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Quantum machine learning (QML) has emerged as a promising approach for enhancing image classification by exploiting quantum computational principles such as superposition and entanglement. However, practical applications on complex datasets like CIFAR-100 remain limited due to the low expressivity of shallow circuits and challenges in circuit optimization. In this study, we propose HQCNN–REGA—a novel hybrid quantum–classical convolutional neural network architecture that integrates data re-uploading and genetic algorithm optimization for improved performance. The data re-uploading mechanism allows classical inputs to be encoded multiple times into quantum states, enhancing the model’s capacity to learn complex visual features. In parallel, a genetic algorithm is employed to evolve the quantum circuit architecture by optimizing gate sequences, entanglement patterns, and layer configurations. This combination enables automatic discovery of efficient parameterized quantum circuits without manual tuning. Experiments on the MNIST and CIFAR-100 datasets demonstrate state-of-the-art performance for quantum models, with HQCNN–REGA outperforming existing quantum neural networks and approaching the accuracy of advanced classical architectures. In particular, we compare our model with classical convolutional baselines such as ResNet-18 to validate its effectiveness in real-world image classification tasks. Our results demonstrate the feasibility of scalable, high-performing quantum–classical systems and offer a viable path toward practical deployment of QML in computer vision applications, especially on noisy intermediate-scale quantum (NISQ) hardware. Full article

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24 pages, 1380 KiB

Open AccessArticle

Critical Smart Functions for Smart Living Based on User Perspectives

by Benjamin Botchway, Frank Ato Ghansah, David John Edwards, Ebenezer Kumi-Amoah and Joshua Amo-Larbi

Buildings 2025, 15(15), 2727; https://doi.org/10.3390/buildings15152727 (registering DOI) - 1 Aug 2025

Abstract

Smart living is strongly promoted to enhance the quality of life via the application of innovative solutions, and this is driven by domain specialists and policymakers, including designers, urban planners, computer engineers, and property developers. Nonetheless, the actual user, whose views ought to be considered during the design and development of smart living systems, has received little attention. Thus, this study aims to identify and examine the critical smart functions to achieve smart living in smart buildings based on occupants’ perceptions. The aim is achieved using a sequential quantitative research method involving a literature review and 221 valid survey data gathered from a case of a smart student residence in Hong Kong. The method is further integrated with descriptive statistics, the Kruskal–Walli’s test, and the criticality test. The results were validated via a post-survey with related experts. Twenty-six critical smart functions for smart living were revealed, with the top three including the ability to protect personal data and information privacy, provide real-time safety and security, and the ability to be responsive to users’ needs. A need was discovered to consider the context of buildings during the design of smart living systems, and the recommendation is for professionals to understand the kind of digital technology to be integrated into a building by strongly considering the context of the building and how smart living will be achieved within it based on users’ perceptions. The study provides valuable insights into the occupants’ perceptions of critical smart features/functions for policymakers and practitioners to consider in the construction of smart living systems, specifically students’ smart buildings. This study contributes to knowledge by identifying the critical smart functions to achieve smart living based on occupants’ perceptions of smart living by considering the specific context of a smart student building facility constructed in Hong Kong. Full article

(This article belongs to the Special Issue Construction 4.0 Era: The Application of Building Information Modelling (BIM) and Digital Construction)

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32 pages, 6588 KiB

Open AccessArticle

Path Planning for Unmanned Aerial Vehicle: A-Star-Guided Potential Field Method

by Jaewan Choi and Younghoon Choi

Drones 2025, 9(8), 545; https://doi.org/10.3390/drones9080545 (registering DOI) - 1 Aug 2025

