronavirus-related anxiety. In a large-scale collaboration spanning 60 countries (Ntotal = 21,513), we examined the CAS's measurement invariance and assessed the convergent validity of CAS scores in relation to the fear of COVID-19 (FCV-19S) and the satisfaction with life (SWLS-3) scales. We utilized both conventional exact invariance tests and alignment procedures, with results revealing that the single-factor model fit the data well in almost all countries. Partial scalar invariance was supported in a subset of 56 countries. To ensure the robustness of results, given the unbalanced samples, we employed resampling techniques both with and without replacement and found the results were more stable in larger samples. The alignment procedure demonstrated a high degree of measurement invariance with 9% of the parameters exhibiting noninvariance. We also conducted simulations of alignment using the parameters estimated in the current model. Findings demonstrated reliability of the means but indicated challenges in estimating the latent variances. Strong positive correlations between CAS and FCV-19S estimated with all three different approaches were found in most countries. Correlations of CAS and SWLS-3 were weak and negative but significantly differed from zero in several countries. Overall, the study provided support for the measurement invariance of the CAS and offered evidence of its convergent validity while also highlighting issues with variance estimation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
    Matched MeSH terms: Reproducibility of Results
  13. Chee ZJ, Scheeren AM, De Vries M
    Autism, 2024 Jan;28(1):32-42.
    PMID: 36632803 DOI: 10.1177/13623613221147395
    The AQ-28 is a questionnaire measuring autistic traits, that is, traits that are related to Autism Spectrum Conditions, but its reliability in other cultures has not been thoroughly evaluated. We, therefore, tested whether the properties of the AQ-28 are comparable between two countries with different cultures, Malaysia and the Netherlands. A total of 437 Malaysian and 818 Dutch participants completed the AQ-28 online. We measured whether the AQ-28 measures autistic traits similarly in Malaysia and the Netherlands. The AQ-28 measures autistic traits similarly, and the reliability was acceptable and good in the general population of Malaysia and the Netherlands, respectively. However, Malaysians scored higher than Dutch participants. Moreover, 11 AQ-28 items showed cultural bias, indicating that these items are answered/interpreted differently in Malaysia and the Netherlands. Cross-cultural differences in interpreting, reporting, and/or expressing autistic traits highlighted in this study could potentially explain why some items are culturally biased and why Malaysians score higher on these items. The findings of this work imply that cutoff scores derived from one culture should not be generalised to another culture. Moreover, the findings are informative for future development of culturally neutral or appropriate screening and diagnostic tools for autism.
    Matched MeSH terms: Reproducibility of Results
  14. Leong SS, Jalalonmuhali M, Md Shah MN, Ng KH, Vijayananthan A, Hisham R, et al.
    Br J Radiol, 2023 Mar 01;96(1144):20220288.
    PMID: 36802861 DOI: 10.1259/bjr.20220288
    OBJECTIVE: Many studies have conflicting findings in using shear wave elastography (SWE) to assess renal fibrosis. This study reviews the use of SWE to evaluate pathological changes in native kidneys and renal allografts. It also tries to elucidate the confounding factors and care taken to ensure the results are consistent and reliable.

    METHODS: The review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Literature search was conducted in Pubmed, Web of Science and Scopus database up to 23 October 2021. To evaluate risk and bias applicability, the Cochrane risk-of bias tool and GRADE was used. The review was registered under PROSPERO CRD42021265303.

    RESULTS: A total of 2921 articles were identified. 104 full texts were examined and 26 studies included in systematic review. 11 studies performed on native kidneys and 15 studies on transplanted kidney. A wide range of impact factors was found that affect the accuracy of SWE of renal fibrosis in adult patients.

    CONCLUSIONS: Compared to point SWE, two-dimensional SWE with elastogram could enable better selection of the region of interest in kidneys, leading to reproducible results. Tracking waves were attenuated as the depth from skin to region of interest increased, therefore, SWE is not recommended for overweight or obese patients. Variable transducer forces might also affect SWE reproducibility, thus, training of operators to ensure consistent operator-dependent transducer forces may be helpful.

    ADVANCES IN KNOWLEDGE: This review provides a holistic insight on the efficiency of using SWE in evaluating pathological changes in native and transplanted kidneys, thereby contributing to the knowledge of its utilisation in clinical practice.

