35 research outputs found

    PENERAPAN STRATEGI REACT UNTUK MENINGKATKAN KEMAMPUAN KONEKSI MATEMATIS SISWA SMP

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    Penelitian dengan fokus penerapan strategi REACT dalam pembelajaran matematika di kelas VIII salah satu SMP Negeri di Bandung, bertujuan mendeskripsikan peningkatan kemampuan koneksi matematis siswa. Penelitian ini menggunakan metode kuasi eksperimen dengan desain penelitian berbentuk desain kelompok kontrol pretest-posttest, pada sampel kelompok (kelas) eksperimen dengan 38 orang siswa dan kontrol dengan 40 orang siswa yang dipilih secara paralel. Hasil analisis data pretes dan postes, lembar observasi dan jurnal harian serta angket menyimpulkan bahwa peningkatan kemampuan koneksi matematis siswa yang pembelajarannya melalui REACT lebih tinggi daripada siswa yang pembelajarannya secara konvensional. Hampir seluruh siswa telah mencapai kriteria ketuntasan belajar minimal dan minat siswa terhadap pembelajaran matematika dengan strategi REACT tergolong baik. Kata kunci: strategi REACT, kemampuan koneksi matematis

    Comparison of the best models identified by GMDR for gene-gene and gene-environment interactions.

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    <p><sup>a</sup> The x1 x2 x3 x4 x6 x7 x9 x10 x11 y1 represent rs7200690, rs12185157, rs7198799, rs17715799, rs7186053, rs6499199, rs13689, rs4533622, rs4135385 and Menarche-FFTP interval (> 11 years vs ≤11 years) respectively.</p><p>* Both parous and nulliparous women were included. This parameter was calculated by age at FFTP minus age at menarche in all parous women, age at menopause minus age at menarche in postmenopausal nulliparous women, and age at breast tumor onset (case) or age at interview (control) minus age at menarche in premenopausal nulliparous women.</p><p><sup>b</sup> Adjusted for age, BMI, age at menarche, age of first birth and family history of cancer in first-degree relatives.</p><p>Comparison of the best models identified by GMDR for gene-gene and gene-environment interactions.</p

    Kaplan-Meier estimates of event-free survival among all patients and patients with stage 0-I tumors respectively.

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    <p>A and B for rs7200690; C and D for rs7198799; E and F for rs4533622. P values were calculated by log rank test.</p

    Kaplan-Meier estimates of event-free survival according to rs7186053 genotypes.

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    <p>A: among all breast cancer patients; B: among patients without lymph node metastasis; C: among patients with ER-positive tumors; D: among patients with PR-positive tumors. P values were calculated by log rank test.</p

    Stratified event-free survival analysis of rs rs7200690, rs7198799 in <i>CDH1</i> and rs4533622 in <i>CTNNB1</i> by clinical stage.

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    <p>* Adjusted for ER status, PR status, Her2 status, tumor size, clinical stage, lymphnode metastasis, chemotherapy and endocrine therapy.</p><p>Bold numbers indicate a statistical significance at 0.05 level.</p><p>Stratified event-free survival analysis of rs rs7200690, rs7198799 in <i>CDH1</i> and rs4533622 in <i>CTNNB1</i> by clinical stage.</p

    Illustratively showing the binding mode of the PB2 cap binding domain in the presence of the cap analog m7GTP.

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    <p>The protein structure was shown in a ribbon diagram, while m7GTP is in ball-and-stick representations. The secondary structure elements of the PB2 cap binding domain are labeled with α-helices in red and β-strands in yellow. The cap analog m7GTP is colored according to its atomic types.</p

    Binding free energies (kcal/mol) of m7GTP and other ligands calculated from both MM-PB/SA and MM-GB/SA.

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    <p>ΔE<sub>ele</sub>: non-bonded electrostatic energy+1,4-electrostatic energy.</p><p>ΔE<sub>vdw</sub>: non-bonded van der Waals energy+1,4-van der Waals energy </p><p>ΔG<sub>sur/PB</sub>: hydrophobic contributions to solvation free energy for the Possion Boltzmann calculations.</p><p>ΔG<sub>cal/PB</sub>: reaction field energy calculated by the Possion Boltzmann approach </p><p>ΔG<sub>sur/GB</sub>: hydrophobic contributions to solvatoion free energy for the Generalized Born calculations.</p><p>ΔG<sub>cal/PB</sub>: reaction field energy calculated by the Generalized Born approach</p
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