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14 pages, 2015 KB

Open AccessArticle

Dark Septate Endophytic Fungi Improve Dry Matter Production and Fruit Yield in Ever-Bearing Strawberry (Fragaria × ananassa Duch.) Under High Temperatures

by Nanako Aomura, Ryuta Ninohei, Mana Noguchi, Midori Sakoda, Eiichi Inoue, Kazuhiko Narisawa and Yuya Mochizuki

Plants 2026, 15(1), 129; https://doi.org/10.3390/plants15010129 (registering DOI) - 2 Jan 2026

Abstract

In Japan, strawberries are produced in the off-season (June to November) in cool regions; however, the high temperatures and strong sunlight limit fruit production. Dark septate endophytic fungi (DSEs) support growth and flower bud formation of plants grown in environments unsuitable for plant [...] Read more.

In Japan, strawberries are produced in the off-season (June to November) in cool regions; however, the high temperatures and strong sunlight limit fruit production. Dark septate endophytic fungi (DSEs) support growth and flower bud formation of plants grown in environments unsuitable for plant growth. In this study, we investigated the effects of DSE on dry matter production and flower bud formation in strawberry plants grown in the summer and autumn. The seeds were sown in soil mixed with DSE on 5 February 2024. The DSEs used were Cladophialophora chaetospira SK51 (S) and Cc. MNB12 (M), and Veronaeopsis simplex Y34 (Y). Plants were planted in a plastic house on April 18. The total dry weight was significantly increased by DSEs. This is because S and Y-cultured plants did not show a significant decrease in leaf emergence under high temperatures, unlike those grown with M; however, its leaf area was larger than that of the control. This resulted in a larger leaf area for receiving light and higher cumulative light reception and light-use efficiency. Although the DSEs increased cumulative fruit yield, the harvest period was limited to July because of the extreme summer heat. In addition, there was no difference in the budding date or flowering date between the treatments. These results suggest that DSEs improve light use efficiency, thereby increasing total dry matter weight and contributing to increased fruit yield in summer-autumn cultivation. Full article

(This article belongs to the Special Issue Horticultural Plant Cultivation in the Climate Change Era: From Genotypes to Environment)

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31 pages, 1263 KB

Open AccessArticle

CASA in Action: Dual Trust Pathways from Technical–Social Features of AI Agents to Users’ Active Engagement Through Cognitive–Emotional Trust

by Qinbo Xue, Magdalena Dzitkowska-Zabielska, Liguo Wang and Jiaolong Xue

J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 11; https://doi.org/10.3390/jtaer21010011 (registering DOI) - 2 Jan 2026

Abstract

As artificial intelligence (AI) agents become deeply integrated into fitness systems, trustworthy human–AI agent interaction has become pivotal for user engagement in smart home fitness (SHF) e-commerce platforms. Grounded in the Computers Are Social Actors (CASA) framework, this study empirically investigates how, acting [...] Read more.

As artificial intelligence (AI) agents become deeply integrated into fitness systems, trustworthy human–AI agent interaction has become pivotal for user engagement in smart home fitness (SHF) e-commerce platforms. Grounded in the Computers Are Social Actors (CASA) framework, this study empirically investigates how, acting as AI fitness coaches, AI agents’ technical and social features shape users’ active engagement in the in-home social e-commerce context. A mixed-method approach was employed, combining computational text mining of 17,582 user reviews from fitness e-commerce platforms with a survey (N = 599) of Chinese consumers. The results show that (1) the technical–social features of AI agents serving as AI fitness coaches include visibility, gamification, interactivity, humanness, and sociability; (2) these five technical–social features of AI agents positively influence user compliance via both cognitive and emotional trust in AI agents; (3) these five technical–social features of AI agents serving as AI fitness coaches positively impact active engagement via both cognitive and emotional trust in AI agents. This study extends the CASA framework to the domain of AI coaching by demonstrating the parallel roles of cognitive and emotional trust in AI agents. For designers and managers in the fitness e-commerce industries, this study offers actionable insights for designing AI agents integrating functional and social features that foster trust and drive behavioral outcomes. Full article

(This article belongs to the Topic Innovations in New Media: Shaping the Future of Interactive Marketing)

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30 pages, 4494 KB

Open AccessArticle

An Uncertainty-Aware Bayesian Deep Learning Method for Automatic Identification and Capacitance Estimation of Compensation Capacitors

by Tongdian Wang and Pan Wang

Sensors 2026, 26(1), 279; https://doi.org/10.3390/s26010279 (registering DOI) - 2 Jan 2026

Abstract

This paper addresses the challenges of misclassification and reliability assessment in compensation capacitor detection under strong noise in high-speed railway track circuits. A hierarchical Bayesian deep learning framework is proposed, integrating multi-domain signal enhancement in the time, frequency, and time–frequency (TF) domains with [...] Read more.

This paper addresses the challenges of misclassification and reliability assessment in compensation capacitor detection under strong noise in high-speed railway track circuits. A hierarchical Bayesian deep learning framework is proposed, integrating multi-domain signal enhancement in the time, frequency, and time–frequency (TF) domains with bidirectional long short-term memory (BiLSTM) sequence modeling for robust feature extraction. Bayesian classification and regression based on Monte Carlo (MC) Dropout and stochastic weight averaging Gaussian (SWAG) enable posterior inference, confidence interval estimation, and uncertainty-aware prediction, while a rejection mechanism filters low-confidence outputs. Experiments on 8782 real-world segments from five railway lines show that the proposed method achieves 97.8% state-recognition accuracy, a mean absolute error of 0.084 μF, and an R² of 0.96. It further outperforms threshold-based, convolutional neural network (CNN), and standard BiLSTM models in negative log-likelihood (NLL), expected calibration error (ECE), and overall calibration quality, approaching the theoretical 95% interval coverage. The framework substantially improves robustness, accuracy, and reliability, providing a viable solution for intelligent monitoring and safety assurance of compensation capacitors in track circuits. Full article

(This article belongs to the Special Issue Artificial Intelligence of Things for Future Networks and Service Management)

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13 pages, 2151 KB

Open AccessFeature PaperArticle

Infrared Thermal Imaging as a Predictor of Lumbar Paravertebral Block Effectiveness in Cattle

by Jaime Viscasillas, Elsa Rave, Ariel Cañón-Pérez, María De Los Reyes Marti-Scharfhausen, Eva Zoe Hernández-Magaña, Agustín Martínez, José Ignacio Redondo and Angel García-Muñoz

Animals 2026, 16(1), 127; https://doi.org/10.3390/ani16010127 (registering DOI) - 2 Jan 2026

Abstract

In the daily clinical practice of cattle, the use of locoregional anaesthesia is needed to provide analgesia during standing surgical procedures. It is important to ensure the success of the blockade before starting the surgery. One of the most used techniques is the [...] Read more.

