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Design, spectroscopic analysis, DFT calculations, adsorption evaluation, molecular docking, comprehensive in silico and in vitro bioactivity studies of thiocarbohydrazide grafted dialdehyde cellulose nanobiosorbent
Abstract Heavy metals have attracted considerable attention lately because of their widespread occurrence in aquatic environments and potential biological toxicity to animals and human. The current investigation focused on synthesizing the DAC@TCH nanobiosorbent by coupling dialdehyde cellulose with thiocarbohydrazide ligand. Subsequent characterization of DAC@TCH was carried out utilizing various analytical methods such as elemental analysis, scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared (FT-IR), and thermogravimetric analysis (TGA and DTA). DFT calculations were utilized to verify the molecular structure, analysis of frontier molecular orbitals (FMOs), molecular electrostatic potential (MEP) and reactivity descriptor for all phases. In vitro experiments were conducted to evaluate the biological properties of the DAC@TCH nanobiosorbent. These findings revealed that the synthesized DAC@TCH nanobiosorbent has been observed to show effective antibacterial IZD value against E. Coli (28 mm) which is superior to the efficacy of standard drug amoxicillin used (5 mm). Furthermore, in silico antibacterial activities (molecular docking) of the DAC@TCH have indicated this to exhibit excellent efficacy with docking score of (−7.4237 kcal/mol) and (−7.1325 kcal/mol) for S. aureus and, E. coli, respectively. Meanwhile the binding energies (best docking scores) in kcal/mol for Amoxicillin are (−5.8090) and (−6.7442) for S. aureus and, E. coli, respectively. Drug-likeness rules like Lipinski’s, Veber’s and Egan’s were considered for a more comprehensive evaluation. The prepared DAC@TCH nanobiosorbent was investigated for its potential to adsorb metal ions (Ag+, Hg2+, and Cu2+) from diverse water samples. Optimal conditions including pH, temperature, DAC@TCH dosage, oscillation time, initial metal ion concentration, and interference from other ions were explored. The adsorption of Hg2+, Cu2+, and Ag+ ions by DAC@TCH followed pseudo-second-order kinetics and Langmuir isothermal model, achieving maximum adsorption capacities of 196 mg/g for Ag+, 190 mg/g for Hg2+, and 73 mg/g for Cu2+. The adsorption process was determined to be exothermic and spontaneous across varying temperatures. Additionally, over 95% of adsorbed metal ions were effectively desorbed using thiourea (5%) and 0.3 M HNO3 elution mixture. DAC@TCH nanobiosorbent demonstrated excellent reusability, retaining its adsorption capacity through five cycles without degradation. The study highlights the potential of DAC@TCH for efficient recovery of heavy metals from different water sources, considering its application versatility, reusability, and minimal interference. Furthermore, the plausible mechanism of Ag+, Hg2+, and Cu2+ adsorption onto DAC@TCH bionanosorbent is elucidated.
Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods
Towards safer steel operations with a multi model framework for accident prediction and risk assessment simulation
Comparison of 10 biometric formulas in combined phacovitrectomy for different underlying retinal pathology
Abstract The refractive accuracy of intraocular lens (IOL) formulas varies in eyes that undergo combined phacovitrectomy for different underlying vitreoretinal pathology. A total of 401 eyes that underwent uncomplicated phacovitrectomy (23–25 g) with implantation of a plate haptic IOL (CT Asphina 409 M) in the capsular bag between April 2020 and December 2022 were included in the study. Inclusion criteria were postoperative best corrected visual acuity of 0.4 LogMAR or better at least 8 weeks after surgery. The Barrett Universal II (BUII), Haigis, Hill-Radial Basis Function (Hill-RBFv3.0), Hoffer Q, Holladay I, Holladay II, Kane, K6, Pearl-DGS and SRK/T formulas were compared for their accuracy in mean absolute error (MAE). Furthermore, all formulas were additionally tested by using the prediction for an IOL power 0,5 or 1D above the IOL used (IOLdown). Wilcox-Holladay-Wang-Koch (WHWK) statistical tests with Holm correction were applied. The Barrett IOLdown formula showed the lowest refractive prediction error (0.03D; together with Hill IOLdown), lowest MAE (0.40D), lowest median absolute error (MedAE; 0.31D), lowest standard deviation of MAE (0.55D) and lowest root mean squared absolute error (RMSAE; 0,54D). Barrett IOLdown had the highest percentage of eyes with predicted error within ± 0.25D (41.6%), Kane IOLdown within ± 0.50D (70.5%) and ± 0.75D (89%) and Hill IOLdown within ± 1D (95.2%). Except for Haigis, Hoffer Q and Pearl-DGS, all other formulas showed a statistically significantly lower MAE after IOLdown modification. The newest formulas with IOLdown modification performed better than old generation formulas, with Barrett IOLdown exhibiting the best results.
