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28 pages, 6885 KiB

Open AccessArticle

A Novel Set of Analysis Tools Integrated with the Energy Gap Method for Energy Accounting Center Diagnosis in Polymer Production

by Omar Augusto Estrada-Ramírez, Nicolás Andrés Muñoz-Realpe, Julián Alberto Patiño-Murillo and Farid Chejne

Resources 2025, 14(4), 60; https://doi.org/10.3390/resources14040060 (registering DOI) - 2 Apr 2025

Abstract

Energy and production efficiency are critical for achieving sustainability and competitiveness in polymer processing plants. A system with high energy efficiency and performance enhances productivity while reducing greenhouse gas emissions. While Monitoring and Targeting (M&T) methodologies are widely used for energy control in [...] Read more.

Energy and production efficiency are critical for achieving sustainability and competitiveness in polymer processing plants. A system with high energy efficiency and performance enhances productivity while reducing greenhouse gas emissions. While Monitoring and Targeting (M&T) methodologies are widely used for energy control in Energy Accounting Centers (EACs), they do not provide a diagnostic framework. The Energy Gap Method (EGM), introduced in 2018, addresses this gap by identifying the origin and magnitude of energy inefficiencies through a hierarchical model that defines six levels of specific energy consumption (SEC). Inspired by M&T strategies, the EGM has led to the development of diagnostic tools, including the Performance Characteristic Line for Diagnostics (PCLD), the Activity-Based Target from Diagnostics (ABTD), and the Performance Characteristic Curve for Diagnostics (PCCD). These tools enable manufacturers to determine optimal production batch sizes, establish minimum productivity requirements, identify molds and product references requiring intervention, and support the design of energy-efficient components. By integrating these tools, manufacturers can optimize energy consumption, achieve cost savings, and enhance environmental sustainability. This paper presents the methodology and two case studies demonstrating the analytical capabilities of the developed tools in improving energy efficiency within polymer production processes. Full article

(This article belongs to the Special Issue Assessment and Optimization of Energy Efficiency)

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15 pages, 9386 KiB

Open AccessArticle

Ovarian Endometriosis Accelerates Premature Ovarian Failure and Contributes to Osteoporosis and Cognitive Decline in Aging Mice

by Lei Ge, Yali Yang, Tianxia Xiao, Yuqing Gao, Wakam Chang, Feifei Du, Ming Yu and Jian V. Zhang

Int. J. Mol. Sci. 2025, 26(7), 3313; https://doi.org/10.3390/ijms26073313 (registering DOI) - 2 Apr 2025

Abstract

Ovarian endometriosis (OEM) is a chronic inflammatory condition that impairs ovarian function. While its effects on ovarian reserve are well established, the long-term consequences of OEM on ovarian dysfunction, premature ovarian failure (POF), and systemic health, particularly in the context of accelerated aging, [...] Read more.

Ovarian endometriosis (OEM) is a chronic inflammatory condition that impairs ovarian function. While its effects on ovarian reserve are well established, the long-term consequences of OEM on ovarian dysfunction, premature ovarian failure (POF), and systemic health, particularly in the context of accelerated aging, remain insufficiently studied. In this study, we employed an OEM mouse model and bulk RNA sequencing to investigate the underlying mechanisms. Our results show that OEM accelerates primordial follicle depletion and upregulates mTOR signaling pathway gene expression, along with mechanical stress and paracrine signaling via the Hippo and Myc pathways. OEM also induces irregular estrus and ovarian fibrosis in aging mice, decreases serum AMH levels, and increases FSH levels. Systemically, elevated serum IgG levels contribute to osteoporosis and cognitive decline, both linked to ovarian dysfunction and POF in OEM. These findings elucidate the mechanisms driving premature ovarian reserve depletion in OEM and highlight its broader systemic effects. This study emphasizes the importance of monitoring ovarian health and ectopic tissue to safeguard ovarian reserves and mitigate long-term risks such as osteoporosis and cognitive decline. Full article

(This article belongs to the Special Issue Molecular Advances in Artificial Reproduction and Female Health: From Molecular Diagnosis to the Treatment of Gynecological Diseases)

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27 pages, 3630 KiB

Open AccessArticle

Integrated Smart City Solutions: A Multi-Axis Approach for Sustainable Development in Varanasi

by Flavia Vespasiano, Tejas Gujrati, Behnam Abbasi and Fabio Bisegna

Sustainability 2025, 17(7), 3152; https://doi.org/10.3390/su17073152 (registering DOI) - 2 Apr 2025

Abstract

In this era of perpetual advancement and innovation, the term “smart” is frequently misused. Linking smartness to a city should reflect and solve multiple problems with a single solution. A city, district, or area can only be smart when it contemplates different development [...] Read more.

In this era of perpetual advancement and innovation, the term “smart” is frequently misused. Linking smartness to a city should reflect and solve multiple problems with a single solution. A city, district, or area can only be smart when it contemplates different development axes rather than having just a single strength. This work is an effort to make an area of Varanasi in Uttar Pradesh, India, smart by concentrating the actions on five principal axes—Environment, Energy, Mobility, Community, and Economy. Practical indicators have been selected and well formalised to obtain an output value that can support the methodology to rank each action in its executable manner. Software like ENVI-met (to simulate greening and pollution) and PVSyst (to simulate rooftop solar PV) have been used to simulate the actions proposed, and a detailed discussion for each result has been presented. The methodology involves the creation of a model based on morphological, structural, and environmental data, as well as using SWOT analysis and community feedback to identify key areas for intervention. The results demonstrate the effectiveness of the proposed interventions, with notable reductions in CO₂ emissions, improved air quality, and significant energy savings through the implementation of Nature-Based Solutions, solar PV systems, and electric mobility. Full article

(This article belongs to the Special Issue Environmental Sustainability and Design Strategies of Future Smart Energy Systems)

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26 pages, 8883 KiB

Open AccessArticle

Enhancing Machine Learning Techniques in VSLAM for Robust Autonomous Unmanned Aerial Vehicle Navigation

by Hussam Rostum and József Vásárhelyi

Electronics 2025, 14(7), 1440; https://doi.org/10.3390/electronics14071440 (registering DOI) - 2 Apr 2025

Abstract

This study introduces a visual SLAM real-time system designed for small indoor environments. The system demonstrates resilience against significant motion clutter and supports wide-baseline loop closing, re-localization, and automatic initialization. Leveraging state-of-the-art algorithms, the approach presented in this article utilizes adapted Oriented FAST [...] Read more.

