Electrical Transport Across an Individual Magnetic Domain Wall in (Ga,Mn)As Microdevices

Recent studies demonstrate that an individual magnetic domain wall (DW) can be trapped and reproducibly positioned within multiterminal (Ga,Mn)As microdevices. The electrical resistance obtained from such measurements is found to be measurably altered by the presence of this single entity. To elucidate these observations we develop a simple model for the electrical potential distribution along a multiterminal device in the presence of a single DW. This is employed to calculate the effect of a single DW upon the longitudinal and transverse resistance. The model provides very good agreement with experimental observations, and serves to highlight important deviations from simple theory. We show that measurements of transverse resistance along the channel permits establishing the position and the shape of the DW contained within it. An experimental scheme is developed that enables unambiguous extraction of the intrinsic DW resistivity. This permits the intrinsic contribution to be differentiated from resistivities originating from the bulk and from magnetic anisotropy - effects that are generally manifested as large backgrounds in the experiments.Comment: Submitted to Physical Review

Framework to Create Cloud-Free Remote Sensing Data Using Passenger Aircraft as the Platform

Cloud removal in optical remote sensing imagery is essential for many Earth observation applications.Due to the inherent imaging geometry features in satellite remote sensing, it is impossible to observe the ground under the clouds directly; therefore, cloud removal algorithms are always not perfect owing to the loss of ground truth. Passenger aircraft have the advantages of short visitation frequency and low cost. Additionally, because passenger aircraft fly at lower altitudes compared to satellites, they can observe the ground under the clouds at an oblique viewing angle. In this study, we examine the possibility of creating cloud-free remote sensing data by stacking multi-angle images captured by passenger aircraft. To accomplish this, a processing framework is proposed, which includes four main steps: 1) multi-angle image acquisition from passenger aircraft, 2) cloud detection based on deep learning semantic segmentation models, 3) cloud removal by image stacking, and 4) image quality enhancement via haze removal. This method is intended to remove cloud contamination without the requirements of reference images and pre-determination of cloud types. The proposed method was tested in multiple case studies, wherein the resultant cloud- and haze-free orthophotos were visualized and quantitatively analyzed in various land cover type scenes. The results of the case studies demonstrated that the proposed method could generate high quality, cloud-free orthophotos. Therefore, we conclude that this framework has great potential for creating cloud-free remote sensing images when the cloud removal of satellite imagery is difficult or inaccurate

Composite Analysis-Based Machine Learning for Prediction of Tropical Cyclone-Induced Sea Surface Height Anomaly

Sea surface height anomaly (SSHA) induced by tropical cyclones (TCs) is closely associated with oscillations and is a crucial proxy for thermocline structure and ocean heat content in the upper ocean. The prediction of TC-induced SSHA, however, has been rarely investigated. This study presents a new composite analysis-based random forest (RF) approach to predict daily TC-induced SSHA. The proposed method utilizes TC’s characteristics and pre-storm upper oceanic parameters as input features to predict TC-induced SSHA up to 30 days after TC passage. Simulation results suggest that the proposed method is skillful at inferring both the amplitude and temporal evolution of SSHA induced by TCs of different intensity groups. Using a TC-centered 5°×5° box, the proposed method achieves highly accurate prediction of TC-induced SSHA over the Western North Pacific with root mean square error of 0.024m, outperforming alternative machine learning methods and the numerical model. Moreover, the proposed method also demonstrated good prediction performance in different geographical regions, i.e., the South China Sea and the Western North Pacific subtropical ocean. The study provides insight into the application of machine learning in improving the prediction of SSHA influenced by extreme weather conditions. Accurate prediction of TC-induced SSHA allows for better preparedness and response, reducing the impact of extreme events (e.g., storm surge) on people and property

Randomized controlled trial to treat migraine with acupuncture: design and protocol

<p>Abstract</p> <p>Background and motivation</p> <p>The effectiveness of using acupuncture to treat migraine is rarely and even suspectedly reported in the literature. In this article, we report the design and the protocol of a randomized controlled large-scale trial to treat migraine using acupuncture, aiming at testifying it is effective to use acupuncture to treat migraine. We demonstrate also that the effectiveness of the treatment may vary due to using acupoints of different meridians or different acupoints of one meridian.</p> <p>Methods and design</p> <p>A multi-center randomized controlled trial is currently undergoing, with three acupoints treatment groups and one non-acupoints control group. The acupuncture treatment consists of 20 sessions per patient with a observation period of 20 weeks. In total, 480 patients with Migraine are registered in this study within 8 hospitals in China from March 2008 to June 2009. These patients are randomly assigned to receive one of the following four acupoints treatment groups, i.e. 1) specific acupoints of Shaoyang meridians (120 patients), 2) non-specific acupoints of Shaoyang meridians (120 patients), 3) acupoints of other meridians (120 patients); or 4) non-acupoints control group (120 patients). The main outcome measurement in this trial is the effect comparison achieved among these four groups in terms of number of days with migraine and intensity of migraine during and after the baseline phase, i.e. the first 4 weeks before randomization and 4, 8 and 16 weeks after randomization. The intensity of headache including Headache intensity grade (0–3) and visual analogue scale (VAS) score will also be used in this study. In addition, the differences of Migraine-Specific Quality-of-Life Questionnaire (MSQ) and Transcranial Doppler Sonography (TCD) before and after randomization are also used as the secondary outcome measurement.</p> <p>Discussion</p> <p>The result of this trial (which will be available in 2009) will demonstrate the efficacy of using acupuncture to treat migraine, and verify whether the specific effect of acupoints exists and whether this specific effect of acupoints is related to meridian and a collection of meridian Qi.</p> <p>Trials registration</p> <p>Clinical Trials.gov NCT00599586</p

