Integrated Intelligent Method Based on Fuzzy Logic for Optimizing Laser Microfabrication Processing of GnPs-Improved Alumina Nanocomposites.

Studies on using multifunctional graphene nanostructures to enhance the microfabrication processing of monolithic alumina are still rare and too limited to meet the requirements of green manufacturing criteria. Therefore, this study aims to increase the ablation depth and material removal rate and minimize the roughness of the fabricated microchannel of alumina-based nanocomposites. To achieve this, high-density alumina nanocomposites with different graphene nanoplatelet (GnP) contents (0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.%) were fabricated. Afterward, statistical analysis based on the full factorial design was performed to study the influence of the graphene reinforcement ratio, scanning speed, and frequency on material removal rate (MRR), surface roughness, and ablation depth during low-power laser micromachining. After that, an integrated intelligent multi-objective optimization approach based on the adaptive neuro-fuzzy inference system (ANIFS) and multi-objective particle swarm optimization approach was developed to monitor and find the optimal GnP ratio and microlaser parameters. The results reveal that the GnP reinforcement ratio significantly affects the laser micromachining performance of Al2O3 nanocomposites. This study also revealed that the developed ANFIS models could obtain an accurate estimation model for monitoring the surface roughness, MRR, and ablation depth with fewer errors than 52.07%, 100.15%, and 76% for surface roughness, MRR, and ablation depth, respectively, in comparison with the mathematical models. The integrated intelligent optimization approach indicated that a GnP reinforcement ratio of 2.16, scanning speed of 342 mm/s, and frequency of 20 kHz led to the fabrication of microchannels with high quality and accuracy of Al2O3 nanocomposites. In contrast, the unreinforced alumina could not be machined using the same optimized parameters with low-power laser technology. Henceforth, an integrated intelligence method is a powerful tool for monitoring and optimizing the micromachining processes of ceramic nanocomposites, as demonstrated by the obtained results.

Sustainable Microfabrication Enhancement of Graphene Nanoplatelet-Reinforced Biomedical Alumina Ceramic Matrix Nanocomposites.

Studies about adding graphene reinforcement to improve the microfabrication performance of alumina (Al2O3) ceramic materials are still too rare and incomplete to satisfy sustainable manufacturing requirements. Therefore, this study aims to develop a detailed understanding of the effect of graphene reinforcement to enhance the laser micromachining performance of Al2O3-based nanocomposites. To achieve this, high-density Al2O3 nanocomposite specimens were fabricated with 0 wt.%, 0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.% graphene nanoplatelets (GNPs) using a high-frequency induction heating process. The specimens were subjected to laser micromachining. Afterward, the effects of the GNP contents on the ablation depth/width, surface morphology, surface roughness, and material removal rate were studied. The results indicate that the micro-fabrication performance of the nanocomposites was significantly affected by the GNP content. All nanocomposites exhibited improvement in the ablation depth and material removal rate compared to the base Al2O3 (0 wt.% GNP). For instance, at a higher scanning speed, the ablation depth was increased by a factor of 10 times for the GNP-reinforced specimens compared to the base Al2O3 nanocomposites. In addition, the MRRs were increased by 2134%, 2391%, 2915%, and 2427% for the 0.5 wt.%, 1 wt.%, 1.5 wt.%, and 2.5 wt.% GNP/Al2O3 nanocomposites, respectively, compared to the base Al2O3 specimens. Likewise, the surface roughness and surface morphology were considerably improved for all GNP/Al2O3 nanocomposite specimens compared to the base Al2O3. This is because the GNP reinforcement reduced the ablation threshold and increased the material removal efficiency by increasing the optical absorbance and thermal conductivity and reducing the grain size of the Al2O3 nanocomposites. Among the GNP/Al2O3 nanocomposites, the 0.5 wt.% and 1 wt.% GNP specimens showed superior performance with minimum defects in most laser micromachining conditions. Overall, the results show that the GNP-reinforced Al2O3 nanocomposites can be machined with high quality and a high production rate using a basic fiber laser system (20 Watts) with very low power consumption. This study shows huge potential for adding graphene to alumina ceramic-based materials to improve their machinability.

One- and Two-Sample Predictions Based on Progressively Type-II Censored Carbon Fibres Data Utilizing a Probability Model.

New Weibull-Pareto distribution is a significant and practical continuous lifetime distribution, which plays an important role in reliability engineering and analysis of some physical properties of chemical compounds such as polymers and carbon fibres. In this paper, we construct the predictive interval of unobserved units in the same sample (one sample prediction) and the future sample based on the current sample (two-sample prediction). The used samples are generated from new Weibull-Pareto distribution due to a progressive type-II censoring scheme. Bayesian and maximum likelihood approaches are implemented to the prediction problems. In the Bayesian approach, it is not easy to simplify the predictive posterior density function in a closed form, so we use the generated Markov chain Monte Carlo samples from the Metropolis-Hastings technique with Gibbs sampling. Moreover, the predictive interval of future upper-order statistics is reported. Finally, to demonstrate the proposed methodology, both simulated data and real-life data of carbon fibres examples are considered to show the applicabilities of the proposed methods.

