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We determine the sensitivity of a current optimal solution to a combinatorial optimization problem to cost changes in a set of elements. In a recent study, the concept of regular set tolerances has been introduced for a combinatorial optimization problem and for three types of cost functions, namely sum, product, and bottleneck. A regular set tolerance is the supremum amount of cost changes that can be distributed in the most favorable way to multiple elements such as not to change the current optimal solution. In this paper, we introduce an alternative concept, namely the reverse set tolerance , which is a measure of the infimum amount of cost changes to multiple elements such that the current optimal solution becomes non-optimal. We characterize the specific cases in which reverse set upper and lower tolerances have positive values and in which they are infinite. We also show a criterion for the uniqueness of an optimal solution. Furthermore, we present bounds and exact formulas for reverse set upper and lower tolerances using the relation to their corresponding single tolerance counterparts. We discuss the similarities and differences in the results between regular and reverse set tolerances. Finally, we motivate this new concept by analyzing them for special combinatorial optimization problems with important practical applications. [ABSTRACT FROM AUTHOR]

In recent times, various real word problems including infectious diseases, engineering problems, and chemical processes, etc are modelled by using differential equations with fractals and fractional orders. The mentioned area provides a powerful tool to investigate the aforesaid problems from different perspectives like analysis, numerical investigation, and qualitative theory. Similarly, one of the global issue is devoted to re-infection of viral diseases like COVID-19. The said behaviour has produced very saviour impact on human life worldwide. Also, this is very critical for health system of a country as well as for its economics situation. To study the aforesaid phenomenon of re-infection, a hybrid type fractal–fractional three compartments model is formulated. The basic results related to boundedness, positivity, equilibrium points, basic reproductive number, and sensitivity analysis of the basic threshold are included in the theoretical aspect. Additionally, the Volterra–Lyapunov approach is used to establish both local and global stability analysis under fractals and fractional derivative. Furthermore, utilizing techniques from numerical functional analysis and fixed point theory, the existence and Hyers–Ulam stability of the solutions are also examined. A numerical algorithm based on Lagrange's interpolation polynomials is extended to simulate the results of various compartments. Graphical interpretations corresponding to different fractals–fractional order values are presented. For verification of our numerical results, a comparison is provided between the real and simulated data. Here it should be kept in mind that the differential operator of fractals–fractional order is considered with Mittag-Leffler kernel. The mentioned operator is more general among the available fractals fractional differential operators in literature. [ABSTRACT FROM AUTHOR]

During patient follow-up in a randomized trial, some deaths may occur. Where death (or noncardiovascular death) is not part of an outcome of interest it is termed a competing risk. Conventional analyses (eg, Cox proportional hazards model) handle death similarly to other censored follow-up. Patients still alive are unrealistically assumed to be representative of those who died. The Fine and Gray model has been used to handle competing risks, but is often used inappropriately and can be misleading. We propose an alternative multiple imputation approach that plausibly accounts for the fact that patients who die tend also to be at high risk for the (unobserved) outcome of interest. This provides a logical framework for exploring the impact of a competing risk, recognizing that there is no unique solution. We illustrate these issues in 3 cardiovascular trials and in simulation studies. We conclude with practical recommendations for handling competing risks in future trials. • In CV trials where competing events are rare or well balanced between groups, they are unlikely to cause major problems. • The Fine and Gray model (although useful in certain specific circumstances) is usually best avoided because it is often used inappropriately and can be misleading. • Where sensitivity analyses for competing risks are warranted, a multiple imputation approach is recommended. • There is no single right answer to the competing risk problem; one needs to seek a consistency of conclusions across a range of assumptions. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is an autoimmune disease affecting various organs. Ocular involvement, particularly retinopathy, is common, emphasizing the significance of early detection. Optical coherence tomography angiography (OCTA), a non-invasive imaging technique, reveals microvascular changes, aiding SLE diagnosis and monitoring. This study evaluates OCTA's effectiveness in detecting SLE-related retinal alterations. A systemic search was undertaken across PubMed, Embase, and Scopus databases to identify studies presenting OCTA measurements in SLE patients compared to healthy controls. The meta-analysis, employing either fixed-effects or random-effects models based on heterogeneity levels, was conducted. Additionally, subgroup and sensitivity analyses, meta-regression, and quality assessments were carried out. Thirteen studies of 565 eyes in the SLE group and 560 eyes in the control group were included. The meta-analyses revealed that SLE patients had a significantly lower retinal vessel density in the superficial and deep capillary plexus layers, choriocapillaris flow area, and foveal avascular zone (FAZ) circularity index compared to healthy controls, but that there were no significant differences in the FAZ area and perimeter. These findings highlight how OCTA can provide a noninvasive assessment of SLE effects on the retinal microvasculature, potentially presenting a reliable biomarker for more precise detection of SLE and disease activity monitoring. [ABSTRACT FROM AUTHOR]

The intense interaction between thruster plumes and spacecraft surfaces presents substantial challenges for the advancement of space technologies. The impingement effects from a 10 N bipropellant thruster plume on a vertical instrumented plate were experimentally and numerically investigated in this study. Impingement pressure and heat flux were measured using micro differential pressure transducers and Gardon gauges, respectively, while the spatial distribution of the plume was captured using the high-speed camera. The phenomena and the distribution characteristics of plume impingement have been summarized, thereby providing a comprehensive validation dataset for subsequent predictions. Numerical simulations are conducted utilizing the coupled hybrid Computational Fluid Dynamics and Direct Simulation Monte Carlo (CFD-DSMC) algorithm. The dependence of the simulation outcomes on grid resolution was critically assessed, and the accuracy of the results was validated by comparison with experimental data. An integrated methodology, combining experimental and numerical approaches, was developed to calculate the maximum heat flux under realistic grid configurations. This method has proven to be effective and supports the accurate and efficient evaluation of intense plume impingement effects for engineering applications. • Systematic experimental data and key features of intense plume impingement effects. • Sensitivity analysis of simulated impingement data to grid configurations. • Validation of simulation methods through comparative analysis with experimental data. • Integrative approach for engineering calculation of impingement heat flux. [ABSTRACT FROM AUTHOR]

The assessment of casualty risks associated with re-entry necessitates a comprehensive analysis of trajectories and the examination of pertinent safety-related quantities such as the ground impact area and ground reaching velocity. In practical scenarios, the presence of uncertainty in input conditions introduces variability in safety-related quantities. Consequently, employing stochastic re-entry trajectory analysis becomes crucial in overcoming the limitations of conventional deterministic analyses. Conducting sensitivity assessments during the break-up phase is imperative to gain more insights into how to manage the variability of safety-related measures. Therefore, this paper conducted a surrogate-based global sensitivity analysis and employed explainability machine learning techniques to unveil the complexities of the relationship between input uncertainty conditions and three key measures: ground-reaching velocity, falling range, and falling time, with the object of interest being the Apollo-type capsule. A three-step polynomial chaos expansion-based strategy was devised to efficiently approximate the discontinuous relationships. The results show that the relationship is characterized by severe discontinuity that separates two modes: low- and high-ground reaching velocity caused by the presence of two distinct trim points, with precautionary measures that should be taken to prevent the occurrence of the latter. From this set of procedures, three key input conditions that significantly affect the safety-related measures were identified, namely, the altitude, pitch rate, and path angle of the capsule during the breakup. Subsequently, explainability techniques were utilized to give suggestions on how to control the input variability and avoid the high ground reaching velocity mode, aiming to achieve more dependable predictions for the three safety parameters mentioned earlier. • Performed surrogate-based sensitivity analysis for stochastic re-entry trajectory. • Utilized explainability machine learning techniques to decipher relationships. • Identified key input conditions influencing safety measures for Apollo-type capsules. • Contributed insights to minimize hazardous re-entry modes and mitigate risks. • Uncovered complex discontinuity in response surface with explainable surrogate models. [ABSTRACT FROM AUTHOR]

This systematic review and meta-analysis investigates the relationship between haemoglobin (Hb) concentrations and obstructive sleep apnea syndrome (OSAS). Following PRISMA guidelines, we searched PubMed, EMBASE, and Cochrane Library from inception to March 8, 2024. Eligible studies included cross-sectional, cohort, and case-control designs comparing Hb concentrations in OSAS patients and healthy controls. Two reviewers independently screened records and extracted data. The risk of bias was assessed using the Joanna Briggs Institute checklist. A total of 27 studies involving 6499 OSAS subjects and 5199 controls were included. Hb concentrations were significantly higher in OSAS patients compared to controls (SMD: 0.28; 95 % CI: 0.18 to 0.39; I2 = 84.4 %). Subgroup analysis by OSAS severity showed that severe OSAS patients had higher Hb concentrations than those with mild/moderate OSAS. Sensitivity analyses confirmed the robustness of the findings. However, 7 studies reported opposite results, indicating possible regional or methodological differences. Hb concentrations are elevated in OSAS patients, with higher levels observed in severe cases. The significant heterogeneity and the predominance of studies from Turkey highlight the need for further research in diverse populations. Limitations include potential publication bias and variability in study designs. • A systematic review and meta-analysis were conducted to investigate the relationship between Hb concentrations and OSAS. • A total of 27 studies with 6499 OSAS patients and 5199 controls were included. • Hb concentrations were significantly higher in OSAS compared to CTRL (SMD: 0.28; 95 % CI: 0.18 to 0.39; I2 = 84.4 %). • The results suggest that elevated Hb levels in OSAS patients may reflect an adaptive response to intermittent hypoxia. • The relationship between OSAS severity and Hb concentrations highlights the potential clinical significance. [ABSTRACT FROM AUTHOR]

