Modelling exchange bias in core/shell nanoparticles

We present an atomistic model of a single nanoparticle with core/shell structure that takes into account its lattice strucutre and spherical geometry, and in which the values of microscopic parameters such as anisotropy and exchange constants can be tuned in the core, shell and interfacial regions. By means of Monte Carlo simulations of the hysteresis loops based on this model, we have determined the range of microscopic parameters for which loop shifts after field cooling can be observed. The study of the magnetic order of the interfacial spins for different particles sizes and values of the interfacial exchange coupling have allowed us to correlate the appearance of loop asymmetries and vertical displacements to the existence of a fraction of uncompensated spins at the shell interface that remain pinned during field cycling, offering new insight on the microscopic origin of the experimental phenomenology.Comment: 7 pages, 3 figures. Contribution presented at HMM 2007 held at Napoli 4-6 June 2007. To be published in J. Phys. Condens. Matte

Exploring Clinician Attitudes Towards Treating Eating Disorders: Bridging Counselor Training Gaps

Eating disorder (ED) clinicians may face various challenges in practice, including burnout and feelings of incompetence. Several deficits may contribute to these challenges, such as graduate education and treatment gaps. In this study, 109 interdisciplinary clinicians were surveyed regarding their personal attitudes, experiences, and challenges in treating EDs. Among the various results, quantitative and qualitative findings highlighted the lack of graduate education as the primary challenge to effectively treating EDs, as well as the need for more ED research and culturally responsive care. Recommendations to enhance ED education and counselor training are provided, including managing countertransference and advocating for specialized coursework. Lastly, critical directions for future research are discussed

A visual embedding for the unsupervised extraction of abstract semantics

Vector-space word representations obtained from neural network models have been shown to enable semantic operations based on vector arithmetic. In this paper, we explore the existence of similar information on vector representations of images. For that purpose we define a methodology to obtain large, sparse vector representations of image classes, and generate vectors through the state-of-the-art deep learning architecture GoogLeNet for 20 K images obtained from ImageNet. We first evaluate the resultant vector-space semantics through its correlation with WordNet distances, and find vector distances to be strongly correlated with linguistic semantics. We then explore the location of images within the vector space, finding elements close in WordNet to be clustered together, regardless of significant visual variances (e.g., 118 dog types). More surprisingly, we find that the space unsupervisedly separates complex classes without prior knowledge (e.g., living things). Afterwards, we consider vector arithmetics. Although we are unable to obtain meaningful results on this regard, we discuss the various problem we encountered, and how we consider to solve them. Finally, we discuss the impact of our research for cognitive systems, focusing on the role of the architecture being used.This work is partially supported by the Joint Study Agreement no. W156463 under the IBM/BSC Deep Learning Center agreement, by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project and by the Generalitat de Catalunya (contracts 2014-SGR-1051), and by the Core Research for Evolutional Science and Technology (CREST) program of Japan Science and Technology Agency (JST).Peer ReviewedPostprint (published version

Materiales silico-carbonosos en el Precámbrico de Sierra Morena

[Resumen] Se aborda, por primera vez, un estudio comparativo de las cuarcitas negras del Precámbrico de Sierra Morena, evidenciando su carácter de rocas sílico-carbonosas, asociadas a sucesiones con importantes aportes volcánicos y producidas por precipitaci6n química-bioquímica de sílice en medios marinos someros y restringidos. Se discute su distribuci6n, valor en la correlación es tratigráfica, evoluci6n textural con el aumento del metamorfismo y la deformación y algunos de los caracteres generales de su quimismo y mineralogíaAbstract] A comparative study of the black quarzites of the Precambrian of Sierra ~orena is atte~pted here for the 'first time, which reveals their character of silicacarbonaceous rocks related to succesion with important volcanic contributions and produced by chemical-biochemical precipitacion of silica in restricted and shallow marine environments. It is discussed their distribution value in .stratigraphical correlation, textural evolution with increasing rnetamorfism ando deformation, and sorne of the general character of its chemistry and mineralog

Normalization factors for magnetic relaxation of small particle systems in non-zero magnetic field

We critically discuss relaxation experiments in magnetic systems that can be characterized in terms of an energy barrier distribution, showing that proper normalization of the relaxation data is needed whenever curves corresponding to different temperatures are to be compared. We show how these normalization factors can be obtained from experimental data by using the $T \ln(t/\tau_0)$ scaling method without making any assumptions about the nature of the energy barrier distribution. The validity of the procedure is tested using a ferrofluid of Fe_3O_4 particles.Comment: 5 pages, 6 eps figures added in April 22, to be published in Phys. Rev. B 55 (1 April 1997

Evaluating the potential use of a dairy industry residue to induce denitrification in polluted water bodies: a flow-through experiment

Improving the effectiveness and economics of strategies to remediate groundwater nitrate pollution is a matter of concern. In this context, the addition of whey into aquifers could provide a feasible solution to attenuate nitrate contamination by inducing heterotrophic denitrification, while recycling an industry residue. Before its application, the efficacy of the treatment must be studied at laboratory-scale to optimize the application strategy in order to avoid the generation of harmful intermediate compounds. To do this, a flow-through denitrification experiment using whey as organic C source was performed, and different C/N ratios and injection periodicities were tested. The collected samples were analyzed to determine the chemical and isotopic composition of N and C compounds. The results proved that whey could promote denitrification. Nitrate was completely removed when using either a 3.0 or 2.0 C/N ratio. However, daily injection with C/N ratios from 1.25 to 1.5 seemed advantageous, since this strategy decreased nitrate concentration to values below the threshold for water consumption while avoiding nitrite accumulation and whey release with the outflow. The isotopic results confirmed that nitrate attenuation was due to denitrification and that the production of DIC was related to bacterial whey oxidation. Furthermore, the isotopic data suggested that when denitrification was not complete, the outflow could present a mix of denitrified and nondenitrified water. The calculated isotopic fractionation values (ε15NNO3/N2 and ε18ONO3/N2) might be applied in the future to quantify the efficiency of the bioremediation treatments by whey application at field-scale

Numerical modeling of enhanced biodenitrification in a laboratory flow-through experiment

High concentration of nitrate (NO3) in water resources has become a widespread and important environmental contaminant, being anthropogenic nitrogen input the principal source of NO3− pollution (Arauzo, 2017). Underanaerobic conditions, microbial reduction of NO3 to N2(g) to oxidize dissolved organic carbon (DOC) is the principal NO3 attenuation process in groundwater aquifers (Matchett et al., 2019)