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Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing number of large AI models that address use cases such as forecasting, downscaling, or nowcasting. While the parallel developments in the AI literature focus on foundation models -- models that can be effectively tuned to address multiple, different use cases -- the developments on the weather and climate side largely focus on single-use cases with particular emphasis on mid-range forecasting. We close this gap by introducing Prithvi WxC, a 2.3 billion parameter foundation model developed using 160 variables from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Prithvi WxC employs an encoder-decoder-based architecture, incorporating concepts from various recent transformer models to effectively capture both regional and global dependencies in the input data. The model has been designed to accommodate large token counts to model weather phenomena in different topologies at fine resolutions. Furthermore, it is trained with a mixed objective that combines the paradigms of masked reconstruction with forecasting. We test the model on a set of challenging downstream tasks namely: Autoregressive rollout forecasting, Downscaling, Gravity wave flux parameterization, and Extreme events estimation. The pretrained model with 2.3 billion parameters, along with the associated fine-tuning workflows, has been publicly released as an open-source contribution via Hugging Face.

Fusion frames are a convenient tool in applications where we deal with a large amount of data or when a combination of local data is needed. Oblique dual fusion frames are suitable in situations where the analysis for the data and its subsequent synthesis have to be implemented in different subspaces of a Hilbert space. These procedures of analysis and synthesis are in general not exact, and also there are circumstances where the exact dual is not available or it is necessary to improve its properties. To resolve these questions we introduce the concept of approximate oblique dual fusion frame, and in particular of approximate oblique dual fusion frame system. We study their properties. We give the relation to approximate oblique dual frames. We provide methods for obtaining them. We show how to construct other duals from a given one that give reconstructions errors as small as we want., Comment: arXiv admin note: text overlap with arXiv:1612.05493

In this work, we investigate the system formed by the equations $\text{div } \vec w=g_0$ and $\text{curl } \vec w=\vec g$ in bounded star-shaped domains of $\mathbb{R}^3$. A Helmholtz-type decomposition theorem is established based on a general solution of the above-mentioned div-curl system which was previously derived in the literature. When $g_0\equiv 0$, we readily obtain a bounded right inverse of $\text{curl}$ which is a divergence-free invariant. The restriction of this operator to the subspace of divergence-free vector fields with vanishing normal trace is the well-known Biot--Savart operator. In turn, this right inverse of $\text{curl}$ will be modified to guarantee its compactness and satisfy suitable boundary-value problems. Applications to Beltrami fields, Vekua-type problems as well as Maxwell's equations in inhomogeneous media are included.

The boll weevil (Anthonomus grandis L.) is a serious pest that primarily feeds on cotton plants. In places like Lower Rio Grande Valley of Texas, due to sub-tropical climatic conditions, cotton plants can grow year-round and therefore the left-over seeds from the previous season during harvest can continue to grow in the middle of rotation crops like corn (Zea mays L.) and sorghum (Sorghum bicolor L.). These feral or volunteer cotton (VC) plants when reach the pinhead squaring phase (5-6 leaf stage) can act as hosts for the boll weevil pest. The Texas Boll Weevil Eradication Program (TBWEP) employs people to locate and eliminate VC plants growing by the side of roads or fields with rotation crops but the ones growing in the middle of fields remain undetected. In this paper, we demonstrate the application of computer vision (CV) algorithm based on You Only Look Once version 5 (YOLOv5) for detecting VC plants growing in the middle of corn fields at three different growth stages (V3, V6, and VT) using unmanned aircraft systems (UAS) remote sensing imagery. All the four variants of YOLOv5 (s, m, l, and x) were used and their performances were compared based on classification accuracy, mean average precision (mAP), and F1-score. It was found that YOLOv5s could detect VC plants with a maximum classification accuracy of 98% and mAP of 96.3 % at the V6 stage of corn while YOLOv5s and YOLOv5m resulted in the lowest classification accuracy of 85% and YOLOv5m and YOLOv5l had the least mAP of 86.5% at the VT stage on images of size 416 x 416 pixels. The developed CV algorithm has the potential to effectively detect and locate VC plants growing in the middle of corn fields as well as expedite the management aspects of TBWEP., Comment: Preprint Under Review

