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Recent Articles

15 pages, 251 KiB

Open AccessArticle

The Impact of COVID-19 on Healthcare Services, Risk Management, and Infection Prevention in Surgical Settings: A Qualitative Study

by Alice Yip, Jeff Yip, Zoe Tsui, Cheung-Hai Yip, Hau-Ling Lung, Kam-Yee Shit and Rachel Yip

Healthcare 2025, 13(6), 579; https://doi.org/10.3390/healthcare13060579 (registering DOI) - 7 Mar 2025

Abstract

Background/Objective In every surgical environment, the prevention of surgical site infections is not merely desirable but essential, given their profound impact on patient health and healthcare costs. To optimize patient care during surgery, a thorough exploration and assessment of all intraoperative nursing practices are necessary, guided by empirical evidence. The aim of this study was to explore nurses’ experiences with surgical site infection prevention practices in the intraoperative setting. Methods Twenty-one nurses working in clinical settings in Hong Kong participated in semi-structured interviews for this qualitative study. Data were analyzed using Colaizzi’s seven-step method. Results Four main themes were identified from the interview data: ensuring safety and minimizing threats; facing silent, intangible, and hidden risks; team collaboration in eliminating risks; and persistent knowledge acquisition. Conclusions Nurses encountered diverse obstacles tied to teamwork, updated knowledge, communication, and patient safety. Enhanced quality of care in clinical settings can be achieved through strategic implementations. Focusing on quality improvement initiatives, establishing consistent teams, and recognizing the vital role of nurses strengthen care delivery. These actions contribute significantly to preventing surgical site infections and ensuring patient safety during intraoperative nursing practices. Full article

(This article belongs to the Collection The Impact of COVID-19 on Healthcare Services)

37 pages, 1801 KiB

Open AccessArticle

Urban Stakeholders for Sustainable and Smart Cities: An Innovative Identification and Management Methodology

by Rafael Esteban-Narro, Vanesa G. Lo-Iacono-Ferreira and Juan Ignacio Torregrosa-López

Smart Cities 2025, 8(2), 41; https://doi.org/10.3390/smartcities8020041 (registering DOI) - 7 Mar 2025

Abstract

The global challenges that cities must face regarding sustainability, efficiency, integration, and resilience have found in the smart city concept a guideline of action as a model for urban development and transformation. The multidimensional nature of the smart city, along with the importance of identifying key urban stakeholders and ensuring their engagement, are two widely recognized characteristics within the scientific community. However, proposals for the identification, classification, and management of urban stakeholders are very scarce and almost non-existent when considered in conjunction with the holistic nature of smart cities. Thus, the significant importance attributed to stakeholder engagement contrasts with the lack of clear guidelines to develop it properly. Based on an iterative analysis of the scientific literature combined with the cross-referencing of smart city dimensions, statistical analysis tools, and multi-criteria analysis methods, this paper proposes a new methodology for the identification and management of urban stakeholders. The proposal includes a comprehensive classification and a new framework for developing urban stakeholder identification processes at their early stages or the monitoring and assessment of ongoing or completed processes, including tools for analyzing the extent and homogeneity achieved. The practical application of the methodology to a specific case study is also discussed. Full article

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18 pages, 706 KiB

Open AccessReview

Neural Excitatory/Inhibitory Imbalance in Motor Aging: From Genetic Mechanisms to Therapeutic Challenges

by Xuhui Chen, Ya Wang, Yongning Zhang, Xucheng Li, Le Zhang, Shangbang Gao and Cuntai Zhang

Biology 2025, 14(3), 272; https://doi.org/10.3390/biology14030272 (registering DOI) - 7 Mar 2025

