Displaying publications 81 - 100 of 309 in total

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  1. Khan AS, Ur Rehman S, Ahmad S, AlMaimouni YK, Alzamil MAS, Dummer PMH
    Int Endod J, 2021 Oct;54(10):1819-1839.
    PMID: 34196006 DOI: 10.1111/iej.13595
    AIM: The International Endodontic Journal (IEJ) has served as a platform for research and clinical practice in Endodontics since 1967. This study provides a bibliographic analysis and overview of the publications that have appeared in the IEJ from 1967 to 2020.

    METHODOLOGY: A literature search was performed in Elsevier's Scopus database to locate all the publications of the International Endodontic Journal. Various bibliometric software packages including the open-source visualization software Gephi and Biblioshiny (version 2.0) were employed for data visualization and analysis.

    RESULTS: A total of 3739 records with citation and bibliographic details were selected and retrieved to allow a bibliometric analysis to be performed. The bibliometric analysis indicates that the IEJ has grown both in terms of productivity and influence. Over time, the journal has been associated with an increase in the number of manuscripts published and the citations they have attracted, but with minor downward fluctuations in citations in the last few years. Bibliographic coupling of the IEJ articles revealed that the major research themes published in the journal include 'endodontics', 'root canal treatment', 'calcium hydroxide', 'apical periodontitis', 'mineral trioxide aggregate', 'microbiology', 'cyclic fatigue', 'cone-beam computed tomography' and 'micro-computed tomography'. Authors affiliated to institutions in the UK were the major contributors to the journal and were linked with other countries such as Brazil, USA and Malaysia. The largest number of publications were from the University of São Paulo, Brazil.

    CONCLUSION: The IEJ is one of the leading journals in Endodontology and has been providing a platform for innovative research and clinical reports for more than 50 years. Publications have been associated with a wide range of authors, institutions and countries around the world.

    Matched MeSH terms: Databases, Factual
  2. Ahmad P, Elgamal HAM
    J Endod, 2020 Aug;46(8):1042-1051.
    PMID: 32417289 DOI: 10.1016/j.joen.2020.04.014
    INTRODUCTION: Bibliometric analysis is the quantitative measure of the impact of a scientific article in its respective field of research. The aim of this study was to identify and analyze the main features of the top 50 most cited articles published in the Journal of Endodontics since its inception as well as the top 50 most downloaded articles in 2017 and 2018 in order to evaluate the changing trends and other bibliometric parameters of the contemporary literature compared with the classic literature.

    METHODS: An electronic search was conducted on the Clarivate Analytics Web of Science "All Databases" to identify and analyze the top 50 most frequently cited scientific articles. After ranking the articles in a descending order based on their citation counts, each article was then crossmatched with the citation counts in Scopus, Google Scholar, and PubMed.

    RESULTS: The citation counts of the 50 selected most cited articles ranged between 218 and 731 (Clarivate Analytics Web of Science). The years in which most top 50 articles were published were 2004 and 2008 (n = 5). Among 131 authors, the greatest contribution was made by M. Torabinejad (n = 14). Most of the articles originated from the United States (n = 38) with the greatest contributions from the School of Dentistry, Loma Linda University, Loma Linda, CA (n = 15). Basic research-technology was the most frequent study design (n = 18). A negative, significant correlation occurred between citation density and publication age (correlation coefficient = -0.708, P < .01).

    CONCLUSIONS: Several interesting differences were found between the main characteristics of the most cited articles and the most downloaded articles.

