Penerapan Metode Pembelajaran Numbered Heads Together (Nht) Untuk Meningkatkan Motivasi Dan Hasil Belajar Kelarutan Dan Hasil Kali Kelarutan Kelas XI IPA 4 Sman 8 Surakarta Tahun Pelajaran 2012/2013

Tujuan penelitian ini adalah untuk meningkatkan (1) motivasi belajar kelarutan dan hasil kali kelarutan dan (2) hasil belajar kelarutan dan hasil kali kelarutan melalui penerapan metode pembelajaran Numbered Heads Together (NHT). Penelitian ini merupakan penelitian tindakan kelas (Classroom Action Research) yang dilaksanakan dalam dua siklus dimana setiap siklusnya terdiri atas empat tahapan, yaitu perencanaan, pelaksanaan, pengamatan, dan refleksi. Subjek penelitian adalah siswa kelas XI IPA 4 SMAN 8 Surakarta Tahun Pelajaran 2012/2013. Pengumpulan data dilakukan melalui pengamatan, wawancara, kajian dokumen, angket, dan tes. Data yang diperoleh divalidasi menggunakan teknik triangulasi sumber dan dianalisis menggunakan analisis deskriptif kualitatif yang mengacu pada Miles dan Huberman. Hasil penelitian menunjukkan capaian motivasi belajar pada siklus I dan siklus II masing-masing mencapai 58,33% dan 79,17%. Hasil belajar yang diukur pada aspek kognitif dan afektif menunjukkan pada siklus I mencapai 29,17% dan 62,5% serta pada siklus II mencapai 70,83% dan 83,33%. Simpulan penelitian ini adalah penerapan metode pembelajaran Numbered Heads Together (NHT) mampu meningkatkan (1) motivasi belajar kelarutan dan hasil kali kelarutan dan (2) hasil belajar kelarutan dan hasil kali kelarutan kelas XI IPA 4 SMAN 8 Surakarta

Self-Bridging of Vertical Silicon Nanowires and a Universal Capacitive Force Model for Spontaneous Attraction in Nanostructures

Spontaneous attractions between free-standing nanostructures have often caused adhesion or stiction that affects a wide range of nanoscale devices, particularly nano/microelectromechanical systems. Previous understandings of the attraction mechanisms have included capillary force, van der Waals/Casimir forces, and surface polar charges. However, none of these mechanisms universally applies to simple semiconductor structures such as silicon nanowire arrays that often exhibit bunching or adhesions. Here we propose a simple capacitive force model to quantitatively study the universal spontaneous attraction that often causes stiction among semiconductor or metallic nanostructures such as vertical nanowire arrays with inevitably nonuniform size variations due to fabrication. When nanostructures are uniform in size, they share the same substrate potential. The presence of slight size differences will break the symmetry in the capacitive network formed between the nanowires, substrate, and their environment, giving rise to electrostatic attraction forces due to the relative potential difference between neighboring wires. Our model is experimentally verified using arrays of vertical silicon nanowire pairs with varied spacing, diameter, and size differences. Threshold nanowire spacing, diameter, or size difference between the nearest neighbors has been identified beyond which the nanowires start to exhibit spontaneous attraction that leads to bridging when electrostatic forces overcome elastic restoration forces. This work illustrates a universal understanding of spontaneous attraction that will impact the design, fabrication, and reliable operation of nanoscale devices and systems

Results (<i>F</i> and <i>P</i> values) of a three-way ANOVA on the effects of year (Y), nitrogen addition (N), water addition (W), and their interactions on aboveground biomass (AGB, g m^-2), net ecosystem CO₂ exchange (NEE, μmol m^-2 s^-1), ecosystem respiration (ER, μmol m^-2 s^-1), and gross ecosystem productivity (GEP, μmol m^-2 s^-1).

