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Listeria monocytogenes is a major public health concern in milk and ready-to-eat dairy products. To meet consumer demand for fresher, minimally processed foods with high nutritional and sensory quality, several non-thermal technologies are being explored as alternatives to conventional heat treatments. This systematic review (2020–2025), following PRISMA guidelines, examines recent applications of selected non-thermal technologies to control Listeria in milk and dairy matrices. Peer-reviewed studies available in full-text, in English or Spanish, focusing on applications at laboratory or pilot plant scales, with milk or dairy produced onsite or purchased, containing Listeria sp., were included. Studies with applications to plant-based or non-dairy products or those not inoculated with Listeria, were excluded. Conference abstracts, corrections, editorials, letters, news, and scientific opinions were excluded as well. The databases searched were Web of Science, Scopus, and ProQuest, which were last consulted in April 2025. Given the naturality of the review, the risk of bias was assessed through independent screening by two of the researchers, focusing on clear objectives, analytical validity, statistical analysis, and methodology. The results are presented in tabulated format. Of the 157 records identified, 22 were included in this review. Seven of the records reported hurdle technologies, while fifteen reported single technology applications, with high-pressure processing being the most frequent. Limitations observed are primarily the use of unreported strains, a lack of information regarding the initial load of inoculum, and expected log reductions. The equipment used is mostly at the laboratory scale, except for HPP. Non-thermal technologies present a promising option for the control of Listeria in dairy products. The basic principles of GMP, HACCP, and cold-chain control in dairy processing are of special importance in safety assurance. This research was funded by Vicerrectoría de Investigación, Universidad de Costa Rica, grant number 735-C3-460. Full article

(This article belongs to the Section Chemistry)

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Open AccessArticle

The Predicted Structure of S. cerevisiae Ssp1 Reveals Parallel Evolution in the Pil1 BAR Domain Family Proteins of Ascomycetes

by Yasuyuki Suda and Aaron M. Neiman

J. Fungi 2025, 11(9), 661; https://doi.org/10.3390/jof11090661 (registering DOI) - 9 Sep 2025

Abstract

BAR domains are a superfamily of widely conserved membrane binding motifs. In fungi, Pil1 family proteins are BAR domain containing proteins involved in organizing the plasma membrane. S. pombe encodes a sporulation-specific Pil1 family protein, Meu14, which has a specialized role in shaping the forespore membrane during sporulation. The functional analog of Meu14 in S. cerevisiae is Ssp1. While Ssp1 has no primary sequence homology to Pil1 or Meu14, AlphaFold predicts that it contains a Pil1-related BAR domain. Consistent with this structural prediction, mutation of residues in the putative lipid binding face of Ssp1 or in a residue implicated in multimerization disrupt sporulation. Characterization of the mutant proteins indicates that the BAR domain is necessary for recruitment of Ssp1 to the highly curved leading edge of the prospore membrane and multimerization of Ssp1 at that location is required for assembly of the leading edge complex. The distribution of Pil1 family proteins across an evolutionary tree of Ascomycetes reveals that Meu14 and Ssp1 arose independently in the lineages leading to S. pombe and S. cerevisiae, respectively. Full article

(This article belongs to the Special Issue Current and Future Development of Mycology: The 10th Anniversary of Journal of Fungi)

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Open AccessArticle

Assessment of Bacterial Presence Among New and “In Use” Resealable Biomaterials Within the Pediatric Dental Clinic

by Gavin Banning, Cindy Kim, Carter Wilkerson, Shelley J. Williams, Karl Kingsley and Victoria Sullivan

Hygiene 2025, 5(3), 42; https://doi.org/10.3390/hygiene5030042 (registering DOI) - 9 Sep 2025

Abstract

Background: Dental offices and clinics utilize a variety of dental materials that are delivered in reusable containers and dispensers. However, many of these materials, including NeoPutty, BC Putty, Flowable, and Diapex, may be subject to bacterial contamination and microbial exposures from the surrounding dental office environment. Objectives: The aim of this study was to quantify and identify microbial contamination, specifically in regard to these reusable dental materials. Methods: Surfaces of new and used reusable and resealable tubes where the material dispenses and the interior surfaces of the cap were swabbed and cultured. DNA was isolated from each sample and quantitative polymerase chain reaction (qPCR) was performed to determine the presence or absence of microbial contamination, as well as the relative abundance. Results: Microbial contamination was observed among all of the “in use” samples from both the dispensing end and the interior surfaces of the cap and was strongly associated with the amount of usage. Conclusions: These data suggest that environmental contamination may be present in measurable and quantifiable amounts on reusable and resealable dental materials, which suggest the need to create protocols for sanitizing the surfaces of reusable materials to reduce the presence of microbial contamination identified in similar clinical settings. Full article