    Matched MeSH terms: Databases, Factual
  3. Chew KT, Raman V, Then PHH
    Sensors (Basel), 2021 Dec 08;21(24).
    PMID: 34960291 DOI: 10.3390/s21248197
    Cardiovascular disease continues to be one of the most prevalent medical conditions in modern society, especially among elderly citizens. As the leading cause of deaths worldwide, further improvements to the early detection and prevention of these cardiovascular diseases is of the utmost importance for reducing the death toll. In particular, the remote and continuous monitoring of vital signs such as electrocardiograms are critical for improving the detection rates and speed of abnormalities while improving accessibility for elderly individuals. In this paper, we consider the design and deployment characteristics of a remote patient monitoring system for arrhythmia detection in elderly individuals. Thus, we developed a scalable system architecture to support remote streaming of ECG signals at near real-time. Additionally, a two-phase classification scheme is proposed to improve the performance of existing ECG classification algorithms. A prototype of the system was deployed at the Sarawak General Hospital, remotely collecting data from 27 unique patients. Evaluations indicate that the two-phase classification scheme improves algorithm performance when applied to the MIT-BIH Arrhythmia Database and the remotely collected single-lead ECG recordings.
    Matched MeSH terms: Databases, Factual
  4. Irfan M, Razzaq A, Suksatan W, Sharif A, Madurai Elavarasan R, Yang C, et al.
    J Therm Biol, 2022 Feb;104:103101.
    PMID: 35180949 DOI: 10.1016/j.jtherbio.2021.103101
    The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.
    Matched MeSH terms: Databases, Factual
  5. Altalib MK, Salim N
    Biomolecules, 2022 Nov 20;12(11).
    PMID: 36421733 DOI: 10.3390/biom12111719
    Information technology has become an integral aspect of the drug development process. The virtual screening process (VS) is a computational technique for screening chemical compounds in a reasonable amount of time and cost. The similarity search is one of the primary tasks in VS that estimates a molecule's similarity. It is predicated on the idea that molecules with similar structures may also have similar activities. Many techniques for comparing the biological similarity between a target compound and each compound in the database have been established. Although the approaches have a strong performance, particularly when dealing with molecules with homogenous active structural, they are not enough good when dealing with structurally heterogeneous compounds. The previous works examined many deep learning methods in the enhanced Siamese similarity model and demonstrated that the Enhanced Siamese Multi-Layer Perceptron similarity model (SMLP) and the Siamese Convolutional Neural Network-one dimension similarity model (SCNN1D) have good outcomes when dealing with structurally heterogeneous molecules. To further improve the retrieval effectiveness of the similarity model, we incorporate the best two models in one hybrid model. The reason is that each method gives good results in some classes, so combining them in one hybrid model may improve the retrieval recall. Many designs of the hybrid models will be tested in this study. Several experiments on real-world data sets were conducted, and the findings demonstrated that the new approaches outperformed the previous method.
    Matched MeSH terms: Databases, Factual
  6. Barua PD, Baygin N, Dogan S, Baygin M, Arunkumar N, Fujita H, et al.
    Sci Rep, 2022 Oct 14;12(1):17297.
    PMID: 36241674 DOI: 10.1038/s41598-022-21380-4
    Pain intensity classification using facial images is a challenging problem in computer vision research. This work proposed a patch and transfer learning-based model to classify various pain intensities using facial images. The input facial images were segmented into dynamic-sized horizontal patches or "shutter blinds". A lightweight deep network DarkNet19 pre-trained on ImageNet1K was used to generate deep features from the shutter blinds and the undivided resized segmented input facial image. The most discriminative features were selected from these deep features using iterative neighborhood component analysis, which were then fed to a standard shallow fine k-nearest neighbor classifier for classification using tenfold cross-validation. The proposed shutter blinds-based model was trained and tested on datasets derived from two public databases-University of Northern British Columbia-McMaster Shoulder Pain Expression Archive Database and Denver Intensity of Spontaneous Facial Action Database-which both comprised four pain intensity classes that had been labeled by human experts using validated facial action coding system methodology. Our shutter blinds-based classification model attained more than 95% overall accuracy rates on both datasets. The excellent performance suggests that the automated pain intensity classification model can be deployed to assist doctors in the non-verbal detection of pain using facial images in various situations (e.g., non-communicative patients or during surgery). This system can facilitate timely detection and management of pain.
    Matched MeSH terms: Databases, Factual
  7. Anuar A, Marwan NF, Smith J, Siriyanun S, Sharif A
    Environ Sci Pollut Res Int, 2022 Feb;29(9):13729-13741.
    PMID: 34599441 DOI: 10.1007/s11356-021-16470-1
    The aim of this paper is to examine immigration and environmental degradation using bibliometric analysis. This paper also analyzes sources of publication, authorship, citations, distributions publications and other bibliometric indicators. The study focuses on a total of 1372 articles published from 2000 to 2020. These articles were collected through an automated process from the Scopus database and later analyzed using techniques such as bibliometric indicators analysis, VOSviewer, and Perish or Publish. The research identified 991 articles from varieties of published sources. The topic of immigrants and environmental degradation has been an emerging topic since 1981. Starting in 2000, most of the scholars actively producing an articles pertinent to this topic. Most of the articles were published in journals, and English is the primary language of research. United States is the leading country in contributing the publications. Meanwhile, the most significant fields in which the sources were produced were environmental science, agricultural and biological sciences, arts and humanities and earth and planetary sciences. However, some limitations has been found. It has been suggested for future research, to lengthen this work to other databases, as well as bibliometric analyses of immigration and environmental degradation in developed and developing countries by adding a new keyword such as energy consumption and climate change. This paper aims to assess recent trends in the expansion of academic literature on immigration and environmental degradation using the bibliometric analysis method. Network visualization and bibliometric indicators are used in this paper to present the results.
    Matched MeSH terms: Databases, Factual
  8. Delavaux CS, Crowther TW, Zohner CM, Robmann NM, Lauber T, van den Hoogen J, et al.
    Nature, 2023 Sep;621(7980):773-781.
    PMID: 37612513 DOI: 10.1038/s41586-023-06440-7
    Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.
    Matched MeSH terms: Databases, Factual
  9. Md Zamri ASS, Saruddin MZ, Harun A, Abd Aziz SF, Aizad Za'bah AK, Dapari R, et al.
    PLoS One, 2023;18(6):e0287040.
    PMID: 37307252 DOI: 10.1371/journal.pone.0287040
    INTRODUCTION: Occupational asthma (OA) is a type of Work-Related Asthma characterised by variable airflow limitation and/or inflammation due to causes and conditions attributable to a particular occupational environment, and not to stimuli encountered outside the workplace. There is an increasing need to extend the depth of knowledge of OA to better manage this condition, especially among food industry workers who are affected by it.