In the daily clinical practice of cattle, the use of locoregional anaesthesia is needed to provide analgesia during standing surgical procedures. It is important to ensure the success of the blockade before starting the surgery. One of the most used techniques is the paravertebral lumbar block. In this pilot study we evaluated the efficacy of thermography in assessing this block. For this matter, 12 cows from our university research and teaching farm, with similar characteristics, were included and in which an ultrasound-guided technique of lumbar paravertebral block (T₁₃/L₁) or (L₁/L₂) with lidocaine was performed. Thermal photographs were taken with a FLIR^® One camera at 0, 15, 30 and 45 min and at the same time a test to evaluate the response to a painful stimulus was performed in each dermatome (T₁₃, L₁, L₂ and L₃). The data was collected in predesigned cards and placed in the Excel programme for further statistical analysis with the R programme. The analysis determined a correlation between the increase in skin temperature of the dermatomes that had been blocked and the increase in skin temperature and the negative response to the painful stimulus test. Although the pilot study has some limitations, this allows us to assess the use of thermography as an efficient method for assessing the success of lumbar paravertebral blockade in cattle. Full article

(This article belongs to the Special Issue Anaesthesia and Pain Management in Large Animals—Second Edition)

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28 pages, 1056 KB

Open AccessArticle

Resilience or Mirage? Deconstructing the Economic Recovery and Labor Market Structural Lag in Macao’s Tourism Sector

by Jingwen Cai, Chunning Wang, Haoqian Hu, Wai In Ho, Ka Ip Chan and Yifen Yin

Tour. Hosp. 2026, 7(1), 10; https://doi.org/10.3390/tourhosp7010010 (registering DOI) - 2 Jan 2026

Abstract

This study investigates the deep-seated impacts of the COVID-19 pandemic on Macao, a mono-economy extremely dependent on the single factor of “tourism mobility”. We investigate a counter-intuitive phenomenon observed during the 2020–2022 shock: the Herfindahl–Hirschman Index (HHI) declined significantly, suggesting “apparent diversification”. Using [...] Read more.

This study investigates the deep-seated impacts of the COVID-19 pandemic on Macao, a mono-economy extremely dependent on the single factor of “tourism mobility”. We investigate a counter-intuitive phenomenon observed during the 2020–2022 shock: the Herfindahl–Hirschman Index (HHI) declined significantly, suggesting “apparent diversification”. Using counterfactual simulations and a Two-Way Fixed Effects (TWFE) model, we quantitatively deconstruct this “resilience illusion”. The results confirm that the decline in the HHI was driven entirely by the “denominator effect” triggered by the collapse of the dominant industry’s (gaming) GVA; if the impact of this recession is excluded, the Counterfactual HHI was even higher than pre-pandemic levels, indicating that the structure did not undergo substantive optimization. Furthermore, inferential statistical tests confirmed the existence of significant “structural lag” in the labor market. This study further reveals a dual divergence mechanism based on “skill specificity”: in sectors with high skill universality (e.g., transport and catering), a structural shift toward “workforce casualization” occurred, manifested by a significant decline in the full-time ratio; conversely, in sectors with strong skill specificity (e.g., gaming and hospitality), firms tended toward “labor hoarding”. This study exposes the macro-indicator trap faced by tourism mono-economies under extreme shocks and provides new micro-evidence for understanding the heterogeneous scars in the service labor market. Full article

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30 pages, 440 KB

Open AccessArticle

Fraud Risk and Audit Opinions Across Countries: Complementing Accounting-Based Fraud Risk with Machine Learning Methods

by Prawat Benyasrisawat and Nadharatch Ounlert

J. Risk Financial Manag. 2026, 19(1), 26; https://doi.org/10.3390/jrfm19010026 (registering DOI) - 2 Jan 2026

Abstract

Financial statement fraud is a significant threat to corporate governance, investor confidence, and global capital markets. Traditional fraud detection models, including DF-Score and PF-Score, often rely on linear approaches that may fail to capture complex fraudulent behaviors. This study applies machine learning techniques [...] Read more.

Financial statement fraud is a significant threat to corporate governance, investor confidence, and global capital markets. Traditional fraud detection models, including DF-Score and PF-Score, often rely on linear approaches that may fail to capture complex fraudulent behaviors. This study applies machine learning techniques using eXtreme Gradient Boosting across 34 countries (2016–2024). Results show that enhanced DF-Score and PF-Score effectively capture fraud risk, which is significantly associated with auditors’ opinions. The study integrates machine learning with traditional models to address data complexity and nonlinearity. Practically, the findings provide auditors, regulators, and financial analysts with a tool for improved fraud detection and risk-based auditing. Full article

(This article belongs to the Section Financial Technology and Innovation)

19 pages, 3988 KB

Open AccessArticle

Fuel Cell Micro-CHP: Analysis of Hydrogen Solid Storage and Artificial Photosynthesis Hydrogen Production

by Saad Fahim, Taoufiq Kaoutari, Guillaume Foin and Hasna Louahlia

Hydrogen 2026, 7(1), 5; https://doi.org/10.3390/hydrogen7010005 (registering DOI) - 2 Jan 2026

Abstract

This paper investigates three distinct hydrogen-related subsystems: production, storage, and the use. An analysis of the micro-combined heat and power production (mCHP) behavior using natural gas is conducted to understand how the system operates under different conditions and to evaluate its yearly performance. [...] Read more.

This paper investigates three distinct hydrogen-related subsystems: production, storage, and the use. An analysis of the micro-combined heat and power production (mCHP) behavior using natural gas is conducted to understand how the system operates under different conditions and to evaluate its yearly performance. To reduce CO₂ emissions, hydrogen fuel consumption is proposed, and an emission analysis under different fuel-supply configurations is performed. The results show that hydrogen produced by artificial photosynthesis has the lowest CO₂ impact. Therefore, the paper examines this process and its main characteristics. An engineering model is proposed to rapidly estimate the mean volumetric hydrogen production rate. To ensure safe coupling between hydrogen production and mCHP demand, the study then focuses on solid-state hydrogen storage. Subsequently, in this framework, the state of charge (SOC) is defined as the central control variable linking storage thermodynamics to hydrogen delivery. Accurate SOC estimation ensures that the storage unit can supply the required hydrogen flow without causing starvation, pressure drops, or thermal drift during CHP operation. The proposed SOC estimation method is based on an analytical approach and experimentally validated while relying solely on external measurements. The overall objective is to enable a coherent, low-carbon, and safely controllable hydrogen-based mCHP system. Full article

(This article belongs to the Topic Advances in Hydrogen Energy)

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24 pages, 766 KB

Open AccessSystematic Review

Artificial Intelligence-Based Automated Analysis for Pleural Effusion Detection on Thoracic Ultrasound: A Systematic Review

by Guido Marchi, Luciano Gabbrielli, Marco Gherardi, Massimiliano Serradori, Francesco Baglivo, Salvatore Claudio Fanni, Jacopo Cefalo, Carmine Salerni, Giacomo Guglielmi, Francesco Pistelli, Laura Carrozzi and Michele Mondoni

Diagnostics 2026, 16(1), 147; https://doi.org/10.3390/diagnostics16010147 (registering DOI) - 2 Jan 2026

Abstract

Background: Pleural effusion (PE) is a common condition where accurate detection is essential for management. Thoracic ultrasound (TUS) is the first-line modality owing to safety, portability, and high sensitivity, but accuracy is operator-dependent. Artificial intelligence (AI)-based automated analysis has been explored as [...] Read more.

