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26 pages, 1125 KB  
Article
Can Technological, Organisational and Environmental Factors Reduce Costs Through Green Innovation in the Construction Industry? Comparison of State-Owned and Private Enterprises
by Ting Peng, Seuk Wai Phoong and Sedigheh Moghavvemi
Sustainability 2025, 17(20), 9139; https://doi.org/10.3390/su17209139 (registering DOI) - 15 Oct 2025
Abstract
Green innovation (GI) plays a pivotal role in advancing sustainable transformation. To implement the concept of green development, China is vigorously advancing green innovation adoption (GIA). Although prior research has largely focused on the manufacturing sector, little is known about how ownership structures [...] Read more.
Green innovation (GI) plays a pivotal role in advancing sustainable transformation. To implement the concept of green development, China is vigorously advancing green innovation adoption (GIA). Although prior research has largely focused on the manufacturing sector, little is known about how ownership structures shape GIA in the construction industry, nor about its impact on cost. To address this gap, this study, grounded in the Technology–Organisation–Environment (TOE) framework, investigates the extent to which technological, organisational, and environmental factors influence the GIA in the construction sector and how GIA contributes to cost reduction, as well as how these effects differ between state-owned and private firms. Data were collected from 277 construction enterprises, and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Our findings show that GIA significantly reduces costs in both state-owned enterprises (SOEs) and private firms, while market pressure exerts no obvious influence on GIA. Notably, organisational support is found to negatively affect green process innovation in SOEs, suggesting that such initiatives may be more symbolic than substantive. This study could serve as a reference for businesses and governments, and contribute to China’s new development philosophy of “innovative, coordinated, green, open, and shared.” Full article
(This article belongs to the Special Issue Sustainable Development of Construction Engineering—2nd Edition)
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23 pages, 5681 KB  
Article
A Comprehensive Analysis of Double-Pass Counter Flow V-Groove Solar Air Collector Performance for Drying Applications
by Azharul Karim, Zakaria Amin and Sabrina Fawzia
Energies 2025, 18(20), 5432; https://doi.org/10.3390/en18205432 (registering DOI) - 15 Oct 2025
Abstract
The economic viability of solar drying mainly depends on the appropriate design of air collectors, which are the main parts of a solar dryer. Although the V-groove collector has been reported to have one of the highest efficiencies, no comprehensive parameter analysis on [...] Read more.
The economic viability of solar drying mainly depends on the appropriate design of air collectors, which are the main parts of a solar dryer. Although the V-groove collector has been reported to have one of the highest efficiencies, no comprehensive parameter analysis on this collector has been reported in the literature. This detailed study investigates the influence of different operating and design variables on the outlet temperature and the efficiency of the air collector. The parameter analysis also contributed to the development of the most effective design guidelines. The parameters examined include solar radiation, airflow rate, incoming air temperature, collector length, height of the vee, the spacing between the top of the vee and the transparent cover, number of such covers, and the thickness of the back insulation. The airflow rate is identified to be the essential operating parameter that affects the efficiency, and a better heat transfer rate is noticed in the intermediate flow state. It is also found that to achieve the best performance, it is necessary to maintain a mass airflow rate between 0.015 and 0.055 kg/m2s, to have incoming air at a near-atmospheric temperature, and to have two transparent covers on top. Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
19 pages, 4267 KB  
Article
Hydration and Water Vapor Transport in Films Based on Cassava Starch Reinforced with Topinambur Fiber (Helianthus tuberosus)
by Luisa F. Sierra Montes, María C. Lorenzo, Maria A. García, Andrés G. Salvay and Laura Ribba
Fibers 2025, 13(10), 141; https://doi.org/10.3390/fib13100141 (registering DOI) - 15 Oct 2025
Abstract
Biodegradable composites obtained by reinforcing thermoplastic starch (TPS) with lignocellulosic fibers show great potential, but their strong sensitivity to water still limits practical applications. Among possible reinforcements, Helianthus tuberosus (topinambur) represents an underutilized agricultural residue that has been scarcely explored in this context. [...] Read more.
