7,885 research outputs found
BEBERAPA FAKTOR EKONOMI YANG MEMPENGARUHI KEMISKINAN DI KOTA SURABAYA
Tujuan yang hendak dicapai oleh penelitian ini adalah : untuk mengetahui pengaruh pendapatan perkapita, tabungan perkapita, kesempatan kerja, pengeluaran pemerintah terhadap kemiskinan di kota Surabaya.
Penelitian ini menggunakan data sekunder yang diperoleh dari Badan Pusat Statistik Jawa Timur. Teknik analisis yang digunakan dalam penelitian ini adalah regresi linier berganda dengan menggunakan alat bantu komputer program Statistic Program For Social science (SPSS) versi 13.0 yang menunjukkan pengaruh secara signifikan antara variabel bebas dan variabel terikat.
Melalui sistem regresi linier berganda dapat diperoleh persamaan regresi dengan menggunakan uji F regresi secara simultan variabel bebas berpengaruh secara nyata terhadap variabel terikat dengan F hitung = 18,700 > F tabel = 3,48 dengan menggunakan level of significant (α) = 0,05. Sedangkan dari pengujian secara parsial, menggunakan uji t dengan α/2 = 0,025, dapat diketahui bahwa variabel bebas pendapatan perkapita berpengaruh (X1) berpengaruh secara nyata terhadap tingkat kemiskinan di Surabaya (Y) dengan t hitung = 3,505 > t tabel = 2,228. Untuk variabel bebas tabungan perkapita (X2) diperoleh t hitung = 0,424 < t tabel = 2,228, secara parsial tabungan perkapita tidak berpengaruh secara nyata terhadap kemiskinan di Surabaya. Untuk variabel kesempatan kerja (X3) diperoleh t hitung = -0,250 < t tabel = -2,228, secara parsial kesempatan kerja tidak berpengaruh secara nyata terhadap kekemiskinan di Surabaya. Untuk variabel pengeluaran pemerintah (X4) diperoleh t hitung = -1,025 < t tabel = -2,228, secara parsial pengeluaran pemerintah tidak berpengaruh secara nyata terhadap kekemiskinan di Surabaya
CosmoHammer: Cosmological parameter estimation with the MCMC Hammer
We study the benefits and limits of parallelised Markov chain Monte Carlo
(MCMC) sampling in cosmology. MCMC methods are widely used for the estimation
of cosmological parameters from a given set of observations and are typically
based on the Metropolis-Hastings algorithm. Some of the required calculations
can however be computationally intensive, meaning that a single long chain can
take several hours or days to calculate. In practice, this can be limiting,
since the MCMC process needs to be performed many times to test the impact of
possible systematics and to understand the robustness of the measurements being
made. To achieve greater speed through parallelisation, MCMC algorithms need to
have short auto-correlation times and minimal overheads caused by tuning and
burn-in. The resulting scalability is hence influenced by two factors, the MCMC
overheads and the parallelisation costs. In order to efficiently distribute the
MCMC sampling over thousands of cores on modern cloud computing infrastructure,
we developed a Python framework called CosmoHammer which embeds emcee, an
implementation by Foreman-Mackey et al. (2012) of the affine invariant ensemble
sampler by Goodman and Weare (2010). We test the performance of CosmoHammer for
cosmological parameter estimation from cosmic microwave background data. While
Metropolis-Hastings is dominated by overheads, CosmoHammer is able to
accelerate the sampling process from a wall time of 30 hours on a dual core
notebook to 16 minutes by scaling out to 2048 cores. Such short wall times for
complex data sets opens possibilities for extensive model testing and control
of systematics.Comment: Published version. 17 pages, 6 figures. The code is available at
http://www.astro.ethz.ch/refregier/research/Software/cosmohamme
Keep your eyes on the goal! The impact of consumer goal pursuit on the effectiveness of subtle marketing cues
Consumers are exposed daily to various subtle marketing stimuli such as colors, brand logos, products characterized by multiple attributes or advertising messages bombarding them from numerous channels. All these subtle marketing cues can influence consumer judgment and decision-making, very often without their awareness. This dissertation demonstrates how states of varying motivational intensity (active vs. completed goals; unfulfilled vs. fulfilled desires) affect how consumers respond to such subtle marketing cues. Some examples of such cues specifically explored in this dissertation are primes (subtle cues incidentally activating knowledge structures such as trait concepts and stereotypes; Bargh, Chen, and Burrows 1996) or assortment cues. These subtle marketing stimuli are often embedded in the context, but are at the same time inconspicuous and unobtrusive, mildly steering consumers into specific decisions and choices. Through a specific focus on states of varying motivational intensity this dissertation pinpoints when and how subtle marketing cues are most likely to influence consumer judgment, decision-making, and behavior. As such, it presents a more refined picture looking at processing of contextual information through the lens of currently active motivations. Therefore, the main contribution of this work is to contextualize previous findings, demonstrating not only when subtle contextual cues (e.g, primes, assortment cues) drive consumer decision-making, but also when they fail to shape these decisions
