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27 pages, 3313 KB

Open AccessArticle

Reversing the Irreversible: miRNA-Targeting Mesyl Phosphoramidate Oligonucleotides Restore Sensitivity to Cisplatin and Doxorubicin of KB-8-5 Epidermoid Carcinoma Cells

by Svetlana Miroshnichenko, Rabia Demirel, Arseny Moralev, Olga Almieva, Andrey Markov, Ekaterina Burakova, Dmitry Stetsenko, Mikhail Maslov, Valentin Vlassov and Marina Zenkova

Biomedicines 2025, 13(12), 3118; https://doi.org/10.3390/biomedicines13123118 (registering DOI) - 18 Dec 2025

Abstract

Background: Chemotherapy remains one of the main approaches for treating malignant tumors, but repeated exposure to cytostatics leads to multidrug resistance (MDR), increasing tumor aggressiveness and reducing therapeutic efficacy. Identifying adjuvant agents that restore tumor sensitivity to drugs while minimizing toxicity is a [...] Read more.

Background: Chemotherapy remains one of the main approaches for treating malignant tumors, but repeated exposure to cytostatics leads to multidrug resistance (MDR), increasing tumor aggressiveness and reducing therapeutic efficacy. Identifying adjuvant agents that restore tumor sensitivity to drugs while minimizing toxicity is a cornerstone challenge today. This study aimed to investigate the potential of mesyl phosphoramidate antisense oligonucleotides (µ-ASOs) targeting miR-17, miR-21, and miR-155 as agents for enhancing the efficacy of cisplatin (Cis) and doxorubicin (Dox) in MDR-positive human epidermoid carcinoma KB-8-5 cells. Methods: Optimal regimens for the simultaneous application of µ-ASOs and Dox or Cis in KB-8-5 cells, including a concentration-dependent analysis and the type of compound interaction in combinations (synergy/additivity/antagonism), were studied using the MTT assay. Antiproliferative effects of the combinations were assessed using the real-time cell monitoring xCELLigence system. The potential molecular mechanism underlying KB-8-5 cell sensitization to cytostatics was investigated using RT-PCR and Western blot hybridization, supported by bioinformatic reconstruction of the gene network. Results: The most effective combinations including µ-ASOs targeting miR-21 and miR-17 together with Cis or Dox demonstrated additive to moderately synergistic effects on KB-8-5 cell viability (HSA synergy score = 4.8–8.7). The co-application of µ-ASOs allowed a 5- to 20-fold reduction in the dose of cytostatics, while maintaining a strong antiproliferative effect of 70–95%. Sensitization of KB-8-5 cells to Cis or Dox following µ-ASO treatment was mediated by a 1.5- to 3-fold decrease in the levels of the well-known MDR marker ABCB1 as well as the newly identified MDR-associated targets ZYX, TUBA4A, and SEH1L. Conclusions: miRNA-targeted mesyl phosphoramidate oligonucleotides are effective tools for overcoming resistance to the clinically approved chemotherapeutics cisplatin and doxorubicin. The relationship between miR-21, miR-17, and miR-155 and the novel MDR markers such as SEH1L, TUBA4A, and ZYX was revealed, thereby expanding the current understanding of the molecular mechanisms underlying tumor cell resistance to chemotherapy. Full article

(This article belongs to the Special Issue Drug Resistance and Novel Targets for Cancer Therapy—Third Edition)

19 pages, 6765 KB

Open AccessArticle

A Dual-Validation Framework for Temporal Robustness Assessment in Brain–Computer Interfaces for Motor Imagery

by Mohamed A. Hanafy, Saykhun Yusufjonov, Payman SharafianArdakani, Djaykhun Yusufjonov, Madan M. Rayguru and Dan O. Popa

Technologies 2025, 13(12), 595; https://doi.org/10.3390/technologies13120595 (registering DOI) - 18 Dec 2025

Abstract

Brain–computer interfaces using motor imagery (MI-BCIs) offer a promising noninvasive communication pathway between humans and engineered equipment such as robots. However, for MI-BCIs based on electroencephalography (EEG), the reliability of the interface across recording sessions is limited by temporal non-stationary effects. Overcoming this [...] Read more.

Brain–computer interfaces using motor imagery (MI-BCIs) offer a promising noninvasive communication pathway between humans and engineered equipment such as robots. However, for MI-BCIs based on electroencephalography (EEG), the reliability of the interface across recording sessions is limited by temporal non-stationary effects. Overcoming this barrier is critical to translating MI-BCIs from controlled laboratory environments to practical uses. In this paper, we present a comprehensive dual-validation framework to rigorously evaluate the temporal robustness of EEG signals of an MI-BCI. We collected data from six participants performing four motor imagery tasks (left/right hand and foot). Features were extracted using Common Spatial Patterns, and ten machine learning classifiers were assessed within a unified pipeline. Our method integrates within-session evaluation (stratified K-fold cross-validation) with cross-session testing (bidirectional train/test), complemented by stability metrics and performance heterogeneity assessment. Findings reveal minimal performance loss between conditions, with an average accuracy drop of just 2.5%. The AdaBoost classifier achieved the highest within-session performance (84.0% system accuracy, F1-score: 83.8%/80.9% for hand/foot), while the K-nearest neighbors (KNN) classifier demonstrated the best cross-session robustness (81.2% system accuracy, F1-score: 80.5%/80.2% for hand/foot, 0.663 robustness score). This study shows that robust performance across sessions is attainable for MI-BCI evaluation, supporting the pathway toward reliable, real-world clinical deployment. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

24 pages, 8113 KB

Open AccessArticle

Incorporation of Temperature Impact on Hot-Carrier Degradation into Compact Physics Model

by Stanislav Tyaginov, Erik Bury, Alexander Grill, Ethan Kao, An De Keersgieter, Alexander Makarov, Michiel Vandemaele, Alessio Spessot, Adrian Chasin and Ben Kaczer

Micromachines 2025, 16(12), 1424; https://doi.org/10.3390/mi16121424 (registering DOI) - 18 Dec 2025

Abstract

We extend our compact physics model (CPM) for hot-carrier degradation (HCD) to cover the impact of ambient temperature on HCD. Three components of this impact are taken into account. First, variations in temperature perturb carrier transport. Second, the thermal component of Si-H bond [...] Read more.

We extend our compact physics model (CPM) for hot-carrier degradation (HCD) to cover the impact of ambient temperature on HCD. Three components of this impact are taken into account. First, variations in temperature perturb carrier transport. Second, the thermal component of Si-H bond rupture becomes more prominent at elevated temperatures. Third, vibrational lifetime of the bond decreases with temperature. While the first and the third mechanisms impede HCD, the second one accelerates this detrimental phenomenon. The aforementioned mechanisms are consolidated in our extended CPM, which was verified against experimental data acquired from foundry quality n-channel transistors with a gate length of 28 nm. For model validation, we use experimental data recorded using four combinations of gate and drain voltages and across a broad temperature range of 150–300 K. We demonstrate that the extended CPM is capable of reproducing measured degradation

Δ I_{d, lin} (t)

(normalized change of the linear drain current with stress time) traces with good accuracy over a broad temperature range. Full article

(This article belongs to the Special Issue Reliability Issues in Advanced Transistor Nodes, Second Edition)

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29 pages, 3742 KB

Open AccessArticle

Integrating High-Dimensional Technical Indicators into Machine Learning Models for Predicting Cryptocurrency Price Movements and Trading Performance: Evidence from Bitcoin, Ethereum, and Ripple

by Rza Hasanli and Mahir Dursun

FinTech 2025, 4(4), 77; https://doi.org/10.3390/fintech4040077 (registering DOI) - 18 Dec 2025

Abstract

The rapid evolution of digital assets transforms cryptocurrencies into one of the most volatile and data-rich financial markets. Their nonlinear and unpredictable nature limits the effectiveness of traditional forecasting models, motivating the use of machine learning methods to identify hidden patterns and short-term [...] Read more.