To control boll weevil (Anthonomus grandis L.) pest re-infestation in cotton fields, the current practices of volunteer cotton (VC) (Gossypium hirsutum L.) plant detection in fields of rotation crops like corn (Zea mays L.) and sorghum (Sorghum bicolor L.) involve manual field scouting at the edges of fields. This leads to many VC plants growing in the middle of fields remain undetected that continue to grow side by side along with corn and sorghum. When they reach pinhead squaring stage (5-6 leaves), they can serve as hosts for the boll weevil pests. Therefore, it is required to detect, locate and then precisely spot-spray them with chemicals. In this paper, we present the application of YOLOv5m on radiometrically and gamma-corrected low resolution (1.2 Megapixel) multispectral imagery for detecting and locating VC plants growing in the middle of tasseling (VT) growth stage of cornfield. Our results show that VC plants can be detected with a mean average precision (mAP) of 79% and classification accuracy of 78% on images of size 1207 x 923 pixels at an average inference speed of nearly 47 frames per second (FPS) on NVIDIA Tesla P100 GPU-16GB and 0.4 FPS on NVIDIA Jetson TX2 GPU. We also demonstrate the application of a customized unmanned aircraft systems (UAS) for spot-spray applications based on the developed computer vision (CV) algorithm and how it can be used for near real-time detection and mitigation of VC plants growing in corn fields for efficient management of the boll weevil pests., Comment: 39 pages

The cotton boll weevil, Anthonomus grandis Boheman is a serious pest to the U.S. cotton industry that has cost more than 16 billion USD in damages since it entered the United States from Mexico in the late 1800s. This pest has been nearly eradicated; however, southern part of Texas still faces this issue and is always prone to the pest reinfestation each year due to its sub-tropical climate where cotton plants can grow year-round. Volunteer cotton (VC) plants growing in the fields of inter-seasonal crops, like corn, can serve as hosts to these pests once they reach pin-head square stage (5-6 leaf stage) and therefore need to be detected, located, and destroyed or sprayed . In this paper, we present a study to detect VC plants in a corn field using YOLOv3 on three band aerial images collected by unmanned aircraft system (UAS). The two-fold objectives of this paper were : (i) to determine whether YOLOv3 can be used for VC detection in a corn field using RGB (red, green, and blue) aerial images collected by UAS and (ii) to investigate the behavior of YOLOv3 on images at three different scales (320 x 320, S1; 416 x 416, S2; and 512 x 512, S3 pixels) based on average precision (AP), mean average precision (mAP) and F1-score at 95% confidence level. No significant differences existed for mAP among the three scales, while a significant difference was found for AP between S1 and S3 (p = 0.04) and S2 and S3 (p = 0.02). A significant difference was also found for F1-score between S2 and S3 (p = 0.02). The lack of significant differences of mAP at all the three scales indicated that the trained YOLOv3 model can be used on a computer vision-based remotely piloted aerial application system (RPAAS) for VC detection and spray application in near real-time., Comment: 38 Pages

A goal of unsupervised machine learning is to build representations of complex high-dimensional data, with simple relations to their properties. Such disentangled representations make easier to interpret the significant latent factors of variation in the data, as well as to generate new data with desirable features. Methods for disentangling representations often rely on an adversarial scheme, in which representations are tuned to avoid discriminators from being able to reconstruct information about the data properties (labels). Unfortunately adversarial training is generally difficult to implement in practice. Here we propose a simple, effective way of disentangling representations without any need to train adversarial discriminators, and apply our approach to Restricted Boltzmann Machines (RBM), one of the simplest representation-based generative models. Our approach relies on the introduction of adequate constraints on the weights during training, which allows us to concentrate information about labels on a small subset of latent variables. The effectiveness of the approach is illustrated with four examples: the CelebA dataset of facial images, the two-dimensional Ising model, the MNIST dataset of handwritten digits, and the taxonomy of protein families. In addition, we show how our framework allows for analytically computing the cost, in terms of log-likelihood of the data, associated to the disentanglement of their representations., Comment: Minor corrections. Accepted for publication in Physical Review X

