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14 pages, 562 KB  
Article
Machine Learning Prediction of Multidrug Resistance in Swine-Derived Campylobacter spp. Using United States Antimicrobial Resistance Surveillance Data (2013–2023)
by Hamid Reza Sodagari, Maryam Ghasemi, Csaba Varga and Ihab Habib
Vet. Sci. 2025, 12(10), 937; https://doi.org/10.3390/vetsci12100937 (registering DOI) - 26 Sep 2025
Abstract
Campylobacter spp. are leading causes of bacterial gastroenteritis globally. Swine are recognized as an important reservoir for this pathogen. The emergence of antimicrobial resistance (AMR) and multidrug resistance (MDR) in Campylobacter is a global health concern. Traditional methods for detecting AMR and MDR, [...] Read more.
Campylobacter spp. are leading causes of bacterial gastroenteritis globally. Swine are recognized as an important reservoir for this pathogen. The emergence of antimicrobial resistance (AMR) and multidrug resistance (MDR) in Campylobacter is a global health concern. Traditional methods for detecting AMR and MDR, such as phenotypic testing or whole-genome sequencing, are resource-intensive and time-consuming. In the present study, we developed and validated a supervised machine learning model to predict MDR status in Campylobacter isolates from swine, using publicly available phenotypic AMR data collected by NARMS from 2013 to 2023. Resistance profiles for seven antimicrobials were used as predictors, and MDR was defined as resistance to at least one agent in three or more antimicrobial classes. The model was trained on 2013–2019 isolates and externally validated using isolates from 2020, 2021, and 2023. Random Forest showed the highest performance (accuracy = 99.87%, Kappa = 0.9962) among five evaluated algorithms, which achieved high balanced accuracy, sensitivity, and specificity in both training and external validation. Our feature importance analysis identified erythromycin, azithromycin, and clindamycin as the most influential predictors of MDR among Campylobacter isolates from swine. Our temporally validated, interpretable model provides a robust, cost-effective tool for predicting MDR in Campylobacter spp. and supports surveillance and early detection in food animal production systems. Full article
19 pages, 2814 KB  
Article
Verification of the Effectiveness of a Token Economy Method Through Digital Intervention Content for Children with Attention-Deficit/Hyperactivity Disorder
by Seon-Chil Kim
Bioengineering 2025, 12(10), 1035; https://doi.org/10.3390/bioengineering12101035 (registering DOI) - 26 Sep 2025
Abstract
Recently, cognitive training programs using digital content with visuoperceptual stimulation have been developed and commercialized. In particular, digital intervention content for children with attention deficit hyperactivity disorder (ADHD) has been developed as games, enhancing motivation and accessibility for the target population. Active stimulation [...] Read more.
Recently, cognitive training programs using digital content with visuoperceptual stimulation have been developed and commercialized. In particular, digital intervention content for children with attention deficit hyperactivity disorder (ADHD) has been developed as games, enhancing motivation and accessibility for the target population. Active stimulation is required to elicit positive effects on self-regulation training, including attention control and impulse inhibition, through task-based content. Common forms of stimulation include emotional stimuli, such as praise and encouragement, and economic stimuli based on a self-directed token economy system. Economic stimulation can serve as active reinforcement because the child directly engages as the primary agent within the task content. This study applied and validated a token economy intervention using digital therapeutic content in children with ADHD. Behavioral assessments were conducted using the Comprehensive Attention Test (CAT) and the Korean version of the Child Behavior Checklist (K-CBCL). The developed digital intervention content implemented a user-centered token economy based on points within the program. In the CAT Flanker Task, the experimental group (0.84 ± 0.40) showed significantly higher sensitivity factor scores than the control group (0.72 ± 0.59) after 4 weeks, with a large effect size (F = 4.76, p = 0.038, partial η2 = 0.150). Additionally, the rate of change in externalizing behavior scores on the K-CBCL showed a significant difference between the two groups (t = 2.35, p = 0.026, Cohen’s d = 0.860), demonstrating greater improvement in externalizing symptoms in the experimental group than in the control group. Therefore, this study suggests that the participant-centered implementation model using token economy mechanisms in digital intervention content may serve as a novel and effective therapeutic approach for children with ADHD. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
15 pages, 3383 KB  
Article
Analysis of Trace Rare Earth Elements in Uranium-Bearing Nuclear Materials
by Ziao Li, Yang Shao, Futao Xin, Chun Li, Jilong Zhang, Xi Li, Min Luo, Diandou Xu and Lingling Ma
Processes 2025, 13(10), 3089; https://doi.org/10.3390/pr13103089 - 26 Sep 2025
Abstract
Rare earth elements (REEs) have significant application value in the quality control of nuclear materials and in traceability research in nuclear forensics. Methods were developed for the determination of REEs in uranium-bearing nuclear materials. The digestion parameters for uranium oxides and uranium ores, [...] Read more.