This study introduces a visual SLAM real-time system designed for small indoor environments. The system demonstrates resilience against significant motion clutter and supports wide-baseline loop closing, re-localization, and automatic initialization. Leveraging state-of-the-art algorithms, the approach presented in this article utilizes adapted Oriented FAST and Rotated BRIEF features for tracking, mapping, re-localization, and loop closing. In addition, the research uses an adaptive threshold to find putative feature matches that provide efficient map initialization and accurate tracking. The assignment is to process visual information from the camera of a DJI Tello drone for the construction of an indoor map and the estimation of the trajectory of the camera. In a ’survival of the fittest’ style, the algorithms selectively pick adaptive points and keyframes for reconstruction. This leads to robustness and a concise traceable map that develops as scene content emerges, making lifelong operation possible. The results give an improvement in the RMSE for the adaptive ORB algorithm and the adaptive threshold (3.280). However, the standard ORB algorithm failed to achieve the mapping process. Full article

(This article belongs to the Special Issue Development and Advances in Autonomous Driving Technology)

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17 pages, 3783 KiB

Open AccessArticle

A Multi-Scale CNN-BiLSTM Framework with An Attention Mechanism for Interpretable Structural Damage Detection

by Shengping Wu and Jingliang Liu

Infrastructures 2025, 10(4), 82; https://doi.org/10.3390/infrastructures10040082 (registering DOI) - 2 Apr 2025

Abstract

Structural damage detection is essential for civil infrastructure safety. The challenges in noise sensitivity, multi-scale feature extraction, and handling bidirectional temporal dependencies are often encountered by traditional methods such as vibration analysis and computer vision. Although potential solutions are offered by recent deep-learning [...] Read more.

Structural damage detection is essential for civil infrastructure safety. The challenges in noise sensitivity, multi-scale feature extraction, and handling bidirectional temporal dependencies are often encountered by traditional methods such as vibration analysis and computer vision. Although potential solutions are offered by recent deep-learning advancements, limitations are frequently imposed by low interpretability and the incapability to adaptively prioritize crucial features within complex time-series data. To address these, a novel hybrid deep-learning framework is proposed. It is integrated with multi-scale convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and attention mechanisms. Localized time-frequency features are captured from vibration signals by the CNN using multi-scale kernels. Bidirectional temporal dependencies are skillfully captured by the BiLSTM. The interpretability is improved by the attention mechanism through dynamic feature weighting. Experiments on a simulated steel frame demonstrate that detection accuracy and robustness can be enhanced by this framework. This work promotes structural health monitoring, providing a practical tool for engineering applications. Full article

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23 pages, 14743 KiB

Open AccessArticle

Mechanistic Insights into Sphingomyelin Nanoemulsions as Drug Delivery Systems for Non-Small Cell Lung Cancer Therapy

by Emma Ramos Docampo, Jenifer García-Fernández, Inés Mármol, Irene Morín-Jiménez, Maria Iglesias Baleato and María de la Fuente Freire

Pharmaceutics 2025, 17(4), 461; https://doi.org/10.3390/pharmaceutics17040461 (registering DOI) - 2 Apr 2025

Abstract

Sphingomyelin nanoemulsions (SNs) are promising drug delivery systems with potential for treating challenging tumors, including non-small cell lung cancer (NSCLC), which has a poor prognosis and a 5-year survival rate below 5%. Understanding the toxicity mechanisms and intracellular behavior of SNs is crucial [...] Read more.

Sphingomyelin nanoemulsions (SNs) are promising drug delivery systems with potential for treating challenging tumors, including non-small cell lung cancer (NSCLC), which has a poor prognosis and a 5-year survival rate below 5%. Understanding the toxicity mechanisms and intracellular behavior of SNs is crucial for optimizing their therapeutic application. This study aims to investigate the interaction between SNs and A549 lung adenocarcinoma cells, focusing on their cytotoxic effects and mechanisms of cellular toxicity. SNs were synthesized and characterized for size, surface charge, and stability. A549 cells were treated with varying concentrations of SNs, and cellular uptake pathways were assessed using inhibitors of energy-dependent processes. Cytotoxicity was evaluated through an alamarBlue assay to determine the IC₅₀ value after 24 h. Mechanisms of toxicity, including lysosomal and mitochondrial involvement, were examined using co-localization studies, mitochondrial membrane potential assays, and markers of apoptosis. SNs exhibited rapid cellular uptake via energy-dependent pathways. The IC₅₀ concentration for A549 cells was 0.89 ± 0.15 mg/mL, suggesting favorable cytocompatibility compared to other nanocarriers. At IC₅₀, SNs induced apoptosis characterized by lysosomal damage, mitochondrial membrane permeabilization, and the release of apoptotic factors. These effects disrupted autophagic flux and contributed to cell death, demonstrating potential for overcoming drug resistance. Resveratrol-loaded SNs showed enhanced cytotoxicity, supporting their application as targeted drug delivery vehicles. This study highlights the potential of SNs as efficient drug delivery systems for NSCLC therapy, offering insights into their cellular interactions and toxicity mechanisms. These findings pave the way for the rational design of SN-based therapeutic platforms for cancer and other mitochondria-related diseases. Full article

(This article belongs to the Special Issue New Nano-Systems for Imaging, Diagnostics, and Drug Delivery)

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36 pages, 4875 KiB

Open AccessArticle

Sustainable Removal of Basic Fuchsine and Methylene Blue Dyes Using Chicken Bone Biomass: Thermodynamics, Kinetics, and Insights from Experimental Studies and Decision Tree with Least Squares Boosting Predictive Modeling

by Assia Ouzani, Yamina Zouambia, Hamida Maachou, Mohamed Krea, Amine Aymen Assadi, Lotfi Khezami, Yacine Benguerba, Jie Zhang, Abdeltif Amrane, Walid Elfalleh and Hichem Tahraoui

Water 2025, 17(7), 1053; https://doi.org/10.3390/w17071053 (registering DOI) - 2 Apr 2025

Abstract

This study addresses the dual challenges of water pollution and waste management by exploring the valorization of chicken bone biomass in native (NBio) and calcined (CBio) forms as biosorbents for dye removal. Basic fuchsine (BF) and methylene blue (MB) were selected as model [...] Read more.

