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Fulltext #EEGManyLabs: Investigating the replicability of influential EEG experiments

Pavlov YG, Adamian N, Appelhoff S, Arvaneh M, Benwell CSY, Beste C, et al.

Cortex, 2021 11;144:213-229.
PMID: 33965167 DOI: 10.1016/j.cortex.2021.03.013

There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations.

Matched MeSH terms: Reproducibility of Results
Chemometrics analysis for the detection of dental caries via UV absorption spectroscopy

Basri KN, Yazid F, Megat Abdul Wahab R, Mohd Zain MN, Md Yusof Z, Zoolfakar AS

Spectrochim Acta A Mol Biomol Spectrosc, 2022 Feb 05;266:120464.
PMID: 34634732 DOI: 10.1016/j.saa.2021.120464

Caries is one of the non-communicable diseases that has a high prevalence trend. The current methods used to detect caries require sophisticated laboratory equipment, professional inspection, and expensive equipment such as X-ray imaging device. A non-invasive and economical method is required to substitute the conventional methods for the detection of caries. UV absorption spectroscopy coupled with chemometrics analysis has emerged as a good potential candidate for such an application. Data preprocessing methods such as mean centre, autoscale and Savitzky-Golay smoothing were implemented to enhance the signal-to-noise ratio of spectra data. Various classification algorithms namely K-nearest neighbours (KNN), logistic regression (LR) and linear discriminant analysis (LDA) were implemented to classify the severity of dental caries into International Caries Detection and Assessment System (ICDAS) scores. The performance of the prediction model was measured and comparatively analysed based on the accuracy, precision, sensitivity, and specificity. The LDA algorithm combined with the Savitzky-Golay preprocessing method had shown the best result with respect to the validation data accuracy, precision, sensitivity and specificity, where each had values of 0.90, 1.00, 0.86 and 1.00 respectively. The area under the curve of the ROC plot computed for the LDA algorithm was 0.95, which indicated that the prediction algorithm was capable of differentiating normal and caries teeth excellently.

Matched MeSH terms: Reproducibility of Results
Fulltext Malay version of the family satisfaction scale: validity and reliability among Malaysian working women

Aazami S, Shamsuddin K, Akmal S

Int J Public Health Res, 2015;5(2):606-612.
MyJurnal

Introduction Family satisfaction is referred to the extent in which family members feel happy and fulfilled with each other. However, there has been lack of evidences on the family satisfaction scale within the Malaysian context. Therefore, the aim of this study was to assess validity of the Malay version of the Olson’s Family Satisfaction Scale. This is to allow Malaysian researchers to bring family satisfaction in line with the different field of studies.
Methods This study was conducted among 567 Malaysian working women. Data were collected using self-administrated questionnaires. This study conducted exploratory and confirmatory factor analysis, convergent validity and internal consistency using Cronbach’s alpha.
Results The findings of this study support the uni-dimensionality of the Malay version of the family satisfaction scale. The 10 items of the scale account for 68.1% of the total variance and the un-rotated factor loadings ranged from 0.76 to 0.87. Confirmatory factor analysis was run and supported the structure of family satisfaction scale. The results of confirmatory factor analysis using AMOS 21 in the current study reported the following indices: RMSEA= 0.06, CFI= 0.94, NFI= 0.94, TLI= 0.93. The convergent validity (average variance extracted= 0.65) and the internal consistency (Cronbach’s alpha= 0.94) of this construct were adequately supported.
Conclusions The findings support the factor structure, convergent validity and the internal consistency of the examined construct. Therefore, Malay version of the family satisfaction scale is a valid and reliable instrument among Malaysian working women.

Matched MeSH terms: Reproducibility of Results
Fulltext Evaluation of inverter reliability performance due to negative bias temperature instability (NBTI) effects in advance CMOS technology nodes

Zainudin, M.F., Hussin, H., Halim, A.K.