Rare earth elements (REEs) have significant application value in the quality control of nuclear materials and in traceability research in nuclear forensics. Methods were developed for the determination of REEs in uranium-bearing nuclear materials. The digestion parameters for uranium oxides and uranium ores, such as the digestion acid, digestion temperature, and digestion time, were optimized and reported. The optimized digestion parameters for uranium oxides were 2 mL HNO3 at 160 °C for 3 h, and those for uranium ores were 7 mL mixed acid (HNO3–HClO4–HF = 5:5:3) at 180 °C for 36 h. Two digestion methods were demonstrated to be effective for the quantitative recovery of REEs. The suitable system and specifications for different resin columns were investigated to achieve a high decontamination factor of U (105) by UTEVA resin. The corresponding loading system was 10 mL 4 M HNO3, and the elution system was 6 mL 4 M HNO3. Additionally, the analysis of ultra-trace REEs in high-uranium matrices was accomplished using two UTEVA resins. The developed methods were subjected to the Cochran test and the Grubbs test, and the relative standard deviation (RSD) for all REEs was below 6%. In uranium oxide samples with different spiked amounts, the recovery of REEs exceeded 80% in all cases, and the RSDs were all less than 10%. The method’s detection limits were below 10 ppt for all REEs (except for Ce), ensuring the accurate measurement of REEs in uranium-bearing nuclear materials. Full article
(This article belongs to the Section Materials Processes)
22 pages, 1000 KB  
Article
Effects of Longitudinal and Transverse Travel Direction on the Hydraulic Performance of Sprinkler Machines on Sloping Terrain
by Zhi Wang, Xingye Zhu and Fuhua Wang
Agriculture 2025, 15(19), 2024; https://doi.org/10.3390/agriculture15192024 - 26 Sep 2025
Abstract
Background: The influence of varying slope gradients on the hydraulic performance of sprinkler irrigation systems operating on sloping farmland is investigated, with a specific focus on longitudinal and transverse travel directions. Methods: A sprinkler irrigation performance test system for sloping terrain is established, [...] Read more.
