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Food safety management has evolved with the Hazard Analysis and Critical Control Point (HACCP) system serving as a global benchmark. However, conventional HACCP does not explicitly address environmental sustainability, leading to challenges such as excessive water use, chemical discharge, and energy inefficiency. Green HACCP extends traditional HACCP by integrating Environmental Respect Practices (ERPs) to fill this critical gap between food safety and sustainability. This study is presented as a conceptual paper based on a structured literature review combined with illustrative industry applications. It analyzes the principles, implementation challenges, and economic viability of Green HACCP, contrasting it with conventional systems. Evidence from recent reports and industry examples shows measurable benefits: water consumption reductions of 20–25%, energy savings of 10–15%, and improved compliance readiness through digital monitoring technologies. It explores how digital technologies—IoT for real-time monitoring, AI for predictive optimization, and blockchain for traceability—enhance efficiency and sustainability. By aligning HACCP with sustainability goals and the United Nations Sustainable Development Goals (SDGs), this paper provides academic contributions including a clarified conceptual framework, quantified advantages, and policy recommendations to support the integration of Green HACCP into global food safety systems. Industry applications from dairy, seafood, and bakery sectors illustrate practical benefits, including waste reduction and improved compliance. This study concludes with policy recommendations to integrate Green HACCP into global food safety frameworks, supporting broader sustainability goals. Overall, Green HACCP demonstrates a cost-effective, scalable, and environmentally responsible model for future food production. Full article

(This article belongs to the Section Sustainable Food)

16 pages, 4761 KB

Open AccessArticle

ACR: Adaptive Confidence Re-Scoring for Reliable Answer Selection Among Multiple Candidates

by Eunhye Jeong and Yong Suk Choi

Appl. Sci. 2025, 15(17), 9587; https://doi.org/10.3390/app15179587 (registering DOI) - 30 Aug 2025

Abstract

With the improved reasoning capabilities of large language models (LLMs), their applications have rapidly expanded across a wide range of tasks. In recent question answering tasks, performance gains have been achieved through Self-Consistency, where LLMs generate multiple reasoning paths and determine the final answer via majority voting. However, this approach can fail when the correct answer is generated but does not appear frequently enough to be selected, highlighting its vulnerability to inconsistent generations. To address this, we propose Adaptive Confidence Re-scoring (ACR)—a method that adaptively evaluates and re-scores candidate answers to select the most trustworthy one when LLMs fail to generate consistent reasoning. Experiments on arithmetic and logical reasoning benchmarks show that ACR maintains or improves answer accuracy while significantly reducing inference cost. Compared to existing verification methods such as FOBAR, ACR reduces the number of inference calls by up to 95%, while improving inference efficiency—measured as accuracy gain per inference call—by a factor of 2× to 17×, depending on the dataset and model. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

25 pages, 1192 KB

Open AccessArticle

Effect of Biobased and Mineral Additives on the Properties of Recycled Polypropylene Packaging Materials

by Wiktor Wyderkiewicz, Robert Gogolewski, Justyna Miedzianowska-Masłowska, Konrad Szustakiewicz and Marcin Masłowski

Polymers 2025, 17(17), 2368; https://doi.org/10.3390/polym17172368 (registering DOI) - 30 Aug 2025