Abstract

Neural excitatory/inhibitory (E/I) imbalance plays a pivotal role in the aging process. However, despite its significant impact, the role of E/I imbalance in motor dysfunction and neurodegenerative diseases has not received sufficient attention. This review explores the mechanisms underlying motor aging through the lens of E/I balance, emphasizing genetic and molecular factors that contribute to this imbalance (such as SCN2A, CACNA1C, GABRB3, GRIN2A, SYT, BDNF…). Key regulatory genes, including REST, vps-34, and STXBP1, are examined for their roles in modulating synaptic activity and neuronal function during aging. With insights drawn from ALS, we discuss how disruptions in E/I balance contribute to the pathophysiology of age-related motor dysfunction. The genes discussed above exhibit a certain association with age-related motor neuron diseases (like ALS), a relationship that had not been previously recognized. Innovative genetic therapies, such as gene editing technology and optogenetic manipulation, are emerging as promising tools for restoring E/I balance, offering hope for ameliorating motor deficits in aging. This review explores the potential of these technologies to intervene in aging-related motor diseases, despite challenges in their direct application to human conditions. Full article

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19 pages, 2634 KiB

Open AccessArticle

An Experimental Assessment of Miscanthus x giganteus for Landfill Leachate Treatment: A Case Study of the Grebača Landfill in Obrenovac

by Svetozar Andrić, Goran Knežević, Snežana Maletić, Srđan Rončević, Marijana Kragulj Isakovski, Tijana Zeremski and Jelena Beljin

Processes 2025, 13(3), 768; https://doi.org/10.3390/pr13030768 (registering DOI) - 7 Mar 2025

Abstract

Water pollution caused by landfill leachate, which contains high concentrations of heavy metals and organic contaminants, poses a serious environmental threat. Among the potential remediation strategies, phytoremediation using Miscanthus x giganteus (giant miscanthus) has gained attention due to its strong resistance to harsh conditions and its capacity to accumulate heavy metals. This study evaluates the effectiveness of Miscanthus x giganteus in treating landfill leachate, with a focus on removing key pollutants such as zinc (Zn), nickel (Ni), and copper (Cu) by simulating wetland conditions. A pilot-scale experiment conducted at the Grebača landfill site assessed the plant’s ability to enhance metal bioavailability, stabilize contaminants, and limit their mobility within the leachate system. The results demonstrated that Miscanthus x giganteus effectively mobilized Zn and Ni through rhizospheric activity, whereas Cu remained largely immobile, indicating potential for phytostabilization. Sequential extraction analysis further confirmed that the plant significantly reduced the mobile fractions of Zn and Ni in the soil, highlighting its dual role in both phytoremediation and phytostabilization. These findings suggest that Miscanthus x giganteus offers a sustainable and cost-effective approach to landfill leachate treatment, serving as a viable alternative to conventional methods. By integrating this nature-based solution into industrial and municipal waste management, it promotes environmental sustainability while enhancing remediation efficiency. Full article

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

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25 pages, 4295 KiB

Open AccessArticle

Sound Change and Consonant Devoicing in Word-Final Sibilants: A Study of Brazilian Portuguese Plural Forms

by Wellington Mendes, Jr.

Languages 2025, 10(3), 48; https://doi.org/10.3390/languages10030048 (registering DOI) - 7 Mar 2025

Abstract

This study investigates consonant devoicing in Brazilian Portuguese (BP), in order to assess whether an ongoing sound change is taking place. We examine plural forms consisting of a stop consonant followed by a word-final sibilant, such as in redes [hedz] ~ [heds] ~ [hets] and sedes [sɛdz] ~ [sɛds] ~ [sɛts], focusing on the emergence of voiceless sibilants before word-initial vowels (e.g., redes amarelas, ‘yellow hammocks’). If sibilants remain voiceless despite a following vowel, this challenges the expected regressive voicing assimilation in BP and raises the question of the conditions under which this devoicing occurs. Data were collected through recordings of oral production from twenty Brazilian speakers, using reading and picture naming tasks. Sibilant voicing was quantified using harmonics-to-noise ratio (HNR). A linear mixed-effects model—including random intercepts and slopes for both speakers and words—reveals that sibilants are significantly more voiced before a vowel than before a pause, but this voicing is substantially reduced when the sibilant is preceded by voiceless consonants. These findings indicate an ongoing devoicing process at pre-vocalic word boundaries in BP, affecting clusters [pz, tz, kz] and [bz, dz, gz] alike. Spectrographic analyses indicate that not only the sibilants but also their preceding stop may exhibit devoicing. Moreover, minimal-pair considerations suggest that speakers potentially maintain sibilant voicing in certain lexical items to preserve intelligibility (e.g., gra[dz] ‘grades’ and se[dz] ‘headquarters’ vs. grá[ts] ‘free’ and se[ts] ‘sets’). Drawing on Exemplar Theory, we propose a competition between the influence of the phonological environment and word-final devoicing: sibilants are sometimes voiced due to a following vowel (e.g., botes argentinos [bɔtz ah.ʒẽ.’tʃi.nus] ‘Argentine boats’), but they often emerge as voiceless due to consonantal devoicing (e.g., [bɔts ah.ʒẽ.’tʃi.nus]), resulting in both expected and unexpected forms. We suggest that fine phonetic detail, whether associated with allophonic or emergent sound patterns, contributes to the construction of phonological representations. Full article