Background: The influence of varying slope gradients on the hydraulic performance of sprinkler irrigation systems operating on sloping farmland is investigated, with a specific focus on longitudinal and transverse travel directions. Methods: A sprinkler irrigation performance test system for sloping terrain is established, combining theoretical analysis with field experiments. The study systematically examines how different slope conditions affect sprinkler irrigation intensity and uniformity, and identifies the impact of longitudinal and transverse sprinkler machine movement on hydraulic performance under sloping conditions. A three-factor, three-level orthogonal experimental design is adopted, using slope gradient, nozzle pressure, and walking speed as variable factors, with sprinkler irrigation intensity and uniformity as optimization objectives. Results: Results indicate that the influence of slope angle on both sprinkler irrigation intensity and uniformity diminishes along both longitudinal and transverse travel directions. Furthermore, slope gradient exerts the greatest influence on sprinkler irrigation uniformity, followed by walking speed and nozzle pressure. For sprinkler irrigation uniformity, optimal parameters under transverse travel are determined as a 5° slope, 250 kPa pressure, and 30 m/h speed. Under longitudinal travel, optimal sprinkler irrigation uniformity is achieved at a 5° slope, 300 kPa pressure, and 30 m/h speed. Regarding sprinkler irrigation intensity, nozzle pressure and walking speed demonstrate the greatest influence, followed by slope gradient. Optimal intensity for both travel directions is attained at a 5° slope, 300 kPa pressure, and 30 m/h speed. Conclusion: These findings provide theoretical guidance for selecting sprinkler travel patterns and optimizing operational parameters on sloping farmland, offering significant practical implications for enhancing irrigation efficiency and mitigating slope soil erosion. Full article
20 pages, 2913 KB  
Article
Numerical Analysis of Thermal–Structural Coupling for Subsea Dual-Channel Connector
by Feihong Yun, Yuming Du, Dong Liu, Xiaofei Wu, Minggang Tang, Qiuying Yan, Peng Gao, Yu Chen, Xu Zhai, Hanyu Sun, Songlin Zhang, Shuqi Lin and Haiyang Xu
J. Mar. Sci. Eng. 2025, 13(10), 1867; https://doi.org/10.3390/jmse13101867 - 26 Sep 2025
Abstract
In deep-sea oil and gas development scenarios, deep-sea dual-channel connectors often face the risk of seal failure due to internal and external temperature difference loads. To address this issue, this paper systematically establishes equivalent heat transfer models for the key parts of the [...] Read more.
In deep-sea oil and gas development scenarios, deep-sea dual-channel connectors often face the risk of seal failure due to internal and external temperature difference loads. To address this issue, this paper systematically establishes equivalent heat transfer models for the key parts of the connector based on the third-type boundary condition. On this basis, the quantitative correlation between the equivalent thermal conductivity, composite heat transfer coefficient and temperature of each part is explored. Using the finite element numerical simulation method, the transient temperature field of the connector under three working conditions (heating, cooling and temperature shock) is simulated and analyzed, revealing the temperature distribution characteristics and temperature change trends of the maximum temperature difference of each key component of the connector; combined with thermal–structural coupling simulation, the temperature field is converted into static load, to determine the behavior of the contact stress on the sealing surface under different temperature–pressure coupling working conditions; in addition, by placing the test prototype in a high-low temperature cycle chamber, the seal performance tests under pressurized and non-pressurized working conditions are carried out to verify the reliable sealing performance of the connector under variable temperature conditions. The results of this paper provide comprehensive theoretical support and an experimental basis for the thermodynamic optimization design of deep-sea connectors and the improvement of the reliability of the sealing system. Full article
(This article belongs to the Section Ocean Engineering)
19 pages, 916 KB  
Article
An Integrated Co-Simulation Framework for the Design, Analysis, and Performance Assessment of EIS-Based Measurement Systems for the Online Monitoring of Battery Cells
by Nicola Lowenthal, Roberta Ramilli, Marco Crescentini and Pier Andrea Traverso
Batteries 2025, 11(10), 351; https://doi.org/10.3390/batteries11100351 - 26 Sep 2025
Abstract
Electrochemical impedance spectroscopy (EIS) is widely used at the laboratory level for monitoring/diagnostics of battery cells, but the design and validation of in situ, online measurement systems based on EIS face challenges due to complex hardware–software interactions and non-idealities. This study aims to [...] Read more.