Stress corrosion cracking (SCC) is a form of failure in metals that is present mostly in systems where humidity contact and mechanical load play a key role. Therefore, prediction of the combined effect is desired. There are models based on path dissolution and film rupture, Hydrogen-embrittlement, based on empirical observations, and the unified approach which recognizes not the maximum applied stress intensity factor (SIF) but the SIF range as the fatigue driving force. So, in the later one, the contribution of corrosion to crack growth is recognized by adding a corrosion SIF.

Measurements of the time of arrival of shock waves from explosions can serve as powerful markers of the evolution of the shock front for determining crucial parameters driving the blast. Using standard theoretical tools and a simple ansatz for solving the hydrodynamics equations, a general expression for the Mach number of the shock front is derived. Dimensionless coordinates are introduced allowing a straightforward visualization and direct comparison of blast waves produced by a variety of explosions, including chemical, nuclear, and laser-induced plasmas. The results are validated by determining the yield of a wide range of explosions, using data from gram-size charges to thermonuclear tests., Comment: 9 pages, 7 figures, 1 table, 23 explosions

We propose a new scheme to infer the metabolic fluxes of cell cultures in a chemostat. Our approach is based on the Maximum Entropy Principle and exploits the understanding of the chemostat dynamics and its connection with the actual metabolism of cells. We show that, in continuous cultures with limiting nutrients, the inference can be done with {\it limited information about the culture}: the dilution rate of the chemostat, the concentration in the feed media of the limiting nutrient and the cell concentration at steady state. Also, we remark that our technique provides information, not only about the mean values of the fluxes in the culture, but also its heterogeneity. We first present these results studying a computational model of a chemostat. Having control of this model we can test precisely the quality of the inference, and also unveil the mechanisms behind the success of our approach. Then, we apply our method to E. coli experimental data from the literature and show that it outperforms alternative formulations that rest on a Flux Balance Analysis framework., Comment: 35 pages, 11 figues

One of the consequences of climate change is anobserved increase in the frequency of extreme cli-mate events. That poses a challenge for weatherforecast and generation algorithms, which learnfrom historical data but should embed an often un-certain bias to create correct scenarios. This paperinvestigates how mapping climate data to a knowndistribution using variational autoencoders mighthelp explore such biases and control the synthesisof weather fields towards more extreme climatescenarios. We experimented using a monsoon-affected precipitation dataset from southwest In-dia, which should give a roughly stable pattern ofrainy days and ease our investigation. We reportcompelling results showing that mapping complexweather data to a known distribution implementsan efficient control for weather field synthesis to-wards more (or less) extreme scenarios., Comment: ICML Climate Change AI Workshop

In representations using frames, oblique duality appears in situations where the analysis and the synthesis has to be done in different subspaces. In some cases, we cannot obtain an explicit expression for the oblique duals and in others there exists only one oblique dual frame which has not the properties we need. Also, in practice the computations are not exact. To give a solution to these problems, in this work we introduce and investigate the notion of approximate oblique dual frames first in the setting of separable Hilbert spaces. We present several properties and provide different characterizations of approximate oblique dual frames. We focus then on approximate oblique dual frames in shift-invariant subspaces of L^2(R)and g ive different conditions on the generators that assure their existence. The importance of approximate oblique dual frames from a numerical and computational point of view is illustrated with an example of frame sequences generated by B-splines, where the previous results are used to construct approximate oblique dual frames which have better attributes than the exact ones. We provide an expression for the approximation error and study its behaviour.