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Open AccessArticle

Improving the Wear Properties of Ductile Iron by Introducing Ultrafine Graphite Nodules

by Chen Liu, Yuzhou Du, Haohao Li, Caiyin You, Chao Yang, Na Tian and Bailing Jiang

Lubricants 2025, 13(9), 399; https://doi.org/10.3390/lubricants13090399 (registering DOI) - 9 Sep 2025

Abstract

The tribological behavior of ferritic ductile iron without ultrafine graphite nodules (FDI) and ferritic ductile iron with ultrafine graphite nodules (FDI-UG) was investigated in the present study. Ultrafine graphite nodules with a count of 3400 nod/mm² were introduced by annealing treatment of quenched ductile iron, which effectively reduced the friction coefficient of ferritic ductile iron from approximately 0.3 to 0.15. This improvement was attributed to the ultrafine graphite nodules, which, due to their small spacing, facilitated a more uniform distribution on the tribological surface. Additionally, the formation of ultrafine graphite nodules in ferritized ductile iron refined the grain size (15 μm) and enhanced the hardness of ferritic ductile iron (183 HV), thereby significantly reducing abrasive wear. The more uniform graphite lubrication on the tribosurface and high hardness of fine ferrite grains in FDI-UG further enhanced wear resistance between the frictional pairs, effectively suppressing adhesion wear at high loads (6 N). Consequently, the ferritic ductile iron containing ultrafine graphite nodules and fine ferrite grains exhibited a superior wear resistance (6.84 × 10⁻³ mm³ and 9.47 × 10⁻³ mm³) compared to its untreated counterpart (9.22 × 10⁻³ mm³ and 11.95 × 10⁻³ mm³). These findings suggest that the incorporation of ultrafine graphite nodules was an effective strategy to enhance the tribological properties of ductile iron. Full article

(This article belongs to the Special Issue Advances in Wear-Resistant Fe-Based Materials)

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Open AccessArticle

Unsupervised Optical Mark Recognition on Answer Sheets for Massive Printed Multiple-Choice Tests

by Yahir Hernández-Mier, Marco Aurelio Nuño-Maganda, Said Polanco-Martagón, Guadalupe Acosta-Villarreal and Rubén Posada-Gómez

J. Imaging 2025, 11(9), 308; https://doi.org/10.3390/jimaging11090308 (registering DOI) - 8 Sep 2025

Abstract

The large-scale evaluation of multiple-choice tests is a challenging task from the perspective of image processing. A typical instrument is a multiple-choice question test that employs an answer sheet with circles or squares. Once students have finished the test, the answer sheets are digitized and sent to a processing center for scoring. Operators compute each exam score manually, but this task requires considerable time. While it is true that mature algorithms exist for detecting circles under controlled conditions, they may fail in real-life applications, even when using controlled conditions for image acquisition of the answer sheets. This paper proposes a desktop application for optical mark recognition (OMR) on the scanned multiple-choice question (MCQ) test answer sheets. First, we compiled a set of answer sheet images corresponding to 6029 exams (totaling 564,040 four-option answers) applied in 2024 in Tamaulipas, Mexico. Subsequently, we developed an image-processing module that extracts answers from the answer sheets and an interface for operators to perform analysis by selecting the folder containing the exams and generating results in a tabulated format. We evaluated the image-processing module, achieving a percentage of 96.15% of exams graded without error and 99.95% of 4-option answers classified correctly. We obtained these percentages by comparing the answers generated through our system with those generated by human operators, who took an average of 2 min to produce the answers for a single answer sheet, while the automated version took an average of 1.04 s. Full article

(This article belongs to the Special Issue Self-Supervised Learning for Image Processing and Analysis)

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Open AccessArticle

Porous Organosilica Films: Is It Possible to Enhance Hydrophobicity While Maintaining Elastic Stiffness?

by Alexey S. Vishnevskiy, Dmitry A. Vorotyntsev, Dmitry S. Seregin, Konstantin A. Vorotilov and Alexander S. Sigov

Polymers 2025, 17(17), 2433; https://doi.org/10.3390/polym17172433 (registering DOI) - 8 Sep 2025