Electrochemical impedance spectroscopy (EIS) is widely used at the laboratory level for monitoring/diagnostics of battery cells, but the design and validation of in situ, online measurement systems based on EIS face challenges due to complex hardware–software interactions and non-idealities. This study aims to develop an integrated co-simulation framework to support the design, debugging, and validation of EIS measurement systems devoted to the online monitoring of battery cells, helping to predict experimental results and identify/correct the non-ideality effects and sources of uncertainty. The proposed framework models both the hardware and software components of an EIS-based system to simulate and analyze the impedance measurement process as a whole. It takes into consideration the effects of physical non-idealities on the hardware–software interactions and how those affect the final impedance estimate, offering a tool to refine designs and interpret test results. For validation purposes, the proposed general framework is applied to a specific EIS-based laboratory prototype, previously designed by the research group. The framework is first used to debug the prototype by uncovering hidden non-idealities, thus refining the measurement system, and then employed as a digital model of the latter for fast development of software algorithms. Finally, the results of the co-simulation framework are compared against a theoretical model, the real prototype, and a benchtop instrument to assess the global accuracy of the framework. Full article
25 pages, 8468 KB  
Article
Robust Backstepping Super-Twisting MPPT Controller for Photovoltaic Systems Under Dynamic Shading Conditions
by Kamran Ali, Shafaat Ullah and Eliseo Clementini
Energies 2025, 18(19), 5134; https://doi.org/10.3390/en18195134 - 26 Sep 2025
Abstract
In this research article, a fast and efficient hybrid Maximum Power Point Tracking (MPPT) control technique is proposed for photovoltaic (PV) systems. The method combines two phases—offline and online—to estimate the appropriate duty cycle for operating the converter at the maximum power point [...] Read more.
In this research article, a fast and efficient hybrid Maximum Power Point Tracking (MPPT) control technique is proposed for photovoltaic (PV) systems. The method combines two phases—offline and online—to estimate the appropriate duty cycle for operating the converter at the maximum power point (MPP). In the offline phase, temperature and irradiance inputs are used to compute the real-time reference peak power voltage through an Adaptive Neuro-Fuzzy Inference System (ANFIS). This estimated reference is then utilized in the online phase, where the Robust Backstepping Super-Twisting (RBST) controller treats it as a set-point to generate the control signal and continuously adjust the converter’s duty cycle, driving the PV system to operate near the MPP. The proposed RBST control scheme offers a fast transient response, reduced rise and settling times, low tracking error, enhanced voltage stability, and quick adaptation to changing environmental conditions. The technique is tested in MATLAB/Simulink under three different scenarios: continuous variation in meteorological parameters, sudden step changes, and partial shading. To demonstrate the superiority of the RBST method, its performance is compared with classical backstepping and integral backstepping controllers. The results show that the RBST-based MPPT controller achieves the minimum rise time of 0.018s, the lowest squared error of 0.3015V, the minimum steady-state error of 0.29%, and the highest efficiency of 99.16%. Full article
(This article belongs to the Special Issue Experimental and Numerical Analysis of Photovoltaic Inverters)
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19 pages, 1373 KB  
Article
Flavonoid-Rich Extracts from Lemon and Orange By-Products: Microencapsulation and Application in Functional Cookies
by Giovanna Dellapina, Giovanna Poli, Vanna Moscatelli, Daniela Magalhães, Ana A. Vilas-Boas and Manuela Pintado
Foods 2025, 14(19), 3346; https://doi.org/10.3390/foods14193346 - 26 Sep 2025
Abstract
Citrus by-products are increasingly recognized as a valuable source of bioactive compounds (BCs), particularly flavonoids. Their incorporation into food matrices as functional ingredients aligns with sustainability goals and consumer demand for health-promoting products. However, challenges such as poor stability and undesirable sensory properties [...] Read more.
