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29 pages, 5514 KiB

Open AccessArticle

Research on Energy Management Strategies for Fuel Cell Hybrid Vehicles Based on Time Classification

by Lihua Ye, Zixing Zhang, Qinglong Zhao, Xu Zhao, Zhou He and Aiping Shi

Energies 2025, 18(8), 2103; https://doi.org/10.3390/en18082103 - 18 Apr 2025

In order to minimize the carbon emission and energy consumption of fuel cell hybrid vehicles and, at the same time, solve the problem of low accuracy of working condition identification in the working condition identification strategy, this paper proposes an energy management strategy [...] Read more.

In order to minimize the carbon emission and energy consumption of fuel cell hybrid vehicles and, at the same time, solve the problem of low accuracy of working condition identification in the working condition identification strategy, this paper proposes an energy management strategy for SUVs on the basis of the working condition identification energy management strategy by using the time classification method. First, the mathematical model of the whole vehicle power system is established, and the driving conditions are constructed using actual collected vehicle driving data. On this basis, the working condition identification model was established, and then the energy management strategy of time working condition classification was established on the basis of the working condition identification model, and the equivalent hydrogen consumption of the two strategies was calculated by the Pontryagin minimization strategy. The results show that the strategy proposed in this paper reduces the equivalent hydrogen consumption by 2.707% compared with the condition identification strategy. This improvement not only greatly improves the energy efficiency of the fuel cell hybrid vehicle but also provides new ideas for the optimization of future energy management strategies. Full article

(This article belongs to the Special Issue Motor Vehicles Energy Management)

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12 pages, 1764 KiB

Open AccessArticle

Short Report: The Variants in CHEK2 in Metastatic Uveal Melanoma

by Mizue Terai, Rino Seedor, Usman Ashraf, Gretchen Hubbard, Sergei Koshkin, Marlana Orloff and Takami Sato

J. Clin. Med. 2025, 14(8), 2815; https://doi.org/10.3390/jcm14082815 (registering DOI) - 18 Apr 2025

Abstract

Background: Uveal melanoma (UM) is a rare subtype of melanoma with distinct clinical and molecular features compared to other melanoma subtypes. UM tumors are frequently detected with mutations in GNA11, GNAQ, EIF1AX, BAP1, and SF3B1 instead of the typical [...] Read more.

Background: Uveal melanoma (UM) is a rare subtype of melanoma with distinct clinical and molecular features compared to other melanoma subtypes. UM tumors are frequently detected with mutations in GNA11, GNAQ, EIF1AX, BAP1, and SF3B1 instead of the typical mutations associated with cutaneous melanoma. Although hereditary UM is rare, germline BAP1 loss predisposes patients to UM and various other cancers. The CHEK2 (Checkpoint kinase 2) gene that encodes the protein CHK2, a serine-threonine kinase, is a cell cycle checkpoint regulator that acts as a tumor suppressor. CHK2 is involved in DNA repair, cell cycle arrest, or apoptosis in response to DNA damage. CHEK2 mutations have been linked to various cancers. While there is no strong evidence that CHEK2 mutations increase the risk of melanoma, two cases of germline CHEK2 mutations in UM patients have been reported. However, the incidence of CHEK2 variants in metastatic UM (MUM) has not been investigated. Thus, we conducted a retrospective analysis of patients with MUM and CHEK2 variants to understand this link better. Methods: We collected MUM cases from 2016 to 2024 from institutional databases. Tissues underwent analyses of molecular and genomic features, including tumor mutational burden, and were performed by a Clinically Certified Laboratory. Next-generation sequencing and variant calling were conducted to identify CHEK2 variants. Results: In this study, we reported ten patients with CHEK2 variants among 740 metastatic UM patients (1.4%) and four primary UM patients with CHEK2 germline mutations. Conclusions: Although rare, UM patients with an abnormal ATM–CHEK2 axis might receive clinical benefits from medications that target DNA repair mechanisms. Full article

(This article belongs to the Section Oncology)

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13 pages, 1096 KiB

Open AccessArticle

Complete Blood Cell Count Parameters Predict Mortality in Patients with Hypersensitivity Pneumonitis

by Matthaios Katsaras, Vasilina Sotiropoulou, Effrosyni Manali, Evangelia Fouka, Despoina Papakosta, Elisabeth Bendstrup, Lykourgos Kolilekas, Ioannis Tomos, Vasilios Tzilas, Paschalis Ntolios, Paschalis Steiropoulos, Ilias Papanikolaou, Athena Gogali, Konstantinos Kostikas, Panagiota Tsiri, Ourania Papaioannou, Elli Malakounidou, Eva Theohari, Ioannis Christopoulos, Fotios Sampsonas, Spyridon A. Papiris, Nikoletta Rovina, Demosthenes Bouros and Argyrios Tzouvelekis Show full author list Hide full author list

Diagnostics 2025, 15(8), 1038; https://doi.org/10.3390/diagnostics15081038 (registering DOI) - 18 Apr 2025

Abstract

Background: Hypersensitivity pneumonitis (HP) represents a chronic lung disease with an unpredictable clinical course. There is a pressing need for clinically applicable prognostic biomarkers in patients with HP. Methods: This was an observational, retrospective study. We investigated the prognostic potential of complete blood [...] Read more.

Background: Hypersensitivity pneumonitis (HP) represents a chronic lung disease with an unpredictable clinical course. There is a pressing need for clinically applicable prognostic biomarkers in patients with HP. Methods: This was an observational, retrospective study. We investigated the prognostic potential of complete blood count parameters in treatment-naïve patients diagnosed with HP between 15 December 2010 and 1 October 2023. Receiver operating characteristic (ROC) curve analysis identified the optimal cut-off thresholds for each parameter in terms of mortality prediction. Results: We included 129 patients diagnosed with HP [median age: 68.0 years (95% CI: 65.0 to 69.0), fibrotic HP: n = 85, 65.9%]. Patients with HP and an eosinophil count >160 cells/μL [ROC curve, area under curve (AUC): 0.61] exhibited increased mortality risk compared to patients with HP and an eosinophil count ≤ 160 cells/μL [Kaplan–Meier, HR: 2.95 (95% CI: 1.36 to 6.42), p = 0.006]. Patients with HP and a monocyte count > 350 cells/μL (ROC curve, AUC: 0.52) had worse survival compared to patients with HP and a monocyte count lower than this threshold [Kaplan–Meier, HR: 2.48 (95% CI: 1.03 to 5.09), p = 0.04]. Patients with HP and an eosinophil–lymphocyte ratio (ELR) > 0.09 (ROC curve, AUC: 0.64) had a higher risk of mortality compared to patients with HP and ELR ≤ 0.09 [Kaplan–Meier, HR: 2.75 (95% CI: 1.3 to 5.78), p = 0.008]. Conclusions: This study demonstrated that eosinophil count, monocyte count, and ELR could be prognostic biomarkers in patients with HP. Further studies aiming to validate the prognostic potential of complete blood count parameters in patients with HP are greatly anticipated. Full article