Since 2013, the International GNSS Service (IGS) real-time service (RTS) has been providing precise orbit and clock corrections for ten years, which enables real-time positioning at the decimeter level. High precision positioning relies heavily on accurate orbit and clock. However, constrained by the relatively short observation duration, the accuracy of real-time products are often worse than the final products. Previous studies indicate that compensating for errors in orbit and clock can improve positioning accuracy. Based on this theory, we proposed an improved positioning model, which incorporates the signal-in-space range error (SISRE) into the ionosphere-free combination observation equation and treats it as a parameter in the Kalman filter. Through the analysis of SISRE, we find that the time-varying characteristic of the parameter follows a random walk assumption. To find the optimal parameter settings of the SISRE parameters, a two-dimensional sensitivity analysis is employed, and a set of recommended values are provided. In the simulated kinematic positioning experiments, the proposed method achieves positioning accuracies of 17.3 cm, 19.6 cm, and 18.0 cm for GPS, BDS-3, and Galileo, respectively, representing a 10–20 % improvement over traditional methods. In real-time PPP experiment, the accuracy reaches 21.7 cm, indicating a 12.9 % improvement compared to traditional methods. [ABSTRACT FROM AUTHOR]

Numerous models have been developed to predict acute kidney injury (AKI) after noncardiac surgery, yet there is a lack of independent validation and comparison among them. We conducted a systematic literature search to review published risk prediction models for AKI after noncardiac surgery. An independent external validation was performed using a retrospective surgical cohort at a large Chinese hospital from January 2019 to October 2022. The cohort included patients undergoing a wide range of noncardiac surgeries with perioperative creatinine measurements. Postoperative AKI was defined according to the Kidney Disease Improving Global Outcomes creatinine criteria. Model performance was assessed in terms of discrimination (area under the receiver operating characteristic curve, AUROC), calibration (calibration plot), and clinical utility (net benefit), before and after model recalibration through intercept and slope updates. A sensitivity analysis was conducted by including patients without postoperative creatinine measurements in the validation cohort and categorising them as non-AKI cases. Nine prediction models were evaluated, each with varying clinical and methodological characteristics, including the types of surgical cohorts used for model development, AKI definitions, and predictors. In the validation cohort involving 13,186 patients, 650 (4.9%) developed AKI. Three models demonstrated fair discrimination (AUROC between 0.71 and 0.75); other models had poor or failed discrimination. All models exhibited some miscalibration; five of the nine models were well-calibrated after intercept and slope updates. Decision curve analysis indicated that the three models with fair discrimination consistently provided a positive net benefit after recalibration. The results were confirmed in the sensitivity analysis. We identified three models with fair discrimination and potential clinical utility after recalibration for assessing the risk of acute kidney injury after noncardiac surgery. [ABSTRACT FROM AUTHOR]

• Assessment of the integrated drought risk, hazard, vulnerability, and response capacity associated with regional water resources. • Securement of objectivity and validity in selecting and weighting indicators by means of probability and statistical methods. • Provision of the drought risk outlook in different climate change scenarios and investigation of the influence of risk in sensitivity analyses. Due to climate change, the frequency and duration of meteorological drought have increased. In addition, local water supply capacity has not met water demand in many regions, which will eventually lead to serious water shortages. To mitigate the effects of drought on sustainable water use, it is necessary to understand how climate change affects regional water supply capacity and drought risk. To this end, this study evaluated the drought response capacity of regional water supply systems and assessed the comprehensive drought risk in terms of drought hazard, vulnerability, and response capacity. To avoid subjectivity in risk analysis, structural equation modeling was used to select primary indicators and probability and statistical methods were used to assign weights to the indicators. The changes in drought risk in different climate change scenarios were assessed using sensitivity analyses. The overall results indicate that the future drought risks in Gyeonggi, Gyeongsang, Chungcheong, Jeolla, and Gangwon are 18, 12, 13, 9, and 10% higher, respectively, than the current risk level. The sensitivity analyses showed that Jinju in Gyeongsang province, which has a high drought response capacity, had the largest decreasing rate in drought risk. The quantified changes in drought risk under future climate change scenarios will be useful for identifying areas with a high drought risk and making decisions about drought mitigation under climate change. [ABSTRACT FROM AUTHOR]

Hydrogen is commonly perceived as the key player in the transition towards a low-carbon future. Nevertheless, H 2 low energy density hinders its easy storage and transportation. To address this issue, different alternatives (liquefied hydrogen, ammonia and liquid organic hydrogen carriers) are explored as hydrogen vectors. The techno-economic assessment of H 2 transport through these carriers is strongly dependent on the basis of design adopted, such that it is difficult to draw general conclusions. In this respect, this work is aimed at performing a sensitivity analysis on the hypotheses introduced in the layout of H 2 value chains. Different scenarios are discussed, depending on harbour-to-harbour distances, cost of utilities and raw materials and H 2 application to the industrial or mobility sector. The most cost-effective carrier is selected for each case-study: NH 3 is the most advantageous for industrial sector, while LH 2 holds promises for mobility. Critical issues are pointed out for future large-scale applications. [Display omitted] • NH 3, liquefied H 2 , toluene and dibenzyltoluene assessment as H 2 carrier. • H 2 application to both the industrial and mobility sectors. • Sensitivity study on harbour-to-harbour distance, utilities and raw materials cost. • NH 3 is the most cost-effective H 2 carrier for industrial applications. • LH 2 is the most cost-effective H 2 carrier for mobility applications. [ABSTRACT FROM AUTHOR]

The development of Chemical-looping Reforming (CLR) for blue hydrogen production requires a precise reactor design and control to achieve optimal efficiency and operability. This study proposes a 1D heterogeneous model for a CLR fixed-bed reactor, targeting the production of blue hydrogen and nitrogen. Validation against experimental data confirms the model's accuracy and reliability. A comprehensive sensitivity analysis highlights reactor variables, including active metal content in the oxygen carrier, steam-to-methane ratio, and molar flow rates during reduction and reforming stages, as key variables in determining reactor performance. Optimizing these variables is crucial for process intensification and enhancing hydrogen production efficiency. Under optimal conditions, the reactor yields nitrogen with a concentration above 98% during the oxidation stage and hydrogen with a 66.7% concentration during the reforming stage. Moreover, the CLR reactor operates autothermally and reaches a hydrogen production efficiency of 63.6%, prior to any further purification. The study concludes with a discussion of the reactor's challenges and opportunities, laying the groundwork for potential future research and advancements in the field. [Display omitted] • An intensified reactor for efficient blue H 2 and N 2 production is proposed. • Reactor key parameters are active metal, steam-to-methane ratio, and pressure. • Reactor optimization maximizes hydrogen production efficiency. • 66% H 2 yield in reforming and > 98 % N 2 purity in oxidation are achieved. [ABSTRACT FROM AUTHOR]

Non-equilibrium plasma is applied for the first time to ignite the ammonium-hydrogen mixture and reduce the NO x /N 2 O emission with effect in this work. Gas chromatography (GC) experiments as well as a detailed kinetic model, including neutral molecules, free radicals, charged particles, vibratory excited states, and electron excited states, are integrated to investigate the kinetic process of ammonia-hydrogen doped ignition and NO x /N 2 O emission facilitated by nanosecond pulsed discharge. The numerical model closely matches the GC-measured values of NH 3 consumption, H 2 increase, and N 2 O production. Pathway fluxes of important species and sensitivity analysis of ignition delay time reveal that the addition of non-equilibrium plasma has an obvious promotion effect on ammonia and hydrogen-doped oxidation and ignition. The initial ignition temperature significantly impacts the ignition delay time, with a more pronounced plasma-promotion effect observed at lower temperatures. Conversely, as the hydrogen mixing ratio increases, the ignition delay time decreases, yet the generation of NO and N 2 O increases. This is attributed to the heightened production of H and NH through elementary reactions such as NH 3 +H NH 2 + H 2 , H + O 2 O + OH, and OH + H 2 H + H 2 O. Nevertheless, NO and N 2 O emissions are reduced by 1-2 orders of magnitude with plasma assistance compared to auto-ignition. The reduction in NO emissions can be attributed to increased consumption in the pathway of NO + NH 2 N 2 + H 2 O and decreased formation in the pathways of HNO + O 2 HO 2 + NO and NH + NO N 2 O + H. Additionally, it was discovered that the electron attachment dissociation reaction e + N 2 O → O− + N 2 predominantly contributes to the reduction of N 2 O. These research findings significantly contribute to advancing our understanding of the kinetics involved in ammonia-hydrogen doped ignition and emissions, particularly with plasma assistance, for potential engine applications. • Kinetic models for plasma-assisted NH 3 /H 2 /air ignition are established. • Measurements of products in plasma-activated NH 3 /H 2 /air pyrolysis are provided. • NO and N 2 O emissions are reduced with plasma assistance compared to auto-ignition. • Pathways for NO and N 2 O generation during NH 3 /H 2 /air ignition are elucidated. [ABSTRACT FROM AUTHOR]

