Acceptability of extending HPV-based cervical screening intervals from 3 to 5 years: An interview study with women in England

Objectives: The introduction of primary HPV testing in the NHS Cervical Screening Programme in England means the screening interval for 25-49-year-olds can be extended from 3 to 5 years. We explored womens responses to the proposed interval extension. Methods: We conducted semi-structured phone/video interviews with 22 women aged 25-49 years. Participants were selected to vary in age, socioeconomics, and screening history. We explored attitudes to the current 3-year interval, then acceptability of a 5-year interval. Interviews were transcribed verbatim and analysed using Framework Analysis. Results: Attitudes to the current 3-year interval varied; some wanted more frequent screening, believing cancer develops quickly. Some participants worried about the proposed change; others trusted it was evidence-based. Frequent questions concerned the rationale and safety of longer intervals, speed of cancer development, the possibility of HPV being missed or cell changes occurring between screens. Many participants felt reassured when the interval change was explained alongside the move to HPV primary screening, of which most had previously been unaware. Conclusions: Communication of the interval change should be done in the context of broader information about HPV primary screening, emphasising that people who test negative for HPV are at lower risk of cell changes so can safely be screened every 5 years. The long time needed for HPV to develop into cervical cancer provides reassurance about safety, but it is important to be transparent that no screening test is perfect.

A new method for solving interval and fuzzy quadratic equations of dual form

In this paper, we present a numerical method for solving a quadratic interval equation in its dual form. The method is based on the generalized procedure of interval extension called” interval extended zero” method. It is shown that the solution of interval quadratic equation based on the proposed method may be naturally treated as a fuzzy number. An important advantage of the proposed method is that it substantially decreases the excess width defect. Several numerical examples are included to demonstrate the applicability and validity of the proposed method.

The Multi-Attributive Border Approximation Area Comparison (Mabac) Method for Decision Making under Interval-Valued Fermatean Fuzzy Environment for Green Supplier Selection

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

Predictive Asset Analytics: The Future of Maintenance

Major Overhauls (MOH) of major Rotating Equipment is an essential activity to ensure equipment and overall plant's productivity and reliability requirements are met. This submission summarizes Maintenance cost reduction and MOH extension benefits on an integrally geared centrifugal Instrument Air (IA) compressor through a first of its kind Predictive Maintenance (PdM) solution project in ADNOC. Appropriate planning for Major Overhauls (MOH) in accordance with OEM, company standards and international best practices are crucial steps. Digitalization continues to transform the industry, with enhancements to maintenance practices a fundamental aspect. Centralized Predictive Analytics & Diagnostics (CPAD) project is a first of its kind in ADNOC as it ventures into on one of the largest predictive maintenance projects in the oil & gas industry. CPAD enables Predictive Maintenance (PdM) through Advanced Pattern Recognition (APR) and Machine Learning (ML) technologies to effectively monitor & assess equipment performance and overall healthiness. Equipment performance is continuously assessed through the developed asset management predictive analytics tool. Through this tool, models associated with the equipment were evaluated to detect performance deviation from historical normal operating behavior. Any deviation from the historical norm would be flagged to indicate condition degradation and/or performance drop. Moreover, the software is configured to alert for subtle changes in the system behavior that are often an early warning sign of failure. This allows for early troubleshooting, planning and appropriate intervention by maintenance teams. Using the predictive analytics software solution, an MOH interval extension was implemented for an integrally geared centrifugal IA compressor installed at an ADNOC Gas Processing site. The compressor was due for MOH at its traditional fixed maintenance interval of 40,000 running hours in Nov 2019. Through this approach, the actual performance and condition of the compressor was assessed. Its process and equipment parameters (i.e. casing vibrations, bearing vibrations, bearing temperatures and lube oil supply temperature/pressure, etc.) were reviewed, which did not flag any abnormality. The compressor's performance had not deviated from the historical norm; indicating that the equipment was in a healthy condition and had no signs of performance degradation. With this insight, a 15 months extension of the MOH was achieved. Furthermore, a 30% maintenance cost reduction throughout the compressor's life cycle is projected while ensuring equipment's reliability and integrity are upheld. A total of 7 days maintenance down time including work force and materials planning for the MOH activities was deferred. The equipment remained in operation until its rescheduled date for MOH. Through the deployment of predictive analytics solutions, informed decisions can be made by maintenance professionals to challenge traditional maintenance practices, increase Mean Time Between Overhauls (MBTO), realize the full potential of a plant's process & utilities machinery and optimize operational costs of plant assets.

Based-restraining interval extension improved truncation algorithm for response analysis of uncertain mechanical systems

Purpose This study aims to propose an improved affine interval truncation algorithm to restrain interval extension for interval function. Design/methodology/approach To reduce the occurrence times of related variables in interval function, the processing method of interval operation sequence is proposed. Findings The interval variable is evenly divided into several subintervals based on correlation analysis of interval variables. The interval function value is modified by the interval truncation method to restrain larger estimation of interval operation results. Originality/value Through several uncertain displacement response engineering examples, the effectiveness and applicability of the proposed algorithm are verified by comparing with interval method and optimization algorithm.

Disease stability and extended dosing under anti-VEGF treatment of exudative age-related macular degeneration (AMD) — a meta-analysis

Purpose To assess disease stability (absence of intra- and/or subretinal fluid) and the portion of eyes being capable to extend their treatment interval to ≥ 12 weeks in exudative age-related macular degeneration (AMD). Methods A systematic literature search was performed in NCBI, PubMed, CENTRAL, and ClinicalTrials.gov to identify clinical studies reporting treatment outcomes for ranibizumab, aflibercept, and brolucizumab in exudative AMD under a treat-and-extend protocol and a follow-up of ≥ 12 months. Weighted mean differences and subgroup comparisons were used to integrate the different studies. Results This meta-analysis refers to 29 published series, including 27 independent samples and 5629 patients. In the pooled group, disease stability was reported in 62.9% and 56.0%, respectively, after 12 and 24 months of treatment, whereas treatment intervals were extended to ≥ 12 weeks in 37.7% and 42.6%, respectively. Ranibizumab, aflibercept, and brolucizumab differed regarding their potential to achieve disease stability (56.3%, 64.5%, and 71.5% after 12, and 50.0%, 52.7% and 75.7% after 24 months; p = < 0.001) and to allow an interval extension to ≥ 12 weeks (28.6%, 34.2%, and 53.3% after 12, and 34.2%, 47.7%, and 41.7% after 24 months; p = < 0.001). Conclusion The portion of eyes achieving disease stability regressed in the second year, whereas the portion of eyes under a ≥ 12-week interval increased. This discrepancy may reflect the challenges in balancing between under-treatment and a reduced treatment burden.

Interval analysis-based Bi-iterative algorithm for robust TDOA-FDOA moving source localisation

In this study, an interval extension method of a bi-iterative is proposed to determine a moving source. This method is developed by utilising the time difference of arrival and frequency difference of arrival measurements of a signals received from several receivers. Unlike the standard Gaussian noise model, the time difference of arrival - frequency difference of arrival measurements are obtained by interval enclosing, which avoids convergence and initialisation problems in the conventional Taylor-series method. Using the bi-iterative strategy, the algorithm can alternately calculate the position and velocity of the moving source in interval vector form. Simulation results indicate that the proposed scheme significantly outperforms other methods, and approaches the Cramer-Rao lower bound at a sufficiently high noise level before the threshold effect occurs. Moreover, the interval widths of the results provide the confidence degree of the estimate.