(This article belongs to the Special Issue Respiratory Diseases: Diagnosis and Management)

16 pages, 1951 KiB

Open AccessArticle

Is Everything Lost? Recreating the Surface Water Temperature of Unmonitored Lakes in Poland

by Mariusz Ptak, Mariusz Sojka, Katarzyna Szyga-Pluta, Muhammad Yousuf Jat Baloch and Teerachai Amnuaylojaroen

Resources 2025, 14(4), 67; https://doi.org/10.3390/resources14040067 (registering DOI) - 18 Apr 2025

Abstract

One of the fundamental features of lakes is water temperature, which determines the functioning of lake ecosystems. However, the overall range of information related to the monitoring of this parameter is quite limited, both in terms of the number of lakes and the [...] Read more.

One of the fundamental features of lakes is water temperature, which determines the functioning of lake ecosystems. However, the overall range of information related to the monitoring of this parameter is quite limited, both in terms of the number of lakes and the duration of measurements. This study addresses this gap by reconstructing the lake surface water temperature (LSWT) of six lakes in Poland from 1994 to 2023, where direct measurements were discontinued. The reconstruction is based on the Air2Water model, which establishes a statistical relationship between LSWT and air temperature. Model validation using historical observations demonstrated high predictive accuracy, with a Nash–Sutcliffe Efficiency exceeding 0.92 and root mean squared error ranging from 0.97 °C to 2.13 °C across the lakes. A trend analysis using the Mann–Kendall test and Sen’s slope estimator indicated a statistically significant warming trend in all lakes, with an average increase of 0.35 °C per decade. Monthly trends were most pronounced in June, September, and November, exceeding 0.50 °C per decade in some cases. The direction, pace, and scale of these changes are crucial for managing individual lakes, both from an ecological and economic perspective. Full article

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19 pages, 518 KiB

Open AccessArticle

Applicability of Hydrodynamics in the Hadronic Phase of Heavy-Ion Collisions

by Ronald Scaria, Captain R. Singh and Raghunath Sahoo

Physics 2025, 7(2), 13; https://doi.org/10.3390/physics7020013 (registering DOI) - 18 Apr 2025

Abstract

The hadronic phase and its dynamics in relativistic heavy-ion collisions are topics of immense discussion. The hadronic phase contains various massive hadrons with an abundance of the lightest hadron, i.e.,

π

-mesons (pions). In this paper, we consider that pions are in the [...] Read more.

The hadronic phase and its dynamics in relativistic heavy-ion collisions are topics of immense discussion. The hadronic phase contains various massive hadrons with an abundance of the lightest hadron, i.e.,

π

-mesons (pions). In this paper, we consider that pions are in the thermal equilibrium in the hadronic phase and use second-order viscous hydrodynamics for a medium of massive pions to obtain its expansion to the boundary of the kinetic freeze-out. We achieve the kinetic freeze-out boundary with the Knudsen number

Kn > 1

limit. When this condition is met, hydrodynamics expansion breaks down, and the mean free path becomes sufficiently large in comparison with the system size so that the particle yields are preserved. Further, we investigate the effect of the massive fluid on the resonance particle yields, including re-scattering and regeneration, along with the natural decay widths of the resonances. The resonances can play an essential role in determining the characteristics of the hadronic phase as they have sufficiently small lifetimes, which may be comparable to the hadronic phase lifetime. In the current study, we predict the hadronic phase lifetime, which is further used to determine the

K^{*} {(892)}^{0} / K

,

ϕ (1020) / K

, and

ρ {(770)}^{0} / π

yield ratios at the kinetic freeze-out. We calculate these ratios as a function of charged particle multiplicity and transverse momentum and compare the findings with experimental data. Our calculations qualitatively agree with the experimental data, indicating a possible hydrodynamical evolution of the hadronic phase. Full article

(This article belongs to the Section High Energy Physics)

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17 pages, 9341 KiB

Open AccessArticle

Simulation of the Diffusion Characteristics of Multifunctional Nanocarriers in Tumor Tissues Using Lattice Gas Automata and the Lattice Boltzmann Method

by Yuming Qin, Kai Yue, Xiaoling Yu, Yu You, Chao Yang and Xinxin Zhang

Bioengineering 2025, 12(4), 429; https://doi.org/10.3390/bioengineering12040429 (registering DOI) - 18 Apr 2025

Abstract

Understanding the diffusion mechanisms of nanocarriers in tumor tissues is crucial for enhancing drug delivery to target areas. This study developed a simulation method combining lattice gas automata and the lattice Boltzmann method to explore the diffusion behaviors of ligand-coated nanoparticles (NPs) in [...] Read more.

Understanding the diffusion mechanisms of nanocarriers in tumor tissues is crucial for enhancing drug delivery to target areas. This study developed a simulation method combining lattice gas automata and the lattice Boltzmann method to explore the diffusion behaviors of ligand-coated nanoparticles (NPs) in the extracellular matrix (ECM) and tumor tissues under the influence of external fields. We propose mathematical models to describe how the movement of NPs is affected by thermomagnetic effects and by their interactions with ECM fiber walls and cells, and to calculate the flow field and temperature distribution in tumor tissues containing interstitial fluids. The results show that reduced tissue porosity and increased ECM fiber and cell densities hinder NP transport. Conversely, degrading ECM collagen fibers with thermal or other energy forms significantly improved NP diffusion in treated tissues. Modifying the surface zeta potential of NPs allowed for the regulation of NP adhesion to ECM fibers and cell membranes based on their charged components. However, altering the charge on the NP surface did not further enhance diffusion once a certain charge level was reached. Increased temperatures from NP heat generation under external fields improved interstitial fluid flow, thereby enhancing NP diffusion. Additionally, a static magnetic field gradient considerably increased the penetration depth of magnetic NPs in the direction of the field, with minimal effects on diffusion in other directions and, in some cases, reducing diffusion. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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24 pages, 6585 KiB

Open AccessArticle

ARCADE—Adversarially Robust Cost-Sensitive Anomaly Detection in Blockchain Using Explainable Artificial Intelligence

by Muhammad Kamran, Muhammad Maaz Rehan, Wasif Nisar and Muhammad Waqas Rehan

Electronics 2025, 14(8), 1648; https://doi.org/10.3390/electronics14081648 (registering DOI) - 18 Apr 2025

Abstract

Blockchain technology is increasingly being adopted across critical domains, such as healthcare and finance, yet it remains susceptible to anomalies and malicious attacks. Hence, robust anomaly detection is essential in these decentralized systems to maintain integrity, trust, and reliability. However, anomaly detection is [...] Read more.

