Surface anisotropy and particle size influence on hysteresis loops in La2/3Ca1/3MnO3 nanoparticles : A simulation approach

Thermal and hysteretic magnetic properties of La2/3Ca1/3MnO3 nanoparticles were studied using Monte Carlo simulations, with emphasis on the influence of anisotropy. In this work, several nanoparticle sizes ranging from 2.32 to 11.58 nm were analyzed and their properties were compared to those of the bulk material. The magnetic behavior of the material was modeled using the three dimensional Heisenberg model with nearest neighbor interactions. Furthermore, both uniaxial and Néel anisotropies were considered for core and surface magnetic sites respectively. Deviations in the critical temperature and coercive field were observed for nanoparticles when compared with those of the bulk material. In addition to these properties, the special spin configurations that arise from the competition between the exchange, anisotropy and external magnetic field were also studied. All these effects are interpreted in terms of the surface properties such as the Néel anisotropy and the decrease in the coordination number

Kernel Spectral Clustering and applications

In this chapter we review the main literature related to kernel spectral clustering (KSC), an approach to clustering cast within a kernel-based optimization setting. KSC represents a least-squares support vector machine based formulation of spectral clustering described by a weighted kernel PCA objective. Just as in the classifier case, the binary clustering model is expressed by a hyperplane in a high dimensional space induced by a kernel. In addition, the multi-way clustering can be obtained by combining a set of binary decision functions via an Error Correcting Output Codes (ECOC) encoding scheme. Because of its model-based nature, the KSC method encompasses three main steps: training, validation, testing. In the validation stage model selection is performed to obtain tuning parameters, like the number of clusters present in the data. This is a major advantage compared to classical spectral clustering where the determination of the clustering parameters is unclear and relies on heuristics. Once a KSC model is trained on a small subset of the entire data, it is able to generalize well to unseen test points. Beyond the basic formulation, sparse KSC algorithms based on the Incomplete Cholesky Decomposition (ICD) and $L_0$, $L_1, L_0 + L_1$, Group Lasso regularization are reviewed. In that respect, we show how it is possible to handle large scale data. Also, two possible ways to perform hierarchical clustering and a soft clustering method are presented. Finally, real-world applications such as image segmentation, power load time-series clustering, document clustering and big data learning are considered.Comment: chapter contribution to the book "Unsupervised Learning Algorithms

Geochemistry of REE, Zr and Hf in a wide range of pH and water composition: The Nevado del Ruiz volcano-hydrothermal system (Colombia)

The geochemical behaviour of Rare Earth Elements, Zr and Hf was investigated in the thermal waters of Nevado del Ruiz volcano system. A wide range of pH, between 1.0 and 8.8, characterizes these fluids. The acidicwaters are sulphate dominatedwith different Cl/SO4 ratios. The important role of the pH and the ionic complexes for the distribution of REE, Zr and Hf in the aqueous phase was evidenced. The pH rules the precipitation of authigenic Fe and Al oxyhydroxides producing changes in REE, Zr, Hf amounts and strong anomalies of Cerium. The precipitation of alunite and jarosite removes LREE from the solution, changing the REE distribution in acidic waters. Y-Ho and Zr-Hf (twin pairs) have a different behaviour in strong acidic waterswith respect to the water with pH near-neutral. Yttrium and Ho behave as Zr and Hf in waters with pH near neutral-to-neutral, showing superchondritic ratios. The twin pairs showed to be sensitive to the co-precipitation and/or adsorption onto the surface of authigenic particulate (Fe-, Al-oxyhydroxides), suggesting an enhanced scavenging of Ho and Hf with respect to Y and Zr, leading to superchondritic values. In acidic waters, a different behaviour of twin pairs occurs with chondritic Y/Ho ratios and sub-chondritic Zr/Hf ratios. For the first time, Zr and Hf were investigated in natural acidic fluids to understand the behaviour of these elements in extreme acidic conditions and different major anion chemistry. Zr/Hf molar ratio changes from 4.75 to 49.29 in water with pH < 3.6. In strong acidic waters the fractionation of Zr and Hf was recognized as function of major anion contents (Cl and SO4), suggesting the formation of complexes leading to sub-chondritic Zr/Hf molar ratios

Optimal phase space sampling for Monte Carlo simulations of Heisenberg spin systems

We present an adaptive algorithm for the optimal phase space sampling in Monte Carlo simulations of 3D Heisenberg spin systems. Based on a golden rule of the Metropolis algorithm which states that an acceptance rate of 50% is ideal to efficiently sample the phase space, the algorithm adaptively modifies a cone-based spin update method keeping the acceptance rate close to 50%. We have assessed the efficiency of the adaptive algorithm through four different tests and contrasted its performance with that of other common spin update methods. In systems at low and high temperatures and anisotropies, the adaptive algorithm proved to be the most efficient for magnetization reversal and for the convergence to equilibrium of the thermal averages and the coercivity in hysteresis calculations. Thus, the adaptive algorithm can be used to significantly reduce the computational cost in Monte Carlo simulations of 3D Heisenberg spin systems