The rapid evolution of digital assets transforms cryptocurrencies into one of the most volatile and data-rich financial markets. Their nonlinear and unpredictable nature limits the effectiveness of traditional forecasting models, motivating the use of machine learning methods to identify hidden patterns and short-term price movements. This study compares the performance of Logistic Regression (LR), Random Forest (RF), XGBoost, Support Vector Classifier (SVC), K-Nearest Neighbors (KNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) models in predicting the daily price directions of Bitcoin (BTC), Ethereum (ETH), and Ripple (XRP). Extensive data preprocessing and feature engineering are performed, integrating a broad set of technical indicators to enhance model generalization and capture temporal market dynamics. The results show that XGBoost achieves the highest classification accuracy of 55.9% for BTC and 53.8% for XRP, while LR provides the best result for Ethereum with an accuracy of 54.4%. In trading simulations, XGBoost achieves the strongest performance, generating a cumulative return of 141.4% with a Sharpe ratio of 1.78 for Bitcoin and 246.6% with a Sharpe ratio of 1.59 for Ripple, whereas LSTM delivers the best results for Ethereum with a 138.2% return and a Sharpe ratio of 1.05. Compared to recent studies, the proposed approach attains slightly higher accuracy, while demonstrating stronger robustness and profitability in practical backtesting. Overall, the findings confirm that through rigorous preprocessing machine learning-based strategies can effectively capture short-term price movements and outperform the conventional buy-and-hold benchmark, even under a simple rule-based trading framework. Full article

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21 pages, 3050 KB

Open AccessArticle

Research on Detection Methods for Major Soil Nutrients Based on Pyrolysis-Electronic Nose Time-Frequency Domain Feature Fusion and PSO-SVM-RF Model

by Li Lin, Dongyan Huang, Chunkai Zhao, Shuyan Liu and Shuo Zhang

Agronomy 2025, 15(12), 2916; https://doi.org/10.3390/agronomy15122916 (registering DOI) - 18 Dec 2025

Abstract

Against the backdrop of growing demand for rapid soil testing technologies in precision agriculture, this study proposes a detection method based on pyrolysis-electronic nose and machine olfaction signal analysis to achieve precise measurement of key soil nutrients. An electronic nose system comprising 10 [...] Read more.

Against the backdrop of growing demand for rapid soil testing technologies in precision agriculture, this study proposes a detection method based on pyrolysis-electronic nose and machine olfaction signal analysis to achieve precise measurement of key soil nutrients. An electronic nose system comprising 10 metal oxide semiconductor gas sensors was constructed to collect response signals from 112 black soil samples undergoing pyrolysis at 400 °C. By extracting time-domain and frequency-domain features from sensor responses, an initial dataset of 180 features was constructed. A novel feature fusion method combining Pearson correlation coefficients (PCC) with recursive feature elimination cross-validation (RFECV) was proposed to optimize the feature space, enhance representational power, and select key sensitive features. In predicting soil organic matter (SOM), total nitrogen (TN), available potassium (AK), and available phosphorus (AP content, we compared support vector machines (SVM), support vector machine-random forest models (SVM-RF), and particle swarm optimization-enhanced support vector machine-random forest models (PSO-SVM-RF). Results indicate that PSO-SVM-RF demonstrated optimal performance across all nutrient predictions, achieving a coefficient of determination (R²) of 0.94 for SOM and TN, with a performance-to-bias ratio (RPD) exceeding 3.8. For AK and AP, R² improved to 0.78 and 0.74, respectively. Compared to the SVM model, the root mean square error (RMSE) decreased by 25.4% and 21.6% for AK and AP, respectively, with RPD values approaching the practical threshold of 2.0. This study validated the feasibility and application potential of combining electronic nose technology with a time-frequency domain feature fusion strategy for precise quantitative analysis of soil nutrients, providing a new approach for soil fertility assessment in precision agriculture. Full article

(This article belongs to the Topic Soil Health and Nutrient Management for Crop Productivity)

20 pages, 816 KB

Open AccessReview

Exploiting Oxidative Stress as Achilles’ Heel: From Redox Homeostasis to Ferroptosis in Prostate Cancer

by Sanghyeon Yu, Jihyun Baek, Taesoo Choi and Man S. Kim

Antioxidants 2025, 14(12), 1517; https://doi.org/10.3390/antiox14121517 (registering DOI) - 18 Dec 2025

Abstract

Prostate cancer remains a leading cause of cancer-related mortality and castration-resistant prostate cancer (CRPC) is a critical therapeutic challenge. This review establishes a conceptual framework analyzing ferroptosis vulnerability through two principles: “robustness through redundancy” in defense systems and the “evolutionary arms race” between [...] Read more.

Prostate cancer remains a leading cause of cancer-related mortality and castration-resistant prostate cancer (CRPC) is a critical therapeutic challenge. This review establishes a conceptual framework analyzing ferroptosis vulnerability through two principles: “robustness through redundancy” in defense systems and the “evolutionary arms race” between androgen receptor (AR) signaling and oxidative resistance. We traced the evolutionary trajectory of hormone-sensitive diseases, where the AR coordinates ferroptosis defenses via SLC7A11, MBOAT2, and PEX10 regulation through progressive adaptations: AR-V7 splice variants that maintain defense independently of androgens, AR amplification conferring hypersensitivity, and AR-independent JMJD6-ATF4 bypass in SPOP-mutated tumors. This transforms ferroptosis from a static vulnerability to a stage-specific strategy. Novel approaches include menadione-based VPS34 targeting, which induces triaptosis through an oxidative endosomal catastrophe. We categorized the rational combinations mechanistically as vertical inhibition (multi-step targeting of single pathways), horizontal inhibition (synthetic lethality across parallel defenses), and vulnerability induction (creating exploitable dependencies). Ferroptosis-induced immunogenic cell death enables synergy with checkpoint inhibitors, potentially transforming immunologically “cold” prostate tumors. This review establishes ferroptosis targeting as a precision medicine paradigm exploiting the tension between the oxidative requirements of cancer cells and their evolved, yet architecturally vulnerable, defense systems, providing a framework for stage-specific, biomarker-guided interventions. Full article

(This article belongs to the Section Health Outcomes of Antioxidants and Oxidative Stress)

9 pages, 370 KB

Open AccessArticle

Real-World Use of GLP-1 Receptor Agonist Liraglutide in Adolescents with Obesity: A First Longitudinal Single-Center Analysis from Switzerland

by Cees Noordam, Urs Eiholzer, Claudia Katschnig, Aikaterini Stasinaki and Ilja Dubinski

Children 2025, 12(12), 1716; https://doi.org/10.3390/children12121716 (registering DOI) - 18 Dec 2025

Abstract

Background: Adolescent obesity remains a challenge with limited treatment options. GLP-1 receptor agonists such as liraglutide (Saxenda^®) have shown efficacy in trials, but real-world data in youth are scarce. Methods: This retrospective longitudinal, non-interventional study analyzed 22 adolescents treated with liraglutide [...] Read more.

