Spectroscopic signatures of crystal momentum fractionalization

We consider gapped Z2 spin liquids, where spinon quasiparticles may carry fractional quantum numbers of space group symmetry. In particular, spinons can carry fractional crystal momentum. We show that such quantum number fractionalization has dramatic, spectroscopically accessible consequences, namely enhanced periodicity of the two-spinon density of states in the Brillouin zone, which can be detected via inelastic neutron scattering. This effect is a sharp signature of certain topologically ordered spin liquids and other symmetry enriched topological phases. Considering square lattice space group and time reversal symmetry, we show that exactly four distinct types of spectral periodicity are possible.Comment: 6 pages; v2: added reference; v3: improved introduction, typos corrected; v4: added referenc

Experiments in representing design knowledge for arid lands design

Thesis (M. Arch.)--Massachusetts Institute of Technology, Dept. of Architecture, 1987.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.Includes bibliographical references (leaves 54-55).This thesis proposes, through a multi-layered exploration, the development of a system of computer tools for architects. The research consists of a series of "design sessions" in the context of a desert design problem. The goal is to create a knowledge-based system using a commercially available expert shell, which provides the designer with an automated interface to visual references. Data can be seen as a collection of things, while knowledge can be similarly seen as a collection of relationships between things. An expert shell is literally a program that is "empty" of knowledge, and into which a designer puts know ledge: a knowledge-base is the result. The shell itself acts as a means of manipulating that knowledge-base by an inference process that is activated by rules, or hypotheses and tests. The experimental framework of the thesis is devised to evaluate both type of inference processes in relation to their capabilities for representing design knowledge. The design problem serves to outline a methodology for understanding the process of design, but it also is the means by which a design grammar and syntax appropriate to the automated system are formally described. The intent is not to compile a vast domain of knowledge on all issues of arid lands design, but to focus on a specific architectural response to the climate: the relationship between the primary structural system and the secondary closure system. The design of a window system is the vehicle for documenting observations of the way visual references are used. From this process a descriptive system and body of "expert" rules are developed to define the function of the automated environment. The larger goal is to then relate the syntactical environment to a general image referencing system so that the expert system can act as a personal design consultant. The image referencing system is a distinct and important component of the automated environment, and as such a detailed specification of its nature and operation is intended to show the interdependence of the knowledge-base and a visual database.by Andrew M. Bennett.M.Arch

SBMLToolbox: an SBML toolbox for MATLAB users

We present SBMLToolbox, a toolbox that facilitates importing and exporting models represented in the Systems Biology Markup Language (SBML) in and out of the MATLAB environment and provides functionality that enables an experienced user of either SBML or MATLAB to combine the computing power of MATLAB with the portability and exchangeability of an SBML model. SBMLToolbox supports all levels and versions of SBML

Polarization-dependence of palladium deposition on ferroelectric lithium niobate (0001) surfaces

We investigate the effect of ferroelectric polarization direction on the geometric properties of Pd deposited on the positive and negative surfaces of LiNbO$_3$ (0001). We predict preferred geometries and diffusion properties of small Pd clusters using density functional theory, and use these calculations as the basis for kinetic Monte Carlo simulations of Pd deposition on a larger scale. Our results show that on the positive surface, Pd atoms favor a clustered configuration, while on the negative surface, Pd atoms are adsorbed in a more dispersed pattern due to suppression of diffusion and agglomeration. This suggests that the effect of LiNbO$_3$ polarization direction on the catalytic activity of Pd [J. Phys. Chem. \textbf{88}, 1148 (1984)] is due, at least in part, to differences in adsorption geometry. Further investigations using these methods can aid the search for catalysts whose activities switch reversibly with the polarization of their ferroelectric substrates

Hedging Break-Even Biodiesel Production Costs Using Soybean Oil Futures

The effectiveness of hedging volatile input prices for biodiesel producers is examined over one- to eight-week time horizons. Results reveal that hedging break-even soybean costs with soybean oil futures offers significant reductions in input price risk. The degree of risk reduction is dependent upon type of hedge, naïve or risk-minimizing, and upon time horizon. In contrast, cross-hedging break-even poultry fat costs with soybean oil futures failed to reduce input price risk.biodiesel, hedging, poultry fat, soybean oil, Agribusiness, Demand and Price Analysis, Environmental Economics and Policy,

Imaging schizophrenia: data fusion approaches to characterize and classify

Schizophrenia is a complex, chronic and disabling mental disorder that affects about one percent of the adult population. The etiology of schizophrenia remains elusive and to date there are no image based tools to diagnose it. Advancements in magnetic resonance imaging (MRI) have enabled researchers to develop less invasive and in vivo techniques, such as structural MRI (sMRI), functional MRI (fMRI) and diffusion tensor imaging (DTI), to construct theories about the neural underpinnings of schizophrenia. With sMRI, fMRI and DTI the distribution of tissues, the functional activity and the brain network are imaged respectively. Subjects with schizophrenia (SZ) and healthy controls (HC) are scanned with different modalities to identify differences, but the analysis of each modality has traditionally been carried out separately. Data fusion of multimodal data and an analysis of the joint information may hold the key to reveal hidden traces of this subtle disorder. In this work we develop techniques to correlate sMRI with fMRI, fMRI with other fMRI and DTI with symptom scores. The brain is a highly interconnected organ and local morphology can influence functional activity at distant regions. Through our methods it is possible to perform a cross correlation analysis between modalities incorporating all brain voxels. By reducing the large cross correlation matrix to useful statistics new aspects of schizophrenia are revealed. The methods introduced are simple, easy to implement and efficient. In another effort we modify canonical correlation analysis (CCA) to fuse two sets of brain data to locate brain regions with significant correlations. The new differential features identified through our fusion methods are used to classify subjects. The sMRI–fMRI fusion indicates that the linkage between gray matter and functional activity probed by a sensorimotor task is weaker in SZ than in HC. Linkages between functional activity and structural regions in the cerebellum and the prefrontal cortex are found to be aberrant in SZ. The pair wise fusion of four different fMRI tasks shows that SZ activate to different tasks less uniquely than do HC. The above results support the ‘disconnection hypothesis’ of schizophrenia and the ‘theory of cognitive dysmetria’. DTI–symptom score fusion indicates that regions in the superior longitudinal fasciculus have high DTI–symptom correlations. Our preliminary classification efforts show high success rates in the leave–one–out scheme. The results presented in this work reveal several novel and interesting findings to better understand schizophrenia. The methods introduced are general, and can be easily applied to healthy and other pathological brain data to explore brain behavior