Biodegradable composites obtained by reinforcing thermoplastic starch (TPS) with lignocellulosic fibers show great potential, but their strong sensitivity to water still limits practical applications. Among possible reinforcements, Helianthus tuberosus (topinambur) represents an underutilized agricultural residue that has been scarcely explored in this context. In this work, we demonstrate for the first time that topinambur fiber can improve the water vapor barrier properties of cassava starch films, while also providing a detailed analysis of sorption isotherms and the humidity-dependent relationship between surface roughness and contact angle, aspects rarely addressed in previous studies. SEM revealed uniform fiber dispersion and integration. Water sorption kinetics showed that fiber addition reduces both hydration and sorption time constant, indicating lower water affinity and greater water mobility. Water sorption isotherms confirmed that fiber incorporation significantly alters overall hydration and water–matrix interactions, revealing reduced effective water solubility in films. Water vapor permeability also decreased with fiber addition, mainly due to decreased water solubility, rather than changes in water diffusivity. While fiber addition enhanced surface-water repellency across all humidity levels, roughness exhibited a humidity-dependent response FTIR analysis confirmed fiber–matrix compatibility and suggested new hydrogen bonding. Overall, these findings identify topinambur fiber as a novel reinforcement for designing biodegradable films with improved humidity resistance for agroecological applications. Full article
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17 pages, 3158 KB  
Article
Enhancing Reverse Design Ability of Functional Materials Based on Data Quality Management: Taking Biomedical Zinc Alloy as an Example
by Xujie Gong, Xue Jiang, Shiyu Huang, Yize Wang, Lishen Ding, Yanjing Su and Yu Yan
Materials 2025, 18(20), 4729; https://doi.org/10.3390/ma18204729 (registering DOI) - 15 Oct 2025
Abstract
Biodegradable zinc alloys have shown great potential in the biomedical field, but are limited by their poor mechanical properties. Alloying is essential for improving mechanical properties, yet designing multicomponent zinc alloys remains challenging due to complex elemental interactions. Notably, while data-driven active learning [...] Read more.
Biodegradable zinc alloys have shown great potential in the biomedical field, but are limited by their poor mechanical properties. Alloying is essential for improving mechanical properties, yet designing multicomponent zinc alloys remains challenging due to complex elemental interactions. Notably, while data-driven active learning approaches offer new strategies for zinc alloy design, data quality issues such as redundancy, outliers, and inconsistencies in multi-source heterogeneous data hinder modeling accuracy and interpretability. In this work, we proposed a data quality management strategy based on recursive screening, targeting three key data problems, namely, redundant data (RD), outlier data (OD), and inconsistent target data (ID). Case studies on hydrogen embrittlement, phase-change refrigeration materials, and matbench_expt_gap datasets showed that, in the aforementioned data-driven research, RD optimized data distribution but risked precision loss in high-performance regions; OD enhanced minority alloy features but risked overfitting; and ID preserved high-performance data, boosting extrapolation but risking underfitting. Six multicomponent zinc alloys were designed and fabricated using these strategies. Experiments showed ID-optimized datasets achieving 482 MPa—near state-of-the-art performance. The highest tensile strength of 482 MPa was obtained in the alloy Zn-1.2Al-0.8Mg-0.45Li-0.3Mn (at%), designed via the ID-optimized dataset. The study revealed that in inverse design, predictive accuracy in high-performance regions outweighs data volume or density, underscoring the value of data quality management for multi-source materials development. Full article
(This article belongs to the Section Metals and Alloys)
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19 pages, 784 KB  
Article
First Assessment of Oral Iron Chelator HBED Increases Iron Excretion in Black Rhinoceros (Diceros bicornis minor)
by Kathleen E. Sullivan, Shana R. Lavin, Lori K. Warren, Natalie D. Mylniczenko, Shannon E. Livingston, Mitchell D. Knutson and Eduardo V. Valdes
Animals 2025, 15(20), 2987; https://doi.org/10.3390/ani15202987 (registering DOI) - 15 Oct 2025
Abstract
Black rhinoceros (Diceros bicornis) face threats to survival due to poaching in the wild and an incomplete understanding of preventive health monitoring under human care. Black rhinos under human care develop iron overload disorder (IOD) which is associated with predisposition to [...] Read more.
