Polarization memory in the nonpolar magnetic ground state of multiferroic CuFeO2

We investigate polarization memory effects in single-crystal CuFeO2, which has a magnetically-induced ferroelectric phase at low temperatures and applied B fields between 7.5 and 13 T. Following electrical poling of the ferroelectric phase, we find that the nonpolar collinear antiferromagnetic ground state at B = 0 T retains a strong memory of the polarization magnitude and direction, such that upon re-entering the ferroelectric phase a net polarization of comparable magnitude to the initial polarization is recovered in the absence of external bias. This memory effect is very robust: in pulsed-magnetic-field measurements, several pulses into the ferroelectric phase with reverse bias are required to switch the polarization direction, with significant switching only seen after the system is driven out of the ferroelectric phase and ground state either magnetically (by application of B > 13 T) or thermally. The memory effect is also largely insensitive to the magnetoelastic domain composition, since no change in the memory effect is observed for a sample driven into a single-domain state by application of stress in the [1-10] direction. On the basis of Monte Carlo simulations of the ground state spin configurations, we propose that the memory effect is due to the existence of helical domain walls within the nonpolar collinear antiferromagnetic ground state, which would retain the helicity of the polar phase for certain magnetothermal histories.Comment: 9 pages, 7 figure

Water Conservation

New Mexico always has had periods of water shortages, some far more long lasting and devastating than others. As warming temperature and changing weather patterns continue to develop, the likelihood that water shortages—like those felt throughout the state from 2010 through 2013—will occur with greater frequency. These changes can and have caused significant economic and environmental damage, and the risk of more harm will not improve unless we improve our water management significant

Uncertainties in Global Warming Temperature-Trend and Their Impacts on Agricultural Production: an Econometric Evaluation

IndonesianMakalah ini membahas kecenderungan dampak pemanasan global yang terjadi akhir-akhir ini. Estimasi dilakukan dengan parameter fraksional dari catatan relatif panjang menggunakan tehnik outlier aditif sebagai pengamatan bebas yang dihasilkan di atmosfer karena pemanasan global. Selanjutnya penelitian ini mengamati secara empiris dampak pemanasan global terhadap aspek tertentu produksi pertanian global. Berdasarkan simulasi Monte Carlo, proses menghasilkan data diterapkan dimana outlier aditif dihasilkan melalui cara discrete atau tidak kontinyu. Hasil observasi menunjukkan bahwa outlier aditif mempengaruhi bias dan MSE parameter fraksional estimasi. Ukuran outlier aditif dalam proses menghasilkan data juga memiliki pengaruh penting terhadap parameter farksional estimasi yang tergantung pada nilai parameter fraksional yang sebenarnya. Hasilnya menunjukkan variabilitas non tren atau siklus alami yang dipengaruhi oleh proses stokastik dalam hal sifat Perubahan iklim dengan observasi bebas (outlier) yang menghasilkan outcome berlawanan dari ketidakpastian yang intensif terhadap tren data temperatur dunia pada kondisi riil. Hasil pengamatan empiris menyimpulkan bahwa pada akhir abad 21 secara meyakinkan pemanasan global akan mempunyai dampak negatif terhadap agregat produksi pertanian global dan dampaknya bisa sangat parah jika manfaat fertilizasi karbon (peningkatan hasil dalam lingkungan yang kaya karbon) tidak tampak, terutama jika kelangkaan air membatasi irigasi. Lagi pula, jika pemasan global tidak berhenti pada tahun 2080, tetapi temperatur global terus meningkat pada abad 22, kegagalan produksi pertanian bisa semakin parah. Studi ini juga menunjukkan bahwa akumulasi pengaruh produksi pertanian kemungkinan lebih serius bagi negara berkembang dengan kerugian terbesar di Afrika, Amerika Latin, dan India. EnglishThis paper primarily attempts to detect the trend in the present upshots of global warming temperature data. It has been done through the estimation of the long memory fractional parameter using a simulation technique in the presence of additive outliers which stands as wild observations generated in the atmosphere due to global warming. Then, the study investigates empirically the impact of global warming on the particular aspect of global agricultural production. Based on Monte Carlo simulations, a data generating process is applied where additive outliers are generated in a discrete way. Observed facts reveal that additive outliers affect the bias and the MSE of the estimated fractional parameter. The size of the additive outliers in data generating process has also important effects on the estimated fractional parameter depending on the value of true fractional parameter. The result exhibits a non-trend or a natural cyclical variability influenced by a stochastic process in the case of climate change behavior with wild observations (outliers) that produce a contradictory outcome of profound uncertainties against the case of true world temperature data trend. The results of empirical investigations assert that in the late 21st century unabated global warming would have a negative impact on global agricultural production in the aggregate and the impact could be severe if carbon fertilization benefits (enhancements of yields in a carbon-rich environment) do not materialize, especially if water scarcity limits irrigation. In addition, if warming would not halt in the 2080s, but would continue on a path toward still higher global temperatures in the 22nd century, agricultural damage could be more severe. The study also shows that the composition of agricultural effects is likely to be seriously unfavorable to developing countries with the most severe losses in Africa, Latin America and India