Pertanika Journal of Science & Technology, 2017;25(101):295-304.
MyJurnal

Negative bias temperature instability (NBTI) is the most concern issue CMOS devices with the scaling
down of the CMOS technologies. NBTI effect contributes to P-MOSFET device degradation which later
reduce the performance and reliability of CMOS circuits. This paper presents a reliability simulation study
based on R-D model on CMOS inverter circuit. HSPICE MOSRA model together with the Predictive
Technology Model (PTM) was used as to incorporate the NBTI model in the circuit reliability simulation
study for different technology nodes. PTM of High Performance (HP) models of 16nm, 22nm, 32nm
and 45nm were used in this simulation study. The atomic hydrogen based model was integrated in the
simulation. The results show that in a CMOS inverter circuit, the threshold voltage shift of p-MOSFET
under NBTI stressing increased as the year progressed.. The threshold voltage shift was observed to
increase up to 45.1% after 10 years of operation. The time exponent, n ~ 0.232 of the threshold voltage
shift observed indicates that the defect mechanism contributed to the degradation is atomic hydrogen.
The propagation delay increased to 19.5% over a 10-year period. s up to 19.5% from the zero year
of operation until 10 years of the operation. In addition, the time propagation delay increased as year
increased when the technology nodes smaller. The finding is important for understanding reliability
issues related to advanced technology nodes in CMOS circuits study.

Matched MeSH terms: Reproducibility of Results
Fulltext A railway rescheduling model with priority setting

Shuib, A., Alwadood, Z.

Pertanika Journal of Science & Technology, 2017;25(2):649-660.
MyJurnal

This paper presents a mathematical approach to solve railway rescheduling problems. The approach assumes that the trains are able to resume their journey after a given time frame of disruption whereby The train that experiences disruption and trains affected by the incident are rescheduled. The approach employed mathematical model to prioritise certain types of train according the railway operator’s requirement. A pre-emptive goal programming model was adapted to find an optimal solution that satisfies the operational constraints and the company’s stated goals. Initially, the model minimises the total service delay of all trains while adhering to the minimum headway requirement and track capacity. Subsequently, it maximises the train service reliability by only considering the trains with delay time window of five minutes or less. The model uses MATLAB R2014a software which automatically generates the optimal solution of the problem based on the input matrix of constraints. An experiment with three incident scenarios on a double-track railway of local network was conducted to evaluate the performance of the proposed model. The new provisional timetable was produced in short computing time and the model was able to prioritise desired train schedule.

Matched MeSH terms: Reproducibility of Results
Fulltext Reliability, technical error of measurement and validity of height measurement using portable stadiometer

Azli Baharudin, Mohamad Hasnan Ahmad, Balkish Mahadir Naidu, Nurul Rufaidah Hamzah, Nor Azian Mohd Zaki, Ahmad Ali Zainuddin, et al.

Pertanika Journal of Science & Technology, 2017;25(3):675-686.
MyJurnal

This study sought to examine the reliability and validity of height measurements using a portable
stadiometer as compared to a mechanical scale. Samples from 142 adults aged 22 to 57 were taken during data collection in November 2014. There was a high degree of reliability for the inter-examiner, intraexaminer and inter-instrument aspects with regards to mean difference, the inter correlation coefficient (ICC) and Bland-Altman Plot. For the inter-examiner aspect, the height measurement taken by the first examiner was 0.01 cm higher than that by the second examiner with an ICC of 0.999. For the intraexaminer aspect, the difference was 0.1 cm; this was higher in the first measurement compared to the second. The ICC was also 0.999. For the inter-instrument aspect, measurement taken by stadiometer was 0.61 cm higher than the measurement taken by mechanical scale and the ICC was 0.997. The Bland-Altman plot showed a distribution of differences between measurements in the inter-examiner, intraexaminer and inter-instrument aspects that were close to zero within the narrow range of ±1.96SD. The technical error of measurement (TEM), coefficient of reliability (R) and coefficient of variation (CV) for the inter-examiner, intra-examiner and inter-instrument aspects were within the acceptable limits. This study suggests that the portable stadiometer is reliable and valid for use in community surveys.

Matched MeSH terms: Reproducibility of Results
Fulltext Development and validation of a Database Forensic Metamodel (DBFM)

Al-Dhaqm A, Razak S, Othman SH, Ngadi A, Ahmed MN, Ali Mohammed A

PLoS One, 2017;12(2):e0170793.
PMID: 28146585 DOI: 10.1371/journal.pone.0170793

Database Forensics (DBF) is a widespread area of knowledge. It has many complex features and is well known amongst database investigators and practitioners. Several models and frameworks have been created specifically to allow knowledge-sharing and effective DBF activities. However, these are often narrow in focus and address specified database incident types. We have analysed 60 such models in an attempt to uncover how numerous DBF activities are really public even when the actions vary. We then generate a unified abstract view of DBF in the form of a metamodel. We identified, extracted, and proposed a common concept and reconciled concept definitions to propose a metamodel. We have applied a metamodelling process to guarantee that this metamodel is comprehensive and consistent.

