Unusual Critical Behavior in a Bilinear‐Biquadratic Exchange Hamiltonian

We have performed a variety of numerical studies on the general bilinear‐biquadratic spin‐1 Hamiltonian H/J=∑ N i=1[S i ⋅S i+1 −β(S i ⋅S i+1)2], over the range 0≤β≤∞. The model is Bethe Ansatz integrable at the special point β=1, where the spectrum is gapless, but is otherwise believed to be nonintegrable. Affleck has predicted that an excitation gap opens up linearly in the vicinity of β=1. Our studies involving spectral excitations (dispersion spectra), scaled‐gap, and finite‐size scaling calculations are not consistent with the Affleck prediction. The situation appears complex, with novel crossover effects occurring in both regimes, ββ\u3e1, complicating the analysis

A fuzzy controlled three-phase centrifuge for waste separation

The three-phase centrifuge technology discussed in this paper was developed by Neal Miller, president of Centech, Inc. The three-phase centrifuge is an excellent device for cleaning up oil field and refinery wastes which are typically composed of hydrocarbons, water, and solids. The technology is unique. It turns the waste into salable oil, reusable water, and landfill-able solids. No secondary waste is produced. The problem is that only the inventor can set up and run the equipment well enough to provide an optimal cleanup. Demand for this device has far exceeded a one man operation. There is now a need for several centrifuges to be operated at different locations at the same time. This has produced a demand for an intelligent control system, one that could replace a highly skilled operator, or at least supplement the skills of a less experienced operator. The control problem is ideally suited to fuzzy logic, since the centrifuge is a highly complicated machine operated entirely by the skill and experience of the operator. A fuzzy control system was designed for and used with the centrifuge

A fuzzy control system for a three-phase oil field centrifuge

The three-phase centrifuge discussed here is an excellent device for cleaning up oil field and refinery wastes. These wastes are typically composed of hydrocarbons, water, and solids. This technology converts waste, which is often classified as hazardous, into salable oil, reusable water, and solids that can be placed in landfills. No secondary waste is produced. A major problem is that only one person can set up and run the equipment well enough to provide an optimal cleanup. Demand for this technology has far exceeded a one-man operation. The solution to this problem is an intelligent control system that can replace a highly skilled operator so that several centrifuges can be operated at different locations at the same time

Neural network for quality control of submunitions produced by injection loading

Injection loading of submunitions for smart weapons is a novel automated processing technique that can benefit from adaptive process control. This paper describes how the quality of submunitions could be controlled by using a neural network code in real time. Future work is planned to demonstrate fewer rejects and pollution reduction during submunition manufacturing

The spectral gap for some spin chains with discrete symmetry breaking

We prove that for any finite set of generalized valence bond solid (GVBS) states of a quantum spin chain there exists a translation invariant finite-range Hamiltonian for which this set is the set of ground states. This result implies that there are GVBS models with arbitrary broken discrete symmetries that are described as combinations of lattice translations, lattice reflections, and local unitary or anti-unitary transformations. We also show that all GVBS models that satisfy some natural conditions have a spectral gap. The existence of a spectral gap is obtained by applying a simple and quite general strategy for proving lower bounds on the spectral gap of the generator of a classical or quantum spin dynamics. This general scheme is interesting in its own right and therefore, although the basic idea is not new, we present it in a system-independent setting. The results are illustrated with an number of examples.Comment: 48 pages, Plain TeX, BN26/Oct/9

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Application of artificial intelligence control to the vapor-liquid-solid silicon carbide whisker process

Silicon carbide whiskers have excellent mechanical and chemical properties, making them very desirable as a reinforcement for structural ceramic and other composite materials. Los Alamos has developed a laboratory-scale batch process for producing very high quality SiC whiskers by the vapor-liquid-solid (VLS) method which is an active candidate for technology transfer involving significant scale-up. The process, however, involves quite complex chemical/physical and parametric relationships and has not as yet lent itself successfully to modeling. An expert computer system was therefore developed to facilitate the transfer of this technology to industry. Optimum conditions were determined by relating the many process parameters to product results to establish a set of rules for running the process. These are incorporated in a two-phase expert system designed to guide inexperienced users. In Phase 1, an expert consultant program provides the user with information that enables him to set up the run. This information is incorporated into the rule base that makes up Phase 2 --- the control system. At present, the operator functions as the controller by responding to the decisions of the expert system; automation can be added later. 13 refs., 16 figs

Heisenberg Antiferromagnetic Chains: Quantum-Classical Crossover

An unusual crossover mechanism has been discovered by numerical investigation of the dispersion spectrum of Heisenberg antiferromagnetic chains with various spin values in a magnetic field. This result is reflected in novel behavior of static properties such as the integrated intensity. A study of various excitation gaps using finite chain calculations extended by quantum Monte Carlo studies indicates unusual behaviour in the T=0 magnetization isotherms