Search Results (405)

Background: Rock–blast design is a canonical inverse problem that joins elastodynamic partial differential equations (PDEs), fracture mechanics, and stochastic heterogeneity. Objective: Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a systematic review of mathematical methods for geomechanically informed blast modelling and optimisation is provided. Methods: A Scopus–Web of Science search (2000–2025) retrieved 2415 records; semantic filtering and expert screening reduced the corpus to 97 studies. Topic modelling with Bidirectional Encoder Representations from Transformers Topic (BERTOPIC) and bibliometrics organised them into (i) finite-element and finite–discrete element simulations, including arbitrary Lagrangian–Eulerian (ALE) formulations; (ii) geomechanics-enhanced empirical laws; and (iii) machine-learning surrogates and multi-objective optimisers. Results: High-fidelity simulations delimit blast-induced damage with ≤0.2 m mean absolute error; extensions of the Kuznetsov–Ram equation cut median-size mean absolute percentage error (MAPE) from 27% to 15%; Gaussian-process and ensemble learners reach a coefficient of determination ($R^2>0.95$) while providing closed-form uncertainty; Pareto optimisers lower peak particle velocity (PPV) by up to 48% without productivity loss. Synthesis: Four themes emerge—surrogate-assisted PDE-constrained optimisation, probabilistic domain adaptation, Bayesian model fusion for digital-twin updating, and entropy-based energy metrics. Conclusions: Persisting challenges in scalable uncertainty quantification, coupled discrete–continuous fracture solvers, and rigorous fusion of physics-informed and data-driven models position blast design as a fertile test bed for advances in applied mathematics, numerical analysis, and machine-learning theory. Full article

Metaheuristics are powerful optimization techniques that are well-suited for addressing complex combinatorial problems across diverse scientific and industrial domains. However, their application to computationally expensive problems remains challenging due to the high cost and significant number of fitness evaluations required during the search process. Surrogate modeling has recently emerged as an effective solution to reduce these computational demands by approximating the true, time-intensive fitness function. While surrogate-assisted metaheuristics have gained attention in recent years, their application to complex scheduling problems such as the Permutation Flowshop Scheduling Problem (PFSP) under learning, deterioration, and maintenance effects remains largely unexplored. To the best of our knowledge, this study is the first to investigate the integration of surrogate modeling within the artificial bee colony (ABC) framework specifically tailored to this problem context. We develop and evaluate two distinct strategies for integrating surrogate modeling into the optimization process, leveraging the ABC algorithm. The first strategy uses a Kriging model to dynamically guide the selection of the most effective search operator at each stage of the employed bee phase. The second strategy introduces three variants, each incorporating a Q-learning-based operator in the selection mechanism and a different evolution control mechanism, where the Kriging model is employed to approximate the fitness of generated offspring. Through extensive computational experiments and performance analysis, using Taillard’s well-known standard benchmarks, we assess solution quality, convergence, and the number of exact fitness evaluations, demonstrating that these approaches achieve competitive results. Full article

The insulin-like growth factor binding protein, acid-labile subunit (IGFALS), plays a crucial role in glucose metabolism and immune regulation, key processes in recovery from surgery. Here, we studied the perioperative serum IGFALS dynamics and explored potential clinical implications. A total of 79 patients undergoing elective cardiac surgery with implementation of cardiopulmonary bypass had their serum isolated at baseline, 24 h, seven days, and three months postoperatively to assess serum concentrations of IGFALS and insulin growth factor 1 (IGF-1). Markers of perioperative injury included troponin I (TnI), high-mobility group box 1 (HMGB-1), and heat shock protein 60 (Hsp-60). Inflammatory status was assessed via interleukin-6 (IL-6) and interleukin-8 (IL-8). Additionally, we measured in vitro cytokine production to viral stimulation of whole blood and monocytes. Surrogates of neuronal distress included neurofilament light chain (NF-L), total tau (τ), phosphorylated tau at threonine 181 (τp181), and amyloid β40 and β42. Renal impairment was defined by RIFLE criteria. Cardiac dysfunction was denoted by serum N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. Serum IGFALS levels declined significantly after surgery and remained depressed even at 3 months. Administration of acetaminophen and acetylsalicylic acid differentiated IGFALS levels at the 24 h postoperatively. Serum IGFALS 24 h post-operatively correlated with production of cytokines by leukocytes after in vitro viral stimulation. Serum amyloid-β1-42 was significantly associated with IGFALS at baseline and 24 h post-surgery Patients discharged home had higher IGFALS levels at 28 days and 3 months than those discharged to healthcare facilities or who died. These findings suggest that IGFALS may serve as a prognostic biomarker for recovery trajectory and postoperative outcomes in cardiac surgery patients. Full article