This study addresses the dual challenges of water pollution and waste management by exploring the valorization of chicken bone biomass in native (NBio) and calcined (CBio) forms as biosorbents for dye removal. Basic fuchsine (BF) and methylene blue (MB) were selected as model pollutants, and adsorption was assessed under varying operational conditions. Characterization using Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD) showed that calcination improved crystallinity, eliminated organic impurities, and increased surface area (247 m²/g for NBio vs. 370 m²/g for CBio). Adsorption tests revealed higher performance for CBio, with maximum adsorption capacities of 100 mg/g (BF) and 142.85 mg/g (MB) based on the Langmuir isotherm, while NBio with maximum adsorption capacities of 111 mg/g (BF) and 111.11 mg/g (MB) followed the Freundlich model. Adsorption kinetics indicated pseudo-second-order behavior, suggesting chemisorption. The possible interactions between dyes and the biosorbent are hydrogen bonding, electrostatic interactions, and Lewis acid–base interactions. Thermodynamic analysis highlighted exothermic behavior for NBio and endothermic, entropy-driven adsorption for CBio, with both processes being spontaneous. A decision tree with Least Squares Boosting (DT_LSBOOST) provided accurate predictions (R² = 0.9999, RMSE < 0.003) by integrating key parameters. These findings promote chicken bone biomass as a cost-effective, sustainable biosorbent, offering promising potential in wastewater treatment and environmental remediation. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

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24 pages, 3625 KiB

Open AccessArticle

Comparative Study on the Effects of Selenium-Enriched Yeasts with Different Selenomethionine Contents on Gut Microbiota and Metabolites

by Zijian Zhang, Li Zhu, Hongtao Zhang, Dan Yu, Zhongwei Yin and Xiaobei Zhan

Int. J. Mol. Sci. 2025, 26(7), 3315; https://doi.org/10.3390/ijms26073315 (registering DOI) - 2 Apr 2025

Abstract

Selenium is an essential trace element for human health, but it mainly exists in an inorganic form that cannot be directly absorbed by the body. Brewer’s yeast efficiently converts inorganic selenium into bioavailable organic selenium, making selenium-enriched yeast highly significant for human health [...] Read more.

Selenium is an essential trace element for human health, but it mainly exists in an inorganic form that cannot be directly absorbed by the body. Brewer’s yeast efficiently converts inorganic selenium into bioavailable organic selenium, making selenium-enriched yeast highly significant for human health research. Selenomethionine (SeM) is an important indicator for evaluating the quality of selenium-enriched yeast. Brewer’s yeast was selected as the experimental subject, and the digestion of this yeast (Brewer’s yeast) was simulated using an in vitro biomimetic gastrointestinal reactor to evaluate the effects of selenium-enriched yeast with various SeM levels on the gut flora of a healthy population. The experimental design comprised normal yeast (control group, OR), yeast containing moderate SeM levels (selenium-enriched group, SE), yeast containing high SeM levels (high-selenium group, MU), and a commercially available group comprising selenium-enriched yeast tablets (MA). The MU group exhibited a significantly higher concentration of short-chain fatty acids than the OR and MA groups during 48 h of fermentation, with significant differences observed (p < 0.05). Sequencing results revealed that the MU group showed significantly increased relative abundances of Bacteroidetes and Actinobacteria, while exhibiting a decreased ratio of Firmicutes to Bacteroidetes, which may simultaneously affect multiple metabolic pathways in vivo. These findings support the theory that selenium-enriched yeast with a high SeM has a more positive effect on human health compared with traditional yeast and offer new ideas for the development and application of selenium-enriched yeast. Full article

(This article belongs to the Special Issue Plant Resilience: Insights into Abiotic and Biotic Stress Adaptations)

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21 pages, 7365 KiB

Open AccessArticle

Analysis of Wind-Induced Vibration Response of Transmission Wire Under Crosswind in Canyon Terrain

by Jianhui Chen and Chaohui Zhou

Appl. Sci. 2025, 15(7), 3902; https://doi.org/10.3390/app15073902 (registering DOI) - 2 Apr 2025

Abstract

The conventional unidirectional coupling method, which separates the flow field from the solid, is generally used for calculations to study the wind-induced response of overhead transmission wires in complex micro-terrain conditions. This study constructed a calculation method for the strong bidirectional coupling of [...] Read more.

The conventional unidirectional coupling method, which separates the flow field from the solid, is generally used for calculations to study the wind-induced response of overhead transmission wires in complex micro-terrain conditions. This study constructed a calculation method for the strong bidirectional coupling of vibrations in canyon terrain based on the bidirectional coupling theory and analyzed the vibration characteristics of a transmission wire under step and pulse wind speed conditions. The simulation results show that the wire’s displacement trend was basically the same and the oscillation period was the same under different step wind speed conditions. The influence of the pulse width on the wire displacement was periodic under pulse wind speed conditions, and the pulse amplitude affected the displacement amplitude. Full article

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24 pages, 2762 KiB

Open AccessArticle

Federated Subgraph Learning via Global-Knowledge-Guided Node Generation

by Yuxuan Liu, Zhiming He, Shuang Wang, Yangyang Wang, Peichao Wang, Zhangshen Huang and Qi Sun

Sensors 2025, 25(7), 2240; https://doi.org/10.3390/s25072240 (registering DOI) - 2 Apr 2025

Abstract

Federated graph learning (FGL) is a combination of graph representation learning and federated learning that utilizes graph neural networks (GNNs) to process complex graph-structured data while addressing data silo issues. However, during the local training of GNNs, each client only has access to [...] Read more.

