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Light polarization-based electro-optic memory
Navigating ethical waters: The impact of ethical judgment, norms, and CSR skepticism on CSR engagement and purchasing intention in a breast cancer campaign
Corporate social responsibility (CSR) campaigns play a crucial role in shaping consumer perceptions and behavior. This study examines Delta Air Lines’ CSR campaign centered on breast cancer awareness, focusing on how ethical judgment and subjective norms are associated with CSR skepticism and how such skepticism, in turn, relates to CSR engagement and ethical purchasing intention. Drawing on the theory of reasoned action (TRA), a quantitative survey was conducted with 787 Delta Air Lines customers, all of whom provided informed consent prior to participation. The data, analyzed between August 1–7, 2024 using structural equation modeling, show that ethical judgment and subjective norms are associated with lower levels of CSR skepticism. In turn, CSR skepticism is negatively related to both CSR engagement and ethical purchasing intention, while higher levels of CSR engagement are associated with greater ethical purchasing intention. These findings provide insight into the role of ethical and social factors in shaping consumer responses to CSR initiatives and highlight the importance of fostering engagement to enhance the effectiveness of CSR campaigns and promote favorable consumer outcomes.
Research on transformer temperature rise detection and optimization method based on multi-physical field coupling
Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium
The use of super absorbent polymers in agriculture for water and fertilizers retention in soils has become popular with the increasing need for resource optimization. The objective of the present study was to use chitosan extracted from shrimp shell waste and reagent grade carboxymethylcellulose to synthesize a biodegradable super absorbent polymer with potential use for soil amendment in agriculture. The super absorbent polymer was synthesized using epichlorohydrin as a crosslinking agent in an alkaline NaOH/urea medium. The structure of the product was confirmed by FTIR and TGA. The polymer was found to be biodegradable with a progressive weight loss percentage reaching 79.1% after 14 days. An adsorption ratio of 15.8 and 17.2 was obtained for water and 22% w/v urea solution, respectively, so the product was categorized as super absorbent in both conditions. In addition, after two hours in the medium, absorption percentages of 48.3% were recorded for water and 22% w/v for urea solution. The reported method is effective for synthesizing a biodegradable super absorbent polymer with potential use for soil amendment and susceptibility to pH changes for both adsorption equilibrium and over time adsorption.
Soluble PD-1 as a key biomarker of disease activity in rheumatoid arthritis: a cross-sectional study at Tikur Anbessa Specialized Hospital
How FAIR data are helping to build trust in science
Design of one-component quasisymmetric protein nanocages
The uncertain self: Intolerance of uncertainty moderates the association of both positive and disorganized schizotypal traits with self-concept clarity in a non-clinical sample
Our objective was to investigate the relationship between self-concept clarity, intolerance of uncertainty, and schizotypal traits, with a focus on whether intolerance of uncertainty moderates the association between self-concept clarity and positive schizotypy in a non-clinical context. A sample of 315 adults (on average 43 (SD = 12) years, 247 women) completed the Self-Concept Clarity Scale, the Intolerance of Uncertainty scale, and the Schizotypal Personality Questionnaire – Brief Revised. Lower self-concept clarity was significantly associated with higher levels of positive, negative, and disorganized schizotypy, as well as with greater inhibitory intolerance of uncertainty. Importantly, a moderation analysis revealed that intolerance of uncertainty significantly altered the strength of the negative relationship between self-concept clarity and both positive and disorganized schizotypy. Specifically, this association was strongest among individuals with low levels of intolerance of uncertainty. In contrast, at higher levels of intolerance of uncertainty, the negative relationship between self-concept clarity and both positive and disorganized schizotypy was weaker. This pattern suggests that, among individuals with lower tolerance for uncertainty, a better-defined self-concept is more strongly associated with lower levels of positive and disorganized schizotypy. These results underscore the importance of considering both self-structure and uncertainty tolerance in models of schizotypy and psychosis risk. Our findings suggest that self-concept clarity and intolerance of uncertainty are interrelated cognitive factors that synergistically explain variance in schizotypal traits. As intolerance of uncertainty is a potentially modifiable cognitive process, the results have implications for early interventions aimed at reducing psychosis risk by improving self-concept clarity and tolerance for uncertainty. Although the study used a non-clinical sample, it supports a dimensional approach to psychosis and highlights key targets for future research.
