Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Aggregation of liposomes induced by calcium: A structural and kinetic study

In this work, the calcium-induced aggregation of phosphatidylserine liposomes is probed by means of the analysis of the kinetics of such process as well as the aggregate morphology. This novel characterization of liposome aggregation involves the use of static and dynamic light-scattering techniques to obtain kinetic exponents and fractal dimensions. For salt concentrations larger than 5 mM, a diffusion-limited aggregation regime is observed and the Brownian kernel properly describes the time evolution of the diffusion coefficient. For slow kinetics, a slightly modified multiple contact kernel is required. In any case, a time evolution model based on the numerical resolution of Smoluchowski's equation is proposed in order to establish a theoretical description for the aggregating system. Such a model provides an alternative procedure to determine the dimerization constant, which might supply valuable information about interaction mechanisms between phospholipid vesicles.

Structural development accounting

We construct and estimate a unified model combining three of the main sources ofcross-country income disparities: differences in factor endowments, barriers to technologyadoption and the inappropriateness of frontier technologies to local conditions. The keycomponents are different types of workers, distortions to capital accumulation, directedtechnical change, costly adoption and spillovers from the world technology frontier. Despiteits parsimonious parametrization, our empirical model provides a good fit of GDP data forup to 86 countries in 1970 and 122 countries in 2000. Removing barriers to technologyadoption would increase the output per worker of the average non-OECD country relativeto the US from 0.19 to 0.61, while increasing skill premia in all countries. Removing barriersto trade in goods amplifies income disparities, induces skill-biased technology adoptionand increases skill premia in the majority of countries. These results are reverted if tradeliberalization is coupled with international IPR protection.

Role of structural saturation and geometry in the luminescence of silicon-based nanostructured materials

The structural saturation and stability, the energy gap, and the density of states of a series of small, silicon-based clusters have been studied by means of the PM3 and some ab initio (HF/6-31G* and 6-311++G**, CIS/6-31G* and MP2/6-31G*) calculations. It is shown that in order to maintain a stable nanometric and tetrahedral silicon crystallite and remove the gap states, the saturation atom or species such as H, F, Cl, OH, O, or N is necessary, and that both the cluster size and the surface species affect the energetic distribution of the density of states. This research suggests that the visible luminescence in the silicon-based nanostructured material essentially arises from the nanometric and crystalline silicon domains but is affected and protected by the surface species, and we have thus linked most of the proposed mechanisms of luminescence for the porous silicon, e.g., the quantum confinement effect due to the cluster size and the effect of Si-based surface complexes.

Gorilla genome structural variation reveals evolutionary parallelisms with chimpanzee

Structural variation has played an important role in the evolutionary restructuring of human and great ape genomes. Recent analyses have suggested that the genomes of chimpanzee and human have been particularly enriched for this form of genetic variation. Here, we set out to assess the extent of structural variation in the gorilla lineage by generating 10-fold genomic sequence coverage from a western lowland gorilla and integrating these data into a physical and cytogenetic framework of structural variation. We discovered and validated over 7665 structural changes within the gorilla lineage, including sequence resolution of inversions, deletions, duplications, and mobile element insertions. A comparison with human and other ape genomes shows that the gorilla genome has been subjected to the highest rate of segmental duplication. We show that both the gorilla and chimpanzee genomes have experienced independent yet convergent patterns of structural mutation that have not occurred in humans, including the formation of subtelomeric heterochromatic caps, the hyperexpansion of segmental duplications, and bursts of retroviral integrations. Our analysis suggests that the chimpanzee and gorilla genomes are structurally more derived than either orangutan or human genomes.

Agricultural productivity and structural transformation. Evidence from Brazil

We study the effects of the adoption of new agricultural technologies on structural transformation. To guide empirical work, we present a simple model where the effect of agriculturalproductivity on industrial development depends on the factor bias of technical change. We testthe predictions of the model by studying the introduction of genetically engineered soybeanseeds in Brazil, which had heterogeneous effects on agricultural productivity across areas withdifferent soil and weather characteristics. We find that technical change in soy production wasstrongly labor saving and lead to industrial growth, as predicted by the model.