A major global health problem continues to be malaria, a disease that can be fatal brought on by Plasmodium parasites and spread by the bite of infected Anopheles mosquitoes. We provide a deterministic mathematical model in this study to simulate the dynamics of malaria transmission between humans and mosquitoes. We present a new compartment for hospitalized patients as well as fractional calculus. The next-generation matrix technique is used to obtain the fundamental reproduction number, R 0 , and stability conditions for the model's equilibrium points are derived. Both locally and globally, the sensitivity analysis for the fundamental reproduction number R 0 is satisfied. In MAPLE, the Runge–Kutta fourth-order approach is used to simulate the model. [ABSTRACT FROM AUTHOR]

Hydrogen plays a crucial role in global net-zero policies due to its numerous advantages and is widely regarded as a key future fuel. Clean and sustainable hydrogen production technologies are currently a focal point of research, with thermochemical methods showing promise in achieving environmentally friendly hydrogen. This study builds upon previous research conducted by the authors on thermochemical hydrogen production through chlorine family cycles. It conducts a thorough sensitivity analysis of various system variables that significantly impact the overall performance of these processes. The investigation assesses the performance of chlorine family thermochemical cycles from exergetic, exergoeconomic, and exergoenvironmental perspectives. Exergetic performance parameters include net thermal exergies and exergy efficiencies, exergoeconomic parameters encompass hourly levelized and total cost rates, and exergoenvironmental parameters involve exergoenvironmental factors and component-associated environmental impact rates. The system variables under consideration include ambient temperature, system lifetime, annual operating hours, and operation and maintenance cost factor. The analysis reveals that the system's lifetime notably influences both the exergoenvironmental factors and component-associated environmental impact rates (by about 80%). Meanwhile, its impact on both the hourly levelized (around 11.5%) and total cost rates (approximately 1.2%) is comparatively less significant. Similarly, ambient temperature has a marginal effect on the net thermal exergies and exergy efficiencies of the considered cycles. [Display omitted] • A comprehensive sensitivity analysis of chlorine family cycles is presented. • Cycles are studied via exergetic, exergoeconomic & exergoenvironmental perspectives. • Lifetime influences the exergoenvironmental factor by about 80%. • Lifetime influences the hourly levelized cost rate by 11.5% and total cost rate by 1.2%. • Ambient temperature marginally affects net thermal exergies and exergy efficiencies. [ABSTRACT FROM AUTHOR]

The targeted placement of selected carbon nanotubes is associated with low throughput rates. Hence, this paper presents a novel stage design for the fully automatic assembly of carbon nanotube field-effect transistors (CNTFETs) via mechanical dry transfer. It constitutes the core module of an assembly machine for the precise deployment of nanotubes onto a prefabricated wafer. The mechanical dry transfer approach allows high level of carbon nanotube selectivity with the aim of enabling a high-volume fabrication of ultra-clean devices. The previous production rate of such ultra-clean devices is less than one per hour, which offers a high potential for improvement. The stage consists of a parallel kinematic mechanism (PKM) with 3 degrees of freedom ( X 2 Y 2 C 1 ) carrying two additional stacked axes ( Z 1 C 2 ). The PKM is suspended on a vacuum preloaded aerostatic bearing, voice coil motors (VCM) and flexure hinges. Together with a combination of high precision and resolution touch probe measurement systems close to its tool center point (TCP), high accuracy and low settling time can be achieved. Based on realistic manufacturing tolerances, a sensitivity analysis of the mechanism's pseudo rigid body model (PRBM) suggests a theoretical closed-loop error below 0. 15 μ m over the entire XY workspace of 20 mm × 2. 8 mm. Measurements of positioning motions show that the settling time can be decreased by the compensation of friction resistances inside the internal bearings of the VCMs. [Display omitted] • Parallel kinematic micromanipulator with novel axis configuration. • Non-monolithic flexure hinge/voice coil combination. • Sensitivity analysis for the accuracy assessment of the manipulator. • Significant reduction of overshoot and settling time. [ABSTRACT FROM AUTHOR]

Over the past fifty years, the form and function of space habitat modules have remained largely unchanged. While cylindrical modules are relatively simple to transport and deploy, their limited size poses a challenge to their efficiency and usability. In contrast, large space habitat construction projects are costly and present logistical difficulties. The development of polyhedral modules could bridge the gap between these two approaches, allowing for modular, polyhedral units to be assembled and linked together to create larger habitats more efficiently and with less risk. However, identifying the most suitable polyhedron for use in space remains a critical question. Previous research has explored the construction of polyhedral modules, but little rigor has been applied to identifying the most optimal form. This is a crucial issue because the first module to be used will likely set the standard for subsequent modules and any disadvantages present at that time will be perpetuated. Therefore, it is essential to identify the optimal form prior to constructing prototypes. This research paper employs multi-criteria decision analysis and sensitivity analysis to compare various candidate polyhedra across several evaluation metrics, including number of faces, volume to surface area ratio, and joint stress, among several other quantitative and qualitative metrics. The results demonstrate that the Rhombic Dodecahedron is a particularly suitable candidate compared to other forms analyzed. Thus, the Rhombic Dodecahedron should be considered the standard polyhedral form for future research involving the development of polyhedral modules. • Rhombic Dodecahedron identified as optimal polyhedron for space habitat design. • Polyhedral modules surpass cylindrical counterparts in multiple criteria. • Novel multi-criteria analysis method allows cross-metric comparison. [ABSTRACT FROM AUTHOR]

Health economic (HE) models are often considered as "black boxes" because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making. This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes. The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist. Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel. To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model's outcomes. PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes. PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models' parameters and outcomes. • Health economic evaluation guidelines emphasize the importance of health economic model validation, but there is currently no easy-to-use tool available to systematically validate (parts of) health economic models. • This article presents the development and testing of the Probabilistic Analysis Check dashBOARD, which is a unique online tool aimed at validating the plausibility of parameters and outcomes of health economic models and at exploring the working of health economic models, using interactive plots and metamodeling methods. • The Probabilistic Analysis Check dashBOARD is a useful tool for model developers to validate health economic models at different stages of model development, through uploading probabilistic parameters and outcomes of the health economic model. Also, it enables reviewers to efficiently evaluate health economic models. [ABSTRACT FROM AUTHOR]

Recent reports of myocardial recovery after mechanical unloading with left ventricular assist devices (LVADs) have challenged the prevailing notion that end-stage heart failure (HF) is irreversible. To improve our understanding of this phenomenon, we comprehensively analysed the structural, functional, and energetic changes in failing human cardiomyocytes after LVAD implantation. Based on a prospectively registered protocol (PROSPERO-CRD42022380214), 30 eligible studies were identified from 940 records with a pooled population of 648 patients predominantly with non-ischaemic cardiomyopathy. LVAD led to a substantial regression in myocyte size similar to that of donor hearts (standardised mean difference, −1.29; p<0.001). The meta-regression analysis revealed that HF duration was a significant modifier on the changes in myocyte size. There were some suggestions of fibrosis reversal (−5.17%; p=0.009); however, this was insignificant after sensitivity analysis. Developed force did not improve in cardiac trabeculae (n=5 studies); however, non-physiological isometric contractions were tested. At the myocyte level (n=4 studies), contractile kinetics improved where the time-to-peak force reduced by 41.7%–50.7% and time to 50% relaxation fell by 47.4%–62.1% (p<0.05). Qualitatively, LVAD enhanced substrate utilisation and mitochondrial function (n=6 studies). Most studies were at a high risk of bias. The regression of maladaptive hypertrophy, partial fibrosis reversal, and normalisation in metabolic pathways after LVAD may be a testament to the heart's remarkable plasticity, even in the advanced stages of HF. However, inconsistencies exist in force-generating capabilities. Using more physiological force-length work-loop assays, addressing the high risks of bias and clinical heterogeneity are crucial to better understand the phenomenon of reverse remodelling. [ABSTRACT FROM AUTHOR]

