Test Plan Research Articles

Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning

Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set while reducing computational costs. A predetermined number of RGRs is selected using an integrated unsupervised machine learning (UML) framework, which includes Euclidean distance measurement, multidimensional scaling (MDS), and a deterministic K-means (DK-means) clustering algorithm. In the context of the intricate 3D aquifer CO2 storage model, PUNQ-S3, these algorithms are utilized. The UML methodology selects five RGRs from a pool of 25 possibilities (20% of the total), taking into account the reservoir quality index (RQI) as a static parameter of the reservoir. To determine the credibility of these RGRs, their simulation results are scrutinized through the application of the Kolmogorov–Smirnov (KS) test, which analyzes the distribution of the output. In this assessment, 40 CO2 injection wells cover the entire reservoir alongside the full set. The end-point simulation results indicate that the CO2 structural, residual, and solubility trapping within the RGRs and full set follow the same distribution. Simulating five RGRs alongside the full set of 25 GRs over 200 years, involving 10 years of CO2 injection, reveals consistently similar trapping distribution patterns, with an average value of Dmax of 0.21 remaining lower than Dcritical (0.66). Using this methodology, computational expenses related to scenario testing and development planning for CO2 storage reservoirs in the presence of geological uncertainties can be substantially reduced.

Curvilinear Approach to Landing

ABSTRACT The article describes the problem of controlling an aircraft control when performing a landing on a curvilinear trajectory. The adoption of a curvilinear approach trajectory allows reducing the impact of air traffic on the areas adjacent to the airport. Performing the correct approach on the curvilinear path requires support. For the correct execution of the landing manoeuvre on the curvilinear track, it is necessary to establish reference points so that the repeatability of the manoeuvre is ensured, especially in the case of landing more than one aircraft at the same time. In the following parts, the landing control system is presented. Particularly carefully presented is the issue of performing tests of the designed control system, which in the case of the aircraft control system during the approach to landing must be extremely thoroughly verified. The test plan included both verification the correctness of the adopted control laws and their robustness to interference occurring as a result of atmospheric air streams.

The Development of Specific Training Programs to Improve the Speed, Agility, Quickness, and Pass-Receiving Performance of Soccer Players

Background and Aim: In the field of college-level soccer, the quality of training mode is directly related to the overall competitive level of the team and the individual performance of the athletes. However, although soccer training at the college level is often aimed at specialization and systematism, research has shown that several common problems prevent the optimal results of training. These problems may involve a lack of personalized, targeted, or scientifically based training programs that limit overall improvement in speed, agility, quickness, and pass-receiving performance. Some college-level soccer training programs may fail to adequately account for individual athlete differences and fail to accurately locate and address bottlenecks in specific skills and abilities. This can lead to erratic training results, making it difficult for some athletes to perform at their best in competition. Therefore, it is necessary to conduct an in-depth analysis of the problems existing in the current college-level soccer training and propose a specific training program to promote the athletes in the key skills and abilities more targeted. To address these issues, this study aims to develop a specific soccer training program to improve the speed, agility, quickness, and pass-receiving performance of college-level soccer players. A specific training program is a training method that combines different training methods and principles, which can make full use of the advantages of various training methods and avoid the disadvantages of various training methods, to achieve the best training effect. The main purposes of this study are as follows: 1) To explore the training elements and mechanisms related to speed, agility, quickness, and pass-receiving performance and to provide a theoretical basis and guiding principles for specific training programs. 2) Design and implement a specific training program to provide college-level soccer players with a novel and effective way of training to improve their skill level and competitiveness. 3) To evaluate and compare the effect and improvement of the specific training program, to provide empirical evidence and suggestions for the optimization and innovation of soccer training. Materials and Methods: This study’s main objective is to develop of specific training program to improve speed, agility, quickness, and pass-receiving performance for soccer players. In this experiment, 32 school soccer players from Jiying University were selected as experimental subjects by simple random sampling. The experimental group (N=16) underwent specific training intervention, while the control group (N=16) underwent regular training. The test indicators were selected from the "2021 National Youth Campus Soccer Summer Camp Best Team Selection Test Measures" jointly issued by the Ministry of Education and the Department of Physical Health and Art in April 2021. There are 5 test indicators in total: the 10-meter sprint test (sec), Agility test (sec), Pass-receiving Performance (sec), quickness test (sec), and Pass performance (sec), which mainly examined the comprehensive test plan of various special physical qualities such as athletes' speed, agility of dribbling change direction, quickness, pass-receiving performance. The experimental group then followed a specific training program for 8 weeks, 3 days, and 1.30 hours per day. Result: The results showed that there was no significant difference between the two groups of athletes before the experiment (p > 0.05), which provided a basis for the experiment. After 8 weeks of experimental, the experimental group 5 test indicators had significant differences compared with the control group and also within the experimental group (p < 0.05). Conclusion: This specific training program can improve the pass-receiving performance of soccer players.