Blockchain technology is increasingly being adopted across critical domains, such as healthcare and finance, yet it remains susceptible to anomalies and malicious attacks. Hence, robust anomaly detection is essential in these decentralized systems to maintain integrity, trust, and reliability. However, anomaly detection is still challenging due to data imbalances, adversarial resilience, and the lack of explanation in existing approaches. This work presents ARCADE, a novel approach for adversarially resilient anomaly detection in blockchain networks that leverages an optimized cost-sensitive stacking ensemble learning combined with explainable artificial intelligence (XAI) techniques. Firstly, the proposed approach uses cost-sensitive learning to address the data imbalance problem by optimizing class weights that are integrated with stacking ensemble learning to enhance detection accuracy. Secondly, along with this, newly engineered features are employed to strengthen the resilience of the model against malicious perturbations. Lastly, XAI techniques are applied to provide comprehensive insights and explanations for model prediction. To evaluate ARCADE, the Ethereum network transactions dataset is utilized to ensure a realistic case study. The experimental results show the superiority of the ARCADE in several aspects, achieving a high accuracy of 99.65%; strong resilience against adversarial perturbations, achieving an accuracy of 99.38% for low-intensity attacks, 91.04% for moderate attacks, and over 78% for extreme attacks; and surpassing existing techniques while also providing explainability for domain users. Full article

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20 pages, 3859 KiB

Open AccessArticle

Using Artificial Intelligence to Predict Power Demand in Small Power Grids—Problem Analysis as a Method to Limit Carbon Dioxide Emissions

by Tomasz Ciechulski, Jacek Paś, Marek Stawowy and Stanisław Duer

Sustainability 2025, 17(8), 3694; https://doi.org/10.3390/su17083694 (registering DOI) - 18 Apr 2025

Abstract

The article discusses the application of advanced data mining methods applicable to electricity consumption within a local power system in Poland. This analysis involves power demand. It is aimed at predicting daily demand variations. In such a case, system demand is characterized by [...] Read more.

The article discusses the application of advanced data mining methods applicable to electricity consumption within a local power system in Poland. This analysis involves power demand. It is aimed at predicting daily demand variations. In such a case, system demand is characterized by high variability over a short period of time, e.g., 24 h. This constitutes a significant issue within a small power grid. It entails effective load programming on a given day and time. Therefore, the authors of the paper suggested employing artificial intelligence to forecast industrial power grid load for successive time intervals of the operation process. Such a solution applied within a power system enables appropriate start-up/shut-down planning, as well as generator operation at a specific capacity in power plants. It thus allows continuous power system (on-line) load demand balancing. Predicting power system load also involves determining moments, e.g., of power plant start-up, transition times to maximum or minimum output, or also the shut-down of such a process. This means ongoing and continuous (automatic) impact on electricity distribution. It significantly reduces carbon dioxide atmospheric emissions and allows zero-emission, e.g., wind, hydro, geothermal, or solar plants to meet current power needs. The issue associated with operating small ‘island’ power systems is a dynamic and rapid change in power demand. This is related to the area-based—‘island’—use’ of available power sources that can only be operated within a specific area. A very important problem occurring within these structurally small grids is the continuous forecasting of load changes and real-time response to power demand (i.e., balancing power demand through in-house or available power sources). Full article

(This article belongs to the Special Issue Contribution of Intelligent Transport Systems to Sustainable Development Goals)

22 pages, 5534 KiB

Open AccessArticle

Reduced-Order Nonlinear Envelope Modeling and Simulation of Resonant Inverter Driving Series Resistor–Inductor–Capacitor Load with Time-Varying Component Values

by Ohad Akler and Alon Kuperman

Appl. Sci. 2025, 15(8), 4502; https://doi.org/10.3390/app15084502 (registering DOI) - 18 Apr 2025

Abstract

Envelope modeling is an efficient way to obtain the large-signal amplitude and phase dynamics of fast-varying sinusoidal signals required for, e.g., resonant frequency tracking or energy transfer rate regulation in power converters. In addition, the method eliminates fast-varying parameters from the model so [...] Read more.

Envelope modeling is an efficient way to obtain the large-signal amplitude and phase dynamics of fast-varying sinusoidal signals required for, e.g., resonant frequency tracking or energy transfer rate regulation in power converters. In addition, the method eliminates fast-varying parameters from the model so that the simulation time and memory requirements are reduced. This paper reveals the envelope-modeling process of a capacitor-powered resonant inverter feeding a time-varying series RLC load, often employed in pulsed-power applications. Such an arrangement is nontrivial since the system does not reach a steady state within a single pulse duration. Furthermore, model order reduction is carried out without performing linearization due to large variations in the expected operation point. As a result, a reduced-order nonlinear envelope model is derived and validated by simulations. Both the proposed modeling method and the derived model aim to simplify the challenging task of feedback controller design. Full article

(This article belongs to the Special Issue New Insights into Wireless Power Transmission Systems)

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15 pages, 1009 KiB

Open AccessArticle

Perception of the Food Environment and Food Security Levels of Residents of the City of Rio de Janeiro

by Paulo César Pereira de Castro Junior, Yoko Ametista Carvalho Suéte Matos, Roberta Teixeira de Oliveira, Rosana Salles-Costa and Aline Alves Ferreira

Int. J. Environ. Res. Public Health 2025, 22(4), 642; https://doi.org/10.3390/ijerph22040642 (registering DOI) - 18 Apr 2025

Abstract

The way individuals perceive and interact with the food environment can contribute to a higher prevalence of food insecurity (FI). Objective: To evaluate the perception of the food environment and its association with FI in households in the city of Rio de Janeiro, [...] Read more.

