Faktor-Faktor Yang Berhubungan Dengan Pemanfaatan Penolong Persalinan Di Desa Moyongkota Baru Kecamatan Modayag Barat

Latar belakang : Persalinan merupakan hal yang sangat kompleks karena disatusisi terjadi kebahagiaan menjelang kelahiran anak tetapi di sisilain terjadi resiko-resiko yang mungkin mengancam keselamatan ibu dan bayi. Di desa Moyongkota Baru Kecamatan Modayag Barat sebagian besar ibu bersalin memanfaatkan dukun sebagai penolong persalinannya dibandingkan dengan pemanfaatan penolong persalinan oleh tenaga kesehatan.Tujuan : Penelitian ini bertujuan untuk mengetahui faktor - faktor yang berhubungan dengan pemanfaatan penolong persalinan pada ibu bersalin di desa Moyongkota Baru Kecamatan Modayag Barat.Metode : Penelitian ini menggunakan desain penelitian observasional analitik dengan rancangan penelitian cross sectional study. Populasi dalam penelitian ini yaitu seluruh ibu yang bersalin pada bulan September – Oktober 2013 di Desa Moyongkota Baru Kecamatan Modayag Barat. Sampel yang digunakan adalah Quota sampling yaitu sampel dikumpulkan sampai mencapai jumlah yang diinginkan, jumlah sampel yang diinginkan adalah 50 responden.Hasil Penelitian : Berdasarkan hasil uji chi square diketahui bahwa faktor pengetahuan (ρ=0,006) dan dukungan suami (ρ=0,001) berhubungan signifikan terhadap pemanfaatan penolong persalinan, sedang kanfaktor status ekonomi tidak berhubungan signifikan dengan pemanfaatan penolong persalinan dengan nilai ρ=0,206.Kesimpulan : 58% ibu bersalin di desa Moyongkota Baru Kecamatan Modayag Barat Kabupaten Bolaang Mongondow Timur memanfaatkan penolong persalinan oleh dukun/paraji dibandingkan ibu bersalin yang memanfaatkan penolong persalinan oleh bidan (14%) dan penolong persalinan olehdokter (28%)

Double Probability Integral Transform Residuals for Regression Models with Discrete Outcomes

The assessment of regression models with discrete outcomes is challenging and has many fundamental issues. With discrete outcomes, standard regression model assessment tools such as Pearson and deviance residuals do not follow the conventional reference distribution (normal) under the true model, calling into question the legitimacy of model assessment based on these tools. To fill this gap, we construct a new type of residuals for regression models with general discrete outcomes, including ordinal and count outcomes. The proposed residuals are based on two layers of probability integral transformation. When at least one continuous covariate is available, the proposed residuals closely follow a uniform distribution (or a normal distribution after transformation) under the correctly specified model. One can construct visualizations such as QQ plots to check the overall fit of a model straightforwardly, and the shape of QQ plots can further help identify possible causes of misspecification such as overdispersion. We provide theoretical justification for the proposed residuals by establishing their asymptotic properties. Moreover, in order to assess the mean structure and identify potential covariates, we develop an ordered curve as a supplementary tool, which is based on the comparison between the partial sum of outcomes and of fitted means. Through simulation, we demonstrate empirically that the proposed tools outperform commonly used residuals for various model assessment tasks. We also illustrate the workflow of model assessment using the proposed tools in data analysis.</p

Supplemental Material - Contextualized Game-Based Language Learning: Retrospect and Prospect

Supplemental Material for Contextualized Game-Based Language Learning: Retrospect and Prospect by Lu Yang and Rui Li in Journal of Educational Computing Research</p

Pair Copula Constructions for Insurance Experience Rating

<p>In nonlife insurance, insurers use experience rating to adjust premiums to reflect policyholders’ previous claim experience. Performing prospective experience rating can be challenging when the claim distribution is complex. For instance, insurance claims are semicontinuous in that a fraction of zeros is often associated with an otherwise positive continuous outcome from a right-skewed and long-tailed distribution. Practitioners use credibility premium that is a special form of the shrinkage estimator in the longitudinal data framework. However, the linear predictor is not informative especially when the outcome follows a mixed distribution. In this article, we introduce a mixed vine pair copula construction framework for modeling semicontinuous longitudinal claims. In the proposed framework, a two-component mixture regression is employed to accommodate the zero inflation and thick tails in the claim distribution. The temporal dependence among repeated observations is modeled using a sequence of bivariate conditional copulas based on a mixed D-vine. We emphasize that the resulting predictive distribution allows insurers to incorporate past experience into future premiums in a nonlinear fashion and the classic linear predictor can be viewed as a nested case. In the application, we examine a unique claims dataset of government property insurance from the state of Wisconsin. Due to the discrepancies between the claim and premium distributions, we employ an ordered Lorenz curve to evaluate the predictive performance. We show that the proposed approach offers substantial opportunities for separating risks and identifying profitable business when compared with alternative experience rating methods. Supplementary materials for this article are available online.</p