Background: Adolescent obesity remains a challenge with limited treatment options. GLP-1 receptor agonists such as liraglutide (Saxenda^®) have shown efficacy in trials, but real-world data in youth are scarce. Methods: This retrospective longitudinal, non-interventional study analyzed 22 adolescents treated with liraglutide in a Swiss pediatric endocrinology center. All received non-structured nutritional/lifestyle counseling with three-monthly follow-up. BMI standard deviation scores (BMI-SDS) and adverse effects were recorded. Results: The mean age at initiation was 14.9 years (range 12.5–17.5); 15 patients had Southern European immigrant background. Mean treatment duration was 8.2 months (range 1–18). BMI-SDS decreased significantly from +2.63 (IQR +2.4/+2.8) to +2.40 (IQR +2.2/+2.6). Median intra-individual reduction was −0.20 (IQR −0.28/−0.10), p = 0.0003 with large effect size (rb = −0.77). Thirteen patients discontinued treatment, mainly due to insufficient weight loss or mild nausea. In the patients continuing therapy BMI-SDS decreased from +2.59 (IQR +2.4/+2.8) to +2.08 (IQR +1.9/+2.4). No serious adverse events occurred. Conclusions: Liraglutide showed a comparable efficacy to the pivotal clinical trial in reducing BMI-SDS in adolescents, while the side-effect profile was similarly mild and consistent with previously reported data. Discontinuation rates remained high, highlighting the need for thorough pre-treatment counseling on expected mild, transient symptoms and strategies to mitigate nausea. Future prospective studies are needed to assess long-term outcomes and identify patient characteristics associated with greater treatment success, to better individualize GLP-1–based therapy in adolescent obesity. Full article

(This article belongs to the Section Pediatric Endocrinology & Diabetes)

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20 pages, 1546 KB

Open AccessArticle

Enhancing Bio-Oil Quality Through Ethyl Esterification Catalyzed by Candida antarctica Lipase

by Aline Gonçalves Gehrke, Leonardo Pellizzari Wielewski, Vinicyus Rodolfo Wiggers, Vanderleia Botton, David Alexander Mitchell and Nadia Krieger

Processes 2025, 13(12), 4085; https://doi.org/10.3390/pr13124085 (registering DOI) - 18 Dec 2025

Abstract

Fast pyrolysis of vegetable oils and residues generates bio-oil (BO), a renewable hydrocarbon source with high acidity that limits its direct use in refineries. In this study, BOs were produced from refined soybean oil (RSO) and waste cooking oil (WCO) at 525 °C [...] Read more.

Fast pyrolysis of vegetable oils and residues generates bio-oil (BO), a renewable hydrocarbon source with high acidity that limits its direct use in refineries. In this study, BOs were produced from refined soybean oil (RSO) and waste cooking oil (WCO) at 525 °C in a continuous bench-scale pyrolysis at 525 °C, with a 390 ± 8 g h⁻¹ feed rate, under steady-state conditions. The resulting bio-oils exhibited high acidity (acid index of 145 and 127 mg KOH g⁻¹, respectively) and elevated olefinic and oxygen contents, making them corrosive and unsuitable for co-refining with petroleum. To reduce acidity, ethyl esterification was performed using lipase B from Candida antarctica (CALB), using a Box–Behnken 3³ factorial design. Variables included temperature (40–60 °C), bio-oil:ethanol mass ratio (1:1–1:5), and catalyst concentration (3–10% w/w). The acid index was reduced by up to 76%, with optimal conditions (62 °C, 1:1 mass ratio, 11% CALB) yielding a final value of 28 mg KOH g⁻¹. Similar reductions were obtained for waste cooking oil bio-oil, confirming robustness across feedstocks. CALB retained over 70% activity after three cycles, demonstrating stability. This enzymatic esterification process shows strong potential for lowering bio-oil acidity, enabling integration into petroleum refineries, diversifying feedstocks, and advancing renewable fuel production. Full article

(This article belongs to the Special Issue Enzymes, Biocatalysis and Metabolic Engineering for Enabling Sustainability)

26 pages, 32319 KB

Open AccessArticle

UAV LiDAR-Based Automated Detection of Maize Lodging in Complex Agroecosystems

by Yajin Wang, Fengbao Yang and Linna Ji

Drones 2025, 9(12), 876; https://doi.org/10.3390/drones9120876 (registering DOI) - 18 Dec 2025

Abstract

Maize lodging poses a significant challenge to agricultural production, severely constraining yield improvement and mechanized harvesting efficiency. Under modern agricultural practices characterized by high-density planting and multi-variety intercropping, there is an urgent need for precise and efficient monitoring technologies to address lodging issues. [...] Read more.

Maize lodging poses a significant challenge to agricultural production, severely constraining yield improvement and mechanized harvesting efficiency. Under modern agricultural practices characterized by high-density planting and multi-variety intercropping, there is an urgent need for precise and efficient monitoring technologies to address lodging issues. This study utilized unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) to acquire high-precision point cloud data of field maize at full maturity. An innovative method was proposed to automatically identify structural differences induced by lodging by analyzing canopy structural similarity across multiple height thresholds through point cloud stratification. This approach enables automated monitoring of maize lodging in complex field environments. The experimental results demonstrate the following: (1) High-precision point cloud data effectively capture canopy structural differences caused by lodging. Based on the structural similarity change curve, the height threshold for lodging can be automatically identified (optimal threshold: 1.76 m), with a deviation of only 2.3% between the calculated lodging area and the manually measured reference (ground truth). (2) Sensitivity analysis of the height threshold shows that when the threshold fluctuates within a ±5 cm range (1.71–1.81 m), the calculation deviation of the lodging area remains below 10% (maximum deviation = 8.2%), indicating strong robustness of the automatically selected threshold. (3) Although UAV flight altitude influences point cloud quality (e.g., low altitude: 25 m, high altitude: 80 m), the height threshold derived from low-altitude flights can be extrapolated to high-altitude monitoring to some extent. In this study, the resulting deviation in lodging area calculation was only 5.3%. Full article

(This article belongs to the Special Issue The Role of UAVs in Modern Agriculture: Precision Spraying and Crop Health Analysis)

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22 pages, 3515 KB

Open AccessArticle

Microbial Co-Occurrence Network Robustness, Not Diversity, Is a Key Predictor of Soil Organic Carbon in High-Altitude Mountain Forests

by Yiming Feng, Chunyan Lv, Tianwei Wu, Jinhua Li, Ling Wang and Changming Zhao

Forests 2025, 16(12), 1876; https://doi.org/10.3390/f16121876 (registering DOI) - 18 Dec 2025

Abstract

Altitude-driven environmental changes influence the persistence of soil organic carbon (SOC) via microbial metabolic pathways. However, the degree to which the network robustness of microbial communities directly predicts the persistence of organic carbon in alpine mountain forests remains unclear. This study focused on [...] Read more.