• Improvement to roller compaction model by considering roll speed dependency. • Model prediction and validation using literature and industrial data. • Built a custom model in gPROMS to incorporate the effect of mass throughput during process optimization and design. This study introduces a modification to the roller compaction model proposed by Sousa et al. 1 to account for the effect of roll speed on powder compaction in the dry granulation process. The proposed model enhances the prediction accuracy, particularly at higher roll speeds, which are often overlooked in existing models. The modified model is validated using literature data, demonstrating improved performance compared to the original model. Additionally, the model is applied to a pharmaceutical formulation, showing its applicability in an industrial context. The integration of the model into gPROMS allows for global sensitivity analysis and design space exploration, providing valuable insights for process optimization and scale-up. The study contributes to the understanding of roller compaction dynamics and offers a practical tool for decision-making in pharmaceutical manufacturing. [ABSTRACT FROM AUTHOR]

Evidence indicates that the use of sedative–hypnotics, including benzodiazepines and z-drugs, is linked to an increased risk of falls and fractures. Nonetheless, the potential exacerbation of this risk by orexin receptor antagonists, which are novel therapeutic agents for treating insomnia, remains uncertain despite their escalating prevalence in clinical practice. We systematically searched four electronic databases from inception to April 17, 2024. In addition, we performed a quality assessment; calculated pooled odds ratios (ORs) to assess the relationship between the use of orexin receptor antagonists and the occurrence of falls or fractures; evaluated heterogeneity across the included studies; and conducted sensitivity analyses. The meta-analysis encompassed eight papers, comprising a total of 46,636 subjects. These papers included 5 case-control studies and 3 randomized controlled trials (RCTs), collectively encompassing ten studies. Analysis of the included case-control studies (pooled adjusted OR = 0.75, 95% confidence interval [CI] = 0.00–1.50, I2 = 66.2%, k = 3) and RCTs (OR = 0.68, 95% CI = 0.31–1.50, I2 = 45.9%, k = 5) indicated that the use of orexin receptor antagonists did not elevate the risk of falls. Similarly, analysis of the included case-control studies revealed no significant increase in the risk of fractures associated with the use of orexin receptor antagonists (pooled adjusted OR = 1.01, 95% CI = 0.82–1.20, I2 = 40.1%, k = 2). This meta-analysis suggests that the use of orexin receptor antagonists for treating insomnia does not escalate the risk of falls or fractures, although the data for lemborexant and daridorexant are limited. • The utilization of orexin receptor antagonists did not heighten the risk of falls. • The use of suvorexant did not elevate the risk of falls. • The use of orexin receptor antagonists did not increase the risk of fractures. [ABSTRACT FROM AUTHOR]

Progress in satellite technology places higher expectations on the design period and reliability of thermal control systems, especially for small satellites with high intensification. Here, a thermal analysis is conducted throughout the satellite development process, with thermal modeling serving as the foundation for thermal analysis in the early and formal design and test verification stages. As a result, designers are required to appreciate, penetrate, and properly apply thermal models for the development of satellite thermal systems. Thus, in this article, we reviewed the research and development of thermal model techniques, as well as the preparation of crucial parameters and means of simplification for accurate and fast solutions. In addition, a summary of the relevant application and state-of-the-art technologies such as uncertainty and sensitivity analysis, intelligent optimization design, and parameter correlation, was dedicated to promoting the comprehensive development and innovation of thermal analysis of satellites. [ABSTRACT FROM AUTHOR]

With the increasing number of hydropower plants under construction and proposed in Nepal, the country is anticipated to experience a surplus of hydropower that exceeds its peak load demand. This surplus electricity becomes particularly high during the wet seasons, when hydropower production reaches its maximum capacity. This research focuses on the mathematical modeling of an alkaline electrolyzer, specifically analyzing the stack performance and the electricity flow within the balance of plants required to support the stack operation. The developed model is then used to estimate the production cost of hydrogen by utilizing forecasted surplus electricity up until the year 2030. The output of the study is expected to help in the sustainable utilization of surplus hydropower in the country, thus enhancing the low carbon economic development path. The study shows that there is a significant opportunity for hydrogen production from surplus hydroelectricity, ranging from 91 ktonne/year to maximum, of 414 ktonne/year. The average levelized cost of hydrogen is estimated at 5.65 USD/kg. The cost can be further reduced if policy interventions like tax rebates and tariff rate subsidies are in place. • Hydrogen production system of an alkaline electrolyzer has been modeled. • Estimation of surplus electricity from installed capacity under demand profile. • Calculation of hydrogen costs using surplus electricity scenarios until 2030. • Sensitivity analysis of critical inputs affecting the hydrogen production cost. [ABSTRACT FROM AUTHOR]

In the feeding system for ruminants developed in 2018 by the French National Institute of Agricultural Research (INRA), the prediction of multiple animal responses is based on the integration of the characteristics of the animal and the available feedstuff characteristics, as well as the rationing objectives. In this framework, the characterization of feedstuffs in terms of net energy, digestible protein, and fill units requires information on their chemical composition, digestibility, and degradability. Despite the importance of these feed characteristics, a comprehensive assessment of their impact on the responses predicted by the INRA 2018 feeding system has not been carried out. Thus, our study investigated how variables predicted by the INRA feeding system (i.e., outputs) for dairy cows are affected by variation in feed characterization (i.e., inputs). We selected 5 input variables for the sensitivity analysis: CP, OM apparent digestibility (OMd), gross energy (GE), effective degradability of nitrogen assuming a passage rate of 6%/h (ED6_N), and true intestinal digestibility (dr_N) of nitrogen. A one-at-a-time sensitivity analysis was performed on predicted digestive, productive, and environmental output variables for dairy cows with 6 contrasted diets. These 6 diets were formulated to meet 95% of the potential daily milk production (37.5 kg) of a multiparous cow at wk 14 of lactation. The values of the 5 key input variables of each feedstuff were then randomly sampled around the INRA 2018 feed table values (reference point). The response of the output variable to the variation of the input variable was quantified and compared using the tangent value at the reference point and the normalized sensitivity coefficient. Among the major final output variables, CP and dr_N had the greatest impact on N excretion in urine (as a proportion of total fecal and urinary N excretion; UN/TN); OMd and GE had the greatest impact on N utilization efficiency (NUE; N in milk as proportion of intake N); and ED6_N had the greatest impact on milk protein yield (MPY). Additionally, CP, GE, and dr_N had the least effect on methane emission, OMd had the least effect on UN/TN, and ED6_N had the least effect on NUE. The responses of most output variables to ED6_N and dr_N variations were highly dependent on diet and were related to the ratio between protein truly digestible in the intestine (PDI; i.e., MP) and net energy for lactation (UFL; i.e., NE L) at the reference point of each diet. Overall, we were able to analyze the response of output variables to the variations of the input variables, using the tangent and its normalized value at the reference point. The predicted final outputs were more affected by variations in CP, GE, and OMd. The other 2 input variables, ED6_N and dr_N, had a smaller effect on the final output variables, but the responses varied between the diets according to their PDI/UFL ratio. Our present study was conducted using 6 representative diets for dairy cattle fed at their potential, but should be completed by the analysis of more diverse conditions. [ABSTRACT FROM AUTHOR]

Failure in cancer treatment often stems from drug resistance, which can manifest as either intrinsic (pre-existing) or acquired (induced by drugs). Despite extensive efforts, overcoming this resistance remains a challenging task due to the intricate and highly individualized biological mechanisms involved. This paper introduces an innovative extension of an already well-established mathematical model to account for tumour resistance development against chemotherapy. This study examines the existence and local stability of model solutions, as well as exploring the model asymptotic dynamics. Additionally, a numerical analysis of the optimal control problem is conducted using an objective functional. The numerical simulations demonstrate that a constant anti-angiogenic treatment leads to a concatenation of bang-bang and singular intervals in chemotherapy control, resembling a combined protocol comprising maximal tolerated dose and metronomic protocols. This observation lends support to the hypothesis that mean-dose chemotherapy protocols may help circumvent acquired drug resistance. Lastly, a sensitivity analysis is undertaken to scrutinize the dependence of model parameters on the outcomes of the previously examined therapeutic protocols. • We consider a heterogeneous tumour consisting of two cellular subpopulations: sensitive and resistant to chemotherapy. • We change the therapy paradigm from total tumour eradication to controlling tumour growth and preventing drug resistance. • An optimal chemotherapy scheduling directly penalizes the subpopulation of resistant cells. • Penalizing chemoresistance gives rise to singular controls, supporting the metronomic chemotherapy administration scheme. • Sensitivity analysis shows how the optimal control structure depends on model parameters and initial conditions. [ABSTRACT FROM AUTHOR]