Matched MeSH terms: Reproducibility of Results
Fulltext Cultural adaptation and validation of the Malay Chronic Kidney Disease Self-management instrument (MCKD-SM)

Al Sawad AA, Lim SK, Tang LY, Rashid AA, Chew BH

BMC Nephrol, 2022 Dec 01;23(1):384.
PMID: 36457069 DOI: 10.1186/s12882-022-03016-x

BACKGROUND: There is growing evidence that self-management behaviour can improve outcomes for patients with chronic kidney disease (CKD). However, no measures are available in Malay to effectively assess the self-management of CKD. The aim of this study was to translate, culturally adapt and validate the Malay Chronic Kidney Disease Self-Management (MCKD-SM) instrument for Malay-speaking health professionals and patients.
METHODS: This study was carried out in two phases: the translation and cultural adaptation phase and the validation phase. The instrument was translated from English to Malay and then adapted and validated in a sample of 337 patients with CKD stages 3-4 attending a nephrology clinic in a tertiary hospital in Malaysia. Structural validity was evaluated by exploratory factor analysis. The instrument's reliability was assessed by internal consistency and test-retest reliability. The correlations between the MCKD-SM and kidney disease knowledge and the MCKD-SM and self-efficacy were hypothesised a priori and investigated.
RESULTS: The MCKD-SM instrument has 29 items grouped into three factors: 'Understanding and Managing My CKD', 'Seeking Support' and 'Adherence to Recommended Regimen'. The three factors accounted for 56.3% of the total variance. Each factor showed acceptable internal reliability, with Cronbach's α from 0.885 to 0.960. The two-week intra-rater test-retest reliability intraclass correlation coefficient values for all items ranged between 0.938 and 1.000. The MCKD-SM scores significantly correlated with kidney disease knowledge (r = 0.366, p

Matched MeSH terms: Reproducibility of Results
Fulltext Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images

Rahman T, Khandakar A, Qiblawey Y, Tahir A, Kiranyaz S, Abul Kashem SB, et al.

Comput Biol Med, 2021 May;132:104319.
PMID: 33799220 DOI: 10.1016/j.compbiomed.2021.104319

Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the healthcare system. Chest X-ray (CXR) imaging has several advantages over other imaging and detection techniques. Numerous works have been reported on COVID-19 detection from a smaller set of original X-ray images. However, the effect of image enhancement and lung segmentation of a large dataset in COVID-19 detection was not reported in the literature. We have compiled a large X-ray dataset (COVQU) consisting of 18,479 CXR images with 8851 normal, 6012 non-COVID lung infections, and 3616 COVID-19 CXR images and their corresponding ground truth lung masks. To the best of our knowledge, this is the largest public COVID positive database and the lung masks. Five different image enhancement techniques: histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE), image complement, gamma correction, and balance contrast enhancement technique (BCET) were used to investigate the effect of image enhancement techniques on COVID-19 detection. A novel U-Net model was proposed and compared with the standard U-Net model for lung segmentation. Six different pre-trained Convolutional Neural Networks (CNNs) (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, and ChexNet) and a shallow CNN model were investigated on the plain and segmented lung CXR images. The novel U-Net model showed an accuracy, Intersection over Union (IoU), and Dice coefficient of 98.63%, 94.3%, and 96.94%, respectively for lung segmentation. The gamma correction-based enhancement technique outperforms other techniques in detecting COVID-19 from the plain and the segmented lung CXR images. Classification performance from plain CXR images is slightly better than the segmented lung CXR images; however, the reliability of network performance is significantly improved for the segmented lung images, which was observed using the visualization technique. The accuracy, precision, sensitivity, F1-score, and specificity were 95.11%, 94.55%, 94.56%, 94.53%, and 95.59% respectively for the segmented lung images. The proposed approach with very reliable and comparable performance will boost the fast and robust COVID-19 detection using chest X-ray images.