Federated graph learning (FGL) is a combination of graph representation learning and federated learning that utilizes graph neural networks (GNNs) to process complex graph-structured data while addressing data silo issues. However, during the local training of GNNs, each client only has access to a subgraph, significantly deteriorating performance. To address this issue, recent solutions propose completing the subgraph with pseudo graph nodes generated by a generator trained using the local subgraph. Despite their effectiveness, such methods may introduce biases as the local pseudo graph nodes cannot accurately represent the global graph distribution. To overcome this problem, we introduce MN-FGAGN, which mitigates the impact of missing neighbor information by generating pseudo graph nodes that follow the global distribution. The main idea of our approach is to partition the generative adversarial neural network into a client-side discriminator and a server-side generator. In this way, the generator can receive supervised information from all clients and can thus generate graph nodes that contain global information. Experiments on four real-world graph datasets show that it outperforms the state-of-the-art methods. Full article

(This article belongs to the Section Sensor Networks)

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15 pages, 695 KiB

Open AccessArticle

Impact of Heat Treatment on Hard Cider Enriched with Cryo-Concentrated Apple Must: Microbiological Profile, Functional Properties, and Storage Stability

by Matheus de Melo Carraro, Isabela Maria Macedo Simon Sola, Raul Dias Moreira dos Santos, Ivo Mottin Demiate, Aline Alberti and Alessandro Nogueira

Fermentation 2025, 11(4), 188; https://doi.org/10.3390/fermentation11040188 (registering DOI) - 2 Apr 2025

Abstract

This study evaluated the impact of heat treatment on the microbiological, chemical, and functional properties of hard cider enriched with cryo-concentrate over 180 days of storage. The experimental protocol for the hard cider was assessed under three conditions: room temperature (18–23 °C, CA), [...] Read more.

This study evaluated the impact of heat treatment on the microbiological, chemical, and functional properties of hard cider enriched with cryo-concentrate over 180 days of storage. The experimental protocol for the hard cider was assessed under three conditions: room temperature (18–23 °C, CA), refrigeration (7–8 °C, CR), and pasteurization at 60 °C for 15 min (P60) and 80 °C for 15 min (P80). The heat treatment employed was mild to preserve the hard cider’s quality. Microbiological results confirmed proper processing conditions. Pasteurization reduced the initial populations of molds and yeasts by 92.9% (P80) and 83.3% (P60), while lactic acid bacteria decreased by over 99.0%. Microbial counts in P60 and P80 continued to decline during storage. Sugar content was the main indicator of instability in P60, particularly at 60 days. Both P60 and P80 ciders exhibited similar reductions in antioxidant activity, with DPPH showing a reduction of 43–45% and ABTS exhibiting a decrease of 50–51%. Additionally, a twofold increase in color intensity (darkening) was observed during storage in heat-treated samples. These findings demonstrate that pasteurization at 80 °C for 15 min effectively extends the shelf life of hard cider with cryo-concentrate to six months at room temperature, offering a practical solution for commercial production. Full article

(This article belongs to the Special Issue Lactic Acid Bacteria Metabolism)

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26 pages, 3676 KiB

Open AccessArticle

A New Endogenous Direction Selection Mechanism for the Direction Distance Function Method Applied to Different Economic–Environmental Development Modes

by Junchao Wang, Jun-Hong Ye and Lei Chen

Sustainability 2025, 17(7), 3151; https://doi.org/10.3390/su17073151 (registering DOI) - 2 Apr 2025

Abstract

As a direction selection in the direction distance function (DDF), endogenous DDF can accurately reflect the numerical characteristics of inputs/outputs, but it is difficult to effectively popularize. And it is also difficult to effectively combine with reality. To solve those problems, this paper [...] Read more.

As a direction selection in the direction distance function (DDF), endogenous DDF can accurately reflect the numerical characteristics of inputs/outputs, but it is difficult to effectively popularize. And it is also difficult to effectively combine with reality. To solve those problems, this paper introduces slack variables to construct a new endogenous direction-setting mechanism, which makes the endogenous model have the conditions to be popularized. Based on the original endogenous DDF, we consider environmental concern, economic concern, coordinated development, and priority development, and then construct six new extended DDF models with slack variables. Based on priority development, we further propose six new extended DDF models. These new extended models can not only realize the complete internalization of direction determination but also overcome the limitations of traditional endogenous models. Combined with the actual case, the emission reduction potential of different areas is revealed, and the improved path is proposed. The results show that the new extended DDF models effectively reflect the different development modes of carbon emissions, and different development modes have a significant impact on emission reduction potential. In addition, compared with economic concern and priority development, coordinated development and environmental concern are most beneficial to carbon emission reduction, but the development mode of environmental concern can better reveal the improved path of environmental development. Full article

(This article belongs to the Special Issue Sustainable Economic Intelligent Information Processing)

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26 pages, 16189 KiB

Open AccessReview

State-of-the-Art Review of Hempcrete for Residential Building Construction

by Anthony C. Jellen and Ali M. Memari

Designs 2025, 9(2), 44; https://doi.org/10.3390/designs9020044 (registering DOI) - 2 Apr 2025

Abstract

Carbon-neutral and carbon-negative construction is gaining significant interest in the home building industry. Accordingly, the development of new materials and innovative redesign of the existing materials are on the rise. This paper presents the results of a review study on hempcrete as a [...] Read more.