Abstract

The recycling of polypropylene (PP) packaging films modified with biobased additives: biochar derived from the pyrolysis of natural fibers and diatomaceous earth was investigated. The aim was to assess the impact of these modifiers on the processing, rheological, mechanical, and thermal properties of the recycled material. The processing behavior was evaluated through extrusion with granulation to determine industrial applicability. Rheological properties, including viscosity and melt flow index (MFI), were measured to characterize flow behavior. Mechanical performance was assessed through tensile strength, hardness, three-point bending, and impact resistance tests. Thermal properties were analyzed using thermogravimetric analysis (TGA), Vicat softening temperature (VST), and differential scanning calorimetry (DSC). The results demonstrate that incorporating biochar and diatomaceous earth can modify and, in selected cases, enhance the processing and performance characteristics of recycled PP films, though their impact on thermal behavior is parameter-specific. While diatomaceous earth slightly increased the onset of thermal degradation (T₅), both fillers caused a slight decrease in the VST, indicating reduced heat resistance under load. Diatomaceous earth was found to effectively improve stiffness and impact strength, while biochar reduced viscosity and promoted finer crystalline structures. Both additives acted as nucleating agents, increasing crystallization temperatures, with diatomaceous earth additionally delaying thermal degradation onset. These findings highlight the potential of using sustainable, waste-derived additives in polymer recycling, supporting the development of environmentally responsible materials within circular economy frameworks. Full article

(This article belongs to the Special Issue Natural Additive-Enhanced Polymer Composites)

22 pages, 813 KB

Open AccessReview

A Narrative Review and Gap Analysis of Blockchain for Transparency, Traceability, and Trust in Data-Driven Supply Chains

by Mitra Madanchian and Hamed Taherdoost

Appl. Sci. 2025, 15(17), 9571; https://doi.org/10.3390/app15179571 (registering DOI) - 30 Aug 2025

Abstract

The increasing complexity and digitization of modern supply chains have created an urgent demand for transparent, traceable, and trustworthy systems of data management. Blockchain, with its core features of immutability, decentralization, and smart contracts, has emerged as a promising solution for strengthening data-driven supply chain operations. This paper presents a narrative review synthesizing insights from academic research, industry reports, and regulatory documents to examine blockchain’s role in enhancing transparency, traceability, and trust. References were identified through targeted searches of major databases and gray literature sources, with emphasis on diverse sectors and global perspectives, rather than exhaustive coverage. The review maps how blockchain’s technical capabilities—such as data integrity preservation, access control, automated validation, and provenance tracking—support these outcomes, and assesses the empirical indicators used to evaluate them. A sectoral applicability analysis distinguishes contexts in which blockchain adoption offers clear advantages from those where benefits are limited. The review also identifies critical research gaps, including inconsistent definitions of core concepts, insufficient interoperability standards, overreliance on subjective performance measures, and lack of longitudinal cost–benefit evidence. Finally, it proposes directions for future research, including the development of sector-specific adoption frameworks, integration with complementary technologies, and cross-border regulatory harmonization. Full article

(This article belongs to the Special Issue Data-Driven Supply Chain Management and Logistics Engineering)

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22 pages, 4928 KB

Open AccessArticle

Inversion Analysis of Stress Fields Based on the LSTM–Attention Neural Network

by Jianxin Wang, Liming Zhang and Junyu Sun

Appl. Sci. 2025, 15(17), 9567; https://doi.org/10.3390/app15179567 (registering DOI) - 30 Aug 2025

Abstract

Conventional geostress methods of measurement cannot reveal an accurate geostress field distribution in an engineering area, limited by both cost and prevailing geological conditions. This study introduces an improved LSTM–Attention neural network for in situ stress field inversion. By integrating long short-term memory (LSTM) networks—which capture temporal dependencies in sequential data with attention mechanisms that emphasize critical features, the proposed method addresses inherent non-linearity and discontinuity challenges in deep subsurface stress field inversion. The integrated LSTM and multi-head attention architecture extracts temporal features and weights critical information within ground stress field data. Through iterative refinement via optimizers and loss functions, this framework successfully inverts stress boundary conditions while mitigating overfitting risks. The inversion of the stress field around a hydropower station indicates that the proposed method allows accurate inversion of distribution of the geostress field; the inversion values of the maximum principal stress, intermediate principal stress, and minimum principal stress conform to those measured. This study provides a new method for accurately and reliably inverting the stress field for deep engineering geological surveys and rock mass engineering design, which has significant scientific value and engineering application prospects. The rockburst risk of chambers is evaluated according to the stress field, which shows that locations with a burial depth of 274.3 m are at moderate to weak risk of rockburst. Full article