Stochastic models for time complexity of computing tasks: I. Development principles, statistical data mining, identification problems

The paper contains the first part of an investigation devoted to the design of the mathematical models for the execution time of user tasks carried out on the virtual calculating nodes. We suppose that the execution time is a random value with the mean and variance depending on the node resources, task parameters, and the current characteristics of the node state. We discover the key features of the mean and variance functions and specify some of their particular cases. Both the mean and variance functions depend on the unknown parameters, and the design of the stochastic model for the time complexity leads to the parameter identification in the form of the generalized maximum likelihood estimates under the heterogeneous statistical information. The paper also contains recommendations concerning the gathering and subsequent usage of this information: the node testbed preparation, stress test planning, and the obtained data processing. The specific illustrating examples of the proposed mathematical model will be presented in the subsequent parts of the investigation.

Customizing Management Strategies for Product Introduction in Low-Volume Manufacturing: Enhancing Information Content Quality

Manufacturing companies characterized by high-mix and low-volume production exhibit distinct features that exert a significant influence on the product introduction process. The quality of information exchange between product design and production interfaces becomes paramount in low-volume manufacturing. Consequently, there is a pressing need to explore various methods for adapting and customizing management strategies to align with the unique characteristics of low-volume manufacturing and its associated product introduction processes. Although this knowledge is critical in low-volume manufacturing, most existing studies focus on the management aspects of high-volume manufacturing. Therefore, this study investigated the customization of management strategies for product introduction in low-volume manufacturing to enhance the quality of information content. Drawing upon a longitudinal analysis of new product introductions within a low-volume manufacturing company, this study identified four management strategies—namely, securing a production test and verification plan, revising the role of product introduction management, developing a formal design and production coordination plan, and developing lessons learned management plan. The paper explains how the examined company adapted and implemented product introduction management strategies to facilitate the enhancement of information content quality across three key stages: pre-implementation, post-implementation, and subsequent modification and refinement of strategies following the initial round of implementation. By shedding light on these strategies, this study offers a comprehensive understanding of management approaches for product introduction in low-volume manufacturing. The study makes a valuable contribution to the discourse on information quality management and design-production interface in the low-volume manufacturing and low-volume product introduction literature.

Influence of Different Powder Conditioning Strategies on Metal Binder Jetting with Ti-6Al-4V.

Metal binder jetting shows great potential for medical technology. This potential can be exploited by integrating binder jetting into existing process routes known from metal injection molding. The biggest challenge here is the flowability and packing behavior of the powders used, due to their low size distributions. This paper investigates different powder-drying strategies to improve flowability using a statistical experimental design. Because of its relevance for medical applications, spherical Ti-6Al-4V powder with a size distribution under 25 µm is dried under various parameters using vacuum and gas purging. The investigated parameters, time and temperature, are selected in a central-composite-circumscribed test plan with eleven tests and three center points. The target parameters-water content, flowability and impurity levels (oxygen, nitrogen)-of the powder are analyzed. For validation, practical test trials are carried out on an industrial binder jetting system with unconditioned powder and conditioning with optimized parameters, comparing the manufactured parts and the powder bed. An optimized drying cycle with a duration of 6 h at 200 °C was determined for the investigated powder. Significant improvements in the dimensional accuracy (from ±1.5 to 0.3%) of the components and the visual impression of the powder bed are demonstrated.

