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Appropriate target range of INR and predictive factors of recurrent thrombosis and bleeding in patients with venous thromboembolism on warfarin
Magnetic resorcinol-formaldehyde supported-DABCO as an effective and recyclable nanocatalyst
Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images
Re-evaluation of quadratic and exponential models of litter accumulation incorporating climatic and species-specific dependence
A sustainable multi-task HPLC–UV method for simultaneous analysis of top neuromodulating agents in diverse pharmaceutical formulations
Abstract Epilepsy is a chronic neurological disease that affects the brain and causes a recurrent seizure. This condition affects a lot of people worldwide making it a global neurological disorder. The first line for managing epilepsy, is the use of Anti-epileptic drugs. Herein, a reliable and ecological chromatographic method was developed, verified and validated for the simultaneous determination of three approved drugs that can be co-administered in many treatment protocols for epilepsy management; Piracetam (PIR), Gabapentin (GBP) and Levetiracetam (LEV). The developed method was founded on high performance liquid chromatography (HPLC–UV). Separation was accomplished using a 5.0 μm particle size, 250 × 4.6 mm Inertsil ODS-3 C18 column with the UV detection set at 210.0 nm. An isocratic elution system was employed, consisting of a mixture of methanol and water in a ratio of 15:85 (v/v) at ambient temperature. The developed method demonstrated linearity throughout a range of concentration of 30.0–1000.0 µg/mL for GBP and 10.0–100.0 µg/mL for LEV and PIR. The suggested method was optimized and validated following the guidelines stated by the ICH and was utilized for the determination of the aforementioned drugs in their respective pharmaceutical formulation. Moreover, the supremacy of the developed method was further extended for monitoring the in-vitro release profile of the stated drugs and content uniformity of their marketed pharmaceutical formulations. Finally, the ecological impact of the suggested method was monitored, evaluated and compared to the official HPLC ones utilizing newly introduced greenness, blueness and whiteness assessment methods tools.
Research on fault diagnosis method for variable condition planetary gearbox based on SKN attention mechanism and deep transfer learning
Abstract Deep learning network models are widely applied to fault diagnosis of planetary gearboxes. However, the multi-coupling fault characteristics, accompanied by data fuzziness and distribution differences, present certain challenges to diagnostic research. Under variable operating conditions, the fault data to be diagnosed becomes more prominently inconsistent in distribution, leading to suboptimal fault recognition rates in diagnostic models. A deep transfer learning method for planetary gearbox fault diagnosis based on a Selective Kernel Networks (SKN) attention mechanism is proposed. First, an input dataset is constructed through overlapping sampling, and a deep neural network diagnostic model is established to automatically learn features and perform diagnostics on the data. Second, a dynamic selection mechanism for convolution kernels is embedded in the deep neural network, enabling each neuron to adaptively adjust its receptive field size based on multi-scale input information. This mechanism extracts common features between the source and target domains, enhancing the network’s feature extraction capability. Third, the Local Maximum Mean Discrepancy (LMMD) is used to perform sub-domain adaptation on the features of the source and target domains, reducing the distribution discrepancy between the two domains and constructing an end-to-end transfer adaptation model. This enables deep transfer learning fault diagnosis of planetary gearboxes under varying operating conditions. Finally, through experimental analysis and validation of 8 variable operating condition tasks, the fault identification accuracy of the diagnostic method proposed in this paper reached an average of 92.9%. Compared with traditional deep transfer learning diagnostic methods, it demonstrates higher diagnostic precision.
Addition of bedtime lafutidine inhibits nocturnal acid-breakthrough and improves sleep quality in gastroesophageal reflux disease patients on esomeprazole: a randomized controlled trial
Strong ground motion prediction model for EPA in Loess Plateau of Northwestern China
A study of traveling wave solutions and modulation instability in the (3+1)-dimensional Sakovich equation employing advanced analytical techniques
Pol θ-mediated end-joining uses microhomologies containing mismatches
Abstract DNA polymerase theta (Pol θ) initiates repair of DNA double-strand breaks by pairing single strands at short “microhomologies”. It is important to understand microhomology selection, as some cancer cells rely on Pol θ for survival. Here, we investigate end-joining by purified human Pol θ, employing DNA sequencing of products generated from oligonucleotide libraries having diverse 3′ ends. Pol θ overwhelmingly selects short internal microhomologies found within 15 nucleotides of the terminus of single-stranded DNAs, restricting deletion size during end-joining. Significantly, we find that the selected microhomologies are usually interrupted by mismatches and that base pairing within 6 nucleotides of the 3′ end is important for determining microhomology choice. Bidirectional synthesis is not necessary to initiate end-joining. The preference for mismatched microhomologies suggests a revision of the definition of microhomology to account for the unique properties of Pol θ. This could advance the analysis of mutations in cancer genomes.
A prospective study on incidence of desaturations in ERCP with non-anesthesiologist sedation and adverse event awareness of endoscopists
Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms
Educational multimedia design principles affect local and global information processing in functional brain networks
Efficacy of aflibercept combined with 80% dose photodynamic therapy for pachychoroid neovasculopathy
A novel intelligent approach for infection protection using a multidisciplinary collaboration in regional general hospitals
Natural variation in GNP3 determines grain number and grain yield in rice
Exploring the synergistic effects of metformin and doxorubicin loaded chitosan nanoparticles for A549 lung cancer therapy
miR-210 locus deletion disrupts cellular homeostasis: an integrated genetic study
Trade-offs between short- and longer-term resilience to warming within and between subtidal marine assemblages
Abstract Subtidal marine ectotherm physiological responses vary with ocean warming. Predicting these responses is important for ecosystem assessments to inform management and conservation strategies. Falkland Islands coastal species representing different mobility, feeding guilds, and habitats were tested, through laboratory incubation experiments, to estimate their short- (acute - seconds to hours) and longer-term (acclimation - weeks to months) resilience to ocean warming, to understand if ecological traits affect temporal trade-offs in responses, and contrasted with other marine assemblages. We found trait-specific, and species-specific, trade-offs in resilience to short-term and longer-term warming. Filter feeders and predators had higher acute tolerance than detritivores and herbivores. Lower acclimation capacity was found in molluscs, sessile species, filter feeders and kelp associated species. Benthic species had amongst the highest acclimation capacity. When compared to analogous experiments conducted with the same methodology at 10 different locations, across latitudes, we found a consistent relationship between short- and long- term resilience across marine assemblages, but with notable exceptions from unpredictable environments with episodic warming events; the Peruvian upwelling and Falklands fauna had a lower short-term resilience, relative to their longer-term resilience, than the other assemblages. When predicted rates of ocean warming under a high anthropogenic carbon emission scenario and anticipated increases in marine heat waves were taken into account, low latitude assemblages showed greater vulnerability in terms of years until acute thermal safety margins are breached (less than 500 years) than higher latitude assemblages (up to 4000 years), which is largely driven by projected rates of ocean warming. Understanding this variation, and the relationship to predictability, in coastal communities will be informative for predicting ecosystem responses and informing management and conservation strategies.