Altitude-driven environmental changes influence the persistence of soil organic carbon (SOC) via microbial metabolic pathways. However, the degree to which the network robustness of microbial communities directly predicts the persistence of organic carbon in alpine mountain forests remains unclear. This study focused on the Qilian Sabina przewalskii forest, situated along an altitude gradient of 2900–3400 m in the Qilian Mountains, systematically exploring the organization of soil microbial communities, the co-occurrence networks’ robustness, and their predictive capacity for organic carbon storage. The results indicate that altitude, as a critical driving factor, not only alters the physicochemical properties, microbial composition, and diversity of the soil but also significantly impacts its complexity and network robustness. The complexity and robustness of the microbial network are highest in the mid-altitude region (3100–3200 m), which is conducive to the development of robust microbial networks. Both bacterial α diversity and network robustness exhibit positive correlations with SOC, whereas fungal diversity shows a negative correlation with SOC. Furthermore, statistical modeling revealed that indices of microbial co-occurrence network robustness were stronger predictors of SOC storage than classical alpha-diversity indices. The structural equation model reveals that microbial biomass nitrogen (MBN) serves as a key mediating factor linking microbial diversity and SOC. Soil characteristics emerge as the primary direct driving factor, whereas the robustness of microbial networks exerts a significant yet minor direct and mediating influence. This study underscores that the robustness of microbial networks, rather than their diversity, is a critical predictor of soil organic carbon in high-altitude mountain forests. It offers a novel theoretical framework for understanding the mechanisms of the carbon cycle in mountain forest ecosystems in the context of climate warming. Full article

(This article belongs to the Special Issue Forest Plant, Soil, Microorganisms and Their Interactions—2nd Edition)

9 pages, 240 KB

Open AccessArticle

Cystolitholapaxy Without Transurethral Resection of the Prostate: Clinical Outcomes and Predictors of Subsequent Resection

by Jeremy Cheng, Arjun Guduguntla, Arveen Kalapara, Jeremy Grummet and Gideon Blecher

Soc. Int. Urol. J. 2025, 6(6), 73; https://doi.org/10.3390/siuj6060073 (registering DOI) - 18 Dec 2025

Abstract

Background/Objectives: Limited data exist on the outcomes of men with bladder stones undergoing cystolitholapaxy alone versus cystolitholapaxy with concurrent transurethral resection of the prostate (TURP). Additionally, factors associated with the need for subsequent TURP in these patients are not well defined. This study [...] Read more.

Background/Objectives: Limited data exist on the outcomes of men with bladder stones undergoing cystolitholapaxy alone versus cystolitholapaxy with concurrent transurethral resection of the prostate (TURP). Additionally, factors associated with the need for subsequent TURP in these patients are not well defined. This study aimed to compare the clinical outcomes in men undergoing cystolitholapaxy alone with those undergoing concurrent cystolitholapaxy with TURP, and determine what factors were associated with the need for subsequent TURP. Methods: A retrospective review was conducted of men undergoing cystolitholapaxy at a single Australian hospital between 2014 and 2021. Patients were grouped into cystolitholapaxy alone (Group A) and cystolitholapaxy with concurrent TURP (Group B). Clinical outcomes compared included rates of acute urinary retention (AUR), urinary tract infection (UTI), and subsequent TURP. Prostate volume (PV), stone size, and the presence of intravesical prostatic protrusion (IPP) were evaluated as potential predictors of subsequent TURP in Group A. Results: Fifty men were included in the final analysis, with a median follow-up of 50 months (IQR 24–81). Baseline characteristics did not differ significantly between groups. There was no statistically significant difference in the rates of AUR (11% vs. 13%) or UTI (22% vs. 30%) between Group A and Group B, respectively. However, 41% of Group A underwent subsequent TURP, compared to 9% in Group B (p = 0.0112). Within Group A, those requiring subsequent TURP had a significantly greater PV (65 vs. 34 cc, p = 0.0059), larger stone size (3.5 vs. 2.0 cm, p = 0.0175), and a higher prevalence of IPP (82% vs. 6%, p < 0.001). Conclusions: Cystolitholapaxy alone is a viable initial treatment for bladder stones, with comparable clinical outcomes to concurrent TURP. PV, stone size, and IPP may help identify patients likely to require future TURP, enabling more tailored treatment and potential reduction in TURP-related morbidity. Full article

22 pages, 3132 KB

Open AccessArticle

A Study on a Low-Cost IMU/Doppler Integrated Velocity Estimation Method Under Insufficient GNSS Observation Conditions

by Yinggang Wang, Hongli Zhang, Kemeng Li, Hanghang Xu and Yijin Chen

Sensors 2025, 25(24), 7674; https://doi.org/10.3390/s25247674 (registering DOI) - 18 Dec 2025

Abstract

The Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) Loosely Coupled (LC) integration framework has been widely adopted due to its simple structure, but it relies on complete GNSS position and velocity solutions, and the rapid accumulation of IMU errors can easily lead [...] Read more.

The Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) Loosely Coupled (LC) integration framework has been widely adopted due to its simple structure, but it relies on complete GNSS position and velocity solutions, and the rapid accumulation of IMU errors can easily lead to navigation failure when fewer than four satellites are visible. In this paper, GNSS Doppler observations are fused with IMU attitude information within an LC framework. An inter-satellite differential Doppler model is introduced, and the velocity obtained from the differential Doppler solution is transformed into the navigation frame using the IMU-derived attitude, enabling three-dimensional velocity estimation in the navigation frame even when only two satellites are available. Analysis of real vehicle data collected by the GREAT team at Wuhan University shows that the Signal-to-Noise Ratio (SNR) and the geometric relationship between the Satellite Difference Vector (SDV) and the Receiver Motion Direction (RMD) are the dominant factors affecting velocity accuracy. A multi-factor threshold screening strategy further indicates that when

S NR >

40 and

∣ SDV \cdot RMD ∣ > 0.2

, the Root Mean Square (RMS) of the velocity error is approximately 0.3 m/s and the data retention rate exceeds 44%, achieving a good balance between accuracy and availability. The results indicate that, while maintaining a simple system structure, the proposed Doppler–IMU fusion method can significantly enhance velocity robustness and positioning continuity within an LC architecture under weak GNSS conditions (when more than two satellites are visible but standalone GNSS positioning is still unavailable), and is suitable for constructing low-cost, highly reliable integrated navigation systems. Full article

(This article belongs to the Section Navigation and Positioning)

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16 pages, 1371 KB

Open AccessCommunication

Magnetic Catalyzed Fenton Oxidation by CuO/ns-Fe₃O₄ for Modification of Humic Acids

by Tianbo Li, Xudong Zheng, Xinyue Hu and Guangzhou Hu

Catalysts 2025, 15(12), 1175; https://doi.org/10.3390/catal15121175 (registering DOI) - 18 Dec 2025

Abstract

Humic acids (HAs) are widely used as adsorbents or carriers, yet they still lack oxygenic functional groups under certain conditions. Modification via catalytic oxidation under mild conditions is an ideal method to increase the oxygenic functional groups in HAs—if simple catalyst separation could [...] Read more.