Asymmetric Power Hazard Distribution for COVID-19 Mortality Rate under Adaptive Type-II Progressive Censoring: Theory and Inferences.

This article investigates the estimation of the parameters for power hazard function distribution and some lifetime indices such as reliability function, hazard rate function, and coefficient of variation based on adaptive Type-II progressive censoring. From the perspective of frequentism, we derive the point estimations through the method of maximum likelihood estimation. Besides, delta method is implemented to construct the variances of the reliability characteristics. Markov chain Monte Carlo techniques are proposed to construct the Bayes estimates. To this end, the results of the Bayes estimates are obtained under squared error and linear exponential loss functions. Also, the corresponding credible intervals are constructed. A simulation study is utilized to assay the performance of the proposed methods. Finally, a real data set of COVID-19 mortality rate is analyzed to validate the introduced inference methods.

SPACE FOR COPD delivered as a maintenance programme on pulmonary rehabilitation discharge: protocol of a randomised controlled trial evaluating the long-term effects on exercise tolerance and mental well-being.

INTRODUCTION: The benefits achieved during pulmonary rehabilitation (PR) are known to be sustained for 6-12 months after the initial programme. Several maintenance trials have been conducted but were heterogeneous in terms of duration, frequency and labour cost. There is no consensus on one best strategy. SPACE FOR COPD (Self-management Programme of Activity, Coping and Education for Chronic Obstructive Pulmonary Disease) is a home-based self-management programme, which has been shown previously to be effective in primary and secondary care settings and is to be tested here as a maintenance programme. The aim is to evaluate the efficacy of the SPACE FOR COPD programme (manual and group sessions), on exercise tolerance and mental well-being, compared with usual care following PR in patients with COPD. METHODS AND ANALYSIS: A prospective, multicentre, single-blinded randomised controlled trial requiring 116 participants with a clinical diagnosis of COPD who have finished PR within 4 weeks will be randomised 1:1 to either a usual care group or a SPACE FOR COPD programme group. The intervention comprises a home-based manual and 4, 2-hour group sessions adopting motivational interviewing techniques over 12 months. The primary outcome is endurance capacity measured by the Endurance Shuttle Walking Test at 12 months. Secondary outcomes are: maximal exercise capacity, health-related quality of life, mood, patient activation, physical activity, lung function and healthcare costs. The measures will be taken at baseline, 6 and 12 months. Patient interviews and staff focus groups will be conducted to explore barriers, facilitators and views about the intervention at the end of the study. A framework analysis will be used for the interpretation of qualitative data. ETHICS AND DISSEMINATION: The trial was granted ethical approval from Health Research Authority and Health and Care Research Wales (HCRW19/EM/0267 on 10 October 2019). Results will be made available to all stakeholders through a dissemination event, conferences and peer-reviewed publications. TRIAL REGISTRATION NUMBER: ISRCTN30110012.

Sparse modelling of cancer patients' survival based on genomic copy number alterations.

Copy number alterations (CNA) are structural variation in the genome, in which some regions exhibit more or less than the normal two chromosomal copies. This genomic CNA profile provides critical information in tumour progression and is therefore informative for patients' survival. It is currently a statistical challenge to model patients' survival using their genomic CNA profiles while at the same time identify regions in the genome that are associated with patients' survival. Some methods have been proposed, including Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties. However, these methods do not take the general dependencies between genomic regions into account and produce results that are difficult to interpret. In this paper, we extend the elastic net penalty by introducing additional penalty that takes into account general dependencies between genomic regions. This new model produces smooth parameter estimates while simultaneously performs variable selection via sparse solution. The results indicate that the proposed method shows a better prediction performance than other models in our simulation study, while enabling us to investigate regions in the genome that are associated with the patients' survival with sensible interpretation. We illustrate the method using a real dataset from a lung cancer cohort and simulated data.

Cuff Leak Test and Airway Obstruction in Mechanically Ventilated Intensive Care Unit Patients: A Pilot Randomized Controlled Clinical Trial.