(This article belongs to the Special Issue Phonetics and Phonology of Ibero-Romance Languages)

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11 pages, 2504 KiB

Open AccessArticle

CO₂-Responsive Plugging Gel with Sodium Dodecyl Sulfate, Polyethyleneimine, and Silica

by Fanghui Liu, Mingmin Zhang, Huiyu Huang, Rui Cheng and Xin Su

Polymers 2025, 17(6), 706; https://doi.org/10.3390/polym17060706 (registering DOI) - 7 Mar 2025

Abstract

Gas channeling during CO₂ flooding poses a significant challenge to enhanced oil recovery (EOR) in heterogeneous reservoirs, limiting both oil recovery and CO₂ sequestration efficiency. To address this issue, a CO₂-responsive plugging gel was developed using polyethyleneimine (PEI), sodium dodecyl sulfate (SDS), and nano-silica. The gel formulation, containing 0.8% SDS, 0.8% PEI, and 0.1% nano-silica, demonstrated excellent CO₂-responsive thickening behavior, achieving a viscosity of over 12,000 mPa·s under selected conditions. The gel exhibited reversible viscosity changes upon CO₂ and N₂ injection, shear-thinning and self-healing properties, and stability under high-temperature (90 °C) and high-salinity (up to 20,000 mg/L) conditions. Plugging experiments using artificial cores with gas permeabilities of 100 mD and 500 mD achieved a plugging efficiency exceeding 95%, reducing permeability to below 0.2 mD. These results emphasize the potential of the CO₂-responsive plugging gel as an efficient approach to reducing gas channeling, boosting oil recovery, and enhancing CO₂ storage capacity in crude oil reservoirs. Full article

(This article belongs to the Special Issue Synthesis, Structure, Characterization and Application of Polymer Networks and Gels)

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24 pages, 1543 KiB

Open AccessArticle

Stochastic Up-Scaling of Discrete Fine-Scale Models Using Bayesian Updating

by Muhammad Sadiq Sarfaraz, Bojana V. Rosić and Hermann G. Matthies

Computation 2025, 13(3), 68; https://doi.org/10.3390/computation13030068 (registering DOI) - 7 Mar 2025

Abstract

In this work, we present an up-scaling framework in a multi-scale setting to calibrate a stochastic material model. In particular with regard to application of the proposed method, we employ Bayesian updating to identify the probability distribution of continuum-based coarse-scale model parameters from fine-scale measurements, which is discrete and also inherently random (aleatory uncertainty) in nature. Owing to the completely dissimilar nature of models for the involved scales, the energy is used as the essential medium (i.e., the predictions of the coarse-scale model and measurements from the fine-scale model) of communication between them. This task is realized computationally using a generalized version of the Kalman filter, employing a functional approximation of the involved parameters. The approximations are obtained in a non-intrusive manner and are discussed in detail especially for the fine-scale measurements. The demonstrated numerical examples show the utility and generality of the presented approach in terms of obtaining calibrated coarse-scale models as reasonably accurate approximations of fine-scale ones and greater freedom to select widely different models on both scales, respectively. Full article

(This article belongs to the Special Issue Synergy between Multiphysics/Multiscale Modeling and Machine Learning)

