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The widespread administration of COVID-19 vaccines has prompted a need to understand their safety profile. This investigation focuses on the safety of inactivated and mRNA-based COVID-19 vaccines, particularly concerning potential cardiovascular and haematological adverse events. A retrospective cohort study was conducted for 1.3 million individuals residing in Abu Dhabi, United Arab Emirates, who received 1.8 million doses of the inactivated BBIBP CorV (by SinoPharm) and mRNA-based BNT162b2 (Pfizer-BioNTech) vaccines between June 1, 2021, and June 30, 2022. The study's primary outcome was to assess the occurrence of selected cardiovascular and haematological events leading to hospitalization or emergency room visits within 21 days post-vaccination. Results showed no significant increase in the incidence rates of these events compared to the subsequent 22 to 42 days following vaccination. Analysis revealed no elevated risk for adverse outcomes following first (IRR 1·03; 95% CI 0·82-1·31), second (IRR 0·92; 95% CI 0·72-1·16) and third (IRR 0·82; 95% CI 0·66-1·00) doses of either vaccine. This study found no substantial link between receiving either mRNA and inactivated COVID-19 vaccines and a higher likelihood of cardiovascular or haematological events within 21 days after vaccination. Adverse cardiovascular and haematological events following COVID-19 vaccination have been reported, leading to safety concerns. Here, the authors find no evidence for increased incidence of these events within 21 days of BIBP-CorV or BNT162b2 vaccination in electronic health record data from Abu Dhabi. [ABSTRACT FROM AUTHOR]

Images captured by cameras are sometimes contaminated either during acquisition or transmission. Therefore, a preprocessing step is required which reduces noise from images. In this paper, a novel and efficient edge preserving universal noise removal algorithm is proposed which exploits both the local and global characteristics of the neighboring non-corrupted pixels. In the proposed algorithm, corrupted pixels are detected by robust outlying ratio (ROR) and replaced with the weighted sum (local characteristics) of the neighboring non-corrupted pixels in 3 × 3 window and these weights are obtained by solving the kernel ridge regression (KRR) which uses the global mean and covariance (global characteristics). Extensive experimental results demonstrate that our algorithm has better noise removal capability in terms of both objective and subjective evaluation as compared to existing denoising algorithms. [ABSTRACT FROM AUTHOR]

The present study evaluates the water quality status of 6-km-long Kali River stretch that passes through the Aligarh district in Uttar Pradesh, India, by utilizing high-resolution IRS P6 LISS IV imagery. In situ river water samples collected at 40 random locations were analyzed for seven physicochemical and four heavy metal concentrations, and the water quality index (WQI) was computed for each sampling location. A set of 11 spectral reflectance band combinations were formulated to identify the most significant band combination that is related to the observed WQI at each sampling location. Three approaches, namely multiple linear regression (MLR), backpropagation neural network (BPNN) and gene expression programming (GEP), were employed to relate WQI as a function of most significant band combination. Comparative assessment among the three utilized approaches was performed via quantitative indicators such as R2, RMSE and MAE. Results revealed that WQI estimates ranged between 203.7 and 262.33 and rated as "very poor" status. Results further indicated that GEP performed better than BPNN and MLR approaches and predicted WQI estimates with high R2 values (i.e., 0.94 for calibration and 0.91 for validation data), low RMSE and MAE values (i.e., 2.49 and 2.16 for calibration and 4.45 and 3.53 for validation data). Moreover, both GEP and BPNN depicted superiority over MLR approach that yielded WQI with R2 ~ 0.81 and 0.67 for calibration and validation data, respectively. WQI maps generated from the three approaches corroborate the existing pollution levels along the river stretch. In order to examine the significant differences among WQI estimates from the three approaches, one-way ANOVA test was performed, and the results in terms of F-statistic (F = 0.01) and p-value (p = 0.994 > 0.05) revealed WQI estimates as "not significant," reasoned to the small water sample size (i.e., N = 40). The study therefore recommends GEP as more rational and a better alternative for precise water quality monitoring of surface water bodies by producing simplified mathematical expressions. [ABSTRACT FROM AUTHOR]

Purpose: To generate virtual models using different hinge locations and to investigate the advantages of a temporal hinge to a superior in LASIK.Methods: The study design was cross sectional. An image processing software was used to construct virtual LASIK models of 56 slit lamp photos of eyes. For a given hinge location and width, the largest flap diameter and maximum treatable stromal bed area were calculated, comparing temporal hinge to superior.Results: Temporal hinge allowed a greater flap diameter than superior and thus a greater treatment zone area for a given hinge width. A temporal hinge allowed a greater hinge width than a superior hinge for a given treatment zone area.Conclusion: We provide a rational basis for a mechanically stable temporal hinge. Moreover, we provide a method to pre-operative model flap size and hinge location, using a slit lamp camera and an image editing software. [ABSTRACT FROM AUTHOR]

In recent years, nanomaterials have made their way into hundreds of biomedical, life-sciences and technological applications. One such nanomaterial of extreme importance is nanoalumina (AlO nanoparticles). This nanomaterial is an epitome of diversity with applications exhibited in the fields of catalysis, cosmetics, theranostics, energy generation, biosensors, drug-delivery, tumor-regression, etc. However, problems persist in terms of biocompatibility, cost-effectiveness, reproducibility and mass-production of nanoalumina by the presently existent physical, chemical and biological methodologies. Herein, we for the first time are presenting a top-down biofabrication method by which size reduction of commercial bulk alumina/aluminum oxide (5 µm) into nanoalumina (5-25 nm) is carried out by a thermophilic fungus Humicola sp. within 96 h of reaction at just 50 °C. The so-formed nanoalumina is highly stable, water dispersible, fluorescent and natural protein capped; characterization engaged standard techniques. These nanoparticles exhibit anti-bacterial properties against Gram-positive Bacillus subtilis strain and may serve as broad spectrum bactericidal agents. We believe that our novel top-down approach may be extensively used in the facile, inexpensive, eco-friendly and reliable fabrication of abundant quantities of nanomaterials of different chemical compositions, sizes and shapes with better control and predictability over the properties as derived from their substrates. The mechanistic aspect of said protocol is underway. [ABSTRACT FROM AUTHOR]