Phase diagram of a two-dimensional lattice gas model of a ramp system

Using Monte Carlo Simulation and fundamental measure theory we study the phase diagram of a two-dimensional lattice gas model with a nearest neighbor hard core exclusion and a next-to-nearest neighbors finite repulsive interaction. The model presents two competing ranges of interaction and, in common with many experimental systems, exhibits a low density solid phase, which melts back to the fluid phase upon compression. The theoretical approach is found to provide a qualitatively correct picture of the phase diagram of our model system.Comment: 14 pages, 8 figures, uses RevTex

Evaluation of the Efficiency of Aqueous Extact of Neem Fruits on Insect Pest of Rice in Rice Agroecosystem of Maga in the Far North Region of Cameroon

The chemical fight against insects pest causes many problems on the biodiversity of ecosystems, destabilizes the trophic level of the ecosystem and has harmful effects on the on health human. Mean while the biological fight using plants extractions can equally play the same role of killing pest, reason why the present study which was carried out in the irrigated perimeters of Maga in the Far North region of Cameroon, have as principal objective to evaluate the aqueous extraction of neem fruit on the insects pest of rice. The specific objectives were to know the biological diversity of insect pest in the irrigated perimeters of Maga, and their repartitioning in the phenological stages, again, to see the effects of the aqueous extractions of the neem fruits on the insects pest per variety and in function of the phenological stages, also to evaluate the damages cause by insects pest during the talling stage in function of the varieties, finally, to evaluate loss cause by the insects pest. The study was made on two rice varieties which were IR46 and NERICA3 in a split plot disposition. The capturing of the insects was done with the help of a sweep net and the identification of the species was done with the help of an entomological buttle, the identification key of insects by Heinrich (1993), Hill (1983), Heinrichs and Barrion (2004) and the families recognition keys by Delvare and Aberlenc (1989).The method of Breniere permited the estimation of loss of output at the talling and harvesting stages of rice caused by the insect pest. The analysis of variance of the result was done using SPSS 20. In the class of insects, twenty two species of insects fall in twenty families divided in seven orders were collected. Among the captured insects, we investigated fourteen insects which were pest. The biological fight have shown an effectiveness in the nursery, talling, and a positive and non negligible effects on the reduction insects pest in the heading and maturation stages and thus has permitted the reduction of damages from insects on the rice plants

Variational Approach to Molecular Kinetics

The eigenvalues and eigenvectors of the molecular dynamics propagator (or transfer operator) contain the essential information about the molecular thermodynamics and kinetics. This includes the stationary distribution, the metastable states, and state-to-state transition rates. Here, we present a variational approach for computing these dominant eigenvalues and eigenvectors. This approach is analogous the variational approach used for computing stationary states in quantum mechanics. A corresponding method of linear variation is formulated. It is shown that the matrices needed for the linear variation method are correlation matrices that can be estimated from simple MD simulations for a given basis set. The method proposed here is thus to first define a basis set able to capture the relevant conformational transitions, then compute the respective correlation matrices, and then to compute their dominant eigenvalues and eigenvectors, thus obtaining the key ingredients of the slow kinetics

Status of the Stony Brook Superconducting Heavy-Ion Linac

The present status of the Stony Brook Superconducting Heavy-Ion Linear Accelerator is described, with emphasis on recent operational results with a prototype unit of the accelerator. The basic LINAC elements are independently-phased lead-plated copper split-loop resonators operating at 151.7 MHz and optimized for velocities of either ß=v/c= 0.055 or ß=0.10. Resonators are grouped in units of either 4 low-ß or 3 high-ß resonators in compact cryostat modules separated by room-temperature quadrupole-doublet lenses. The LINAC consisting of 4 low-ß and 7 high-ß modules injected with heavy ions of mass A≃16-100 from the Stony Brook EN tandem will produce an additional energy gain of ~18 MeV per unit charge with a total heat dissipation at 4.5K of <300 Watts. In recent tests with low-ß prototype units, individual resonators were operated continuously at accelerating gradients in excess of 3.5 MV/m, and were phase and amplitude stabilized at 3.0 MV/ m using 175 Watts of RF power. Helium-temperature dissipation at 3.0 MV/m is ~8 Watts after helium-gas conditioning. The prototype low-ß module was used to accelerate a 30 Mev ^(16)O^(5+) beam to ~35 MeV

Ab-initio quantum chemistry with neural-network wavefunctions

Machine learning and specifically deep-learning methods have outperformed human capabilities in many pattern recognition and data processing problems, in game playing, and now also play an increasingly important role in scientific discovery. A key application of machine learning in the molecular sciences is to learn potential energy surfaces or force fields from ab-initio solutions of the electronic Schr\"odinger equation using datasets obtained with density functional theory, coupled cluster, or other quantum chemistry methods. Here we review a recent and complementary approach: using machine learning to aid the direct solution of quantum chemistry problems from first principles. Specifically, we focus on quantum Monte Carlo (QMC) methods that use neural network ansatz functions in order to solve the electronic Schr\"odinger equation, both in first and second quantization, computing ground and excited states, and generalizing over multiple nuclear configurations. Compared to existing quantum chemistry methods, these new deep QMC methods have the potential to generate highly accurate solutions of the Schr\"odinger equation at relatively modest computational cost.Comment: review, 17 pages, 6 figure

A Rapid Murine Coma and Behavior Scale for Quantitative Assessment of Murine Cerebral Malaria

