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Efficacy of topical heparin spray on donor site wound healing after split thickness skin grafting
The longitudinal effects of global and regional brain measurements on cognitive abilities
Detection of the distribution frequency of Diego blood type based on multiplex droplet digital PCR
Facial synthesis of reduced grapheneoxide/magnetite nanocomposite for energy generation and toxic metal bioremediation via microbial fuel cells
Water content alters soil organic carbon metabolism via microbial traits in Tibetan alpine peatlands
Warhead Strategy for Targeted Protein S-Nitrosation
Access to translated invitations online increases involvement of linguistically diverse households in a population-based study: a cluster randomized controlled study
Abstract This double-blind cluster-randomized controlled study examined the effectiveness of a multilingual physical-digital recruitment strategy to increase the involvement of linguistically diverse households in the German sub-survey of the World Health Organization European Childhood Obesity Surveillance Initiative. Students in primary schools received German study invitations either alone or with a supplemental flyer containing a QR-code for accessing translations online. A total of 114 classrooms (2306 students) received the flyer, while 115 classrooms (2276 students) served as control group. Main outcomes were active of responses to invitations and study participation. Response proportions were 48% overall, 48.6% in the flyer and 47.4% in the control group. Participation proportions were 26.7% overall, 27.8% in the flyer and 25.4% (571/2251) in the control groups. The flyer increased the odds of participation (14.9, 95% CI 1.003–1.315), but not the odds of active responses. In medium-social-level schools, response and participation proportions in the flyer group rose by 1.5% (ROR 1.015, 95% CI 1.003–1.027) and by 2% (ROR 1.020, 95% CI 1.005–1.034), respectively, for each percentage point increase in the proportion of non-German speaking households per classroom. The flyer’s effect in low- and high-social level schools was inconclusive. Although modest in magnitude, the addition of the flyer increased overall participation and, in particular, the involvement of linguistically diverse households in medium-social-level schools.
Knowledge, attitudes, and practices of oxygen therapy among emergency nurses
Food reward entrainment increases mealtime anxiety in goldfish via a ghrelin-dependent mechanism
Abstract Food anticipatory activity (FAA), the increase in locomotor activity prior to a scheduled feeding time, is linked not only to energy demands but also to food reward expectations. However, the mechanisms behind FAA remain unclear. We hypothesize that FAA induces anxiety due to reward anticipation. To test this, anxiety-like behavior was assessed in goldfish using open field and black-and-white preference tests under different feeding conditions and daytimes. Increased thigmotactic and scototactic behavior during FAA, compared to the post-FAA period, was observed, even in animals under constant light. Additionally, an unexpected meal did not reduce anxiety, while more hours of fasting did not increase it, suggesting that FAA is an anxiogenic state driven by a food-entrained oscillator rather than energy status. Ghrelin signaling was further explored using two antagonists, both of which reduced anxiety-like behavior when administered during FAA. Moreover, ghrelin administration induced anxiety-like behavior that was reversed by co-injection with an antagonist, supporting its anxiogenic role. These findings suggest a shared neural mechanism between FAA and anxiety, mediated by ghrelin. The possible involvement of ghrelin in activating dopamine-reward circuits in teleosts should be explored in future studies to gain further insight into the neurobiological basis of food anticipatory activity.
Broadband impedance matching for lossy magnetic metamaterials in conductive media
Abstract We present a broadband impedance matching model for traveling waves on lossy magnetic metamaterials known as magnetoinductive waveguides (MIWs) in conductive media. Thus far, broadband impedance matching has only been demonstrated in the case of a lossless MIW in free-space due to complexities introduced by losses and eddy current effects. As such, current studies in conductive environments have been limited to utilizing narrow-band matching techniques or relying on attenuation to mitigate reflections, thus limiting the system performance in terms of bandwidth and transmission loss. The proposed model overcomes these limitations by utilizing the nearest neighbor coupling and binomial approximations to generate transducer design criteria in terms of equivalent circuit parameters for broadband impedance matching. To validate the model, a transducer is designed for a 40-MHz lossy MIW submerged in an ocean water phantom. Reflection coefficient results demonstrate a 15.5% fractional bandwidth and a maximum value of − 9.0 dB in the propagation band of the MIW, indicating excellent performance. This model expands the potential design space of MIWs to include complex environments such as underwater, underground, or on the human body.