The way individuals perceive and interact with the food environment can contribute to a higher prevalence of food insecurity (FI). Objective: To evaluate the perception of the food environment and its association with FI in households in the city of Rio de Janeiro, Brazil. Methods: Cross-sectional study. The survey was conducted with a sample of 2000 households, a representative stratified sample, with a margin of error of 4.9 percentage points and a 95% confidence interval (CI95%) in the city of Rio de Janeiro. The studies were evaluated using the Brazilian Food Insecurity Scale (EBIA). Perceptions of the food environment were measured by assessing the perceived availability, price, and quality of fruits and vegetables (FVs) and ultra-processed foods (UPFs) sold in the neighborhood. To analyze the association between stage variations and the perceived food environment, we conducted multinomial logistic regression, considering a 95%CI. Results: Household heads in Rio de Janeiro perceive that both FVs and UPFs are available in their neighborhoods. However, UPFs are perceived as cheaper and more diverse than FVs, regardless of the level of food safety. In the association analysis, a greater relative risk ratio was found for heads of households who perceive an unfavorable scenario in the food environment for FVs, in terms of availability (RRR = 5.6; 95%IC: 3.0–10.4), quality (RRR = 4.5; 95%IC: 2.6–7.9), and price (RRR = 2.5; 95%IC: 1.7–3.6), to experience a situation of moderate/severe FI. Conclusions: The way individuals interact with and perceive their territories can reflect on access to adequate and healthy food, especially in households in a situation of FI. Full article

(This article belongs to the Special Issue Bridging the Gap in Studies on the Food Environment: The State-of-the-Art in Low- and Middle-Income Countries (LMICs))

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20 pages, 550 KiB

Open AccessArticle

Economic Analysis of Fossil CO₂ Emissions: A European Perspective on Sustainable Development

by Alina Yakymchuk and Małgorzata Agnieszka Rataj

Energies 2025, 18(8), 2106; https://doi.org/10.3390/en18082106 (registering DOI) - 18 Apr 2025

Abstract

The economic assessment of CO₂ emissions from fossil fuels is gaining importance in the context of sustainable development. Climate change, driven by excessive greenhouse gas emissions, poses a significant threat to humanity, requiring an integrated approach that considers both environmental and economic [...] Read more.

The economic assessment of CO₂ emissions from fossil fuels is gaining importance in the context of sustainable development. Climate change, driven by excessive greenhouse gas emissions, poses a significant threat to humanity, requiring an integrated approach that considers both environmental and economic factors. The European Union (EU) plays a key role in global efforts to reduce CO₂ emissions and promote sustainability. This study explores economic approaches to analyzing CO₂ emissions in Europe, focusing on trends in fossil fuel use and their economic drivers. The research highlights the connection between economic activity, energy consumption, and emissions, contributing to a better understanding of climate change mitigation strategies. The findings emphasize the strong influence of demographic factors on carbon emissions, stressing the need for targeted policies to address the environmental impact of population growth. This study presents a literature-based assessment of CO₂ emissions from fossil fuel consumption in the context of sustainable development, with a focus on Europe. Recognizing the urgent threat posed by climate change, the paper explores how economic and demographic factors influence emissions trends and energy consumption. Through the synthesis of recent research and statistical data, it examines the relationship between economic activity and CO₂ emissions across EU countries. Special attention is given to national policy frameworks, particularly Germany’s “Energiewende”, as a successful example of emission reduction through building-sector reform. The study highlights that while economic growth remains a driver of emissions, strategic investments in renewable energy, energy efficiency, and sectoral transformation can decouple growth from environmental degradation. The findings support the need for country-specific mitigation strategies, emphasizing that uniform approaches may not address the diverse challenges faced by EU member states. This work contributes to the broader understanding of climate policy design by linking empirical evidence with policy implications in the transition to a low-carbon economy. Full article

(This article belongs to the Special Issue Energy and Environmental Economics for a Sustainable Future)

16 pages, 20042 KiB

Open AccessArticle

Application of Deep Learning in Glacier Boundary Extraction: A Case Study of the Tomur Peak Region, Tianshan, Xinjiang

by Yan Zhang, Feng Han, Mingfeng Zhou, Yichen Hou and Song Wang

Sustainability 2025, 17(8), 3678; https://doi.org/10.3390/su17083678 (registering DOI) - 18 Apr 2025

Abstract

Glaciers are one of the most important water resources in the arid regions of Xinjiang, making it crucial to accurately monitor glacier changes for the region’s sustainable development. However, due to their typical distribution in remote, high-altitude areas, large-scale and long-term field observations [...] Read more.

Glaciers are one of the most important water resources in the arid regions of Xinjiang, making it crucial to accurately monitor glacier changes for the region’s sustainable development. However, due to their typical distribution in remote, high-altitude areas, large-scale and long-term field observations are often constrained by the high costs of manpower, resources, and finances. Globally, fewer than 40 glaciers have been monitored for more than 20 years, and, in China, only Glacier No. 1 at the headwaters of the Urumqi River has monitoring records exceeding 50 years. To address these challenges, this study analyzed glacier changes in the Tomur Peak region of the Tianshan Mountains over the past 35 years using Landsat satellite imagery. Through experiments with deep learning models, the results show that the 3-4-5 band combination performed best for glacier boundary extraction. The DeepLabV3+ model, with MobileNetV2 as the backbone, achieved an overall accuracy of 90.44%, a recall rate of 82.75%, and a mean Intersection over Union (IoU) that was 1.6 to 5.94 percentage points higher than other models. Based on these findings, the study further analyzed glacier changes in the Tomur Peak region, revealing an average annual glacier reduction rate of 0.18% and a retreat rate of 6.97 km²·a⁻¹ over the past 35 years. This research provides a more precise and comprehensive scientific reference for understanding glacier changes in arid regions, with significant implications for enhancing our understanding of the impacts of climate change on glaciers, optimizing water resource management, and promoting regional sustainable development. Full article

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27 pages, 1094 KiB

Open AccessArticle

Quantum Computing as a Catalyst for Microgrid Management: Enhancing Decentralized Energy Systems Through Innovative Computational Techniques

by Minghong Liu, Mengke Liao, Ruilong Zhang, Xin Yuan, Zhaoqun Zhu and Zhi Wu

Sustainability 2025, 17(8), 3662; https://doi.org/10.3390/su17083662 (registering DOI) - 18 Apr 2025

Abstract

This paper introduces a groundbreaking framework for optimizing microgrid operations using the Quantum Approximate Optimization Algorithm (QAOA). The increasing integration of decentralized energy systems, characterized by their reliance on renewable energy sources, presents unique challenges, including the stochastic nature of energy supply-and-demand management. [...] Read more.