Abstract

The utilization of Unmanned Aerial Vehicles (UAVs) in missions such as reconnaissance and surveillance has grown rapidly, underscoring the need for efficient path planning algorithms that ensure both optimality and collision avoidance. The A-star algorithm is widely used for global path planning due to its ability to generate optimal routes; however, its high computational cost makes it unsuitable for real-time applications, particularly in unknown or dynamic environments. For local path planning, the Artificial Potential Field (APF) algorithm enables real-time navigation by attracting the UAV toward the target while repelling it from obstacles. Despite its efficiency, APF suffers from local minima and limited performance in dynamic settings. To address these challenges, this paper proposes the A-star-Guided Potential Field (AGPF) algorithm, which integrates the strengths of A-star and APF to achieve robust performance in both global and local path planning. The AGPF algorithm was validated through simulations conducted in the Robot Operating System (ROS) environment. Simulation results demonstrate that AGPF produces smoother and more optimal paths than A-star, while avoiding the local minima issues inherent in APF. Furthermore, AGPF effectively handles moving and previously unknown obstacles by generating real-time avoidance trajectories, demonstrating strong adaptability in dynamic and uncertain environments. Full article

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33 pages, 2015 KiB

Open AccessArticle

From Development to Regeneration: Insights into Flight Muscle Adaptations from Bat Muscle Cell Lines

by Fengyan Deng, Valentina Peña, Pedro Morales-Sosa, Andrea Bernal-Rivera, Bowen Yang, Shengping Huang, Sonia Ghosh, Maria Katt, Luciana Andrea Castellano, Lucinda Maddera, Zulin Yu, Nicolas Rohner, Chongbei Zhao and Jasmin Camacho

Cells 2025, 14(15), 1190; https://doi.org/10.3390/cells14151190 (registering DOI) - 1 Aug 2025

Abstract

Skeletal muscle regeneration depends on muscle stem cells, which give rise to myoblasts that drive muscle growth, repair, and maintenance. In bats—the only mammals capable of powered flight—these processes must also sustain contractile performance under extreme mechanical and metabolic stress. However, the cellular and molecular mechanisms underlying bat muscle physiology remain largely unknown. To enable mechanistic investigation of these traits, we established the first myoblast cell lines from the pectoralis muscle of Pteronotus mesoamericanus, a highly maneuverable aerial insectivore. Using both spontaneous immortalization and exogenous hTERT/CDK4 gene overexpression, we generated two stable cell lines that retain proliferative capacity and differentiate into contractile myotubes. These cells exhibit frequent spontaneous contractions, suggesting robust functional integrity at the neuromuscular junction. In parallel, we performed transcriptomic and metabolic profiling of native pectoralis tissue in the closely related Pteronotus parnellii to define molecular programs supporting muscle specialization. Gene expression analyses revealed enriched pathways for muscle metabolism, development, and regeneration, highlighting supporting roles in tissue maintenance and repair. Consistent with this profile, the flight muscle is triglyceride-rich, which serves as an important fuel source for energetically demanding processes, including muscle contraction and cellular recovery. Integration of transcriptomic and metabolic data identified three key metabolic modules—glucose utilization, lipid handling, and nutrient signaling—that likely coordinate ATP production and support metabolic flexibility. Together, these complementary tools and datasets provide the first in vitro platform for investigating bat muscle research, enabling direct exploration of muscle regeneration, metabolic resilience, and evolutionary physiology. Full article

(This article belongs to the Special Issue Advances in Understanding Skeletal Muscle Metabolism and Regeneration: From Mechanisms to Therapeutics)

25 pages, 830 KiB

Open AccessArticle

Writing Is Coding for Sustainable Futures: Reimagining Poetic Expression Through Human–AI Dialogues in Environmental Storytelling and Digital Cultural Heritage

by Hao-Chiang Koong Lin, Ruei-Shan Lu and Tao-Hua Wang

Sustainability 2025, 17(15), 7020; https://doi.org/10.3390/su17157020 (registering DOI) - 1 Aug 2025

Abstract

In the era of generative artificial intelligence, writing has evolved into a programmable practice capable of generating sustainable narratives and preserving cultural heritage through poetic prompts. This study proposes “Writing Is Coding ” as a paradigm for sustainability education, exploring how students engage with AI-mediated multimodal creation to address environmental challenges. Using grounded theory methodology with 57 twelfth-grade students from technology-integrated high schools, we analyzed their experiences creating environmental stories and digital cultural artifacts using MidJourney, Kling, and Sora. Data collection involved classroom observations, semi-structured interviews, and reflective journals, analyzed through systematic coding procedures (κ = 0.82). Five central themes emerged: writing as algorithmic design for sustainability (89.5%), emotional scaffolding for environmental awareness (78.9%), aesthetics of imperfection in cultural preservation (71.9%), collaborative dynamics in sustainable creativity (84.2%), and pedagogical value of prompt literacy (91.2%). Findings indicate that AI deepens environmental consciousness and reframes writing as a computational process for addressing global issues. This research contributes a theoretical framework integrating expressive writing with algorithmic thinking in AI-assisted sustainability education, aligned with SDGs 4, 11, and 13. Full article