Carbon-neutral and carbon-negative construction is gaining significant interest in the home building industry. Accordingly, the development of new materials and innovative redesign of the existing materials are on the rise. This paper presents the results of a review study on hempcrete as a new, emerging construction material, which is crop-based and is accordingly expected to provide a highly sustainable construction system. The paper reviews the mixture design, properties and attributes, different methods for its application in construction, building code requirements for construction of hempcrete homes, mechanical and structural properties for home building, and evaluation of the current state of hempcrete application as a non-load-bearing construction material. The paper also reviews the status of developments toward using hempcrete as a load-bearing system. The study shows a snapshot of the methods used for the construction of hempcrete buildings and touches on efforts that are ongoing to increase the compressive strength of hempcrete toward load-bearing applications. Such an increase would depend on different factors such as curing temperature and humidity, binder type and percentage, hemp-to-binder ratio, water-to-binder ratio, and additives. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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11 pages, 254 KiB

Open AccessArticle

Randomised Clinical Trial: Effect of AH Plus and Neosealer Flo on Postoperative Pain and Healing of Periapical Lesions

by Juan Algar, Cristian Docampo-Vázquez, Cristina Rico-Romano, Ana Boquete-Castro, Cristina Obispo-Díaz and Juan Manuel Aragoneses

Bioengineering 2025, 12(4), 376; https://doi.org/10.3390/bioengineering12040376 (registering DOI) - 2 Apr 2025

Abstract

Apical periodontitis is a common inflammatory condition associated with root canal treatment (RCT) failure. The quality of the three-dimensional root canal seal is critical to the success of the treatment. Bioceramic sealants, such as Neosealer Flo, offer biological advantages such as osteoconduction, biocompatibility [...] Read more.

Apical periodontitis is a common inflammatory condition associated with root canal treatment (RCT) failure. The quality of the three-dimensional root canal seal is critical to the success of the treatment. Bioceramic sealants, such as Neosealer Flo, offer biological advantages such as osteoconduction, biocompatibility and sustained calcium ion release, which may improve apical healing. The aim of this study was to compare AH Plus and Neosealer Flo in terms of postoperative pain, extrusion and periapical healing. A single-blind, randomised clinical trial was conducted with 60 patients divided into AH Plus and Neosealer Flo groups. Post-operative pain was assessed using a visual analogue scale (VAS) at 24 and 48 h and at 7 days. Seal quality and periapical healing were assessed at 6 months using the AAE success criteria by clinical and radiographic evaluation. Neosealer Flo resulted in less postoperative pain at 24 h and 7 days compared to AH Plus. Extrusion did not significantly affect pain or correlate with the type of sealer used. Both materials achieved similar periapical healing rates. Neosealer Flo demonstrated advantages in pain reduction, while both sealants showed comparable efficacy. Full article

(This article belongs to the Special Issue Advanced Biomaterials, Coatings, and Techniques: Applications in Medicine)

18 pages, 8524 KiB

Open AccessArticle

Pull-Out Test and Mechanical Properties Analysis Based on Intelligent Bolt and Internet of Things

by Zengle Li, Huimei Zhang, Xin Li and Junliang He

Appl. Sci. 2025, 15(7), 3901; https://doi.org/10.3390/app15073901 (registering DOI) - 2 Apr 2025

Abstract

The disadvantages of traditional bolt support technology relying too much on engineering experience in slope engineering in China are becoming more and more obvious. Aiming at this problem, this paper establishes an intelligent bolt pull-out test system based on the Internet of Things, [...] Read more.

The disadvantages of traditional bolt support technology relying too much on engineering experience in slope engineering in China are becoming more and more obvious. Aiming at this problem, this paper establishes an intelligent bolt pull-out test system based on the Internet of Things, monitors the whole process of a bolt pull-out test, determines the ultimate pull-out bearing capacity, and grasps the friction of a bolt in real time. Based on the local common deformation theory, the force of the bolt is analyzed theoretically. The results show that the stress process of bolt rod end tension–rod end displacement is divided into quasi-elastic stage, strengthening stage and failure stage. The stress history of bolts with different anchorage lengths is the same, but the curve shape changes from steep to slow with the increase in anchorage length. Increasing the length of the long bolt can increase the ultimate pull-out bearing capacity of the bolt. Full article

(This article belongs to the Special Issue Development, Reliability, Maintenance and Control of Cyber-Physical Systems)

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29 pages, 2458 KiB

Open AccessArticle

The Impact of Income Inequality on Energy Poverty in the European Union

by Mihaela Simionescu

Int. J. Financial Stud. 2025, 13(2), 54; https://doi.org/10.3390/ijfs13020054 (registering DOI) - 2 Apr 2025

Abstract

The EU has consistently tackled the challenge of energy poverty (EP) through various legislative and non-legislative measures, particularly in the context of ongoing energy crisis, but it should also support the reduction of income inequality that might accelerate EP. The aim of this [...] Read more.

The EU has consistently tackled the challenge of energy poverty (EP) through various legislative and non-legislative measures, particularly in the context of ongoing energy crisis, but it should also support the reduction of income inequality that might accelerate EP. The aim of this study is to evaluate the impact of income inequality on EP and other interconnected indicators in the EU in the period 2005–2023 using method of moments quantile (MMQ) regression and mean group (MG) estimators. The results suggest that income inequality based on Gini index enhances energy poverty, while gender pay gap, economic growth, and urban population reduce it. Foreign direct investment (FDI) and renewable energy consumption (REC) might combat EP only in the long-run. These findings suggest that macroeconomic policies should focus not only on economic growth, but also on addressing income inequalities. Policymakers must prioritize measures to reduce income inequality, such as progressive taxation or targeted social programs. Full article

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26 pages, 4195 KiB

Open AccessArticle

Soil Amendment-Mediated Herbivory Resistance, Crop Improvement, and Phytoremediation in Canola: Physiological Defense Mechanism and Health Risk Assessment

by Muhammad Wajid Javed, Mansoor ul Hasan, Muhammad Sagheer, Asim Abbasi, Mubshar Hussain, Muhammad Arshad, Dilbar Hussain, Raja Adil Sarfaraz, Razia Riaz and Nazih Y. Rebouh

Plants 2025, 14(7), 1110; https://doi.org/10.3390/plants14071110 (registering DOI) - 2 Apr 2025

Abstract

A two-year field study was conducted using canola to check the efficacy of different soil amendment treatments (SAT), i.e., with elemental sulfur (ES), bio-sulfur (BS), and compost (Cp) mixtures against insecticide-treated (Carbosulfan) and untreated controls regarding aphid populations. The results of the experiment [...] Read more.

