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Syntheses, crystal structures, magnetic properties and vibrational spectra of nitridoborate-halide compounds Sr-2[BN2]Br and Eu-2[BN2]X (X = Br, I) with isolated [BN2](3-) units
No full textThe title compounds Sr-2[BN2]Br (1), Eu-2[BN2]Br (2) and Eu-2[BN2]I (3) were obtained from reactions of mixtures of Sr-3[BN2](2) and SrBr2 (1) and the binaries EuN, h-BN and EuX2 (X = Br, I) (2, 3), respectively. The crystal structure of Sr-2[BN2]Br was solved from X-ray powder diffraction data and those of the europium compounds from X-ray single crystal data. Sr-2[BN2]Br and Eu-2[BN2]Br are isotypic crystallizing in the rhombohedral space group R (3) over barm (No. 166, Pearson code: hR18; Z = 3; a = 4.11692(2) angstrom, c = 26.4611(2) angstrom (1); a = 4.0728(3) angstrom, c = 26.589(3) angstrom (2)). The crystal structures are built up by layers of condensed edge-sharing [B-N-B]@Eu-6 and [Br]@Eu-6 trigonal antiprisms, which are alternately stacked along [001] Eu-2[BN2]I - isotypic to Sr-2[BN2]I - crystallizes in the monoclinic space group P2(1)/m (No. 11, Pearson code: mP24; Z = 4; a = 10.2548(6) angstrom, b = 4.1587(3) angstrom, c = 13.1234(9) angstrom, beta = 91.215(4)degrees). The crystal structure is characterized by slightly puckered layers formed by condensed edge-sharing I@Eu-6 octahedra which are separated by isolated [BN2](3-) units. The bond lengths for the strictly linear [BN2](3-) anions in (1) and (2) are d(B-N) = 1.351(4) angstrom and 1.356(8) angstrom, respectively. In Eu-2[BN2]I two crystallograhically distinct [BN2](3-) anions are present with d(B1-N) = 1.32(4) angstrom, 1.37(4)angstrom and d(B2-N) = 1.30(4) angstrom, 1.34(4) angstrom, respectively. Their bond angles vary slightly: angle(N-B1-N) = 179(3)degrees and angle(N-B2-N) = 177(3)degrees. The magnetic susceptibility data of the europium compounds (2) and (3) indicate that the Eu ions are divalent with 4f(7) configuration. Vibrational spectra were measured and interpreted based on the D infinity(h) symmetry of the discrete linear [N-B-N](3-) moieties, considering the site symmetry reduction and the presence of two distinct [BN2](3-) groups in (3)
Molecular dynamics with Langevin equation using local harmonics and Chandrasekhar's convolution
No full textA numerical method for studying molecular systems subject to a random force field leading to a Gaussian velocity distribution and described by the Langevin equation is presented. Two basic elements constitute the formulation: local harmonic modes and Chandrasekhar's formula for the distribution function for a convolution involving a random function. First, by linearizing the governing Langevin equations locally and employing an orthogonal change of coordinates, an explicit solution for the displacement and velocity is constructed. Second, Chandrasekhar's formula is employed in deriving the probability distribution function of the displacements and the velocities coming from the random forces. The local mode analysis is essential for the use of the Chandrasekhar's formula, since we need the formal solution as a convolution of the random forces and the local Green's function. For an illustration of the method in a significant case representative of real problems, we study a one dimensional idealization of a long chain molecule possessing internal energy barriers and subjected to an applied tension. The results are compared with the predictions of a conventional approximate method where a finite number of random realizations are generated in each time step. This truncation constitutes an approximation to obtain the desired Gaussian probability distribution function for the velocities which is reached in the limit of an infinity of random realizations. The calculations show that the conventional approximations may be acceptable only for short times, small temperatures, and average values over very long times. In particular, these approximations fail to give accurate results for transient phenomena, show slow convergence with the increase in the number of random realizations, and predict large values for the variance even in the steady regime. The new proposed method on the other hand, (i) incorporates the mathematically and conceptually correct limit for the distribution function, (ii) is quite stable with respect to increases in the value of the time increment as well as in terms of fluctuations characterized by the variance, (iii) leads to considerable savings in computer time over the approximate method, and (iv) has the proper description during the transient regime, which is usually the most interesting phase of dynamical processes
Density-based 3D shape descriptors
No full textWe propose a novel probabilistic framework for the extraction of density-based 3D shape descriptors using kernel density estimation. Our descriptors are derived from the probability density functions (pdf) of local surface features characterizing the 3D object geometry. Assuming that the shape of the 3D object is represented as a mesh consisting of triangles with arbitrary size and shape, we provide efficient means to approximate the moments of geometric features on a triangle basis. Our framework produces a number of 3D shape descriptors that prove to be quite discriminative in retrieval applications. We test our descriptors and compare them with several other histogram-based methods on two 3D model databases, Princeton Shape Benchmark and Sculpteur, which are fundamentally different in semantic content and mesh quality. Experimental results show that our methodology not only improves the performance of existing descriptors, but also provides a rigorous framework to advance and to test new ones
Speed accuracy trade-off under response deadlines
No full textPerceptual decision making has been successfully modeled as a process of evidence accumulation up to a threshold. In order to maximize the rewards earned for correct responses in tasks with response deadlines, participants should collapse decision thresholds dynamically during each trial so that a decision is reached before the deadline. This strategy ensures on-time responding, though at the cost of reduced accuracy, since slower decisions are based on lower thresholds and less net evidence later in a trial (compared to a constant threshold). Frazier and Yu (2008) showed that the normative rate of threshold reduction depends on deadline delays and on participants' uncertainty about these delays. Participants should start collapsing decision thresholds earlier when making decisions under shorter deadlines (for a given level of timing uncertainty) or when timing uncertainty is higher (for a given deadline). We tested these predictions using human participants in a random dot motion discrimination task. Each participant was tested in free-response, short deadline (800 ms), and long deadline conditions (1000 ms). Contrary to optimal-performance predictions, the resulting empirical function relating accuracy to response time (RT) in deadline conditions did not decline to chance level near the deadline; nor did the slight decline we typically observed relate to measures of endogenous timing uncertainty. Further, although this function did decline slightly with increasing RT, the decline was explainable by the best-fitting parameterization of Ratcliff's diffusion model (Ratcliff, 1978), whose parameters are constant within trials. Our findings suggest that at the very least, typical decision durations are too short for participants to adapt decision parameters within trials