BACKGROUND: Cerebral malaria (CM) is a neurological syndrome that includes coma and seizures following malaria parasite infection. The pathophysiology is not fully understood and cannot be accounted for by infection alone: patients still succumb to CM, even if the underlying parasite infection has resolved. To that effect, there is no known adjuvant therapy for CM. Current murine CM (MCM) models do not allow for rapid clinical identification of affected animals following infection. An animal model that more closely mimics the clinical features of human CM would be helpful in elucidating potential mechanisms of disease pathogenesis and evaluating new adjuvant therapies. METHODOLOGY/PRINCIPAL FINDINGS: A quantitative, rapid murine coma and behavior scale (RMCBS) comprised of 10 parameters was developed to assess MCM manifested in C57BL/6 mice infected with Plasmodium berghei ANKA (PbA). Using this method a single mouse can be completely assessed within 3 minutes. The RMCBS enables the operator to follow the evolution of the clinical syndrome, validated here by correlations with intracerebral hemorrhages. It provides a tool by which subjects can be identified as symptomatic prior to the initiation of trial treatment. CONCLUSIONS/SIGNIFICANCE: Since the RMCBS enables an operator to rapidly follow the course of disease, label a subject as affected or not, and correlate the level of illness with neuropathologic injury, it can ultimately be used to guide the initiation of treatment after the onset of cerebral disease (thus emulating the situation in the field). The RMCBS is a tool by which an adjuvant therapy can be objectively assessed

A weak characterization of slow variables in stochastic dynamical systems

We present a novel characterization of slow variables for continuous Markov processes that provably preserve the slow timescales. These slow variables are known as reaction coordinates in molecular dynamical applications, where they play a key role in system analysis and coarse graining. The defining characteristics of these slow variables is that they parametrize a so-called transition manifold, a low-dimensional manifold in a certain density function space that emerges with progressive equilibration of the system's fast variables. The existence of said manifold was previously predicted for certain classes of metastable and slow-fast systems. However, in the original work, the existence of the manifold hinges on the pointwise convergence of the system's transition density functions towards it. We show in this work that a convergence in average with respect to the system's stationary measure is sufficient to yield reaction coordinates with the same key qualities. This allows one to accurately predict the timescale preservation in systems where the old theory is not applicable or would give overly pessimistic results. Moreover, the new characterization is still constructive, in that it allows for the algorithmic identification of a good slow variable. The improved characterization, the error prediction and the variable construction are demonstrated by a small metastable system

Prediction of the in situ coronal mass ejection rate for solar cycle 25: Implications for Parker Solar Probe in situ observations

The Parker Solar Probe (PSP) and Solar Orbiter missions are designed to make groundbreaking observations of the Sun and interplanetary space within this decade. We show that a particularly interesting in situ observation of an interplanetary coronal mass ejection (ICME) by PSP may arise during close solar flybys ($< 0.1$~AU). During these times, the same magnetic flux rope inside an ICME could be observed in situ by PSP twice, by impacting its frontal part as well as its leg. Investigating the odds of this situation, we forecast the ICME rate in solar cycle 25 based on 2 models for the sunspot number (SSN): (1) the forecast of an expert panel in 2019 (maximum SSN = 115), and (2) a prediction by McIntosh et al. (2020, maximum SSN = 232). We link the SSN to the observed ICME rates in solar cycles 23 and 24 with the Richardson and Cane list and our own ICME catalog, and calculate that between 1 and 7 ICMEs will be observed by PSP at heliocentric distances $< 0.1$ AU until 2025, including 1$\sigma$ uncertainties. We then model the potential flux rope signatures of such a double-crossing event with the semi-empirical 3DCORE flux rope model, showing a telltale elevation of the radial magnetic field component $B_R$, and a sign reversal in the component $B_N$ normal to the solar equator compared to field rotation in the first encounter. This holds considerable promise to determine the structure of CMEs close to their origin in the solar corona.Comment: 11 pages, 6 figures, accepted for publication in the Astrophysical Journal on 2020 September 1

No Far-Infrared-Spectroscopic Gap in Clean and Dirty High-TC_C Superconductors

We report far infrared transmission measurements on single crystal samples derived from Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8}$. The impurity scattering rate of the samples was varied by electron-beam irradiation, 50MeV $^{16}$O$^{+6}$ ion irradiation, heat treatment in vacuum, and Y doping. Although substantial changes in the infrared spectra were produced, in no case was a feature observed that could be associated with the superconducting energy gap. These results all but rule out ``clean limit'' explanations for the absence of the spectroscopic gap in this material, and provide evidence that the superconductivity in Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8}$ is gapless.Comment: 4 pages and 3 postscript figures attached. REVTEX v3.0. Accepted for publication in Phys. Rev. Lett. IRDIRT

Status of the Stony Brook Superconducting Heavy-Ion Linac

We describe the present status of the State University of New York at Stony Brook Superconducting Heavy-Ion LINAC (SUNYLAC). The LINAC will extend at very modest cost the capabilities of the existing FN tandem Van de Graaff into the energy range 5-10 MeV/A for light heavy-ions from oxygen to bromine. The active elements are 43 lead-plated copper superconducting resonators of the split-loop type optimized for either velocity ß=v/c=0.055 or ß=0.10. Phase and amplitude of each resonator is independently set through RF-feedback controllers interfaced to an overall computer control system. Full scale construction work began in July, 1979 following the in-beam demonstration of a prototype LINAC module containing 4 low-ß resonators, and the majority of the installation work on the beam transport and refrigeration systems was completed in the summer of 1980. The project is now well into its final assembly and testing phase, with the completion of assembly scheduled in early 1982. We describe details of the design of key elements of the LINAC and the initial operating experience with the injection beam path, helium refrigerator and first production accelerator module. The progress of a continuing program aimed at optimizing crucial aspects of the LINAC is also reviewed