Black rhinoceros (Diceros bicornis) face threats to survival due to poaching in the wild and an incomplete understanding of preventive health monitoring under human care. Black rhinos under human care develop iron overload disorder (IOD) which is associated with predisposition to other disease, compromised immune function, hemolytic crisis, and death. Management of IOD is challenging but has been mitigated in some cases with dietary intervention and phlebotomy and documented through serum biomarker evaluation. Chelation therapy to reduce iron is rare in rhinos partially because of limited product availability and route of administration. An iron-specific chelator HBED (N,N’-Di(2-hydroxybenzyl)ethylenediamine-N,N’-diacetic acid) was investigated for oral use in southern black rhinos (n = 3) after successful testing was performed with equids as a model. Using a cross-over design, we tested the efficacy of short-term HBED administration. HBED was dosed at 40 mg/kg body weight for 10 days and resulted in increased urinary excretion of iron but unaltered fecal iron excretion in rhinos compared to control trials. Two rhinos maintained blood chemistry and cell distribution considered normal for the species. The third rhino experienced a hemolytic event after stopping HBED administration in the same time frame and at the same dose as the two conspecifics but fully recovered. Careful monitoring and tapering the drug at the completion of treatment is warranted, especially if the rhino’s iron load is considered high. HBED’s potential to induce iron excretion safely, as well as prevent excessive dietary iron uptake, may significantly benefit the black rhino population under human care. Full article
(This article belongs to the Section Mammals)
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15 pages, 1260 KB  
Article
Identification and Analysis of Resistance to Northern Corn Leaf Blight in Maize Germplasm Resources
by Bing Meng, Junwei Yang, Lixiu Tong, Qingli Liu, Dongfeng Zhang, Wen-Xue Li, Jianjun Wang, Yunbi Xu, Zifeng Guo and Canxing Duan
Plants 2025, 14(20), 3171; https://doi.org/10.3390/plants14203171 (registering DOI) - 15 Oct 2025
Abstract
Northern corn leaf blight (NCLB), caused by the fungus Exserohilum turcicum, is one of the most significant foliar diseases in maize worldwide, with its severity being highly influenced by environmental conditions. An effective strategy used to control NCLB involves screening diverse maize [...] Read more.
Northern corn leaf blight (NCLB), caused by the fungus Exserohilum turcicum, is one of the most significant foliar diseases in maize worldwide, with its severity being highly influenced by environmental conditions. An effective strategy used to control NCLB involves screening diverse maize germplasm for resistant sources through multi-environment inoculation assays, ultimately aiming to develop resistant varieties. This study systematically evaluated 711 maize germplasm accessions with rich genetic diversity. The evaluation was conducted under four location–year environment combinations (Shangluo, Shaanxi Province, China in 2014–2015 and Xinzhou, Shanxi Province, China in 2021–2022) using artificial inoculation with physiological race 123N (or races 1, 2, 3, N). The results showed that the estimated variances of genotype, environment, and genotype-by-environment interaction were all highly significant (p < 0.01). Significant correlations (p < 0.01) were observed among replicates within each environment, with correlation coefficients (r) ranging from 0.67 to 0.88. At the Xinzhou trial in 2021, four replicates were inoculated with four physiological races (1, 2, 3, and N), revealing highly significant correlations (r = 0.77–0.80, p < 0.01) among them. The disease severity of the tropical germplasm was significantly lower (p < 0.001) than that of the temperate germplasm. Among the temperate subgroups, the PA and PB (groups A and B germplasms derived from modern US hybrids) subgroups exhibited lower disease severity, with the PB subgroup showing the lowest, while the Iodent and Reid subgroups exhibited higher susceptibility. The disease severity responses to the four physiological races were highly positively correlated (r = 0.77–0.80, p < 0.001), and their correlations with the composite inoculation (race 123N) ranged from 0.65 to 0.83. Based on the resistance evaluations across four location–year environment combinations, the 711 maize accessions were classified into five categories: 20 were highly resistant, 236 resistant, 205 moderately resistant, 237 susceptible, and 13 highly susceptible. The findings indicate that the tropical germplasm and the temperate PB subgroup are major sources of NCLB resistance. Full article
(This article belongs to the Special Issue Identification of Resistance of Maize Germplasm Resources to Disease)
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22 pages, 4701 KB  
Review
The Status of Intelligent Control Technology for the Working Height of a Crop Harvesting Header
by Chenxu Zhao, Feng Wu, Fengwei Gu, Xinsheng Zhou, Yanqin Zhang, Peng Chen, Jiayong Pei and Hongguang Yang
Sensors 2025, 25(20), 6367; https://doi.org/10.3390/s25206367 (registering DOI) - 15 Oct 2025
Abstract
As is well known, intelligence and efficiency are important development directions for modern agriculture. The harvesting header, as key components of crop harvesters, have significant implications for achieving intelligent control of their working height, which has a notable impact on reducing harvest loss. [...] Read more.