The multi drug-resistant Neisseria gonorrhoeae has been classified by the World Health Organisation (WHO) as a high-priority global public health problem. This underlines the need for better understanding of the transmission dynamics and proposing an optimal intervention strategy to control the disease. In this article, a deterministic mathematical model for the transmission dynamics of gonorrhoea as an antibiotic resistant disease in a population with an imperfect vaccination is proposed and analysed. The model incorporates the classes of vaccinated individuals and individuals equipped with self protection interventions to reduce antibiotic resistant cases. The threshold parameter R 0 , the basic reproduction number, for the analysis of the model is calculated. In the given setting, the model exhibits a backward bifurcation for R 0 < 1. However, if the efficacy of the vaccine is 100% without a waning effect, the model is shown to be without a backward bifurcation and the disease-free equilibrium is globally asymptotically stable whenever R 0 < 1. The global sensitivity analysis of the model to variations in parameter values is also performed to determine the most influential parameters on the disease transmission. Moreover, the optimal control analysis of the full model is presented and the optimal intervention strategies are proposed. The proposed intervention strategies are shown to be able to control the disease within a relatively shorter period of time. Finally, numerical experiments are presented to support the theoretical analysis of the model. • Imperfect vaccination is not helpful to eradicate the disease from the population. • Awareness campaign about the antibiotic resistant strain can reduce the transmission of the disease. • Sensitive parameters for the transmission dynamics of the disease are identified. • With the use of the optimal control analysis, cost effective intervention measures are proposed. [ABSTRACT FROM AUTHOR]

Major depression is a public health problem facing the world. This study aimed to identify the risk factors for major depression and clarify their causal effects. Data from the National Health and Nutrition Examination Survey (NHANES). Multifactorial logistic regression analysis was used to calculate the effect of each variable on major depression. Subgroup analyses and interaction tests were conducted to observe the stability of the association between them. Nonlinear correlations were explored using restricted cubic spline plots. The causal effects of serum Klotho on major depression were assessed using Mendelian randomization (MR) analysis. A total of 8359 participated in the study. After adjusting for all covariates, the risk of having major depression was 1.47 times higher for each unit rise in serum Klotho (OR = 1.47, 95 % CI = 1.07–2.02; P = 0.0183). MR analysis showed no causal relationship between serum Klotho levels and risk of major depression (OR = 1.09, 95 % CI = 0.91–1.30; P = 0.4120). Sensitivity analysis verified the reliability of the results. Serum Klotho is positively associated with an increased risk of major depression in the U.S. population, but MR analyses did not show genetic causality between Klotho and major depression in individuals of European ancestry. Based on the results of the current study, no indication maintaining high levels of Klotho may increase the risk of major depression. The main limitation of this study is the inconsistency of the cross-sectional study and the MR population. • Serum Klotho was first observed as a risk factor for major depression, but MR findings suggest no causal relationship. • J-shaped association between serum Klotho and major depression. • This study combines comprehensive data from a large-sample cross-sectional survey and a genomic analysis system. • No indication that serum Klotho may help improve major depression. [ABSTRACT FROM AUTHOR]

Most of the scientific research is focused on KOH-based alkaline electrolysers, while NaOH-based ones are unexplored although they present interesting features. This paper presents a semi-empirical model developed in the Python environment to predict a NaOH-based alkaline electrolyser's performance to cover such a research gap and perform an optimisation procedure of electrochemical parameters. A sensitivity analysis has been carried out to study how its performance changes while varying the: i) NaOH content, ii) pressure, and iii) both. Separately, the best result has been obtained with a NaOH content and an operating pressure of 8% and 6.5 bar, respectively. Furthermore, the same values have been recorded even by varying both the NaOH content and the operating pressure. Specifically, a maximum average efficiency increase of 3.57% at 35 ° C , 0.17% at 40 ° C , and 3.74% at 35 ° C in the case of NaOH content, pressure, and both, respectively. [Display omitted] • A semi-empirical model of a NaOH-based alkaline electrolyser is developed. • Optimised electrochemical coefficients are obtained using non-linear regression. • A sensitivity analysis of a NaOH-based alkaline electrolyser is performed. • Optimal operating conditions, based on the cell temperature, are achieved. • Efficiency increase of 3.74% is obtained with NaOH content and pressure variation. [ABSTRACT FROM AUTHOR]

Combining synthetic aperture radar and optical imagery can effectively improve crop type identification. However, optical remote sensing imagery is limited by cloud contamination. In this study, fake optical images were generated using seven image-to-image translation methods and their performance in improving crop classification accuracies was evaluated. Although the sensitivity analysis of the classification models showed lower similarity between real and fake images in the near-infrared band compared to the green and red bands, a significant improvement was confirmed after adding fake images created by generative adversarial networks (GANs). In this study, we generated fake optical images using GAN–based SAR–optical image transformations and evaluated whether adding these fake optical images contributes to improving the accuracy of crop identification from SAR images. This was especially true for the signed attribute vector image-to-image transformation (SAVI2I) method, which was the most effective, achieving an overall accuracy (OA) of 81.3 % with an allocation disagreement (AD) of 11.8 % and a quantity disagreement (QD) of 6.9 %. In contrast, the OA, AD, and QD were respectively 75.9 %, 18.2 %, and 5.9 % when only vertical-horizontal polarization, vertical–vertical polarization, or the polarization ratio were applied. As a result, it was demonstrated that utilizing fake images generated through GAN–based SAR–optical image transformations is effective in improving the accuracy of crop identification from SAR images. [ABSTRACT FROM AUTHOR]

This study delves into the exploration of the dynamics of (3 + 1) -dimensional Painlevé integrable generalized model from different perspectives, which delineates the evolution of nonlinear phenomena in three spatial dimensions and one temporal dimension, displaying the remarkable Painlevé integrability property. The ϕ 6 -expansion technique is applied to extract traveling wave solutions in the form of Jacobi elliptic functions. To give physical insights of obtained solutions, we present these solutions through graphs such as 2D, 3D and contour plots. Further, to understand the planar dynamical system, we employ the concepts of bifurcation, chaos theory and sensitivity analysis. Bifurcation analysis reveals the dependence on the solution of a planar dynamical system at critical points. Additionally, the detection of chaotic movements in the perturbed dynamical system is achieved by detecting tools. Also the sensitivity analysis of the model is investigate by three distinct initial conditions. The findings are innovative, valuable and captivating for the readers in exploring this model. [ABSTRACT FROM AUTHOR]

This study focuses on the improvement of the tracking performance of space observation radar systems. Coherent radar systems usually provide an observation vector including four observables (range, range rate, azimuth, elevation) measured at a given epoch. Moreover, for some coherent radars, such as the TIRA system, it is possible to determine an additional parameter, the range rate, which is extracted from the collected complex amplitude. The tracking performance can be improved by increasing the observation parameter accuracy. The influence of each parameter on the overall tracking performance can be assessed by conducting a sensitivity analysis. The investigation shows that the best way to increase the accuracy of the state vector is by improving the angle estimates. The TIRA system is equipped with a tracking radar and an imaging radar. A powerful solution to improve the tracking performance is the realization of a multi-sensor data fusion between the two radars of the system. [ABSTRACT FROM AUTHOR]

A challenging SIR epidemiological dynamic model with harmonic rate of incidence and nonlinear rate of recovery is developed to examine the effects of available beds in hospitals and intervention decrease upon the propagation of viral disease. The incorporation of the harmonic mean as an incidence rate is the novelty of the present manuscript. The assumed incidence rate is less sensitive to the larger values of the variables and proves more advantageous for highly skewed data compared to the bi-linear and monod types of incidence rates. For model's stability, precise mathematical conclusions have been produced. The model has two states of equilibrium: an infection-free equilibrium (E 0) , whenever the threshold number assumes values less than one, and a disease-present state (E 1) , whenever R 0 > 1. We employ the principle of LaSalle invariance and Lyapunov's direct technique to demonstrate that the basic threshold quantity R 0 < 1 indicates the global asymptotic stability of E 0. Also whenever 1 < R 0 then the equilibrium point E 1 is stable, under specific parametric conditions. The optimal control strategies for the described model are chosen with the aid of maximum principle of Pontryagin. To support the analytical conclusions, some numerical results are presented. The study's findings show that the model can accurately reflect the complex dynamics of numerous epidemic diseases, resulting in a considerable decrease in infection transmission. [ABSTRACT FROM AUTHOR]