Humic acids (HAs) are widely used as adsorbents or carriers, yet they still lack oxygenic functional groups under certain conditions. Modification via catalytic oxidation under mild conditions is an ideal method to increase the oxygenic functional groups in HAs—if simple catalyst separation could be realized. Here, we report the use of CuO nanoparticles supported by Fe₃O₄ magnetic nanospheres as magnetic catalytic systems (MCSs) that could catalyze HA modification via Fenton oxidation. These MCSs can be easily magnetically separated from the products. The content of carboxyl groups increased from 2.45% to 10.47% after reaction, while the yield of modified HAs remained approximately 100%. These results indicate that oxidation with MCSs could be a potential method for HA modification. Full article

(This article belongs to the Special Issue Heterogeneous Catalysis in China: New Horizons and Recent Advances)

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15 pages, 2362 KB

Open AccessArticle

Seismic Vulnerability of Single-Story Precast Industrial Buildings in Romania

by Viorel Popa, Eugen Lozincă, Dietlinde Köber and Mihai Pavel

Appl. Sci. 2025, 15(24), 13274; https://doi.org/10.3390/app152413274 (registering DOI) - 18 Dec 2025

Abstract

The paper investigates the seismic vulnerability of single-story precast industrial buildings constructed in Romania during the 1970s, with particular reference to the damage observed following the 1977 Romanian earthquake. More than 800 structures were analytically assessed using a displacement-based evaluation procedure grounded in [...] Read more.

The paper investigates the seismic vulnerability of single-story precast industrial buildings constructed in Romania during the 1970s, with particular reference to the damage observed following the 1977 Romanian earthquake. More than 800 structures were analytically assessed using a displacement-based evaluation procedure grounded in their original design specifications. Several displacement capacity models for flexure-controlled concrete columns were applied, and their suitability for the analyzed buildings is critically discussed. The study also includes a detailed case study that illustrates the practical application of the assessment methodology and highlights specific structural behaviors under seismic loading. The results demonstrate that the displacement-based assessment provides realistic predictions of seismic performance, consistent with observations from similar buildings constructed after the 1977 Vrancea earthquake. The conclusions indicate that the analyzed buildings generally exhibit favorable seismic behavior, with flexural hinging preceding shear failure and displacement-based methods offering more realistic and less conservative assessments than traditional force-based approaches. The scientific contribution of this work lies in using a comprehensive framework for evaluating the seismic response of existing precast industrial structures, offering insights into the effectiveness of different column capacity models, and establishing a foundation for future research on retrofitting strategies and the interaction of structural and non-structural components under seismic actions. Full article

(This article belongs to the Topic Degradation, Repair and Rehabilitation of Reinforced Concrete Structures)

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20 pages, 1954 KB

Open AccessArticle

Explaining Street-Level Thermal Variability Through Semantic Segmentation and Explainable AI: Toward Climate-Responsive Building and Urban Design

by Yuseok Lee, Minjun Kim and Eunkyo Seo

Atmosphere 2025, 16(12), 1413; https://doi.org/10.3390/atmos16121413 (registering DOI) - 18 Dec 2025

Abstract

Understanding outdoor thermal environments at fine spatial scales is essential for developing climate-responsive urban and building design strategies. This study investigates the determinants of local air temperature deviations in Seoul, Korea, using high-resolution in situ sensor data integrated with multi-source urban and building [...] Read more.

Understanding outdoor thermal environments at fine spatial scales is essential for developing climate-responsive urban and building design strategies. This study investigates the determinants of local air temperature deviations in Seoul, Korea, using high-resolution in situ sensor data integrated with multi-source urban and building information. Hourly temperature records from 436 road-embedded sensors (March 2024–February 2025) were transformed into relative metrics representing deviations from the network-wide mean and were combined with semantic indicators derived from street-view imagery—Green View Index (GVI), Road View Index (RVI), Building View Index (BVI), Sky View Index (SVI), and Street Enclosure Index (SEI)—along with land-cover and building attributes such as impervious surface area (ISA), gross floor area (GFA), building coverage ratio (BCR), and floor area ratio (FAR). Employing an eXtreme Gradient Boosting (XGBoost)–Shapley Additive exPlanations (SHAP) framework, the study quantifies nonlinear and interactive relationships among morphological, environmental, and visual factors. SEI, BVI, and ISA emerged as dominant contributors to localized heating, while RVI, GVI, and SVI enhanced cooling potential. Seasonal contrasts reveal that built enclosure and vegetation visibility jointly shape micro-scale heat dynamics. The findings demonstrate how high-resolution, observation-based data can guide climate-responsive design strategies and support thermally adaptive urban planning. Full article

(This article belongs to the Special Issue Urban Adaptation to Heat and Climate Change)

20 pages, 501 KB

Open AccessArticle

Cultivating Risk-Response Capability: The Impact of Partner Compatibility and Supply Chain Collaboration

by Su Kyong Cho, Pyoungsoo Lee and Dawoon Jung

Systems 2025, 13(12), 1130; https://doi.org/10.3390/systems13121130 (registering DOI) - 18 Dec 2025

Abstract

Supply chains operate in increasingly volatile environments, making it essential to understand the mechanisms through which partner characteristics shape risk-response capability. This study examines how compatibility between supply chain partners promotes collaboration and, in turn, strengthens robustness and resilience. Using survey data from [...] Read more.

Supply chains operate in increasingly volatile environments, making it essential to understand the mechanisms through which partner characteristics shape risk-response capability. This study examines how compatibility between supply chain partners promotes collaboration and, in turn, strengthens robustness and resilience. Using survey data from 219 managers in South Korea, the study develops a conceptual model grounded in congruence theory and the dynamic capability view, and tests it through partial least squares path modeling. The results show that compatibility enhances collaboration, which subsequently improves risk-response capability and mediates the effect of compatibility on robustness and resilience. These findings provide empirical support for a capability-building mechanism in which inter-organizational compatibility enables more effective collaborative practices that enhance a supply chain’s ability to withstand and recover from disruptions. The study extends prior research by shifting the discussion of compatibility from interpersonal or person–organization settings to the inter-organizational domain and by demonstrating its critical role in cultivating dynamic capabilities in supply chain risk management. Full article

(This article belongs to the Special Issue Navigating Complexity in a Changing World: Challenges and Opportunities for Sustainable and Resilient Supply Chains)

65 pages, 4875 KB

Open AccessArticle

Logistics Performance and the Three Pillars of ESG: A Detailed Causal and Predictive Investigation

by Nicola Magaletti, Valeria Notarnicola, Mauro Di Molfetta, Stefano Mariani and Angelo Leogrande

Sustainability 2025, 17(24), 11370; https://doi.org/10.3390/su172411370 (registering DOI) - 18 Dec 2025

Abstract

This study investigates the complex relationship between the performance of logistics and Environmental, Social, and Governance (ESG) performance, drawing upon the multi-methodological framework of combining econometrics with state-of-the-art machine learning approaches. Employing Instrumental Variable (IV) Panel data regressions, viz., 2SLS and G2SLS, with [...] Read more.

