Anomalous organic magnetoresistance from competing carrier-spin-dependent interactions with localized electronic and nuclear spins

We describe a new regime for low-field magnetoresistance in organic semiconductors, in which the spin-relaxing effects of localized nuclear spins and electronic spins interfere. The regime is studied by the controlled addition of localized electronic spins to a material that exhibits substantial room-temperature magnetoresistance ($\sim 20$\%). Although initially the magnetoresistance is suppressed by the doping, at intermediate doping there is a regime where the magnetoresistance is insensitive to the doping level. For much greater doping concentrations the magnetoresistance is fully suppressed. The behavior is described within a theoretical model describing the effect of carrier spin dynamics on the current

An evaluation of the utilization of remote sensing in resource and environmental management of the Chesapeake Bay region

A nine-month study was conducted to assess the effectiveness of the NASA Wallops Chesapeake Bay Ecological Program in remote sensing. The study consisted of a follow-up investigation and information analysis of actual cases in which remote sensing was utilized by management and research personnel in the Chesapeake Bay region. The study concludes that the NASA Wallops Chesapeake Bay Ecological Program is effective, both in terms of costs and performance

Neural correlates of cognitive dissonance and choice-induced preference change

According to many modern economic theories, actions simply reflect an individual's preferences, whereas a psychological phenomenon called “cognitive dissonance” claims that actions can also create preference. Cognitive dissonance theory states that after making a difficult choice between two equally preferred items, the act of rejecting a favorite item induces an uncomfortable feeling (cognitive dissonance), which in turn motivates individuals to change their preferences to match their prior decision (i.e., reducing preference for rejected items). Recently, however, Chen and Risen [Chen K, Risen J (2010) J Pers Soc Psychol 99:573–594] pointed out a serious methodological problem, which casts a doubt on the very existence of this choice-induced preference change as studied over the past 50 y. Here, using a proper control condition and two measures of preferences (self-report and brain activity), we found that the mere act of making a choice can change self-report preference as well as its neural representation (i.e., striatum activity), thus providing strong evidence for choice-induced preference change. Furthermore, our data indicate that the anterior cingulate cortex and dorsolateral prefrontal cortex tracked the degree of cognitive dissonance on a trial-by-trial basis. Our findings provide important insights into the neural basis of how actions can alter an individual's preferences

Hyperfine interaction induced decoherence of electron spins in quantum dots

We investigate in detail, using both analytical and numerical tools, the decoherence of electron spins in quantum dots (QDs) coupled to a bath of nuclear spins in magnetic fields or with various initial bath polarizations, focusing on the longitudinal relaxation in low and moderate field/polarization regimes. An increase of the initial polarization of nuclear spin bath has the same effect on the decoherence process as an increase of the external magnetic field, namely, the decoherence dynamics changes from smooth decay to damped oscillations. This change can be observed experimentally for a single QD and for a double-QD setup. Our results indicate that substantial increase of the decoherence time requires very large bath polarizations, and the use of other methods (dynamical decoupling or control of the nuclear spins distribution) may be more practical for suppressing decoherence of QD-based qubits.Comment: Rev. Tex, 5 pages, 3 eps color figures, submitted to Phys. Rev.

Genome-Enabled Hitchhiking Mapping Identifies QTLs for Stress Resistance in Natural \u3ci\u3eDrosophila\u3c/i\u3e