In this paper, the fractional space-time nonlinear Chen-Lee-Liu equation has been considered using various methods. The investigation of the transition from periodic to quasi-periodic behavior has been conducted using a saddle-node bifurcation approach. The paper reports the conditions of multi-dimensional bifurcations of dynamical solutions. Additionally, a direct algebraic method has been used to calculate various 2D and 3D solitonic structures of the equation, and an analysis of their accuracy and effectiveness has been conducted. Furthermore, the Galilean transformation has been used to convert the equation into a planar dynamical system, which is further utilized to obtain bifurcations and chaotic structures. Chaotic structures of perturbed dynamical system are observed and detected through chaos detecting tools such as 2D-phase portrait, 3D-phase portrait, time series analysis, multistability and Lyapunov exponents over time. Further, sensitivity behavior for a range of initial conditions, both perturbed and unperturbed. The results suggest that the investigated equation exhibits a higher degree of multi-stability. [ABSTRACT FROM AUTHOR]

A six-axis machining configuration is proposed to improve the surface quality and finishing efficiency of an aeroengine blisk. It flexibly enlarges the accessible interference-free space of the tool for finishing the full-shape surface, including the blade body, root, and hub surfaces. An error model for tool contact posture with respect to the kinematic axis errors is established, revealing the relationship between the kinematic deviation of the axes and resultant profile error. An improved Sobol method is applied for error sensitivity analysis to identify crucial error terms based on the quasi-Monte Carlo algorithm. In particular, an efficient error sensitivity index is proposed by combining a unified objective function to identify crucial error terms, followed by the simulations and cutting experiments for validation. As a result, the blade profile error was successfully suppressed by approximately 40 % in most. This work provides a fundamental framework for elevating the multi-axis machining accuracy of aeroengine blisk. • A six-axis machine tool has been proposed to achieve the full-shape-surface grinding on the blisk. • A constrained error sensitivity index model was proposed to compensate for key error terms. • Sensitivity analysis was conducted using an improved Sobol method incorporated quasi-Monte-Carlo algorithm. • The effectiveness of error sensitivity analysis and corresponding tool-path-based compensation were verified. [ABSTRACT FROM AUTHOR]

Respondent-driven sampling (RDS) is widely used to sample populations with higher risk of HIV infection for whom no sampling frames exist. However, few studies have been done to assess the reliability of RDS in real world settings. We assessed the reliability of naïve RDS samples using five rounds of the National HIV Behavioral Surveillance – People Who Inject Drugs surveys in Newark, New Jersey from 2005 to 2018. Specifically, we compared the distributions of time-insensitive demographic characteristics in temporally adjacent RDS samples with Monte Carlo Two-Sample Kolmogorov-Smirnov Test with 100,000 replicates. The distributions of time-sensitive demographic characteristics were also compared as sensitivity analyses. The study showed that repeated RDS samples among people who inject drugs in the greater Newark area, New Jersey were reliable in most of time-insensitive demographics and recruitment homophily statistics. Sensitivity analyses of time-sensitive demographics also presented consistencies in most of temporally adjacent samples. In conclusion, RDS has the potential to provide reliable samples, but demographic characteristics of RDS samples may be easily biased by homophily. Future studies using RDS may need to pay more attention to potential homophily bias and consider necessary diagnostic procedures and sample adjustments. [ABSTRACT FROM AUTHOR]

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of NASA's state-of-the-art Probabilistic Asteroid Impact Risk (PAIR) model. PAIR's remarkable capability to handle a broad spectrum of entry conditions and a high volume of scenarios establishes it as our reference model, with PAIR estimates assumed ground truth and used to train, test, and validate the machine learning models. The ML models, initially trained with PAIR's primitive input variables, are then further enhanced with engineered features to improve the performance of interpretable models. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler, interpretable linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with less than 10% average relative errors for radii greater than 100 km. The CPU time is decreased by a factor O(1 0 3 ) compared to the PAIR model, enabling the simulation of millions of scenarios within minutes on a local computer. Beyond serving as surrogate models, we incorporate the machine learning models into a comprehensive Shapley sensitivity analysis, yielding a ranking of entry parameters based on their contributions to ground damages. These results offer valuable insights for prioritizing observation missions. • Machine learning models enable accurate and rapid simulations of asteroid hazards. • Data-driven methods can assess the radius of damaged areas with 10% average errors. • Models provide insights on the relative importance of entry parameters. • Risk studies can be performed on local machines instead of supercomputers. [ABSTRACT FROM AUTHOR]

The water hammer, resulting from sudden valve closures or similar operations, is a primary cause of leakage and damage in fluid-conveying pipe systems. This work aims to investigate the reliability sensitivity of fluid-conveying pipes under the water hammer. A reliability model for the fluid-conveying straight pipe, involving uncertainty and fluid-structure interaction, is developed based on the stress-strength interference theory. Then the method of characteristics is employed to analyze the nonlinear behaviors of the pipe. To avoid excessive model evaluations, the Kriging surrogate strategy is used to evaluate rapidly the statistics of nonlinear responses. Furthermore, the Kriging model coupled with the single-loop Monte Carlo simulation is presented for estimating reliability sensitivity indices. The accuracy of results is verified by the Monte Carlo simulation. The results reveal that the proposed method is feasible for the reliability sensitivity analysis of fluid-conveying pipe under the water hammer. Moreover, the wall thickness has the most obvious influence on stress failure, followed by the inner radius, while the pipe length, Young's modulus, density of the pipe material, and Poisson ratio show a low effect. This work can not only guide the safety design of pipe but also enrich the theory and application of statistical analysis and reliability sensitivity evaluation for liquid-conveying pipe systems. • A reliability model for water hammer-induced failure of fluid-conveying pipe is developed. • The reliability model is proposed, incorporating uncertainty and fluid-structure interaction. • The Kriging-based strategy is employed to estimate the response and reliability sensitivity of the pipe. • Different input variables have diverse effects on the nonlinear behavior and reliability of the pipe. [ABSTRACT FROM AUTHOR]

A previous cost-effectiveness analysis published in 2022 found that the Total Posterior Spine (TOPSTM) system was dominant over transforaminal lumbar interbody fusion (TLIF). This analysis required updating to reflect a more complete dataset and pricing considerations. To evaluate the cost-effectiveness of TOPSTM system as compared with TLIF based on an updated and complete FDA investigational device exemption (IDE) data set. Cost-utility analysis of the TOPSTM system compared to TLIF. A multicenter, FDA IDE, randomized control trial (RCT) investigated the efficacy of TOPSTM compared to TLIF with a current population of n=305 enrolled and n=168 with complete 2-year follow-up. Cost and quality adjusted life years (QALYs) were calculated to determine our primary outcome measure, the incremental cost-effectiveness ratio. Secondary outcome measures included: net monetary benefit as well at willingness-to-pay (WTP) thresholds. The primary outcome of cost-effectiveness is determined by incremental cost-effectiveness ratio. A Markov model was used to simulate the health outcomes and costs of patients undergoing TOPSTM or TLIF over a 2-year period. alternative scenario sensitivity analysis, one-way sensitivity analysis, and probabilistic sensitivity analysis were conducted to assess the robustness of the model results. The updated base case result demonstrated that TOPSTM was immediately and longitudinally dominant compared with the control with an incremental cost-effectiveness ratio of −9,637.37 $/QALY. The net monetary benefit was correspondingly $2,237, both from the health system's perspective and at a WTP threshold of 50,000 $/QALY at the 2-year time point. This remained true in all scenarios tested. The Alternative Scenario Sensitivity Analysis suggested cost-effectiveness irrespective of payer type and surgical setting. To remain cost-effective, the cost difference between TOPSTM and TLIF should be no greater than $1,875 and $3,750 at WTP thresholds of $50,000 and 100,000 $/QALY, respectively. This updated analysis confirms that the TOPSTM device is a cost-effective and economically dominant surgical treatment option for patients with lumbar stenosis and degenerative spondylolisthesis compared to TLIF in all scenarios examined. [ABSTRACT FROM AUTHOR]

In this paper, a diabatic compressed air energy storage system fueled by a natural gas/hydrogen mixture that integrates heating and power generation is proposed. A comprehensive thermodynamic analysis has been conducted to identify the key factors influencing system performance and elucidate the detailed formation and distribution patterns of irreversible losses when utilizing a hydrogen-natural gas blend as fuel in the proposed system. The research results indicate that increasing the hydrogen blending ratio from 0.5 to 1 lead to greater enhancements in roundtrip efficiency (∼1.08% vs. ∼0.33%), exergy efficiency (∼3.88% vs. ∼1.15%), and energy density (∼1.24% vs. ∼0.42%) compared to an increase from 0 to 0.5. The combustor suffers the largest exergy destruction proportion, with a notable reduction in exergy destruction achieved through increased hydrogen blending. System performance benefits significantly from higher combustor outlet temperatures and expansion ratios at various hydrogen blending ratios. The rate of change in exergy efficiency (∼42.76% vs. ∼83.17%) and energy density (∼58.83%) demonstrates an inverse correlation with the varied parameters (1100–1500K, 4–8), except for the rate of change in energy density (∼6.76%), which displays a positive relationship with the combustor outlet temperature. Notably, a significant decrease in the rate of change in roundtrip efficiency (∼1.87% vs. ∼6.64%) is observed within a specific parameter range (1400–1500K, 5–6). Sensitivity analysis identifies the combustor outlet temperature as the most influential factor in enhancing system performance, consistently showing positive effects of the hydrogen blending ratio. [Display omitted] • A natural gas/hydrogen-fueled CAES system combined heating and power is proposed. • Increasing the hydrogen contents significantly reduces combustor exergy destruction. • Higher hydrogen content (>0.5) yields notable performance boosts, especially in EXE. • The ROC s infected by ER display a remarkable correlation compared to the COT. • The COT is the crucial parameter on system performance via sensitivity analysis. [ABSTRACT FROM AUTHOR]