Rationale: Laryngeal edema is a known complication of endotracheal intubation that may cause airway obstruction upon extubation. The only test available to predict this complication is the cuff leak test (CLT). Objectives: Given the uncertainty of the CLT's clinical utility, we conducted the COMIC (Cuff Leak Test and Airway Obstruction in Mechanically Ventilated ICU Patients) pilot study to examine the feasibility of undertaking a larger trial. Methods: COMIC is a multicentered, parallel-group randomized trial performed in Canada, Saudi Arabia, and Poland. We enrolled mechanically ventilated adults admitted to the intensive care unit who were deemed ready for extubation. Those allocated to the intervention arm had the results of their CLT communicated to the healthcare team, who then decided to proceed with extubation or not. In those randomized to the control arm, the CLT results were not communicated to the healthcare team and patients were extubated, regardless of the CLT result. The primary outcomes focused on feasibility. Results: One hundred patients (56 in the intervention and 44 in the control arm) were enrolled. All feasibility criteria were met, including 1) recruitment rate of 7.6 patients/month, 2) consent rate of 88.3% (95% confidence interval [CI], 82.1-94.5%), and 3) protocol adherence of 98% (95% CI, 95-100%). There were two episodes of clinically significant stridor in the intervention group and four patients who required reintubation in each group. Conclusions: The results of the COMIC pilot trial support the feasibility of a larger trial to determine the effect of the CLT on reintubation and clinically important stridor.Clinical trial registered with www.clinicaltrials.gov (NCT03372707).

Machine Learning-Enabled Smart Industrial Automation Systems Using Internet of Things.

Industrial automation uses robotics and software to operate equipment and procedures across industries. Many applications integrate IoT, machine learning, and other technologies to provide smart features that improve the user experience. The use of such technology offers businesses and people tremendous assistance in successfully achieving commercial and noncommercial requirements. Organizations are expected to automate industrial processes owing to the significant risk management and inefficiency of conventional processes. Hence, we developed an elaborative stepwise stacked artificial neural network (ESSANN) algorithm to greatly improve automation industries in controlling and monitoring the industrial environment. Initially, an industrial dataset provided by KLEEMANN Greece was used. The collected data were then preprocessed. Principal component analysis (PCA) was used to extract features, and feature selection was based on least absolute shrinkage and selection operator (LASSO). Subsequently, the ESSANN approach is proposed to improve automation industries. The performance of the proposed algorithm was also examined and compared with that of existing algorithms. The key factors compared with existing technologies are delay, network bandwidth, scalability, computation time, packet loss, operational cost, accuracy, precision, recall, and mean absolute error (MAE). Compared to traditional algorithms for industrial automation, our proposed techniques achieved high results, such as a delay of approximately 52%, network bandwidth accomplished at 97%, scalability attained at 96%, computation time acquired at 59 s, packet loss achieved at a minimum level of approximately 53%, an operational cost of approximately 59%, accuracy of 98%, precision of 98.95%, recall of 95.02%, and MAE of 80%. By analyzing the results, it can be seen that the proposed system was effectively implemented.

Pulmonary rehabilitation for COPD: A narrative review and call for further implementation in Saudi Arabia.

Chronic obstructive pulmonary disease (COPD) is a common, preventable, and treatable condition, in which outcomes can be improved with careful management. Pulmonary rehabilitation (PR) comprises exercise and education, delivered by multidisciplinary teams. PR is a cost-effective management strategy in COPD patients which improves exercise performance, reduces dyspnea, reduces the risk of exacerbation, and improves health-related quality of life. All COPD patients appear to benefit irrespective of their baseline function, and PR has also been shown to be a clinically and cost-effective management approach following an acute exacerbation. COPD patients with greater disability and those recovering postexacerbation should be specifically targeted for PR. Due to limited current capacity, the latter group may not currently be able to benefit from PR. Therefore, there is a need for the wider implementation of PR services in Saudi Arabia, requiring us to address challenges including capacity and workforce competency.

A Statistical Model to Determine the Relationship between Employee Supervisor Characteristics and Overall Satisfaction in Dental Departments in Saudi Arabia.

AIM AND OBJECTIVE: An exploratory study was undertaken to determine the relationship between supervisor characteristics and overall satisfaction with supervisors as perceived by the employees of dental departments in hospitals in Saudi Arabia. MATERIALS AND METHODS: We conducted a survey that included six questions designed to measure the overall performance of a supervisor, as well as questions that were related to specific activities involving interactions between supervisors and employees indental departments of 30 hospitals that were randomly selected. At least 35 employees and one supervisor in each dental department were interviewed. Initially, six questionnaire items were chosen as possible explanatory variables. There are two broad types of variables included in this study. Variables X1 (handles employee complaints), X2 (does not allow for special treatment), and X5 (too critical of poor performance) relate to direct interpersonal relationships, i.e., direct connection between the employee and supervisor, whereas variables X3 (opportunity to learn new things) and X4 (raises based on performance) are of a less personal nature and relate to the job as a whole, i.e., indirect relationship between employees and their supervisor. Variable X6 (rate of advancing to better jobs) is not a direct evaluation of the supervisor, but serves more as a general measure of how the employee perceives his or her own progress in the hospital. RESULTS: Using regression analysis, we observed that only X1 (handles employee complaints) and X3 (opportunity to learn new things) have an impact on response Y (overall rating of job being done by supervisor). There is a strong positive relationship between X1 and Y and also between X3 and Y. CONCLUSION: Therefore, when the supervisor listens and handles employee complaints and gives employees the opportunity to learn new things, the supervisor becomes favorable. CLINICAL SIGNIFICANCE: The relationship between supervisor characteristics and overall satisfaction with supervisors as perceived by the employees of dental departments has not been studied. An understanding of this relationship is valuable to improve employee-supervisor relations, which can improve the overall functioning of hospitals.