Examining the importance of the teachers' emotional support for students' social inclusion using the one-with-many design
No full textThe importance of high quality teacher-student relationships for students' well-being has been long documented. Nonetheless, most studies focus either on teachers' perceptions of provided support or on students' perceptions of support. The degree to which teachers and students agree is often neither measured nor taken into account. In the current study, we will therefore use a dyadic analysis strategy called the one-with-many design. This design takes into account the nestedness of the data and looks at the importance of reciprocity when examining the influence of teacher support for students' academic and social functioning. Two samples of teachers and their students from Grade 4 (age 9-10 years) have been recruited in primary schools, located in Turkey and Romania. By using the one-with-many design we can first measure to what degree teachers' perceptions of support are in line with students' experiences. Second, this level of consensus is taken into account when examining the influence of teacher support for students' social well-being and academic functioning
Rock faces, opium and wine: speculations on the original viewing context of persianate manuscripts
No full textOne of the most delightful and interesting features of Islamic miniature painting in the Persian-speaking world is the appearance of hidden faces and figures in the background of compositions, which usually consist of rocky outcrops, tree roots or boulders. Scholars have provided different reasons for this feature, from narrative enhancement to the artists' creativity and imagination. Although accepting these reasons as valid, this paper proposes an additional raison d'etre - that is, the original viewing context of the majlis where wine and opium consumption were part of the entertainment, as both textual and visual evidence demonstrates. Based on first-hand accounts of users of psychoactive substances as well as psychological studies on their effect on creativity and visual perception, I argue that opium and wine consumption caused a perceptional shift that rendered the hidden figures even more entertaining than they would have been in a sober state of mind
Lubricated friction and volume dilatancy are coupled
No full textDilation (expansion of film thickness) by similar to0.1 A, which is less than one-tenth of the width of confined fluid molecules, was observed when confined films crossed from the resting state ("static friction") to sliding ("kinetic friction"). These measurements were based on using piezoelectric bimorph sensors possessing extremely high resolution for detecting position changes, during the course of sliding molecularly thin films of squalane, a model lubricant fluid, between atomically smooth single crystals of mica. Detailed inspection of energy balance shows that the dilation data and the friction forces satisfied energy conservation of identifiable energies at the slip point, from static to kinetic friction. This shows experimentally, for the first time to the best of our knowledge, a direct coupling between friction forces and decrease in the mean density of the intervening molecularly thin fluid
Geolocation of terrestrial gamma-ray flash source lightning
No full textTerrestrial gamma-ray flashes (TGFs) are impulsive (similar to 1 ms) but intense sources of gamma-rays associated with lightning activity and typically detected via low orbiting spacecrafts. We present the first catalog of precise (< 30 km error) TGF source locations, determined via ground-based detection of ELF/VLF radio atmospherics (or sferics) from lightning discharges, which enables precise geolocation of lightning locations. We present the distribution of source-tonadir distances, established due to effects of Compton scattering on the escaping photons. We find that TGFs occur in coincidence with the lightning discharge, but with a few ms variance, and that a detectable sferic at long distances is nearly always present. The properties of TGF-associated sferics and their connection to multiple-peak TGFs are highly variable and inconsistent, and are classified into two categories
Enhancing local linear models using functional connectivity for brain state decoding
No full textThe authors propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resonance imaging (fMRI). In the proposed learning machine, local meshes are formed around each voxel. The distance between voxels in the mesh is determined by using functional neighborhood concept. In order to define functional neighborhood, the similarities between the time series recorded for voxels are measured and functional connectivity matrices are constructed. Then, the local mesh for each voxel is formed by including the functionally closest neighboring voxels in the mesh. The relationship between the voxels within a mesh is estimated by using a linear regression model. These relationship vectors, called Functional Connectivity aware Mesh Arc Descriptors (FC-MAD) are then used to train a statistical learning machine. The proposed method was tested on a recognition memory experiment, including data pertaining to encoding and retrieval of words belonging to ten different semantic categories. Two popular classifiers, namely k-Nearest Neighbor and Support Vector Machine, are trained in order to predict the semantic category of the item being retrieved, based on activation patterns during encoding. The classification performance of the Functional Mesh Learning model, which range in 62-68% is superior to the classical multi-voxel pattern analysis (MVPA) methods, which range in 40-48%, for ten semantic categories
Optical position feedback and phase control of resonant 1D and 2D MOEMS-scanners
No full textResonantly driven oscillating MOEMS mirrors have many applications in the fields of optics, telecommunication and spectroscopy. Assuring stable resonant oscillation with well controlled amplitude under varying environmental conditions is a complex task, which can impede or retard incorporation of such MOEMS mirrors in large systems. For this we have developed compact modules comprising optical position sensing and driver electronics with closed loop control, which can ensure stable resonant operation of 1D and 2D micro-mirrors. In this contribution we present in much detail the position encoding and feedback scheme, and show very first experimental results with the novel 2D device