Images of an explosion can be used to study some of its physical properties. After reviewing the key aspects of the method originally developed to study the first nuclear detonation and analyzing the Trinity blast data, the method is applied to the Beirut explosion of August 2020 by using images from videos posted online. The applicability of the method is discussed and the process of selection, extraction, and analysis of the data is presented. The estimate for the energy yield of the Beirut explosion is found to be $2.3^{+1.1}_{-1.1}$ TJ or $0.6^{+0.3}_{-0.3}$ kt of TNT equivalent. The result is consistent with others recently appeared in the literature using different methods. Notice that this article includes content that some readers may find distressing., Comment: Minor edits to match published version. 8 pages, 6 figures, 1 table

We cast the metabolism of interacting cells within a statistical mechanics framework considering both, the actual phenotypic capacities of each cell and its interaction with its neighbors. Reaction fluxes will be the components of high-dimensional spin vectors, whose values will be constrained by the stochiometry and the energy requirements of the metabolism. Within this picture, finding the phenotypic states of the population turns out to be equivalent to searching for the equilibrium states of a disordered spin model. We provide a general solution of this problem for arbitrary metabolic networks and interactions. We apply this solution to a simplified model of metabolism and to a complex metabolic network, the central core of the \emph{E. coli}, and demonstrate that the combination of selective pressure and interactions define a complex phenotypic space. Cells may specialize in producing or consuming metabolites complementing each other at the population level and this is described by an equilibrium phase space with multiple minima, like in a spin-glass model., Comment: 4 Figures

Continuous cultures of mammalian cells are complex systems displaying hallmark phenomena of nonlinear dynamics, such as multi-stability, hysteresis, as well as sharp transitions between different metabolic states. In this context mathematical models may suggest control strategies to steer the system towards desired states. Although even clonal populations are known to exhibit cell-to-cell variability, most of the currently studied models assume that the population is homogeneous. To overcome this limitation, we use the maximum entropy principle to model the phenotypic distribution of cells in a chemostat as a function of the dilution rate. We consider the coupling between cell metabolism and extracellular variables describing the state of the bioreactor and take into account the impact of toxic byproduct accumulation on cell viability. We present a formal solution for the stationary state of the chemostat and show how to apply it in two examples. First, a simplified model of cell metabolism where the exact solution is tractable, and then a genome-scale metabolic network of the Chinese hamster ovary (CHO) cell line. Along the way we discuss several consequences of heterogeneity, such as: qualitative changes in the dynamical landscape of the system, increasing concentrations of byproducts that vanish in the homogeneous case, and larger population sizes.

A fundamental question in biology is how cell populations evolve into different subtypes based on homogeneous processes at the single cell level. Here we show that population bimodality can emerge even when biological processes are homogenous at the cell level and the environment is kept constant. Our model is based on the stochastic partitioning of a cell component with an optimal copy number. We show that the existence of unimodal or bimodal distributions depends on the variance of partition errors and the growth rate tolerance around the optimal copy number. In particular, our theory provides a consistent explanation for the maintenance of aneuploid states in a population. The proposed model can also be relevant for other cell components such as mitochondria and plasmids, whose abundances affect the growth rate and are subject to stochastic partition at cell division.

Additive, multiplicative, and odd ratio neutral models for interactions are for long advocated and controversial in epidemiology. We show here that these commonly advocated models are biased, leading to spurious interactions, and missing true interactions., Comment: 7 pages, 3 figures

We derive a general statistical model of interactions, starting from probabilistic principles and elementary requirements. Prevailing interaction models in biomedical researches diverge both mathematically and practically. In particular, genetic interaction inquiries are formulated without an obvious mathematical unity. Our model reveals theoretical properties unnoticed so far, particularly valuable for genetic interaction mapping, where mechanistic details are mostly unknown, distribution of gene variants differ between populations, and genetic susceptibilities are spuriously propagated by linkage disequilibrium. When applied to data of the largest interaction mapping experiment on Saccharomyces Cerevisiae to date, our results imply less aversion to positive interactions, detection of well-documented hubs and partial remapping of functional regions of the currently known genetic interaction landscape. Assessment of divergent annotations across functional categories further suggests that positive interactions have a more important role on ribosome biogenesis than previously realized. The unity of arguments elaborated here enables the analysis of dissimilar interaction models and experimental data with a common framework., Comment: 19 pages, 4 figures in the main text and 7 other figures