Abstract

Organosilica films, composed of a silicon oxide network with terminal methyl groups, are widely utilized in various applications, including microelectronics. Many of these applications require high hydrophobicity and good mechanical properties, which pose a significant challenge because the Si–CH₃ groups disrupt the Si–O–Si network. This issue becomes particularly pronounced in porous films. Here, we investigate whether material properties can be tuned by simply altering the spatial arrangement of methyl groups. To achieve this, we prepared copolymer films with one or two methyl groups bonded to a silicon atom, while maintaining a constant total amount of methyl groups. The films were deposited using a sol–gel technique combined with template self-assembly. The precursor content was varied to compare films with different proportions of Si–CH₃ and Si(–CH₃)₂. Film characterization included FTIR, ellipsometric porosimetry, AFM, and WCA measurements and dielectric constant evaluations. Our findings indicate that precursors containing dimethyl groups enhance the connectivity of the Si–O–Si network, resulting in a higher Young’s modulus and smaller pore size compared to films with an equivalent amount of methyl groups. However, the lower thermal stability of dimethyl bonds limits the thermal budget of these films. Thus, the spatial arrangement of organic groups within the polymer structure can be employed to tune material properties. These results expand the understanding of organic–inorganic hybrid materials and offer novel approaches for their applications. Full article

(This article belongs to the Special Issue Silicon-Based Polymers: From Synthesis to Applications)

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Open AccessArticle

Hot Deformation Behavior and Processing Maps of Nitrogen-Containing 2Cr13 Corrosion-Resistant Plastic Die Steel

by Baoshuai Chu, Shengwei Cheng and Wen Yang

Metals 2025, 15(9), 998; https://doi.org/10.3390/met15090998 (registering DOI) - 8 Sep 2025

Abstract

To investigate the hot deformation behavior of nitrogen-containing 2Cr13 (2Cr13N) corrosion-resistant plastic mold steel, uniaxial compression tests were conducted at temperatures ranging from 850 to 1200 °C and strain rates between 0.01 and 10 s⁻¹. The results indicate that the flow stress exhibits pronounced peak characteristics under conditions of low strain rate and high temperature, with peak stress decreasing as deformation temperature increases and strain rate decreases. Using the Arrhenius model, a hot deformation equation was established, and activation energy for deformation was 454.85 kJ/mol. The processing diagram was constructed based on the dynamic material model (DMM) theory. The optimal hot working window was at 1050–1150 °C with a strain rate less than 0.05 s⁻¹ and at 1150–1200 °C with a strain rate greater than 2 s⁻¹, with excellent efficiency of power dissipation (η > 0.32) and lower values of Kernel Average misorientation (KAM) (1.2386 and 1.3095, respectively). Full article

(This article belongs to the Section Metal Casting, Forming and Heat Treatment)

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Open AccessArticle

Co-Served Dining by Humans and Automations: The Effects of Experience Quality in Intelligent Restaurants

by Liu Xu, Shiyi Zhang, Jose Weng Chou Wong and Jing (Bill) Xu

Sustainability 2025, 17(17), 8085; https://doi.org/10.3390/su17178085 (registering DOI) - 8 Sep 2025

Abstract

Automation has been widely applied and has greatly affected quality management in the catering industry. Intelligent restaurants refer to those in which smart devices and artificial intelligence (AI) technologies (such as robots and self-service technologies) are embedded in the restaurant environment. However, the existing research on intelligent restaurants has mostly focused on the technological development of equipment. Hence, this interdisciplinary study, integrating insights from hospitality management and human–computer interaction, examines how human-provided and automated-provided services interactively influence customers’ dining experience quality in intelligent restaurants, and how they affect customers’ perceived value and their social media sharing generation. This study develops a measurement scale of dining experience quality in intelligent restaurants that contains human-provided experience and automated-provided experience through in-depth interviews with 15 customers (Study1), and a model was proposed and verified using partial least-squares structural equation modelling (PLS-SEM) analysis on a sample of 493 customers dining in intelligent restaurants (Study 2), which shows that the quality of dining experience has a positive effect on customer perceived value, overall satisfaction in intelligent restaurants, and social media sharing generation. Specifically, automated-provided services offer functional value, while human employees mainly provide perceived emotional value. Perceived functional value has a greater impact on overall satisfaction with intelligent restaurants. The originality of this research is that it integrates services provided by humans and services provided by automated devices and clarifies the different roles of functional and emotional value in shaping customers’ perceived value. These findings provide a new research perspective for intelligent restaurants and insight into the optimization of service quality and automation systems in intelligent restaurants, thereby promoting sustainable business practices in the industry. Full article

