MDPI - Publisher of Open Access Journals

19 pages, 1161 KB

Open AccessEntry

Toward an Integrated Model of Reading: Bridging Lexical Quality and Comprehension Systems

by Jessica Sishi Fei and Min Wang

Encyclopedia 2026, 6(1), 23; https://doi.org/10.3390/encyclopedia6010023 (registering DOI) - 19 Jan 2026

This entry introduces an integrated model of reading that situates the Lexical Quality Hypothesis (LQH) within the Reading Systems Framework (RSF). The LQH posits that skilled reading depends on high-quality lexical representations—precise and flexible mappings of orthographic, phonological, morpho-syntactic, and semantic features—stored in [...] Read more.

This entry introduces an integrated model of reading that situates the Lexical Quality Hypothesis (LQH) within the Reading Systems Framework (RSF). The LQH posits that skilled reading depends on high-quality lexical representations—precise and flexible mappings of orthographic, phonological, morpho-syntactic, and semantic features—stored in the mental lexicon. These representations facilitate automatic word identification, accurate meaning retrieval, and efficient word-to-text integration (WTI), forming the foundation of text comprehension. Extending this micro-level perspective, the RSF positions lexical quality (LQ) within a macro-level cognitive architecture where the lexicon bridges word identification and reading comprehension systems. The RSF integrates multiple knowledge systems (linguistic, orthographic, and general world knowledge) with higher-order processes (sentence parsing, inference generation, comprehension monitoring, and situation model construction), emphasizing the bidirectional interactions between lower-level lexical knowledge and higher-order text comprehension. Central to this model is WTI, a dynamic mechanism through which lexical representations are incrementally incorporated into a coherent mental model of the text. This integrated model carries important implications for theory refinement, empirical investigation, and evidence-based instructional practices. Full article

(This article belongs to the Section Behavioral Sciences)

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15 pages, 3172 KB

Open AccessArticle

Accelerating the Measurement of Fatigue Crack Growth with Incremental Information-Based Machine Learning Approach

by Cheng Wen, Haipeng Lu, Yiliang Wang, Meng Wang, Yuwan Tian, Danmei Wu, Yupeng Diao, Jiezhen Hu and Zhiming Zhang

Materials 2026, 19(2), 396; https://doi.org/10.3390/ma19020396 (registering DOI) - 19 Jan 2026

Abstract

Measuring the fatigue crack growth rate via the crack growth experiment (a-N curve) is labor-intensive and time-consuming. A machine learning interpolation–extrapolation strategy (MLIES) aimed at enhancing the prediction accuracy of small-data models has been proposed to accelerate fatigue testing. Two [...] Read more.

Measuring the fatigue crack growth rate via the crack growth experiment (a-N curve) is labor-intensive and time-consuming. A machine learning interpolation–extrapolation strategy (MLIES) aimed at enhancing the prediction accuracy of small-data models has been proposed to accelerate fatigue testing. Two specific approaches are designed by transforming a-N curve data from N to ΔN and from a to Δa (S1)/Δa/ΔN (S2) to enrich the data volume and leverage the incremental information. Thus, a simple and fast-responding single-layer neural network model can be trained based on the early-stage data points from fatigue testing and accurately predict the remaining part of an a-N curve, thereby enhancing the experimental efficiency. Through exponential data expansion and data augmentation, the trained neural network model is able to learn the underlying rules governing crack growth directly from the experimental data, requiring no explicit analytical crack growth laws. The proposed MLIES was validated on fatigue tests for aluminum alloy and titanium alloy samples under different experimental parameters. Results demonstrate its effectiveness in reducing testing time/cost by 15–32% while achieving over 30% higher prediction accuracy for the a-N curve compared to a traditional machine learning modeling approach. Our research offers a data-driven recipe for accurate crack growth prediction and accelerated fatigue testing. Full article

(This article belongs to the Section Materials Simulation and Design)

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16 pages, 6135 KB

Open AccessArticle

Interlayer Identification Method Based on SMOTE and Ensemble Learning

by Shengqiang Luo, Bing Yu, Tianrui Zhang, Junqing Rong, Qing Zeng, Tingting Feng and Jianpeng Zhao

Processes 2026, 14(2), 351; https://doi.org/10.3390/pr14020351 (registering DOI) - 19 Jan 2026

Abstract

The interlayer is a key geological factor that regulates reservoir heterogeneity and remaining oil distribution, and its accurate identification directly affects the reservoir development effect. To address the strong subjectivity of traditional identification methods and the insufficient recognition accuracy of single machine learning [...] Read more.

The interlayer is a key geological factor that regulates reservoir heterogeneity and remaining oil distribution, and its accurate identification directly affects the reservoir development effect. To address the strong subjectivity of traditional identification methods and the insufficient recognition accuracy of single machine learning models under imbalanced sample distributions, this study focuses on three types of interlayers (argillaceous, calcareous, and petrophysical interlayers) in the W Oilfield, and proposes an accurate identification method integrating the Synthetic Minority Over-Sampling Technique (SMOTE) and heterogeneous ensemble learning. Firstly, the corresponding data set of interlayer type and logging response is established. After eliminating the influence of dimension using normalization, the sensitive logging curves are optimized using the crossplot method, mutual information, and effect analysis. SMOTE technology is used to balance the sample distribution and solve the problem of the identification deviation of minority interlayers. Then, a heterogeneous ensemble model composed of the k-nearest neighbor algorithm (KNN), decision tree (DT), and support vector machine (SVM) is constructed, and the final recognition result is output using a voting strategy. The experiments show that SMOTE technology improves the average accuracy of a single model by 3.9% and effectively improves the model bias caused by sample imbalance. The heterogeneous integration model improves the overall recognition accuracy to 92.6%, significantly enhances the ability to distinguish argillaceous and petrophysical interlayers, and optimizes the F1-Score simultaneously. This method features a high accuracy and reliable performance, providing robust support for interlayer identification in reservoir geological modeling and remaining oil potential tapping, and demonstrating prominent practical application value. Full article

(This article belongs to the Special Issue Advances in Improving Efficiency, Decarbonization, Modeling and Intelligent Operations of Modern Oilfield Development)

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18 pages, 2295 KB

Open AccessArticle

Automatic Retinal Nerve Fiber Segmentation and the Influence of Intersubject Variability in Ocular Parameters on the Mapping of Retinal Sites to the Pointwise Orientation Angles

by Diego Luján Villarreal and Adriana Leticia Vera-Tizatl

J. Imaging 2026, 12(1), 47; https://doi.org/10.3390/jimaging12010047 (registering DOI) - 19 Jan 2026

Abstract

The current study investigates the influence of intersubject variability in ocular characteristics on the mapping of visual field (VF) sites to the pointwise directional angles in retinal nerve fiber layer (RNFL) bundle traces. In addition, the performance efficacy on the mapping of VF [...] Read more.