Influence of Anesthesia and Clinical Variables on the Firing Rate, Coefficient of Variation and Multi-Unit Activity of the Subthalamic Nucleus in Patients with Parkinson's Disease

BACKGROUND: Microelectrode recordings (MER) are used to optimize lead placement during subthalamic nucleus deep brain stimulation (STN-DBS). To obtain reliable MER, surgery is usually performed while patients are awake. Procedural sedation and analgesia (PSA) is often desirable to improve patient comfort, anxiolysis and pain relief. The effect of these agents on MER are largely unknown. The objective of this study was to determine the effects of commonly used PSA agents, dexmedetomidine, clonidine and remifentanil and patient characteristics on MER during DBS surgery. METHODS: Data from 78 patients with Parkinson's disease (PD) who underwent STN-DBS surgery were retrospectively reviewed. The procedures were performed under local anesthesia or under PSA with dexmedetomidine, clonidine or remifentanil. In total, 4082 sites with multi-unit activity (MUA) and 588 with single units were acquired. Single unit firing rates and coefficient of variation (CV), and MUA total power were compared between patient groups. RESULTS: We observed a significant reduction in MUA, an increase of the CV and a trend for reduced firing rate by dexmedetomidine. The effect of dexmedetomidine was dose-dependent for all measures. Remifentanil had no effect on the firing rate but was associated with a significant increase in CV and a decrease in MUA. Clonidine showed no significant effect on firing rate, CV or MUA. In addition to anesthetic effects, MUA and CV were also influenced by patient-dependent variables. CONCLUSION: Our results showed that PSA influenced neuronal properties in the STN and the dexmedetomidine (DEX) effect was dose-dependent. In addition, patient-dependent characteristics also influenced MER

Variables hormonales y bioquímicas de la densidad mineral ósea y su correlación con hombres jóvenes obesos y no obesos sin diabetes

Introducción: la obesidad se ha asociado con mayor densidad mineral ósea (DMO), sin embargo, recientes estudios reportan que pudiese conllevar incremento de la resorción ósea y, por ende, mayor riesgo de fractura. Metodología: estudio de corte transversal analítico en donde se incluyeron hombres entre 18 y 30 años en quienes se realizaron diversas mediciones hormonales (insulina, testosterona libre y total, IGF-1, estradiol, leptina y adiponectina), bioquímicas (PTOG-glucosa, colesterol total, cHDL, cLDL, proteína C reactiva y HOMA-IR), antropométricas y otras, como composición grasa corporal, DMO y composición mineral ósea. Se evaluaron las diferencias de las variables cuantitativas entre obesos y no obesos mediante una prueba T-student o prueba de Wilcoxon. Para evaluar la correlación de DMO con las demás variables se usó la correlación de Spearman. Finalmente, se realizó un modelo de regresión lineal para predecir la DMO. Resultados: se incluyen 34 obesos y 35 no obesos. En el grupo de no obesos se obtuvo una media de 1,159 +/- 0,08 g/ cm2 de DMO comparado con el grupo de hombres obesos, con una media de 1,311 +/- 0,1 g/cm2 (p = 0,001). Se encontró que la DMO tiene una correlación fuerte con el contenido mineral óseo en los obesos respecto a los no obesos 3412,37 g (+/- 454,01) vs. 2575,96 g (+/-388,04), respectivamente, p <0,001. La adiponectina se correlacionó de forma negativa, aunque sin significancia en los obesos respecto a la densidad mineral ósea (r: -0,1913 y p = 0,27) y de forma débil y no significativa con los no obesos (r: 0,0074 y p = 0,96). Finalmente, se encontró que la presencia de obesidad, grasa total, contenido mineral óseo, insulina basal y HOMA-IR predicen de forma significativa la DMO en un modelo de regresión lineal. Conclusión: la DMO y el contenido mineral óseo son más altos en individuos obesos comparados con individuos no obesos, el índice de masa corporal y variables como insulina predicen la densidad mineral ósea

Magnetic stray fields in nanoscale magnetic tunnel junctions

The magnetic stray field is an unavoidable consequence of ferromagnetic devices and sensors leading to a natural asymmetry in magnetic properties. Such asymmetry is particularly undesirable for magnetic random access memory applications where the free layer can exhibit bias. Using atomistic dipole-dipole calculations we numerically simulate the stray magnetic field emanating from the magnetic layers of a magnetic memory device with different geometries. We find that edge effects dominate the overall stray magnetic field in patterned devices and that a conventional synthetic antiferromagnet structure is only partially able to compensate the field at the free layer position. A granular reference layer is seen to provide near-field flux closure while additional patterning defects add significant complexity to the stray field in nanoscale devices. Finally we find that the stray field from a nanoscale antiferromagnet is surprisingly non-zero arising from the imperfect cancellation of magnetic sublattices due to edge defects. Our findings provide an outline of the role of different layer structures and defects in the effective stray magnetic field in nanoscale magnetic random access memory devices and atomistic calculations provide a useful tools to study the stray field effects arising from a wide range of defects