Matched MeSH terms: Reproducibility of Results
Metal-free Sulfur-doped graphitic carbon nitride-modified GCE-based electrocatalyst for the enhanced electrochemical determination of Omeprazole in Drug formulations and Biological Samples

Pandian K, Kalayarasi J, Gopinath SCB

Biotechnol Appl Biochem, 2022 Dec;69(6):2766-2779.
PMID: 35287249 DOI: 10.1002/bab.2321

This study presents a novel sulfur-doped graphitic carbon nitride (S@g-C3 N4 ) with a wider potential range as electrocatalyst for electrochemical sensor application. The S@g-C3 N4 nanosheets were successfully prepared with a ball milling method by mixing appropriate molar concentration required precursors. The as-synthesized heteroatom-doped graphitic carbon nitride is characterized by spectroscopic techniques including PL, DRS-UV, FT-IR, and Brunauer-Emmett-Teller equation. The morphological features were studied by FE-SEM and HR-TEM analysis. Chit-S@g-C3 N4 -modified glassy carbon electrode (GCE) was employed for the electrochemical detection of omeprazole (OMZ) use in drug formulations. We have noted an oxidation peak current response at a potential of +0.8 V versus Ag/AgCl in PBS medium (0.1 M, pH 7.0). Differential pulse voltammetry amperometry experimental method can be used to measure the concentration of OMZ for quantitative studies in known samples. Under the optimized experimental condition, the calibration plot was constructed by plotting the peak currents versus OMZ in the linear ranges from 6.0 × 10-7 to 26 × 10-5 M. The linear regression equation is estimated to be Ip (μA) = 0.9518 (C/μM) + 0.3340 with a good correlation coefficient of 0.9996. The lower determination limit was found to be 20 nM and the current sensitivity was calculated (31.722 μA μM-1 cm-2 ). The developed sensor was utilized successfully to determine the OMZ concentration in drug formulations and biological fluids. These results revealed that the Chit-S@g-C3 N4 -modified GCE showed excellent electroanalytical performance for the detection of OMZ at a low LOD, wider linear range, high sensitivity, good reproducibility, long-term storage stability, and selectivity with an acceptable relative standard deviation value.

Matched MeSH terms: Reproducibility of Results
Fulltext Translation and psychometric evaluation of Smartphone Addiction Scale-Short Version (SAS-SV) among Chinese college students

Zhao H, Rafik-Galea S, Fitriana M, Song TJ

PLoS One, 2022;17(11):e0278092.
PMID: 36445890 DOI: 10.1371/journal.pone.0278092

BACKGROUND: Smartphone addiction is very prevalent among college students, especially Chinese college students, and it can cause many psychological problems for college students. However, there is no valid research instrument to evaluate Chinese college students' smartphone addiction.
OBJECTIVE: This study aimed to translate the Smartphone Addiction Scale-Short Version (SAS-SV) into Chinese and evaluate the psychometric characteristics of the Smartphone Addiction Scale- Chinese Short version (SAS-CSV) among Chinese college students.
METHODS: The SAS-SV was translated into Chinese using the forward-backward method. The SAS-CSV was completed by 557 Chinese college students (sample 1: n = 279; sample 2: n = 278). 62 college students were randomly selected from the 557 Chinese college students to be meas- ured twice, with an interval of two weeks. The reliability of the SAS-CSV was evaluated by internal consistency reliability and test-retest reliability, and the validity of the SAS-CSV was evaluated by content validity, structural validity, convergent validity, and discriminant validity.
RESULTS: The SAS-CSV presented good content validity, high internal consistency (sample 1: α = 0.829; sample 2: α = 0.881), and good test-retest reliability (ICC: 0.975; 95% CI: 0.966-0.985). After one exploratory factor analysis, three components (tolerance, withdrawal, and negative effect) with eigenvalues greater than 1 were obtained, and the cumulative variance contribution was 50.995%. The results of confirmatory factor analysis indicated that all the fit indexes reached the standard of good model fit (χ2/df = 1.883, RMSEA = 0.056, NFI = 0.954, RFI = 0.935, IFI = 0.978, TLI = 0.969, CFI = 0.978). The SAS-CSV presented good convergent validity for the factor loading of all the items ranged from 0.626 to 0.892 (higher than 0.50), the three latent variables' AVE ranged from 0.524 to 0.637 (higher than 0.50), and the three latent variables' CR ranged from 0.813 to 0.838 (higher than 0.70). Moreover, the square roots of the AVE of component 1 (tolerance), component 2 (withdrawal) and component 3 (negative effect) were 0.724, 0.778, and 0.798, respectively, higher than they were with other correlation coefficients, indicating that the SAS-CSV had good discrimination validity.
CONCLUSION: The SAS-CSV is a valid instrument for measuring smartphone addiction among Chinese college students.