    Matched MeSH terms: Reproducibility of Results
  15. Wang J, Li C, Awasthi MK, Nyambura SM, Zhu Z, Li H, et al.
    J Environ Manage, 2024 Feb 27;353:120182.
    PMID: 38278112 DOI: 10.1016/j.jenvman.2024.120182
    Randomly collected food waste results in inaccurate experimental data with poor reproducibility for composting. This study investigated standard food waste samples as replacements for randomly collected food waste. A response surface methodology was utilised to analyse data from a 28-day compost process optimisation experiment using collected food waste, and the optimal combination of composting parameters was derived. Experiments using different standard food waste samples (high oil and salt, high oil and sugar, balanced diet, and vegetarian) were conducted for 28 days under optimal conditions. The ranking of differences between the standard samples and collected food waste was vegetarian > balanced diet > high oil and sugar > high oil and salt. Statistical analysis indicated t-tests for increased oil and salt samples and collected food waste were not significant, and Cohen's d effect values were minimal. High oil and salt samples can be used as replacements for collected food waste in composting experiments.
    Matched MeSH terms: Reproducibility of Results
  16. Azhar Hilmy SH, Nordin N, Yusof MYPM, Soh TYT, Yusof N
    Nutr J, 2024 Jan 17;23(1):11.
    PMID: 38233923 DOI: 10.1186/s12937-023-00884-3
    Excessive sugar consumption is well documented as a common risk factor for many Non-Communicable Diseases (NCDs). Thus, an adequate intervention description is important to minimise research waste and improve research usability and reproducibility. A systematic review was conducted to identify components in published evidence interventions pertaining to the health promotions on reducing sugar intake among adults. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and used the Mixed Methods Appraisal Tool (MMAT) for quality appraisal. The period for the selected study was from 2000 to 2022, and articles were retrieved from Web of Science (WOS), Medline, Scopus, and PubMed. The target population was adults aged 18 years old and above who underwent intervention to assess the changes in their sugar intake. Data sources and all human epidemiologic studies were included. Out of the 9,333 papers identified, 25 were included. The overall quality of evidence of the studies was considered moderate. Apart from the characteristics of the reviewed studies, components of interventions are including the basis of theoretical or model for the intervention, which majority use Social Cognitive Theory, followed by PRECEDE-PROCEED model, socio-ecological and process-improvement theories and Transtheoretical Model; providers, who are commercial provider, qualified nutritionist, professor of nutrigenomics and nutrigenetics, doctor, dietitian nutritionist, lifestyle coaches, and junior public health nurses; duration of the intervention and follow-up time, varies from as short as one month to as long as 24 months; material provided either softcopy or hardcopy; tailoring approach, based on the individual goals, the process of change, genotype analysis, beliefs, barriers, and sociocultural norms; delivery mechanism either face-to-face or technology-mediated; and tools to measure the sugar consumption outcome mostly used Food Frequency Questionnaire (FFQ), besides 24-h dietary recalls, and food diaries. There are various components in downstream health promotion to reduce sugar intake among adults that can be adapted according to the local health promotion and intervention context. More well-designed interventions using integration components are encouraged in further studies.
    Matched MeSH terms: Reproducibility of Results
  17. Fessi MS, Ben Saad H, Soares Oliveira RF, Washif JA, Chamari K, Moalla W
    Tunis Med, 2023 Nov 05;101(11):795-799.
    PMID: 38468578
    AIM: This research design protocol outlines the methodology for a thorough evaluation of workload monitoring and management strategies in football.

    METHODS: The study involves conducting a global survey to fitness coaches, sports scientists, analysts, and physicians with experience in load monitoring within football. The research adheres to the principles of the Helsinki Declaration and complies with General Data Protection Regulation standards, with ethical approvals obtained from multiple Ethics Committees across various countries, including Tunisia. A consortium of professionals collaboratively crafted the survey instrument, dividing it into seven sections, each addressing specific aspects of workload monitoring in football. Survey reliability will undergo evaluation in a pilot study utilizing Cronbach's alpha and intraclass correlation coefficient. To ensure inclusivity, the survey will be translated into multiple languages, facilitating participation from diverse regions. As such, survey distribution will consider online platforms (such as social media) and email invitations, with a specific focus on engaging football clubs, federations, and professional networks. The targeted sample size will remain at 385 participants. Statistical analysis planning encompasses descriptive examination, exploration of variable relationships, hypothesis testing, and qualitative analyses of participant feedback and recommendations regarding load monitoring practices.