This paper introduces a groundbreaking framework for optimizing microgrid operations using the Quantum Approximate Optimization Algorithm (QAOA). The increasing integration of decentralized energy systems, characterized by their reliance on renewable energy sources, presents unique challenges, including the stochastic nature of energy supply-and-demand management. Our study leverages quantum computing to enhance the operational efficiency and resilience of microgrids, transcending the limitations of traditional computational methods. The proposed QAOA-based model formulates the microgrid scheduling problem as a Quadratic Unconstrained Binary Optimization (QUBO) problem, suitable for quantum computation. This approach not only accommodates complex operational constraints—such as energy conservation, peak load management, and cost efficiency—but also dynamically adapts to the variability inherent in renewable energy sources. By encoding these constraints into a quantum-friendly Hamiltonian, QAOA facilitates a parallel exploration of multiple potential solutions, enhancing the probability of reaching an optimal solution within a feasible time frame. We validate our model through a comprehensive simulation using real-world data from a microgrid equipped with photovoltaic systems, wind turbines, and energy storage units. The results demonstrate that QAOA outperforms conventional optimization techniques in terms of cost reduction, energy efficiency, and system reliability. Furthermore, our study explores the scalability of quantum algorithms in energy systems, providing insights into their potential to handle larger, more complex grid architectures as quantum technology advances. This research not only underscores the viability of quantum algorithms in real-world applications but also sets a precedent for future studies on the integration of quantum computing into energy management systems, paving the way for more sustainable, efficient, and resilient energy infrastructures. Full article

(This article belongs to the Topic Intelligent, Flexible, and Effective Operation of Smart Grids with Novel Energy Technologies and Equipment)

17 pages, 7709 KiB

Open AccessArticle

Analysis of Factors Affecting Random Measurement Error in LiDAR Point Cloud Feature Matching Positioning

by Guoliang Liu, Wang Gao and Shuguo Pan

Remote Sens. 2025, 17(8), 1457; https://doi.org/10.3390/rs17081457 (registering DOI) - 18 Apr 2025

Abstract

Light detection and ranging (LiDAR) has the advantage of simultaneous localization and mapping with high precision, making it one of the important sensors for intelligent robotics navigation, positioning, and perception. It is common knowledge that the random measurement error of global navigation satellite [...] Read more.

Light detection and ranging (LiDAR) has the advantage of simultaneous localization and mapping with high precision, making it one of the important sensors for intelligent robotics navigation, positioning, and perception. It is common knowledge that the random measurement error of global navigation satellite system (GNSS) observations is usually considered to be closely related to the elevation angle factor. However, in the LiDAR point cloud feature matching positioning model, the analysis of factors affecting the random measurement error of observations is unsophisticated, which limits the ability of LiDAR sensors to estimate pose parameters. Therefore, this work draws on the random measurement error analysis method of GNSS observations to study the impact of factors such as distance, angle, and feature accuracy on the random measurement error of LiDAR. The experimental results show that feature accuracy is the main factor affecting the measurement error in the LiDAR point cloud feature matching positioning model, compared with distance and angle factors, even under different sensor specifications, point cloud densities, prior maps, and urban road scenes. Furthermore, a simple random measurement error model based on the feature accuracy factor is used to verify the effect of parameter estimation, and the results show that the random error model can effectively reduce the error of pose parameter estimation, with an improvement effect of about 50%. Full article

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20 pages, 3358 KiB

Open AccessArticle

Transnasal PLGA Nanoparticles with Terpene Permeation Enhancers: Membrane Remodeling and Tight Junction Modulation for Enhanced Brain Drug Delivery

by Yi Zhang, Zishuo Guo, Haitong Zhang, Hongmei Wei, Tieshan Wang, Shouying Du and Pengyue Li

Int. J. Mol. Sci. 2025, 26(8), 3861; https://doi.org/10.3390/ijms26083861 (registering DOI) - 18 Apr 2025

Abstract

Nasal nanodrug delivery has gained prominence as a non-invasive method for administering therapeutic agents to the brain. However, the limited nasal cavity volume and the low drug loading capacity of nanoparticles contribute to a reduced accumulation of the drug within the brain tissue. [...] Read more.

Nasal nanodrug delivery has gained prominence as a non-invasive method for administering therapeutic agents to the brain. However, the limited nasal cavity volume and the low drug loading capacity of nanoparticles contribute to a reduced accumulation of the drug within the brain tissue. Therefore, the aim of the present study was to investigate the role of the drug delivery combination “transnasal route + nanoparticle drug delivery system + chemical osmosis technology” in promoting drug accumulation in the brain. We constructed an in vitro olfactory sheath cell model based on the direct nose–brain pathway and a vascular endothelial cell model based on the indirect pathway, and investigated the transport behaviors and mechanisms of Poly(lactic-co-glycolicacid)-Nanoparticles(PLGA-NPs )in combination with two terpene aroma constituents (menthol and curcumol). Menthol and curcumol significantly improved the intracellular accumulation of PLGA-NPs, which may be related to changes in the endocytosis pathway and intercellular tight junction proteins. Meanwhile, the results of laser scanning confocal microscopy and atomic force microscopy showed that menthol and curcumol disrupted different tight junction proteins of vascular endothelial cells, and the biomechanical properties (e.g., rigidity and roughness) of the olfactory sheath cells and vascular endothelial cell cytomembranes were also greatly changed. The delivery system of “transnasal route + nanoparticle drug delivery system + chemical osmosis technology” has great potential for intranasal delivery of drugs for the treatment of brain diseases. Full article

(This article belongs to the Section Molecular Pharmacology)

13 pages, 223 KiB

Open AccessArticle

The Sacred in the Mud: On Downward Transcendence in Religious and Spiritual Experience

by Yue Wu

Religions 2025, 16(4), 530; https://doi.org/10.3390/rel16040530 (registering DOI) - 18 Apr 2025

Abstract

Although there has been an increasing focus on religious and spiritual experience in literary studies within the context of post-critical and post-secular movements, much of the research is framed around the idea of “upward transcendence” in redemption narratives. This focus tends to overlook [...] Read more.

