Free Vibration Characteristics of the Conical Shells Based on Precise Integration Transfer Matrix Method

<div><p>Abstract Based on transfer matrix theory and precise integration method, precise integration transfer matrix method (PITMM) is advanced to research free vibration characteristics of the conical shells. The influences of the boundary conditions, the shell thickness and the semi-vertex conical angle on vibration characteristics are discussed. Based on Flügge thin shell theory and transfer matrix method, field transfer matrix of conical shells is obtained. According to the boundary conditions at ends of the conical shell, natural frequencies of the conical shell are solved by precise integration method. The approach of studying free vibration characteristics of the conical shells is obtained. Contrast of natural frequencies from the paper and previous literature, the method of the paper is confirmed. On this basis, the effects of the boundary conditions, the shell thickness and the semi-vertex conical angle on vibration characteristics are presented.</p></div

Prediction performance of DNF learning on hospital and 90-day mortality data.

<p>10-fold cross validation is applied to assess the prediction performance of DNF learning on hospital and 90-day mortality, and compare the performance when using the whole feature set (Model 8, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089053#pone-0089053-t001" target="_blank">Table 1</a>) and only day 1 (Model 7) and/or day 2 cytokine (Model 7 + day 2 cytokines).</p

Predictors (features) inluded in the different models.

<p>Predictors (features) inluded in the different models.</p

DNF of the patient mortality.

<p>DNF of the patient mortality.</p

Comparative performance of models on predicting 90-day mortality.

<p>NB-Naive Bayes, SVM-Support vector machine, NN-neural network, LOG-Logistic regression, BL-Boosted logistic regression, RT-Random tree, RF-Random forest, DNF-Disjunctive Normal Form learning.</p

Interpreting DNF models on three patients.

<p>The prediction procedure of DNF is represented in three layers: the top layer is the DNF itself; the middle layer is the clause level; and the bottom layer is the final outcome. Red color rectangles indicate that patient data is above the threshold and a severity condition is met; green rectangles indicate that patient data is below and the condition is not met. Three example patients are shown. For patient A, , and are all above the threshold and results in a positive Clause 2 so the predicted outcome is mortality. For patient B, Clause 2 is negative due to the low (procalcitonin in the lowest quartile); however high turns on Clause 1 and predicts mortality too. Patient C has high but it is not sufficient to turn on either Clause 1 or 2 and she is therefore predicted to survive.</p

Availability of data across physiologic domains.

<p>Of 1815 patients with cytokine data on day 1, much smaller numbers of patients had single nucleotide profiles (SNP), Fluorescent-Antibody Cell Sorting (FACS) measurements of surface markers, or full coagulation studies (Coags)performed.</p

DNF literals explanation.

<p>Note.</p><p>*: when missing values present in the data, they are treated as a literal, but they are never selected in the DNF learning.</p

Cascaded multicore fiber interferometers for enhanced bending sensing based on Vernier effect

In this paper, cascaded modal interferometers constructed by strongly-coupled seven-core fiber (SC-SCF) with different lengths are demonstrated for enhanced bending sensing based on Vernier effect. The free spectral range (FSR) of a single SC-SCF interferometer is determined by the length of SC-SCF. Two SC-SCF interferometers with different FSRs are cascaded, in which, one functions as the sensor while the other functions as the reference. The wavelength shift of the envelope of the output spectrum is much larger than that of a single SC-SCF interferometer due to Vernier effect. Therefore, enhanced sensing can be achieved. Experimental results show that the bending sensitivity of the proposed sensor is improved from -2.20 nm/m-1 (single SC-SCF interferometer) to 42.32 nm/m-1 (cascaded SC-SCF interferometers). The temperature response of the sensor is also investigated. Our proposed cascaded SC-SCF sensor has advantages of high sensitivity, ease of fabrication, and low cost. It is attractive for high precision bending sensing applications

Comparative Analysis of Transcriptional Profiles of Adult <i>Schistosoma japonicum</i> from Different Laboratory Animals and the Natural Host, Water Buffalo

<div><p>Background</p><p>Schistosomiasis is one of the most widely distributed parasitic diseases in the world. <i>Schistosoma japonicum</i>, a zoonotic parasite with a wide range of mammalian hosts, is one of the major pathogens of this disease. Although numerous studies on schistosomiasis japonica have been performed using laboratory animal models, systematic comparative analysis of whole-genome expression profiles in parasites from different laboratory animals and nature mammalian hosts is lacking to date.</p><p>Methodology/Principal Findings</p><p>Adult schistosomes were obtained from laboratory animals BALB/c mice, C57BL/6 mice, New Zealand white rabbits and the natural host, water buffaloes. The gene expression profiles of schistosomes from these animals were obtained and compared by genome-wide oligonucleotide microarray analysis. The results revealed that the gene expression profiles of schistosomes from different laboratory animals and buffaloes were highly consistent (r>0.98) genome-wide. Meanwhile, a total of 450 genes were identified to be differentially expressed in schistosomes which can be clustered into six groups. Pathway analysis revealed that these genes were mainly involved in multiple signal transduction pathways, amino acid, energy, nucleotide and lipid metabolism. We also identified a group of 1,540 abundantly and stably expressed gene products in adult worms, including a panel of 179 <i>Schistosoma</i>- or Platyhelminthes-specific genes that may be essential for parasitism and may be regarded as novel potential anti-parasite intervention targets for future research.</p><p>Conclusions/Significance</p><p>This study provides a comprehensive database of gene expression profiles of schistosomes derived from different laboratory animals and water buffaloes. An expanded number of genes potentially affecting the development of schistosomes in different animals were identified. These findings lay the foundation for schistosomiasis research in different laboratory animals and natural hosts at the transcriptional level and provide a valuable resource for screening anti-schistosomal intervention targets.</p></div