24 pages, 1479 KB

Open AccessArticle

Beyond L2 Learners: Evaluating LexTALE-ESP as a Proficiency Measure for Heritage Language Learners of Spanish

by Cristina Lozano-Argüelles and Alberta Gatti

Languages 2025, 10(9), 223; https://doi.org/10.3390/languages10090223 (registering DOI) - 30 Aug 2025

Abstract

LexTALE has emerged as a popular measure of language proficiency in research studies. While it has been widely validated for L2 learners across multiple languages, its applicability to heritage language learners (HLLs)—who often show distinct language development from L2ers—has not been established. Here, we evaluate the Spanish version of LexTALE (LexTALE-Esp) as a predictor of writing proficiency among college-aged HLLs in the United States. We show that LexTALE-Esp scores significantly correlate with ACTFL-rated functional writing levels and outperform self-assessment as a predictor of proficiency. Our results suggest that, despite concerns about HLLs’ limited experience with written texts in the heritage language, vocabulary-based tasks capture core aspects of written language ability. These findings indicate that vocabulary-based tests like LexTALE-Esp capture proficiency-relevant lexical knowledge across speaker profiles and may tap into dimensions of both core and extended language competence. Full article

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21 pages, 955 KB

Open AccessTechnical Note

Applying the Concept of Verification in Fire Engineering to the Wildland–Urban Interface

by Greg Drummond, Greg Baker, Daniel Gorham, Andres Valencia and Anthony Power

Fire 2025, 8(9), 346; https://doi.org/10.3390/fire8090346 (registering DOI) - 30 Aug 2025

Abstract

Despite increased focus on resilient planning and construction design in areas prone to wildfire impacts, recent research has found inconsistent approaches, a lack of evidence-based performance criteria, and limited suitable code-based verification methods for use in wildfire contexts. These limitations serve to reduce the potential effectiveness of measures intended to improve wildfire community and build resilience. The lack of suitable verification methods is particularly problematic in Australia, where complex building code requirements associated with enhanced wildfire resilience have been extended to hospitals, child care facilities, schools, and other assembly buildings. To address this issue, this paper proposes the Wildfire Expected Risk to Life and Property (WERLP) verification method. As a holistic absolute probabilistic verification method, WERLP can be applied to both building and urban design contexts within the Australian jurisdiction. The application of WERLP is demonstrated using the case study of a new hospital development. Full article

(This article belongs to the Section Mathematical Modelling and Numerical Simulation of Combustion and Fire)

13 pages, 3117 KB

Open AccessArticle

Functioning and Safety of the Non-Invasive Corneal Esthesiometer Brill: A Multicenter Study

by Concepción Renedo Laguna, Carmen Gómez Martín, Javier Lozano-Sanroma, José Manuel Benítez del Castillo, Jesús Montero Iruzubieta, Salvador García Delpech and Jesús Merayo-Lloves

Diagnostics 2025, 15(17), 2208; https://doi.org/10.3390/diagnostics15172208 (registering DOI) - 30 Aug 2025

Abstract

Background/Objectives: Corneal sensitivity can be decreased by several ocular conditions, including dry eye and refractive surgery, which can lead to ocular epithelial lesions. This decrease can be detected by esthesiometry. The main objective of this study was to evaluate the performance, safety, and efficacy of the Corneal Esthesiometer Brill in healthy subjects without ocular pathologies. Methods: A controlled, randomized, prospective, multicenter pilot clinical study was conducted in adult patients with healthy eyes. Corneal sensitivity measurements were made three times for one eye randomly selected to obtain the corneal sensitivity reference ranges. Additionally, one more measurement was taken after the application of a topical anesthetic. An intra- and inter-observer analysis was performed to assess user dependence, and the last measurement was taken after ocular topical anesthesia to evaluate the device’s sensitivity in detecting corneal sensitivity loss. Results: Ninety-one volunteers were included with a mean age of 25 (SD 3.46, range 18–30), and fifty-eight (63.7%) were female. Corneal sensitivity reference levels ranged from level 2 (3–4 mbar) to level 3 (4–5 mbar). Intra- and inter-observer measurement differences on the same subject without anesthesia were not statistically significant. Corneal pressure before and after local ocular anesthesia had statistically significant differences (p < 0.0001). Conclusions: The Corneal Esthesiometer Brill yielded consistent and reproducible measurements in young volunteers with healthy eyes, enabling objective, observer-independent use and facilitating the detection of significant loss of sensitivity. Full article