Mass Transport and Reactions in the Tube-in-Tube Reactor

The tube-in-tube reactor is a convenient method for implementing gas/liquid reactions on the microscale, in which pressurized gas permeates through a Teflon AF-2400 membrane and reacts with substrates in liquid phase. Here we present the first quantitative models for analytically and numerically computing gas and substrate concentration profiles within the tube-in-tube reactor. The model accurately predicts mass transfer performance in good agreement with experimental measurement. The scaling behavior and reaction limitations of the tube-in-tube reactor are predicted by modeling and compared with gas/liquid micro- and minireactors. The presented model yields new insights into the scalability and applicability of the tube-in-tube reactor

Mechanism of Radical Initiation and Transfer in Class Id Ribonucleotide Reductase Based on Density Functional Theory

Class Id ribonucleotide reductase (RNR) is a newly discovered enzyme, which employs the dimanganese cofactor in the superoxidized state (MnIII/MnIV) as the radical initiator. The dimanganese cofactor of class Id RNR in the reduced state (inactive) is clearly based on the crystal structure of the Fj-β subunit. However, the state of the dimanganese cofactor of class Id RNR in the oxidized state (active) is not known. The X-band EPR spectra have shown that the activated Fj-β subunit exists in two distinct complexes, 1 and 2. In this work, quantum mechanical/molecular mechanical calculations were carried out to study class Id RNR. First, we have determined that complex 2 contains a MnIII-(μ-oxo)2-MnIV cluster, and complex 1 contains a MnIII-(μ-hydroxo/μ-oxo)-MnIV cluster. Then, based on the determined dimanganese cofactors, the mechanism of radical initiation and transfer in class Id RNR is revealed. The MnIII-(μ-oxo)2-MnIV cluster in complex 2 has not enough reduction potential to initiate radical transfer directly. Instead, it needs to be monoprotonated into MnIII-(μ-hydroxo/μ-oxo)-MnIV (complex 1) before the radical transfer. The protonation state of μ-oxo can be regulated by changing the protein microenvironment, which is induced by the protein aggregation and separation of β subunits with α subunits. The radical transfer between the cluster of MnIII-(μ-hydroxo/μ-oxo)-MnIV and Trp30 in the radical-transfer chain of the Fj-β subunit (MnIII/MnIV ↔ His100 ↔ Asp194 ↔ Trp30 ↔ Arg99) is a water-mediated tri-proton-coupled electron transfer, which transfers proton from the ε-amino group of Lys71 to the carboxyl group of Glu97 via the water molecule Wat551 and the bridging μ-hydroxo ligand through a three-step reaction. This newly discovered proton-coupled electron-transfer mechanism in class Id RNR is different from those reported in the known Ia–Ic RNRs. The ε-amino group of Lys71, which serves as a proton donor, plays an important role in the radical transfer

KI as iodine source for the synthesis of E-iodovinyl sulfones via metal-free iodosulfonylation of terminal alkynes

<p>The <i>E</i>-selective iodosulfonylation of terminal alkynes has been achieved by employing sulfonyl hydrazines and potassium iodide as sulfonyl and iodine sources, respectively. Besides using simple and cheap reactants, the present method requires no metal catalyst and proceeds well at room temperature. A broad array of iodovinyl sulfones have been efficiently synthesized via the alkyne difunctionalization in the presence of benzoic peroxyanhydride (BPO).</p

Characterization and Modeling of the Operating Curves of Membrane Microseparators

The membrane microseparator is a milliliter-scale flow chemistry module that continuously separates a biphasic flow through a PTFE microporous membrane. It has found a wide range of applications in the continuous manufacturing of active pharmaceutical ingredients and fine chemicals, especially those involving multiple synthetic steps. Yet, the accurate prediction and control of the pressure balance needed for successful phase separations is technically challenging. In this article, we present systematic modeling of the operating ranges of the membrane microseparator. We characterize the retention and breakthrough phenomena of the device and develop two new analytic models for retention and breakthrough by taking into consideration the tortuosity factor and pore size distribution. The new models are shown to be better predictors of the experimental results than the original theoretical models based on the simple Young–Laplace equation and the straight-channel Hagen–Poiseuille equation

sj-png-1-tct-10.1177_15330338241245943 - Supplemental material for Feasibility Study of Computed Tomographic Radiomics Model for the Prediction of Early and Intermediate Stage Hepatocellular Carcinoma Using BCLC Staging

Supplemental material, sj-png-1-tct-10.1177_15330338241245943 for Feasibility Study of Computed Tomographic Radiomics Model for the Prediction of Early and Intermediate Stage Hepatocellular Carcinoma Using BCLC Staging by Han Dong, Lu Yang, Duan Shaofeng and Guo Lili in Technology in Cancer Research & Treatment</p