Evaluating the Effect of Cement and ARG Fiber on the Mechanical and Microstructural Properties of Dune Sand

Despite its collapsible nature and weakness, desert sand can be used for construction purposes all over the world if properly stabilized. Therefore, the aim of this study is to evaluate the effectiveness of cement and fiber in stabilizing locally available dune sand. A test plan was used to investigate the effects of varying quantities of alkali resistance glass (ARG) fiber (F: 0%, 0.2%, 0.4%, and 0.6%) and portland cement (C: 0.0%, 1.0%, 3.0%, and 5.0%) on the mechanical and microstructural properties of dune sand. Mechanical properties such as unconfined strength (UCS), strain at failure (εf), California bearing ratio (CBR), and modulus of elasticity (Es) were evaluated, and microstructure properties were investigated using Raman spectrum and laser-scanning microscopy (LSM) tests on stabilized sand samples. The results of the experimental study showed that the percentage of cement in the treated sand has a more significant impact on the investigated properties of the treated sand than the percentage of fibers. In addition, increasing fiber content results in an increase in the ductility of the sand mix. Raman analysis revealed significant interactions between sand mix components. Moreover, LSM results showed that fiber–cement interaction increased with increasing cement percentage, as calcium silicate hydrates (CSH) formed in the mix and filamentous and intrastrand binding occurred. The findings of this study indicate that ARG fiber and cement can be effective in the stabilization of dune sand for construction purposes even with the use of low percentages of ARG fiber (0.2%–0.4%) and cement (3%).

Impact of atherosclerosis imaging-quantitative computed tomography on diagnostic certainty, downstream testing, coronary revascularization, and medical therapy: the CERTAIN study.

The incremental impact of atherosclerosis imaging-quantitative computed tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of this study was to compare the clinical utility of the routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation. In this multi-centre cross-over study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnoses and plans for downstream non-invasive testing, coronary intervention, and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years; 433 (57.7%) were male. Compared with the conventional site CCTA evaluation, AI-QCT analysis improved physician's confidence two- to five-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; P < 0.001), including for measures such as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; P < 0.001) and plaque burden (197; 26.3%; P < 0.001). After AI-QCT including ischaemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (P < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (P < 0.001) and 23.0% (P < 0.001) of patients, respectively. The use of AI-QCT improves diagnostic certainty and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy.

EXPLORING THE RELATIONSHIP BETWEEN PATIENT SYMPTOMS AND PROVIDER GOALS FOR MUCOSAL HEALING IN IBD: INSIGHTS FROM THE IBD QORUS SURVEY DATA

Abstract INTRODUCTION Patients with inflammatory bowel disease (IBD) often experience symptoms such as abdominal pain, diarrhea, and bloody bowel movements. While these symptoms traditionally guided treatment, their predictive value for disease progression is limited. The latest STRIDE-II guidelines recommend a comprehensive IBD management approach, with an emphasis on short-term symptom relief, intermediate-term biomarker normalization, and long-term achievement of endoscopic remission. This treat-to-target strategy necessitates collaboration between physicians and patients. Our study aims to investigate the relationship between patient-reported outcomes and physician efforts to achieve mucosal healing (MH) using IBD QORUS patient and provider survey data. METHODS This was a multi-center prospective study that used patient and provider matched survey data from the Crohn’s &amp; Colitis Foundation IBD QORUS program. Surveys completed between June 2021-October 2022 were analyzed. Univariate and multivariate analyses were performed to determine the relationship between severity of patient reported symptoms and frequency of MH assessment with modalities including endoscopy and fecal calprotectin, as well as to determine how symptoms and MH status influence treatment. RESULTS In total 5,460 paired patient and provider surveys (Crohn’s disease (CD), n=3,276; ulcerative colitis (UC), n=2,184) were included in the analysis. Demographic information including age, sex and steroid-free MH, as well as severity of patient-reported symptoms were similar between CD and UC patients (Table 1). Abdominal pain severity reported by both IBD populations significantly impacted plans for future endoscopy (CD, p=0.000019; UC, p=0.000055) but not for fecal calprotectin testing. Reported stool frequency in both IBD populations significantly impacted future endoscopy plans (CD, p=0.000001; UC, p=0.000001) and future fecal calprotectin testing (CD, p=0.000304; UC, p=0.000001). Reported blood in stool had no effect on MH assessment in CD patients whereas it significantly affected plans for endoscopy (p=0.000001) and fecal calprotectin testing (p=0.000001) in UC patients. Provider discussions regarding MH occurred with 82.4% of CD patients and 85.3% of UC patients, and treatment plans in those without steroid free MH were influenced by severity of symptoms (p=0.000001). DISCUSSION Patient reported symptoms influenced fecal calprotectin and endoscopy plans in both IBD groups. Similarly, severity of symptoms in those without steroid-free MH significantly affected treatment management. These findings suggest that target-based treatment for IBD is feasible in the clinical setting and holds the potential to enhance patient outcomes.