(This article belongs to the Special Issue Advances in Diagnostics of the Cornea, Cataract and Refractive Surgery)

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16 pages, 1500 KB

Open AccessArticle

Emotion Recognition in Autistic Children Through Facial Expressions Using Advanced Deep Learning Architectures

by Petra Radočaj and Goran Martinović

Appl. Sci. 2025, 15(17), 9555; https://doi.org/10.3390/app15179555 (registering DOI) - 30 Aug 2025

Abstract

Atypical and subtle facial expression patterns in individuals with autism spectrum disorder (ASD) pose a significant challenge for automated emotion recognition. This study evaluates and compares the performance of convolutional neural networks (CNNs) and transformer-based deep learning models for facial emotion recognition in this population. Using a labeled dataset of emotional facial images, we assessed eight models across four emotion categories: natural, anger, fear, and joy. Our results demonstrate that transformer models consistently outperformed CNNs in both overall and emotion-specific metrics. Notably, the Swin Transformer achieved the highest performance, with an accuracy of 0.8000 and an F1-score of 0.7889, significantly surpassing all CNN counterparts. While CNNs failed to detect the fear class, transformer models showed a measurable capability in identifying complex emotions such as anger and fear, suggesting an enhanced ability to capture subtle facial cues. Analysis of the confusion matrix further confirmed the transformers’ superior classification balance and generalization. Despite these promising results, the study has limitations, including class imbalance and its reliance solely on facial imagery. Future work should explore multimodal emotion recognition, model interpretability, and personalization for real-world applications. Research also demonstrates the potential of transformer architectures in advancing inclusive, emotion-aware AI systems tailored for autistic individuals. Full article

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20 pages, 460 KB

Open AccessArticle

Towards Comprehensive Characterization of GaoFen-3: Polarimetric Radar Performance and Data Quality Assessment

by Weibin Liang, Lihong Kang and Shijie Ren

Remote Sens. 2025, 17(17), 3016; https://doi.org/10.3390/rs17173016 (registering DOI) - 30 Aug 2025

Abstract

Although synthetic aperture radar (SAR) performance and polarimetric data quality are closely related, they represent fundamentally different concepts. This paper delineates their distinctions, investigates their interdependence, and introduces a comprehensive set of technical metrics for evaluating radar system performance and assessing polarimetric data quality. Specifically, radar performance is quantified by seven independent parameters, whereas data quality is characterized by a three-component channel imbalance vector and a twelve-element channel crosstalk matrix. The paper details the measurement methods for these parameters and outlines the associated technical requirements, including calibrator specifications and test-site conditions. To improve operational applicability, an approximate method for data quality assessment is proposed, and its associated errors are analyzed. Special attention is given to the

γ

factor, which is highlighted as a critical and irreplaceable indicator of radar performance. Using field data from the GaoFen-3 (GF-3) satellite, the proposed metrics are applied to evaluate both radar performance and data quality. The results provide insights into the polarimetric characteristics of the system and offer practical guidance for the calibration and application of GF-3 polarimetric SAR data. Full article

(This article belongs to the Special Issue Cutting-Edge PolSAR Imaging Applications and Techniques)

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15 pages, 2728 KB

Open AccessArticle

Inversion of Vertical Electrical Sounding Data Based on PSO-BP Neural Network

by Yingjie Wang, Guanwen Gu, Ye Wu, Shunji Wang, Xingguo Niu, Zhihe Xu, Haoyuan He, Xinglong Lin and Lai Cao