Matched MeSH terms: Reproducibility of Results
Evaluation of vegetable sauerkraut quality during storage based on convolution neural network

Du J, Zhang M, Teng X, Wang Y, Lim Law C, Fang D, et al.

Food Res Int, 2023 Feb;164:112420.
PMID: 36738024 DOI: 10.1016/j.foodres.2022.112420

Vegetable sauerkraut is a traditional fermented food. Due to oxidation reactions that occur during storage, the quality and flavor in different periods will change. In this study, the quality evaluation and flavor characteristics of 13 groups of vegetable sauerkraut samples with different storage time were analyzed by using physical and chemical parameters combined with electronic nose. Photographs of samples of various periods were collected, and a convolutional neural network (CNN) framework was established. The relationship between total phenol oxidative decomposition and flavor compounds was linearly negatively correlated. The vegetable sauerkraut during storage can be divided into three categories (full acceptance period, acceptance period and unacceptance period) by principal component analysis and Fisher discriminant analysis. The CNN parameters were fine-tuned based on the classification results, and its output results can reflect the quality changes and flavor characteristics of the samples, and have better fitting, prediction capabilities. After 50 epochs of the model, the accuracy of three sets of data namely training set, validation set and test set recorded 94%, 85% and 93%, respectively. In addition, the accuracy of CNN in identifying different quality sauerkraut was 95.30%. It is proved that the convolutional neural network has excellent performance in predicting the quality of Szechuan Sauerkraut with high reliability.

Matched MeSH terms: Reproducibility of Results
Fulltext Hydrological Analysis of Batu Dam, Malaysia in the Urban Area: Flood and Failure Analysis Preparing for Climate Change

Allias Omar SM, Wan Ariffin WNH, Mohd Sidek L, Basri H, Moh Khambali MH, Ahmed AN

Int J Environ Res Public Health, 2022 Dec 09;19(24).
PMID: 36554413 DOI: 10.3390/ijerph192416530

Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m3/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam.

Matched MeSH terms: Reproducibility of Results
Fulltext A validity study to consult on a protocol of a home hazard management program for falls prevention among community dwelling stroke survivors

Ahmad Ainuddin H, Romli MH, S F Salim M, Hamid TA, Mackenzie L

PLoS One, 2023;18(1):e0279657.
PMID: 36630460 DOI: 10.1371/journal.pone.0279657

OBJECTIVE: A fall after a stroke is common but the consequences can be devastating not only for the stroke survivors, but also for caregivers, healthcare, and the society. However, research on falls prevention among the stroke population are limited, particularly on home hazards assessment and home modifications, demanding for a study to be conducted. The aim of the study is to validate the protocol and content of a home hazard management program guided by the Person-Environment-Occupation (PEO) Model for falls prevention among community dwelling stroke survivors.
METHOD: Researchers developed their own questionnaire for content validation which consist of 23 items that covers two domains, namely justification for telehealth home hazard management practice and the protocol's overall methodology. Occupational therapists with at least one year of experience in conducting a home hazard assessment were consulted for the content validation of a two-group clinical controlled trial protocol utilizing a home hazard assessment, home modifications and education over the usual care. Written consent was obtained prior to the study. The occupational therapists were given a Google Form link to review the protocol and intervention based on the questionnaire and rated each item using a four-point Likert scale for relevance and feasibility. Open-ended feedback was also recorded on the google form. Content Validity Index (CVI), Modified Kappa Index and Cronbach's Alpha was calculated for the content validity and reliability analysis.
RESULTS: A total of sixteen occupational therapists participated in the study. 43.7% of participants had a master's degree, 93.7% worked in the government sector and 56.2% had six years and more experience on conducting home hazard assessments. Content validity of the protocol is satisfactory for relevancy and feasibility (CVI = 0.84, ranging from 0.5 to 1.00), and for the reliability (α = 0.94 (relevance) and α = 0.97 (feasibility), respectively. The Modified Kappa ranged from 0.38 to 1.00 for all items. Feedback was also received regarding the design and procedure of the study protocol which included participant's selection criteria, sample size, equipment provided, cost, location, and care for the participants during the intervention.
CONCLUSIONS: Introducing a home hazard management program to prevent falls among the stroke population is viewed relevant and feasible. Practical suggestions from the consultation panel were adopted, and minor adjustments were required to strengthen the protocol's overall methodology. This study established a rigorous and robust experimental protocol for future undertaking.