The current study investigates the influence of intersubject variability in ocular characteristics on the mapping of visual field (VF) sites to the pointwise directional angles in retinal nerve fiber layer (RNFL) bundle traces. In addition, the performance efficacy on the mapping of VF sites to the optic nerve head (ONH) was compared to ground truth baselines. Fundus photographs of 546 eyes of 546 healthy subjects (with no history of ocular disease or diabetic retinopathy) were enhanced digitally and RNFL bundle traces were segmented based on the Personalized Estimated Segmentation (PES) algorithm’s core technique. A 24-2 VF grid pattern was overlaid onto the photographs in order to relate VF test points to intersecting RNFL bundles. The PES algorithm effectively traced RNFL bundles in fundus images, achieving an average accuracy of 97.6% relative to the Jansonius map through the application of 10th-order Bezier curves. The PES algorithm assembled an average of 4726 RNFL bundles per fundus image based on 4975 sampling points, obtaining a total of 2,580,505 RNFL bundles based on 2,716,321 sampling points. The influence of ocular parameters could be evaluated for 34 out of 52 VF locations. The ONH-fovea angle and the ONH position in relation to the fovea were the most prominent predictors for variations in the mapping of retinal locations to the pointwise directional angle (p < 0.001). The variation explained by the model (R² value) ranges from 27.6% for visual field location 15 to 77.8% in location 22, with a mean of 56%. Significant individual variability was found in the mapping of VF sites to the ONH, with a mean standard deviation (95% limit) of 16.55° (median 17.68°) for 50 out of 52 VF locations, ranging from less than 1° to 44.05°. The mean entry angles differed from previous baselines by a range of less than 1° to 23.9° (average difference of 10.6° ± 5.53°), and RMSE of 11.94. Full article

(This article belongs to the Section Medical Imaging)

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16 pages, 1998 KB

Open AccessArticle

Identification and Characterization of Botryosphaeria dothidea Associated with Sweet Cherry (Prunus avium L.) Branch Dieback Disease in Greenhouses of Liaoning, China

by Qidong Dai, Qijing Zhang, Yao Chen, Feng Cai, Mingli He and Jiayin Ai

Biology 2026, 15(2), 183; https://doi.org/10.3390/biology15020183 (registering DOI) - 19 Jan 2026

Abstract

Between 2022 and 2024, a severe branch dieback disease was observed affecting over 6% of sweet cherry trees of the ‘Tieton’ cultivar in commercial greenhouses in southern Liaoning Province, China. Symptoms primarily occurred at the top of young branches. At the early stage [...] Read more.

Between 2022 and 2024, a severe branch dieback disease was observed affecting over 6% of sweet cherry trees of the ‘Tieton’ cultivar in commercial greenhouses in southern Liaoning Province, China. Symptoms primarily occurred at the top of young branches. At the early stage of disease onset, the lesions appeared as dark brown, irregularly shaped areas with a moist surface; as the disease progressed, these lesions turned dry and rotten, leading to tree decline symptoms in sweet cherry trees. Disease diagnosis was carried out in sweet cherry greenhouses across Liaoning Province, where 24 diseased samples were collected and 14 fungal isolates were obtained therefrom. Based on morphological traits, cultural characteristics, and multi-locus phylogenetic analyses of the internal transcribed spacer (ITS) region, beta-tubulin (TUB2) gene, and translation elongation factor 1-α (TEF1) gene, these isolates were identified as Botryosphaeria dothidea. Two representative isolates, namely zdcy-1 and zdcy-2, were selected for pathogenicity assays. Both mycelial plug and spore suspension inoculation methods confirmed the pathogenicity of the pathogen. The biological characteristic assays revealed that the optimal temperature range for the pathogen’s mycelial growth on PDA medium was 25–28 °C, and the optimal pH range was 6.0–8.0. This study improves the understanding of branch dieback disease in sweet cherry orchards in China, enriches the knowledge regarding the geographical distribution, host range, and infection sites of the pathogen, and provides novel insights for the management of sweet cherry diseases. Full article

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24 pages, 7155 KB

Open AccessReview

Advances in Plant Mediated Iron Oxide Nanoparticles for Dye Colorant Degradation—A Review

by Louisah Mmabaki Mahlaule-Glory and Nomso Charmaine Hintsho-Mbita

Colorants 2026, 5(1), 3; https://doi.org/10.3390/colorants5010003 (registering DOI) - 19 Jan 2026

Abstract

Water polluted by dye colorants has been on the rise in the last decade. This is due to the over reliance on the textile industry, and it is holding a high economic value in most countries. This industry is the highest consumer of [...] Read more.

Water polluted by dye colorants has been on the rise in the last decade. This is due to the over reliance on the textile industry, and it is holding a high economic value in most countries. This industry is the highest consumer of fresh water whilst also discharging several natural and synthetic pollutants to the environment. Several methods have been used for the removal of these pollutants and one of the most efficient technologies to be developed includes the photocatalysis method, via advanced oxidation processes. This review highlights the developments of green iron oxide nanoparticles as photocatalysts in the last decade. It was noted that tuning and controlling the phytochemical concentration and synthesis conditions, can assist with forming uniform and non-agglomerated materials, as this has limited the vast usage of these materials in major applications. Also, upon controlling the synthesis conditions, improved surface area and charge separation efficiency was noted. Their limitations and need for modification through forming composites are highlighted. Moreover, future perspectives are given on the use of green IONPs as photocatalysts. Full article

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18 pages, 293 KB

Open AccessReview

Academic Integrity and Cheating in Dental Education: Prevalence, Drivers, and Career Implications

by Akhilesh Kasula, Gadeer Zahran, Undral Munkhsaikhan, Vivian Diaz, Michelle Walker, Candice Johnson, Kathryn Lefevers, Ammaar H. Abidi and Modar Kassan

Dent. J. 2026, 14(1), 65; https://doi.org/10.3390/dj14010065 (registering DOI) - 19 Jan 2026

Abstract

Background: Integrity, encompassing honesty, accountability, and ethical conduct, is a cornerstone of the dental profession, essential for patient trust and safety. Despite its importance, academic dishonesty remains a pervasive issue in dental education globally. This review examines the prevalence, causes, and long-term [...] Read more.