(This article belongs to the Special Issue Interdisciplinary Approaches to Sustainable Tourism)

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Open AccessArticle

A Novel Lactobacillus acidophilus Strain Isolated from a 2-Month-Old Shiba Inu: In Vitro Probiotic Evaluation Safety Assessment in Mice and Whole-Genome Sequencing Analysis

by Huiming Huang, Xiaoling Tang, Yichuan Zhang, Mengyao Chen and Min Wen

Microorganisms 2025, 13(9), 2095; https://doi.org/10.3390/microorganisms13092095 (registering DOI) - 8 Sep 2025

Abstract

Owing to their remarkable biological activities and health benefits, probiotics have gained widespread application in enhancing pet health and welfare. Host-derived probiotics are considered optimal due to their unique digestive tract environments. This study isolated Lactobacillus acidophilus L1 from the feces of a 2-month-old Shiba Inu puppy and conducted a comprehensive evaluation of its potential as a probiotic candidate for pet health. Strain L1 demonstrated high tolerance to acidic conditions (survival rates of 90.41%, 92.90% and 98.81% at pH 2, 2.5, and 3.0, respectively) and bile salts (survival rates of 98.05%, 95.68%, and 82.21% at 0.1%, 0.2%, and 0.3% concentrations, respectively). Adhesion to Caco-2 intestinal epithelial cells reached 38.33%, with hydrophobicity of 97.81% and auto-aggregation of 32.28%. L1 also displayed pronounced antioxidant activity, with DPPH and ABTS radical scavenging rates of 71.15% and 83.20%. Both the bacterial suspension and the cell-free supernatant had potent inhibition of pathogenic bacteria, while the strain showed a non-hemolytic phenotype and remained sensitive to clinically relevant antibiotics (e.g., penicillin). On the other hand, animal experiments conducted in ICR mice (randomly divided into four groups) demonstrated that oral administration of L1 had no toxic effects on the mice and increased serum SOD and CAT levels, while reducing MDA levels. Furthermore, whole-genome sequencing revealed that L1 is 2,106,895 bp in size and contains 2098 coding sequences, two CRISPR arrays, ten genomic islands, and two prophage regions. Collectively, the in vitro and in vivo data presented here indicate that L. acidophilus L1, originally isolated from canine feces, supports further evaluation as a candidate strain for incorporation into functional pet foods. Full article

(This article belongs to the Special Issue Probiotics, Pebiotics and Pet Health)

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Open AccessArticle

Removal of Ciprofloxacin from Pharmaceutical Wastewater Using Untreated and Treated Eggshells as Biosorbents

by Maryam Bin Hammad, Sameer Al-Asheh and Mohamed Abouleish

Water 2025, 17(17), 2656; https://doi.org/10.3390/w17172656 (registering DOI) - 8 Sep 2025

Abstract

Pharmaceutical wastewater contains high levels of organic matter, salts, and toxic compounds that are resistant to conventional treatment methods. Even after secondary treatment, traces of dissolved organics and suspended solids often remain, contributing to environmental concerns such as increased microbial resistance and harm to aquatic life. This study introduces a sustainable “waste-to-treat-waste” approach that utilizes discarded white chicken eggshells as a low-cost biosorbent for removing ciprofloxacin, a common antibiotic. Unlike previous eggshell-based adsorption studies that primarily targeted dyes or heavy metals, this work demonstrates the first comprehensive evaluation of both untreated and chemically/thermally modified eggshells for antibiotic removal from real pharmaceutical wastewater. Batch adsorption experiments under optimized conditions showed removal efficiencies of 85% for raw eggshells, 91% after HCl activation, and 96% after thermal conversion to CaO. Batch adsorption experiments under optimized conditions (pH 7, 25 °C, 625 µm particle size, 3 g/100 mL dose, 90 min contact time) showed maximum adsorption capacities of 23.75 mg/g for untreated ES, 4.08 mg/g after HCl activation, and 1.82 mg/g after thermal conversion to CaO, with removal efficiencies of 85%, 91%, and 96%, respectively. The simplicity of preparation, use of an abundant waste material, and high removal efficiency highlight the potential for scalable cost-effective applications in industrial wastewater treatment systems. Full article

(This article belongs to the Special Issue Adsorption Technologies in Wastewater Treatment Processes—2nd Edition)