Background: To identify drug candidates that reduce cellular stress, linear peptides known as endomorphin (EM) analogs containing proline surrogates in position 2 were tested in in vitro injury models induced by corticosterone (CORT). Methods: In this study, neuroblastoma (SH-SY5Y) cells were treated with CORT and synthesized peptides, and then the cell viability and morphology, reactive oxygen species production (ROS), mitochondrial membrane potential (ΔΨm), adenosine triphosphate (ATP), and intracellular calcium ion [Ca²⁺]_i levels were evaluated. We also conducted an in-depth analysis of the apoptosis markers using quantitative real-time PCR (qPCR). Finally, we explore the brain-derived neurotrophic factor (BDNF) expression (qPCR) and protein levels (ELI-SA and Western blot). Results: The strongest neuroprotective effect in the CORT-induced stress model was shown by peptide 3 and peptide 7 (in the following sequence Tyr-Inp-Trp-Phe-NH2 and Tyr-Inp-Phe-Phe-NH2, respectively). These peptides significantly improved cell viability and reduced oxidative stress in CORT-treated cells. Conclusions: Their neuroprotective potential appears linked to anti-apoptotic effects, along with in-creased BDNF expression. Moreover, in the lipopolysaccharide (LPS)- and interferon-γ (IFN-γ)-induced damage model in macrophage RAW 264.7 cells, these two peptides reduced the secretion of inflammatory mediators nitric oxide (NO), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6). Peptides exhibiting both neuroprotective and anti-inflammatory properties warrant further investigation as potential therapeutic agents. Full article

A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high levelized cost of energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor’s performance, the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function is provided by the definition of a surrogate model (SM). An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea. Full article

Nitrifying bacteria, including ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB), are players in the nitrogen cycle but pose serious health risks when colonizing drinking water distribution networks (DWDNs). While the global impact of these bacteria is increasingly recognized, a significant research gap remains concerning their effects in tropical regions, particularly in developing countries. This study aims to bridge that gap by systematically reviewing the existing literature on nitrifying bacteria in DWDNs, their behavior in biofilms, and associated public health risks, particularly in systems reliant on surface water sources in tropical climates. Using the PRISMA guidelines for systematic reviews, 51 relevant studies were selected based on content validity and relevance to the research objective. The findings highlight the critical role of nitrifying bacteria in the formation of nitrogenous disinfection by-products (N-DBPs) and highlight specific challenges faced by developing countries, including insufficient monitoring and low public awareness regarding safe water storage practices. Additionally, this review identifies key surrogate indicators, such as ammonia, nitrite, and nitrate concentrations, that influence the formation of DBPs. Although health risks from nitrifying bacteria are reported in comparable studies, there is a lack of epidemiological data from tropical regions. This underscores the urgent need for localized research, systematic monitoring, and targeted interventions to mitigate the risks associated with nitrifying bacteria in DWDNs. Addressing these challenges is essential for enhancing water safety and supporting sustainable water management in tropical developing countries. Full article

The objective of this study was to evaluate the time-course of incubation for the potential preventative mitigation of megaviruses using Termin-8 (a formaldehyde-based product) and Finio (non-formaldehyde solution) from Anitox. Emiliania huxleyi virus (EhV), an algal surrogate for African swine fever virus (ASFV), was treated with the recommended concentrations of Termin-8 (0.1% to 0.3%) and Finio (0.05% to 0.2%), and both viability qPCR (V-qPCR) and standard PCR (S-qPCR) were used to quantify EhV concentrations at 1 h, 5 h, 24 h and day 7 post-inoculation. Overall, Finio, and to a lesser extent Termin-8, at their highest treatment concentrations, showed the greatest log reduction of 4.5 and 2 log₁₀ units, respectively, at 1 h post-inoculation. Although Termin-8 efficacy did not improve with time, due to its fixing of viral particles and rendering them non-infectious, treatment with Finio showed 100% viable viral inactivation (>5 log₁₀ reduction units) at the lowest concentration after 7 days of exposure. Our results demonstrate that both Termin-8 and Finio can be used as effective chemical mitigants against megaviruses such as EhV and ASFV and can be used as effective preventive or mitigation strategies to prevent the transmission of ASFV by reducing particle viability in contaminated feed, although additional research is warranted. Full article