(This article belongs to the Special Issue Generative Artificial Intelligence (GAI) and AI-Generated Content (AIGC) for Sustainable Futures: Innovations in Education, Culture, and Society)

22 pages, 3273 KiB

Open AccessArticle

Virtual Acoustic Environment Rehearsal and Performance in an Unknown Venue

by Charlotte Fernandez, Martin S. Lawless, David Poirier-Quinot and Brian F. G. Katz

Virtual Worlds 2025, 4(3), 35; https://doi.org/10.3390/virtualworlds4030035 (registering DOI) - 1 Aug 2025

Abstract

Due to the effect of room acoustics on musical interpretation, a musician’s rehearsal may be greatly enhanced by leveraging virtual and augmented reality technology. This paper presents a preliminary study on a rehearsal tool designed for musicians, enabling practice in a virtual acoustic environment with audience-positioned playback. Fourteen participants, both professional and non-professional musicians, were recruited to practice with the rehearsal tool prior to performing in an unfamiliar venue. Throughout the rehearsal, the subjects either played in a virtual environment that matched the acoustics of the performance venue or one that was acoustically different. A control group rehearsed in an acoustically dry room with no virtual acoustic environment. The tool’s effectiveness was evaluated with two 16-item questionnaires that assessed quality, usefulness, satisfaction with the rehearsal, and aspects of the performance. Findings indicate that rehearsing in a virtual acoustic environment that matches the performance venue improves acoustic awareness during the performance and enhances ease and comfort on stage compared to practising in a different environment. These results support the integration of virtual acoustics in rehearsal tools to help musicians better adapt their performance to concert settings. Full article

(This article belongs to the Special Issue Contemporary Developments in Mixed, Augmented, and Virtual Reality: Implications for Teaching and Learning)

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24 pages, 3172 KiB

Open AccessArticle

A DDPG-LSTM Framework for Optimizing UAV-Enabled Integrated Sensing and Communication

by Xuan-Toan Dang, Joon-Soo Eom, Binh-Minh Vu and Oh-Soon Shin

Drones 2025, 9(8), 548; https://doi.org/10.3390/drones9080548 (registering DOI) - 1 Aug 2025

Abstract

This paper proposes a novel dual-functional radar-communication (DFRC) framework that integrates unmanned aerial vehicle (UAV) communications into an integrated sensing and communication (ISAC) system, termed the ISAC-UAV architecture. In this system, the UAV’s mobility is leveraged to simultaneously serve multiple single-antenna uplink users (UEs) and perform radar-based sensing tasks. A key challenge stems from the target position uncertainty due to movement, which impairs matched filtering and beamforming, thereby degrading both uplink reception and sensing performance. Moreover, UAV energy consumption associated with mobility must be considered to ensure energy-efficient operation. We aim to jointly maximize radar sensing accuracy and minimize UAV movement energy over multiple time steps, while maintaining reliable uplink communications. To address this multi-objective optimization, we propose a deep reinforcement learning (DRL) framework based on a long short-term memory (LSTM)-enhanced deep deterministic policy gradient (DDPG) network. By leveraging historical target trajectory data, the model improves prediction of target positions, enhancing sensing accuracy. The proposed DRL-based approach enables joint optimization of UAV trajectory and uplink power control over time. Extensive simulations validate that our method significantly improves communication quality and sensing performance, while ensuring energy-efficient UAV operation. Comparative results further confirm the model’s adaptability and robustness in dynamic environments, outperforming existing UAV trajectory planning and resource allocation benchmarks. Full article