Although there has been an increasing focus on religious and spiritual experience in literary studies within the context of post-critical and post-secular movements, much of the research is framed around the idea of “upward transcendence” in redemption narratives. This focus tends to overlook the negative aspects of life, such as absurdity, meaninglessness, and existential anxiety. Furthermore, it frequently resonates with capitalist ideals that champion a “seamless existence” while dismissing the unrefined essence of materiality. This article engages in two main tasks: First, it emphasizes the negative dimensions of religious and spiritual experience, drawing on Slavoj Žižek’s interpretation of theological and non-theological literature. Second, it expands the definition and scope of religious and spiritual experience, proposing an alternative paradigm based on absurdity and meaninglessness. This paradigm, “downward transcendence,” rejects the redemptive promise of “ascension” and redefines the sacred by engaging with the disruptive and unsettling fabric of existence, reconstructing the coordinates of the sacred within the fissures of reality. Through the case study of Sartre’s Nausea, the article explores how existential absurdity and meaninglessness can reconfigure the sacred, particularly through marginality and the transformative potential of negative experiences. It ultimately proposes downward transcendence as a radical reimagining of spiritual and existential freedom. Full article

(This article belongs to the Special Issue Imagining Ultimacy: Religious and Spiritual Experience in Literature)

19 pages, 4550 KiB

Open AccessArticle

Development of Biomimetic Edible Scaffolds for Cultured Meat Based on the Traditional Freeze-Drying Method for Ito-Kanten (Japanese Freeze-Dried Agar)

by Ping Xia, Hiroki Miyajima and Satoshi Fujita

Gels 2025, 11(4), 299; https://doi.org/10.3390/gels11040299 (registering DOI) - 18 Apr 2025

Abstract

In this study, we aimed to develop soy protein-derived edible porous hydrogel scaffolds for cultured meat based on mechanical anisotropy to mimic the physical and biochemical properties of muscle tissues. Based on the traditional Japanese Ito-Kanten (thread agar) freeze–thaw process, we used liquid [...] Read more.

In this study, we aimed to develop soy protein-derived edible porous hydrogel scaffolds for cultured meat based on mechanical anisotropy to mimic the physical and biochemical properties of muscle tissues. Based on the traditional Japanese Ito-Kanten (thread agar) freeze–thaw process, we used liquid nitrogen directional freezing combined with ion crosslinking to fabricate an aligned scaffold composed of soy protein isolate (SPI), carrageenan (CA), and sodium alginate (SA). SPI, CA, and SA were dissolved in water, heated, mixed, and subjected to directional freezing in liquid nitrogen. The frozen gel was immersed in Ca²⁺ and K⁺ solutions for low-temperature crosslinking, followed by a second freezing step and lyophilization to create the SPI/CA/SA cryogel scaffold with anisotropic pore structure. Furthermore, C2C12 myoblasts were seeded onto the scaffold. After 14 d of dynamic culture, the cells exhibited significant differentiation along the aligned structure of the scaffold. Overall, our developed anisotropic scaffold provided a biocompatible environment to promote directed cell differentiation, showing potential for cultured meat production and serving as a sustainable protein source. Full article

(This article belongs to the Special Issue Customizing Hydrogels: A Journey from Concept to End-Use Properties)

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18 pages, 6291 KiB

Open AccessArticle

Multi-Sensor Collaborative Positioning in Range-Only Single-Beacon Systems: A Differential Chan–Gauss–Newton Algorithm with Sequential Data Fusion

by Yun Ye, Hongyang He, Enfan Lin and Hongqiong Tang

Sensors 2025, 25(8), 2577; https://doi.org/10.3390/s25082577 (registering DOI) - 18 Apr 2025

Abstract

The development of underwater high-precision navigation technology is of great significance for the application of autonomous underwater vehicles (AUVs). Traditional long baseline (LBL) positioning systems require pre-deployment and the calibration of multiple beacons, which consumes valuable time and manpower. In contrast, the range-only [...] Read more.

The development of underwater high-precision navigation technology is of great significance for the application of autonomous underwater vehicles (AUVs). Traditional long baseline (LBL) positioning systems require pre-deployment and the calibration of multiple beacons, which consumes valuable time and manpower. In contrast, the range-only single-beacon (ROSB) positioning technology can help autonomous underwater vehicles (AUVs) obtain accurate position information by deploying only one beacon. This method greatly reduces the time and workload of deploying beacons, showing high application potential and cost ratio. Given the operational constraints of AUV open-ocean navigation with single-beacon weak observations and absence of valid a priori positioning data in calibration zones, a multi-sensor underwater virtual beacon localization framework was established, proposing a differential Chan–Gauss–Newton (DCGN) methodology for submerged vehicles. Based on inertial navigation, the method uses the distance measurement information from a single beacon and observations from multiple sensors, such as the Doppler velocity log (DVL) and pressure sensor, to obtain accurate position estimates by discriminating the initial position of multiple hypotheses. A simulation experiment and lake test show that the proposed method not only significantly improves the positioning accuracy and convergence speed, but also shows high reliability. Full article

(This article belongs to the Section Navigation and Positioning)

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48 pages, 6137 KiB

Open AccessReview

The Inflammatory Link of Rheumatoid Arthritis and Thrombosis: Pathogenic Molecular Circuits and Treatment Approaches

by Theodora Adamantidi, Maria Stavroula Pisioti, Sofia Pitsouni, Chatzikamari Maria, Karamanis Georgios, Vasiliki Dania, Nikolaos Vordos, Xenophon Krokidis and Alexandros Tsoupras

Curr. Issues Mol. Biol. 2025, 47(4), 291; https://doi.org/10.3390/cimb47040291 (registering DOI) - 18 Apr 2025

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by systemic inflammation that primarily affects the joints but can also involve extra-articular organs. Its multifactorial etiology remains incompletely understood, necessitating further investigation into its underlying mechanisms. The primary therapeutic goal in RA management [...] Read more.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by systemic inflammation that primarily affects the joints but can also involve extra-articular organs. Its multifactorial etiology remains incompletely understood, necessitating further investigation into its underlying mechanisms. The primary therapeutic goal in RA management is to achieve disease remission or maintain low RA activity to prevent long-term morbidity. RA therapies aim to mitigate joint damage, reduce disability, and prevent systemic complications such as cardiovascular diseases. In addition to pharmacological treatments, non-pharmacological interventions—including physiotherapy, occupational therapy, and lifestyle modifications such as smoking cessation, regular exercise, and adherence to a balanced diet—play a crucial role in managing the disease. Beyond joint inflammation, RA has been strongly associated with an increased risk of thrombosis, contributing significantly to both morbidity and mortality. The link between RA and thrombotic events arises from a complex interplay of inflammatory pathways, endothelial dysfunction, and coagulation abnormalities. This review provides an in-depth analysis of the mechanisms driving the association between thrombo-inflammatory manifestations and the incidence of RA, the impact of RA treatment on thrombosis prevalence, and potential therapeutic strategies for managing both conditions concurrently. By integrating recent advancements in rheumatoid arthritis (RA) pathophysiology and thrombo-inflammatory research, this paper provides a comprehensive resource on the inflammatory link between RA and thrombosis while discussing and comparing current and emerging treatment approaches. Further investigation into these mechanisms could facilitate the development of targeted therapies that reduce the risk of thrombosis in patients with RA. Full article