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Abstract

The cost of producing organic crops is increasing. Agricultural wastes can be used as biostimulants to increase plant growth and productivity and reduce the dependence on chemical fertilizers. A pouch assay and a potted greenhouse experiment were conducted to investigate the effect of pyroligneous acid (PA) and sea lettuce (SL) on kale (Brassica oleracea subsp. acephala (DC.) Metzg) seed germination and growth. Although previous studies have demonstrated that these two biostimulants could promote plant germination and growth, there is little research to compare their effects on seed germination and plant growth. The pouch assay showed that PA liquid affected the seed germination rate under different concentrations; the seed germination rate decreased as the concentration of PA liquid increased. However, the effect of seed germination was less pronounced in SL liquids. Kale seeds treated with 0.01% PA showed the best elongation and seedling growth performance. Moreover, the greenhouse experiment indicates that SL liquids significantly (p < 0.05) affected kale growth production, while PA liquid had less difference on kale growth under various concentrations. The 0.25% PA and 1% SL increased the aboveground fresh weight by ca. 26% and 29%, respectively. Also, the phytochemical contents of kale leaves, including phenolics, flavonoids, ascorbate, and protein, were significantly increased with 0.25% PA and 1% SL application. These results suggest that low concentrations of PA are more suitable for seedling root growth in kale and 1% SL had the most significant growth-promoting effect on kale. Hydrothermal carbonization sea lettuce liquid can be used as a good biostimulant for agricultural production to improve kale germination and growth. Full article

19 pages, 4910 KiB

Open AccessArticle

A Novel SHAP-GAN Network for Interpretable Ovarian Cancer Diagnosis

by Jingxun Cai, Zne-Jung Lee, Zhihxian Lin and Ming-Ren Yang

Mathematics 2025, 13(5), 882; https://doi.org/10.3390/math13050882 - 6 Mar 2025

Abstract

Ovarian cancer stands out as one of the most formidable adversaries in women’s health, largely due to its typically subtle and nonspecific early symptoms, which pose significant challenges to early detection and diagnosis. Although existing diagnostic methods, such as biomarker testing and imaging, can help with early diagnosis to some extent, these methods still have limitations in sensitivity and accuracy, often leading to misdiagnosis or missed diagnosis. Ovarian cancer’s high heterogeneity and complexity increase diagnostic challenges, especially in disease progression prediction and patient classification. Machine learning (ML) has outperformed traditional methods in cancer detection by processing large datasets to identify patterns missed by conventional techniques. However, existing AI models still struggle with accuracy in handling imbalanced and high-dimensional data, and their “black-box” nature limits clinical interpretability. To address these issues, this study proposes SHAP-GAN, an innovative diagnostic model for ovarian cancer that integrates Shapley Additive exPlanations (SHAP) with Generative Adversarial Networks (GANs). The SHAP module quantifies each biomarker’s contribution to the diagnosis, while the GAN component optimizes medical data generation. This approach tackles three key challenges in medical diagnosis: data scarcity, model interpretability, and diagnostic accuracy. Results show that SHAP-GAN outperforms traditional methods in sensitivity, accuracy, and interpretability, particularly with high-dimensional and imbalanced ovarian cancer datasets. The top three influential features identified are PRR11, CIAO1, and SMPD3, which exhibit wide SHAP value distributions, highlighting their significant impact on model predictions. The SHAP-GAN network has demonstrated an impressive accuracy rate of 99.34% on the ovarian cancer dataset, significantly outperforming baseline algorithms, including Support Vector Machines (SVM), Logistic Regression (LR), and XGBoost. Specifically, SVM achieved an accuracy of 72.78%, LR achieved 86.09%, and XGBoost achieved 96.69%. These results highlight the superior performance of SHAP-GAN in handling high-dimensional and imbalanced datasets. Furthermore, SHAP-GAN significantly alleviates the challenges associated with intricate genetic data analysis, empowering medical professionals to tailor personalized treatment strategies for individual patients. Full article

(This article belongs to the Special Issue Advances in Artificial Intelligence, Machine Learning and Optimization)

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