(This article belongs to the Special Issue Recent Developments in Artificial Intelligence and Interdisciplinary Research for UAV Application)

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64 pages, 1429 KiB

Open AccessReview

Pharmacist-Driven Chondroprotection in Osteoarthritis: A Multifaceted Approach Using Patient Education, Information Visualization, and Lifestyle Integration

by Eloy del Río

Pharmacy 2025, 13(4), 106; https://doi.org/10.3390/pharmacy13040106 (registering DOI) - 1 Aug 2025

Abstract

Osteoarthritis (OA) remains a major contributor to pain and disability; however, the current management is largely reactive, focusing on symptoms rather than preventing irreversible cartilage loss. This review first examines the mechanistic foundations for pharmacological chondroprotection—illustrating how conventional agents, such as glucosamine sulfate and chondroitin sulfate, can potentially restore extracellular matrix (ECM) components, may attenuate catabolic enzyme activity, and might enhance joint lubrication—and explores the delivery challenges posed by avascular cartilage and synovial diffusion barriers. Subsequently, a practical “What–How–When” framework is introduced to guide community pharmacists in risk screening, DMOAD selection, chronotherapeutic dosing, safety monitoring, and lifestyle integration, as exemplified by the CHONDROMOVING infographic brochure designed for diverse health literacy levels. Building on these strategies, the P4–4P Chondroprotection Framework is proposed, integrating predictive risk profiling (physicians), preventive pharmacokinetic and chronotherapy optimization (pharmacists), personalized biomechanical interventions (physiotherapists), and participatory self-management (patients) into a unified, feedback-driven OA care model. To translate this framework into routine practice, I recommend the development of DMOAD-specific clinical guidelines, incorporation of chondroprotective chronotherapy and interprofessional collaboration into health-professional curricula, and establishment of multidisciplinary OA management pathways—supported by appropriate reimbursement structures, to support preventive, team-based management, and prioritization of large-scale randomized trials and real-world evidence studies to validate the long-term structural, functional, and quality of life benefits of synchronized DMOAD and exercise-timed interventions. This comprehensive, precision-driven paradigm aims to shift OA care from reactive palliation to true disease modification, preserving cartilage integrity and improving the quality of life for millions worldwide. Full article

24 pages, 2329 KiB

Open AccessArticle

Flavonoid Extract of Senecio Scandens Buch.-Ham. Ameliorates CTX-Induced Immunosuppression and Intestinal Damage via Activating the MyD88-Mediated Nuclear Factor-κB Signaling Pathway

by Xiaolin Zhu, Lulu Zhang, Xuan Ni, Jian Guo, Yizhuo Fang, Jianghan Xu, Zhuo Chen and Zhihui Hao

Nutrients 2025, 17(15), 2540; https://doi.org/10.3390/nu17152540 (registering DOI) - 1 Aug 2025

Abstract

Background/Objectives: Senecio scandens Buch.-Ham. is a flavonoid-rich traditional medicinal plant with established immunomodulatory properties. However, the mechanisms underlying the immunoregulatory and intestinal protective effects of its flavonoid extract (Senecio scandens flavonoids—SSF) remain unclear. This study characterized SSF’s bioactive components and evaluated its efficacy against cyclophosphamide (CTX)-induced immunosuppression and intestinal injury. Methods: The constituents of SSF were identified using UHPLC/Q-Orbitrap/HRMS. Mice with CTX-induced immunosuppression were treated with SSF (80, 160, 320 mg/kg) for seven days. Immune parameters (organ indices, lymphocyte proliferation, cytokine, and immunoglobulin levels) and gut barrier integrity markers (ZO-1, Occludin, Claudin-1 protein expression; sIgA secretion; microbiota composition) were assessed. Network pharmacology combined with functional assays elucidated the underlying regulatory mechanisms. Results: Twenty flavonoids were identified in SSF, with six prototype compounds detectable in the blood. The SSF treatment significantly ameliorated CTX-induced weight loss and atrophy of the thymus and spleen. It enhanced splenic T- and B-lymphocyte proliferation by 43.6% and 29.7%, respectively; normalized the CD4⁺/CD8⁺ ratio (1.57-fold increase); and elevated levels of IL-2, IL-6, IL-10, TNF-α, IFN-γ, IgM, and IgG. Moreover, SSF reinforced the intestinal barrier by upregulating tight junction protein expression and sIgA levels while modulating the gut microbiota, enriching beneficial taxa (e.g., the Lachnospiraceae_NK4A136_group, Akkermansia) and suppressing pathogenic Alistipes. Mechanistically, SSF activated the TLR/MyD88/NF-κB pathway, with isoquercitrin identified as a pivotal bioactive constituent. Conclusions: SSF effectively mitigates CTX-induced immunosuppression and intestinal damage. These findings highlight SSF’s potential as a dual-functional natural agent for immunomodulation and intestinal protection. Subsequent research should validate isoquercitrin’s molecular targets and assess SSF’s clinical efficacy. Full article