<p>The bold numerals highlight significance at the <i>P</i> < 0.05 level.</p><p>Results (<i>F</i> and <i>P</i> values) of a three-way ANOVA on the effects of year (Y), nitrogen addition (N), water addition (W), and their interactions on aboveground biomass (AGB, g m^-2), net ecosystem CO₂ exchange (NEE, μmol m^-2 s^-1), ecosystem respiration (ER, μmol m^-2 s^-1), and gross ecosystem productivity (GEP, μmol m^-2 s^-1).</p

Positive dependence of growing season mean (A) net ecosystem CO₂ exchange (NEE, μmol m^-2 s^-1), (B) ecosystem respiration (ER, μmol m^-2 s^-1) and (C) gross ecosystem productivity (GEP, μmol m^-2 s^-1) on the amount of early growing season (Apr, May, Jun) precipitation (water added + natural precipitation) across the 3 years in both fertilized (open circles) and unfertilized plots (solid circles).

<p>Nitrogen fertilized plots include both the N and WN plots, and unfertilized plots include both the CK and W plots. Water addition was treated as a precipitation event and included in the calculation of the precipitation amount. * and ** represent significant relationships at the <i>P</i> < 0.05 and <i>P</i> < 0.01 levels, respectively.</p

Dependence of growing season mean (A) net ecosystem CO₂ exchange (NEE, μmol m^-2 s^-1), (B) ecosystem respiration (ER, μmol m^-2 s^-1), and (C) gross ecosystem productivity (GEP, μmol m^-2 s^-1) on aboveground biomass (AGB) across treatments in 2012 (solid circles), 2013 (open triangle), and 2014 (open square).

<p>** represents a significant relationship at the <i>P</i> < 0.01 level.</p

Responses of net ecosystem CO₂ exchange (NEE, μmol m^-2 s^-1) to monthly precipitation regimes (A, frequency; B, amount; C, intensity; D, evenness) across the 3 years for both nitrogen fertilized (open circles, A: y = Exp(2.240 – 2.662x^-1); B: y = Exp(2.017 – 6.269x^-1); C: y = Exp(2.053 – 1.190x^-1); D: y = Exp(2.479 – 0.316x^-1)) and unfertilized plots (solid circles, A: y = Exp(1.905 – 3.610x^-1); B: y = Exp(1.613 – 9.101x^-1); C: y = Exp(1.700 – 1.983x^-1); D: y = Exp(2.141 – 0.381x^-1)).

<p>Nitrogen fertilized plots include both N and WN plots, and unfertilized plots include both CK and W plots. Water addition was treated as a precipitation event and included in the calculation of monthly precipitation regimes. * and ** represent significant relationships at the <i>P</i> < 0.05 and <i>P</i> < 0.01 levels, respectively.</p

Seasonal dynamics and means of (A, B, and C) net ecosystem CO₂ exchange (NEE, μmol m^-2 s^-1), (D, E, and F) ecosystem respiration (ER, μmol m^-2 s^-1), and (G, H, and I) gross ecosystem productivity (GEP, μmol m^-2 s^-1) in 2012, 2013, and 2014.

<p>Different lowercase letters indicate significant differences (<i>P</i> < 0.05) in seasonal averages among treatments (Duncan’s test). CK: control; W: water addition; N: nitrogen addition; WN: water and nitrogen added in combination. Data are reported as mean ± 1 SD (<i>n</i> = 6).</p

Seasonal means of soil pH (unitless value), vegetation density of the community (VD, plant m^-2), <i>Leymus chinensis</i> importance value (IV), aboveground biomass (AGB, g m^-2), and belowground (to 10 cm depth) biomass (BGB, g m^-2) under different treatments in July across the 3 years.

<p>Values are presented as mean ± 1 SD (<i>n</i> = 6). Different letters in a column indicate significant difference among treatments at the <i>P</i> < 0.05 level (Duncan test). CK: control; W: water addition; N: nitrogen addition; WN: water and nitrogen added.</p><p>Seasonal means of soil pH (unitless value), vegetation density of the community (VD, plant m^-2), <i>Leymus chinensis</i> importance value (IV), aboveground biomass (AGB, g m^-2), and belowground (to 10 cm depth) biomass (BGB, g m^-2) under different treatments in July across the 3 years.</p

Seasonal patterns of (A) daily precipitation (bars, mm), daily mean air temperature (lines, °C), and (B) monthly precipitation (mm) in 2012, 2013, and 2014.

<p>Arrows on top of panel A indicate dates when water addition treatments were applied.</p

Appendix B. A table showing the initial vegetation characteristics and understory light availability among the four types of plots in August 2011.

A table showing the initial vegetation characteristics and understory light availability among the four types of plots in August 2011