Unexpected periosteal bone apposition including newly embedded osteocytes occurs around a mouse calvaria critical defect, independently of the presence of biomaterials
Abstract Osteocytes embedded in mineralized bone have their network disrupted when a bone injury occurs. However, their role in regeneration is still unclear. Bone substitutes, including bioceramics and bone-derived extracts, are commonly implanted in critical-sized defects due to their bioactive properties that promote healing, yet few studies have examined their effects on osteocytes in vivo. We studied early repair phases of a critical defect model in adult male mice calvaria, with or without biomaterial implantation (β-TCP, bovine bone). Using microCT we determined that, after 14 days, bone formation had mainly occurred along the surface of existing bone, increasing its thickness by a factor of 1.6, independently of the biomaterial presence. Using HE staining and fluorescence imaging, we described the newly formed bone and showed the presence of recently embedded osteocytes. We specifically collected osteocytes close, and distant from the defect, using laser-assisted microdissection and analyzed their gene expression. We show that IL6 was mainly dependent on the delay after surgery whereas Dmp1 was spatially regulated. Thus, even with limited bone formation in the defect, bone apposition occurs on the inner and outer periosteal surfaces of the calvaria, a phenomenon that may have been overlooked in the development of bone repair strategies.
Health impacts of climate change on children and adolescents: A protocol for review of reviews
Introduction Climate change is a contemporary phenomenon of grave concern to global public health. Climate change events such as droughts, wildfires, tornadoes, heatwaves, floods, sea level rise, hurricanes, tropical cyclones, landslides, extreme rainfall, typhoons, dust storms, and desertification significantly affect local, regional, and global living conditions. In Sub-Saharan Africa, the most disturbing of these are desertification, droughts, and floods, which directly threaten water supplies, food security, and the livelihoods of millions of people. The climate crisis affects the health of older people, adults, children, and adolescents. However, climate-related events are gravely affecting the current and future health and well-being of children and adolescents. Although evidence exists, its integration is vital for policy and practice to protect children and adolescents in the ever-changing climate. Therefore, this review aims to map the existing reviews of the impact of climate change on the health and well-being of children and adolescents. Method This review will be conducted according to Arksey and O’Malley’s [36] recommendations and will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). Scopus, JSTOR, Web of Science, PubMed, Embase and Cochrane Library will be searched to identify relevant records for inclusion in this review. Additional searches will be conducted in Google Scholar and Google for other relevant articles. The review protocol is registered at Open Science Framework: ( https://doi.org/10.17605/OSF.IO/A7DEQ ). Analysis Extracted data will be analysed using thematic content analysis, where data are summarised and qualitatively synthesized according to the recommendations of PRISMA-ScR and Tricco et al. [37]. The results and findings regarding the impacts of climate change on the health and safety of children and adolescents will be compiled, categorized, and presented using a qualitative narrative synthesis.
Association of physical activity with cardiovascular autonomic modulation and the serum metabolome in healthy men
Seasonal patterns of vegetation drought resilience and vegetation loss in Central Asia
Drought events have become increasingly common in Central Asia, increasing the risk of vegetation degradation. In this study, the resilience of vegetation to drought and its drivers was investigated across different seasons. The findings revealed that western Central Asia faced a notably high incidence of spring droughts, characterized by longer durations and greater severity than droughts in other seasons. In contrast, the Aral Sea Basin experienced fewer droughts in summer and autumn, although these droughts were more severe and intense and had longer durations. Croplands, particularly those in northern Kazakhstan, generally demonstrated relatively low resistance but relatively strong resilience. In contrast, sparsely vegetated areas in regions such as southern Xinjiang and areas downstream of the Aral Sea Basin presented high drought resistance but relatively low resilience. Precipitation and vapour pressure deficit (VPD) had the most significant impact on drought resilience in Central Asia, with a combined contribution of 55.18%, particularly in the northern and eastern regions of the area. The vegetation in spring was characterized by the highest resistance and resilience levels (40.67% and 40.65%, respectively) in Central Asia, followed by those in summer. In terms of vegetation loss, vegetation in spring accounted for the greatest proportion (44.03%), followed by that in summer, at 31.07%. The main characteristics of drought (duration and intensity) were the major factors influencing the loss of vegetation, especially in grasslands and sparsely vegetated areas. During prolonged summer droughts (>40 months), grasslands and sparse vegetation suffered substantial declines in gross primary productivity (GPP). In contrast, forests exhibited more severe GPP reduction at a drought peak of around 2 and intensity above 1.5. Quantifying the resilience and loss of vegetation to drought across different seasons can aid in the formulation of effective strategies to prevent and manage vegetation degradation in Central Asia.