Decision making techniques with similarity measures and OWA operators

We analyse the use of the ordered weighted average (OWA) in decision-making giving special attention to business and economic decision-making problems. We present several aggregation techniques that are very useful for decision-making such as the Hamming distance, the adequacy coefficient and the index of maximum and minimum level. We suggest a new approach by using immediate weights, that is, by using the weighted average and the OWA operator in the same formulation. We further generalize them by using generalized and quasi-arithmetic means. We also analyse the applicability of the OWA operator in business and economics and we see that we can use it instead of the weighted average. We end the paper with an application in a business multi-person decision-making problem regarding production management

Silicon quantum dots embedded in a SiO2 matrix: From structural study to carrier transport properties

We study the details of electronic transport related to the atomistic structure of silicon quantum dots embedded in a silicon dioxide matrix using ab initio calculations of the density of states. Several structural and composition features of quantum dots (QDs), such as diameter and amorphization level, are studied and correlated with transport under transfer Hamiltonian formalism. The current is strongly dependent on the QD density of states and on the conduction gap, both dependent on the dot diameter. In particular, as size increases, the available states inside the QD increase, while the QD band gap decreases due to relaxation of quantum confinement. Both effects contribute to increasing the current with the dot size. Besides, valence band offset between the band edges of the QD and the silica, and conduction band offset in a minor grade, increases with the QD diameter up to the theoretical value corresponding to planar heterostructures, thus decreasing the tunneling transmission probability and hence the total current. We discuss the influence of these parameters on electron and hole transport, evidencing a correlation between the electron (hole) barrier value and the electron (hole) current, and obtaining a general enhancement of the electron (hole) transport for larger (smaller) QD. Finally, we show that crystalline and amorphous structures exhibit enhanced probability of hole and electron current, respectively.

Ferromagnetic shape memory alloys: structural and thermal properties

The most extensively studied Heusler alloys are those based on the Ni-Mn-Ga system. However, to overcome the high cost of Gallium and the usually low martensitic transformation temperature, the search for Ga-free alloys has been recently attempted, particularly, by introducing In, Sn or Sb. In this work, two alloys (Mn50Ni35.5In14.5 and Ni50Mn35In15) have been obtained by melt spinning. We outline their structural and thermal behaviour. Mn50Ni35.5In14.5 alloy has the transformation above room temperature whereas Ni50Mn35In15 does not have this transformation in the temperature range here analyzed

Thermally-Induced Structural Transformations on Polymorphous Silicon

Polymorphous Si is a nanostructured form of hydrogenated amorphous Si that contains a small fraction of Si nanocrystals or clusters. Its thermally induced transformations such as relaxation, dehydrogenation, and crystallization have been studied by calorimetry and evolved gas analysis as a complementary technique. The observed behavior has been compared to that of conventional hydrogenated amorphous Si and amorphous Si nanoparticles. In the temperature range of our experiments (650700 C), crystallization takes place at almost the same temperature in polymorphous and in amorphous Si. In contrast, dehydrogenation processes reflect the presence of different hydrogen states. The calorimetry and evolved gas analysis thermograms clearly show that polymorphous Si shares hydrogen states of both amorphous Si and Si nanoparticles. Finally, the total energy of the main SiH group present in polymorphous Si has been quantified

Decision making techniques with similarity measures and OWA operators

We analyse the use of the ordered weighted average (OWA) in decision-making giving special attention to business and economic decision-making problems. We present several aggregation techniques that are very useful for decision-making such as the Hamming distance, the adequacy coefficient and the index of maximum and minimum level. We suggest a new approach by using immediate weights, that is, by using the weighted average and the OWA operator in the same formulation. We further generalize them by using generalized and quasi-arithmetic means. We also analyse the applicability of the OWA operator in business and economics and we see that we can use it instead of the weighted average. We end the paper with an application in a business multi-person decision-making problem regarding production management

Demand-based structural change and balanced economic growth

[eng] We analyze the equilibrium of a multi-sector exogenous growth model where the introduction of minimum consumption requirements drives structural change. We show that equilibrium dynamics simultaneously exhibt structural change and balanced growth of aggregate variables as is observed in US when the initial intensity of minimum consumption requirements is sufficiently small. This intensity is measured by the ratio between the aggregate value of the minimum consumption requirements and GDP and, therefore, it is inversely related with the level of economic development. Initially rich economies benefit from an initially low intensity of the minimum consumption requirements and, as a consequence, these economies end up exhibiting balanced growth of aggregate variables, while there is structural change. In contrast, initially poor economies suffer from an initially large intensity of the minimum consumption requirements, which makes the growth of the aggregate variables unbalanced during a very large period. These economies may never exhibit simultaneously balanced growth of aggregate variables and structural change.