Background: Pleural effusion (PE) is a common condition where accurate detection is essential for management. Thoracic ultrasound (TUS) is the first-line modality owing to safety, portability, and high sensitivity, but accuracy is operator-dependent. Artificial intelligence (AI)-based automated analysis has been explored as an adjunct, with early evidence suggesting potential to reduce variability and standardise interpretation. This review evaluates the diagnostic accuracy of AI-assisted TUS for PE detection. Methods: This review was registered with PROSPERO (CRD420251128416) and followed PRISMA guidelines. MEDLINE, Scopus, Google Scholar, IEEE Xplore, Cochrane CENTRAL, and ClinicalTrials.gov were searched through 20 August 2025 for studies assessing AI-based TUS analysis for PE. Eligible studies required recognised reference standards (expert interpretation or chest CT). Risk of bias was assessed with QUADAS-2, and certainty with GRADE. Owing to heterogeneity, structured narrative synthesis was performed instead of meta-analysis. Results: Five studies (7565 patients) published between 2021–2025 were included. All used convolutional neural networks with varied architectures (ResNet, EfficientNet, U-net). Sensitivity ranged 70.6–100%, specificity 67–100%, and AUC 0.77–0.99. Performance was reduced for small, trace, or complex effusions and in critically ill patients. External validation showed attenuation compared with internal testing. All studies had high risk of bias in patient selection and index test conduct, reflecting retrospective designs and inadequate dataset separation. Conclusions: AI-assisted TUS shows promising diagnostic performance for PE detection in curated datasets; however, evidence is inconsistent and limited by key methodological weaknesses. Overall certainty is low-to-moderate, constrained by retrospective designs, limited dataset separation, and scarce external validation. Current evidence is insufficient to support routine clinical use. Robust prospective multicentre studies with rigorous independent validation and evaluation of clinically meaningful outcomes are essential before clinical implementation can be considered. Full article

(This article belongs to the Special Issue Diagnostic Imaging of Pulmonary Diseases)

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16 pages, 937 KB

Open AccessReview

The Dawn of Precision Medicine in Pediatric Nephrology: Lumasiran and the Era of siRNA Therapies for Primary Hyperoxaluria Type 1

by John Dotis and Maria Fourikou

J. Pers. Med. 2026, 16(1), 15; https://doi.org/10.3390/jpm16010015 (registering DOI) - 2 Jan 2026

Abstract

Primary hyperoxaluria type 1 (PH1) is a rare autosomal recessive disorder that causes progressive renal failure, nephrolithiasis, and nephrocalcinosis in children. It is characterized by hepatic overproduction of oxalate. Conventional management, which involves combined liver–kidney transplantation, vitamin B6 supplementation, and intense hydration, does [...] Read more.

Primary hyperoxaluria type 1 (PH1) is a rare autosomal recessive disorder that causes progressive renal failure, nephrolithiasis, and nephrocalcinosis in children. It is characterized by hepatic overproduction of oxalate. Conventional management, which involves combined liver–kidney transplantation, vitamin B6 supplementation, and intense hydration, does not address the underlying metabolic defect for most patients and it generally provides only supportive care. The first approved disease-modifying treatment for pediatric PH1 is Lumasiran, a small interfering RNA (siRNA) therapeutic. By specifically inhibiting the hepatic glycolate oxidase mRNA, Lumasiran lowers the production of oxalate at its origin. Along with fewer kidney stone events and stabilization of nephrocalcinosis, clinical trials (ILLUMINATE-A/B/C) showed significant decreases in urinary oxalate excretion. The most frequently reported adverse event is mild injection-site reactions, which are generally well tolerated. The molecular mechanism, pharmacokinetics, and clinical effectiveness of Lumasiran in children with PH1 are compiled in this review. We go over possible long-term safety concerns, the impact of early intervention on renal outcomes, and the function of siRNA therapies in pediatric precision medicine. Furthermore, we highlight Lumasiran’s importance as a model for targeted treatment in uncommon pediatric kidney diseases by considering it in the larger context of RNAi-based therapies. A paradigm shift in pediatric nephrology is signaled by Lumasiran, which changes the therapeutic approach from supportive care to precision, targeted medicine. Further research and empirical data will clarify its long-term advantages, the best ways to treat it, and the possible use of siRNA technologies for other genetic renal disorders. Full article

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17 pages, 1904 KB

Open AccessArticle

Polymer Crosslinked Activated Carbon Pellets for Dye Adsorption

by Muhammad Hadi and Sungho Yoon

Materials 2026, 19(1), 155; https://doi.org/10.3390/ma19010155 (registering DOI) - 2 Jan 2026

Abstract

The use of activated carbon (AC) in environmental applications, particularly for water and air purification, is highly valued due to its excellent microstructural and adsorption properties. However, its powdered form presents significant challenges in industrial applications, such as difficulty in handling and potential [...] Read more.

The use of activated carbon (AC) in environmental applications, particularly for water and air purification, is highly valued due to its excellent microstructural and adsorption properties. However, its powdered form presents significant challenges in industrial applications, such as difficulty in handling and potential environmental risks due to its tendency to disperse easily. To overcome these issues, converting activated carbon into a more industrially viable form, such as pellets, is crucial. In this study, pelletizing AC within a crosslinked polyvinyl alcohol–diglycidyl ether of bisphenol A (PVA–DGEBA) matrix enabled the production of structurally stable cylindrical pellets through the formation of a robust three-dimensional polymeric network. This approach required minimal binder usage and facilitated processing at relatively low temperatures, effectively overcoming common disintegration issues associated with traditional pelletization methods reliant on linear polymer binders and compression-based techniques. The resulting pellets exhibited methylene blue (MB) adsorption (q max ~14.8 mg/g of pellet), which is about 50% of the initial AC’s adsorption capability, and retained structural integrity across multiple aqueous cycles. They also remained stable in methanol, ethanol and acetone by showing no observable disintegration, which highlights their excellent stability. Comprehensive characterizations, including hardness tests, swelling behavior, and various structural evaluations, revealed a mechanical strength of 3.37 ± 0.46 MPa and an adsorption volume of ~250 cm³/g through Brunauer–Emmett–Teller analysis, confirming effective crosslinking and the adsorption capabilities of the pellets. This eco-friendly and stable pelletization strategy demonstrated great potential for low-temperature pelletizing of AC, ensuring advanced applications in wastewater treatment even under pressurized conditions, presenting a significant improvement over the traditional method. Full article