Background: Integrity, encompassing honesty, accountability, and ethical conduct, is a cornerstone of the dental profession, essential for patient trust and safety. Despite its importance, academic dishonesty remains a pervasive issue in dental education globally. This review examines the prevalence, causes, and long-term career implications of academic dishonesty in dental education and explores institutional strategies to cultivate a culture of integrity. Method: The study was conducted using PubMed, Scopus, Web of Science, and Google Scholar to identify studies published between 1970 and 2025 on academic dishonesty in dental education. Search terms included dental students, cheating, plagiarism, and clinical falsification. Eligible studies reported prevalence, drivers, or consequences of dishonest behaviors. Data were extracted and thematically synthesized to highlight common patterns and professional implications. Results: Self-reported data indicate alarmingly high rates of cheating among dental students, ranging from 43% to over 90%. Common forms include exam fraud, plagiarism, and the falsification of clinical records. Key drivers include intense academic pressure, competitive environments, and a perception of weak enforcement. Such behaviors are not merely academic violations—they have profound professional consequences. A history of academic dishonesty can damage a student’s reputation, hinder licensure and credentialing processes, and limit postgraduate opportunities. Crucially, studies indicate that unethical behavior in school can normalize dishonesty, predicting a higher likelihood of future professional misconduct, such as insurance fraud or malpractice, thereby jeopardizing patient care and public trust. Conclusions: Academic integrity is a critical predictor of professional ethical conduct. Dental schools must move beyond punitive policies to implement proactive, multi-faceted approaches. This includes integrating comprehensive ethics curricula, fostering reflective practice, promoting faculty role modeling, and empowering student-led initiatives to uphold honor codes. Cultivating an unwavering culture of integrity is essential not only for academic success but for developing trustworthy practitioners committed to lifelong ethical patient care. Full article

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Graphical abstract

16 pages, 3075 KB

Open AccessArticle

Liner Wear Evaluation of Jaw Crushers Based on Binocular Vision Combined with FoundationStereo

by Chuyu Wen, Zhihong Jiang, Zhaoyu Fu, Quan Liu and Yifeng Zhang

Appl. Sci. 2026, 16(2), 998; https://doi.org/10.3390/app16020998 (registering DOI) - 19 Jan 2026

Abstract

To address the bottlenecks of traditional jaw crusher liner wear detection—high safety risks, insufficient precision, and limited full-range analysis—this paper proposes a non-contact, high-precision wear analysis method based on binocular vision and deep learning. At its core is the integration of the state-of-the-art [...] Read more.

To address the bottlenecks of traditional jaw crusher liner wear detection—high safety risks, insufficient precision, and limited full-range analysis—this paper proposes a non-contact, high-precision wear analysis method based on binocular vision and deep learning. At its core is the integration of the state-of-the-art FoundationStereo zero-shot stereo matching algorithm, following scenario-specific adaptations, into the 3D reconstruction of industrial liners for wear analysis. A novel wear quantification methodology and corresponding indicator system are also proposed. After calibrating the ZED2 binocular camera and fine-tuning the algorithm, FoundationStereo achieves an Endpoint Error (EPE) of 0.09, significantly outperforming traditional algorithms. To meet on-site efficiency requirements, a “single-view rapid acquisition + CUDA engineering acceleration” strategy is implemented, reducing point cloud generation latency from 165 ms to 120 ms by rewriting kernel functions and optimizing memory access patterns. Geometric accuracy verification shows a Mean Absolute Error (MAE) ≤ 0.128 mm, fully meeting industrial measurement standards. A complete process of “3D reconstruction–model registration–quantitative analysis” is constructed, utilizing three core indicators (maximum wear depth, average wear depth, and wear area ratio) to characterize liner wear. Statistical results—such as an average maximum wear depth of 55.05 mm—are highly consistent with manual inspection data, providing a safe, efficient, and precise digital solution for the predictive maintenance and intelligent operation and maintenance (O&M) of liners. Full article

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17 pages, 4177 KB

Open AccessArticle

Inline Profiling of Reactive Thermoplastic Pultruded GFRP Rebars: A Study on the Influencing Factors

by Moritz Fünkner, Georg Zeeb, Michael Wilhelm, Peter Eyerer and Frank Henning

J. Compos. Sci. 2026, 10(1), 55; https://doi.org/10.3390/jcs10010055 (registering DOI) - 19 Jan 2026

Abstract

Compared to reinforcing concrete with steel bars, rebars—made of fiber-reinforced plastic—have a high potential for resource savings in the construction industry due to their corrosion resistance. For the large-volume market of reinforcement elements, efficient manufacturing processes must be developed to ensure the best [...] Read more.

Compared to reinforcing concrete with steel bars, rebars—made of fiber-reinforced plastic—have a high potential for resource savings in the construction industry due to their corrosion resistance. For the large-volume market of reinforcement elements, efficient manufacturing processes must be developed to ensure the best possible bond behavior between concrete and rebar. In contrast to established FRP-rebars made with thermosetting materials, the use of a thermoplastic matrix enables surface profiling without severing the edge fibers as well as subsequent bending of the bar. The rebars to be produced in this study are based on the process of reactive thermoplastic pultrusion of continuously glass fiber reinforced aPA6. Their surface must enable a mechanical interlocking between the reinforcement bar and concrete. Concepts for a profiling device have been methodically developed and evaluated. The resulting concept of a double wheel embossing unit with a variable infeed and an infrared preheating section is built as a prototype, implemented in a pultrusion line, and further optimized. For a comprehensive understanding of the embossing process, reinforcement bars are manufactured, characterized, and evaluated under parameter variation according to a statistical experimental plan. The present study demonstrates the relationship between the infeed, preheating temperature, and haul-off speed with respect to the embossing depth, which is equivalent to the rib height. No degradation of the Young’s modulus was observed as a result of the profiling process. Full article

(This article belongs to the Section Composites Manufacturing and Processing)

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33 pages, 326 KB

Open AccessArticle

Intelligent Risk Identification in Construction Projects: A Case Study of an AI-Based Framework

by Kristijan Vilibić, Zvonko Sigmund and Ivica Završki

Buildings 2026, 16(2), 409; https://doi.org/10.3390/buildings16020409 (registering DOI) - 19 Jan 2026

Abstract

Risk management in large-scale construction projects is a critical yet complex process influenced by financial, safety, environmental, scheduling, and regulatory uncertainties. Effective risk management contributes directly to project optimization by minimizing disruptions, controlling costs, and enhancing decision-making efficiency. Early identification and mitigation of [...] Read more.