(This article belongs to the Special Issue Molecular Research in Osteoarthritis and Osteoarticular Diseases)

14 pages, 2539 KiB

Open AccessArticle

Effects of Saturation on Anger in a Low-Saturation Range: A Comparison of Background Colors in 12 Tones

by Akinori Shimodaira and Noriyuki Kida

Behav. Sci. 2025, 15(4), 551; https://doi.org/10.3390/bs15040551 (registering DOI) - 18 Apr 2025

Abstract

This study used an online survey to investigate the effects of brightness in low-saturation color ranges on anger processing. Specifically, it explored how background hues—red, yellow-green, and blue-green—affect perceptions of illustrations of an angry red face. The experiment involved 36 color combinations classified [...] Read more.

This study used an online survey to investigate the effects of brightness in low-saturation color ranges on anger processing. Specifically, it explored how background hues—red, yellow-green, and blue-green—affect perceptions of illustrations of an angry red face. The experiment involved 36 color combinations classified into three hue groups and three saturation levels (high, medium, and low) based on the Practical Color Co-ordinate System. The results indicate that the influence of hue disappears in the low-saturation range. Across all the saturation levels, lower brightness intensified the perception of anger, with the anger elicited by darker colors similar in strength to that elicited from vivid red. These findings offer new insights into the role of color in emotional processing, particularly in relation to anger. Full article

23 pages, 2518 KiB

Open AccessArticle

Viper Venom and Synthetic Peptides: Emerging Active Ingredients in Anti-Ageing Cosmeceuticals

by Dana Georgiana Moisă, Anca Maria Juncan, Luca-Liviu Rus, Andreea Loredana Vonica-Țincu, Gabriela Cormoș and Felicia Gabriela Gligor

Appl. Sci. 2025, 15(8), 4501; https://doi.org/10.3390/app15084501 (registering DOI) - 18 Apr 2025

Abstract

The animal kingdom, particularly reptiles, is widely recognized as a valuable source of peptides and proteins with applications in medicine, the pharmaceutical industry and, more recently, the cosmetic industry. This prompted an investigation into the prevalence of cosmetic products utilizing synthetic peptides, with [...] Read more.

The animal kingdom, particularly reptiles, is widely recognized as a valuable source of peptides and proteins with applications in medicine, the pharmaceutical industry and, more recently, the cosmetic industry. This prompted an investigation into the prevalence of cosmetic products utilizing synthetic peptides, with a specific focus on viper venom. A major objective of our study was a comparative analysis between natural venom-derived peptides and synthetic analogues, which could provide valuable insights into the market impact. The identification and inclusion of these products were based on their listings according to the International Nomenclature of Cosmetic Ingredients (INCI), alongside a review of the current literature and the recognition of relevant studies aimed at evaluating the composition of viper venom. Additionally, cosmetics were identified through online media using specific keywords such as “viper venom”, “snake venom”, “snake”, “SYN^®-AKE”, “analogues of snake venom” or “synthetic snake venom”, followed by a comparative analysis of the products identified. The study provided an extensive background considering the market segmentation of viper venom-based and synthetic peptide-based cosmetics, including 245 cosmetics (70 manufacturers), also including the classification into Mass-Market and Premium-Market segments, which adds practical value. In 81% of the total analyzed products, the synthetic analogue was present, SYN^®-AKE (INCI Dipeptide Diaminobutyroyl Benzylamide Diacetate (and) Glycerin (and) Aqua), while 13% contained snake venom or viper venom. The high percentage of cosmetics categorized under the Mass-Market segment could be attributed to the use of synthetic peptides, given the high cost of natural viper venom as an anti-ageing ingredient, a price likely reflected in the final cosmetic product. In terms of product category, skin care cosmetics made up the largest share, followed by body care products, typically claiming anti-ageing and moisturizing properties. Full article

(This article belongs to the Special Issue Cosmetics Ingredients Research - 2nd Edition)

13 pages, 715 KiB

Open AccessArticle

Enhancing Heavy Metal Removal and Stabilization in River Sediment by Combined Application of Nanoscale Zero-Valent Iron and Sediment Microbial Fuel Cells

by Xun Xu, Mingsong Wu and Guoling Ren

Processes 2025, 13(4), 1235; https://doi.org/10.3390/pr13041235 (registering DOI) - 18 Apr 2025

Abstract

This study investigates the effect of nanoscale zero-valent iron (NZVI) and sediment microbial fuel cells (SMFCs) on the three typical heavy metals’ (Pb, Cr and As) removal and stabilization. Results showed that the combined use of NZVI and SMFCs obtained the highest removal [...] Read more.

This study investigates the effect of nanoscale zero-valent iron (NZVI) and sediment microbial fuel cells (SMFCs) on the three typical heavy metals’ (Pb, Cr and As) removal and stabilization. Results showed that the combined use of NZVI and SMFCs obtained the highest removal efficiencies in the sediment (Pb 37.7 ± 2.2%, Cr 26.4 ± 1.5% and As 30.1 ± 2.0%) and overlying water (Pb 55.8 ± 2.3%, Cr 47.6 ± 1.9% and As 45.8 ± 2.1%). The use of an NZVI electrode can transform heavy metals with relatively weak binding into forms with stronger binding, thereby diminishing their bioavailability and toxicity. After 60 days of operation with the addition of NZVI in the SMFC system, over 50% of the Pb, Cr and As in the sediment was transformed into the residual fraction. An anodic microbial communities analysis indicated that operating a SMFC can mitigate the adverse effects of NZVI on the community diversity and increase the content of electrogenic bacteria in sediments. Consequently, our findings indicated that integrating SMFCs and NZVI represents a viable approach for remediating rivers contaminated with heavy-metal-polluted sediments. Full article

(This article belongs to the Section Environmental and Green Processes)

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17 pages, 1689 KiB

Open AccessArticle

Ultrafast Rechargeable Aluminum-Chlorine Batteries Enabled by a Confined Chlorine Conversion Chemistry in Molten Salts

by Junling Huang, Linhan Xu, Yu Wang, Xiaolin Wu, Meng Zhang, Hao Zhang, Xin Tong, Changyuan Guo, Kang Han, Jianwei Li, Jiashen Meng and Xuanpeng Wang

Materials 2025, 18(8), 1868; https://doi.org/10.3390/ma18081868 (registering DOI) - 18 Apr 2025

Abstract

Rechargeable metal chloride batteries, with their high discharge voltage and specific capacity, are promising for next-generation sustainable energy storage. However, sluggish solid-to-gas conversion kinetics between solid metal chlorides and gaseous Cl₂ cause unsatisfactory rate capability and limited cycle life, hindering their further [...] Read more.