As is well known, intelligence and efficiency are important development directions for modern agriculture. The harvesting header, as key components of crop harvesters, have significant implications for achieving intelligent control of their working height, which has a notable impact on reducing harvest loss. To understand the current state of intelligent control technology for the working height of a crop harvesting header, and to explore their application potential, this article provides a relatively systematic literature review. Firstly, we analyzed the structure and principle of the harvesting header of typical grain and oil crops such as rice and peanuts. Secondly, we briefly described the current methods for controlling the working height of the harvesting header. They mainly use two methods: mechanical profiling and electro-hydraulic profiling. Thirdly, we focused on researching and analyzing the measurement methods and control algorithms for the working height of the harvesting header. Finally, we pointed out the problems in the current height control of the harvesting header. These problems mainly include insufficient measurement accuracy of working height in complex terrain, slow response and large delay of working height hydraulic control system, incompatibility between working height control models and strategies, and relatively single working height measurement methods. Full article
(This article belongs to the Section Smart Agriculture)
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16 pages, 1743 KB  
Article
Automated and Selective Product Removal for Lab-Scale Draft Tube Baffle Crystallizer Under Vacuum Operation
by Laura Marsollek, Merlin Hubmann, Kim Buchhorn and Norbert Kockmann
Crystals 2025, 15(10), 893; https://doi.org/10.3390/cryst15100893 (registering DOI) - 15 Oct 2025
Abstract
Continuous product removal in lab-scale vacuum applications poses significant challenges, particularly due to the risk of clogging in the product tube caused by the small tubing diameter relative to the particle size. This contribution addresses this problem by presenting an automatic gate system [...] Read more.
Continuous product removal in lab-scale vacuum applications poses significant challenges, particularly due to the risk of clogging in the product tube caused by the small tubing diameter relative to the particle size. This contribution addresses this problem by presenting an automatic gate system specifically designed for selective product removal within a Draft Tube Baffle Crystallizer (DTBC). In order to enable selective product removal, the classification behavior of the crystals in the DTBC was evaluated in experimental studies by determining the crystal size distributions in the product removal and in the fine grain dissolution. The influence of different stirring speeds and solid contents were considered for different product removal rates. The results indicated that sufficient classification occurs at stirring speeds of 600 rpm and a crystal content of ≥3 wt%. Under these conditions, more than 75% of the crystals in the product were larger than 210 μm from a sieve size range of 45 to 500 µm. During experiments, the automatic gate system allowed for blockage-free, continuous product removal for six hours per experiment and more than thirty hours in total, proving the reliability of the system. Although designed for down-scaling of the DTBC, this system can also be applied to other continuous-flow lab-scale applications. Full article
(This article belongs to the Section Crystal Engineering)
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23 pages, 3461 KB  
Article
Plasmonic Nanosensors for EGFR Detection: Optimizing Aptamer-Based Competitive Displacement Assays
by Alexandra Falamas, Andra-Sorina Tatar, Sanda Boca and Cosmin Farcău
Biosensors 2025, 15(10), 699; https://doi.org/10.3390/bios15100699 (registering DOI) - 15 Oct 2025
Abstract
This study presents a comparative investigation of plasmonic sensing platforms based on colloidal gold nanoparticle (AuNP) suspensions and gold film over nanosphere (AuFoN) solid substrates for the detection of epidermal growth factor receptor (EGFR), an essential biomarker and therapeutic target in oncology. The [...] Read more.