Citrus by-products are increasingly recognized as a valuable source of bioactive compounds (BCs), particularly flavonoids. Their incorporation into food matrices as functional ingredients aligns with sustainability goals and consumer demand for health-promoting products. However, challenges such as poor stability and undesirable sensory properties limit their direct use in food systems. This study aimed to develop and evaluate functional cookies enriched with microencapsulated flavonoid-rich extracts derived from lemon and orange peels. Flavonoids were extracted with hydroethanolic solvent and characterized by HPLC-DAD. The extracts exhibited high total flavonoid contents: 1960.1 mg/L for orange and 845.7 mg/L for lemon. The extracts were encapsulated using a 1% sodium alginate and 1.36% corn starch blend, producing thermally stable microbeads with flavonoid retention higher than 85% after heating at 230 °C for 30 min. These microbeads were incorporated into gluten-free oat and buckwheat cookies, delivering 166.11 mg/100 g (orange) and 177.13 mg/100 g (lemon) of flavonoids in the product, which covers approximately one-third of the recommended daily intake. Sensory analysis using triangle tests (ISO 4120) (n = 23) showed no significant difference (p > 0.05) between control and enriched cookies, indicating successful masking of potential bitterness or astringency associated with flavonoids. These results demonstrate the effectiveness of microencapsulation in protecting citrus flavonoid-rich extracts and support the development of sustainable, health-oriented bakery products. Moreover, this approach promotes the valorization of agro-industrial by-products, contributing to a more circular food supply chain. Full article
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27 pages, 2519 KB  
Article
Examining the Influence of AI on Python Programming Education: An Empirical Study and Analysis of Student Acceptance Through TAM3
by Manal Alanazi, Alice Li, Halima Samra and Ben Soh
Computers 2025, 14(10), 411; https://doi.org/10.3390/computers14100411 - 26 Sep 2025
Abstract
This study investigates the adoption of PyChatAI, a bilingual AI-powered chatbot for Python programming education, among female computer science students at Jouf University. Guided by the Technology Acceptance Model 3 (TAM3), it examines the determinants of user acceptance and usage behaviour. A Solomon [...] Read more.
This study investigates the adoption of PyChatAI, a bilingual AI-powered chatbot for Python programming education, among female computer science students at Jouf University. Guided by the Technology Acceptance Model 3 (TAM3), it examines the determinants of user acceptance and usage behaviour. A Solomon Four-Group experimental design (N = 300) was used to control pre-test effects and isolate the impact of the intervention. PyChatAI provides interactive problem-solving, code explanations, and topic-based tutorials in English and Arabic. Measurement and structural models were validated via Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM), achieving excellent fit (CFI = 0.980, RMSEA = 0.039). Results show that perceived usefulness (β = 0.446, p < 0.001) and perceived ease of use (β = 0.243, p = 0.005) significantly influence intention to use, which in turn predicts actual usage (β = 0.406, p < 0.001). Trust, facilitating conditions, and hedonic motivation emerged as strong antecedents of ease of use, while social influence and cognitive factors had limited impact. These findings demonstrate that AI-driven bilingual tools can effectively enhance programming engagement in gender-specific, culturally sensitive contexts, offering practical guidance for integrating intelligent tutoring systems into computer science curricula. Full article
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26 pages, 10082 KB  
Article
Numerical Investigation of Modified Punching Shear Behavior in Precast Prestressed Hollow Core Slabs Under Concentrated Loads
by Shadi Firouzranjbar and Arturo Schultz
Buildings 2025, 15(19), 3482; https://doi.org/10.3390/buildings15193482 - 26 Sep 2025
Abstract
Precast prestressed hollow-core slabs (HCSs), primarily designed for uniformly distributed loads, frequently encounter concentrated loads, causing complex stress states. Load distribution occurs through longitudinal joints; however, the hollow cross-section and absence of transverse reinforcement increase susceptibility to shear, including punching. Existing guidelines offer [...] Read more.