Fuel cell behavior is characterized by important electric and kinetic parameters such as charge transfer coefficient, exchange current density and ohmic resistance. The quantitative estimate of these parameters by a semi-empirical approach without resorting to the sophisticated and costly methods like AC Impedance spectroscopy is presented in this paper. A fuel cell model that describes voltage-current density behavior is utilized to acquire the fuel cell parameters by using two different kinds of fitting procedures. A set of equations suitable for fitting various regions of voltage-current density variation are proposed and the criteria used to assess the quality of fit is uniformly applied to all the fitting procedures. The importance of leakage current as a parameter is also discussed by presenting improved form of fuel cell model. The model is fitted on the DC Impedance (Polarization) curve experimental data obtained for liquid feed passive Direct Methanol Fuel Cell (DMFC) at different methanol feed concentration and the operating torque. After establishing the applicability of the model and the proposed fitting procedure, a detailed sensitivity analysis is conducted to demonstrate the reliability of the model. The sensitivity analysis, along with an independent parameter sensitivity method is used to study the impact of individual model parameters on fitting criteria. The results showed higher sensitivity ratio (SR) for the model equation as compared to the sensitivity analysis for a given assumed value of charge transfer coefficient. Also, the fitted curve on experimental data shows nearly same Sum of Squared Residue (SSR) for two kinds of fitting procedures. The 95% confidence intervals for all the fuel cell parameters were presented and analyzed. The ohmic resistance and exchange current density obtained by improved form of model equation were validated by the experimental data in the literature. The deviation and dispersion behavior of important parameters of charge transfer coefficient and ohmic resistance are thoroughly studied for various kinds of variation types, percentage of points and the type of method. Finally, the trends of the sensitivity factor based on the value of model parameter were analyzed. The importance of the present model in obtaining valuable information regarding the fuel cell behavior under different operating conditions is presented. [Display omitted] • A simple semi-empirical method for estimation of kinetic and electric parameters of the fuel cell is developed. • Normal equations and well-defined objective function have been used for fitting. • Experimental I–V curve is used for fitting and EIS-ohmic resistance is utilized for validation. • Sensitivity analysis accompanied with parameter sensitivity method are used to establish the validity of the model and fitting procedure. • Estimation of important fuel cell parameters without resort to sophisticated AC Impedance techniques is a novel feature. [ABSTRACT FROM AUTHOR]

The Proton Exchange Membrane Fuel Cell - Mechanical Heat Pump - Combined Heat and Power (PEMFC-MHP-CHP) system is a reliable energy supply solution, which can operate independently of the grid during emergencies or be used for peak shaving and load leveling in renewable energy networks. This paper proposes two system structures, namely the separated and integrated systems and establishes MATLAB/Simulink models. Then, a sensitivity analysis is conducted, examining system design and operation. The results show that the separated system can satisfy basic heating and electricity demands without an external power supply at −14.5 °C. Increasing the number of cells by 20, reducing one room's heat load (36 m2), or increasing the current density by 0.1 A/cm2 results in reductions in compressor power consumption ranging from 1.76 % to 2.91 %, 7.42 %–10.57 %, and 6.52 %–16.88 %, respectively. On the other hand, the integrated system has higher power consumption but can operate smoothly at lower temperatures than the separated system. It is suitable for integration with auxiliary power devices in low-temperature environments. The PEMFC's heat output minimally affects system efficiency. Reducing the number of rooms improves system performance, with each reduction of one room decreasing compressor power consumption by 5.43 %–8.55 %. Meanwhile, two design options are identified based on the power supply and hot water demands. Further research and development can enhance the efficiency and performance of these systems, promoting their wider use in the future. • Established MATLAB/Simulink models for the PEMFC-MHP-CHP system. • Demonstrated better performance and stable heating capacity compared to conventional CHP systems. • Provided insights into advantages and limitations of separated and integrated systems. • Conducted a thorough performance analysis under load fluctuations for energy supply and peak shaving. • Proposed system design and operational options based on sensitivity analysis. [ABSTRACT FROM AUTHOR]

The ignition of lean hydrogen-air mixtures behind reflected shock waves at the temperature range of 902–1630 K and the pressure of 1 atm is studied experimentally and numerically. For the first time, reliable experimental data is obtained for temperatures below 1000 K, directly in the zone of change in the dominance of chain branching and chain termination reactions, which influence the formation of the ignition delay value. Expressions are formulated for ignition delay in two temperature intervals below and above 970–980 K, and the corresponding activation energy values are determined. Good agreement between the experimentally observed and calculated ignition delay values is demonstrated. The local sensitivity analysis allowed us to reduce the kinetic mechanism. • The new data on ignition of lean H 2 -air mixtures at the T of 902–1630 K and the P of 1 atm is presented. • Correlation expressions for ignition delay in two temperature intervals are formulated. • Good agreement between the experimentally observed and calculated ignition delay values is demonstrated. • The reactions determining the kinetic mechanisms of ignition delay formation of lean H 2 -air mixtures are identified. • Reduced kinetic mechanism is presented. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient computational strategy to deal with uncertainty propagation problems for the Navier–Stokes equations coupled with a temperature equation based on a sensitivity analysis technique model. Sensitivity analysis allows one to investigate how the model response in a point is affected by a change in the boundary conditions on the temperature, the heat capacity, the thermal conductivity, and the thermal diffusivity under the hypothesis of a small variance of the input parameters. The variance can be estimated with just one simulation of the state and as many simulations of the sensitivity as there are uncertain parameters. We focused on the benchmark problem of natural convection in a square cavity, also known as the de Vahl Davis problem. Various areas of the domain were analysed to determine the relative influence of each parameter on temperature and velocity. We use the open-source code TrioCFD to simulate the state equations and a specific module is developed for the sensitivity equations. [ABSTRACT FROM AUTHOR]

This research aimed to develop best-practice recommendations for identifying the "standard of care" (SoC) and integrate it when it is the comparator in diagnostic economic models (SoC comparator). A multi-methods approach comprising 2 pragmatic literature reviews and 9 expert interviews was used. Experts rated their agreement with draft recommendations based on the authors' analysis of the reviews. These were refined iteratively to produce final recommendations. Fourteen best-practice recommendations are provided. Care pathway mapping (using quantitative, qualitative, or mixed-methods approaches) should be used for identifying the SoC comparator. Guidelines analysis can be integrated with expert opinion to identify pathway variability and discrepancies from clinical practice. For integrating the SoC comparator into the model, recommendations around structure, input sourcing, data aggregation and reporting, input uncertainty, and model variability are presented. For example, modelers should consider that the reference standard is not synonymous with the SoC, and the SoC may not be the only comparator. The comparator limitations should be discussed with clinical experts, but elicitation of its diagnostic accuracy is not recommended. Probabilistic sensitivity analysis is recommended when evaluating the overall input uncertainty, and deterministic sensitivity analysis is useful when there is high model uncertainty or SoC variability. Consensus could not be reached for some topics (eg, the role of real-world data, model averaging, and alternative model structures), but the reported discussions provide points for consideration. To our knowledge, this is the first guidance to support modelers when identifying and operationalizing the SoC comparator in diagnostic cost-effectiveness models. • Modeling the cost-effectiveness requires a comparison of the new diagnostic and patient management strategy with a comparator, often a complex standard of care (SoC) pathway. The new diagnostic test can replace or, more commonly, be integrated with the diagnostic SoC pathway. This presents 2 main challenges in obtaining useful estimates of cost-effectiveness: (1) identifying the diagnostic SoC pathway to define the comparator and (2) integrating it into the model. • We identified possible methodological approaches through pragmatic literature reviews and expert interviews. Some examples are to identify the SoC comparator via mapping the care pathway through qualitative, quantitative, or mixed-methods approaches; to select data on the diagnostic accuracy of the SoC comparator from studies in which the reference standard is the one used for the new test and report detailed information of the data source; and to assess the impact of the SoC pathway variability through scenario analysis. • We provide 14 recommendations that can support modelers to minimize the risk of a misrepresentation of the incremental clinical utility of the new diagnostic test because of the uncertainty and variability of the SoC comparator. We identified practice recommendations, gaps in knowledge, and areas where further research would advance the field. [ABSTRACT FROM AUTHOR]