Minerals 2025, 15(9), 925; https://doi.org/10.3390/min15090925 (registering DOI) - 30 Aug 2025

Abstract

To address the issues of traditional linear inversion methods, such as their dependence on initial models and the high computational cost of Jacobian matrix calculations, this study conducts inversion research on vertical electrical sounding data based on the backpropagation (BP) neural network combined with the Particle Swarm Optimization (PSO) algorithm. First, two-layer and three-layer horizontally layered geoelectric models were constructed to generate the sample data required for neural network training. Secondly, the PSO-BP neural network model was employed to perform test inversions. The inversion results demonstrate that both neural network methods can successfully invert apparent resistivity data into corresponding geoelectric model parameters, thereby validating the correctness of the PSO-BP neural network inversion approach. Finally, the PSO-BP neural network method was applied to training and inversion of field-measured apparent resistivity data. A comparison between the inversion results of the PSO-BP neural network and those of the conventional BP neural network revealed that the PSO-BP neural network yields superior inversion results. This further confirms the reliability, effectiveness, and practical applicability of the proposed inversion method. The work presented in this study provides a novel approach and perspective for the inversion of vertical electrical sounding data. Full article

(This article belongs to the Special Issue Application of Big Data Mining, Machine Learning and Artificial Intelligence in Geoscience, 2nd Edition)

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25 pages, 811 KB

Open AccessArticle

Logistics Companies’ Efficiency Analysis and Ranking by the DEA-Fuzzy AHP Approach

by Nikola Petrović, Vesna Jovanović, Dragan Marinković, Boban Nikolić and Saša Marković

Appl. Sci. 2025, 15(17), 9549; https://doi.org/10.3390/app15179549 (registering DOI) - 30 Aug 2025

Abstract

The logistics industry saw substantial growth in the second half of the 20th century, and logistics companies play a vital role in today’s modern market. Constant shifts in the market present challenges for logistics firms, which must find the optimal balance between achieved goals and utilized resources. The primary indicator that reflects this relationship is efficiency. Measuring and monitoring efficiency in logistics companies is extremely demanding because the final product is not a tangible item; instead, it often consists of transportation, storage, transloading, and forwarding services that require extensive resources. This paper focuses on measuring and improving efficiency. Numerous approaches and methods for evaluating the efficiency of logistics companies are examined. To measure and enhance efficiency, as well as rank companies based on operational efficiency, a three-phase DEA-fuzzy AHP model has been developed. This model was tested using a real-world example by analyzing the efficiency of ten logistics companies in the Republic of Serbia. The results of the analysis indicate the applicability of this model for measuring and improving the efficiency of logistics companies, as well as for their ranking. Full article

(This article belongs to the Special Issue Applications of Fuzzy Systems and Fuzzy Decision Making)

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19 pages, 1713 KB

Open AccessArticle

Air Sensor Data Unifier: R-Shiny Application

by Karoline K. Barkjohn, Catherine Seppanen, Saravanan Arunachalam, Stephen Krabbe and Andrea L. Clements

Air 2025, 3(3), 21; https://doi.org/10.3390/air3030021 (registering DOI) - 30 Aug 2025

Abstract

Data is needed to understand local air quality, reduce exposure, and mitigate the negative impacts on human health. Measuring local air quality often requires a hybrid monitoring approach consisting of the national air monitoring network and one or more networks of air sensors. However, it can be challenging to combine this data to produce a consistent picture of air quality, largely because sensor data is produced in a variety of formats. Users may have difficulty reformatting, performing basic quality control steps, and using the data for their intended purpose. We developed an R-Shiny application that allows users to import text-based air sensor data, describe the format, perform basic quality control, and export the data to standard formats through a user-friendly interface. Format information can be saved to speed up the processing of additional sensors of the same type. This tool can be used by air quality professionals (e.g., state, local, Tribal air agency staff, consultants, researchers) to more efficiently work with data and perform further analysis in the Air Sensor Network Analysis Tool (ASNAT), Google Earth or Geographic Information System (GIS) programs, the Real Time Geospatial Data Viewer (RETIGO), or other applications they already use for air quality analysis and management. Full article