This study presents a comparative investigation of plasmonic sensing platforms based on colloidal gold nanoparticle (AuNP) suspensions and gold film over nanosphere (AuFoN) solid substrates for the detection of epidermal growth factor receptor (EGFR), an essential biomarker and therapeutic target in oncology. The strategy relies on fluorescence emission modulation of an Atto647N-labeled DNA oligomer competitively bound to an EGFR-specific aptamer. Our results demonstrate that the colloidal AuNPs can function as competitive binding sensors, leading to fluorescence quenching upon fluorophore attachment to the surface of the NPs and partial fluorescence recovery due to EGFR-induced displacement of the fluorophore–aptamer complex. This specificity was confirmed by reversed binding experiments. However, the system proved highly sensitive to the experimental design: excessive washing (centrifugation) led to unspecific aggregation and signal loss, while reduced washing steps improved signal retention and revealed EGFR-induced fluorophore displacement into the supernatant. On the contrary, film-based substrates exhibited strong initial fluorescence, but failed to retain the fluorophore–aptamer complex after washing, resulting in fluorescence decay independent of EGFR incubation. This indicates that AuFoN lacked the binding stability necessary for specific displacement-based sensing. These findings highlight that while colloidal AuNPs can support competitive binding detection, their reproducibility is limited by colloidal stability and protocol sensitivity, whereas AuFoN substrates require improved surface functionalization strategies. The study emphasizes the critical role of surface chemistry, aptamer–fluorophore affinity, and washing protocols in determining the success or failure of plasmon-enhanced aptamer-based biosensing systems and suggests opportunities for improving specificity and robustness in future designs. Full article
(This article belongs to the Special Issue Aptamer-Based Sensing: Designs and Applications)
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17 pages, 1554 KB  
Article
Sodium Butyrate Supplementation in Whole Milk Modulates the Gastrointestinal Microbiota Without Altering the Resistome and Virulome in Preweaned Calves
by Liwen Xing, Song Niu, Donglin Wu, Zhanghe Zhang and Ming Xu
Microorganisms 2025, 13(10), 2375; https://doi.org/10.3390/microorganisms13102375 (registering DOI) - 15 Oct 2025
Abstract
This study investigated the effects of supplementing whole milk (WM) with sodium butyrate (SB) on the gastrointestinal microbiota of preweaned calves. Twelve newborn Holstein calves (4 days old, 39.21 ± 1.45 kg) were randomly assigned into one of two dietary treatments: (1) WM [...] Read more.
This study investigated the effects of supplementing whole milk (WM) with sodium butyrate (SB) on the gastrointestinal microbiota of preweaned calves. Twelve newborn Holstein calves (4 days old, 39.21 ± 1.45 kg) were randomly assigned into one of two dietary treatments: (1) WM without SB (CON) and (2) WM supplemented with SB (8.8 g/d; SB). At 74 days of age, all calves were slaughtered to collect ruminal and cecal digesta. Metagenomic analysis was used to characterize the microbial composition, virulence factor genes (VFGs), and antibiotic resistance genes (ARGs). SB supplementation altered the ruminal microbial composition and increased the abundance of beneficial bacteria, including Actinobacteria, Bifidobacterium, and Olsenella (p < 0.05). Although SB did not significantly affect the overall microbial composition or diversity in the cecum (p > 0.05), it promoted the growth of beneficial genera such as Flavonifractor and Subdoligranulum (p < 0.05). Furthermore, SB supplementation did not significantly alter the composition of VFGs or ARGs in either the rumen or the cecum (p > 0.05). However, significant differences in VFGs and ARGs were observed between the rumen and the cecum, with a greater diversity of both VFGs and ARGs detected in the cecum compared to that in the rumen (p < 0.05). In summary, supplementing whole milk with sodium butyrate modulates gastrointestinal health in preweaned calves by favorably shaping the microbial community without significantly altering the antibiotic resistome or virulome. Full article
(This article belongs to the Section Gut Microbiota)
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24 pages, 3792 KB  
Article
From Space–Behavior Mismatch to Regional Integration: A Cross-Scale Social Network Analysis of Sustainable Rural Construction in Suburban China
by Yi Qian and Xianfeng Li
Sustainability 2025, 17(20), 9137; https://doi.org/10.3390/su17209137 (registering DOI) - 15 Oct 2025
Abstract
Rapid urbanization in China has intensified spatial and social disparities between urban and rural areas, posing major challenges to sustainable rural development. Traditional top-down rural construction and evaluation models often neglect villagers’ everyday practices, resulting in mismatches between spatial planning and actual use. [...] Read more.
