23 research outputs found

    Analysis of Hall Anchor Pulling Force on Soft Soil Condition

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    Taking 60kg C Hall anchor as an example. We established the pulling anchor model on soft soil condition based on the theoretical formula and hall anchor simulation model in CEL analysis method of ABAQUS software. That got the pulling force in soft soil and the flow of soft soil. These results show that although the method of theoretical calculation can accurately calculate the pulling force, could not reflect the change of the pulling force with the change of the distance of pulling anchor, and could not assess the stability of the pulling force. In the results of numerical calculation, the pulling force in soft soil is a wave force. In the results of the flow of soft soil, the wave of the force in first 20 seconds is related to the concave pit in the initial formation of the anchor, in this stage, to avoid the slide of the anchor, the pulling speed and the pulling force should be controlled to reduce

    Cryptanalysis of JAMBU

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    In this article, we analyse the security of the authenticated encryption mode JAMBU, a submission to the CAESAR competition that remains currently unbroken. We show that the security claims of this candidate regarding its nonce-misuse resistance can be broken. More precisely, we explain a technique to guess in advance a ciphertext block corresponding to a plaintext that has never been queried before (nor its prefix), thus breaking the confidentiality of the scheme when the attacker can make encryption queries with the same nonce. Our attack is very practical as it requires only about 2^{32} encryption queries and computations (instead of the 2^{128} claimed by the designers). Our cryptanalysis has been fully implemented in order to verify our findings. Moreover, due to the small tag length of JAMBU, we show how this attack can be extended in the nonce-respecting scenario to break confidentiality in the adaptative chosen-ciphertext model (IND-CCA2) with 2^{96} computations, with message prefixes not previously queried

    A Cryophyte Transcription Factor, CbABF1, Confers Freezing, and Drought Tolerance in Tobacco

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    Abscisic acid responsive element binding factors (ABFs) play crucial roles in plant responses to abiotic stress. However, little is known about the roles of ABFs in alpine subnival plants, which can survive under extreme environmental conditions. Here, we cloned and characterized an ABF1 homolog, CbABF1, from the alpine subnival plant Chorispora bungeana. Expression of CbABF1 was induced by cold, drought, and abscisic acid. Subcellular localization analysis revealed that CbABF1 was located in the nucleus. Further, CbABF1 had transactivation activity, which was dependent on the N-terminal region containing 89 residues. A Snf1-related protein kinase, CbSnRK2.6, interacted with CbABF1 in yeast two-hybrid analysis and bimolecular fluorescence complementation assays. Transient expression assay revealed that CbSnRK2.6 enhanced the transactivation of CbABF1 on ABRE cis-element. We further found that heterologous expression of CbABF1 in tobacco improved plant tolerance to freezing and drought stress, in which the survival rates of the transgenic plants increased around 40 and 60%, respectively, compared with wild-type plants. Moreover, the transgenic plants accumulated less reactive oxygen species, accompanied by high activities of antioxidant enzymes and elevated expression of stress-responsive genes. Our results thus suggest that CbABF1 is a transcription factor that plays an important role in cold and drought tolerance and is a candidate gene in molecular breeding of stress-tolerant crops

    An investigation in the correlation between Ayurvedic body-constitution and food-taste preference

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    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    A comparative study on the development of hybrid SSA-RF and PSO-RF models for predicting the uniaxial compressive strength of rocks

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    In the field of rock engineering, uniaxial compressive strength (UCS) is a crucial mechanical parameter that cannot be ignored. Due to the difficulty in obtaining high-quality rock core samples in some projects, it is essential to develop a reliable UCS prediction method. In this study, the prediction of UCS was accomplished by employing random forest (RF) models, and two optimizers were used for hyperparameter optimization. A total of 126 cases were collected, which included four input indicators: density, p-wave velocity, Schmidt hammer rebound number, and point load index. In addition, five traditional models, including RF, multiple regression analysis (MR), back propagation neural network (BPNN), extreme learning machine (ELM), and support vector regression (SVR), were introduced for comparison. In order to improve the performance of the models, a five-fold cross-validation method was considered. To evaluate the comprehensive performance of the models, the technique for order preference by similarity to an ideal solution (TOPSIS) method was used, providing an effective approach for model selection. The results showed that the proposed hybrid models can predict the UCS of rocks well. Overall, the SSA-RF model was determined to be the best model for the prediction of the UCS, with values of coefficient of determination (R2), mean absolute error (MAE), mean absolute percentage error (MAPE), root-mean-square error (RMSE), value accounted for (VAF), Nash-Sutcliffe efficiency coefficient (NSC), and Theil's U-value of 0.9587, 7.0681, 11.8988%, 9.4234, 95.9747, − 2.0781, and 0.0129, respectively. The Gini index indicated that the UCS was more sensitive to the Schmidt hammer rebound number than other indicators. Finally, the UCS prediction models were ranked as follows: SSA-RF, PSO-RF, SVR, RF, MR, BPNN, and ELM. These findings provide valuable insights into the development of accurate and reliable UCS prediction models, which are critical in the engineering practice

    Experimental demonstration in X-band of dual-negative refraction in photonic crystals

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    The effect of dual-negative refraction (DNR) in a photonic crystal (PhC) is demonstrated experimentally in X-band (8–12 GHz) for the first time. The two-dimensional PhC sample is made of highly pure Al2O3 ceramic cylinders close packed in air with a triangular lattice structure. The frequency regions of DNR are predicted by the analyses of wave vector diagrams. Experiments of anomalous refraction in PhCs are carried out in a near-field scanning system to demonstrate the theory and numerical results. The experimental measurements of electric field (real part and spatial intensity) for DNR are in good agreement with the numerical simulations. This work demonstrates that the unique feature of photonic crystals can be realized experimentally in different frequency regions which are proportional to the lattice constant of the PhC. Due to the large design flexibility, we believe this result will be promising for application in the range of optical devices

    Non-stationary Parallel Multisplitting Two-Stage Iterative Methods with Self-AdaptiveWeighting Schemes

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    In this paper, we study the non-stationary parallel multisplitting two-stage iterative methods with selfadaptive weighting matrices for solving a linear system whose coefficient matrix is symmetric positive definite. Two choices of Self-adaptive weighting matrices are given, especially, the nonnegativity is eliminated. Moreover, we prove the convergence of the non-stationary parallel multisplitting two-stage iterative methods with self-adaptive weighting matrices. Finally, the numerical comparisons of several self-adaptive nonstationary parallel multisplitting two-stage iterative methods are shown
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