Risk management in large-scale construction projects is a critical yet complex process influenced by financial, safety, environmental, scheduling, and regulatory uncertainties. Effective risk management contributes directly to project optimization by minimizing disruptions, controlling costs, and enhancing decision-making efficiency. Early identification and mitigation of risks allow resources to be allocated where they have the greatest effect, thereby optimizing overall project outcomes. However, conventional methods such as expert judgment and probabilistic modeling often struggle to process extensive datasets and complex interdependencies among risk factors. This study explores the potential of an AI-based framework for risk identification, utilizing artificial intelligence to analyze project documentation and generate a preliminary set of identified risks. The proposed methodology is implemented on the ‘Trg pravde’ judicial infrastructure project in Zagreb, Croatia, applying AI models (GPT-5, Gemini 2.5, Sonnet 4.5) to identify phase-specific risks throughout the project lifecycle. The approach aims to improve the efficiency of risk identification, reduce human bias, and align with established project management methodologies such as PM². Initial findings suggest that the use of AI may broaden the range of identified risks and support more structured risk analysis, indicating its potential value as a complementary tool in risk management processes. However, human expertise remains crucial for prioritization, contextual interpretation, and mitigation. The study demonstrates that AI augments, rather than replaces, traditional risk management practices, enabling more proactive and data-driven decision-making in construction projects. Full article

(This article belongs to the Special Issue Applying Artificial Intelligence in Construction Management)

15 pages, 2462 KB

Open AccessArticle

The Effects of Different Substrates in Pond Net Cages on the Succession of Periphyton and the Seedling Protection of Sea Cucumber Apostichopus japonicus

by Yanqing Wu, Liming Liu, Rongbin Du, Wengang Xu, Bo Qin, Na Ying and Bianbian Zhang

Biology 2026, 15(2), 182; https://doi.org/10.3390/biology15020182 (registering DOI) - 19 Jan 2026

Abstract

With the industry development of sea cucumber Apostichopus japonicus aquaculture, the indoor high cost and low survival rate have become serious problems. Therefore, it is necessary to optimize substrate selection for seedling protection in outdoor pond net cages. This study explores the succession [...] Read more.

With the industry development of sea cucumber Apostichopus japonicus aquaculture, the indoor high cost and low survival rate have become serious problems. Therefore, it is necessary to optimize substrate selection for seedling protection in outdoor pond net cages. This study explores the succession of periphyton on the different substrate surface types, including a curvimurate net (CU), nylon mesh (NM), and ground cages (including a ground cage net (CN) and ground cage plate (CP)), and their effects on the seedling protection of sea cucumbers. In addition, we monitored the substrates’ dry weight, chlorophyll-a, and the community composition of substrates, alongside seedling growth, yield, and survival rate. The results show that a total of 7 phyla, 23 genera, and 31 species were detected on the substrates, with diatoms dominating (19 species) and Chlorophyta (4 species) being the main species. The CU had the highest total number of alga species attached, significantly higher than the other substrates in week 13 (p < 0.05). In week 9, the diatom density dropped to its lowest point, and, after September, it rose with the decrease in water temperature. In terms of dry weight with and without ash, CP increased rapidly in the early stage, with NM, CU, and CP being significantly higher than CN in week 13 (p < 0.05). The chlorophyll-a content showed a decreasing–increasing–decreasing trend, with CU reaching 3.62 ± 0.48 μg/cm² in the 13th week, significantly higher than other substrates (p < 0.05). Finally, the A. japonicus survival rate and yield in the CU group at week 12 were significantly higher than those in the NM and ground cage groups (p < 0.05). At week 17, the average weight, yield, and survival rate in the CU group were still optimal, with the yield 5.76 times that in the initial dosage. These results suggest that the CU has a suitable mesh size, has good permeability, and may stably support sediment, which is conducive to the growth of benthic diatoms. In addition, it can provide sufficient natural feed and a good habitat environment and is the preferred substrate for A. japonicus seedling protection in outdoor pond net cages. Full article

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21 pages, 1423 KB

Open AccessSystematic Review

Diagnosis-Specific Links Between Physical Activity and Sleep Duration in Youth with Disabilities: A Systematic Review with Quantitative Synthesis

by Janette M. Watkins, Martin E. Block, Janelle M. Goss, Emily M. Munn and Devan X. Antczak

Int. J. Environ. Res. Public Health 2026, 23(1), 121; https://doi.org/10.3390/ijerph23010121 (registering DOI) - 19 Jan 2026

Abstract

Children and adolescents with disabilities experience disproportionate challenges in achieving recommended levels of physical activity (PA) and adequate sleep, two core determinants of health and functional well-being. This systematic review examined associations between meeting PA guidelines and sleep duration among youth with disabilities. [...] Read more.

Children and adolescents with disabilities experience disproportionate challenges in achieving recommended levels of physical activity (PA) and adequate sleep, two core determinants of health and functional well-being. This systematic review examined associations between meeting PA guidelines and sleep duration among youth with disabilities. Following PRISMA guidelines, MEDLINE, PsycARTICLES, and SPORTDiscus were searched through Spring 2024 for studies assessing PA and sleep in children and adolescents (<18 years) with disabilities using subjective or objective measures. Data were extracted from 28 studies (N = 138,016) and synthesized using qualitative methods and regression-based quantitative analyses to examine the effects of diagnosis category and PA guideline adherence on sleep duration. The diagnosis type was associated with sleep duration, with youth with autism spectrum disorder (ASD) exhibiting shorter sleep than those with physical disabilities. Meeting PA guidelines (≥60 min/day) was associated with longer sleep duration among youth with ASD, but not consistently across other diagnostic groups. Qualitative findings further indicated diagnosis-specific variability, with PA positively associated with sleep outcomes in ASD, attention deficit/hyperactivity disorder, and epilepsy, and mixed associations observed for cerebral palsy and intellectual disability. These findings suggest that PA may support sleep health in specific disability groups. Given persistently low PA participation among youth with disabilities, integrating accessible, diagnosis-specific PA opportunities within school, community, and clinical settings may represent a feasible strategy to improve sleep and overall health. Full article

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28 pages, 376 KB

Open AccessArticle

The Validity of the Ehrenfest Theorem in Quantum Gravity Theory

by Claudio Cremaschini, Cooper K. Watson, Ramesh Radhakrishnan and Gerald Cleaver

Symmetry 2026, 18(1), 182; https://doi.org/10.3390/sym18010182 (registering DOI) - 19 Jan 2026

Abstract

The Ehrenfest theorem is a well-known theoretical result of quantum mechanics. It relates the dynamical evolution of the expectation value of a quantum operator to the expectation value of its corresponding commutator with the Hermitian Hamiltonian operator. However, the proof of validity of [...] Read more.

The Ehrenfest theorem is a well-known theoretical result of quantum mechanics. It relates the dynamical evolution of the expectation value of a quantum operator to the expectation value of its corresponding commutator with the Hermitian Hamiltonian operator. However, the proof of validity of the Ehrenfest theorem for quantum gravity field theory has remained elusive, while its validation poses challenging conceptual questions. In fact, this presupposes a number of minimum requirements, which include the prescription of quantum Hamiltonian operator, the definition of scalar product, and the identification of dynamical evolution parameter. In this paper, it is proven that the target can be established in the framework of the manifestly covariant quantum gravity theory (CQG theory). This follows as a consequence of its peculiar canonical Hamiltonian structure and the commutator-bracket algebra that characterizes its representation and probabilistic interpretation. The theoretical proof of the theorem for CQG theory permits to elucidate the connection existing between quantum operator variables of gravitational field and the corresponding expectation values to be interpreted as dynamical physical observables set in the background metric space-time. Full article

(This article belongs to the Special Issue Symmetry in Classical and Quantum Gravity and Field Theory)

10 pages, 2137 KB

Open AccessArticle

Professional Perspectives and Research Challenges Among AO CMF Surgeons in the Middle East and North Africa

by Khalid Abdel-Galil, Ammar Khalafalla and Mohamed Amir

Craniomaxillofac. Trauma Reconstr. 2026, 19(1), 5; https://doi.org/10.3390/cmtr19010005 (registering DOI) - 19 Jan 2026

Abstract

Purpose: Research drives clinical advancement in oral and craniomaxillofacial surgery by generating evidence that guides practice and innovation. However, limited literature exists describing research engagement among surgeons within AO CMF in the Middle East and North Africa. This study evaluated awareness, participation, and [...] Read more.