A two-year field study was conducted using canola to check the efficacy of different soil amendment treatments (SAT), i.e., with elemental sulfur (ES), bio-sulfur (BS), and compost (Cp) mixtures against insecticide-treated (Carbosulfan) and untreated controls regarding aphid populations. The results of the experiment revealed that ES treatments significantly reduced aphid abundance, followed by Cp and ES+Cp. However, BS improved aphid herbivory. The number of siliques, seeds, thousand-seed weight, and yield were improved with a trend of ES+Cp > Cp > BS+Cp. Similarly, physiological mechanisms revealed the regulation of nutrient and phenolic contents in canola with ES improving sulfur, BS nitrogen, Cp, and ES+Cp calcium, and BS+Cp enhancing phosphorus, potassium, iron, and zinc. Furthermore, RP-HPCL indicated that ferulic acid was highest in insecticide-treated plot. Similarly, Cp improved quercetin and gallic acid; ES+Cp caffeic, chlorogenic, m-coumaric, and sinapic acid; and BS+Cp enhances syringic, vanillic, ferulic, p-coumaric, and cinnamic acid. The analysis regarding health risk assessment revealed among different SAT, ES+Cp significantly reduced the Hazardous Quotient (HQ) of Cu and Zn. However, further research is still needed to explore SAT’s potential to remediate other heavy metal stresses with possible implications for pest management in different field crops. Full article

(This article belongs to the Collection Feature Papers in Plant Protection)

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12 pages, 1250 KiB

Open AccessArticle

A Light Source Authentication Algorithm Based on the Delay and Sum of the Light Source Emission Sequence

by Deyue Zou, Linna Yan and Siyu Gao

Electronics 2025, 14(7), 1438; https://doi.org/10.3390/electronics14071438 (registering DOI) - 2 Apr 2025

Abstract

Indoor visible light positioning is susceptible to specular interference, which reduces the accuracy of positioning. From the perspective of increasing the number of identity documents (IDs), this paper proposes a light source authentication algorithm based on the delay and sum of the light [...] Read more.

Indoor visible light positioning is susceptible to specular interference, which reduces the accuracy of positioning. From the perspective of increasing the number of identity documents (IDs), this paper proposes a light source authentication algorithm based on the delay and sum of the light source emission sequence. After obtaining the sub-light source emission sequence at the receiving end, the algorithm performs a cross-correlation operation on the adjacent sub-light source emission sequence in chiral order, and the emission sequence delay of the adjacent sub-light source can be obtained. Then, the relationship between the sum of the delays of all emitted sequences and the length of the sequence is calculated to identify the authenticity of the light source array. We conduct a simulation analysis of the light source authentication algorithm based on the delay and sum of the light source emission sequence. The results show that the algorithm can effectively improve the sequence utilization and localization success rate. Compared with the light source authentication algorithm based on the vector product, the number of light source IDs of the proposed algorithm is significantly increased. For example, when the number of light sources is 3 and the sequence length is 63, the number of light source IDs of the proposed algorithm is greater than that of the light source authentication algorithm based on the vector product by about 35. Therefore, the light source authentication algorithm based on the delay and sum of the light source emission sequence can effectively improve the utilization of the sequence. Full article

(This article belongs to the Special Issue Security and Privacy in AI and Large Model-Driven 6G Networks)

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23 pages, 19316 KiB

Open AccessArticle

Enhanced Isolation Forest-Based Algorithm for Unsupervised Anomaly Detection in Lidar SLAM Localization

by Guoqing Geng, Peining Wang, Liqin Sun and Han Wen

World Electr. Veh. J. 2025, 16(4), 209; https://doi.org/10.3390/wevj16040209 (registering DOI) - 2 Apr 2025

Abstract

Lidar SLAM (simultaneous localization and mapping) systems provide vehicles with high-precision maps and localization for environmental perception. However, sensor noise and dynamic changes can lead to the localization drift or localization failure of the SLAM system. Identifying such anomalies currently relies on post-trajectory [...] Read more.

Lidar SLAM (simultaneous localization and mapping) systems provide vehicles with high-precision maps and localization for environmental perception. However, sensor noise and dynamic changes can lead to the localization drift or localization failure of the SLAM system. Identifying such anomalies currently relies on post-trajectory analysis with subjective parameter thresholds. To address this issue, we propose an unsupervised real-time localization anomaly detection model based on the isolation forest algorithm. We first determined the necessity of variable research through variable correlation analysis. Then, we enhanced the scoring mechanism of the isolation forest by introducing a path-weighting method, improving sensitivity to complex variables and anomalies. Finally, to further increase the model’s reliability, we employed an adaptive OTSU (Otsu’s method) algorithm for automatic score classification. Experimental results show that our proposed model can effectively detect positioning anomalies by determining variable thresholds in four scenarios of the KITTI dataset. The results show excellent real-time performance, with an average running time of about 0.02 s, which is shorter than the time required to process a single data frame. Using the mean, RMSE, and standard deviation as evaluation metrics, data comparisons confirmed the algorithm’s accuracy. Compared with several SOTA (state-of-the-art) algorithms and ablation studies, our algorithm also showed higher sensitivity. Full article

(This article belongs to the Special Issue Intelligent Electric Vehicle Control, Testing and Evaluation)

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14 pages, 259 KiB

Open AccessArticle

Diet, Eating Habits, and Lifestyle Factors Associated with Adequate Sleep Duration in Children and Adolescents Living in 5 Mediterranean Countries: The DELICIOUS Project

by Justyna Godos, Alice Rosi, Francesca Scazzina, Maria Antonieta Touriz Bonifaz, Francesca Giampieri, Osama Abdelkarim, Achraf Ammar, Mohamed Aly, Evelyn Frias-Toral, Juancho Pons, Laura Vázquez-Araújo, Josep Alemany-Iturriaga, Lorenzo Monasta, Ana Mata, Adrián Chacón, Pablo Busó and Giuseppe Grosso

Nutrients 2025, 17(7), 1242; https://doi.org/10.3390/nu17071242 (registering DOI) - 2 Apr 2025

Abstract

Background/Objectives: Sleep is a fundamental physiological function that plays a crucial role in maintaining health and well-being. The aim of this study was to assess dietary and lifestyle factors associated with adequate sleep duration in children and adolescents living in five Mediterranean [...] Read more.