Rechargeable metal chloride batteries, with their high discharge voltage and specific capacity, are promising for next-generation sustainable energy storage. However, sluggish solid-to-gas conversion kinetics between solid metal chlorides and gaseous Cl₂ cause unsatisfactory rate capability and limited cycle life, hindering their further applications. Here we present a rechargeable aluminum-chlorine (Al-Cl₂) battery that relies on a confined chlorine conversion chemistry in a molten salt electrolyte, exhibiting ultrahigh rate capability and excellent cycling stability. Both experimental analysis and theoretical calculations reveal a reversible solution-to-gas conversion reaction between AlCl₄^- and Cl₂ in the cathode. The designed nitrogen-doped porous carbon cathode enhances Cl₂ adsorption, thereby improving the cycling lifespan and coulombic efficiency of the battery. The resulting Al-Cl₂ battery demonstrates a high discharge plateau of 1.95 V, remarkable rate capability without capacity decay at different rates from 5 to 50 A g⁻¹, and good cycling stability with over 1200 cycles at a rate of 10 A g⁻¹. Additionally, we implemented a carbon nanofiber membrane on the anode side to mitigate dendrite growth, which further extends the cycle life to 3000 cycles at an ultrahigh rate of 30 A g⁻¹. This work provides a new perspective on the advancement of high-rate metal chloride batteries. Full article

(This article belongs to the Special Issue Advanced Electrode Materials for Batteries: Design and Performance)

16 pages, 3570 KiB

Open AccessArticle

Insights into the Regulatory Role of MicroRNAs in Penaeus monodon Under Moderately Low Salinity Stress

by Jianzhi Shi, Song Jiang, Yangyang Ding, Hongshan Diao, Wenzhe Li, Yundong Li, Jianhua Huang, Lishi Yang, Qibin Yang and Falin Zhou

Biology 2025, 14(4), 440; https://doi.org/10.3390/biology14040440 (registering DOI) - 18 Apr 2025

Abstract

MicroRNAs (miRNAs) play crucial roles in regulating various biological processes in crustaceans, including stress responses. Under acute low salinity stress conditions, miRNAs exhibit dynamic expression patterns that significantly influence the physiological and molecular responses of the shrimp. However, research on miRNAs in P. [...] Read more.

MicroRNAs (miRNAs) play crucial roles in regulating various biological processes in crustaceans, including stress responses. Under acute low salinity stress conditions, miRNAs exhibit dynamic expression patterns that significantly influence the physiological and molecular responses of the shrimp. However, research on miRNAs in P. monodon is very limited, and their functions under low salinity stress remain unclear. In this study, by using high-throughput sequencing technology, we identified miRNAs and investigated their regulatory mechanism in P. monodon under low salinity stress. A total of 118 miRNAs were differentially expressed after low salinity exposure. These miRNAs were found to target genes involved in metabolism, pathogen infection, immune response and stress signaling pathways. By modulating the expression of these target genes, miRNAs were able to fine-tune the stress response of P. monodon, thereby enhancing its tolerance to low salinity. This study provides new insights into the regulatory roles of miRNAs in the stress response of aquatic organisms and suggests potential targets for genetic improvement to enhance stress tolerance in P. monodon aquaculture. Full article

(This article belongs to the Special Issue Advances in Biological Research into Shrimps, Crabs and Lobsters)

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64 pages, 1570 KiB

Open AccessReview

The Impact of Implementing Indicators of Quality of Oncological Care on Improving Patient Outcomes: A Cross-Sectional Review of Experiences from Countries Using Indicators in the Quality Assessment Process

by Karolina Piekarska, Piotr Bednarski, Barbara Politynska, Anna M. Wojtukiewicz, Maciej Krzakowski and Marek Z. Wojtukiewicz

Cancers 2025, 17(8), 1362; https://doi.org/10.3390/cancers17081362 (registering DOI) - 18 Apr 2025

Abstract

The implementation of QIs in the pursuit of improving patient outcomes in oncological care has become a primary goal for many countries. The purpose of this cross-sectional review is to present the experiences of several countries that have implemented different strategies in using [...] Read more.

The implementation of QIs in the pursuit of improving patient outcomes in oncological care has become a primary goal for many countries. The purpose of this cross-sectional review is to present the experiences of several countries that have implemented different strategies in using QIs to assess the quality of cancer care. Countries such as the United States, the United Kingdom, Canada, the Netherlands, Australia, and Israel have been pioneers in integrating QIs into their healthcare systems, which has led to significant improvements in the delivery of care. These indicators help assess adherence to clinical guidelines, timeliness of treatment, safety of practices, and overall patient survival. Data from these countries show that the use of QIs correlates with improved five-year survival rates, earlier diagnosis, better adherence to evidence-based treatment protocols, and increased patient satisfaction. For example, in the Netherlands and Germany, the introduction of quality cancer care programs has led to improved surgical outcomes and overall survival for patients with colorectal cancer. The United Kingdom and Denmark have reported improvements in waiting times for diagnosis and treatment, and in Israel, screening rates for breast and colorectal cancer increased after the introduction of QIs for monitoring these conditions. The current review highlights the fact that countries with robust reporting systems and national cancer registries with high levels of data completeness, such as Denmark, Sweden, and Norway, were able to effectively monitor outcomes and adjust clinical practices accordingly. The findings suggest that implementing QIs in cancer care not only improves clinical outcomes but also promotes accountability and stimulates improved healthcare, ensuring better long-term patient care. This study highlights the value of adopting QIs as a global standard for assessing cancer care. Full article

(This article belongs to the Section Cancer Survivorship and Quality of Life)

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