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Design and modeling of a nanocomposite system for demineralization of sweet whey
Real-time detection of loosening torque in bolted joints using piezoresistive pressure-sensitive layer based on multi-walled carbon nanotubes reinforced epoxy nanocomposites
Abstract Bolted connections are extensively used in construction and machine design, playing critical roles in various industrial applications. Bolts and screws are, however, prone to loosening or separating due to factors such as shock, vibration, and temperature fluctuations. This self-loosening phenomenon poses a considerable challenge to the reliability of bolted connections, necessitating regular inspections to ensure their safety. In this study, we report a cost-effective technique for monitoring bolted joint loosening torque: BoltWISE (Bolt loosening detection with innovative sensors). BoltWISE employs an innovative sensor element consisting of a piezoresistive, pressure-sensitive layer made from multi-walled carbon nanotube/epoxy nanocomposites coated onto an FR4 substrate, functioning as a washer. Our approach provides high sensitivity, durability, linearity, and fast response times, with minimal hysteresis during both the tightening and loosening processes. Finite-element method simulations were conducted to determine the optimal sensor positions, ensuring fast response during bolt tightening and loosening. Our findings highlight BoltWISE as a promising, low-cost solution for efficiently detecting bolt loosening in industrial environments. Its ease of implementation and fabrication make it a valuable tool for improving safety and maintenance practices across various industries.
Performance analysis of hybrid optimization approach for UAV path planning control using FOPID-TID controller and HAOAROA algorithm
Cross modal recipe retrieval with fine grained modal interaction
Improvement of engineering properties and environmental impact of fired clay bricks utilizing industry sludge waste
FBN2 promotes the proliferation, mineralization, and differentiation of osteoblasts to accelerate fracture healing
A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system
Reduction of nutrients concentration in culture medium has no effect on bovine embryo production, pregnancy and birth rates
Nutritional assessment using subjective global assessment identifies energy malnutrition and predicts mortality in patients with liver cirrhosis
Abstract This study aimed to evaluate whether the subjective global assessment (SGA) could effectively predict energy malnutrition, as assessed by indirect calorimetry, and mortality in hospitalized patients with cirrhosis. Energy malnutrition was defined by a nonprotein respiratory quotient (npRQ) < 0.85 using an indirect calorimetry. The usefulness of the SGA in identifying energy malnutrition and predicting mortality was assessed by the logistic regression and Cox proportional hazards models, respectively. Out of the 230 patients analyzed, 43% were found to have energy malnutrition. The distribution of SGA classifications was 54% for SGA-A, 32% for SGA-B, and 14% for SGA-C. Multivariable analysis indicated that both SGA-B (odds ratio, 3.59; 95% confidence interval [CI], 1.59–8.10) and SGA-C (odds ratio, 19.70; 95% CI, 3.46–112.00), along with free fatty acids (FFA), were independently linked to energy malnutrition. Regarding mortality, 125 patients (54%) died over a median follow-up period of 2.8 years. After adjustment, SGA-B (hazard ratio, 1.81; 95% CI, 1.08–3.03) and SGA-C (hazard ratio, 3.35; 95% CI, 1.28–8.76) were predictors of mortality in cirrhosis patients, while energy malnutrition and FFA were not. The SGA is a valuable tool for identifying energy malnutrition and predicting mortality in patients with cirrhosis.
Vehicle game lane-changing mechanism and strategy evolution based on trajectory data
Abstract To improve the safety of ramp vehicles changing lane and to shorten the merging distance, this paper explores the dynamic game interaction properties of vehicles merging and the consistency of vehicles’ decision-making behaviors at the macro-microscopic levels. Using the exiD dataset and evolutionary game theory, the merging behavior of ramp vehicles is modeled to explore the effects of different driving states on the evolutionary convergence of strategies. Based on the game cost theory, the lane choice behavior of mainline vehicles is modeled. Validated by SUMO software, the results show that the model in this paper can significantly improve the safety of vehicle merging and reduce the merging distance. The mainline vehicles are more inclined to change lane and cut out in advance when facing the ramp vehicles under the influence of the change of advantage in the subsequent game.
Establishment and characterization of three gemcitabine-resistant human intrahepatic cholangiocarcinoma cell lines
Comparative in vitro study of a new silicone mouth swab for soft tissue cleaning under wet and dry brushing conditions
Structural characteristics, sugar metabolizing enzyme activity and biological activity of Ganoderma lucidum polysaccharides at different growth stages
An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks
A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints
Unraveling the genetic connections for mitochondrial DNA control region and breast cancer susceptibility
Triglyceride glucose index as a biomarker for heart failure risk in H-type hypertension patients
Tracking the genetic diversity of SARS-CoV-2 variants in Nicaragua throughout the COVID-19 pandemic
Abstract The global circulation of SARS-CoV-2 has been extensively documented; however, the dynamics within Central America, particularly Nicaragua, remain underexplored. This study characterizes the genomic diversity of SARS-CoV-2 in Nicaragua from March 2020 through December 2022, utilizing 1064 genomes obtained via next-generation sequencing. These sequences were selected nationwide and analyzed for variant classification, lineage predominance, and phylogenetic diversity. We employed both Illumina and Oxford Nanopore Technologies for all sequencing procedures. Results indicated a temporal and spatial shift in dominant lineages, initially from B.1 and A.2 in early 2020 to various Omicron subvariants toward the study’s end. Significant lineage shifts correlated with changes in COVID-19 positivity rates, underscoring the epidemiological impact of variant dissemination. Comparative analysis with regional data underscored the low diversity of circulating lineages in Nicaragua and their delayed introduction compared to other countries in the Central American region. The study also linked specific viral mutations with hospitalization rates, emphasizing the clinical relevance of genomic surveillance. This research advances the understanding of SARS-CoV-2 evolution in Nicaragua and provides valuable information regarding its genetic diversity for public health officials in Central America. We highlight the critical role of ongoing genomic surveillance in identifying emergent lineages and informing public health strategies.
Full-length inhibitor protein is the most effective to perturb human dUTPase activity
Abstract It has been demonstrated recently that knockout of the dUTPase enzyme leads to early embryonic lethality in mice. However, to explore the physiological processes arising upon the lack of dUTPase an effective and selective enzyme inhibitor is much needed. A highly specific and strong binding proteinaceous human dUTPase inhibitor described by us recently was a promising starting point to develop a molecular tool to study temporal and conditional dUTPase inhibition in cellulo. Towards this end we determined the 3D crystal structure of the crystallizable amino terminal domain of inhibitor protein, named StlNT in complex with the human dUTPase and designed several point mutants based on the structure to improve the inhibition effectivity. The effect of StlNT and a peptide derived from the full-length inhibitor on the activity of the human dUTPase was also tested. We showed that the C-terminal part of the Stl protein omitted from the crystal structure has an important role in the enzyme inhibition as the full-length Stl is needed to exert maximal inhibition on the human dUTPase.