Evaluation of a novel patient-specific quality assurance phantom for robotic single-isocentre, multiple-target stereotactic radiosurgery, and stereotactic radiotherapy.

To evaluate patient-specific quality assurance (PSQA) of 3 targets in a single delivery using a novel film-based phantom. The phantom was designed to rotate freely as a sphere and could measure 3 targets with film in a single delivery. After identifying the coordinates of 3 targets in the skull, the rotation angles about the equator and meridian were computed for optimal phantom setup, ensuring the film plane intersected the 3 targets. The plans were delivered on the CyberKnife system using fiducial tracking. The irradiated films were scanned and processed. All films were analysed using 3 gamma criteria. Fifteen CyberKnife test plans with 3 different modalities were delivered on the phantom. Both automatic and marker-based registration methods were applied when registering the irradiated film and dose plane. Gamma analysis was performed using a 3%/1 mm, 2%/1 mm, and 1%/1 mm criteria with a 10% threshold. For the automatic registration method, the passing rates were 98.2% ± 1.9%, 94.2% ± 3.7%, and 80.9% ± 6.3%, respectively. For the marker-based registration approach, the passing rates were 96.4% ± 2.7%, 91.7% ± 4.3%, and 78.4% ± 6.2%, respectively. A novel spherical phantom was evaluated for the CyberKnife system and achieved acceptable PSQA passing rates using TG218 recommendations. The phantom can measure true-composite dose and offers high-resolution results for PSQA, making it a valuable device for robotic radiosurgery. This is the first study on PSQA of 3 targets concurrently on the CyberKnife system.

Implementation and Adaptability Analysis of Numerical Simulation for Shale Oil CO2 Huff and Puff

Carbon dioxide (CO2) is being considered for use to enhance oil recovery and resource utilization and storage, with wide technical adaptability. In this paper, a numerical simulation method is used to study the adaptability of CO2 huff and puff in shale reservoirs. A fluid model introduces the nanoconfinement effect and reflects the nanoconfinement effect using the fluid p–T phase diagram. This method uses local grid refinement and changes the permeability near the grid to characterize the reservoir reconstruction volume (SRV) fracture network while considering the CO2 diffusion effect. The results indicate that by using the incremental recovery rate and oil change rate as references, adaptive charts can be obtained for different Kf/Km and oil saturation. When Kf/Km is 1000 and the increase in the CO2 recovery rate reaches 1.5%, the lower limit of oil saturation is 0.54. When Kf/Km is 1000 and the increase in the CO2 recovery rate reaches 2%, the lower limit of oil saturation is 0.57. When the oil saturation is 0.5 and the CO2 huff and puff oil change rate reaches 0.3, the lower limit of Kf/Km is 700. Finally, when the oil saturation is 0.548 and the CO2 huff and puff oil change rate reaches 0.6, the lower limit of Kf/Km is 10. The research results are significant and can guide the design and application of on-site CO2 throughput test plans.