    OBJECTIVE: This systematic review aimed to determine the factors associated with occupational asthma among food industry workers by electronically collecting articles from two databases (Medline and Scopus).

    METHODS: This systematic review was prepared in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analyses) updated guideline. Two independent reviewers screened the titles and abstracts of the collected data, which were then stored in Endnote20 based on the inclusion and exclusion criteria. The included articles have been critically appraised to assess the quality of the studies using the Mixed Methods Appraisal Tool (MMAT).

    RESULT: The search yielded 82 articles from Medline and 85 from SCOPUS, resulting in 167 unique hits. Only 22 articles have been included in the full-text assessment following a rigorous selection screening. Of the 22 articles identified, five were included in the final review. Several factors were found to have contributed to occupational asthma among food industry workers. They were classified into two categories: (1) work environment-related factors; and (2) individual factors.

    CONCLUSION: Several work environment and individual-related factors were found to be associated with OA among food industry workers. A better understanding of the development of the disease and its potential risk factors is needed because it can affect worker's quality of life. Pre-employment and periodic medical surveillance should be conducted to assess and detect any possible risk of developing occupational asthma among workers.

    Matched MeSH terms: Databases, Factual
  10. Zara J, Nordin SM, Isha ASN
    Front Public Health, 2023;11:1225995.
    PMID: 37614453 DOI: 10.3389/fpubh.2023.1225995
    Health, safety, and environment (HSE) are critical aspects of any industry, particularly in high-risk environments, such as the oil and gas industry. Continuous accident reports indicate the requirement for the effective implementation of safety rules, regulations, and practices. This systematic literature review examines the relationship between safety communication and safety commitment in high-risk workplaces, specifically focusing on the oil and gas industry. The review comprises 1,439 articles from 2004 to 2023, retrieved from the Scopus and Web of Science databases following the PRISMA comprehensive guidelines. This study considers safety communication, communication climate, and communication satisfaction to evaluate their influence on safety commitment under occupational health and safety. This study identifies safety commitment issues and their underlying factors, discussing measures for preventing and reducing accidents and incidents and highlighting preventive measures for future research. It also signifies the variables influencing accident and incident rates. The research underscores the importance of communication dimensions and the need for workers to possess adequate skills, knowledge, and attitudes regarding occupational safety and health procedures. Moreover, the study contributes to the industrial and academic domains by improving organizational safety commitment, promoting a safety culture, and developing effective communication strategies. Furthermore, practitioners may benefit from this comprehensive overview in developing, evaluating, and enhancing occupational safety.
    Matched MeSH terms: Databases, Factual
  11. Mansor N, Awang H, Amuthavalli Thiyagarajan J, Mikton C, Diaz T
    Age Ageing, 2023 Oct 28;52(Suppl 4):iv118-iv132.
    PMID: 37902520 DOI: 10.1093/ageing/afad101
    OBJECTIVE: this study aims to conduct a systematic review on available instruments for measuring older persons' ability to learn, grow and make decisions and to critically review the measurement properties of the identified instruments.