Keep your eyes on the goal! The impact of consumer goal pursuit on the effectiveness of subtle marketing cues
Consumers are exposed daily to various subtle marketing stimuli such as colors, brand logos, products characterized by multiple attributes or advertising messages bombarding them from numerous channels. All these subtle marketing cues can influence consumer judgment and decision-making, very often without their awareness. This dissertation demonstrates how states of varying motivational intensity (active vs. completed goals; unfulfilled vs. fulfilled desires) affect how consumers respond to such subtle marketing cues. Some examples of such cues specifically explored in this dissertation are primes (subtle cues incidentally activating knowledge structures such as trait concepts and stereotypes; Bargh, Chen, and Burrows 1996) or assortment cues. These subtle marketing stimuli are often embedded in the context, but are at the same time inconspicuous and unobtrusive, mildly steering consumers into specific decisions and choices. Through a specific focus on states of varying motivational intensity this dissertation pinpoints when and how subtle marketing cues are most likely to influence consumer judgment, decision-making, and behavior. As such, it presents a more refined picture looking at processing of contextual information through the lens of currently active motivations. Therefore, the main contribution of this work is to contextualize previous findings, demonstrating not only when subtle contextual cues (e.g, primes, assortment cues) drive consumer decision-making, but also when they fail to shape these decisions
The Effects of Vespa Amino Acid Mixture on Cycling Performance During a 20k Time Trial
The effects of Vespa Amino Acid Mixture on cycling performance during a 20k time trial.
Sebastian Haynes and Adam Parker, Ph.D.
Department of Kinesiology
Angelo State University, San Angelo, TX
Category: Undergraduate
Mentor: Adam Parker ([email protected])
Abstract
Vespa amino acid mixture (VAAM) is a nutritional supplement derived from the Asian Mandarin Wasp (Vespa Mandarina). VAAM has been shown to enhance lipolysis in rat adipocytes and is purported to improve endurance performance via enhanced fat metabolism. The purpose of this study was to examine the effects VAAM on cycling performance during a 20k time trial. 10 trained, male cyclists participated in this single-blind, randomized, cross-over study. Participants were asked to perform two 20 kilometer time trials on a CompuTrainer (RacerMate, Inc. Seattle, WA) on two separate occasions separated by at least 48 hours. Participants consumed either an 80 mL serving of VAAM (70 mg of wasp extract, 8 g of carbohydrate, 31 kcal) or 80 mL of sports drink placebo (PL) (4.7 g carbohydrate, 18 kcal) in a randomized, cross-over fashion. Dependent variables included time to complete the 20k distance (TT), peak power, average power, max heart rate (MHR), and average heart rate. Data was analyzed using paired t-tests. The participants’ MHR was significantly lower (p = .021) after consuming VAAM (174.4 + 13.6 bpm) vs. PL (178.8 + 14 bpm). There was no significant difference (p = .349) in TT performance; VAAM (38.3 + 3.5 min) vs. PL (37.96 + 2.87 min). There were no other significant differences between supplement groups. Although we found no significant effects on cycling performance, future research should examine the effects of VAAM during more prolonged and/or exhaustive endurance exercise
Simulating the Large-Scale Structure of HI Intensity Maps
Intensity mapping of neutral hydrogen (HI) is a promising observational probe
of cosmology and large-scale structure. We present wide field simulations of HI
intensity maps based on N-body simulations of a box with
particles (particle mass ).
Using a conditional mass function to populate the simulated dark matter density
field with halos below the mass resolution of the simulation (), we assign HI to
those halos according to a phenomenological halo to HI mass relation. The
simulations span a redshift range of 0.35 < z < 0.9 in redshift bins of width
and cover a quarter of the sky at an angular resolution
of about 7'. We use the simulated intensity maps to study the impact of
non-linear effects and redshift space distortions on the angular clustering of
HI. Focusing on the autocorrelations of the maps, we apply and compare several
estimators for the angular power spectrum and its covariance. We verify that
these estimators agree with analytic predictions on large scales and study the
validity of approximations based on Gaussian random fields, particularly in the
context of the covariance. We discuss how our results and the simulated maps
can be useful for planning and interpreting future HI intensity mapping
surveys.Comment: 35 pages, 19 Figures. Accepted for publication in JCA
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