Purpose: Research drives clinical advancement in oral and craniomaxillofacial surgery by generating evidence that guides practice and innovation. However, limited literature exists describing research engagement among surgeons within AO CMF in the Middle East and North Africa. This study evaluated awareness, participation, and perceived barriers to research among AO CMF members and affiliated surgeons in the MENA region. Methods: A cross-sectional, questionnaire-based survey was distributed electronically to AO CMF members, affiliates, and professional CMF surgeon networks between October and December 2024. The 14-item survey assessed demographics, research awareness, attitudes, productivity, and barriers. Responses were anonymized and analyzed descriptively using SurveyPlanet analytics. Results: A total of 144 surgeons from 21 countries completed the survey. Pakistan (35%), Morocco (9.8%), Kuwait (7.7%), and the United Arab Emirates (7%) contributed the largest proportions. Most respondents (47.6%) expressed strong interest in research but reported difficulty initiating projects, while 32.2% cited lack of time as a major constraint. The most frequently reported barriers included challenges in research methodology (14.6%), publishing (14.6%), and manuscript writing (14.1%). Only 18.9% of participants had published more than ten articles, while 29.4% had none. Mentorship demand was high (94.4%), but awareness of the AO PEER program remained limited (37.8%). Conclusion: Surgeons expressed strong enthusiasm for research yet face substantial barriers. Strengthening research methodology training, establishing structured mentorship, expanding AO PEER engagement, and facilitating multicenter collaboration are key strategies to enhance research productivity across the region. Full article

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24 pages, 6437 KB

Open AccessArticle

Wildfire Mitigation in Small-to-Medium-Scale Industrial Hubs Using Cost-Effective Optimized Wireless Sensor Networks

by Juan Luis Gómez-González, Effie Marcoulaki, Alexis Cantizano, Myrto Konstantinidou, Raquel Caro and Mario Castro

Fire 2026, 9(1), 43; https://doi.org/10.3390/fire9010043 (registering DOI) - 19 Jan 2026

Abstract

Wildfires are increasingly recognized as a climatological hazard, able to threaten industrial and critical infrastructure safety and operations and lead to Natech disasters. Future projections of exacerbated fire regimes increase the likelihood of Natech disasters, therefore increasing expected direct damage costs, clean-up costs, [...] Read more.

Wildfires are increasingly recognized as a climatological hazard, able to threaten industrial and critical infrastructure safety and operations and lead to Natech disasters. Future projections of exacerbated fire regimes increase the likelihood of Natech disasters, therefore increasing expected direct damage costs, clean-up costs, and long-term economic losses due to business interruption and environmental remediation. While large industrial complexes, such as oil, gas, and chemical facilities have sufficient resources for the implementation of effective prevention and mitigation plans, small-to-medium-sized industrial hubs are particularly vulnerable due to their scattered distribution and limited resources for investing in comprehensive fire prevention systems. This study targets the vulnerability of these communities by proposing the deployment of Wireless Sensor Networks (WSNs) as cost-effective Early Wildfire Detection Systems (EWDSs) to safeguard wildland and industrial domains. The proposed approach leverages wildland–industrial interface (WII) geospatial data, simulated wildfire dynamics data, and mathematical optimization to maximize detection efficiency at minimal cost. The WII delimits the boundary where the presence of wildland fires impacts industrial activity, thus representing a proxy for potential Natech disasters. The methodology is tested in Cocentaina, Spain, a municipality characterized by a highly flammable Mediterranean landscape and medium-scale industrial parks. Results reveal the complex trade-offs between detection characteristics and the degree of protection in the combined wildland and WII areas, enabling stakeholders to make informed decisions. This methodology is easily replicable for any municipality and industrial installation, or for generic wildland–human interface (WHI) scenarios, provided there is access to wildfire dynamics data and geospatial boundaries delimiting the areas to protect. Full article

(This article belongs to the Section Fire Science Models, Remote Sensing, and Data)

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43 pages, 12092 KB

Open AccessArticle

Sustainable Valorization of Spent Garnet Wastes in Construction Eco-Materials: Validation Stage of Performance Assessment

by Cornelia Baera, Ana-Cristina Vasile, Aurelian Gruin, Paula Sfirloaga, Claudiu-Sorin Dragomir, Raul Zaharia, Ionel Balcu, Corina Macarie and Doru Buzatu

Sustainability 2026, 18(2), 1000; https://doi.org/10.3390/su18021000 (registering DOI) - 19 Jan 2026

Abstract

Spent garnet (SG) wastes are generated in significant quantities by several industrial activities, including abrasive waterjet cutting (AWJ), abrasive blasting, and filtration and powdered media applications. These wastes represent a promising secondary raw material for the production of sustainable construction materials, particularly green [...] Read more.

Spent garnet (SG) wastes are generated in significant quantities by several industrial activities, including abrasive waterjet cutting (AWJ), abrasive blasting, and filtration and powdered media applications. These wastes represent a promising secondary raw material for the production of sustainable construction materials, particularly green mortars and concretes, through their partial replacement of natural sand in cementitious systems. Such applications are relevant to both hydraulically setting inorganic binders (cement-based materials) and alkali-activated cementitious materials (AACMs). The valorization of SG wastes offers multiple benefits, notably a dual environmental advantage: reducing the consumption of natural aggregates and diverting industrial waste from disposal by integrating it into a new life cycle as a value-added by-product. Additional potential advantages include reduced production costs and possible improvements in the overall performance of mortars and concretes. Despite these benefits, the use of SG as an aggregate replacement remains insufficiently explored, with existing studies providing only preliminary and fragmented evidence of its feasibility. This paper presents an overview of a comprehensive four-year research program investigating SG wastes derived from single-cycle AWJ processes and their incorporation into conventional mortars as partial fine aggregate replacement in cement-based construction composites. The validation stage of the performance assessment expands the range of SG sources by including new sampling from the original suppliers, enabling verification of the repeatability and reproducibility of earlier findings. A broad set of physical, mechanical, and durability properties—particularly resistance to freeze–thaw cycles—is evaluated to achieve a robust and comprehensive material characterization. These results are further correlated with chemical and microstructural analyses, providing critical insights to support the technological transfer of SG-based construction materials to industrial applications with reduced carbon footprint. Full article

(This article belongs to the Special Issue Sustainable Civil Engineering: Circular Economy, Environmental Impact, and Tools Driving Transformation)

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15 pages, 856 KB

Open AccessReview

Digital Governance as an Enabler of Economic Recovery and Developmental Transformation: Insights from Greece’s 2010–2018 Financial Adjustment Programmes

by Eleni Tsiaousi, Dimitrios Dimitriou and Dionysios Chionis

Encyclopedia 2026, 6(1), 22; https://doi.org/10.3390/encyclopedia6010022 (registering DOI) - 19 Jan 2026

Abstract

Greece’s 2010–2018 adjustment programmes provide an insightful case of how timing of reforms, institutional frictions, and digital transformation jointly condition the outcomes of macroeconomic stabilization efforts. This review builds on programme evaluations, recent academic work, and empirical indicators to analyze the dynamics at [...] Read more.