In order to explicitly and smoothly implement fluid-based topology optimization for improving the performance and manufacturing efficiency of flow systems, the moving morphable void (MMV) method is employed to optimize the steady-state navier-stokes (NS) flow for minimizing the dissipation energy under a volume constraint. To this end, a MMV-based Brinkman term is proposed to penalize the velocity in solid area, which can expand the region controlled by the NS flow equilibrium equation from fluid to whole design domain, and can also establish the relationship between design variables and governing equations. Then, a MMV-based optimization model of NS flow is proposed and the design variables are updated by the method of moving asymptotes according to the sensitivity analysis. In benchmark examples, we can precisely track the topology boundary with detailed geometric information without the intuitive geometric judgement error. Also, by means of contrasting the results of proposed method with previous work, the effectiveness and advantages of the MMV method can be confirmed. [ABSTRACT FROM AUTHOR]

Efficient and precise optimisation methodologies, when applied to improve the real performance of engineering devices, must balance the need to reduce high computational cost and maintain accuracy in the treatment of first principles and physicochemical properties. This is the aim of the time– and parameter–adaptive model order reduction technique presented in this article. In contrast to (standard) pre–processed reduced order models (ROMs), the proposed adaptive strategy presents two principal advantages: (i) it does not require any previous information to derive an accurate ROM, which provides a substantial acceleration of solution calculations, and (ii) the periods of full order model calculations can be further reduced when information needed by the optimisation algorithms to derive ROM updates is provided by the previous simulations. Its implementation within the framework of efficient gradient–like optimisation methods requires a careful analysis of the sensitivities computation in order to resolve certain issues inherent to adaptive ROMs. The proposed technique is applied to the optimisation of the performance of a three–dimensional lithium–ion cell described by the electrochemical pseudo–four–dimensional battery model (p4D model). In particular, the results obtained when maximising the energy delivered by a graphite–NMC811 cell and a graphite–LFP cell demonstrate the robustness and efficacy of the method. The presented methodology has been implemented in a software tool named OptiBat, developed in the framework of a H2020 project, and available in the project website https://defacto-project.eu/defacto-rom-optimisation-tool/. [ABSTRACT FROM AUTHOR]

The clinical profiles of methamphetamine-induced psychosis (MIP) and schizophrenia are largely overlapping making differentiation challenging. In this systematic review and meta-analysis, we aim to compare the positive and negative symptoms of MIP and schizophrenia to better understand the differences between them. In accordance with our pre-registered protocol (CRD42021286619), we conducted a search of English-language studies up to December 16th, 2022, in PubMed, EMBASE, and PsycINFO, including stable outpatients with MIP and schizophrenia. We used the Newcastle-Ottawa Scale to measure the quality of cross-sectional, case-control, and cohort studies. Of the 2052 articles retrieved, we included 12 studies (6 cross-sectional, 3 case-control, and 2 cohort studies) in our meta-analysis, involving 624 individuals with MIP and 524 individuals with schizophrenia. Our analysis found no significant difference in positive symptoms between the two groups (SMD, −0.01; 95%CI, −0.13 to +0.11; p = 1). However, individuals with MIP showed significantly less negative symptoms compared to those with schizophrenia (SMD, −0.35; 95CI%, −0.54 to −0.16; p = 0.01; I2 = 54 %). Our sensitivity analysis, which included only studies with a low risk of bias, did not change the results. However, our meta-analysis is limited by its cross-sectional approach, which limits the interpretation of causal associations. Furthermore, differences in population, inclusion criteria, methodology, and drug exposure impact our findings. Negative symptoms are less prominent in individuals with MIP. While both groups do not differ regarding positive symptoms, raises the possibility of shared and partly different underlying neurobiological mechanisms related to MIP and schizophrenia. [ABSTRACT FROM AUTHOR]

High-occupancy vehicle (HOV) lanes, which exclusively allow vehicles with two or more travelers on board to enter, has been recognized as a promising and practical way to motivate travelers to carpool. However, in the presence of ride-sourcing services, ride-sourcing vehicles with one driver and one (or more) passenger on board also meet the vehicle requirements of HOV lanes. So instead of encouraging travelers to carpool, HOV lanes may benefit ride-sourcing users and stimulate ride-sourcing demand. In this paper, in a single-corridor network with both HOV lanes and general purpose (GP) lanes, we model travelers' mode choices among transit, driving alone, ride-sourcing, and carpool, and delineate travelers' lane choices at user equilibrium, with the travel time of GP/HOV lanes and the carpool price being endogenously determined. With numerical examples, we show that the occupation of HOV lanes by ride-sourcing vehicles will greatly reduce the time saving on HOV lanes, thus lower the attractiveness of carpool, and increase the total travel time cost on the corridor. To solve this problem, we propose to implement an additional tolling scheme on HOV lanes, so that carpool users can split the toll evenly, while ride-sourcing riders have to pay the toll alone. As shown by numerical examples, the optimal tolling scheme can effectively reduce the occupancy of ride-sourcing vehicles on the HOV lane and encourage users to carpool. And the impacts of the ride-sourcing price, driving car cost and the HOV lane capacity ratio on the effectiveness of the proposed hybrid toll and HOV strategies are examined through sensitivity analysis. • Model the impacts of HOV lane on ride-sourcing and carpool demand. • Reveal the phenomena that HOV lanes may stimulate ride-sourcing demand. • Reveal how ride-sourcing vehicles on the HOV lane discourage carpool demand. • Propose tolling and tradable credit schemes to improve the HOV-lane efficacy. [ABSTRACT FROM AUTHOR]

Building integrated photovoltaic thermal (BIPV/T) systems offer a highly effective means of generating clean energy for both electricity and heating purposes in residential buildings. Hence, this article introduces a new BIPV/T system to optimally minimize the energy consumption of a household residential building. The meticulous design of the proposed BIPV/T system is accomplished through MATLAB/Simulink® dynamic modeling. Performance analysis for the BIPV/T system is performed under different seasonal conditions with in-depth techno-economic analyses to estimate the expected enhancement in the thermal, electrical, and economic performance of the system. Moreover, a sensitivity analysis is conducted to explore the impact of various factors on the energetic and economic performances of the proposed BIPV/T system. More so, the two-layer feed-forward back-propagation artificial neural network modeling is developed to accurately predict the hourly solar radiation and ambient temperature for the BIPV/T. Additionally, a multi-objective optimization using the NSGA-II method is also conducted for the minimization of the total BIPV/T plant area and maximization of the total efficiency and net thermal power of the system as well as to estimate the optimized operating conditions for input variables across different seasons within the provided ranges. The sensitivity analysis revealed that higher solar flux levels lead to increased electric output power of the BIPV/T plant, but total efficiency decreases due to higher thermal losses. Moreover, the proposed NSGA-II shows a feasible method to attain a maximum net thermal power and optimal total efficiency of 5320 W and 63% with a minimal total plant area of 32.89 m2 that attained a very low deviation index from the ideal solution. The levelised cost of electricity is obtained as 0.10 $/kWh under the optimal conditions. Thus, these findings offer valuable insights into the potential of BIPV/T systems as a sustainable and efficient energy solution for residential applications. [ABSTRACT FROM AUTHOR]

As the global market develops for green hydrogen and ammonia derived from renewable electricity, the bulk transmission of hydrogen and ammonia from production areas to demand-intensive consumption areas will increase. Repurposing existing infrastructure may be economically and technically feasible, but increases in supply and demand will necessitate new developments. Bulk transmission of hydrogen and ammonia may be effected by dedicated pipelines or liquefied fuel tankers. Transmission of electricity using HVDC lines to directly power electrolysers producing hydrogen near the demand markets is another option. This paper presents and validates detailed cost models for newly-built dedicated offshore transmission methods for green hydrogen and ammonia and carries out a techno-economic comparison over a range of transmission distances and production volumes. New pipelines are economical for short distances, while new HVDC interconnectors are suited to medium-large transmission capacities over a wide range of distances, and liquefied gas tankers are best for long distances. [Display omitted] • Future hydrogen and ammonia markets will require new-build long-distance transmission. • Energy may be transmitted in dedicated pipelines, liquid tankers or by HVDC lines. • Levelised cost of transmission depends on the transferred quantity and the distance. • Pipelines are the best option over short distances for hydrogen and ammonia. • HVDC has lowest cost for medium distances, tankers are suitable for long distances. [ABSTRACT FROM AUTHOR]