Editorial: Special Issue on Opportunities and Challenges with Autonomous Racing

In the ever-evolving landscape of autonomous vehicles, competition and research of high-speed autonomous racing emerged as a captivating frontier, pushing the limits of perception, planning, and control. Autonomous racing presents a setup where the intersection of cutting-edge software and hardware development sparks unprecedented opportunities and confronts unique challenges. The motorsport axiom, “If everything seems under control, then you are not going fast enough,” resonates in this special issue, underscoring the demand for algorithms and hardware that can navigate at the cutting edge of control, traction, and agility. In pursuing autonomy at high speeds, the racing environment becomes a crucible, pushing autonomous vehicles to execute split-second decisions with high precision. Autonomous racing, we believe, offers a litmus test for the true capabilities of self-driving software. Just as racing has historically served as a proving ground for automotive technology, autonomous racing now presents itself as the crucible for testing self-driving algorithms. While routine driving situations dominate much of the autonomous vehicle operations, focusing on extreme situations and environments is crucial to support investigation into safety benefits. The urgency of advancing highspeed autonomy is palpable in burgeoning autonomous racing competitions like Formula Student Driverless, F1TENTH autonomous racing, Roborace, and the Indy Autonomous Challenge. These arenas provide a literal testbed for testing perception, planning, and control algorithms and symbolize the accelerating traction of autonomous racing as a proving ground for agile and safe autonomy. Our special issue focuses on cutting-edge research into software and hardware solutions for highspeed autonomous racing. We sought contributions from the robotics and autonomy communities that delve into the intricacies of head-to-head multi-agent racing: modeling vehicle dynamics at high speeds, developing advanced perception, planning, and control algorithms, as well as the demonstration of algorithms, in simulation and in real-world vehicles. While presenting recent developments for autonomous racing, we believe these special issue papers will also create an impact in the broader realm of autonomous vehicles.

Experimental investigation on thermal performance of self-service cold storage cabinet based on the orthogonal test

Self-service cold storage cabinets (SCSCs) are widely used in the delivery end of cold chain logistics for fresh agricultural products, to maintain the freshness of the products in a low temperature environment. Based on the three-factor and four-level orthogonal test, this paper first analyzed the impact of pure geometric structure factors on the thermal performance of SCSC. The priority of the geometric structure factors of the SCSC on the thermal performance is determined by means of four evaluation metrics. Then, two operating factors including air supply velocity and temperature are added to the consideration, and a five-factor and four-level orthogonal test is conducted based on the aforementioned five factors. The priority and optimal level of various factors were determined based on the test results. By comparing the results of two sets of orthogonal tests, it is found that the optimal level of the structure is affected by the change of air supply conditions. After optimizing the SCSC, the temperature range, temperature inhomogeneity coefficient, and velocity inhomogeneity coefficient decreased by 1.316 ℃, 21.16%, and 2.18% respectively, while the average temperature increased by 2.028 ℃, and the power consumption decreased by 4.81% compared to the original level of factors (test plan 1).

Integrated Project Development through Combined Theory and Practices of Core Courses focusing on Software Development Skills: Integrated Learning Framework