This study investigates the complex relationship between the performance of logistics and Environmental, Social, and Governance (ESG) performance, drawing upon the multi-methodological framework of combining econometrics with state-of-the-art machine learning approaches. Employing Instrumental Variable (IV) Panel data regressions, viz., 2SLS and G2SLS, with data from a balanced panel of 163 countries covering the period from 2007 to 2023, the research thoroughly investigates how the performance of the Logistics Performance Index (LPI) is correlated with a variety of ESG indicators. To enrich the analysis, machine learning models—models based upon regression, viz., Random Forest, k-Nearest Neighbors, Support Vector Machines, Boosting Regression, Decision Tree Regression, and Linear Regressions, and clustering, viz., Density-Based, Neighborhood-Based, and Hierarchical clustering, Fuzzy c-Means, Model-Based, and Random Forest—were applied to uncover unknown structures and predict the behavior of LPI. Empirical evidence suggests that higher improvements in the performance of logistics are systematically correlated with nascent developments in all three dimensions of the environment (E), social (S), and governance (G). The evidence from econometrics suggests that higher LPI goes with environmental trade-offs such as higher emissions of greenhouse gases but cleaner air and usage of resources. On the S dimension, better performance in terms of logistics is correlated with better education performance and reducing child labor, but also demonstrates potential problems such as social imbalances. For G, better governance of logistics goes with better governance, voice and public participation, science productivity, and rule of law. Through both regression and cluster methods, each of the respective parts of ESG were analyzed in isolation, allowing us to study in-depth how the infrastructure of logistics is interacting with sustainability research goals. Overall, the study emphasizes that while modernization is facilitated by the performance of the infrastructure of logistics, this must go hand in hand with policy intervention to make it socially inclusive, environmentally friendly, and institutionally robust. Full article

(This article belongs to the Special Issue Sustainable Logistics and Supply Chain Operations: Risks, Rebuck, and Resilience)

12 pages, 5317 KB

Open AccessArticle

Impact of Environmental Weathering on the Chemical Composition of Spilled Oils in a Real Case in Brazil

by Ana Beatriz A. de M. Salata, Marília G. A. Pereira, Isabelle F. S. de Lima, Ignes Regina dos Santos, Danielle M. M. Franco, Boniek G. Vaz and Jandyson M. Santos

Coasts 2025, 5(4), 49; https://doi.org/10.3390/coasts5040049 (registering DOI) - 18 Dec 2025

Abstract

Brazil suffered the largest oil spill disaster in its history, beginning on August 2019, affecting the Northeast coast. This study proposes a chemical investigation of oils from the 2019 spill in Brazil, which had naturally undergone different weathering processes in terrestrial and aquatic [...] Read more.

Brazil suffered the largest oil spill disaster in its history, beginning on August 2019, affecting the Northeast coast. This study proposes a chemical investigation of oils from the 2019 spill in Brazil, which had naturally undergone different weathering processes in terrestrial and aquatic environments after an extended period of exposure. Three samples were collected at different times and under distinct environmental conditions, coded as spilled oil (SO), oil recovered from the aquatic environment (SA), and oil collected from the terrestrial environment (ST), the latter two having spent more time naturally exposed to aquatic and terrestrial environments. The analyses were performed by gas chromatography–mass spectrometry (GC-MS) and electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS). The results of the GC-MS analysis indicated that, although the samples share a common geochemical origin, the SA and ST samples showed a decrease in the intensity of n-alkane distribution compared to the SO sample, mainly attributed to evaporation and biodegradation processes. FT-ICR MS analysis identified dozens of classes of ESI(+) and ESI(–) compounds, most of them rich in sulfur and oxygen, with the highest intensities and quantities of molecular formulas in the SA and ST samples. Diagnostic ratios for heteroatom classes concluded that the SA and ST samples had undergone a higher level of weathering, mainly associated with photooxidation and biodegradation processes. Thus, the combined use of GC-MS and FT-ICR MS proved to be a robust approach for the detailed characterization of spilled oils, contributing to a clearer understanding of the extent and type of weathering in samples from the 2019 Brazilian spill. Full article

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24 pages, 7865 KB

Open AccessArticle

An Indoor UAV Localization Framework with ESKF Tightly-Coupled Fusion and Multi-Epoch UWB Outlier Rejection

by Jianmin Zhao, Zhongliang Deng, Enwen Hu, Wenju Su, Boyang Lou and Yanxu Liu

Sensors 2025, 25(24), 7673; https://doi.org/10.3390/s25247673 (registering DOI) - 18 Dec 2025

Abstract

Unmanned aerial vehicles (UAVs) are increasingly used indoors for inspection, security, and emergency tasks. Achieving accurate and robust localization under Global Navigation Satellite System (GNSS) unavailability and obstacle occlusions is therefore a critical challenge. Due to their inherent physical limitations, Inertial Measurement Unit [...] Read more.

Unmanned aerial vehicles (UAVs) are increasingly used indoors for inspection, security, and emergency tasks. Achieving accurate and robust localization under Global Navigation Satellite System (GNSS) unavailability and obstacle occlusions is therefore a critical challenge. Due to their inherent physical limitations, Inertial Measurement Unit (IMU)–based localization errors accumulate over time, Ultra-Wideband (UWB) measurements suffer from systematic biases in Non-Line-of-Sight (NLOS) environments and Visual–Inertial Odometry (VIO) depends heavily on environmental features, making it susceptible to long-term drift. We propose a tightly coupled fusion framework based on the Error-State Kalman Filter (ESKF). Using an IMU motion model for prediction, the method incorporates raw UWB ranges, VIO relative poses, and TFmini altitude in the update step. To suppress abnormal UWB measurements, a multi-epoch outlier rejection method constrained by VIO is developed, which can robustly eliminate NLOS range measurements and effectively mitigate the influence of outliers on observation updates. This framework improves both observation quality and fusion stability. We validate the proposed method on a real-world platform in an underground parking garage. Experimental results demonstrate that, in complex indoor environments, the proposed approach exhibits significant advantages over existing algorithms, achieving higher localization accuracy and robustness while effectively suppressing UWB NLOS errors as well as IMU and VIO drift. Full article

(This article belongs to the Section Navigation and Positioning)

28 pages, 2395 KB

Open AccessArticle

Efficiency and Running Time Robustness in Real Metro Automatic Train Operation Systems: Insights from a Comprehensive Comparative Study

by María Domínguez, Adrián Fernández-Rodríguez, Asunción P. Cucala and Antonio Fernández-Cardador

Sustainability 2025, 17(24), 11371; https://doi.org/10.3390/su172411371 (registering DOI) - 18 Dec 2025

Abstract

Automatic Train Operation (ATO) systems are widely deployed in metro networks to improve punctuality, service regularity, and ultimately the sustainability of rail operation. Although eco-driving optimisation has been extensively studied, no previous work has provided a systematic, side-by-side comparison of the two ATO [...] Read more.