Rapid urbanization in China has intensified spatial and social disparities between urban and rural areas, posing major challenges to sustainable rural development. Traditional top-down rural construction and evaluation models often neglect villagers’ everyday practices, resulting in mismatches between spatial planning and actual use. This study develops a cross-scale, bottom-up framework for assessing rural construction through social network analysis (SNA), taking Xiongfan Village in Dawu County, Hubei Province, as a case study. At the village scale, the comparison between the “Public Space Structure Network” and the “Villagers’ Space Usage Behavior Network” reveals a significant mismatch between spatial compactness and behavioral dispersion, with high-frequency activities concentrated along the north–south axis while peripheral and east–west spaces remain underutilized. At the township scale, GPS-based analysis shows that the revitalization of Xiongfan transformed it from a peripheral node into a central hub, restructuring the network into a new pattern of “characteristic towns—traditional villages—ecological scenic areas.” These findings highlight the dual role of rural construction in both meeting residents’ daily needs and fostering regional integration. The proposed cross-scale SNA framework not only advances methodological tools for evaluating rural construction but also provides practical guidance for inclusive, resilient, and sustainable urban–rural development in line with the UN Sustainable Development Goals (SDGs). Full article
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13 pages, 3465 KB  
Article
Raman and Infrared Signatures of Layered Boron Nitride Polytypes: A First-Principles Study
by Priyanka Mishra and Nevill Gonzalez Szwacki
Nanomaterials 2025, 15(20), 1567; https://doi.org/10.3390/nano15201567 (registering DOI) - 15 Oct 2025
Abstract
We present a study based on first-principles calculations of the vibrational and spectroscopic properties of four types of layered boron nitride (BN) polymorphs: e-BN (AA), h-BN (AA), r-BN (ABC), and b-BN (AB). By using density functional [...] Read more.
We present a study based on first-principles calculations of the vibrational and spectroscopic properties of four types of layered boron nitride (BN) polymorphs: e-BN (AA), h-BN (AA), r-BN (ABC), and b-BN (AB). By using density functional perturbation theory with van der Waals corrections, we calculate phonon frequencies and Raman/infrared (IR) activities at the Γ point and extract specific spectral fingerprints for each stack. In e-BN, we observe a sharp, isolated high-frequency E mode at 1420.9cm1 that is active in both Raman and IR. For h-BN, the characteristic Raman E2g line occurs at 1415.5cm1. The out-of-plane IR-active A2u branch shows a mid-frequency TO/LO pair at 673.5/806.6cm1, which closely matches experimental results. Rhombohedral r-BN has a strong, coincident Raman/IR high-frequency feature (E) at 1418.5cm1, along with a large IR LO partner at 1647.3cm1, consistent with observed Raman and IR signatures. Bernal b-BN displays the most complicated pattern. It combines a robust mid-frequency A2 pair (TO/LO at 697.9/803.5cm1) with multiple high-frequency E modes (TO near 1416.9 and 1428.1cm1, each with LO counterparts). These stack-dependent Raman and IR fingerprints match existing experimental data for h-BN and r-BN and provide clear predictions for e-BN and b-BN. The results offer a consistent framework for identifying and interpreting vibrational spectra in layered sp2 boron nitride and related materials. Full article
(This article belongs to the Special Issue Structure–Property Correlation Studies of Low-Dimensional Materials)
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21 pages, 7603 KB  
Article
Non-Invasive Inversion and Characteristic Analysis of Soil Moisture in 0–300 cm Agricultural Soil Layers
by Shujie Jia, Yaoyu Li, Boxin Cao, Yuwei Cheng, Abdul Sattar Mashori, Zheyu Bai, Mingyi Cui, Zhimin Zhang, Linqiang Deng and Wuping Zhang
Agriculture 2025, 15(20), 2143; https://doi.org/10.3390/agriculture15202143 (registering DOI) - 15 Oct 2025
Abstract
Accurate profiling of deep (20–300 cm) soil moisture is crucial for precision irrigation but remains technically challenging and costly at operational scales. We systematically benchmark eight regression algorithms—including linear regression, Lasso, Ridge, elastic net, support vector regression, multi-layer perceptron (MLP), random forest (RF), [...] Read more.