Glutamine for prevention and alleviation of radiation-induced oral mucositis in patients with head and neck squamous cell cancer: Systematic review and meta-analysis of controlled trials.

We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) that investigated glutamine efficacy in preventing and alleviating radiation-induced oral mucositis (OM) among patients with head and neck (H&N) cancer. We screened five databases from inception till February 4, 2021 and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We included 11 RCTs, comprising 922 patients (458 and 464 patients were assigned to glutamine and control group, respectively). The incidence and onset of radiation-induced OM of any grade did not substantially differ between both groups. However, glutamine substantially reduced the severity of radiation-induced OM, as reflected by the reduced incidence of severe OM and reduced mean maximal OM grade score. Additionally, glutamine significantly decreased the rates of analgesic opioid use, nasogastric tube feeding, and therapy interruptions. Oral glutamine supplementation demonstrated various therapeutic benefits in preventing and ameliorating radiation-induced OM among patients with H&N cancer.

A bibliometric analysis of the top 100 most-cited articles in the Journal of Oral Pathology & Medicine (1972-2020).

OBJECTIVE: The steady and continued increase of the Journal of Oral Pathology & Medicine's (JOPM) popularity prompted a bibliometric analysis of the journal. The purpose was to assess the significance and effect of the published research articles in the Journal from 1972 and 2020, aiding the identification of landmark articles. We performed a bibliometric analysis using the top 100 cited papers in the Journal of Oral Pathology & Medicine. MATERIALS AND METHODS: An extensive review of the Web of Science was undertaken. Standard information such as author details, affiliated institutions, publication year and the country of origin was recorded. RESULTS: The top 100 cited articles in JOPM were assessed. The maximum and minimum number of citations in the top 100 articles was 1459 and 95, respectively. A total of 16 790 citations were recorded for these 100 articles. Authors were affiliated to 28 different countries, 17 research articles from the UK and 12 from the USA. Other countries furnished seven or fewer articles. CONCLUSION: This bibliometric analysis provides a synopsis of research published in the journal over a 48-year period. Recent interest in the journal shows a healthy increase in submissions and profile.

Prediction of tumour pathological subtype from genomic profile using sparse logistic regression with random effects.

The purpose of this study is to highlight the application of sparse logistic regression models in dealing with prediction of tumour pathological subtypes based on lung cancer patients' genomic information. We consider sparse logistic regression models to deal with the high dimensionality and correlation between genomic regions. In a hierarchical likelihood (HL) method, it is assumed that the random effects follow a normal distribution and its variance is assumed to follow a gamma distribution. This formulation considers ridge and lasso penalties as special cases. We extend the HL penalty to include a ridge penalty (called 'HLnet') in a similar principle of the elastic net penalty, which is constructed from lasso penalty. The results indicate that the HL penalty creates more sparse estimates than lasso penalty with comparable prediction performance, while HLnet and elastic net penalties have the best prediction performance in real data. We illustrate the methods in a lung cancer study.

A bibliometric analysis of the 100 most cited articles on early childhood caries.

BACKGROUND: Bibliometric analysis aids to quantify the research prolificacy. The citation count acquired by a scientific article is one of the measures of its influence within a field. AIM: To employ bibliometrics to offer a quantitative-qualitative analysis of publications on early childhood caries (ECC) published between 1950 and 2019. DESIGN: Two researchers independently read all the titles and abstracts of articles retrieved from Scopus database on 16 October 2019. The articles were categorized according to citation and study characteristics. Collaboration network amongst authors, countries, and keywords were generated using VOSviewer software. RESULTS: Amongst a total of 10 578 articles published on ECC, 100 most cited articles were sorted. The top-cited articles appeared in 34 journals, with Community Dentistry and Oral Epidemiology journal (n = 18) contributing maximum number of articles. The papers originated from 25 countries, with the United States (n = 54) accounting for largest number. Amid the papers with high levels of evidence, 11 were systematic reviews and 8 were randomized clinical trials. The topic most commonly addressed was aetiology/associated factors (63%). Amongst a total of 990 keywords, 'dental caries' appeared 89 times. CONCLUSION: The findings of this paper will help researchers, academicians, and students for appropriate article referrals for evidence-based clinical decision-making.