    METHODS: we searched six electronic databases, which include PubMed, Embase, PsycINFO, SciELO, ERIC and AgeLine, between January 2000 and April 2022. Reference lists of the included papers were also manually searched. The COSMIN (CONsensus-based Standards for the selection of health Measurement Instruments) guidelines were used to evaluate the measurement properties and the quality of evidence for each instrument.

    RESULTS: 13 instruments from 29 studies were included for evaluation of their measurement properties. Of the 13 reviewed, 6 were on the ability to learn, 3 were on the ability to grow and 4 were on the ability to make decisions. The review found no single instrument that measured all three constructs in unidimensional or multidimensional scales. Many of the instruments were found to have sufficient overall rating on content validity, structural validity, internal consistency and cross-cultural validity. The quality of evidence was rated as low due to a limited number of related validation studies.

    CONCLUSION: a few existing instruments to assess the ability to learn, grow and make decisions of older people can be identified in the literature. Further research is needed in validating them against functional, real-world outcomes.

    Matched MeSH terms: Databases, Factual
  12. Ramanjot, Mittal U, Wadhawan A, Singla J, Jhanjhi NZ, Ghoniem RM, et al.
    Sensors (Basel), 2023 May 15;23(10).
    PMID: 37430683 DOI: 10.3390/s23104769
    A significant majority of the population in India makes their living through agriculture. Different illnesses that develop due to changing weather patterns and are caused by pathogenic organisms impact the yields of diverse plant species. The present article analyzed some of the existing techniques in terms of data sources, pre-processing techniques, feature extraction techniques, data augmentation techniques, models utilized for detecting and classifying diseases that affect the plant, how the quality of images was enhanced, how overfitting of the model was reduced, and accuracy. The research papers for this study were selected using various keywords from peer-reviewed publications from various databases published between 2010 and 2022. A total of 182 papers were identified and reviewed for their direct relevance to plant disease detection and classification, of which 75 papers were selected for this review after exclusion based on the title, abstract, conclusion, and full text. Researchers will find this work to be a useful resource in recognizing the potential of various existing techniques through data-driven approaches while identifying plant diseases by enhancing system performance and accuracy.
    Matched MeSH terms: Databases, Factual
  13. Mahdi SS, Jafri HA, Allana R, Battineni G, Khawaja M, Sakina S, et al.
    BMC Emerg Med, 2023 May 24;23(1):52.
    PMID: 37226121 DOI: 10.1186/s12873-023-00824-8
    INTRODUCTION: The simulation exercise (SimEx) simulates an emergency in which an elaboration or description of the response is applied. The purpose of these exercises is to validate and improve plans, procedures, and systems for responding to all hazards. The purpose of this study was to review disaster preparation exercises conducted by various national, non-government, and academic institutions.

    METHODOLOGY: Several databases, including PubMed (Medline), Cumulative Index to Nursing and Allied Health Literature (CINAHL), BioMed Central, and Google Scholar, were used to review the literature. Information was retrieved using Medical Subject Headings (MeSH) and documents were selected according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). To assess the quality of the selected articles, the Newcastle-Ottawa Scale (NOS) technique was utilized.

    RESULTS: A total of 29 papers were selected for final review based on PRISMA guidelines and the NOS quality assessment. Studies have shown that many forms of SimEx commonly used in disaster management including tabletop exercises, functional exercises, and full-scale exercises have their benefits and limitations. There is no doubt that SimEx is an excellent tool for improving disaster planning and response. It is still necessary to give SimEx programs a more rigorous evaluation and to standardize the processes more thoroughly.

    CONCLUSIONS: Drills and training can be improved for disaster management, which will enable medical professionals to face the challenges of disaster management in the 21st century.