Accurate profiling of deep (20–300 cm) soil moisture is crucial for precision irrigation but remains technically challenging and costly at operational scales. We systematically benchmark eight regression algorithms—including linear regression, Lasso, Ridge, elastic net, support vector regression, multi-layer perceptron (MLP), random forest (RF), and gradient boosting trees (GBDT)—that use easily accessible inputs of 0–20 cm surface soil moisture (SSM) and ten meteorological variables to non-invasively infer soil moisture at fourteen 20 cm layers. Data from a typical agricultural site in Wenxi, Shanxi (2020–2022), were divided into training and testing datasets based on temporal order (2020–2021 for training, 2022 for testing) and standardized prior to modeling. Across depths, non-linear ensemble models significantly outperform linear baselines. Ridge Regression achieves the highest accuracy at 0–20 cm, SVR performs best at 20–40 cm, and MLP yields consistently optimal performance across deep layers from 60 cm to 300 cm (R2 = 0.895–0.978, KGE = 0.826–0.985). Although ensemble models like RF and GBDT exhibit strong fitting ability, their generalization performance under temporal validation is relatively limited. Model interpretability combining SHAP, PDP, and ALE shows that surface soil moisture is the dominant predictor across all depths, with a clear attenuation trend and a critical transition zone between 160 and 200 cm. Precipitation and humidity primarily drive shallow to mid-layers (20–140 cm), whereas temperature variables gain relative importance in deeper profiles (200–300 cm). ALE analysis eliminates feature correlation biases while maintaining high predictive accuracy, confirming surface-to-deep information transmission mechanisms. We propose a depth-adaptive modeling strategy by assigning the best-performing model at each soil layer, enabling practical non-invasive deep soil moisture prediction for precision irrigation and water resource management. Full article
(This article belongs to the Section Agricultural Soils)
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28 pages, 678 KB  
Systematic Review
OCTA Biomarkers Underlying Structure–Function Correlations in Idiopathic Epiretinal Membrane: A Systematic Review
by Anca Mădălina Sere, George Adrian Muntean, Andreea Petra Cristea and Simona Delia Nicoară
Diagnostics 2025, 15(20), 2596; https://doi.org/10.3390/diagnostics15202596 (registering DOI) - 15 Oct 2025
Abstract
Background: Idiopathic epiretinal membrane (iERM) is a common retinal pathology in elderly patients, thought to originate primarily from an anomalous process of posterior vitreous detachment. The standard treatment is pars plana vitrectomy (PPV) with membrane peeling. No consensus exists regarding the optimal timing [...] Read more.