Identification of genes underlying complex traits is an important problem. Quantitative trait loci (QTL) are mapped using marker-trait co-segregation in large panels of recombinant genotypes. Most frequently, recombinant inbred lines derived from two isogenic parents are used. Segregation pat-terns are also studied in pedigrees from multiple families. Great advances have been made through creative use of these techniques, but narrow sampling and inadequate power represent strong limi-tations. Here, we propose an approach combining the strengths of both techniques. We established a mapping population from a sample of natural genotypes and applied artificial selection for a com-plex character. Selection changed the frequencies of alleles in QTLs contributing to the selection re-sponse. We infer QTLs with dense genotyping microarrays by identifying blocks of linked markers undergoing selective changes in allele frequency. We demonstrated this approach with an experi-mental population composed from 20 isogenic strains. Selection for starvation survival was executed in three replicated populations with three control non-selected populations. Three individuals per population were genotyped using Affymetrix GeneChips. Two regions of the genome, one each on the left arms of the second and third chromosomes, showed significant divergence between control and selected populations. For the former region, we inferred allele frequencies in selected and control populations by pyrosequencing. We conclude that the allele frequency difference, averaging approx-imately 40% between selected and control lines, contributed to selection response. Our approach can contribute to the fine scale decomposition of the genetics of direct and indirect selection responses and genotype by environment interactions

Genome-Enabled Hitchhiking Mapping Identifies QTLs for Stress Resistance in Natural \u3ci\u3eDrosophila\u3c/i\u3e

Identification of genes underlying complex traits is an important problem. Quantitative trait loci (QTL) are mapped using marker-trait co-segregation in large panels of recombinant genotypes. Most frequently, recombinant inbred lines derived from two isogenic parents are used. Segregation pat-terns are also studied in pedigrees from multiple families. Great advances have been made through creative use of these techniques, but narrow sampling and inadequate power represent strong limi-tations. Here, we propose an approach combining the strengths of both techniques. We established a mapping population from a sample of natural genotypes and applied artificial selection for a com-plex character. Selection changed the frequencies of alleles in QTLs contributing to the selection re-sponse. We infer QTLs with dense genotyping microarrays by identifying blocks of linked markers undergoing selective changes in allele frequency. We demonstrated this approach with an experi-mental population composed from 20 isogenic strains. Selection for starvation survival was executed in three replicated populations with three control non-selected populations. Three individuals per population were genotyped using Affymetrix GeneChips. Two regions of the genome, one each on the left arms of the second and third chromosomes, showed significant divergence between control and selected populations. For the former region, we inferred allele frequencies in selected and control populations by pyrosequencing. We conclude that the allele frequency difference, averaging approx-imately 40% between selected and control lines, contributed to selection response. Our approach can contribute to the fine scale decomposition of the genetics of direct and indirect selection responses and genotype by environment interactions

Carbon flux from decomposing wood and its dependency on temperature, wood N2 fixation rate, moisture and fungal composition in a Norway spruce forest

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Digital electron microscopic examination of human sural nerve biopsies

Diabetic peripheral polyneuropathy is characterized by axonal degeneration and regeneration as well as by Schwann cell and microvascular changes. These changes have been described at both the light (LM) and the electron microscopic (EM) levels; however, EM has not been applied to large clinical trials. Our goal was to adapt the rigorous techniques used for quantifying human biopsies with LM image analysis to accommodate ultrastructural analyses. We applied digital image capture and analysis to the ultrastructural examination of axons in sural nerve biopsies from diabetic patients enrolled in a multicenter clinical trial. The selection of sural nerve biopsies was based on the quality of specimen fixation, absence of physical distortion, and nerve fascicle size (≥100 000; ≤425 000 µm 2 ). Thin sections were collected on formvar-coated slot grids, stabilized with carbon and scanned on a Phillips CM100 transmission electron microscope. Digital images were captured with a Kodak Megaplus 1.6 camera. A montage was constructed using software derived from aerial mapping applications, and this virtual image was viewed by EM readers. Computer-assisted analyses included identification and labeling of individual axons and axons within regenerating clusters. The average density of regenerating myelinated axon clusters per mm 2 was 65.8 ± 5.1, range of 0–412 ( n  = 193). These techniques increase the number of samples that may be analyzed by EM and extend the use of this technique to clinical trials using tissue biopsies as a primary endpoint.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72529/1/j.1085-9489.2003.03030.x.pd