Background/Objectives: Sleep is a fundamental physiological function that plays a crucial role in maintaining health and well-being. The aim of this study was to assess dietary and lifestyle factors associated with adequate sleep duration in children and adolescents living in five Mediterranean countries. Methods: Parents of children and adolescents taking part in an initial survey for the DELICIOUS project were examined to assess their children’s dietary and eating habits (i.e., meal routines), as well as other lifestyle behaviors (i.e., physical activity levels, screen time, etc.) potentially associated with adequate sleep duration (defined as 8–10 h according to the National Sleep Foundation). The youth healthy eating index (Y-HEI) was used to assess the diet quality of children and adolescents. Multivariate logistic regression analyses were performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs), indicating the level of association between variables. Results: A total of 2011 individuals participated in the survey. The adolescents and children of younger parents reported being more likely to have inadequate sleep duration. Among eating behaviors, having breakfast (OR = 2.23, 95% CI: 1.62, 3.08) and eating at school (OR = 1.33, 95% CI: 1.01, 1.74) were associated with adequate sleep duration. In contrast, children eating alone, screen time, and eating outside of the home were less likely to have adequate sleep duration, although these findings were only significant in the unadjusted model. After adjusting for covariates, a better diet quality (OR = 1.63, 95% CI: 1.24, 2.16), including higher intake of fruits, meat, fish, and whole grains, was associated with adequate sleep duration. Conclusions: Adequate sleep duration seems to be highly influenced by factors related to individual lifestyles, family and school eating behaviors, as well as diet quality. Full article

(This article belongs to the Special Issue The Impact of Children’s and Adolescents’ Diet, Nutrition and Lifestyle Habits on Physical and Mental Health: From the Latest Perspective)

11 pages, 2124 KiB

Open AccessArticle

Tunable Hydrogen Evolution Reaction Property of Janus SWSe Monolayer Using Defect and Strain Engineering

by Tian Chen, Lu Shen, Fuyuan Wang and Ping Jiang

Molecules 2025, 30(7), 1588; https://doi.org/10.3390/molecules30071588 (registering DOI) - 2 Apr 2025

Abstract

Janus-structured transition metal dichalcogenides (TMDs) demonstrate remarkable electronic, optical, and catalytic characteristics owing to their distinctive asymmetric configurations. In this study, we comprehensively analyze the stability of Janus SWSe containing common vacancy defects through first-principles calculations. The findings indicate that the Gibbs free [...] Read more.

Janus-structured transition metal dichalcogenides (TMDs) demonstrate remarkable electronic, optical, and catalytic characteristics owing to their distinctive asymmetric configurations. In this study, we comprehensively analyze the stability of Janus SWSe containing common vacancy defects through first-principles calculations. The findings indicate that the Gibbs free energy for the hydrogen evolution reaction (HER) is notably decreased to around 0.5 eV, which is lower compared with both pristine SWSe and traditional MoS₂ monolayers. Importantly, the introduction of external strain further improves the HER efficiency of defect-modified Janus SWSe. This enhancement is linked to the adaptive relaxation of localized strain by unsaturated bonds in the defect area, leading to unique adjustable patterns. Our results clarify the fundamental mechanism driving the improved HER performance of SWSe via strain modulation, offering theoretical insights for designing effective HER catalysts using defective Janus TMDs. Full article

(This article belongs to the Special Issue Novel Two-Dimensional Energy-Environmental Materials)

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14 pages, 4102 KiB

Open AccessArticle

Investigation of 2-Mercapto-1-Methylimidazole as a New Type of Leveler in Wafer Electroplating Copper

by Tong Tan, Renlong Liu, Lanfeng Guo, Zhaobo He, Xing Fan, Rui Ye and Changyuan Tao

Materials 2025, 18(7), 1622; https://doi.org/10.3390/ma18071622 (registering DOI) - 2 Apr 2025

Abstract

Through-Silicon-Via (TSV) technology is of crucial importance in the process of defect-free copper filling in vias. In this study, the small molecule 2-mercapto-1-methylimidazole (SN2) is proposed as a new leveler. It enables bottom-up super-filling of blind vias without the need for inhibitors. Atomic [...] Read more.

Through-Silicon-Via (TSV) technology is of crucial importance in the process of defect-free copper filling in vias. In this study, the small molecule 2-mercapto-1-methylimidazole (SN2) is proposed as a new leveler. It enables bottom-up super-filling of blind vias without the need for inhibitors. Atomic force microscopy (AFM), X-ray diffraction (XRD), and XPS were employed to characterize the surface morphology, crystal structure, and adsorption properties of copper crystals in these systems. Meanwhile, by means of electrochemical measurements, the inhibitory effect of the leveler SN2 on copper ion deposition and the synergistic effect between SN2 molecules and other additives were investigated. The LSV test indicated that additive SN2 inhibited copper electrodeposition after being added to the plating solution, and this inhibitory effect enhanced with increasing SN2 concentration. In the actual plating wafer test (1 ASD plating for 1 min, 5 ASD plating for 5 min, and 10 ASD plating for 1 h), the best plating effect was achieved at 3 ppm, which verified the conjecture of the galvanostatic measurements. Moreover, XPS and computer simulations revealed that SN2 could be adsorbed onto the copper surfaces. This work will inspire the discovery of new effective levelers in the future. Full article

(This article belongs to the Special Issue Advanced Electronic Packaging Technology: From Hard to Soft (Second Edition))

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19 pages, 1288 KiB

Open AccessArticle

Machine Learning-Based Harvest Date Detection and Prediction Using SAR Data for the Vojvodina Region (Serbia)

by Gordan Mimić, Amit Kumar Mishra, Miljana Marković, Branislav Živaljević, Dejan Pavlović and Oskar Marko

Sensors 2025, 25(7), 2239; https://doi.org/10.3390/s25072239 (registering DOI) - 2 Apr 2025

Abstract

Information on the harvest date of crops can help with logistics management in the agricultural industry, planning machinery operations and also with yield prediction modelling. In this study, the determination and prediction of harvest dates for different crops were performed by applying machine [...] Read more.