(This article belongs to the Section Nutrition and Metabolism)

48 pages, 3956 KiB

Open AccessArticle

SEP and Blockchain Adoption in Western Balkans and EU: The Mediating Role of ESG Activities and DEI Initiatives

by Vasiliki Basdekidou and Harry Papapanagos

FinTech 2025, 4(3), 37; https://doi.org/10.3390/fintech4030037 (registering DOI) - 1 Aug 2025

Abstract

This paper explores the intervening role in SEP performance of corporate environmental, cultural, and ethnic activities (ECEAs) and diversity, equity, inclusion, and social initiatives (DEISIs) on blockchain adoption (BCA) strategy, particularly useful in the Western Balkans (WB), which demands transparency due to extended fraud and ethnic complexities. In this domain, a question has been raised: In BCA strategies, is there any correlation between SEP performance and ECEAs and DEISIs in a mediating role? A serial mediation model was tested on a dataset of 630 WB and EU companies, and the research conceptual model was validated by CFA (Confirmation Factor Analysis), and the SEM (Structural Equation Model) fit was assessed. We found a statistically sound (significant, positive) correlation between BCA and ESG success performance, especially in the innovation and integrity ESG performance success indicators, when DEISIs mediate. The findings confirmed the influence of technology, and environmental, cultural, ethnic, and social factors on BCA strategy. The findings revealed some important issues of BCA that are of worth to WB companies’ managers to address BCA for better performance. This study adds to the literature on corporate blockchain transformation, especially for organizations seeking investment opportunities in new international markets to diversify their assets and skill pool. Furthermore, it contributes to a deeper understanding of how DEI initiatives impact the correlation between business transformation and socioeconomic performance, which is referred to as the “social impact”. Full article

(This article belongs to the Special Issue Fintech Innovations: Transforming the Financial Landscape)

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26 pages, 1567 KiB

Open AccessArticle

A CDC–ANFIS-Based Model for Assessing Ship Collision Risk in Autonomous Navigation

by Hee-Jin Lee and Ho Namgung

J. Mar. Sci. Eng. 2025, 13(8), 1492; https://doi.org/10.3390/jmse13081492 (registering DOI) - 1 Aug 2025

Abstract

To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries. Full article

(This article belongs to the Special Issue Advanced Research in Guidance, Navigation, and Control for Autonomous Surface Vehicle)

16 pages, 2028 KiB

Open AccessArticle

A Hybrid Algorithm for PMLSM Force Ripple Suppression Based on Mechanism Model and Data Model

by Yunlong Yi, Sheng Ma, Bo Zhang and Wei Feng

Energies 2025, 18(15), 4101; https://doi.org/10.3390/en18154101 (registering DOI) - 1 Aug 2025

Abstract

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

11 pages, 459 KiB

Open AccessCase Report

Urinary Multidrug-Resistant Klebsiella pneumoniae: Essential Oil Countermeasures in a One Health Case Report

by Mălina-Lorena Mihu, Cristiana Ştefania Novac, Smaranda Crăciun, Nicodim Iosif Fiţ, Cosmina Maria Bouari, George Cosmin Nadăş and Sorin Răpuntean

Microorganisms 2025, 13(8), 1807; https://doi.org/10.3390/microorganisms13081807 (registering DOI) - 1 Aug 2025