Precast prestressed hollow-core slabs (HCSs), primarily designed for uniformly distributed loads, frequently encounter concentrated loads, causing complex stress states. Load distribution occurs through longitudinal joints; however, the hollow cross-section and absence of transverse reinforcement increase susceptibility to shear, including punching. Existing guidelines offer limited guidance, often conflicting with experimental results. While limited previous studies have examined concentrated load effects on various HCS types, research on the Spancrete system—distinguished by unique core geometries—is lacking. This study presents a detailed numerical investigation of modified punching shear behavior in Spancrete HCS floors using a 3D finite element (FE) model developed in ABAQUS. The model, comprising three interconnected HCS units, was validated against experimental data from single-unit and full-scale floor tests exhibiting modified punching shear failure. Results show that modified punching shear in HCSs is driven initially by localized stress distribution in the top flange along one direction and secondarily by compression stresses in the loaded region, unlike the symmetric failure in solid slabs. While variations in loading area affected post-peak response, shifting the load closer to the longitudinal joints led to earlier joint debonding, reducing ultimate capacity. These insights challenge the adequacy of current design guidance and emphasize the necessity of refined HCS provisions. Full article
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10 pages, 808 KB  
Article
Autonomic Modulation and Symptomatic Efficacy of Transurethral Resection of the Prostate in Benign Prostatic Hyperplasia
by Kuan-Yu Chen, Yun-Sheng Chen, Min-Hsin Yang, Yu-Hui Huang and Sung-Lang Chen
Life 2025, 15(10), 1520; https://doi.org/10.3390/life15101520 - 26 Sep 2025
Abstract
Background: Benign Prostatic Hyperplasia (BPH) causes Lower Urinary Tract Symptoms (LUTS), impairing quality of life (QoL). Transurethral Resection of the Prostate (TURP) is the gold-standard surgical treatment for Bladder Outlet Obstruction (BOO), but its effects on Autonomic Nervous System (ANS) function—assessed via [...] Read more.
Background: Benign Prostatic Hyperplasia (BPH) causes Lower Urinary Tract Symptoms (LUTS), impairing quality of life (QoL). Transurethral Resection of the Prostate (TURP) is the gold-standard surgical treatment for Bladder Outlet Obstruction (BOO), but its effects on Autonomic Nervous System (ANS) function—assessed via Heart Rate Variability (HRV)—remains underexplored. To our knowledge, this is the first study to correlate HRV with specific LUTS domains pre- and post-TURP, establishing HRV as a potential biomarker for BPH management. Methods: In a prospective study, 242 men with BPH underwent TURP (2018–2024). Inclusion required age ≥ 50 years, International Prostate Symptom Score (IPSS) ≥ 8, and BOO evidence. HRV (Standard Deviation of Normal-to-Normal Intervals [SDNN], Low-Frequency/High-Frequency [LF/HF] ratio), IPSS, and QoL were assessed preoperatively and 3 months postoperatively. Paired t-tests, Pearson correlations, and multivariate regression (adjusted for age, Body Mass Index [BMI], prostate volume) were used (p < 0.05). Results: HRV (SDNN) increased from 36.97 ± 22.80 ms to 51.67 ± 27.59 ms (p = 0.032), and LF/HF ratio decreased from 1.63 ± 1.60 to 0.73 ± 0.52 (p = 0.028). IPSS fell from 18.5 ± 6.2 to 8.3 ± 4.1 (p < 0.001), with improved voiding (p = 0.004) and storage (p = 0.002) subscores. QoL improved from 3.5 ± 1.2 to 1.8 ± 0.9 (p = 0.003). HRV correlated inversely with IPSS voiding (r = −0.42, p = 0.012; r = −0.38, p = 0.019 post-TURP) and storage subscores (r = −0.29, p = 0.045). Older patients (≥65 years) and those with larger prostates (≥50 mL) showed greater improvements. Conclusions: TURP enhances LUTS, QoL, and ANS function. HRV’s correlation with LUTS suggests its biomarker potential, with possible cardiovascular benefits. Longitudinal studies are needed. Full article
(This article belongs to the Section Medical Research)
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16 pages, 6331 KB  
Article
Microstructural Analysis of Hot-Compressed Mg-Nd-Zr-Ca Alloy with Low Rare-Earth Content
by Yiquan Li, Bingchun Jiang, Rui Yang, Lei Jing and Liwei Lu
Materials 2025, 18(19), 4490; https://doi.org/10.3390/ma18194490 - 26 Sep 2025
Abstract
Microstructural analysis of hot-compressed magnesium alloys is crucial for understanding the plastic formability of magnesium alloys during thermo-mechanical processing. Thermal compression tests and finite element simulations were conducted on a low rare-earth (RE) Mg-1.8Nd-0.4Zr-0.3Ca alloy. Multiple microstructural characterization techniques were employed to analyze [...] Read more.