The production of hydroponic fresh produce presents unique food safety and intervention challenges. A systematic approach was used to map and characterize the evidence on hydroponic food safety. Quantitative data describing the effectiveness of intervention studies were extracted, synthesized, and assessed for quality. A search of electronic databases yielded 131 relevant papers related to hydroponic food safety. Thirty-two studies focusing on food safety interventions reported 53 different interventions using chemical (n = 39), physical (n = 10), multiple-hurdle (n = 2), and biological (n = 2) approaches. Human pathogen indicators and surrogates were most often studied (n = 19), while pathogenic strains like Salmonella spp. (n = 9), Shiga toxin-producing Escherichia coli (STEC) (n = 5), Listeria monocytogenes (n = 2), and viruses (Hepatitis A virus (HAV), n = 1; norovirus (NoV), n = 1) were studied less frequently. Of fourteen articles (43.8%) investigating pre-harvest interventions, most (42.9%) did not specify the hydroponic system type. Gaps remain in the available evidence regarding the efficacy of interventions for controlling human pathogens in near-commercial hydroponic systems. The quality assessment revealed a significant lack of detailed reporting on methods and outcomes, making it difficult to translate the findings into practical recommendations for the industry; therefore, this review provides recommendations for the scientific community to improve future research design and reporting in this field. Full article

The accuracy of the blade pitch angle (BPA) motion in controllable pitch propellers (CPPs) is considered crucial for the efficacy and reliability of marine propulsion systems. The pitch adjustment process of CPPs is highly complex and influenced by various uncertain factors. A parametric kinematic model for the pitch adjustment process for CPPs was established, incorporating the geometric dimensions and material surface friction coefficients caused during workpiece production as uncertainty parameters. The aim was to establish the correspondence between these uncertainty parameters and the BPA of CPPs. A large dataset was generated by batch calling on Adams. Based on the collected dataset, five surrogate models (e.g., deep neural network (DNN), Kriging, support vector regression (SVR), random forest (RF), and polynomial chaos expansion Kriging (PCK)) were constructed to predict the BPA. Among these, the DNN approach demonstrated the highest prediction accuracy. Accordingly, the influence of uncertainties on the BPA was investigated using the DNN model, focusing on variations in the slider width, crank pin diameter, crank disc diameter, piston rod–slider friction coefficient, crank pin–slider friction coefficient, and hub bearing–crank disc friction coefficient. The high-fidelity model established in this study can replace the kinematic model of the CPP pitch adjustment process, significantly improving computational efficiency. The research findings also provide important references for the design optimization of CPPs. Full article

Waste biomass gasification can contribute to the production of alternative and environmentally sustainable green fuels. Research at the CREC–UWO (Chemical Reactor Engineering Center–University of Western Ontario) considers an integrated gasification process where both electrical power, biochar, and tar-free syngas suitable for alcohol synthesis are produced. In particular, the present review addresses the issues concerning tar removal from the syngas produced in a waste biomass gasifier via a catalytic post-gasification (CPG) downer unit. Various questions concerning CPG, such as reaction conditions, thermodynamics, a Tar Conversion Catalyst (TCC), and tar surrogate chemical species that can be employed for catalyst performance evaluations are reported. Catalyst performance-reported results were obtained in a fluidizable CREC Riser Simulator invented at CREC–UWO. The present review shows the suitability of the developed fluidizable Ni–Ceria γ-alumina catalyst, given the high level of tar removal it provides, the minimum coke that is formed with its use, and the adequate reforming of the syngas exiting the biomass waste gasifier, suitable for alcohol synthesis. Full article

Accelerating healing is a clinical goal in both acute and chronic non-healing skin wounds. We leveraged the public Recon database, which seeks to aggregate all of the metabolic pathways in the human body, to uncover whether increasing the supply of specific metabolites can bolster cellular metabolism and, in turn, enhance wound healing. The database was reduced to a set of 357 reactions and 339 metabolites that were better suited for human cells in culture. Monte Carlo simulations were performed to identify the impact of 25 different inputs on the metabolic fluxes within the cellular biochemical network. Biomass and ATP production were used as surrogate markers for cell proliferation and cell migration (an energy-intensive process), respectively, both of which are critical to wound healing. The subset of simulations yielding the highest ATP production or biomass production were those where glycine and/or glutamine uptake was increased. Maximizing ATP and biomass also generally increased oxygen uptake. Due to its low availability in chronic wounds, another set of simulations was carried out in which oxygen uptake was held constant to mimic the effect of a limited oxygen supply. However, even with this constraint, glycine and glutamine remained the most promising interventions. The predictions were tested in vitro using immortalized human keratinocytes. Amino acid uptake was tentatively increased by supplementing the base culture media with additional glycine and/or glutamine, with valine supplementation with a similar nitrogen load as a control. Glycine supplementation significantly increased cellular proliferation above the base media and accelerated wound closure rate in wound scratch assay. However, glutamine and valine supplementation did not improve these parameters above base media, and glutamine even suppressed the benefit of glycine in cultures supplemented with both amino acids. In conclusion, glycine supplementation enhances cellular processes that are associated with wound healing. Full article