(This article belongs to the Special Issue Novel Materials for Advanced Water and Wastewater Treatment and Environmental Health Protection)

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31 pages, 1891 KB

Open AccessArticle

Refugee Housing Access Through Urban Studies and Strategic Digital City Context

by NourAllah Al Lahham, Denis Alcides Rezende, Giovana Goretti Feijó Almeida and Godswill Udoh Okon

Urban Sci. 2026, 10(1), 24; https://doi.org/10.3390/urbansci10010024 (registering DOI) - 2 Jan 2026

Abstract

The current refugee crisis has revealed flaws in existing systems. Factors such as socioeconomic background, access to housing, and urban policies influence refugees’ abilities to fully participate in city life. The research objective is to analyze the interplay between housing access for adult [...] Read more.

The current refugee crisis has revealed flaws in existing systems. Factors such as socioeconomic background, access to housing, and urban policies influence refugees’ abilities to fully participate in city life. The research objective is to analyze the interplay between housing access for adult refugees residing in Curitiba, Brazil, and the city’s targeted public policies and strategies for refugees. The research methodology adopts a case study approach centered on Curitiba, Brazil, with the city shown as a key destination for refugees in Brazil. This study combines qualitative and quantitative techniques, following a structured research protocol that guides the processes of data collection and analysis. The innovation and originality lie in offering a new perspective on how urban strategies intersect with the rights and inclusion of refugees, exploring the relationship between refugees’ housing access and its interconnection with the strategic digital city framework. The results highlight the importance of a multifaceted approach to addressing housing access challenges for refugees, which includes safeguarding their rights, promoting stability, integration, and ensuring their participation in shaping public policies. The conclusion outlines the urgent need to promote integration by reassessing housing affordability, ensuring access to services, engaging refugees in decision-making processes, and improving their social welfare. Full article

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11 pages, 1725 KB

Open AccessArticle

Tool Wear Detection in Milling Using Convolutional Neural Networks and Audible Sound Signals

by Halil Ibrahim Turan and Ali Mamedov

Machines 2026, 14(1), 59; https://doi.org/10.3390/machines14010059 (registering DOI) - 2 Jan 2026

Abstract

Timely tool wear detection has been an important target for the metal cutting industry for decades because of its significance for part quality and production cost control. With the shift toward intelligent and sustainable manufacturing, reliable tool-condition monitoring has become even more critical. [...] Read more.

Timely tool wear detection has been an important target for the metal cutting industry for decades because of its significance for part quality and production cost control. With the shift toward intelligent and sustainable manufacturing, reliable tool-condition monitoring has become even more critical. One of the main challenges in sound-based tool wear monitoring is the presence of noise interference, instability and the highly volatile nature of machining acoustics, which complicates the extraction of meaningful features. In this study, a Convolutional Neural Network (CNN) model is proposed to classify tool wear conditions in milling operations using acoustic signals. Sound recordings were collected from tools at different wear stages under two cutting speeds, and Mel-Frequency Cepstral Coefficients (MFCCs) were extracted to obtain a compact representation of the short-term power spectrum. These MFCC matrices enabled the CNN to learn discriminative spectral patterns associated with wear. To evaluate model stability and reduce the effects of algorithmic randomness, training was repeated three times for each cutting speed. For the 520 rpm dataset, the model achieved an average validation accuracy of 96.85 ± 2.07%, while for the 635 rpm dataset it achieved 93.69 ± 2.07%. The results demonstrate the feasibility of using acoustic signals, despite inherent noise challenges, as a complementary approach for identifying suitable tool replacement intervals in milling. Full article

(This article belongs to the Special Issue Intelligent Tool Wear Monitoring)

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21 pages, 2963 KB

Open AccessArticle

Effect of Ultrasonic-Assisted Extraction on the Structural and Physiological Activity of Jackfruit Polysaccharides

by Jinmei Hu, Zongcheng Luo, Fengzhen You, Donghui Luo, Fengchuan Ma, Zhongsheng Tang and Siming Zhu

Foods 2026, 15(1), 132; https://doi.org/10.3390/foods15010132 (registering DOI) - 2 Jan 2026

Abstract

This study aimed to investigate the effects of ultrasound-assisted extraction (UAE) on the physicochemical properties, biological activities, and intestinal flora regulatory capacity of jackfruit polysaccharides (JPs). Under optimized UAE conditions (liquid-to-solid ratio 30 mL/g, extraction time 30 min, power 90 W), the yield [...] Read more.

This study aimed to investigate the effects of ultrasound-assisted extraction (UAE) on the physicochemical properties, biological activities, and intestinal flora regulatory capacity of jackfruit polysaccharides (JPs). Under optimized UAE conditions (liquid-to-solid ratio 30 mL/g, extraction time 30 min, power 90 W), the yield of JP reached 8.70 ± 0.11%. Compared with hot-water-extracted jackfruit polysaccharides (HAE-JPs), ultrasonic-assisted extracted jackfruit polysaccharides (UAE-JPs) exhibited a lower molecular weight, a smaller particle size, and a significant 11.5-fold increase in galacturonic acid content. Structural analyses confirmed that UAE-JPs retained a triple-helix and highly branched conformation but with enhanced exposure of acidic monosaccharides. These structural modifications contributed to superior antioxidant activity and enzyme inhibition ability, demonstrated by its lower IC₅₀ values against DPPH, ABTS radicals, and α-glucosidase. Crucially, in vitro fecal fermentation revealed that UAE-JPs and HAE-JPs differentially modulated the gut microbiota. UAE-JPs preferentially promoted the proliferation of Lactobacillus (an increase of 27.04%) and Bifidobacterium, facilitating short-term acidification. In contrast, HAE-JPs enriched butyrate-producing bacteria like Clostridium (increase of 18.56%). Both polysaccharides significantly inhibited the growth of Fusobacterium (a decrease of 5.23%) related to cancer. Consequently, this study establishes UAE as a green and efficient technique capable of not only modifying the structure of JPs but also precisely tailoring their prebiotic functionality, which ultimately demonstrates the potential of UAE-JPs as a functional food ingredient with enhanced bioactivity. Full article

(This article belongs to the Special Issue The Extraction, Structure and Bioactivities of Plant Polysaccharides)

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37 pages, 2575 KB

Open AccessReview

A Review of High-Throughput Optical Sensors for Food Detection Based on Machine Learning

by Yuzhen Wang, Yuchen Yang and Huilin Liu

Foods 2026, 15(1), 133; https://doi.org/10.3390/foods15010133 (registering DOI) - 2 Jan 2026

Abstract

As the global food industry expands and consumers demand higher food safety and quality standards, high-throughput detection technology utilizing digital intelligent optical sensors has emerged as a research hotspot in food testing due to its advantages of speed, precision, and non-destructive operation. Integrating [...] Read more.