A CPU-GPU heterogeneous parallel encryption scheme for raster remote sensing images using hybrid DNA operations and cellular automaton diffusion
Towards the construction of a virtual yeast
Association of oral health knowledge, attitudes, and practice with dental caries status among 6–12-year-old Iranian orphaned children using the CAST index: A Cross-sectional study
Introduction Orphaned children face heightened vulnerability due to the absence of parental care and limited access to preventive services. Evidence linking oral health knowledge, attitudes, and practice (KAP) with clinical outcomes in this population remains limited. This study aimed to assess oral health KAP among orphaned children in Karaj, Iran, and examine their associations with clinical indicators of dental caries, gingival status, and oral hygiene. Methods In this cross-sectional study, 72 children aged 6–12 years residing in four government-run quasi-family centers in Karaj were examined between October 2024 and January 2025 through a census sampling approach. Inclusion required age eligibility and informed consent, whereas children with systemic or developmental disorders or those receiving orthodontic treatment were excluded. Data were collected using a structured, validated questionnaire (α = 0.83) to assess KAP and demographic factors. Clinical examinations were performed by a calibrated examiner (ZJ) (Kappa = 87.68%) using the CAST, GI, and OHI-s indices. Logistic and linear regression models were used to examine predictor variables of KAP and oral health outcomes. Results The mean scores of knowledge, attitude, and practice were 3.16 ± 1.60 (out of 7), 33.52 ± 4.36 (out of 50), and 10.26 ± 2.72 (out of 20), respectively. Overall, 62.5% of children demonstrated fair oral hygiene (OHI-s = 1.75 ± 1.58) with mild gingival inflammation. CAST assessment indicated that fewer than one-third of primary molars were sound, while more than half of permanent first molars showed enamel caries. Regression analyses showed that frequent toothbrushing (p = 0.015, OR=0.52, 95% CI: 0.30–0.88) and more positive attitudes toward oral health (p = 0.013, OR=0.70, 95% CI: 0.53–0.93) were significant predictors of improved oral status, whereas knowledge and self-reported practice were not consistent predictors. Conclusions Orphaned children in Karaj demonstrated moderate oral hygiene, a high prevalence of untreated dental caries, and limited awareness of oral health. Addressing these behavioral and systemic gaps through targeted, evidence-based interventions—particularly oral health education, caregiver involvement, and routine dental monitoring—may help improve oral health outcomes in this vulnerable population.
The relationship of a novel systemic inflammatory response index with metabolic syndrome: a cross-sectional study in Chinese older adults
Research on the impact of artificial intelligence on the export technological complexity of chinese manufacturing enterprises: An analysis based on mediating effects
Technological innovation drives high-quality economic development, and artificial intelligence (AI) represents a new impetus for developing productive forces with new qualities. AI is becoming a focal point in economic development plans and national strategies worldwide due to its contribution to economic growth and the transformation of traditional production methods. This paper examines the impact and mechanism of AI on the export technological complexity of Chinese manufacturing enterprises from a corporate perspective. It utilizes data from listed manufacturing companies on the Shanghai and Shenzhen A-shares from 2008 to 2021 and employs a fixed-effects model. The results indicate that: (1) AI positively promotes the export technological complexity of Chinese manufacturing enterprises, with more pronounced effects in regions with higher export technological complexity. (2) Heterogeneity analysis indicates that AI significantly enhances the export technological complexity across various categories of enterprises. Particularly notable impacts are observed among state-owned enterprises, light textile enterprises, and enterprises located in the eastern and central regions. (3) Mechanism analysis reveals that AI indirectly promotes the export technological complexity of manufacturing enterprises by improving labor structure and enhancing corporate innovation capabilities. This study proposes relevant policy recommendations from four aspects: strengthening AI technology research and application, optimizing labor structure, enhancing corporate innovation development, and promoting balanced AI development.
Integrated bioinformatics analysis reveals fatty acid metabolism subtypes and immune landscape in recurrent implantation failure
Dual-stream learning with inverted transformer and BiGRU for rolling bearing remaining useful life prediction
Abstract Predicting the remaining useful life (RUL) of rolling bearings is essential for ensuring the reliability and safety of rotating machinery. However, accurate RUL prediction remains challenging due to the non-stationary degradation behavior of bearings operating under complex and time-varying conditions. Existing deep learning approaches often suffer from two key limitations: conventional Transformer architectures treat time steps as tokens, potentially mixing heterogeneous physical meanings across variables, while static feature fusion strategies lack adaptability to different degradation stages. To overcome these challenges, this study proposes a dual-stream framework that decouples spatial correlations from temporal degradation trends. Specifically, an Inverted Transformer is employed to model cross-variable relationships among multiple sensor signals, enabling effective extraction of spatial feature dependencies. Meanwhile, a Bidirectional Gated Recurrent Unit (BiGRU) is introduced to capture long-term temporal evolution and cumulative damage progression. Furthermore, a dynamic gating mechanism is developed to adaptively fuse spatial and temporal representations according to the current degradation stage, thereby enhancing prediction robustness under varying operating conditions. Experimental results on bearing degradation datasets demonstrate that the proposed method achieves competitive performance, reaching an average coefficient of determination ( $$R^2$$ ) of 0.8706. In addition, SHAP-based interpretability analysis indicates that the model focuses on high-frequency degradation indicators closely associated with bearing fatigue failure, providing physically consistent insights into the degradation process. The proposed framework offers a reliable and interpretable solution for predictive maintenance and intelligent condition monitoring of industrial rotating machinery.