The National Education Policy promotes moving from the conventional content-heavy and memorization learning practice towards holistic learning/integrated learning. It imparts a creative and multidisciplinary curriculum that focuses equally on curriculum and assessment. All educational establishments assess students using written examinations, quizzes, seminars, term paper writing, and course projects. A semester typically includes 4-5 courses, and students must earn credits for these courses by scoring a good Cumulative Grade Point Average (CGPA). As course projects offer depth knowledge/holistic learning/lifelong learning of a course for the student, many courses include course projects as one of the activities in the course. If all the courses are intended to include course projects as a mandatory pedagogy, it will be difficult for students to acquire in-depth knowledge and required skills while also dealing with stress. So we are proposing an integrated learning framework by applying the theory and practices of two core courses- Software Engineering and Web Technologies to develop a web application. This integrated learning focuses on developing software development and software testing skills in computer science for undergraduate students pursuing a bachelor of engineering degree. This framework alleviated the pressure on students during placement and created job opportunities in software development. The framework consists of three important phases- The first phase includes the identification of the problem as a need for customers, writing requirements and analyzing the same. Students apply modular design principles and break down the codebase into distinct modules. This technique enhances code organization, reusability, and maintainability. The second phase focused on developing the front end by harnessing the power of Angular, a leading web framework, to craft a sleek and interactive user interface. The backend is built using Node.js, which serves as the foundation, enabling the software system to cater to highperformance server environments. These modules communicated seamlessly through well-defined APIs, facilitating the integration of various components within the application, ultimately delivering a seamless and responsive user experience. An industry expert conducted a workshop on Angularsoftware testing workshop was conducted for students by industry experts to expose the students to designing test cases, test plans, and testing strategies. The hands-on experience on testing tools was provided during the workshop. Faculty reviews are conducted on each phase, and rubrics-based assessment is done on each phase. Approximately sixty teams created web-based applications for real-world scenarios. Positive aspects of the framework in feedback indicated that more than 87% of the students agreed that they could apply Software engineering principles and practices such as requirements management. modular design and testing in web applications. Also, more than 85% of students acquire skills from code-to-web design mastery by developing web applications in Angular Node.js and backend implementation. This framework helped to improve teamwork, presentation and communication skills. Confidence in software development improved to a greater extent. The design and implementation of the framework met the stated outcome of the courses. The student's academic performance improved by 10% compared to the previous year when students were not involved in the integrated project development. Keywords— Framework, learning, practices, project, skills, technology, testing, web

Conceptual framework for preterm birth review in San Francisco.

Preterm birth persists as a leading cause of infant mortality and morbidity despite decades of intervention effort. Intervention null effects may reflect failure to account for social determinants of health (SDH) or jointly acting risk factors. In some communities, persistent preterm birth trends and disparities have been consistently associated with SDH such as race/ethnicity, zip code, and housing conditions. Health authorities recommend conceptual frameworks for targeted action on SDH and precision public health approaches for preterm birth prevention. We document San Francisco, California's experience identifying the need, rationale, methods, and pilot work for developing a conceptual framework for preterm birth review (PTBR) in San Francisco. The PTBR conceptual framework is intended to enable essential public health services in San Francisco that prevent a range of preterm birth phenotypes by guiding plans for data collection, hypothesis testing, analytical methods, reports, and intervention strategy. Key elements of the PTBR conceptual framework are described including, 10 domains of SDH, 9 domains at the whole person level, such as lived experience and health behaviors, 8 domains at the within-person level, such as biomarkers and clinical measures, 18 preterm birth phenotypes, and the interconnections between domains. Assumptions for the PTBR conceptual framework were supported by a scoping review of literature on SDH effects on preterm birth, health authority consensus reports, and PTBR pilot data. Researcher and health authority interest in each of the domains warrants the framework to prompt systematic consideration of variables in each proposed domain. PTBR pilot data, illustrated in heatmaps, confirm the feasibility of data collection based on the framework, prevalence of co-occurring risk factors, potential for joint effects on specific preterm birth phenotypes, and opportunity for intervention to block SDH effects on preterm birth. The proposed PTBR conceptual framework has practical implications for specifying (1) population groups at risk, (2) grids or heatmap visualization of risk factors, (3) multi-level analyses, and (4) multi-component intervention design in terms of patterns of co-occurring risk factors. Lessons learned about PTBR data collection logistics, variable choice, and data management will be incorporated into future work to build PTBR infrastructure based on the PTBR conceptual framework.

Process Evaluation of Services for HIV-Infected Post-Partum Women and HIV-Exposed Infants in Primary Health Care Blantyre Malawi.