Matched MeSH terms: Reproducibility of Results
Fulltext Quality assessment of global health care system in the shadow of COVID-19: - a systematic review

Kaur KN, Niazi F, Thakur R, Saeed S, Rana S, Singh H

BMC Public Health, 2023 May 26;23(1):979.
PMID: 37237332 DOI: 10.1186/s12889-023-15840-3

INTRODUCTION: The healthcare system is critical to the country's overall growth, which involves the healthy development of individuals, families, and society everywhere. This systematic review focuses on providing an overall assessment of the quality of healthcare delivery during COVID-19.
METHODOLOGY: The literature search was conducted from March 2020 till April 2023 utilising the databases "PubMed," "Google Scholar," and "Embase." A total of nine articles were included. Descriptive statistics was performed using Microsoft Excel. PROSPERO registration ID- CRD42022356285.
RESULTS: According to the geographic location of the studies included, four studies were conducted in Asia [Malaysia(n = 1); India (Madhya Pradesh) (n = 1); Saudi Arabia(n = 1); Indonesia (Surabaya) (n = 1)], three in Europe [U.K. (n = 1); Poland (n = 1); Albania (n = 1)] and two in Africa [Ethiopia(n = 1); Tunisia (n = 1)]. Overall patient satisfaction was found highest among studies conducted in Saudi Arabia (98.1%) followed by India (Madhya Pradesh) (90.6%) and the U.K. (90%).
CONCLUSION: This review concluded five different aspects of patients satisfaction level i.e. reliability, responsiveness, assurance, empathy, and tangibility. It was found that the empathy aspect had the greatest value of the five factors, i.e., 3.52 followed by Assurance with a value of 3.51.

Matched MeSH terms: Reproducibility of Results
Fulltext A Survey on Handover and Mobility Management in 5G HetNets: Current State, Challenges, and Future Directions

Ullah Y, Roslee MB, Mitani SM, Khan SA, Jusoh MH

Sensors (Basel), 2023 May 25;23(11).
PMID: 37299808 DOI: 10.3390/s23115081

Fifth-generation (5G) networks offer high-speed data transmission with low latency, increased base station volume, improved quality of service (QoS), and massive multiple-input-multiple-output (M-MIMO) channels compared to 4G long-term evolution (LTE) networks. However, the COVID-19 pandemic has disrupted the achievement of mobility and handover (HO) in 5G networks due to significant changes in intelligent devices and high-definition (HD) multimedia applications. Consequently, the current cellular network faces challenges in propagating high-capacity data with improved speed, QoS, latency, and efficient HO and mobility management. This comprehensive survey paper specifically focuses on HO and mobility management issues within 5G heterogeneous networks (HetNets). The paper thoroughly examines the existing literature and investigates key performance indicators (KPIs) and solutions for HO and mobility-related challenges while considering applied standards. Additionally, it evaluates the performance of current models in addressing HO and mobility management issues, taking into account factors such as energy efficiency, reliability, latency, and scalability. Finally, this paper identifies significant challenges associated with HO and mobility management in existing research models and provides detailed evaluations of their solutions along with recommendations for future research.

Matched MeSH terms: Reproducibility of Results
Fulltext Assessment of RNA extraction protocols from cladocerans