    Matched MeSH terms: Databases, Factual
  14. Hamzah N, Malim NHAH, Abdullah JM, Sumari P, Mokhtar AM, Rosli SNS, et al.
    Neuroinformatics, 2023 Jul;21(3):589-600.
    PMID: 37344699 DOI: 10.1007/s12021-023-09637-3
    The sharing of open-access neuroimaging data has increased significantly during the last few years. Sharing neuroimaging data is crucial to accelerating scientific advancement, particularly in the field of neuroscience. A number of big initiatives that will increase the amount of available neuroimaging data are currently in development. The Big Brain Data Initiative project was started by Universiti Sains Malaysia as the first neuroimaging data repository platform in Malaysia for the purpose of data sharing. In order to ensure that the neuroimaging data in this project is accessible, usable, and secure, as well as to offer users high-quality data that can be consistently accessed, we first came up with good data stewardship practices. Then, we developed MyneuroDB, an online repository database system for data sharing purposes. Here, we describe the Big Brain Data Initiative and MyneuroDB, a data repository that provides the ability to openly share neuroimaging data, currently including magnetic resonance imaging (MRI), electroencephalography (EEG), and magnetoencephalography (MEG), following the FAIR principles for data sharing.
    Matched MeSH terms: Databases, Factual
  15. Hui BSM, Zhi LR, Retinasamy T, Arulsamy A, Law CSW, Shaikh MF, et al.
    J Alzheimers Dis, 2023;94(s1):S45-S66.
    PMID: 36776068 DOI: 10.3233/JAD-221081
    BACKGROUND: Neurodegenerative diseases (NDs) impose significant financial and healthcare burden on populations all over the world. The prevalence and incidence of NDs have been observed to increase dramatically with age. Hence, the number of reported cases is projected to increase in the future, as life spans continues to rise. Despite this, there is limited effective treatment against most NDs. Interferons (IFNs), a family of cytokines, have been suggested as a promising therapeutic target for NDs, particularly IFN-α, which governs various pathological pathways in different NDs.

    OBJECTIVE: This systematic review aimed to critically appraise the currently available literature on the pathological role of IFN-α in neurodegeneration/NDs.

    METHODS: Three databases, Scopus, PubMed, and Ovid Medline, were utilized for the literature search.

    RESULTS: A total of 77 journal articles were selected for critical evaluation, based on the inclusion and exclusion criteria. The studies selected and elucidated in this current systematic review have showed that IFN-α may play a deleterious role in neurodegenerative diseases through its strong association with the inflammatory processes resulting in mainly neurocognitive impairments. IFN-α may be displaying its neurotoxic function via various mechanisms such as abnormal calcium mineralization, activation of STAT1-dependent mechanisms, and increased quinolinic acid production.

    CONCLUSION: The exact role IFN-α in these neurodegenerative diseases have yet to be determine due to a lack in more recent evidence, thereby creating a variability in the role of IFN-α. Future investigations should thus be conducted, so that the role played by IFN-α in neurodegenerative diseases could be delineated.