As the global food industry expands and consumers demand higher food safety and quality standards, high-throughput detection technology utilizing digital intelligent optical sensors has emerged as a research hotspot in food testing due to its advantages of speed, precision, and non-destructive operation. Integrating cutting-edge achievements in optics, electronics, and computer science with machine learning algorithms, this technology efficiently processes massive datasets. This paper systematically summarizes the construction principles of intelligent optical sensors and their applications in food inspection. Sensors convert light signals into electrical signals using nanomaterials such as quantum dots, metal nanoparticles, and upconversion nanoparticles, and then employ machine learning algorithms including support vector machines, random forests, and convolutional neural networks for data analysis and model optimization. This enables efficient detection of target substances like pesticide residues, heavy metals, microorganisms, and food freshness. Furthermore, the integration of multiple detection mechanisms—including spectral analysis, fluorescence imaging, and hyperspectral imaging—has significantly broadened the sensors’ application scenarios. Looking ahead, optical sensors will evolve toward multifunctional integration, miniaturization, and intelligent operation. By leveraging cloud computing and IoT technologies, they will deliver innovative solutions for comprehensive monitoring of food quality and safety across the entire supply chain. Full article

(This article belongs to the Special Issue Advances in AI for the Quality Assessment of Agri-Food Products)

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21 pages, 19614 KB

Open AccessArticle

Hydrothermal–Membrane Valorization of Coffee Pulp for Xylooligosaccharide Production

by James Villar, Iris Paola Roncal Huaman, Delicia L. Bazán, Ruly Teran Hilares and Rita de Cássia Lacerda Brambilla Rodrigues

Processes 2026, 14(1), 153; https://doi.org/10.3390/pr14010153 (registering DOI) - 2 Jan 2026

Abstract

Wet coffee pulp residues (WCPRs) are typically underutilized, and their accumulation increases alongside coffee production, generating significant environmental impacts. This study proposes a sustainable valorization approach through hydrothermal treatment followed by membrane filtration for the production of xylooligosaccharides (XOSs). Extractive-free WCPR contained 35.4% [...] Read more.

Wet coffee pulp residues (WCPRs) are typically underutilized, and their accumulation increases alongside coffee production, generating significant environmental impacts. This study proposes a sustainable valorization approach through hydrothermal treatment followed by membrane filtration for the production of xylooligosaccharides (XOSs). Extractive-free WCPR contained 35.4% structural carbohydrates (20.4% cellulose and 15.0% hemicellulose) and 27.0% lignin. Hydrothermal treatments (180 °C, 3 °C min⁻¹, 15–60 min) were performed with and without citric acid as an organic catalyst. The acid-assisted treatment (T4) enhanced hemicellulose depolymerization and xylose release (16 g·kg⁻¹ dry biomass), whereas milder, non-acidic conditions (T3) promoted the selective formation and recovery of short-chain XOS, reaching cumulative biomass-normalized yields of up to 14 g·kg⁻¹ of xylobiose (X2) and 9 g·kg⁻¹ of xylotriose (X3). Subsequent membrane processing (UF–DF–NF) enabled progressive purification and enrichment of XOS fractions. Diafiltration was identified as the main step governing XOS enrichment, whereas nanofiltration primarily refined separation by directing monomeric sugars to the permeate rather than substantially increasing XOS yields. Additionally, Multiple Factor Analysis (MFA) integrated process and compositional variables, explaining 79.6% of the total variance. Dimension 1 represented process intensity and xylose transport, while Dimension 2 reflected molecular-weight-driven XOS fractionation. The acid-assisted process (T4) exhibited a distinct multivariate signature, characterized by enhanced carbohydrate mobilization and improved XOS recovery with reduced dependence on dilution. Overall, coupling hydrothermal pretreatment with membrane fractionation proved to be an efficient, and environmentally friendly strategy for coffee by-product valorization, consistent with hemicellulose-first biorefinery models and the principles of the circular bioeconomy. Full article

(This article belongs to the Special Issue Advances in Green Extraction and Separation Processes)

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22 pages, 1632 KB

Open AccessFeature PaperArticle

Selective Ruthenium-Catalysed Functionalisation Reactions and ROMP of exo-Norbornene-Based Organosilicon Boronic Esters

by Jerzy Garbarek and Mariusz Majchrzak

Catalysts 2026, 16(1), 45; https://doi.org/10.3390/catal16010045 (registering DOI) - 2 Jan 2026

Abstract

The ruthenium-catalysed silylative coupling (SC) reaction is a useful method for obtaining selectively functionalised organosilicon compounds, which have a wide range of applications in organometallic and organic chemistry. It is possible to prepare such compounds with norbornene matrices, which can be used for [...] Read more.

The ruthenium-catalysed silylative coupling (SC) reaction is a useful method for obtaining selectively functionalised organosilicon compounds, which have a wide range of applications in organometallic and organic chemistry. It is possible to prepare such compounds with norbornene matrices, which can be used for ring-opening metathesis polymerisation (ROMP) in the synthesis of linear-type polymers. Herein, we present a method for the synthesis of the aforementioned matrices by a condensation reaction between diol and vinylphenylboronic acids. Furthermore, these compounds were subsequently modified by SC reaction and polymerised by ROMP. To assess the possibility of using styryl-based silyl-derived monomers as building blocks in further organic transformations, the process of bromodesilylation was also investigated. We would also like to perform a comparative study on the selectivity of hydrosilylation and silylative coupling processes in the case of discovered materials. Full article

(This article belongs to the Special Issue New Development of Catalysts for Organometallic Chemistry)

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15 pages, 16374 KB

Open AccessArticle

Achieving High Strength and Low Yield Ratio via Direct Quenching and Aging in Cu-Precipitation-Strengthened Steel

by Xinghao Wei, Youjing Zhang, Yajie Wen, Chaofei Yang, Xinghua Wang, Jiajia Niu and Renfu Wang

Nanomaterials 2026, 16(1), 66; https://doi.org/10.3390/nano16010066 (registering DOI) - 2 Jan 2026

Abstract

The high yield ratio remains a critical challenge restricting the widespread application of ultra-high-strength steels. This study investigates a direct quenching and aging (DQA) route without solution treatment in a Cu-precipitation-strengthened steel, aiming to achieve high strength combined with a low yield ratio, [...] Read more.