Sensitive fluorescence detection of nucleic acids based on isothermal circular strand-displacement polymerization reaction

Here we have developed a sensitive DNA amplified detection method based on isothermal strand-displacement polymerization reaction. This method takes advantage of both the hybridization property of DNA and the strand-displacement property of polymerase. Importantly, we demonstrate that our method produces a circular polymerization reaction activated by the target, which essentially allows it to self-detect. Functionally, this DNA system consists of a hairpin fluorescence probe, a short primer and polymerase. Upon recognition and hybridization with the target ssDNA, the stem of the hairpin probe is opened, after which the opened probe anneals with the primer and triggers the polymerization reaction. During this process of the polymerization reaction, a complementary DNA is synthesized and the hybridized target is displaced. Finally, the displaced target recognizes and hybridizes with another probe, triggering the next round of polymerization reaction, reaching a target detection limit of 6.4 × 10−15 M

The mHz quasi-regular modulations of 4U 1630--47 during its 1998 outburst

We present the results of a detailed timing and spectral analysis of the quasi-regular modulation (QRM) phenomenon in the black hole X-ray binary 4U 1630--47 during its 1998 outburst observed by Rossi X-ray Timing Explore (RXTE). We find that the $\sim$ 50-110 mHz QRM is flux dependent, and the QRM is detected with simultaneous low frequency quasi-periodic oscillations (LFQPOs). According to the behavior of the power density spectrum, we divide the observations into four groups. In the first group, namely behavior A, LFQPOs are detected, but no mHz QRM. The second group, namely behavior B, a QRM with frequency above $\sim$ 88 mHz is detected and the $\sim$ 5 Hz and $\sim$ 7 Hz LFQPOs are almost overlapping. In the third group, namely behavior C, the QRM frequency below $\sim$ 88 mHz is detected and the LFQPOs are significantly separated. In the forth group, namely behavior D, neither QRM nor LFQPOs are detected. We study the energy-dependence of the fractional rms, centroid frequency, and phase-lag of QRM and LFQPOs for behavior B and C. We then study the evolution of QRM and find that the frequency of QRM increases with hardness, while its rms decreases with hardness. We also analyze the spectra of each observation, and find that the QRM rms of behavior B has a positive correlation with $\rm F_{\rm powerlaw}$ / $\rm F_{\rm total}$. Finally, we give our understanding for this mHz QRM phenomena.Comment: 14pages, 15 figure

Using force spectroscopy analysis to improve the properties of the hairpin probe

The sensitivity of hairpin-probe-based fluorescence resonance energy transfer (FRET) analysis was sequence-dependent in detecting single base mismatches with different positions and identities. In this paper, the relationship between the sequence-dependent effect and the discrimination sensitivity of a single base mismatch was systematically investigated by fluorescence analysis and force spectroscopy analysis. The same hairpin probe was used. The uneven fluorescence analysis sensitivity was obviously influenced by the guanine-cytosine (GC) contents as well as the location of the mismatched base. However, we found that force spectroscopy analysis distinguished itself, displaying a high and even sensitivity in detecting differently mismatched targets. This could therefore be an alternative and novel way to minimize the sequence-dependent effect of the hairpin probe. The advantage offered by force spectroscopy analysis could mainly be attributed to the percentage of rupture force reduction, which could be directly and dramatically influenced by the percentage of secondary structure disruption contributed by each mismatched base pair, regardless of its location and identity. This yes-or-no detection mechanism should both contribute to a comprehensive understanding of the sensitivity source of different mutation analyses and extend the application range of hairpin probes

Genetic Variation of the Human α-2-Heremans-Schmid Glycoprotein (AHSG) Gene Associated with the Risk of SARS-CoV Infection

Genetic background may play an important role in the process of SARS-CoV infection and SARS development. We found several proteins that could interact with the nucleocapsid protein of the SARS coronavirus (SARS-CoV). α-2-Heremans-Schmid Glycoprotein (AHSG), which is required for macrophage deactivation by endogenous cations, is associated with inflammatory regulation. Cytochrome P450 Family 3A (CYP4F3A) is an ω-oxidase that inactivates Leukotriene B4 (LTB4) in human neutrophils and the liver. We investigated the association between the polymorphisms of these two inflammation-associated genes and SARS development. The linkage disequilibrium (LD) maps of these two genes were built with Haploview using data on CHB+JPT (version 2) from the HapMap. A total of ten tag SNPs were selected and genotyped. In the Guangzhou cohort study, after adjusting for age and sex, two AHSG SNPs and one CYP4F3 SNP were found to be associated with SARS susceptibility: rs2248690 (adjusted odds ratio [AOR] 2.42; 95% confidence interval [CI] 1.30-4.51); rs4917 (AOR 1.84; 95% CI 1.02-3.34); and rs3794987 (AOR 2.01; 95% CI 1.10–3.68). To further validate the association, the ten tag SNPs were genotyped in the Beijing cohort. After adjusting for age and sex, only rs2248690 (AOR, 1.63; 95% CI, 1.30–2.04) was found to be associated with SARS susceptibility. The combined analysis of the two studies confirmed tag SNP rs2248690 in AHSG as a susceptibility variant (AOR 1.70; 95% CI 1.37–2.09). The statistical analysis of the rs2248690 genotype data among the patients and healthy controls in the HCW cohort, who were all similarly exposed to the SARS virus, also supported the findings. Further, the SNP rs2248690 affected the transcriptional activity of the AHSG promoter and thus regulated the AHSG serum level. Therefore, our study has demonstrated that the AA genotype of rs2268690, which leads to a higher AHSG serum concentration, was significantly associated with protection against SARS development