Microstructural analysis of hot-compressed magnesium alloys is crucial for understanding the plastic formability of magnesium alloys during thermo-mechanical processing. Thermal compression tests and finite element simulations were conducted on a low rare-earth (RE) Mg-1.8Nd-0.4Zr-0.3Ca alloy. Multiple microstructural characterization techniques were employed to analyze slip systems, twinning mechanisms, dynamic recrystallization (DRX), and precipitate phases in the hot-compressed alloy. The results demonstrated that the equivalent strain distribution within compressed specimens exhibits heterogeneity, with a larger equivalent strain in the core. After thermal compression, the original microscopic structure formed a necklace-like structure. The primary DRX mechanisms comprise continuous dynamic recrystallization (CDRX), twin-induced dynamic recrystallization (TDRX), and particle-stimulated nucleation (PSN). Pyramidal slip and recrystallization constitute primary contributors to peak texture weakening and tilting. Mg41Nd5 and α-Zr phases enhanced dislocation density by impeding dislocation motion and promoting cross-slip activation. Hot compression provided the necessary thermal activation energy and stress conditions for solute atom diffusion and clustering, triggering dynamic precipitation of Mg41Nd5 phases. Full article
(This article belongs to the Section Metals and Alloys)
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22 pages, 5564 KB  
Article
Non-Destructive and Real-Time Discrimination of Normal and Frozen-Thawed Beef Based on a Novel Deep Learning Model
by Rui Xi, Xiangyu Lyu, Jun Yang, Ping Lu, Xinxin Duan, David L. Hopkins and Yimin Zhang
Foods 2025, 14(19), 3344; https://doi.org/10.3390/foods14193344 - 26 Sep 2025
Abstract
Discrimination between normal (fresh/non-frozen) and frozen-thawed beef is crucial for ensuring food safety. This paper proposed a novel, non-destructive and real-time you only look once for normal and frozen-thawed beef discrimination (YOLO-NF) model using deep learning techniques. The simple, parameter-free attention module (SimAM) [...] Read more.
Discrimination between normal (fresh/non-frozen) and frozen-thawed beef is crucial for ensuring food safety. This paper proposed a novel, non-destructive and real-time you only look once for normal and frozen-thawed beef discrimination (YOLO-NF) model using deep learning techniques. The simple, parameter-free attention module (SimAM) and the squeeze and excitation (SE) attention mechanism were introduced to enhance the model’s performance. A total of 1200 beef samples were used, with their images captured by a charge-coupled device (CCD) camera. In the model development, specifically, the training set comprised 3888 images after data augmentation, while the validation set and test set each included 216 original images. Experimental results on the test set showed that the YOLO-NF model achieved precision, recall, F1-Score and mean average precision (mAP) of 95.5%, 95.2%, 95.3% and 98.6%, respectively, significantly outperforming YOLOv7, YOLOv5 and YOLOv8 models. Additionally, gradient-weighted class activation mapping (Grad-CAM) was adopted to interpret the model’s decision basis. Moreover, the model was deployed on the web interface for user convenience, and the discrimination time on the local server was 0.94 s per image, satisfying the requirements for real-time processing. This study provides a promising technique for high-performance and rapid meat quality assessment in food safety monitoring systems. Full article
(This article belongs to the Section Food Engineering and Technology)
16 pages, 3204 KB  
Article
Emissivity Measurements of Metals Used in Wire-Arc-Directed Energy Deposition Processes
by Kevin Mullaney and Ralph P. Tatam
Metals 2025, 15(10), 1078; https://doi.org/10.3390/met15101078 - 26 Sep 2025
Abstract
Accurate temperature measurement is a key parameter that determines the quality of additive manufactured components in directed energy deposition processes. Optical pyrometers which are used to provide in-process temperature data require accurate emissivity data of the metal surface. Process-specific emissivity data for metals [...] Read more.
