The residual doses and sensitivity change for potassium-rich feldspar (K-feldspar) have been studied using the post-infrared infrared stimulated luminescence (pIRIR) and multi-elevated-temperature post-IR IRSL (MET-pIRIR) protocols. Laboratory simulated poorly-bleached and well-bleached samples were those K-feldspar grains bleached using a solar simulator for 10 minutes and 8 hours, respectively. The residual doses rise with stimulation temperature and time. The poorly-bleached sample has larger residual doses than the well-bleached sample, especially at high stimulation temperatures. The high-temperature pIRIR signals contain a large amount of hard-to-bleach signals. A decrease of luminescence sensitivity was observed after conducting a high-temperature-treatment in the measurement cycles. The sensitivity decreases significantly between the first and the second cycle. The extent of decrease in sensitivity shows a clear temperature trend. The higher the stimulation temperature of pIRIR signals is, the larger the sensitivity decreases. This decrease is more severe for the poorly-bleached sample than for the well-bleached sample, and could possibly lead to problems in sensitivity correction.
Application of Random Amplified Polymorphic DNA Analysis in Identifying Phellinus Igniarius Strains
Described in this paper, the random amplified polymorphic DNA (RAPD) analysis was conducted with 20 random primers in various strains of Phellinus igniarius collected from different localities. The results showed that 17 of the 20 random primers were polymorphic ones. The DNA bands derived from each primer amplifying in tested strains ranged from 10 to 33. The size of the amplified DNA fragments ranged from 250 to 2000 base pairs. Of each test primer, a wide variation in banding profiles was observed among the 7 strains of P. igniarius. A total of 377 band positions were scored for all of the tested strains, which differed significantly among the bands from different primers. UPGMA cluster analysis subdivided the tested strains into two groups, which was helpful to find out the difference among the tested strains and to distinguish them directly.
Background: The role of nursing in the management of chest drains is diverse and important. There is a paucity of data regarding the management of chest drains by nurses.
Objective: To establish an evaluation system for nurses to help guide the care of patients being treated with closed thoracic drainage tubes.
Methods: An ADC (availability, dependability, and capacity) model was used as the framework to evaluate treatment guidelines. A questionnaire was developed and tested for reliability and validity based on experimental models of thoracic drainage. Patients were subsequently randomly selected and screened using the effectiveness assessment form.
Results: Overall dimension scores and subgroups were correlated (r > 0.7). Test-retest reliability met required standards (r = 0.769-0.889, p < 0.01). The correlation coefficient between scores of each dimension and total score was 0.542 to 0.920, and correlation coefficients for each item and its dimension were 0.429 to 0.887.
Conclusions: The proposed assessment form provides an evidence-based tool for nurses to effectively manage patients with closed thoracic drainage systems. Experimental and clinical measures confirm the tool’s reliability and validity.
Reliability prediction of spinning machines can result in a time-saving and cost-saving development process with high reliability. Based on an analysis of failure times among systems and subsystems, a simulation method for reliability prediction of spinning machines is proposed by using the Monte Carlo simulation model. Firstly, factor weights are determined according to the fuzzy scoring and analytic hierarchy process. According to the status of reliability growth, growth coefficients are proposed based on reliability influencing factor weights and fuzzy scoring. To achieve the prediction of reliability distribution law, reliability index, and fault frequency, the reliability prediction model is constituted by combining the reliability growth coefficient and the Monte Carlo simulation model. Simulation results for spinning machines are obtained via the model thus built, which are confirmed with a practical example.
Filtering out irrelevant documents and classifying the relevant ones into topical categories is a de facto task in many applications. However, supervised learning solutions require extravagant human efforts on document labeling. In this paper, we propose a novel seed-guided topic model for dataless short text classification and filtering, named SSCF. Without using any labeled documents, SSCF takes a few “seed words” for each category of interest, and conducts short text filtering and classification in a weakly supervised manner. To overcome the issues of data sparsity and imbalance, the short text collection is mapped to a collection of pseudodocuments, one for each word. SSCF infers two kinds of topics on pseudo-documents: category-topics and general-topics. Each category-topic is associated with one category of interest, covering the meaning of the latter. In SSCF, we devise a novel word relevance estimation process based on the seed words, for hidden topic inference. The dominating topic of a short text is identified through post inference and then used for filtering and classification. On two real-world datasets in two languages, experimental results show that our proposed SSCF consistently achieves better classification accuracy than state-of-the-art baselines. We also observe that SSCF can even achieve superior performance than the supervised classifiers supervised latent dirichlet allocation (sLDA) and support vector machine (SVM) on some testing tasks.