The high yield ratio remains a critical challenge restricting the widespread application of ultra-high-strength steels. This study investigates a direct quenching and aging (DQA) route without solution treatment in a Cu-precipitation-strengthened steel, aiming to achieve high strength combined with a low yield ratio, and compares it with the conventional solution treatment plus aging (SQA) process. The DQA sample exhibits an excellent yield strength of 1205 MPa, a low yield ratio of 0.93, and an impact energy of 105 J at −20 °C. Microstructural analysis reveals that the high dislocation density and refined grain structure generated during rolling provided numerous nucleation sites for fine, dense Cu precipitates during DQA treatment, thereby enhancing precipitation strengthening. The reduced yield ratio is primarily attributed to the high initial dislocation density and deformation substructure, which enhance work-hardening capacity and consequently lower the yield ratio. The toughness mechanisms of both processes are also discussed in detail. These findings offer valuable insights into optimizing the strength–toughness balance of ultra-high-strength steels. Full article

(This article belongs to the Special Issue Mechanical Properties and Applications for Nanostructured Alloys)

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10 pages, 841 KB

Open AccessArticle

Investigating the Prophylactic Efficacy of Linalool to Control Campylobacter jejuni in Broiler Chickens

by Leya Susan Viju, Divya Joseph, Poonam Gopika Vinayamohan and Kumar Venkitanarayanan

Poultry 2026, 5(1), 7; https://doi.org/10.3390/poultry5010007 (registering DOI) - 2 Jan 2026

Abstract

Campylobacter jejuni (CJ) is a major foodborne pathogen with chickens serving as the reservoir host. This study investigated the efficacy of linalool, a Generally Recognized as Safe (GRAS) phytochemical, as an in-feed intervention to reduce CJ colonization in broiler chickens. Three independent trials [...] Read more.

Campylobacter jejuni (CJ) is a major foodborne pathogen with chickens serving as the reservoir host. This study investigated the efficacy of linalool, a Generally Recognized as Safe (GRAS) phytochemical, as an in-feed intervention to reduce CJ colonization in broiler chickens. Three independent trials were conducted using 212-day-old Cornish Cross chicks per trial. Of these, 192 birds were randomly allocated to eight treatment groups (n = 24/group): negative control, linalool-only controls (1.0%, 1.5%, and 1.8%), positive control (CJ only), and CJ-challenged birds supplemented with linalool at 1.0%, 1.5%, or 1.8%. Linalool supplementation commenced on day 0, and birds were orally challenged with approximately 9 log₁₀ CFU of CJ on day 7. Cecal CJ populations were enumerated on days 14, 24, and 34. Positive control birds harbored approximately 6–7 log CFU/g of CJ in the ceca, whereas linalool supplementation significantly reduced CJ colonization (p < 0.05) by 2–3 log on day 14 and by 3–5 log on days 24 and 34. No adverse effects of linalool were observed on body weight, feed intake, or feed conversion ratio. Additionally, RT-qPCR analysis demonstrated downregulation (p < 0.0001) of key CJ virulence and colonization-associated genes. These findings suggest that dietary linalool is a potential strategy to reduce CJ colonization in broiler chickens; however, large-scale studies under field conditions are warranted. Full article

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22 pages, 927 KB

Open AccessArticle

The Relationship Between Leader-Member Exchange and Team Cohesion: A Multi-Team Study in the Croatian Banking Sector

by Mark Bratek, Domagoj Hruška and Ana Sertić

Adm. Sci. 2026, 16(1), 23; https://doi.org/10.3390/admsci16010023 (registering DOI) - 2 Jan 2026

Abstract

This study explores the relationship between Leader-Member Exchange (LMX) quality and team cohesion within the Croatian banking sector. Drawing from relationship-based leadership theories, we investigate how the quality of dyadic relationships between leaders and team members influences team cohesiveness in a hierarchical, regulated [...] Read more.

This study explores the relationship between Leader-Member Exchange (LMX) quality and team cohesion within the Croatian banking sector. Drawing from relationship-based leadership theories, we investigate how the quality of dyadic relationships between leaders and team members influences team cohesiveness in a hierarchical, regulated organizational environment. Using validated instruments (LMX-7 and adapted Group Environment Questionnaire), we surveyed 76 employees across 10 teams. Results demonstrate a strong positive correlation between LMX quality and team cohesion (r = 0.854, p = 0.002). Our findings contribute to understanding how relationship-based leadership practices can foster stronger team dynamics in knowledge-intensive organizational contexts, with implications for leadership development in banking and similar professional services sectors. Full article

(This article belongs to the Special Issue Navigating the Challenges: Entrepreneurship and Leadership in the Modern Global Business Landscape)

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20 pages, 878 KB

Open AccessArticle

Functional Characterization and Application of Lacticaseibacillus and Lactobacillus Strains to Hatching Eggs for Control of Salmonella Enteritidis in Layer Hatchlings

by Muhammed Shafeekh Muyyarikkandy, Praveen Kosuri and Mary Anne Amalaradjou

Poultry 2026, 5(1), 6; https://doi.org/10.3390/poultry5010006 (registering DOI) - 2 Jan 2026

Abstract

With growing emphasis on antibiotic-free poultry production, functional probiotics represent a promising strategy to improve gut health and reduce pathogen transmission. This study characterized three lactic acid bacteria (LAB) strains Lactobacillus delbrueckii subsp. bulgaricus NRRL-B-548 (LD), Lacticaseibacillus paracasei DUP-13076 (LP), and Lacticaseibacillus rhamnosus [...] Read more.

With growing emphasis on antibiotic-free poultry production, functional probiotics represent a promising strategy to improve gut health and reduce pathogen transmission. This study characterized three lactic acid bacteria (LAB) strains Lactobacillus delbrueckii subsp. bulgaricus NRRL-B-548 (LD), Lacticaseibacillus paracasei DUP-13076 (LP), and Lacticaseibacillus rhamnosus NRRL-B-442 (LR) for their probiotic potential and evaluated their efficacy against Salmonella enterica in poultry. The LAB strains were assessed for acid and bile tolerance, lysozyme resistance, cholesterol assimilation, antimicrobial activity, surface hydrophobicity, epithelial adherence, hemolysis, and antibiotic susceptibility. Genomic analysis was performed to identify genes associated with probiotic functionality. The protective potential of LR and LP was further validated in hatchlings using a hatchery spray model challenged with Salmonella Enteritidis. All strains survived simulated gastric and intestinal conditions, exhibited strong adhesion to epithelial cells, and demonstrated high hydrophobicity, indicating robust colonization capacity. The LAB significantly inhibited Salmonella Enteritidis, S. Typhimurium, and S. Heidelberg growth in vitro and remained sensitive to clinically relevant antibiotics. In vivo application of LR and LP to hatching eggs markedly reduced S. Enteritidis colonization in the liver, spleen, and ceca of hatchlings. Further, genomic profiling of the LAB strains revealed genes for bacteriocin production, exopolysaccharide synthesis, and carbohydrate metabolism supporting probiotic function. In summary, the evaluated LAB strains exhibit multiple probiotic attributes and strong anti-Salmonella activity, confirming their potential as safe, hatchery-applied probiotics for improving gut health and biosecurity in poultry production systems. Full article