    EXPECTED RESULTS: Expected outcomes include i) A comprehensive global overview of training and match load monitoring practices in football, ii) The identification of emerging trends, an improved understanding of training optimization processes, and iii) The development of practical recommendations to enhance player well-being and performance.

    CONCLUSION: This study will contribute to the ongoing development of knowledge in the field of football workload monitoring.

    Matched MeSH terms: Reproducibility of Results
  18. Teoh YX, Lai KW, Usman J, Goh SL, Mohafez H, Hasikin K, et al.
    J Healthc Eng, 2022;2022:4138666.
    PMID: 35222885 DOI: 10.1155/2022/4138666
    Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren-Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.
    Matched MeSH terms: Reproducibility of Results
  19. Amaechi CV, Reda A, Kgosiemang IM, Ja'e IA, Oyetunji AK, Olukolajo MA, et al.
    Sensors (Basel), 2022 Sep 25;22(19).
    PMID: 36236369 DOI: 10.3390/s22197270
    Recent activities in the oil and gas industry have shown an increasing need for monitoring engagements, such as in shipping, logistics, exploration, drilling, or production. Hence, there is a need to have asset management of these offshore assets (or facilities). Much of the offshore infrastructure is currently approaching or past its operational life expectancy. The study presents an overview on asset management of offshore facilities towards monitoring, safe practices, maintenance, and sustainability. This study outlines the major considerations and the steps to take when evaluating asset life extensions for an aging offshore structure (or asset). The design and construction of offshore structures require some materials that are used to make the structural units, such as offshore platform rigs, ships, and boats. Maintaining existing assets in the field and developing new platforms that are capable of extracting future oil and gas resources are the two key issues facing the offshore sector. This paper also discusses fault diagnosis using sensors in the offshore facilities. The ocean environment is constantly corrosive, and the production activities demand extremely high levels of safety and reliability. Due to the limited space and remote location of most offshore operations, producing cost-effective, efficient, and long-lasting equipment necessitates a high level of competence. This paper presents the guidelines on asset monitoring, sustainable maintenance, and safety practices for offshore structures. In this study, the management of offshore structures were also presented with some discussions on fault monitoring using sensors. It also proposes sustainable asset management approaches as guidelines that are advised, with policy implications.
    Matched MeSH terms: Reproducibility of Results
  20. Zainurin SN, Wan Ismail WZ, Mahamud SNI, Ismail I, Jamaludin J, Ariffin KNZ, et al.
    Int J Environ Res Public Health, 2022 Oct 28;19(21).
    PMID: 36360992 DOI: 10.3390/ijerph192114080
    Nowadays, water pollution has become a global issue affecting most countries in the world. Water quality should be monitored to alert authorities on water pollution, so that action can be taken quickly. The objective of the review is to study various conventional and modern methods of monitoring water quality to identify the strengths and weaknesses of the methods. The methods include the Internet of Things (IoT), virtual sensing, cyber-physical system (CPS), and optical techniques. In this review, water quality monitoring systems and process control in several countries, such as New Zealand, China, Serbia, Bangladesh, Malaysia, and India, are discussed. Conventional and modern methods are compared in terms of parameters, complexity, and reliability. Recent methods of water quality monitoring techniques are also reviewed to study any loopholes in modern methods. We found that CPS is suitable for monitoring water quality due to a good combination of physical and computational algorithms. Its embedded sensors, processors, and actuators can be designed to detect and interact with environments. We believe that conventional methods are costly and complex, whereas modern methods are also expensive but simpler with real-time detection. Traditional approaches are more time-consuming and expensive due to the high maintenance of laboratory facilities, involve chemical materials, and are inefficient for on-site monitoring applications. Apart from that, previous monitoring methods have issues in achieving a reliable measurement of water quality parameters in real time. There are still limitations in instruments for detecting pollutants and producing valuable information on water quality. Thus, the review is important in order to compare previous methods and to improve current water quality assessments in terms of reliability and cost-effectiveness.
    Matched MeSH terms: Reproducibility of Results
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