The rational design of photoanode materials is pivotal for advancing photoelectrochemical (PEC) water splitting toward sustainable hydrogen production. This review highlights recent progress in the machine learning (ML)-assisted development of nanostructured metal oxide photoanodes, focusing on bridging materials discovery and device-level performance optimization. We first delineate the fundamental physicochemical criteria for efficient photoanodes, including suitable band alignment, visible-light absorption, charge carrier mobility, and electrochemical stability. Conventional strategies such as nanostructuring, elemental doping, and surface/interface engineering are critically evaluated. We then discuss the integration of ML techniques—ranging from high-throughput density functional theory (DFT)-based screening to experimental data-driven modeling—for accelerating the identification of promising oxides (e.g., BiVO₄, Fe₂O₃, WO₃) and optimizing key parameters such as dopant selection, morphology, and catalyst interfaces. Particular attention is given to surrogate modeling, Bayesian optimization, convolutional neural networks, and explainable AI approaches that enable closed-loop synthesis-experiment-ML frameworks. ML-assisted performance prediction and tandem device design are also addressed. Finally, current challenges in data standardization, model generalizability, and experimental validation are outlined, and future perspectives are proposed for integrating ML with automated platforms and physics-informed modeling to facilitate scalable PEC material development for clean energy applications. Full article

Accurate preform design in forging processes is critical for improving part quality, conserving material, reducing manufacturing costs, and eliminating secondary operations. This paper presents a finite element (FE) simulation-based methodology for preform design aimed at achieving flashless and near-flashless forging. The approach leverages material point backtracking within FE models to generate physics-informed preform geometries that capture complex material flow, die geometry interactions, and thermal gradients. An iterative scheme combining backtracking, surface reconstruction, and point-cloud solid modeling was developed and applied to several three-dimensional forging case studies, including a cross-joint and a three-lobe drive hub. The methodology demonstrated significant reductions in flash formation, particularly in parts that traditionally exhibit severe flash under conventional forging. Beyond supporting the development of new flashless forging sequences, the method also offers a framework for modifying preforms during production to minimize waste and for diagnosing preform defects linked to variability in frictional conditions, die temperatures, or material properties. Future integration of the proposed method with design of experiments (DOE) and surrogate modeling techniques could further enhance its applicability by optimizing preform designs within a localized design space. The findings suggest that this approach provides a practical and powerful tool for advancing both new and existing forging production lines toward higher efficiency and sustainability. Full article

Background/Objectives: Abdominal aortic aneurysm (AAA) repair is a prophylactic intervention aimed at preventing rupture. As the population ages, surgical decision-making becomes increasingly complex, especially in older and frailer patients. Imaging biomarkers, such as psoas muscle area (PMA) and density (PMD), have been proposed as surrogates for frailty and potential predictors of surgical outcomes. However, their clinical utility remains uncertain. Methods: In this retrospective, single-center study, we evaluated 199 patients who underwent elective AAA repair between 2015 and 2019. Preoperative computed tomography angiography (CTA) was used to measure PMA and PMD at the level of the third lumbar vertebra. Lean psoas muscle area (LPMA) was calculated as the product of PMA and PMD. Sarcopenia was defined as the lowest tertile of each measurement. Outcomes were assessed using Fisher’s exact test, Kaplan–Meier survival analysis, and logistic regression. Results: No significant associations were found between PMA, PMD, or LPMA and early or late postoperative complications or mortality. Conclusions: Psoas muscle indices, measured on routine CTA scans, do not reliably predict postoperative outcomes in AAA patients. These findings suggest that further studies integrating broader clinical and functional assessments are needed to improve risk stratification and inform preoperative decision-making in this patient population. Full article

Expensive medical devices, especially in the areas of orthopedics, and cardiology, have a significant impact on hospital costs and the delivery of high-quality services. These medical supplies are known as physician preference items (PPIs), as they act as “surrogate buyers”—impacting the selection and sourcing of products. There is a gap between the purchasing strategy and the adoption of tactical activities for these complex medical supplies. In the context of the healthcare exceptionalism thesis, this research investigates how healthcare organizations can successfully adopt suitable sourcing levers aiming to achieve different purchasing results. This research conducts a multi-case study in 15 healthcare organizations in nine countries. Three new sourcing levers specific to the healthcare sector emerged, based on the healthcare exceptionalism thesis. It was possible to identify five main sourcing levers clusters. The fit between strategy and tactical level can be allowed by the implementation of suitable sourcing levers—facilitating the achievement of the desired objectives. Healthcare procurement practitioners should assess the fit between strategy and the tactical level by employing suitable sourcing levers. Organizations wishing to move towards a value-based procurement approach should adopt a set of supporting sourcing levers to enable this transition. Full article