    Matched MeSH terms: Databases, Factual
  16. Rahmat RF, Andreas TSM, Fahmi F, Pasha MF, Alzahrani MY, Budiarto R
    J Healthc Eng, 2019;2019:5810540.
    PMID: 31316743 DOI: 10.1155/2019/5810540
    Compression, in general, aims to reduce file size, with or without decreasing data quality of the original file. Digital Imaging and Communication in Medicine (DICOM) is a medical imaging file standard used to store multiple information such as patient data, imaging procedures, and the image itself. With the rising usage of medical imaging in clinical diagnosis, there is a need for a fast and secure method to share large number of medical images between healthcare practitioners, and compression has always been an option. This work analyses the Huffman coding compression method, one of the lossless compression techniques, as an alternative method to compress a DICOM file in open PACS settings. The idea of the Huffman coding compression method is to provide codeword with less number of bits for the symbol that has a higher value of byte frequency distribution. Experiments using different type of DICOM images are conducted, and the analysis on the performances in terms of compression ratio and compression/decompression time, as well as security, is provided. The experimental results showed that the Huffman coding technique has the capability to compress the DICOM file up to 1 : 3.7010 ratio and up to 72.98% space savings.
    Matched MeSH terms: Databases, Factual
  17. Thangaveloo A, Dorasamy M, Bin Ahmad AA, Marimuthu SB, Jayabalan J
    F1000Res, 2022;11:144.
    PMID: 38434005 DOI: 10.12688/f1000research.73317.2
    Background: The confidence of Bottom 40 (B40) shareholders is crucial for cooperative's sustenance within wider corporate governance. An in-depth study on cooperatives is needed, as they play a crucial role in the Malaysian economic system and contribute greatly to the country's social development. However, in the current landscape, confidence among shareholders is at stake. This study aims to identify the research gap into corporate governance for cooperativess in relation to B40 shareholder confidence, as well as identify current study challenges and develop a conceptual framework for future research. Methods: We conducted a systematic literature review, with the use of agency theory to assess shareholders' confidence. Emerald, ProQuest, InderScience, Scopus and Science Direct were the online databases used in this study to search five keyword phrases: corporate governance, confidence, cooperative, agency theory and Bottom 40% (B40) household. Tranfield's five stages were used to conduct the systematic review. Results: Only 5 of the 324 studies assess shareholders' confidence in cooperatives, as well as one paper on B40 and two papers on agency theory. Our review presents three major findings. First, research in the context of B40 shareholder's confidence in cooperatives is scarce. Second, the challenges related to shareholders' confidence in B40 are major issues in the context. Third, research on agency theory in the context of shareholders' confidence within cooperatives and corporate governance is still scant. Conclusions: This review urges the research community to conduct more studies based on the highlighted research gaps.
    Matched MeSH terms: Databases, Factual
  18. Wang L, Md Sani N
    Health Place, 2024 Jan;85:103168.
    PMID: 38211359 DOI: 10.1016/j.healthplace.2023.103168
    Research on natural health has identified the potential benefit of outdoor blue spaces for human health and wellbeing. However, the existing evidence has relatively limited attention to the elderly. This study aims to review the available evidence on outdoor blue spaces and health outcomes among older individuals and identify knowledge gaps. In accordance with the PRISMA guidelines, specific keywords were used to search for articles published in English from inception to October 2023. Five databases (Scopus, PubMed, Web of Science, CINAHL, and PsycINFO) were searched, and 22 studies were identified in this review. We classified articles based on elderly health as general health (e.g., self-reported, perceived health and wellbeing), physical health (e.g., physical activity, physical function index), and mental health and wellbeing (e.g., depression). The findings indicated a positive correlation between outdoor blue space and the health of the elderly. In terms of the characteristics of exposure to outdoor blue spaces, direct contact (e.g., sensory-based) has not been well documented compared to indirect contact (e.g., distance, percentage, region-based). Although encouraging, the available body of evidence is limited and lacks consistency. Future research is needed to provide complementary evidence between outdoor blue spaces and elderly health.
    Matched MeSH terms: Databases, Factual
  19. Alhajj MN, Halboub E, Yacob N, Al-Maweri SA, Ahmad SF, Celebić A, et al.
    BMC Oral Health, 2024 Mar 04;24(1):303.
    PMID: 38439020 DOI: 10.1186/s12903-024-04083-2
    BACKGROUND: The present systematic review and meta-analysis investigated the available evidence about the adherence of Candida Albicans to the digitally-fabricated acrylic resins (both milled and 3D-printed) compared to the conventional heat-polymerized acrylic resins.

    METHODS: This study followed the guidelines of the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA). A comprehensive search of online databases/search tools (Web of Science, Scopus, PubMed, Ovid, and Google Scholar) was conducted for all relevant studies published up until May 29, 2023. Only in-vitro studies comparing the adherence of Candida albicans to the digital and conventional acrylic resins were included. The quantitative analyses were performed using RevMan v5.3 software.

    RESULTS: Fourteen studies were included, 11 of which were meta-analyzed based on Colony Forming Unit (CFU) and Optical Density (OD) outcome measures. The pooled data revealed significantly lower candida colonization on the milled digitally-fabricated compared to the heat-polymerized conventionally-fabricated acrylic resin materials (MD = - 0.36; 95%CI = - 0.69, - 0.03; P = 0.03 and MD = - 0.04; 95%CI = - 0.06, - 0.01; P = 0.0008; as measured by CFU and OD respectively). However, no differences were found in the adhesion of Candida albicans between the 3D-printed digitally-fabricated compared to the heat-polymerized conventionally-fabricated acrylic resin materials (CFU: P = 0.11, and OD: P = 0.20).

    CONCLUSION: The available evidence suggests that candida is less likely to adhere to the milled digitally-fabricated acrylic resins compared to the conventional ones.

    Matched MeSH terms: Databases, Factual
  20. Aqra I, Herawan T, Abdul Ghani N, Akhunzada A, Ali A, Bin Razali R, et al.
    PLoS One, 2018;13(1):e0179703.
    PMID: 29351287 DOI: 10.1371/journal.pone.0179703
    Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets.
    Matched MeSH terms: Databases, Factual
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