Accurate temperature measurement is a key parameter that determines the quality of additive manufactured components in directed energy deposition processes. Optical pyrometers which are used to provide in-process temperature data require accurate emissivity data of the metal surface. Process-specific emissivity data for metals used in these processes is not readily available. This paper provides the emissivity of a variety of metals used in wire-arc directed energy deposition processes. For the first time, the test samples were fabricated using typical deposition processes and systems. The metals evaluated were titanium alloy (Ti-6Al-4V), Inconel 718, mild steel, aluminum alloy 2319, and nickel aluminum bronze. At ambient temperature, the measured normal emissivity was 0.26–0.28 for Ti-6Al-4V; for Inconel 718, it was 0.45–0.54; for mild steel, it was 0.4–0.72; for aluminum 2319, it was 0.14; and for nickel aluminum bronze, it was 0.35. The approximate emissivity values are also given over the temperature range 20–1400 °C. The effect of residual oxygen in the shield gas on emissivity is explored for the first time. The spectrophotometric technique was used to measure the metal thermo-optical properties. Full article
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19 pages, 1923 KB  
Article
Folate-Functionalized ROS-Scavenging Covalent Organic Framework for Oral Targeted Delivery of Ferulic Acid in Ulcerative Colitis
by Jin Xue, Zifan Qiao, Shiyu Huang, Mubarak G. Bello and Lihua Chen
Pharmaceutics 2025, 17(10), 1263; https://doi.org/10.3390/pharmaceutics17101263 - 26 Sep 2025
Abstract
Background/Objectives: Ulcerative colitis (UC) involves chronic colon inflammation and oxidative stress. Treating UC is challenging due to systemic drug side effects and poor targeted delivery. Nanocarriers responsive to the UC microenvironment, particularly elevated reactive oxygen species (ROS), could overcome these limitations. This study [...] Read more.
Background/Objectives: Ulcerative colitis (UC) involves chronic colon inflammation and oxidative stress. Treating UC is challenging due to systemic drug side effects and poor targeted delivery. Nanocarriers responsive to the UC microenvironment, particularly elevated reactive oxygen species (ROS), could overcome these limitations. This study developed an oral delivery system for ROS-triggered drug release and active targeting. Using ferulic acid (FER), a system was designed to enhance site-specific accumulation and therapeutic efficacy against colitis. Methods: A ROS-sensitive covalent organic framework (COF) was synthesized from γ-cyclodextrin and functionalized with folic acid (FA) to create a carrier (COF-FA) designed for potential active targeting. This carrier was loaded with FER to form FER@COF-FA. The system was characterized (SEM, FTIR, TGA), and its ROS scavenging and sustained drug release profiles were confirmed in vitro. Biocompatibility was evaluated in cell lines, and therapeutic efficacy was tested in a DSS-induced murine colitis model. Results: The synthesized FER@COF-FA demonstrated high drug loading, potent ROS-scavenging capability, and a sustained drug release profile. It showed excellent biocompatibility and, in the murine model, significantly outperformed free FER. Treatment alleviated disease severity, prevented colon shortening, restored healthy tissue histology, and rebalanced pro- and anti-inflammatory cytokines. Conclusions: The FER@COF-FA system represents a highly promising therapeutic strategy for UC. Its superior efficacy is attributed to a synergistic multi-mechanism approach, combining sustained release, ROS-responsive drug delivery, intrinsic antioxidant activity, and potential folate receptor-mediated targeting, which collectively enhance site-specific accumulation and therapeutic outcomes in the inflammatory colon microenvironment. Full article
(This article belongs to the Section Drug Delivery and Controlled Release)
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