Microwave spectrometry for the Evaluation of the structural integrity of metallic stents

Purpose: To assess the feasibility of a method based on microwave spectrometry to detect structural distortions of metallic stents in open air conditions and envisage the prospects of this approach toward possible medical applicability for the evaluation of implanted stents. Methods: Microwave absorbance spectra between 2.0 and 18.0 GHz were acquired in open air for the characterization of a set of commercial stents using a specifically design setup. Rotating each sample over 360º, 2D absorbance diagrams were generated as a function of frequency and rotation angle. To check our approach for detecting changes in stent length (fracture) and diameter (recoil), two specific tests were performed in open air. Finally, with a few adjustments, this same system provides 2D absorbance diagrams of stents immersed in a water-based phantom, this time over a bandwidth ranging from 0.2 to 1.8 GHz. Results: The authors show that metallic stents exhibit characteristic resonant frequencies in their microwave absorbance spectra in open air which depend on their length and, as a result, may reflect the occurrence of structural distortions. These resonances can be understood considering that such devices behave like dipole antennas in terms of microwave scattering. From fracture tests, the authors infer that microwave spectrometry provides signs of presence of Type I to Type IV stent fractures and allows in particular a quantitative evaluation of Type III and Type IV fractures. Recoil tests show that microwave spectrometry seems able to provide some quantitative assessment of diametrical shrinkage, but only if it involves longitudinal shortening. Finally, the authors observe that the resonant frequencies of stents placed inside the phantom shift down with respect to the corresponding open air frequencies, as it should be expected considering the increase of dielectric permittivity from air to water. Conclusions: The evaluation of stent resonant frequencies provided by microwave spectrometry allows detection and some quantitative assessment of stent fracture and recoil in open air conditions. Resonances of stents immersed in water can be also detected and their characteristic frequencies are in good agreement with theoretical estimates. Although these are promising results, further verifica tion in a more relevant phantom is required in order to foresee the real potential of this approach.

Structural Insight into the Mode of Action of a Direct Inhibitor of Coregulator Binding to the Thyroid Hormone Receptor.

The development of nuclear hormone receptor antagonists that directly inhibit the association of the receptor with its essential coactivators would allow useful manipulation of nuclear hormone receptor signaling. We previously identified 3-(dibutylamino)-1-(4-hexylphenyl)-propan-1-one (DHPPA), an aromatic β-amino ketone that inhibits coactivator recruitment to thyroid hormone receptor β (TRβ), in a high-throughput screen. Initial evidence suggested that the aromatic β-enone 1-(4-hexylphenyl)-prop-2-en-1-one (HPPE), which alkylates a specific cysteine residue on the TRβ surface, is liberated from DHPPA. Nevertheless, aspects of the mechanism and specificity of action of DHPPA remained unclear. Here, we report an x-ray structure of TRβ with the inhibitor HPPE at 2.3-Å resolution. Unreacted HPPE is located at the interface that normally mediates binding between TRβ and its coactivator. Several lines of evidence, including experiments with TRβ mutants and mass spectroscopic analysis, showed that HPPE specifically alkylates cysteine residue 298 of TRβ, which is located near the activation function-2 pocket. We propose that this covalent adduct formation proceeds through a two-step mechanism: 1) β-elimination to form HPPE; and 2) a covalent bond slowly forms between HPPE and TRβ. DHPPA represents a novel class of potent TRβ antagonist, and its crystal structure suggests new ways to design antagonists that target the assembly of nuclear hormone receptor gene-regulatory complexes and block transcription.