Octupolar Ordering in the b>0 Bilinear-Biquadratic Heisenberg Pyrochlore

We investigate the bilinear-biquadratic Heisenberg model on the pyrochlore lattice. While negative biquadratic couplings result in a first-order transition into a nematic ordered state with spins aligned mutually collinearly, it is found that positive biquadratic interactions lead to spins orienting in mutually perpendicular directions, described as octupolar or tetrahedral ordering. This transition is probed using classical Monte Carlo and it is found that the system undergoes a first-order transition into a octupolar ordered state with no long-range order. Unfortunately, we find that single spin-flip Monte Carlo simulations freeze completely at the transition with exceptionally slow dynamics and an extreme lack of ergodicity. The application of parallel tempering does not improve simulation results, which, due to the poor ergodicity of the simulation, cannot be reweighted using histogram techniques. We also present and discuss a potential loop algorithm which may allow simulations to overcome local energy barriers and regain ergodicity. Upon warming Monte Carlo simulations initialized in potential octupolar long-range ordered states, we observe the dynamics of weathervane modes; zero energy rotational excitations in the lattice. Taking the form of 2D membranes in the lattice, these weathervane modes may rotate at no energy cost, allowing for the successful use of the single spin-flip Monte Carlo algorithm. We note that these weathervane modes exist at rotational angles of 0 and corresponding to alternating layers of spins, in agreement with previous work. Depending on the long-range ordered state that the simulation is initialized in, weathervane modes may be stabilized by the periodic boundary conditions or, if free to rotate at will, may enter a weathervane manifold state where fast dynamics permit the simulation to rapidly sample various weathervane ordered states

Effect of vibroacoustic therapy on pain management in adolescents with low back pain

Vibroacoustic Therapy (VT) is a very distinct form of treatment. The purpose of this study was to determine the effect of vibroacoustic therapy on low back pain management in adolescents. A total of 40 adolescents (13-18 years old) were randomly divided into two equal groups (exercise – control group, and exercise and vibroacoustic therapy – vibroacoustic group), and participated in a 3-week physiotherapy program for back pain management. The participants in both groups performed the same exercise program five times per week. The participants in the vibroacoustic group apart from exercise also received treatment on a special vibro chair set at 4-8 Hz frequency for relaxation. Music was heard through the headphones. Standard tests (Oswestry disability index and the visual analogue pain scale) to assess low back pain were used before and after the intervention to monitor changes. The intensity of low back pain significantly decreased in both groups after the intervention (P < 0.05), but there were no significant differences between the groups in low back pain management in adolescents

Advisory, Negotiation and Intelligent Decision Support System for Leadership Analysis

The development of the Leader Model for quantitative and qualitative analyses began with the goal of integrating managerial, organizational, technical, technological, economic, legal/regulatory, innovative, social, cultural, ethical, psychological, religious, ethnic and other aspects involved in the process of a leaders life cycle. The need to determine the most efficient life cycle of a leader led to the development of the Advisory, Negotiation and Intelligent DEcision support System for Leadership Analysis (ANDES). The objective of the authors of this work for integrating text analytics, advisory, negotiation and decision support systems is to improve the quality and efficiency of intelligent decision-making regarding a leaders life cycle. This ANDES consists of an intelligent database, database management system, model-base, model-base management system and user interface

Robust Flow Component Identification for Blockwise SVD Clutter Filtering in High-Frame-Rate Ultrasound Using a Deeply Connected Neural Network

Ultrasound plays a critical role in the accurate and reliable observation of blood flow dynamics within the human body and is instrumental in the assessment of cardiovascular health and subsequent follow-up treatment. However, flow imaging innovations in ultrasound are dependent on the ability to remove the unwanted portion of the signal corresponding to static or slow moving tissues (or clutter ) from the dynamic blood signal. If this filtering process cannot be done to a high degree of precision, any corresponding flow image will be of low quality, corrupted by non-flow signals. Filtering is typically performed on the basis of frequency, using a high-pass filter. This approach functions well when the velocity distributions of tissues and flow signals are distinct but fails entirely when the two spectra overlap. New types of filters in high-frame-rate ultrasound (HiFRUS) making use of both temporal and spatial information use the singular value decomposition (SVD) have been proposed. These filters function by decomposing the input signal into a series of orthonormal basis vectors or components. In theory, as tissue and flow signals posses different signal statistics, they should be decomposed into different components and readily identified. The identified flow components can then be reconstituted to produce a filtered flow signal. In practice, flow and clutter component identification is a challenging task considering the adaptive nature of the SVD. Furthermore, flow and clutter signals may be mixed in the same components to varying degrees, making identification of flow signals a challenging task. While increased flow sensitivity and clutter rejection has been demonstrated by SVD filters, they currently lack the robustness required for clinical applications, often failing to perform in scenarios that challenge their innate assumptions of the flow signal decomposition. The goal of this work is to develop a robust generalizable flow identification framework that produces high quality filtered flow images across challenging in-vivo flow scenarios where current SVD filters demonstrate inconsistency. A deeply-connected neural network (DNN) was trained on a variety of flow acquisitions to reproduce the area under the curve (AUC) value obtained after performing receiver operator characteristic (ROC) analysis on the segmented flow region using a variety of statistical quantities correlated to the presence of flow in each component of the decomposition. The use of the AUC metric and subsequent training of the DNN using multiple statistical factors represents the first attempt at using a supervised learning approach to identify the flow components of the decomposition using many statistical factors simultaneously. When the proposed model was applied to acquisitions of an in-vitro flow phantom, in-vivo brachial artery, and in-vivo femoral arteries, greater sensitivity and specificity (measured using contrast and AUC) were obtained when compared to literature SVD techniques. The proposed model was also sufficiently generalizable to identify small blood vessels in the in-vivo human kidney. The proposed methodology demonstrates an improvement on the performance and consistency of SVD filters, helping to put this powerful technique in the hands of more users. Furthermore, the supervised training methodology developed here, using ROC analysis to obtain an AUC value for each component that describes the spatial distribution of its signal power, has the potential to be extended to other clutter filtering algorithms potentially leading to better feature identification than current unsupervised techniques

Nontarget Effects of Herbicides on Soybean Fungi and Tissues

103 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1981.Alternaria sp., Colletotrichum dematium var. truncata, Macrophomina phaseolina and Phomopsis sp., isolated from soybean (Glycine max) seeds, differed in tolerance to paraquat as measured by mycelial production, linear mycelial growth, spore germination and glucose consumption. Mycelial discs oU of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Effect of herbicides on competitive saprophytic colonization by Macrophomina phaseolina of soybean stems

The effect of paraquat, glyphosate and sodium chlorate : sodium borate (50:50), applied at commercial rates was tested on the competitive saprophytic colonization by Macrophomina phaseolina of greenhouse and field grown soybean stems at three different growth stages in two soils. A significant difference in colonization was recorded between herbicide treatments and controls in soil with a high organic content but no significant difference in colonization was found between herbicides. The highest levels of stem colonization occurred 10 days after incubation in soil. Colonization in treated and untreated stems progressively declined at similar rates for all growth stages and in both soil types. In both soils, field stems had greater levels of colonization when sampling time and herbicide factors were excluded. The nonpersistence of M. phaseolina in stems in soil suggests that the saprophytic activity of the fungus does not effectively increase its inoculum density in soil