A driving feel oriented dynamic model for commercial vehicles
Seniors’ attitudes and intention toward IoT enabled healthcare devices in emerging economies
Unveiling the mitochondrial genome of Salvia splendens insights into the evolutionary traits within the genus Salvia
Abstract Previously, we resolved the complete sequences of the mitochondrial genomes (mitogenome) of two Salvia species (S. miltiorrhiza and S. officinalis). The major configurations of these two species were two circular chromosomes. In this study, we further studied the mitogenome of a floral species of Salvia (Salvia splendens) to understand the diversity and evolution of the Salvia mitogenomes. We sequenced the total DNAs of S. splendens using the Nanopore and Illumina platforms and assembled the mitogenome using a hybrid assembly strategy. The major configurations of the S. splendens were two circular chromosomes with lengths of 182,239 and 165,055 bp. There were 32 protein-coding genes (PCGs), three rRNA genes, and 18 tRNA genes annotated in the S. splendens mitogenome. We found 56 pairs of repetitive sequences in the S. splendens mitogenome. Three of them (R01, 04, and 07) could mediate recombination, whose products could be identified by the mapping of Nanopore reads, PCR amplifications, and Sanger sequencing of the PCR products. 457 RNA editing sites were identified in the S. splendens mitochondrial RNAs when comparing the RNA-seq data with their corresponding DNA templates. We showed that S. splendens was a sister taxon to S. miltiorrhiza based on the mitogenomes, consistent with the phylogeny determined with the plastome sequences. Crucially, we developed 12 mitochondrial markers sourced from mitochondrial intron regions to facilitate the identification of three Salvia species. Our study offers a comprehensive view of the structure of the Salvia mitogenomes and provides robust mitochondrial markers for Salvia species identification.
Structured evaluation processes are associated with higher levels of employee belonging
Weather warning archives reveal spatio-temporal hot spots of compound natural hazards
Abstract Individual natural hazards may be combined in different ways, leading to cascading or co-occurring effects, turning them into compound hazards. However, assessment of individual as well as compound hazards is often hampered by short or incomplete observational records of actual hazards, and records of various hazards that do not easily combine. In this study we propose an alternative way to detect potential risk of compound natural hazards via archived severe weather warnings. We investigate weather warnings in Sweden from 2011 to 2020 regarding their distributions and frequencies in time (at daily level) and space (at warning district level) from both an individual and compound perspective. We illustrate the methodology and results by focusing on compound flood-related risk, generated by combinations of heavy rainfall, high streamflow and high sea level, and contextualize with two actual compound flood events in Sweden. We find compound fluvial and coastal flood risk primarily along the southwest coast during the winter half year as well as compound fluvio-pluvial flood risk during the summer half year. The results show that severe weather warnings can be used to assess the frequency and compounding nature of natural hazards, as well as to identify actual cases for further investigation, and we encourage similar investigations elsewhere.
Plantar pressure classification and feature extraction based on multiple fusion algorithms
Cyclic voltammetry insights into Ni/Al-carbonate hydrotalcite catalysis for methanol oxidation
Finite element analysis and clinical evaluation of cross locking external fixator configuration for distal third tibia fracture
Abstract External fixators have been used effectively in damage control orthopaedic and open fractures management of various bones. It is well known that stability of external fixators is greatly influenced by its construct. Various rules have been documented to influence the stiffness and stability of external fixators. In this study, two clinical cases treated with a novel concept of cross self-locking rods external fixation construct were being described, coupled with biomechanical analysis of its stability in comparison with other constructs by using finite element study. These novel self-locking rods configuration proven improve strength by applying the same numbers of rod and pin with the delta frame construct in clinical practice. A validated three-dimensional (3D) model of the bone from a previous study was used and external fixator were designed via computer-aided design (CAD) modelling software, Solidworks. A 1500 N load representing the axial load compression during weight bearing was applied to the tibia with the distal segment of the fracture site secured without any movement. The clinical results showed bone healing process with both cases achieving bone union within the acceptable time. The results of the finite element study shows that the double cross self-locking rods construct had better stability since it showed optimum magnitude in relative micromotion (0.18 mm), lowest stress at the fracture site (189 MPa), displacement of fixator (13.4 mm), and stress at the fixator (687 MPa). In conclusion, double cross self-locking design could provide optimum stability of the external fixator construct by providing better stress distribution at the bone and external fixator, minimize displacement and micromotion at fracture fragments.
Integrated analysis of the complete sequence of a macaque genome
Author Correction: Comparative mitogenomics of freshwater snails of the genus Bulinus, obligatory vectors of Schistosoma haematobium, causative agent of human urogenital schistosomiasis
Height loss with age in adults with Prader-Willi syndrome may result in artifactual increases in BMI
Relationship between smoking status and ulcerative colitis: a meta-analysis based on a case–control study
Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement
Abstract Electromagnetic (EM) simulation is widespread in microwave engineering. EM tools ensure evaluation reliability but incur significant expenses. These can be mitigated by employing surrogate modeling methods, especially to expedite design workflows like local/global optimization or uncertainty quantification. However, building accurate surrogates is a daunting task beyond simple cases (low dimensionality, narrow geometry parameter and frequency ranges). This research suggests a new technique for dependable modeling of microwave circuits. Its main ingredient is a recurrent neural network (RNN) with the main architectural components being bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers. These are incorporated to accurately represent frequency relationship within circuit characteristics as well as dependencies between its dimensions and outputs considered as vector-valued functions parameterized by frequency. The network’s hyperparameters are adjusted through Bayesian Optimization (BO). Utilization of frequency as a sequential variable handled by RNN is a distinguishing feature of our approach, which leads to the enhancement of dependability and cost efficiency. Another critical factor is dimension- and volume-wise reduction of the model’s domain achieved through global sensitivity analysis. It allows for additional and dramatic accuracy improvements without diminishing the surrogate’s coverage regarding circuit’s operating parameters. Our methodology has been extensively validated using several microstrip structures. The results demonstrate its competitive performance over a range of kernel-based regression techniques and diverse neural networks. The proposed procedure ensures building models of outstanding predictive power while using small training datasets, which is beyond the capabilities of benchmark algorithms.