Greece’s 2010–2018 adjustment programmes provide an insightful case of how timing of reforms, institutional frictions, and digital transformation jointly condition the outcomes of macroeconomic stabilization efforts. This review builds on programme evaluations, recent academic work, and empirical indicators to analyze the dynamics at the intersection of macroeconomic adjustment, institutional quality, and entrepreneurship, placing emphasis on productivity and the evolving role of digital governance. The paper argues that the asymmetric sequencing of fiscal consolidation, internal devaluation, institution-building, and digital modernization is consistent with deeper and more persistent output losses than initially anticipated, as complementary reforms in product markets and public administration were not yet in place. Recovery momentum was observed when administrative simplification, transparency reforms, and digital public services began to reduce transaction costs, uncertainty, and implementation frictions. In this perspective, digital governance—through initiatives such as Diavgeia, and interoperable registries—acted as an enabling complement to the effectiveness of structural reforms, supporting the shift towards a more innovation-oriented entrepreneurial ecosystem. While the evidence is associative rather than causally identified, the synthesis highlights mechanisms and transferable lessons for the design and sequencing of reform programmes in crisis and recovery contexts. Full article

(This article belongs to the Collection Encyclopedia of Entrepreneurship in the Digital Era)

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38 pages, 3557 KB

Open AccessArticle

Cultural–Tourism Integration and People’s Livelihood and Well-Being in China’s Yellow River Basin: Dynamic Panel Evidence and Spatial Spillovers (2011–2023)

by Fei Lu and Sung Joon Yoon

Sustainability 2026, 18(2), 1006; https://doi.org/10.3390/su18021006 (registering DOI) - 19 Jan 2026

Abstract

Despite its rich cultural heritage, the Yellow River Basin (YRB) faces challenges of ecological fragility and unbalanced development that constrain residents’ welfare improvement. Cultural–tourism integration (CTI)—aimed at creating employment, optimizing industrial structure, and improving public services—is increasingly promoted as a pathway to enhance [...] Read more.

Despite its rich cultural heritage, the Yellow River Basin (YRB) faces challenges of ecological fragility and unbalanced development that constrain residents’ welfare improvement. Cultural–tourism integration (CTI)—aimed at creating employment, optimizing industrial structure, and improving public services—is increasingly promoted as a pathway to enhance people’s livelihood and well-being (PLW). Grounded in industrial integration theory and welfare economics, this study examined the impact effects, transmission mechanisms, and spatial spillovers of CTI on PLW. Panel data from 75 prefecture-level cities in the YRB, spanning 2011 to 2023, were utilized, and multi-dimensional indices were constructed for both CTI and PLW. Impact effects, mediating mechanisms, and spatial spillovers were examined through kernel density estimation, a dynamic system generalized-method-of-moments (SYS-GMM) model, mediation analysis, and a spatial Durbin model (SDM). The results showed that CTI and PLW both improved over time and displayed a spatial pattern of “midstream and downstream leading, upstream lagging”. CTI significantly promoted PLW, after controlling for dynamics and endogeneity (SYS-GMM coefficient = 0.130, p < 0.01). Industrial structure upgrading acted as a positive mediator, whereas digital infrastructure exhibited a short-term suppressing (negative mediating) effect, implying a phased mismatch between CTI investment priorities and digital input. Spatial estimates further indicated that CTI generated positive spillovers, improving PLW in neighboring cities, in addition to local gains. These findings suggest that basin-wide coordination and better alignment between CTI projects and digital infrastructure are essential for inclusive and sustainable well-being improvements, supporting regional progress toward the Sustainable Development Goals. Full article

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22 pages, 2754 KB

Open AccessArticle

Advancing River Health Assessment: An Integrated ISC Methodology Applied to Taiwan’s River Restoration Case Study

by Ching-Feng Chen and Shih-Kai Chen

Sustainability 2026, 18(2), 1007; https://doi.org/10.3390/su18021007 (registering DOI) - 19 Jan 2026

Abstract

River health assessment frameworks play a critical role in guiding restoration planning and watershed management, yet conventional index-based approaches often rely on fixed weighting schemes that limit diagnostic sensitivity and interpretability. This study proposes an integrated assessment framework that enhances the traditional Index [...] Read more.

River health assessment frameworks play a critical role in guiding restoration planning and watershed management, yet conventional index-based approaches often rely on fixed weighting schemes that limit diagnostic sensitivity and interpretability. This study proposes an integrated assessment framework that enhances the traditional Index of Stream Condition (ISC) by incorporating data-driven structural information while preserving transparency and regulatory relevance. Rather than replacing existing indices, the framework recalibrates sub-index contributions based on intrinsic data patterns derived from nonlinear embedding and density-based clustering. The proposed methodology is applied to the Zhuoshui River basin in Taiwan to demonstrate its capability to improve internal consistency, reduce metric redundancy, and clarify dominant environmental drivers. Results indicate that the recalibrated index provides clearer differentiation among ecological conditions and improves explanatory consistency compared with the original ISC formulation. By balancing methodological innovation with interpretability, the proposed framework offers a practical pathway for strengthening river health assessment and supporting restoration-oriented decision-making. Full article

(This article belongs to the Special Issue Ecology, Environment, and Watershed Management)

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32 pages, 18470 KB

Open AccessArticle

Enhancing Neuromorphic Robustness via Recurrence Resonance: The Role of Shared Weak Attractors in Quantum Logic Networks

by Yu Huang and Yukio-Pegio Gunji

Biomimetics 2026, 11(1), 81; https://doi.org/10.3390/biomimetics11010081 (registering DOI) - 19 Jan 2026

Abstract

Recurrence resonance, a phenomenon that enhances system computational capability by exploiting noise to amplify hidden attractors, holds significant potential for applications such as edge computing and neuromorphic computing. Although previous studies have extensively explored its characteristics, the underlying mechanism regarding its generation remains [...] Read more.