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15 pages, 11119 KB

Open AccessArticle

Gas Hydrate Exploration Using Deep-Towed Controlled-Source Electromagnetics in the Shenhu Area, South China Sea

by Jianping Li, Zhongliang Wu, Xi Chen, Jian’en Jing, Ping Yu, Xianhu Luo, Mingming Wen, Pibo Su, Kai Chen, Meng Wang, Yan Gao and Yao Zhang

J. Mar. Sci. Eng. 2025, 13(9), 1665; https://doi.org/10.3390/jmse13091665 - 29 Aug 2025

Abstract

This study presents the first application of a deep-towed transmitter–receiver marine controlled-source electromagnetic (TTR-MCSEM) system for gas hydrate exploration in the Shenhu area of the South China Sea. High-resolution electromagnetic data were acquired along a 13 km transect using dynamic source–receiver offsets and a 500 A transmitter. The results reveal the following: (1) unprecedented near-seafloor resolution (20~100 m) for the precise delineation of hydrate-bearing caprock, surpassing conventional ocean-bottom electromagnetic systems; (2) laterally continuous high-resistivity anomalies (~10 Ω·m) extending from the base of the gas hydrate stability zone to the seafloor, which correlate with seismic bottom-simulating reflector (BSR) distributions and suggest heterogeneous hydrate saturation; and (3) fault-controlled fluid migration pathways that supply hydrate reservoirs and lead to seabed methane seepage at structural highs. Through 2D inversion, we show that the inverted resistivity values (~10 Ω·m) are slightly higher than those obtained from resistivity logs (~5 Ω·m). Saturation values derived from inverted resistivity exhibit remarkable consistency with well-log-based measurements. The high efficiency of the system confirms its potential for the transformative quantitative assessment of hydrate systems, seafloor massive sulfides, and marine geohazards. Full article

(This article belongs to the Special Issue Advances in Marine Gas Hydrate Exploration and Discovery—2nd Edition)

21 pages, 628 KB

Open AccessReview

Relationship Between Skin Temperature and Pressure Injuries: A Systematic Review

by Catalina Jimenez Cerquera, Rosa Nury Zambrano Bermeo and Jorge Eliecer Manrique Julio

Appl. Sci. 2025, 15(17), 9537; https://doi.org/10.3390/app15179537 (registering DOI) - 29 Aug 2025

Abstract

Background/Objectives: Skin temperature has been considered a physiological variable associated with the risk of pressure injuries. This systematic review analyzed the available evidence regarding the relationship between skin temperature and the development, progression, or prevention of pressure injuries in humans. Methods: A systematic search was conducted in the PubMed, Scopus, and Dimensions databases, including studies published between 2013 and 2023 in English or Spanish. PRISMA 2020 guidelines and EQUATOR network checklists (CONSORT, STROBE, CARE) were applied to assess methodological quality. Risk of bias was evaluated using RoB 2, ROBINS-I, ROBINS-E, and JBI tools. Results: The reviewed studies reported thermal variations in tissues subjected to sustained pressure, some of which preceded the appearance of visible clinical signs of tissue damage. However, methodological heterogeneity, lack of standardized thermal thresholds, and variability in measurement conditions limited the generalizability of the findings. Conclusions: Skin temperature may be associated with relevant pathophysiological mechanisms in the development of pressure injuries. Its measurement could complement traditional clinical tools, such as the Braden scale, enhancing early risk identification. More robust, multicenter, and standardized studies are needed to validate its clinical applicability. Full article

(This article belongs to the Section Applied Biosciences and Bioengineering)

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