HIV testing among HIV-exposed infants (HEI) in Malawi is below global targets and, affected by low utilisation of health services after birth. We conducted a mixed methods evaluation of the implementation of services for early infant diagnosis (EID) of HIV against national guidelines in Blantyre, Malawi, to inform the development of strategies to improve EID services uptake. We estimated coverage of HEI enrolment in HIV care and HIV testing at 6 weeks through a retrospective data review. We qualitatively explored implementation gaps in EID services through process mapping of 8 mother-infant pairs (MIP); and investigated healthcare workers' (HCW) perspectives on the implementation gaps through group interviews with 16 HCWs. We analysed the quantitative data descriptively and conducted a thematic content analysis of qualitative data. Of 163 HEIs born at the study sites, 39 (24%) were enrolled in an HIV care clinic before post-natal discharge, and 85 (52%) received HIV testing by 6 weeks. The median time for MIP to receive EID services was 4 (1-8) hours. The implementation gaps observed during process mapping included: failure to identify and enrol HEI in HIV care clinic; lack of immunisation, counselling for HEI testing, HIV testing, drug refilling, and family planning; and different appointment dates for mother and infant. HCWs reported delays and gaps influencing optimal service provision including: lack of screening to identify MIP, limited supervision for student HCWs when providing services, inadequate capacity of point of care machines, challenges with integrating services, and role confusion. Use of unique identifiers for MIP and establishing a booking system to schedule appointments to suit point of care machine capacity were primary service improvement recommendations. This study identified suboptimal EID services in Malawi due to process, capacity, and system factors. Context-appropriate interventions accommodating systems thinking are needed to enhance service provision.

Optimal test plans for accelerated life tests based on progressive type-I censoring with engineering applications

In reliability engineering studies, the accelerated life tests with optimal test design that balances cost constraints is particularly important since the lifetimes of electro-mechanical, electronic, and mechanical goods are typically modelled with this characteristic. Comparative optimal test plans for accelerated life tests are developed in a variety of applications, including engineering, biological, medical, and other related fields. In this study, we compare, under cost restriction with a specified budget, optimum multiple constant stress and step stress accelerated life tests based on progressive-type-I censoring. The goal is to assess the advantage provided by step-stress testing over constant-stress testing. In order to conduct an accelerated life test effectively, stress durations need to be carefully specified during the design stage due to limited resources in engineering practice. The estimated accuracy of the parameters of interest and the expense of the experiment are directly impacted by the stress durations. Under a prespecified budget and cost constraints, this article examines the optimal stress durations based on D-, E-, T-, C-, R-, and P-optimal criteria. These criteria are also contrasted together. We illustrate the application of the optimal durations using numerical and simulation examples. A study is conducted to determine how sensitive the optimal duration is to model parameter misspecification.

Experimental characterization of energy consumption in 5-axis milling machine and developing optimization strategy

The optimization of machining processes is of paramount significance because of its pivotal role in modern manufacturing. Efficient machining techniques not only enhance product quality but also reduce costs and environmental impacts. This study focuses on the experimental characterization of energy consumption in a 5-axis milling machine and the simulation of possible solutions to reduce it. The first step is to understand the key drivers of energy consumption which is crucial for enhancing energy management and optimization. This was achieved by developing a mathematical model that uses the most common machining parameters as input using a Response Surface Methodology experimental test plan and an analysis of the contributions of the auxiliary systems to the overall energy consumption. As a second step, the effectiveness of different solutions was simulated considering different application scenario, like the type of operations. Such solutions include the introduction of duty cycle strategies for some auxiliary systems and the optimization of process parameters.

Reliability Demonstration Test Planning for Systems Using Prior Knowledge

Reliability Demonstration Test Planning for Systems Using Prior Knowledge

A probabilistic approach to monitoring the condition of complex technical equipment

A probabilistic cascade-hierarchical approach is proposed for monitoring the condition of complex technical equipment in production, taking into account the types of controlled catches (software, hardware and mechanical) and types of control: technical means and the appropriate level of qualification of personnel based on polymodeling. In contrast to the deterministic control process, when sequential tests are carried out until a certain outcome is obtained, the proposed approach made it possible to form non-stationary rules for estimating the probabilities of process outcomes dynamically, relative to changing test conditions and the environment. The use of the KullbackLeibler measure to assess the divergence of the probability distribution functions of defects in complex technical equipment, having high sensitivity, allowed us to form a scheme of a two-circuit decision support system for dynamic test planning of complex technical equipment, which ultimately increased the degree of validity of the decisions made.