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Open AccessArticle

Distributionally Robust Chance-Constrained Task Assignment for Heterogeneous UAVs with Time Windows Under Uncertain Fuel Consumption

by Zhichao Gao, Mingfa Zheng, Yu Mei, Aoyu Zheng and Haitao Zhong

Drones 2025, 9(9), 633; https://doi.org/10.3390/drones9090633 (registering DOI) - 8 Sep 2025

Abstract

This paper addresses the cooperative task assignment problem for heterogeneous unmanned aerial vehicles with time windows considering uncertain fuel consumption. In the scenario where probabilistic fuel consumption exists and its distribution needs to be estimated from historical data samples, we first formulate the problem as a chance-constrained combinatorial optimization problem and utilize the sample average approximation method to solve it. Further, to address the issue of ambiguous distribution, we introduce distributionally robust chance constraints, which consider a set of probability distributions that are contained within a 1-Wasserstein ball centered around the empirical distribution of field data. We approximate the distributionally robust chance-constrained cooperative task assignment problem by applying a CVaR-based tractable approximation such that the problem can be transformed into a deterministic mixed-integer linear programming problem, which can be efficiently solved by state-of-the-art optimization solvers. Finally, we conduct a series of numerical experiments, which not only verify the computational efficiency of the distributionally robust chance-constrainted models but also reduce the degree of constraint violation in out-of-sample tests compared with a sample average approximation method. Full article

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Open AccessArticle

Methods for Untargeted Analysis of Milk Metabolites: Influence of Extraction Method and Optimization of Separation

by Daisy Wilkie, Brad White, Golnaz Heidari, Rafea Naffa, Gaile Peddie, Gareth J. Rowlands and Paul G. Plieger

Metabolites 2025, 15(9), 597; https://doi.org/10.3390/metabo15090597 (registering DOI) - 8 Sep 2025

Abstract

Background/Objectives: Cow’s milk is a complex food, and research into its metabolome can provide information useful in the study of animal health, farming practices, food safety and the adulteration of milk. Comparative interlaboratory metabolic analysis is hampered by the lack of standardized methods—a requirement addressed in this study. Methods: We studied the influence of the chromatography column and extraction solvent on the metabolites isolated during untargeted metabolomics. Results: After studying fifteen columns and four extraction solvents, it was determined that an HILIC column offered the best compromise between retention time and separation of metabolites. Each extraction solvent covered a different area of the metabolome, only overlapping with previously annotated compounds. Extraction mixtures containing methanol tend to give better recovery. Conclusions: The choice of extraction solvent was crucial when looking at the difference between samples, but if interest lies only in previously annotated compounds, then there is little difference between the solvents. Full article

(This article belongs to the Section Food Metabolomics)

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Open AccessArticle

Improving Anti-Corrosion and Conductivity of NiTi Alloy Bipolar Plate Used for PEMFCs via Nb Alloying

by Ziyang Niu, Yingping Li, Yuanyuan Li, Xiaofen Wang, Yumin Pan, Zhuo He, Guohong Zhang, Zhen Wang and Qiongyu Zhou

Molecules 2025, 30(17), 3658; https://doi.org/10.3390/molecules30173658 (registering DOI) - 8 Sep 2025

Abstract

NiTi alloy has emerged as a promising bipolar plate (BP) material for proton exchange membrane fuel cells (PEMFCs), combining Ti-like corrosion resistance with Ni-like electrical conductivity through its intermetallic characteristics. However, its performance faces greater challenges under aggressive operating conditions (70 °C, F⁻-containing acidic solution with air bubbling). This study demonstrates that Nb alloying effectively enhances NiTi while preserving its balanced properties. The developed NiTiNb alloy exhibits improved performance with 26% lower corrosion current density (i_c) and 29% reduced interfacial contact resistance (ICR) compared to conventional NiTi, effectively overcoming the conventional corrosion–conductivity trade-off in metallic BPs. The alloy also shows superior electrochemical stability and microhardness relative to pure Ti and Ni. These enhancements stem from a unique dual-phase microstructure comprising a NiTi (B2) matrix with continuous β-Nb grain boundary networks. During operation, this structure enables in situ formation of protective TiO₂-Nb₂O₅ films while maintaining conductive Nb/Nb₂O₅ pathways and metallic Ni domains. The findings establish Nb alloying as a viable optimization strategy for NiTi-based BP substrate in demanding PEMFC applications. Full article

(This article belongs to the Special Issue Electroanalysis of Biochemistry and Material Chemistry—2nd Edition)