Recurrence resonance, a phenomenon that enhances system computational capability by exploiting noise to amplify hidden attractors, holds significant potential for applications such as edge computing and neuromorphic computing. Although previous studies have extensively explored its characteristics, the underlying mechanism regarding its generation remains unclear. Here, we employed a Stochastic Recurrent Neural Network to simulate neural networks under various coupling conditions. By introducing appropriate inhibitory connections and examining the state transition matrices, we analyzed the characteristics and correlations of attractor landscapes in both global and local systems to elucidate the generative mechanism behind the “Edge of Chaos” dynamics observed under the quantum logic connectivity structure during recurrence resonance. The results show that the strategic introduction of inhibitory connections enriches the system’s attractor landscape without compromising the intensity of recurrence resonance. Furthermore, we find that when neurons are coupled via quantum logic and noise intensity meets specific conditions, the strong attractors of the global system decompose into those of distinct local subsystems, accompanied by the sharing of structurally similar weak attractors. These findings suggest that under quantum logic connectivity, the interaction between the strong attractors of different subsystems is mediated by a background of shared weak attractors, thereby enhancing both the system’s robustness against noise and the diversity of its state evolution. Full article

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15 pages, 5988 KB

Open AccessArticle

Evaluation of the Effects of the Anti-Inflammatory and Antioxidant Properties of Aloperine on Recovery in an Experimental Sciatic Nerve Injury Model

by Mehmet Ertanıdır, Erkan Sabri Ertaş, Ali Güleç, Bahadır Öztürk, Nejat Ünlükal and Sadettin Çiftci

Antioxidants 2026, 15(1), 126; https://doi.org/10.3390/antiox15010126 (registering DOI) - 19 Jan 2026

Abstract

Peripheral nerve injuries affect 13–23 out of 100,000 people annually, with Wallerian degeneration and subsequent inflammatory/oxidative responses critically impacting recovery. Aloperine, a natural alkaloid from Sophora alopecuroides L., exhibits potent anti-inflammatory and antioxidant properties but has never been studied for nerve repair. In [...] Read more.

Peripheral nerve injuries affect 13–23 out of 100,000 people annually, with Wallerian degeneration and subsequent inflammatory/oxidative responses critically impacting recovery. Aloperine, a natural alkaloid from Sophora alopecuroides L., exhibits potent anti-inflammatory and antioxidant properties but has never been studied for nerve repair. In this study, we aimed to investigate whether aloperine could enhance peripheral nerve regeneration by modulating inflammation and oxidative stress in a rat sciatic nerve injury model. Thirty male Wistar rats underwent sciatic nerve neurotmesis with epineural repair. Animals were divided into surgical controls (Group A), aloperine-treated rats (Group B; single 100 mg/kg intraperitoneal dose), and intact controls (Group C). After 8 weeks, outcomes were assessed via functional tests (pinprick, hot plate, extensor postural thrust), biochemical analyses (TNF-α, IL-6, IL-10, TOS/TAS), and histomorphometric evaluations (axon counts, diameter indices, immunohistochemistry). Aloperine treatment significantly improved functional recovery, with near-normal hot plate latency and motor performance. Biochemically, it reduced pro-inflammatory markers (TNF-α) while elevating IL-10. Oxidative stress was attenuated. Histologically, treated nerves showed better-preserved axonal architecture (reduced inflammation). This first investigation of aloperine for nerve repair demonstrates its therapeutic potential through dual anti-inflammatory and antioxidant mechanisms, significantly improving functional and structural outcomes. These findings support its development as a novel treatment for peripheral nerve injuries. Full article

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Graphical abstract

27 pages, 2766 KB

Open AccessArticle

Explainable Reciprocal Recommender System for Affiliate–Seller Matching: A Two-Stage Deep Learning Approach

by Hanadi Almutairi and Mourad Ykhlef

Information 2026, 17(1), 101; https://doi.org/10.3390/info17010101 (registering DOI) - 19 Jan 2026

Abstract

This paper presents a two-stage explainable recommendation system for reciprocal affiliate–seller matching that uses machine learning and data science to handle voluminous data and generate personalized ranking lists for each user. In the first stage, a representation learning model was trained to create [...] Read more.

This paper presents a two-stage explainable recommendation system for reciprocal affiliate–seller matching that uses machine learning and data science to handle voluminous data and generate personalized ranking lists for each user. In the first stage, a representation learning model was trained to create dense embeddings for affiliates and sellers, ensuring efficient identification of relevant pairs. In the second stage, a learning-to-rank approach was applied to refine the recommendation list based on user suitability and relevance. Diversity-enhancing reranking (maximal marginal relevance/explicit query aspect diversification) and popularity penalties were also implemented, and their effects on accuracy and provider-side diversity were quantified. Model interpretability techniques were used to identify which features affect a recommendation. The system was evaluated on a fully synthetic dataset that mimics the high-level statistics generated by affiliate platforms, and the results were compared against classical baselines (ALS, Bayesian personalized ranking) and ablated variants of the proposed model. While the reported ranking metrics (e.g., normalized discounted cumulative gain at 10 (NDCG@10)) are close to 1.0 under controlled conditions, potential overfitting, synthetic data limitations, and the need for further validation on real-world datasets are addressed. Attributions based on Shapley additive explanations were computed offline for the ranking model and excluded from the online latency budget, which was dominated by approximate nearest neighbors-based retrieval and listwise ranking. Our work demonstrates that high top-K accuracy, diversity-aware reranking, and post hoc explainability can be integrated within a single recommendation pipeline. While initially validated under synthetic evaluation, the pipeline was further assessed on a public real-world behavioral dataset, highlighting deployment challenges in affiliate–seller platforms and revealing practical constraints related to incomplete metadata. Full article

(This article belongs to the Special Issue 2nd Edition of Modern Recommender Systems: Approaches, Challenges and Applications)

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17 pages, 3320 KB

Open AccessArticle

Structural Feasibility and Compliance Assessment of Container vs. Cold-Formed Steel for a Sustainable 3D Printing Micro-Factory

by Michael Natale Cunzolo and Aziz Ahmed

Designs 2026, 10(1), 7; https://doi.org/10.3390/designs10010007 (registering DOI) - 19 Jan 2026

Abstract

This paper addresses critical issues related to the structural design of a micro-factory housing a mobile 3D printing system for plastic recycling. Rather than a simple comparison, it quantifies the “modification penalty”, the structural and economic cost of retrofitting a repurposed ISO shipping [...] Read more.