Automatic Train Operation (ATO) systems are widely deployed in metro networks to improve punctuality, service regularity, and ultimately the sustainability of rail operation. Although eco-driving optimisation has been extensively studied, no previous work has provided a systematic, side-by-side comparison of the two ATO control philosophies most commonly implemented in metro systems worldwide: (i) Type 1, based on speed holding followed by a single terminal coasting at a kilometre point, and (ii) Type 2, which uses speed thresholds to apply either continuous speed holding or iterative coasting–remotoring cycles. These strategies differ fundamentally in their control logic and may lead to distinct operational and energetic behaviours. This paper presents a comprehensive comparison of these two ATO philosophies using a high-fidelity train movement simulator and Pareto-front optimisation via a multi-objective particle swarm algorithm. 40 interstations of a real metro line were evaluated under realistic comfort and operational constraints, and robustness was assessed through sensitivity to three different passenger-load variations (empty train, nominal load and full load). Results show that, once nominal profiles are implemented, Type 1 has up to 5% variability in running times, and Type 2 has up to 20% variability in energy consumption. In conclusion, a new ATO deployment combining both strategies could better balance energy efficiency and timetable robustness in metro operations. Full article

(This article belongs to the Section Sustainable Transportation)

34 pages, 13059 KB

Open AccessArticle

Synthesis, Anti-Tumour, and Antibacterial Activities of Monocarbonyl Curcumin Analogues of Piperidones

by Renhua Dong, Ruirui Xu and Xiuli Wang

Int. J. Mol. Sci. 2025, 26(24), 12179; https://doi.org/10.3390/ijms262412179 (registering DOI) - 18 Dec 2025

Abstract

Curcumin has anti-tumour and antibacterial effects. In this research, fourteen kinds of piperidone monocarbonyl curcumin analogues with 3,5-dimethylene-4-piperidone as the parent scaffold and halogen substitution on both sides of the benzene ring were synthesized by Claisen–Schmidt reaction, and their anti-tumour effect, mechanism, and [...] Read more.

Curcumin has anti-tumour and antibacterial effects. In this research, fourteen kinds of piperidone monocarbonyl curcumin analogues with 3,5-dimethylene-4-piperidone as the parent scaffold and halogen substitution on both sides of the benzene ring were synthesized by Claisen–Schmidt reaction, and their anti-tumour effect, mechanism, and antibacterial activity were investigated. It was found that a series of curcumin analogues has different degrees of anti-tumour and antibacterial dual activity. Among them, 2,5-2Cl, 2Br-5Cl, 2-Cl, 2-F, and benzaldehyde have strong broad-spectrum anti-tumour effects and have obvious selective inhibitory effects on A549 cells. The IC₅₀ value is less than 5 μmol/L. The five promising compounds, respectively, inhibited the expression of AKT and ERK to induce apoptosis of A549 cells to varying degrees. The newly synthesized analogues 2,5-2Cl and 2Br-5Cl had stronger inhibitory effects on the growth of A549 cells than other analogues, and they tended to mainly inhibit the expression of AKT and ERK, respectively. However, 2-Cl and 2-F have significantly better inhibitory effects on methicillin-resistant Staphylococcus aureus (MRSA) than antibiotics. Taken together, piperidone monocarbonyl curcumin analogues may be developed as good candidates for potential prevention and treatment of cancer and bacterial infection complications. Full article

(This article belongs to the Collection Bioactive Natural Compounds for Therapeutics and Nutraceutical Applications)

22 pages, 5170 KB

Open AccessArticle

Generalizations of Choquet-like Integrals by Restricted Dissimilarity Functions Applied to Multi-Channel Edge Detection Problems

by Miqueias Amorim, Giancarlo Lucca, Bruno L. Dalmazo, Cedric Marco-Detchart and Graçaliz Pereira Dimuro

Appl. Sci. 2025, 15(24), 13273; https://doi.org/10.3390/app152413273 (registering DOI) - 18 Dec 2025

Abstract

Edge detection is a fundamental component of vision tasks, yet the fusion stage that combines multi-cue evidence has received limited attention. We explore the use of a family of Choquet-based fusion operators generalised by restricted dissimilarity functions for robust, training-free, single-scale edge detection [...] Read more.

Edge detection is a fundamental component of vision tasks, yet the fusion stage that combines multi-cue evidence has received limited attention. We explore the use of a family of Choquet-based fusion operators generalised by restricted dissimilarity functions for robust, training-free, single-scale edge detection on the BSDS500 dataset. Local cues are extracted from eight connected neighbours after Gaussian or Gravitational smoothing; ordered samples are aggregated with a fuzzy power measure using three operator families: d-CF, d-XC, and d-CC integrals. Binary edge maps are obtained through non-maximum suppression and Rosin thresholding. Evaluation follows the Bezdek framework for edge detection, utilising the Estrada–Jepson correspondence, and extracts precision, recall, and the F-score. All inferential statistics are restricted to within-family comparisons among our variants. The main results are that gravitational smoothing consistently improves performance, and the best performance is achieved with the absolute-difference restricted dissimilarity under gravitational smoothing. Under Gaussian smoothing, the best performance is obtained with the modulus of the squared difference and with the squared difference of the roots. These findings indicate that restricted-dissimilarity-based Choquet operators, particularly d-CC integrals with gravitational smoothing, form a straightforward and interpretable fusion mechanism, motivating further analysis of component interactions and multi-scale extensions. Full article

(This article belongs to the Special Issue Image Processing: Technologies, Methods, Apparatus)

32 pages, 3557 KB

Open AccessArticle

ANSYS/LS-DYNA Simulation and Experimental Study of a Corrugated Hob-Type Laver Harvesting Device

by Yizhi Chang, Shuai Lv, Yazhou Yang, Shang Ni, Bin Xu, Guochen Zhang, Xiuchen Li, Hanbing Zhang, Qian Zhang, Hangqi Li, Hao Wu and Gang Mu

Appl. Sci. 2025, 15(24), 13271; https://doi.org/10.3390/app152413271 (registering DOI) - 18 Dec 2025

Abstract

Harvesting of laver is an important link in the laver culture chain, and a new type of corrugated harvesting blade with a curved edge angle was designed to solve the problems of low cutting ratio in laver harvesting. The mechanical model of the [...] Read more.

Harvesting of laver is an important link in the laver culture chain, and a new type of corrugated harvesting blade with a curved edge angle was designed to solve the problems of low cutting ratio in laver harvesting. The mechanical model of the corrugated blade cutting laver was established to elucidate the dynamic characteristics of laver cutting under single-point support. Based on the measured biomechanical characteristic parameters of Porphyra yezoensis, a rigid-flexible coupling model of laver harvesting was established based on ANSYS/LS-DYNA2022R2. The Box–Behnken design (BBD) test method was used to study the influence of the main structural parameters of the corrugated blade on the harvesting of laver, and the optimal structural parameter combinations of the corrugated blade were determined as follows: a slip angle of 21°, blade inclination angle of 106°, and curved edge angle of 15°; the slip-cutting mowing force of the laver was 11.18 N and the tensile force was 1.4 N. A bench test was completed, and the results showed that the corrugated blade could be used for harvesting laver. The results showed that the average loss rate of the harvesting equipment was 1.85% and the average net recovery rate was 98.75% when the corrugated blade rotational speed was 900 rpm and the boat speed was 0.71 m/s; compared to the traditional straight-blade hob-type harvesting machine, the cutting force on laver has increased by 45.26%, and the tensile force has decreased by 68.35%, which satisfied the requirements of laver harvesting. This study provides theoretical and simulation model references for the design, analysis, and optimization of laver harvesting equipment. Full article

24 pages, 1503 KB

Open AccessReview

Progress in Charge Transfer in 2D Metal Halide Perovskite Heterojunctions: A Review

by Chenjing Quan, Jiahe Yan, Xiaofeng Liu, Qing Lin, Beibei Xu and Jianrong Qiu

Materials 2025, 18(24), 5690; https://doi.org/10.3390/ma18245690 (registering DOI) - 18 Dec 2025

Abstract

Metal halide perovskite (MHP)-based heterojunctions have become a forefront area in the research of optoelectronic functional materials due to their unique layered crystal structure, tunable band gaps, and exceptional optoelectronic properties. Recent studies have demonstrated that interface charge transfer is a crucial factor [...] Read more.