Abstract

Carbapenem-resistant Klebsiella pneumoniae (CR-Kp) is eroding therapeutic options for urinary tract infections. We isolated a multidrug-resistant strain from the urine of a chronically bacteriuric patient and confirmed its identity by Vitek-2 and MALDI-TOF MS. Initial disk-diffusion profiling against 48 antibiotics revealed susceptibility to only 5 agents. One month later, repeat testing showed that tetracycline alone remained active, highlighting the strain’s rapidly evolving resistome. Given the scarcity of drug options, we performed an “aromatogram” with seven pure essential oils, propolis, and two commercial phytotherapeutic blends. Biomicin Forte^® produced a 30 mm bactericidal halo, while thyme, tea tree, laurel, and palmarosa oils yielded clear inhibition zones of 11–22 mm. These in vitro data demonstrate that carefully selected plant-derived products can target CR-Kp where conventional antibiotics fail. Integrating aromatogram results into One Health’s stewardship plans may therefore help preserve last-line antibiotics and provide adjunctive options for persistent urinary infections. Full article

(This article belongs to the Special Issue Infectious Disease Surveillance in Romania)

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20 pages, 804 KiB

Open AccessArticle

Application of Animal- and Plant-Derived Coagulant in Artisanal Italian Caciotta Cheesemaking: Comparison of Sensory, Biochemical, and Rheological Parameters

by Giovanna Lomolino, Stefania Zannoni, Mara Vegro and Alberto De Iseppi

Dairy 2025, 6(4), 43; https://doi.org/10.3390/dairy6040043 (registering DOI) - 1 Aug 2025

Abstract

Consumer interest in vegetarian, ethical, and clean-label foods is reviving the use of plant-derived milk coagulants. Cardosins from Cynara cardunculus (“thistle”) are aspartic proteases with strong clotting activity, yet their technological impact in cheese remains under-explored. This study compared a commercial thistle extract (PC) with traditional bovine rennet rich in chymosin (AC) during manufacture and 60-day ripening of Caciotta cheese. Classical compositional assays (ripening index, texture profile, color, solubility) were integrated with scanning electron microscopy, three-dimensional surface reconstruction, and descriptive sensory analysis. AC cheeses displayed slower but sustained proteolysis, yielding a higher and more linear ripening index, softer body, greater solubility, and brighter, more yellow appearance. Imaging revealed a continuous protein matrix with uniformly distributed, larger pores, consistent with a dairy-like sensory profile dominated by milky and umami notes. Conversely, PC cheeses underwent rapid early proteolysis that plateaued, producing firmer, chewier curds with lower solubility and darker color. Micrographs showed a fragmented matrix with smaller, heterogeneous pores; sensory evaluation highlighted vegetal, bitter, and astringent attributes. The data demonstrate that thistle coagulant can successfully replace animal rennet but generates cheeses with distinct structural and sensory fingerprints. The optimization of process parameters is therefore required when targeting specific product styles. Full article

(This article belongs to the Section Milk Processing)

27 pages, 1382 KiB

Open AccessReview

Application of Non-Destructive Technology in Plant Disease Detection: Review

by Yanping Wang, Jun Sun, Zhaoqi Wu, Yilin Jia and Chunxia Dai

Agriculture 2025, 15(15), 1670; https://doi.org/10.3390/agriculture15151670 (registering DOI) - 1 Aug 2025

Abstract

In recent years, research on plant disease detection has combined artificial intelligence, hyperspectral imaging, unmanned aerial vehicle remote sensing, and other technologies, promoting the transformation of pest and disease control in smart agriculture towards digitalization and artificial intelligence. This review systematically elaborates on the research status of non-destructive detection techniques used for plant disease identification and detection, mainly introducing the following two types of methods: spectral technology and imaging technology. It also elaborates, in detail, on the principles and application examples of each technology and summarizes the advantages and disadvantages of these technologies. This review clearly indicates that non-destructive detection techniques can achieve plant disease and pest detection quickly, accurately, and without damage. In the future, integrating multiple non-destructive detection technologies, developing portable detection devices, and combining more efficient data processing methods will become the core development directions of this field. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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