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3 pages, 134 KB

Open AccessEditorial

State of the Art and Perspectives on Polymer Science and Technology in China

by Sixun Zheng

Polymers 2026, 18(1), 136; https://doi.org/10.3390/polym18010136 (registering DOI) - 2 Jan 2026

Abstract

In 2023, the Polymers journal launched a Special Issue to report research by Chinese scholars focusing on the physics and processing of polymers, the development of new materials, and the application of new technologies [...] Full article

(This article belongs to the Special Issue State of the Art and Perspectives of Polymer Science and Technology in China)

26 pages, 3750 KB

Open AccessReview

Research Progress on Heat Transfer of Herringbone Plate Heat Exchangers Under Single-Phase/Two-Phase Flow

by Junhui Song, Li Lei, Naixiang Zhou and Jingzhi Zhang

Energies 2026, 19(1), 249; https://doi.org/10.3390/en19010249 (registering DOI) - 2 Jan 2026

Abstract

Against the backdrop of the “dual carbon” strategy, enhancing energy utilization efficiency and promoting low-carbon urban heating have become key directions for energy system transformation. Due to the compact structure, high heat transfer efficiency, and strong adaptability, herringbone plate heat exchangers have emerged [...] Read more.

Against the backdrop of the “dual carbon” strategy, enhancing energy utilization efficiency and promoting low-carbon urban heating have become key directions for energy system transformation. Due to the compact structure, high heat transfer efficiency, and strong adaptability, herringbone plate heat exchangers have emerged as critical intermediate heat exchange equipment in long-distance heating systems. This paper reviews research on the heat transfer performance of herringbone plate heat exchangers, systematically examining fluid flow patterns within plate heat exchangers and the mechanisms influencing thermohydraulic performance under single-phase and two-phase flow conditions, along with recent advancements. First, factors affecting fluid flow within herringbone corrugated plates are introduced. Subsequently, recent experimental and numerical simulation advancements under single-phase and two-phase conditions are presented, along with corresponding performance correlation equations. In contrast, two-phase heat transfer mechanisms are more complex, with relatively insufficient research and a lack of universally applicable theoretical models and performance correlations. This paper argues that future efforts should focus on strengthening research into two-phase flow heat transfer mechanisms and developing more universal and predictive performance models to support the efficient application of plate heat exchangers in low-carbon heating and industrial energy conservation. Full article

(This article belongs to the Special Issue Heat Transfer and Fluid Flows for Industry Applications)

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24 pages, 8627 KB

Open AccessArticle

{Zn^II₂} and {Zn^IIAu^I} Metal Complexes with Schiff Base Ligands as Potential Antitumor Agents Against Human Glioblastoma Multiforme Cells

by Lora Dyakova, Tanya Zhivkova, Abedulkadir Abudalleh, Daniela C. Culita, Teodora Mocanu, Augustin M. Madalan, Anamaria Hanganu, Gabriela Marinescu, Emanuil Naydenov and Radostina Alexandrova

Molecules 2026, 31(1), 173; https://doi.org/10.3390/molecules31010173 (registering DOI) - 1 Jan 2026

Abstract

The challenges of glioblastoma multiforme treatment are related to limitations in tumor removal surgery, its high heterogeneity and aggressiveness, development of resistance to standard therapy, the blood–brain barrier, and the side and toxic effects of the conventional antitumor agents used in clinical practice. [...] Read more.

The challenges of glioblastoma multiforme treatment are related to limitations in tumor removal surgery, its high heterogeneity and aggressiveness, development of resistance to standard therapy, the blood–brain barrier, and the side and toxic effects of the conventional antitumor agents used in clinical practice. Although new treatment strategies continue to emerge, progress remains slow and has not resulted in substantial improvements in patient survival. The main goal of research in recent years has been aimed at developing ways to deal with all these challenges. One of the ways to improve the control of glioblastomas is the introduction of effective new antitumor agents. Metal complexes represent a particularly promising class of compounds in this context. This is why the aim of this study was to assess the effects of six homo- and heterometallic coordination compounds bearing Schiff base ligands—[Zn₂(Ampy)(µ-OH)(H₂O)₂](ClO₄)₂ (ZnAmpy), [Zn₂(Dmen)(µ-OH)(H₂O)₂](ClO₄)₂ (ZnDmen), ¹_∞[{Zn₂(Ampy)(μ₃-OH)}₂(H₂O){μ-[Au(CN)₂]}](ClO₄)₃·THF·H₂O (ZnAmpyAu), [{Zn₂(Dmen)(μ-OH)}₂{μ-[Au(CN)₂]}{[Au(CN)₂]₂}](ClO₄)·H₂O (ZnDmenAu), ¹_∞[Zn(Salampy){μ-Au(CN)₂}] (ZnSalampyAu), and ¹_∞[Zn(Saldmen)(μ-Au(CN)₂}] (ZnSaldmenAu)—on the viability and proliferation of 8MGBA and U251MG human glioblastoma multiforme cells (HDmen and HAmpy are bicompartmental Schiff base ligands resulting from the condensation of 2,6-diformyl-p-cresol with N,N-dimethylethylenediamine and 2-(aminomethyl)pyridine, respectively, while HSaldmen and HSalampy are tridentate Schiff base ligands obtained via condensation of salicylaldehyde with N,N-dimethylethylenediamine and 2-(aminomethyl)pyridine, respectively). Among these compounds, ZnSaldmenAu is a new compound and is reported here for the first time. Cytotoxicity of the compounds was evaluated through analysis of cell viability, 2D/3D growth, cytopathological alterations, and induction of cell death. The results obtained by methods with different targets in cells and the associated mechanisms of action revealed that the compounds investigated show promising cytotoxic/potential antitumor activity in treated cells. Full article

(This article belongs to the Special Issue Exploring Schiff Base Ligands and Their Metal Complexes)

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14 pages, 1285 KB

Open AccessArticle

Endoscopic Ultrasound and Endoscopic Retrograde Cholangiopancreatography for Bile Duct Stones—Avoiding the Avoidable

by Stefan Chiriac, Catalin Sfarti, Horia Minea, Sebastian Zenovia, Irina Girleanu, Laura Huiban, Cristina Muzica, Adrian Rotaru, Remus Stafie, Robert Nastasa, Ermina Stratina, Bogdan Mihnea Ciuntu, Raluca Avram and Anca Trifan

Biomedicines 2026, 14(1), 91; https://doi.org/10.3390/biomedicines14010091 (registering DOI) - 1 Jan 2026

Abstract

Background: Endoscopic retrograde cholangiopancreatography (ERCP) is the primary treatment option for choledocholithiasis. However, this procedure carries an inherent non-negligible risk of complications, requiring precise indications and careful patient selection. Endoscopic ultrasonography (EUS) can verify the presence of bile duct stones prior to ERCP. [...] Read more.