This paper addresses critical issues related to the structural design of a micro-factory housing a mobile 3D printing system for plastic recycling. Rather than a simple comparison, it quantifies the “modification penalty”, the structural and economic cost of retrofitting a repurposed ISO shipping container (ISCC) versus deploying a purpose-built cold-formed steel (CFS) volumetric structure. Finite Element Analysis of a standard 20-foot shipping container revealed a serviceability failure in its roof under standard imposed loads. Concurrently, an initial analysis of an equivalent CFS structure also indicated non-compliance, with significant floor and roof deflections. Both platforms were subsequently redesigned with structural reinforcements to achieve full compliance with Australian Standards. The comparative evaluation moves beyond static analysis to incorporate critical performance metrics. While the CFS structure proved to be 575 kg lighter with a lifespan 300–400% longer, the modified ISCC was 47% cheaper in initial capital outlay ($7161 vs. $13,549). However, when considering the totality of performance factors, specifically the ISCC’s inherent vulnerability to resonance (8–18 Hz), which overlaps with transport frequencies, and the logistical burden of losing CSC certification upon modification, the CFS platform is conclusively identified as the superior engineering solution. Its design flexibility, predictable performance, and amenability to purpose-built optimization make it a more reliable and operationally secure platform for this specialized application. Full article

(This article belongs to the Special Issue Sustainable Construction: Innovations in Design, Engineering, and the Circular Economy)

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25 pages, 4294 KB

Open AccessArticle

Algorithm Based on the Boole’s Integration Rule to Obtain Automatically the Five Solar Cell Parameters Within the One-Diode Solar Cell Model with an Executable Program

by Victor-Tapio Rangel-Kuoppa

Energies 2026, 19(2), 490; https://doi.org/10.3390/en19020490 (registering DOI) - 19 Jan 2026

Abstract

An algorithm has been implemented and it is provided in this article as an executable program to extract the five solar cell parameters within the one-diode solar cell model. Boole’s integration rule has been put into practice to integrate the current minus the [...] Read more.

An algorithm has been implemented and it is provided in this article as an executable program to extract the five solar cell parameters within the one-diode solar cell model. Boole’s integration rule has been put into practice to integrate the current minus the short-circuit current, yielding a more accurate Co-Content function. Afterwards, the Co-Content function is fitted to a second-degree polynomial in two variables, namely, the voltage and the current minus the short-circuit current, providing six fitting constants. The five solar cells are deduced from these six fitting constants. This algorithm has been implemented in an automatic program that performs the calculations. The program also obtains the standard deviations of the fitting errors, which are used to obtain the standard deviations of the five solar cell parameters. The program reports to the user the results in three text files, from which the user can easily copy-paste the results into softwares like Origin, Word, or Excel. A program to smooth the current voltage curves is also provided. Two videos are also available, one explaining how to profit from this executable program, and the other one how to use the smoothing program. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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23 pages, 365 KB

Open AccessArticle

Research on the Mechanism Through Which Digital Platform Capability Drives Servitization Innovation Performance in Manufacturing

by Hongbo Jiao, Liming Cheng and Guanghui Li

Sustainability 2026, 18(2), 1003; https://doi.org/10.3390/su18021003 (registering DOI) - 19 Jan 2026

Abstract

Against the backdrop of accelerating servitization transformation in the global manufacturing sector, how digital platform capability effectively drives improvements in innovation performance has become a critical issue. Existing research mainly focuses on the instrumental attributes of digital technologies, while relatively few studies examine [...] Read more.

Against the backdrop of accelerating servitization transformation in the global manufacturing sector, how digital platform capability effectively drives improvements in innovation performance has become a critical issue. Existing research mainly focuses on the instrumental attributes of digital technologies, while relatively few studies examine their strategic role in servitization transformation, particularly the systematic explanation of the “capability–behavior–context–performance” transmission mechanism. To address this gap, this study integrates dynamic capability theory and the opportunity window theory to construct a moderated mediation model that uncovers the internal mechanisms and boundary conditions through which digital platform capability influences servitization innovation performance. Based on survey data from 237 manufacturing firms in Guangdong Province, the empirical results indicate that: (1) digital platform capability and value co-creation both exert significant positive effects on servitization innovation performance; (2) value co-creation mediates the relationship between digital platform capability and servitization innovation performance; and (3) although organizational distance was theoretically expected to function as an important contextual variable, this study does not find evidence supporting its inverted U-shaped moderating effect, suggesting that its role in digital contexts may be more complex. This study not only extends the application of dynamic capability theory and opportunity window theory in servitization innovation settings but also provides managerial insights for manufacturing firms to optimize digital platform strategies and build more resilient and sustainable innovation systems. Full article

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17 pages, 5297 KB

Open AccessArticle

Liver Safety Assessment of an Indonesian Hexavalent Vaccine Candidate Through Histopathology and ALT/AST Evaluation in Rats and Rabbits

by Elisa D. Pratiwi, Tiza W. Mawaddah, Arif R. Sadjuri, Dimas T. Nugroho, Arip Hidayat, Astria N. Nidom, Zakiyyan I. Ayyuba, Eka S. Wahyuningsih, Kuncoro P. Santoso, Hani Plumeriastuti, Soeharsono, Setyarina Indrasari, Reviany V. Nidom, Acep R. Wijayadikusumah and Chairul A. Nidom

Vaccines 2026, 14(1), 94; https://doi.org/10.3390/vaccines14010094 (registering DOI) - 19 Jan 2026

Abstract

Background: Administering several separate childhood vaccines can reduce adherence to immunization schedules due to missed appointments and the burden of repeated injections. A hexavalent formulation targeting diphtheria, tetanus, pertussis, hepatitis B, Haemophilus influenzae type B, and poliovirus offers a practical approach to improve [...] Read more.

Background: Administering several separate childhood vaccines can reduce adherence to immunization schedules due to missed appointments and the burden of repeated injections. A hexavalent formulation targeting diphtheria, tetanus, pertussis, hepatitis B, Haemophilus influenzae type B, and poliovirus offers a practical approach to improve compliance and streamline immunization. Methods: Toxicity testing was performed in Wistar rats and New Zealand White rabbits (60 rats and 30 rabbits). Animals were distributed into three groups: hexavalent vaccine + low-dose sIPV, hexavalent vaccine + high-dose sIPV, and control. Each animal received a 0.5 mL intramuscular injection at weeks 0, 4, 8, and 12. Clinical observations were conducted throughout the study. Serum samples were collected one day before each injection and at the endpoint, while liver tissue was collected at the endpoint. ALT and AST concentrations were analyzed using an automated analyzer, and hepatic morphology was evaluated microscopically. Results: No abnormal clinical signs related to vaccination were observed. ALT concentrations showed no significant differences (p > 0.05). AST differences (p < 0.05) were detected between the high-dose group and the control on day 27 in female rabbits and on day 83 in female rats; however, all values remained within normal physiological limits. Histopathological examination revealed no irreversible hepatic lesions, including hydropic degeneration, portal inflammation, focal necrosis, or connective tissue proliferation, and no significant differences were noted (p > 0.05). Conclusions: Repeated administration of the hexavalent vaccine candidate at low and high doses produced no toxicological effects in animal models, supporting its safety for further clinical development. Full article

(This article belongs to the Section Vaccine Advancement, Efficacy and Safety)

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