Triple-doped Dy3+/Tb3+/Eu3+ activated Na2Ca4(PO4)3F halo-phosphors for next-generation WLEDs and solar cell efficiency enhancement
GC vitamin D-binding protein gene functional genetic variants and gestational diabetes mellitus risk and prediction
Design of highly sensitive refractive index biosensor with cobalt-glass materials for detection of glucose concentration in blood
Abstract Diabetes represents a conceivably fatal condition that occurs because of elevated blood glucose levels. The surface plasmon resonance (SPR) biosensor has emerged as currently the most sophisticated method for determining glucose levels. The blood glucose biosensor performance is determined by the refraction coefficient of the substance containing glucose in the form of molecules. In this study, we have offered Hollow-Ring Cubic-Structured Refractive Index Biosensor (HRCSRIB) for monitoring glucose levels in blood from normal concentrations of 165 to 180 (mg/dL) in compared to diabetic glucose concentrations of 182, 205, 220, 240, 255, 289, 255 (mg/dL). This biosensor detects variations in the refractive index of urine, which correlate with changes in blood glucose concentration. The presented biosensing technology uses cobalt compounds and their unique structure to analyze blood glucose levels by measuring the urine refractive value. The study of various parameters associated with geometrical shape dimensions has been also represented. This offered biosensor has an exceptional sensitivity with 1750 nm/RIU, and a detection limit of 0.000410. The exceptional value of the quality factor, as well as the figure of merit value, is 1670.07 nm/RIU for 182 mg/dL and 1241.13 for 205–289 mg/dL respectively. The best transmittance response of 6%, 9%, 4%, and 32% has been obtained. The aforementioned sensor’s distinctive characteristics facilitate its biomedical applications as an optical on-chip sensor that monitors level of glucose.
Assessing the socioeconomic and environmental determinants of flood vulnerability in India: a panel data approach
Abstract This study investigates the socioeconomic and environmental determinants of flood vulnerability in Indian states using a panel data approach. Drawing on state-level flood damage data from 1953 to 2020, sourced from the Ministry of Jal Shakti and affiliated agencies, this study employs a robust econometric framework to identify the key drivers of flood-related damage. The dataset included 16 variables, and rigorous preprocessing steps, such as data cleaning, interpolation, stationarity testing, and multicollinearity checks, to ensure model reliability. Endogeneity was tested using IV regression, and the absence of such issues allowed for the application of Fixed Effects (FE) and Random Effects (RE) models. The Hausman test favored the RE model, which was further validated through diagnostic and robustness tests. The findings reveal that capital expenditure, government spending on natural calamities, and mangrove coverage significantly reduce flood damage, highlighting the importance of both fiscal and ecological interventions. Conversely, population affected, damage to houses, and damage to public utilities were positively associated with flood damage, indicating the need for targeted infrastructure and community resilience strategies. This study offers actionable insights for policymakers, emphasizing the integration of environmental conservation with strategic public investment to enhance flood resilience in India.
Frustration-Induced Many-Body Degeneracy in Spin −1/2 Molecular Quantum Rings
Variation of vegetation cover and the relationship with land surface temperature across Thailand (2007 to 2022)
Understanding the impact of urban exposure on obesity among middle and old-age migrants in India
Rural-to-urban migration is associated with elevated obesity in Western settings. However, whether migration to urban areas ages has any impact on obesity in India is inconclusive and scarce. We, therefore, assessed the impact of migration on obesity among rural-to-urban migrants and compared it with their rural counterparts. This study utilized the first wave of Longitudinal Ageing Study in India. BMI (BMI ≥ 25 kg/m2) and waist circumference (>102 cm and >88 cm for men and women, respectively) were employed to assess overall obesity and abdominal obesity. To fulfil the study objective, this study employed logistic and quantile regression techniques. The study found that individuals migrating from rural to urban areas are significantly more likely to develop obesity than rural stayers. Moreover, within the group of rural-urban migrants, prolonged urban residence was a strong and cumulative predictor for obesity. The risk of obesity was 1.91 times higher (those who lived 5 or fewer years in urban areas), 2.05 times higher (for 6–10 years), and 2.40 times higher (for more than 10 years) compared to their rural counterparts. This study identified migration and prolonged urban exposure as crucial risk factors for the development of obesity among middle-aged and older adults in India.
Optimistic effects of dual nano-encapsulated probiotics on breeders laying performance, intestinal barrier functions, immunity and resistance against Salmonella Typhimurium challenge
Divide-and-conquer routing for learning heterogeneous individualized capsules
Capsule Networks (CapsNets) have demonstrated an enhanced ability to capture spatial relationships and preserve hierarchical feature representations compared to Convolutional Neural Networks (CNNs). However, the dynamic routing mechanism in CapsNets introduces substantial computational costs and limits scalability. In this paper, we propose a divide-and-conquer routing algorithm that groups primary capsules, enabling the model to leverage independent feature subspaces for more precise and efficient feature learning. By partitioning the primary capsules, the initialization of coupling coefficients is aligned with the hierarchical structure of the capsules, addressing the limitations of existing initialization strategies that either disrupt feature aggregation or lead to excessively small activation values. Additionally, the grouped routing mechanism simplifies the iterative process, reducing computational overhead and improving scalability. Extensive experiments on benchmark image classification datasets demonstrate that our approach consistently outperforms the original dynamic routing algorithm as well as other state-of-the-art routing strategies, resulting in improved feature learning and classification accuracy. Our code is available at: https://github.com/rqfzpy/DC-CapsNet.