In this paper, for multiple different chaotic systems with fully unknown parameters, a novel synchronization scheme called ‘modified function projective multi-lag generalized compound synchronization’ is put forward. As an advantage of the new method, not only the addition and subtraction, but also the multiplication of multiple chaotic systems are taken into consideration. This makes the signal hidden channels more abundant and the signal hidden methods more flexible. By virtue of finite-time stability theory and an adaptive control technique, a finite-time adaptive control scheme is established to realize the finite-time synchronization and to properly evaluate the unknown parameters. A detailed theoretical derivation and a specific numerical simulation demonstrate the feasibility and validity of the advanced scheme.
Transcription factor NF-E2-related factor 2 (Nrf2) is important for cell protection against chemical-induced oxidative stress. Previously, we have reported that in PC12 cells, Nrf2 can be triggered by deltamethrin (DM), a commonly used pyrethroid insecticide. Molecular mechanisms behind Nrf2 activation by DM are still unclear. Here we studied the effects of cell glutathione (GSH) depletion on Nrf2 activation by DM. We found that DM enhanced Nrf2 expression at the mRNA and protein levels and increased nuclear Nrf2 levels. Activation of Nrf2 was associated with activation of its downstream targets, such as heme oxygenase-1 (HO-1) and glutamate cysteine ligase catalytic subunit (GCLC). In contrast, DL-buthionine-[S,R]- sulfoximine (BSO), a known GSH-depleting agent, did not increase Nrf2 protein expression or cause its nuclear accumulation. However, pre-treatment with BSO triggered mRNA expression of HO-1 and GCLC. Furthermore, BSO pre-treatment suppressed DM-induced Nrf2 upregulation and activation and lowered mRNA expression of HO-1 and GCLC upon DM treatment. These data demonstrate that GSH depletion is not necessary for the activation of Nrf2/ARE by DM in PC12 cells, and that GCLC and HO-1 expression can increase through other signalling pathways.
Submerged floating tunnel (SFT for short) is a special underwater traffic structure, and wave load is one of the main environmental loads of SFT structure. In this paper, the 1:60 physical model test of three kinds of SFT in a two-dimensional wave flume is tested. The effects of random irregular waves on the SFT structure under different wave heights and periods are discussed. The study shows that: (1) Compared with circular and polygonal sections, there are multiple local peaks in the elliptical section during the period. with the increase of wave height, the number of local peaks also increases. It suggests that the rotational moment plays an important role in the elliptical section which has a relatively small depth-width ratio. (2) The position of the maximum and minimum pressure in the three kinds of SFT sections is consistent. Their vertical wave forces are all larger than their horizontal wave forces. The increase of vertical wave force relative to horizontal wave force in polygon section is larger than that in elliptical section, and the difference in the circular section is the smallest. (3) Under the same traffic condition, the wave force of the elliptical and polygon section is smaller, but they are more sensitive to the change of wave height, and the increase is obvious. The distribution of wave force in the circular section is more uniform.
A systematic approach, based on multiple products of the vector algebra (S-VA), is proposed to derive the spherical triangle formulae for solving the great circle track (GCT) problems. Because the mathematical properties of the geometry and algebra are both embedded in the S-VA approach, derivations of the spherical triangle formulae become more understandable and more straightforward as compared with those approaches which use the complex linear combination of a vector basis. In addition, the S-VA approach can handle all given initial conditions for solving the GCT problems simpler, clearer and avoid redundant formulae existing in the conventional approaches. With the technique of transforming the Earth coordinates system of latitudes and longitudes into the Cartesian one and adopting the relative longitude concept, the concise governing equations of the S-VA approach can be easily and directly derived. Owing to the advantage of the S-VA approach, it makes the practical navigator quickly adjust to solve the GCT problems. Based on the S-VA approach, a program namely GCTPro_VA is developed for friendly use of the navigator. Several validation examples are provided to show the S-VA approach is simple and versatile to solve the GCT problems.
A Method for the Estimation of the Square Size in the Chessboard Image using Gray-level Co-occurrence Matrix
The paper proposes a new simple procedure for measuring the square size employing the gray-level co-occurrence matrix of a chessboard image. As the size of the square structure in a chessboard image provides the geometric constraint information among the corners, it is available to improve the precision of extracting corners and serve the camera calibration. The co-occurrence matrix of a chessboard image is constructed to obtain the statistic information of the grayscale distribution. The 2D offset of the matrix is parameterized to calculate the correlation which is regarded as the implication of the repetition probability of the similar textures. A descending tendency is observed in the experiments because the similarity decreases with the greater offset. However, minimum and maximum are captured in the correlation curve, which represents that the square texture reappears with the periods of one and two square size, separately. The size of the square is tested by applying the first minimum of the correlation. The experiments are performed on the horizontal and vertical directions which are corresponding to the length and the width of the square, respectively. The experiments prove that the described method has the potential to measure square size of the chessboard.