Background: Idiopathic epiretinal membrane (iERM) is a common retinal pathology in elderly patients, thought to originate primarily from an anomalous process of posterior vitreous detachment. The standard treatment is pars plana vitrectomy (PPV) with membrane peeling. No consensus exists regarding the optimal timing of surgery, nor is it clear which patients are most likely to benefit. Given that iERM profoundly affects retinal vascular morphology and function, optical coherence tomography angiography (OCTA) has emerged as a valuable tool for identifying potential biomarkers. This systematic review aimed to synthesize the available evidence on OCTA-derived biomarkers and their correlations with visual function before and/or after surgical intervention in iERM, with a particular focus on their prognostic value for postoperative outcomes. Methods: A systematic search of PubMed/MEDLINE and Scopus was conducted on the 20th of May 2025 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligible studies included patients with iERM undergoing vitreoretinal surgery, used OCTA for pre- and/or postoperative assessment, investigated structure–function correlations, and were designed as clinical trials, observational studies, or case series with more than 10 patients. Exclusion criteria were studies with ≤10 cases, absence of separate iERM analysis, lack of surgical intervention, or non-English language. Data extraction covered study design, demographics, surgical approach, OCTA device, follow-up, OCTA biomarkers, and structure–function outcomes. Risk of bias in observational studies was assessed using the National Institute of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: The search yielded 1053 records, of which 71 underwent full-text review and 43 met eligibility criteria. All included studies were observational, encompassing 1958 eyes from 1953 patients. The most frequently investigated biomarkers were the foveal avascular zone (FAZ) area and related parameters, vessel density (VD), and foveal density 300 (FD-300). Additional studies evaluated average vessel length (VL), blood flow area, vessel length density (VLD), vessel tortuosity (VT), fractal dimension (FD), and perfusion capacity (PC). Conclusions: By consolidating current evidence, this systematic review provides a comprehensive overview of structure–function correlations in iERM and highlights the potential of OCTA-derived metrics as biomarkers of disease severity and surgical prognosis. These findings help clarify underlying mechanisms of visual decline and establish the context for further research. Nonetheless, interpretation is limited by the observational design of all included studies and by heterogeneity in OCTA methodology and nomenclature, underscoring the need for standardization to improve comparability and foster greater coherence across studies. No funding was provided for this review. Full article
(This article belongs to the Special Issue Optical Coherence Tomography in Diagnosis of Ophthalmology Disease)
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Article
Visual Feature Domain Audio Coding for Anomaly Sound Detection Application
by Subin Byun and Jeongil Seo
Algorithms 2025, 18(10), 646; https://doi.org/10.3390/a18100646 (registering DOI) - 15 Oct 2025
Abstract
Conventional audio and video codecs are designed for human perception, often discarding subtle spectral cues that are essential for machine-based analysis. To overcome this limitation, we propose a machine-oriented compression framework that reinterprets spectrograms as visual objects and applies Feature Coding for Machines [...] Read more.
Conventional audio and video codecs are designed for human perception, often discarding subtle spectral cues that are essential for machine-based analysis. To overcome this limitation, we propose a machine-oriented compression framework that reinterprets spectrograms as visual objects and applies Feature Coding for Machines (FCM) to anomalous sound detection (ASD). In our approach, audio signals are transformed log-mel spectrograms, from which intermediate feature maps are extracted, compressed, and reconstructed through the FCM pipeline. For comparison, we implement AAC-LC (Advanced Audio Coding Low Complexity) as a representative perceptual audio codec and VVC (Versatile Video Coding) as spectrogram-based video codec. Experiments were conducted on the DCASE (Detection and Classification of Acoustic Scenes and Events) 2023 Task 2 dataset, covering four machine types (fan, valve, toycar, slider), with anomaly detection performed using the official Autoencoder baseline model released in DCASE 2024. Detection scores were computed from reconstruction error and Mahalanobis distance. The results show that the proposed FCM-based ACoM (Audio Coding for Machines) achieves comparable or superior performance to AAC at less than half the bitrate, reliably preserving critical features even under ultra-low bitrate conditions (1.3–6.3 kbps). While VVC retains competitive performance only at high bitrates, it degrades sharply at low bitrates. These findings demonstrate that feature-based compression offers a promising direction for next-generation ACoM standardization, enabling efficient and robust ASD in bandwidth-constrained industrial environments. Full article
(This article belongs to the Special Issue Visual Attributes in Computer Vision Applications)
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