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Open AccessSystematic Review

Propolis as a Natural Remedy in Reducing Dental Plaque and Gingival Inflammation: A Systematic Review and Meta-Analysis

by Magdalena Sycińska-Dziarnowska, Liliana Szyszka-Sommerfeld, Monika Bugajska, Magdalena Ziąbka, Izabela Szućko-Kociuba, Gianrico Spagnuolo, Krzysztof Woźniak and Hyo-Sang Park

J. Funct. Biomater. 2025, 16(9), 336; https://doi.org/10.3390/jfb16090336 (registering DOI) - 8 Sep 2025

Abstract

Dental plaque, if not regularly removed through proper oral hygiene, can lead to tooth decay, gingivitis, and more severe periodontal disease. Effective plaque removal is essential in preventing gingivitis, the precursor to periodontitis. Propolis, a bee product known for its antibacterial, anti-inflammatory, and antioxidant properties, has shown potential in dental applications. This systematic review and meta-analysis was conducted to evaluate the efficacy of propolis-containing mouthwashes and toothpastes in reducing dental plaque and gingival inflammation. Materials and Methods: The study protocol was registered in PROSPERO (CRD42023467573), and the review was conducted in accordance with PRISMA guidelines. A comprehensive search of PubMed, PubMed Central, Embase, Scopus, and Web of Science was performed up to 10 May 2025 to identify randomized controlled trials and observational studies assessing propolis-based mouthwashes or toothpastes. Data synthesis used random-effects meta-analysis due to anticipated heterogeneity among studies. Results: Seven randomized controlled trials were included in the meta-analysis, evaluating the efficacy of propolis alcohol-free mouthwash on plaque index (PI) and gingival index (GI). For PI, the pooled standardized mean difference (SMD) was 1.74 (95% CI: 0.19–3.29; p = 0.036), with low between-study heterogeneity (I² = 13.7%). For GI, the pooled SMD was 2.19 (95% CI: 1.10–3.29; p = 0.005), with no observed heterogeneity (I² = 0.0%). Propolis mouthwashes demonstrated large effect sizes, significantly reducing plaque accumulation and gingival inflammation compared to baseline. Conclusions: The evidence supports the potential of propolis-containing mouthwashes and toothpastes in managing dental plaque and gingival health. Propolis-based oral care products could be a valuable addition to preventive strategies in dental hygiene, offering an alternative for reducing dental plaque and gingival inflammation. Full article

(This article belongs to the Special Issue Dental Biomaterials in Implantology and Orthodontics)

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Open AccessArticle

An Extension of Input Setup Assistance Service Using Generative AI to Unlearned Sensors for the SEMAR IoT Application Server Platform

by I Nyoman Darma Kotama, Nobuo Funabiki, Yohanes Yohanie Fridelin Panduman, Komang Candra Brata, Anak Agung Surya Pradhana and Noprianto

IoT 2025, 6(3), 52; https://doi.org/10.3390/iot6030052 (registering DOI) - 8 Sep 2025

Abstract

Nowadays, Internet of Things (IoT) application systems are broadly applied to various sectors of society for efficient management by monitoring environments using sensors, analyzing sampled data, and giving proper feedback. For their fast deployment, we have developed Smart Environmental Monitoring and Analysis in Real Time (SEMAR) as an integrated IoT application server platform and implemented the input setup assistance service using prompt engineering and a generative AI model to assist connecting sensors to SEMAR with step-by-step guidance. However, the current service cannot assist in connections of the sensors not learned by the AI model, such as newly released ones. To address this issue, in this paper, we propose an extension to the service for handling unlearned sensors by utilizing datasheets with four steps: (1) users input a PDF datasheet containing information about the sensor, (2) key specifications are extracted from the datasheet and structured into markdown format using a generative AI, (3) this data is saved to a vector database using chunking and embedding methods, and (4) the data is used in Retrieval-Augmented Generation (RAG) to provide additional context when guiding users through sensor setup. Our evaluation with five generative AI models shows that OpenAI’s GPT-4o achieves the highest accuracy in extracting specifications from PDF datasheets and the best answer relevancy (0.987), while Gemini 2.0 Flash delivers the most balanced results, with the highest overall RAGAs score (0.76). Other models produced competitive but mixed outcomes, averaging 0.74 across metrics. The step-by-step guidance function achieved a task success rate above 80%. In a course evaluation by 48 students, the system improved the student test scores, further confirming the effectiveness of our proposed extension. Full article

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