Razak MR, Aris AZ, Md Yusoff F, Yusof ZNB, Kim SD, Kim KW

PLoS One, 2022;17(4):e0264989.
PMID: 35472091 DOI: 10.1371/journal.pone.0264989

The usage of cladocerans as non-model organisms in ecotoxicological and risk assessment studies has intensified in recent years due to their ecological importance in aquatic ecosystems. The molecular assessment such as gene expression analysis has been introduced in ecotoxicological and risk assessment to link the expression of specific genes to a biological process in the cladocerans. The validity and accuracy of gene expression analysis depends on the quantity, quality and integrity of extracted ribonucleic acid (RNA) of the sample. However, the standard methods of RNA extraction from the cladocerans are still lacking. This study evaluates the extraction of RNA from tropical freshwater cladocerans Moina micrura using two methods: the phenol-chloroform extraction method (QIAzol) and a column-based kit (Qiagen Micro Kit). Glycogen was introduced in both approaches to enhance the recovery of extracted RNA and the extracted RNA was characterised using spectrophotometric analysis (NanoDrop), capillary electrophoresis (Bioanalyzer). Then, the extracted RNA was analysed with reverse transcription polymerase chain reaction (RT-PCR) to validate the RNA extraction method towards downstream gene expression analysis. The results indicate that the column-based kit is most suitable for the extraction of RNA from M. micrura, with the quantity (RNA concentration = 26.90 ± 6.89 ng/μl), quality (A260:230 = 1.95 ± 0.15, A280:230 = 1.85 ± 0.09) and integrity (RNA integrity number, RIN = 7.20 ± 0.16). The RT-PCR analysis shows that the method successfully amplified both alpha tubulin and actin gene at 33-35 cycles (i.e. Ct = 32.64 to 33.48). The results demonstrate that the addition of glycogen is only suitable for the phenol-chloroform extraction method. RNA extraction with high and comprehensive quality control assessment will increase the accuracy and reliability of downstream gene expression, thus providing more ecotoxicological data at the molecular biological level on other freshwater zooplankton species.

Matched MeSH terms: Reproducibility of Results
Fulltext Effectiveness of Artificial Intelligence (AI) in Improving Pupils' Deep Learning in Primary School Mathematics Teaching in Fujian Province

Qiu Y, Pan J, Ishak NA

Comput Intell Neurosci, 2022;2022:1362996.
PMID: 36193186 DOI: 10.1155/2022/1362996

Several primary school students in Fujian Province have perceived studying mathematics as challenging. To deal with this issue, computer technology advancements, specifically artificial intelligence (AI), present an opportunity to evaluate individual students' learning challenges and give individualized support to optimize their success in mathematics classes. It is also possible to use virtual reality (VR) to assist learners in acquiring complex mathematical and logical ideas and to lessen learners' mistakes. As a result, researchers, particularly beginners, are missing out on a complete perspective of the study of AI in teaching mathematics. That is why we are exploring the role of AI in math education by developing a "fuzzy-based tweakable convolution neural network with a long short-term memory (FT-CNN-LSTM-AM)" method. For this investigation, the students' datasets are taken and educated by mathematical teaching via the application of AI. The proposed method is utilized to predict the students' performance in mathematical education. A grey wolf optimizer is employed to boost the effectiveness of the proposed method. Furthermore, the performance of the proposed method is analyzed and compared with existing approaches to gain the highest reliability.

Matched MeSH terms: Reproducibility of Results
Fulltext Automated Gait Analysis Based on a Marker-Free Pose Estimation Model

Hii CST, Gan KB, Zainal N, Mohamed Ibrahim N, Azmin S, Mat Desa SH, et al.

Sensors (Basel), 2023 Jul 18;23(14).
PMID: 37514783 DOI: 10.3390/s23146489

Gait analysis is an essential tool for detecting biomechanical irregularities, designing personalized rehabilitation plans, and enhancing athletic performance. Currently, gait assessment depends on either visual observation, which lacks consistency between raters and requires clinical expertise, or instrumented evaluation, which is costly, invasive, time-consuming, and requires specialized equipment and trained personnel. Markerless gait analysis using 2D pose estimation techniques has emerged as a potential solution, but it still requires significant computational resources and human involvement, making it challenging to use. This research proposes an automated method for temporal gait analysis that employs the MediaPipe Pose, a low-computational-resource pose estimation model. The study validated this approach against the Vicon motion capture system to evaluate its reliability. The findings reveal that this approach demonstrates good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all temporal gait parameters except for double support time (right leg switched to left leg) and swing time (right), which only exhibit a moderate (ICC(2,1) > 0.50) agreement. Additionally, this approach produces temporal gait parameters with low mean absolute error. It will be useful in monitoring changes in gait and evaluating the effectiveness of interventions such as rehabilitation or training programs in the community.

Matched MeSH terms: Reproducibility of Results
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: Reproducibility of Results

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