Metal halide perovskite (MHP)-based heterojunctions have become a forefront area in the research of optoelectronic functional materials due to their unique layered crystal structure, tunable band gaps, and exceptional optoelectronic properties. Recent studies have demonstrated that interface charge transfer is a crucial factor in determining the optoelectronic performance of the heterojunction devices. By constructing heterojunctions between MHPs and two-dimensional (2D) materials such as graphene, MoS₂, and WS₂, efficient electron–hole separation and transport can be achieved, significantly extending carrier lifetimes and suppressing non-radiative recombination. This results in enhanced response speed and energy conversion efficiency in photodetectors, photovoltaic devices, and light-emitting devices (LEDs). In these heterojunctions, the thickness of the MHP layer, interface defect density, and band alignment significantly influence carrier dynamics. Furthermore, techniques such as interface engineering, molecular passivation, and band engineering can effectively optimize charge separation efficiency and improve device stability. The integration of multilayer heterojunctions and flexible designs also presents new opportunities for expanding the functionality of high-performance optoelectronic devices. In this review, we systematically summarize the charge transfer mechanisms in MHP-based heterojunctions and highlight recent advances in their optoelectronic applications. Particular emphasis is placed on the influence of interfacial coupling on carrier generation, transport, and recombination dynamics. Furthermore, the ultrafast dynamic behaviors and band-engineering strategies in representative heterojunctions are elaborated, together with key factors and approaches for enhancing charge transfer efficiency. Finally, the potential of MHP heterojunctions for high-performance optoelectronic devices and emerging photonic systems is discussed. This review aims to provide a comprehensive theoretical and experimental reference for future research and to offer new insights into the rational design and application of flexible optoelectronics, photovoltaics, light-emitting devices, and quantum photonic technologies. Full article

(This article belongs to the Section Energy Materials)

22 pages, 3324 KB

Open AccessArticle

Estimation of Leaf Nitrogen Content in Rice Coupling Feature Fusion and Deep Learning with Multi-Sensor Images from UAV

by Xinlei Xu, Xingang Xu, Sizhe Xu, Yang Meng, Guijun Yang, Bo Xu, Xiaodong Yang, Xiaoyu Song, Hanyu Xue, Yuekun Song and Tuo Wang

Agronomy 2025, 15(12), 2915; https://doi.org/10.3390/agronomy15122915 (registering DOI) - 18 Dec 2025

Abstract

Assessing Leaf Nitrogen Content (LNC) is critical for evaluating crop nutritional status and monitoring growth. While Unmanned Aerial Vehicle (UAV) remote sensing has become a pivotal tool for nitrogen monitoring at the field scale, current research predominantly relies on uni-modal feature variables. Consequently, [...] Read more.

Assessing Leaf Nitrogen Content (LNC) is critical for evaluating crop nutritional status and monitoring growth. While Unmanned Aerial Vehicle (UAV) remote sensing has become a pivotal tool for nitrogen monitoring at the field scale, current research predominantly relies on uni-modal feature variables. Consequently, the integration of multidimensional feature information for nitrogen assessment remains largely underutilized in existing literature. In this study, the four types of feature variables (two kinds of spectral indices, color space parameters and texture features from UAV images of RGB and multispectral sensors) were extracted from three dimensions, and crop nitrogen-sensitive feature variables were selected by GCA (Gray Correlation Analysis), followed by one fused deep neural network (DNN-F2) for remote sensing monitoring of rice nitrogen and a comparative analysis with five common machine learning algorithms (RF, GPR, PLSR, SVM and ANN). Experimental results indicate that the DNN-F2 model consistently outperformed conventional machine learning algorithms across all three growth stages. Notably, the model achieved an average R² improvement of 40%, peaking at the rice jointing stage with an R² of 0.72 and an RMSE of 0.08. The study shows that the fusion of multidimensional feature information from UAVs combined with deep learning algorithms has great potential for nitrogen nutrient monitoring in rice crops, and can also provide technical support to guide decisions on fertilizer application in rice fields. Full article

(This article belongs to the Section Precision and Digital Agriculture)

27 pages, 1696 KB

Open AccessArticle

Carbon-Rich Sediment Amendments and Aging: Effects on Desorption and Maize Phytoextraction of 4-Octylphenol and 4-Nonylphenol

by Slaven Tenodi, Snežana Maletić, Marijana Kragulj Isakovski, Aleksandra Tubić, Srđan Rončević, Kristiana Zrnić Tenodi and Jasmina Agbaba

Appl. Sci. 2025, 15(24), 13270; https://doi.org/10.3390/app152413270 (registering DOI) - 18 Dec 2025

Abstract

Carbonaceous amendments are widely proposed to sequester hydrophobic organic contaminants in sediments, yet their effectiveness for alkylphenolic endocrine disruptors in organic-rich freshwater systems—and its time dependence—remains poorly constrained. Here, we compared activated carbon (AC), biochar (BC), and humic compost (HC) for reducing desorption [...] Read more.

Carbonaceous amendments are widely proposed to sequester hydrophobic organic contaminants in sediments, yet their effectiveness for alkylphenolic endocrine disruptors in organic-rich freshwater systems—and its time dependence—remains poorly constrained. Here, we compared activated carbon (AC), biochar (BC), and humic compost (HC) for reducing desorption and maize phytoexposure to 4-octylphenol (4-OP) and 4-nonylphenol (4-NP) in canal sediment from the Jegrička River. Sediment was spiked (~1.1 mg kg⁻¹ 4-OP; 1.2 mg kg⁻¹ 4-NP), amended with 0.5–10% (w/w) AC, BC, or HC, and aged for up to 180 days prior to multi-step XAD-4 desorption tests. A two-compartment first-order model resolved fast- and slow-desorbing pools, while a 10-day maize (Zea mays L.) pot experiment quantified early phytoextraction and sediment–plant–loss mass balances for AC and HC treatments. The unamended sediment exhibited high operational bioavailability: ~98% of both alkylphenols were XAD-4-extractable, and 83–89% of the desorbable pool was released within 24 h. AC produced the most rapid immobilization; at 0.5–1%, it halved XAD-4-extractable fractions within weeks and reduced them to near-zero within months, whereas BC and HC achieved comparable reductions only after longer aging. Plant uptake was a minor sink: in the control, shoots accumulated ~21 µg kg⁻¹ sediment of 4-OP and 65 µg kg⁻¹ sediment of 4-NP (≈2% and 5% of the initial inventory). HC generally lowered uptake, and high AC doses kept plant burdens consistently low. Overall, amendment-enhanced sorption and sequestration dominated attenuation, with AC delivering the fastest risk reduction and HC representing a more plant-compatible amendment option. Full article

(This article belongs to the Section Environmental Sciences)

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