Advancing Open Science

Mathematics is a discipline that forms the foundation of many fields and should be learned gradually, starting from early childhood. However, some subjects can be difficult to learn due to their abstract nature, the need for attention and planning, and math anxiety. Therefore, in this study, a system that contributes to mathematics teaching using computer vision approaches has been developed. In the proposed system, users can write operations directly in their own handwriting on the system interface, learn their results, or test the accuracy of their answers. They can also test themselves with random questions generated by the system. In addition, visual graph generation has been added to the system, ensuring that education is supported with visuals and made enjoyable. Besides the character recognition test, which is applied on public datasets, the system was also tested with images obtained from 22 different users, and successful results were observed. The study utilizes CNN networks for handwritten character detection and self-created image processing algorithms to organize the obtained characters into equations. The system can work with equations that include single and multiple unknowns, trigonometric functions, derivatives, integrals, etc. Operations can be performed, and successful results can be achieved even for users who write in italicized handwriting. Furthermore, equations written within each closed figure on the same page are evaluated locally. This allows multiple problems to be solved on the same page, providing a user-friendly approach. The system can be an assistant for improving performance in mathematics education.

Objectives: Real-world evidence that supports decision-making must meet numerous criteria, including validated identification of clinical outcomes. This study aimed to develop and validate a method for identifying new cases of myocardial infarction (MI) and ischemic stroke (IS) within real-world clinical data in China. Methods: Algorithms to identify MI and IS events were developed using ICD-10-CM codes and Chinese diagnosis keywords within the Tianjin Regional Healthcare Database. Validation followed predefined criteria: MI required cardiac troponin elevation and ischemic symptoms or cardiac troponin elevation and electrocardiogram changes; IS required clinical symptoms and neuroimaging confirmation of cerebral Magnetic Resonance Imaging (MRI) or Computerized Tomography (CT) reports. Positive predictive value (PPV) with 95% confidence intervals (CI) was calculated for each outcome. Results: Among 304 MI and 302 IS cases randomly selected, approximately half were identified using ICD-10-CM codes and half through Chinese diagnosis keywords. Overall PPV for MI was 69% (95% CI: 63–74%), with similar PPVs across identification methods. PPV increased to 88% for inpatient MI and 97% for primary inpatient MI. For IS, overall PPV was 65% (95% CI: 58–71%), with higher PPV for cases identified by ICD-10-CM codes (76%) compared to keyword-only cases (56%). PPV increased to 76% for inpatient IS and 91% for primary inpatient IS. Conclusions: The use of ICD-10-CM codes and Chinese diagnosis keywords in primary inpatient diagnoses provides a validated approach for the identification of clinical outcomes of MI and IS within real-world clinical data in China.

Over the last 40 years, the Kingdom of Saudi Arabia (KSA) has experienced economic growth that has driven urbanization and infrastructure improvements. However, this has also led to high resource use and poor planning, exacerbating climate challenges and underscoring the need for international cooperation. Given the substantial energy use associated with buildings, sustainable global building standards have been developed. Saudi Vision 2030 encourages sustainable practices in energy, housing, and water by adopting green building standards to guide environmentally friendly initiatives. This study provides an overview of the current status of green building rating systems in KSA and examines the principal obstacles faced during their implementation. Utilizing importance-performance analysis (IPA), the study identifies and evaluates strategies to advance green building ratings, drawing upon survey data from diverse stakeholders. Major barriers include low awareness across the public and private sectors and technical challenges such as a shortage of qualified professionals, limited information, and unreliable resources. The strategies proposed aim to establish clear standards for sustainable construction and promote targeted awareness campaigns with industry leaders and government, highlighting the long-term environmental and financial advantages of green buildings. Identifying these barriers and evaluating interventions will help to advance green building rating systems and sustainability in KSA and worldwide.

This review elucidates the foundational principles of nicotinamide adenine dinucleotide (NAD⁺) homeostasis in humans, emphasizing its depletion during aging and in age-associated disorders. Subsequently, the discussion extends to NAD⁺ precursors and their potential therapeutic applications, with insights from research using zebrafish as a disease model. This information sheds light on the growing interest in NAD and its metabolism in the medical field and sparks curiosity among researchers focused on fish studies. The review further explores the role of nicotinamide in fish, encompassing core NAD⁺ metabolism, its participation in oxidative stress, environmental challenges, and the mitigation of pollutant-induced toxicity. Additionally, the implications of NAD⁺ in fish neurobiology, immune regulation, host–pathogen interactions, skin, eggs, and post mortem muscle were considered. Dietary modulation of NAD⁺ pathways to enhance growth, immunity, and product quality in aquaculture has also been highlighted. This review highlights the significance of NAD⁺ metabolism in fish biology, covering cellular energy production, physiological processes, and environmental adaptation, and proposes targeting NAD⁺-related pathways as a strategy for aquaculture and fish health management.