Information on the harvest date of crops can help with logistics management in the agricultural industry, planning machinery operations and also with yield prediction modelling. In this study, the determination and prediction of harvest dates for different crops were performed by applying machine learning techniques on C-band synthetic aperture radar (SAR) data. Ground truth data were provided for the Vojvodina region (Serbia), an area with intensive agricultural production, considering winter wheat, maize and soybean fields with exact harvest dates, for the period 2017–2020, including 592 samples in total. Data from the Sentinel-1 satellite were used in the study. Time series of backscattering coefficients for vertical–horizontal (VH) and vertical–vertical (VV) polarisations, both from ascending and descending orbits, were collected from Google Earth Engine. Clustering of harvested and unharvested fields was performed with Principal Component Analysis, multidimensional scaling and t-distributed Stochastic Neighbour Embedding, for initial cluster visualization. It is shown that the separability of unharvested and harvested data in two-dimensional space does not depend on the selected method but more on the crop itself. Support Vector Machine and Multi-layer Perceptron were used as classification algorithms for harvest detection, with the former achieving higher accuracies of 79.65% for wheat, 83.41% for maize and 95.97% for soybean. Finally, regression models were developed for the prediction of the harvest date using Random Forest and the long short-term memory network, with the latter achieving better results: an R² score of 0.72, mean absolute error of 6.80 days and root mean squared error of 9.25 days, for all crops considered together. Full article

(This article belongs to the Special Issue Application of Satellite Remote Sensing in Geospatial Monitoring)

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11 pages, 1003 KiB

Open AccessArticle

Impact of Removing Race Coefficient from Glomerular Filtration Rate Estimation Equations on Antidiabetics Among Black Patients

by Dhakrit Rungkitwattanakul, Ebony Evans, Ewanna Brown, Kent Patterson Jr., Weerachai Chaijamorn, Taniya Charoensareerat, Sanaa Belrhiti, Uzoamaka Nwaogwugwu and Constance Mere

Pharmacy 2025, 13(2), 52; https://doi.org/10.3390/pharmacy13020052 (registering DOI) - 2 Apr 2025

Abstract

Background: In 2021, the National Kidney Foundation–American Society of Nephrology (NKF-ASN) recommended the use of the 2021 refit equation without race; however, the effect of the removal is unclear. Our research aimed to examine the implications of antidiabetic dosing and eligibility on the [...] Read more.

Background: In 2021, the National Kidney Foundation–American Society of Nephrology (NKF-ASN) recommended the use of the 2021 refit equation without race; however, the effect of the removal is unclear. Our research aimed to examine the implications of antidiabetic dosing and eligibility on the new 2021 equation among Black patients. Methods: This is a retrospective analysis of patients receiving care at the diabetes treatment center (DTC) of an academic medical center. Estimated glomerular filtration rates (eGFRs) based on serum creatinine were calculated using the 2009 and 2021 CKD-EPI equations. A Monte Carlo simulation was performed to create 10,000 virtual patients. Dosing simulations based on each estimate of kidney function were performed for antidiabetics based on product labeling. The proportion and percentage of patients who were eligible based on the estimates were calculated. Results: The percentages of patients ineligible for metformin based on the estimates from the 2009 and 2021 CKD-EPI equations at the DTC were comparable (8.02% and 8.36%, respectively). In our 10,000 simulated virtual patients, the percentage of ineligibility increased only by 1%. For the GFR cut points of 20 mL/min and 25 mL/min, the rates of ineligibility were similar in our cohort and simulated patients. Conclusions: The exclusion of race from the 2021 CKD-EPI equation may slightly reduce medication eligibility among Black patients. Full article

(This article belongs to the Special Issue Medication Use and Patient Safety in Clinical Pharmacy)

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11 pages, 216 KiB

Open AccessArticle

Healthcare Professionals’ Perceptions About Medical Cannabis in Greece: A Qualitative Study

by Christos Ntais, Yioula Melanthiou and Michael A. Talias

J. Mark. Access Health Policy 2025, 13(2), 13; https://doi.org/10.3390/jmahp13020013 (registering DOI) - 2 Apr 2025

Abstract

Background: Medical cannabis continues to generate interest as a potential therapeutic option, yet its acceptance in clinical practice faces challenges, including regulatory barriers, social stigma, and gaps in scientific evidence. Methods: This study explores the perspectives of Greek medical doctors and pharmacists on [...] Read more.

Background: Medical cannabis continues to generate interest as a potential therapeutic option, yet its acceptance in clinical practice faces challenges, including regulatory barriers, social stigma, and gaps in scientific evidence. Methods: This study explores the perspectives of Greek medical doctors and pharmacists on medical cannabis—key stakeholders in its clinical application—through semi-structured interviews with 12 participants from each profession. Results: Medical doctors and pharmacists expressed a range of views on medical cannabis, with many acknowledging its potential while emphasizing the need for rigorous, disease-specific research. Medical doctors highlighted the lack of consistent clinical trials, concerns about drug interactions, and the fine line between medical use and misuse. Pharmacists echoed these concerns, citing regulatory inconsistencies and the need for standardized dosing. Both groups agreed that social stigma and misinformation hinder cannabis adoption, advocating for targeted education and transparent research communication. Participants indicated that regulatory barriers also pose challenges, with calls for harmonized policies and phased market entry approaches. Effective communication strategies, including digital outreach and clear messaging, were suggested to differentiate medical cannabis from recreational use and improve trust among healthcare providers and patients. Participants also highlighted the urgent need for collaboration between policymakers, researchers, and healthcare professionals to establish medical cannabis as a credible therapeutic option. Conclusion: The insights gained provide actionable recommendations to bridge existing gaps and emphasize the need for a responsible, evidence-based approach to the acceptance of medical cannabis as a therapeutic option. Full article

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