Background: Endoscopic retrograde cholangiopancreatography (ERCP) is the primary treatment option for choledocholithiasis. However, this procedure carries an inherent non-negligible risk of complications, requiring precise indications and careful patient selection. Endoscopic ultrasonography (EUS) can verify the presence of bile duct stones prior to ERCP. The current ESGE recommendations permit ERCP in high-risk patients without confirmation; however, several individuals undergo ERCP without evident advantage, indicating a necessity for enhanced stratification. Objectives: We aim to evaluate the rate of EUS-validated choledocholithiasis in patients with suspected common bile duct (CBD) stones and to determine the predictors of residual stones. A secondary objective was to create and internally validate a streamlined scoring system to enhance risk assessment in ESGE high-risk patients. Methods: We conducted a retrospective analysis of patients who had endoscopic ultrasound for suspected choledocholithiasis from January 2023 to December 2024 at a tertiary center. Multivariate logistic regression determined independent predictors of retained calculi. A simplified score was derived from model coefficients and internally validated. Results: Among 438 examined patients, 186 were included and 87 had choledocholithiasis confirmed via EUS. ERCP was conducted in 81 patients and postponed for 6 patients due to contraindications. According to the ESGE criteria, 10 patients (5.4%) were classified as low risk, 92 (49.5%) as intermediate risk, and 84 (45.2%) as high risk for choledocholithiasis. For high-risk individuals, EUS identified stones in 45 (53.5%), while 39 (46.4%) experienced spontaneous clearance. Acute pancreatitis (aOR 0.075), cholangitis (aOR 6.939), and EUS CBD diameter (aOR 1.220 per mm) were independent predictors of stones. The resultant three-component score (−2 to +4 points) demonstrated effective discrimination (AUROC 0.788). A criterion of ≥2 resulted in 85.7% sensitivity and 59.0% specificity. Conclusions: Almost fifty percent of ESGE high-risk patients were not found to have CBD stones during EUS. Integrating EUS data with a straightforward predictive score may enhance risk classification and avert superfluous ERCP procedures. Full article

(This article belongs to the Special Issue Gastrointestinal Diseases: From Pathophysiology to Innovative Therapeutic Approaches)

29 pages, 12380 KB

Open AccessArticle

MIE-YOLO: A Multi-Scale Information-Enhanced Weed Detection Algorithm for Precision Agriculture

by Zhoujiaxin Heng, Yuchen Xie and Danfeng Du

AgriEngineering 2026, 8(1), 16; https://doi.org/10.3390/agriengineering8010016 (registering DOI) - 1 Jan 2026

Abstract

As precision agriculture places higher demands on real-time field weed detection and recognition accuracy, this paper proposes a multi-scale information-enhanced weed detection algorithm, MIE-YOLO (Multi-scale Information Enhanced), for precision agriculture. Based on the popular YOLO12 (You Only Look Once 12) model, MIE-YOLO combines [...] Read more.

As precision agriculture places higher demands on real-time field weed detection and recognition accuracy, this paper proposes a multi-scale information-enhanced weed detection algorithm, MIE-YOLO (Multi-scale Information Enhanced), for precision agriculture. Based on the popular YOLO12 (You Only Look Once 12) model, MIE-YOLO combines edge-aware multi-scale fusion with additive gated blocks and two-stage self-distillation to boost small-object and boundary detection while staying lightweight. First, the MS-EIS (Multi-Scale-Edge Information Select) architecture is designed to effectively aggregate and select edge and texture information at different scales to enhance fine-grained feature representation. Next, the Add-CGLU (Additive-Convolutional Gated Linear Unit) pyramid network is proposed, which enhances the representational power and information transfer efficiency of multi-scale features through additive fusion and gating mechanisms. Finally, the DEC (Detail-Enhanced Convolution) detection head is introduced to enhance detail and refine the localization of small objects and fuzzy boundaries. To further improve the model’s detection accuracy and generalization performance, the DS (Double Self-Knowledge Distillation) strategy is defined to perform double self-knowledge distillation within the entire network. Experimental results on the custom Weed dataset, which contains 9257 images of eight weed categories, show that MIE-YOLO improves the F1 score by 1.9% and the mAP by 2.0%. Furthermore, it reduces computational parameters by 29.9%, FLOPs by 6.9%, and model size by 17.0%, achieving a runtime speed of 66.2 FPS. MIE-YOLO improves weed detection performance while maintaining a certain level of inference efficiency, providing an effective technical path and engineering implementation reference for intelligent field inspection and precise weed control in precision agriculture. The source code is available on GitHub. Full article

(This article belongs to the Special Issue Integrating AI and Robotics for Precision Weed Control in Agriculture)

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26 pages, 2109 KB

Open AccessArticle

Integrated Assessment of Odour Emissions from a Municipal Wastewater Pumping Station Using Field Olfactometry and Chemometric Modelling

by Mirosław Szyłak-Szydłowski, Andrzej Kulig and Wojciech Kos

Appl. Sci. 2026, 16(1), 468; https://doi.org/10.3390/app16010468 (registering DOI) - 1 Jan 2026

Abstract

Odour emissions from wastewater infrastructure represent a significant environmental and social challenge in urban areas. This study evaluates the odour impact of a municipal wastewater pumping station using an integrated field-based approach that combines sensory observations, chemical measurements and meteorological data. Field olfactometry [...] Read more.

Odour emissions from wastewater infrastructure represent a significant environmental and social challenge in urban areas. This study evaluates the odour impact of a municipal wastewater pumping station using an integrated field-based approach that combines sensory observations, chemical measurements and meteorological data. Field olfactometry and on-site gas monitoring were applied over a two-year campaign covering different operational and seasonal conditions. The results indicate that odour perception is strongly influenced by hydrogen sulphide concentration, air temperature and wind speed, with short-term high-intensity episodes playing a disproportionate role in odour nuisance. To support integrated interpretation, a Synthetic Odour Index (SOI) was developed to consolidate chemical, sensory and microclimatic information into a single numerical indicator, extending existing odour indices by explicitly integrating field-based sensory and meteorological data. The SOI showed a moderate but statistically significant association with odour intensity (r ≈ 0.3) and effectively differentiated low- and high-nuisance conditions. The proposed methodology demonstrates the value of combining field measurements with integrated data analysis for assessing and managing odour emissions from urban wastewater pumping stations and provides a practical basis for operational monitoring and odour mitigation strategies. Full article

(This article belongs to the Special Issue Novel Research on By-Products and Treatment of Waste)

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