Thanks to both endogenous and exogenous antioxidants (AOs), the antioxidant defense system ensures redox homeostasis, which is crucial for protecting the body from oxidative stress and maintaining overall health. The food industry also exploits the antioxidant properties to prevent or delay the oxidation of other molecules during processing and storage. There are many classical methods for assessing antioxidant capacity/activity, which are based on mechanisms such as hydrogen atom transfer (HAT), single electron transfer (SET), electron transfer with proton conjugation (HAT/SET mixed mode assays) or the chelation of selected transition metal ions (e.g., Fe²⁺ or Cu¹⁺). The antioxidant capacity (AOxC) index value can be expressed in terms of standard AOs (e.g., Trolox or ascorbic acid) equivalents, enabling different products to be compared. However, there is currently no standardized method for measuring AOxC. Nanoparticle sensors offer a new approach to assessing antioxidant status and can be used to analyze environmental samples, plant extracts, foodstuffs, dietary supplements and clinical samples. This review summarizes the available information on nanoparticle sensors as tools for assessing antioxidant status. Particular attention has been paid to nanoparticles (with a size of less than 100 nm), including silver (AgNPs), gold (AuNPs), cerium oxide (CeONPs) and other metal oxide nanoparticles, as well as nanozymes. Nanozymes belong to an advanced class of nanomaterials that mimic natural enzymes due to their catalytic properties and constitute a novel signal transduction strategy in colorimetric and absorption sensors based on the localized surface plasmon resonance (LSPR) band. Other potential AOxC sensors include quantum dots (QDs, <10 nm), which are particularly useful for the sensitive detection of specific antioxidants (e.g., GSH, AA and baicalein) and can achieve very good limits of detection (LOD). QDs and metallic nanoparticles (MNPs) operate on different principles to evaluate AOxC. MNPs rely on optical changes resulting from LSPR, which are monitored as changes in color or absorbance during synthesis, growth or aggregation. QDs, on the other hand, primarily utilize changes in fluorescence. This review aims to demonstrate that, thanks to its simplicity, speed, small sample volumes and relatively inexpensive instrumentation, nanoparticle-based AOxC assessment is a useful alternative to classical approaches and can be tailored to the desired aim and analytes.

Stilbenes are a group of polyphenols that are gaining steady attention and have promising biological activity. While much attention is given to polyhydroxy compounds derived from resveratrol, other substituents remain largely unexplored. In this work, we present the results of studies on the synthesis, physicochemical characterisation, and ADME parameters simulation of polymethoxy and brominated stilbenes. We also examined their anticancer activity and found that some of the brominated compounds reveal desirable properties. While the brominated derivatives are not significantly more active than the polymethoxy derivatives, they were found to be safer for the tested pseudo-normal cell lines.

This study quantifies vertical earth pressure on the roofs of box culverts under high fills in valley terrain using centrifuge model tests with expanded polystyrene (EPS) geofoam for load mitigation. We compare buried-type culverts with valley-terrain high-fill culverts and isolate the effects of the EPS installation height and panel thickness on the roof pressure and the associated concentration factor. The analysis of fill settlement elucidates the terrain-dependent load reduction mechanism and the efficacy of EPS panels. The results show that the roof pressure increases with EPS installation height but decreases and then plateaus once the panel thickness exceeds 75 cm; the load reduction benefit weakens when the installation height exceeds 2 m. Optimal performance is achieved with panels installed at 2 m and with a 75 cm thickness, which lowers applied loads while maintaining structural stability. These findings clarify soil–structure interactions in complex topography and provide practical guidance for deploying EPS in high-fill valley projects.

Background/Objectives: This study aimed to examine the effect of different forgetting strategies on intentional forgetting, specifically comparing the passive decay strategy (‘forgetting by keeping the mind blank’) and the active rehearsal strategy (‘forgetting by rehearsing other words’). Methods: An item-method directed forgetting paradigm was used in a between-subjects design while the electroencephalogram (EEG) was recorded. Results: Behavioral results showed that both strategies produced a robust directed forgetting (DF) effect, but participants in the active rehearsal group recognized more to-be-remembered (TBR) words. Event-related potential (ERP) results indicated that both groups exhibited a DF effect in the cue-induced P2–P3 complex. Compared to the passive decay group, the active rehearsal group did not show a DF effect in the cue-induced later positive component (LPC); instead, a significant DF effect appeared in the P600 during the test phase. Time–frequency results showed that the passive decay group exhibited a significant DF effect in the 9–25 Hz frequency band during the late stage of cue processing, while the active rehearsal group showed a reversed DF effect in the 8–16 Hz frequency band during the mid-stage of cue processing. Conclusions: These findings indicate that forgetting strategies do not affect the recognition performance of to-be-forgotten (TBF) words. The active rehearsal strategy led participants to shift attention from TBF to TBR words, resulting in better TBR recognition performance in this group.