Magnetodielectric effect of Bi6Fe2Ti3O18 film under an ultra-low magnetic field

Good quality and fine grain Bi6Fe2Ti3O18 magnetic ferroelectric films with single-phase layered perovskite structure have been successfully prepared via metal organic decomposition (MOD) method. Results of low-temperature magnetocapacitance measurements reveal that an ultra-low magnetic field of 10 Oe can produce a nontrivial magnetodielectric (MD) response in zero-field-cooling condition, and the relative variation of dielectric constants in magnetic field is positive, i.e., MD=0.05, when T<55K, but negative with a maximum of MD=-0.14 when 55K<T<190K. The magnetodielectric effect appears a sign change at 55K, which is due to transition from antiferromagnetic to weak ferromagnetic; and vanishes abruptly around 190K, which is thought to be associated with order-disorder transition of iron ion at B site of perovskite structures. The ultra-low-field magnetodielectric behaviour of Bi6Fe2Ti3O18 film has been discussed in the light of quasi-two-dimension unique nature of local spin order in ferroelectric film. Our results allow expectation on low-cost applications of detectors and switches for extremely weak magnetic fields in a wide temperature range 55K-190K.Comment: 10 pages 4 figures, planned to submit to J. Phys.: Condensed Matte

Uncertainties in Global Warming Temperature-Trend and Their Impacts on Agricultural Production: an Econometric Evaluation

IndonesianMakalah ini membahas kecenderungan dampak pemanasan global yang terjadi akhir-akhir ini. Estimasi dilakukan dengan parameter fraksional dari catatan relatif panjang menggunakan tehnik outlier aditif sebagai pengamatan bebas yang dihasilkan di atmosfer karena pemanasan global. Selanjutnya penelitian ini mengamati secara empiris dampak pemanasan global terhadap aspek tertentu produksi pertanian global. Berdasarkan simulasi Monte Carlo, proses menghasilkan data diterapkan dimana outlier aditif dihasilkan melalui cara discrete atau tidak kontinyu. Hasil observasi menunjukkan bahwa outlier aditif mempengaruhi bias dan MSE parameter fraksional estimasi. Ukuran outlier aditif dalam proses menghasilkan data juga memiliki pengaruh penting terhadap parameter farksional estimasi yang tergantung pada nilai parameter fraksional yang sebenarnya. Hasilnya menunjukkan variabilitas non tren atau siklus alami yang dipengaruhi oleh proses stokastik dalam hal sifat perubahan iklim dengan observasi bebas (outlier) yang menghasilkan outcome berlawanan dari ketidakpastian yang intensif terhadap tren data temperatur dunia pada kondisi riil. Hasil pengamatan empiris menyimpulkan bahwa pada akhir abad 21 secara meyakinkan pemanasan global akan mempunyai dampak negatif terhadap agregat produksi pertanian global dan dampaknya bisa sangat parah jika manfaat fertilizasi karbon (peningkatan hasil dalam lingkungan yang kaya karbon) tidak tampak, terutama jika kelangkaan air membatasi irigasi. Lagi pula, jika pemasan global tidak berhenti pada tahun 2080, tetapi temperatur global terus meningkat pada abad 22, kegagalan produksi pertanian bisa semakin parah. Studi ini juga menunjukkan bahwa akumulasi pengaruh produksi pertanian kemungkinan lebih serius bagi negara berkembang dengan kerugian terbesar di Afrika, Amerika Latin, dan India. EnglishThis paper primarily attempts to detect the trend in the present upshots of global warming temperature data. It has been done through the estimation of the long memory fractional parameter using a simulation technique in the presence of additive outliers which stands as wild observations generated in the atmosphere due to global warming. Then, the study investigates empirically the impact of global warming on the particular aspect of global agricultural production. Based on Monte Carlo simulations, a data generating process is applied where additive outliers are generated in a discrete way. Observed facts reveal that additive outliers affect the bias and the MSE of the estimated fractional parameter. The size of the additive outliers in data generating process has also important effects on the estimated fractional parameter depending on the value of true fractional parameter. The result exhibits a non-trend or a natural cyclical variability influenced by a stochastic process in the case of climate change behavior with wild observations (outliers) that produce a contradictory outcome of profound uncertainties against the case of true world temperature data trend. The results of empirical investigations assert that in the late 21st century unabated global warming would have a negative impact on global agricultural production in the aggregate and the impact could be severe if carbon fertilization benefits (enhancements of yields in a carbon-rich environment) do not materialize, especially if water scarcity limits irrigation. In addition, if warming would not halt in the 2080s, but would continue on a path toward still higher global temperatures in the 22nd century, agricultural damage could be more severe. The study also shows that the composition of agricultural effects is likely to be seriously unfavorable to developing countries with the most severe losses in Africa, Latin America and India

Using Wavelet to Analyze Periodicities in Hydrologic Variables

The trend and shift in the seasonal temperature, precipitation and streamflow time series across the Midwest have been analyzed, for the period 1960-2013, using the statistical analyses (Mann- Kendall test with and without considering short term persistence (MK2 and MK1, respectively) and Pettitt test). The paper also utilizes a relatively new approach, wavelet analysis, for testing the existence of trend and shift in the time series. The method has the ability to decompose a time series in to lower (trend) and higher frequency components (noise). Discrete wavelet transform (DWT) has been employed in the present study with an aim to find which periodicities are mainly responsible for trend in the original data. The combination of MK1, MK2, and DWT along with Pettitt test hasn’t been extensively used up to this time, especially in detecting trend and shift in the Midwest. The analysis of climate division temperature and precipitation data and USGS naturalized streamflow data revealed the presence of periodicity in the time series data. All the incorporated time series data were seasonal to analyze the trends and shifts for four seasons-winter, spring, summer and fall independently. D3 component of DWT were observed to be influential in detecting real trend in temperature, precipitation and streamflow data, however unlike temperature, precipitation and streamflow showed decreasing trend as well. Shift was relatively observed more than trend in the region with dominance of D3 component in the data. The result indicate the significant warming trend which agrees with the “increasing temperature” observations in the past two decades, however a clear explanation for precipitation and streamflow is not obvious