We present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. More importantly, we derive a number of consequences from the model that are independent of parameter values. First, that the ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties invariant across perfusion systems. This conclusion is robust even in the presence of multi-stability, which is explained in our model by the negative feedback loop on cell growth due to toxic byproduct accumulation. Moreover, a complex landscape of steady states in continuous cell culture emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. Thus, in order to actually reflect the expected behavior in perfusion, performance benchmarks of cell-lines and culture media should be carried out in a chemostat.

We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient reservoir (the blood), aimed at characterizing the role of the microenvironment for aberrant growth. Accounting for cellular metabolic activity, competition for nutrients, spatial diffusion and their feedbacks on aberrant replication and death rates, we obtain a phase portrait where distinct asymptotic whole-tissue states are found upon varying the tissue-blood turnover rate and the level of blood-borne primary nutrient. Over a broad range of parameters, the spreading dynamics is bistable as random fluctuations can impact the final state of the tissue. Such a behaviour turns out to be linked to the re-cycling of overflow products by non-aberrant cells. Quantitative insight on the overall emerging picture is provided by a spatially homogeneous version of the model., Comment: 14 pages

Neutrino experiments can be considered sensitive tools to test Lorentz and CPT invariance. Taking advantage of the great variety of neutrino experiments, including neutrino oscillations, weak decays, and astrophysical neutrinos, the generic experimental signatures of the breakdown of these fundamental symmetries in the neutrino sector are presented., Comment: 6 pages; accepted for publication in Symmetry

Searches for violations of Lorentz invariance using cosmic rays, gamma rays, and astrophysical neutrinos and the prospects for future tests using cosmic-ray showers are presented., Comment: Presented at the Seventh Meeting on CPT and Lorentz Symmetry, Bloomington, Indiana, June 20-24, 2016

Violations of CPT invariance can induce neutrino-to-antineutrino transitions. We study this effect for solar neutrinos and use the upper bound on the solar neutrino-to-antineutrino transition probability from the KamLAND experiment to constrain CPT-symmetry-violating coefficients of the general Standard-Model Extension. The long propagation distance from the Sun to the Earth allows us to improve existing limits by factors ranging from about a thousand to $10^{11}$., Comment: 7 pages, 1 table; published version

In multiple scientific and technological applications we face the problem of having low dimensional data to be justified by a linear model defined in a high dimensional parameter space. The difference in dimensionality makes the problem ill-defined: the model is consistent with the data for many values of its parameters. The objective is to find the probability distribution of parameter values consistent with the data, a problem that can be cast as the exploration of a high dimensional convex polytope. In this work we introduce a novel algorithm to solve this problem efficiently. It provides results that are statistically indistinguishable from currently used numerical techniques while its running time scales linearly with the system size. We show that the algorithm performs robustly in many abstract and practical applications. As working examples we simulate the effects of restricting reaction fluxes on the space of feasible phenotypes of a {\em genome} scale E. Coli metabolic network and infer the traffic flow between origin and destination nodes in a real communication network., Comment: 25 pages, 11 figures

Maximum entropy method is a constructive criterion for setting up a probability distribution maximally non-committal to missing information on the basis of partial knowledge, usually stated as constrains on expectation values of some functions. In connection with experiments sample average of those functions are used as surrogate of the expectation values. We address sampling bias in maximum entropy approaches with finite data sets without forcedly equating expectation values to corresponding experimental average values. Though we rise the approach in a general formulation, the equations are unfortunately complicated. We bring simple case examples, hopping clear but sufficient illustration of the concepts.

The experimental signatures of nonstandard neutrino interactions are shown to be equivalent to CPT violation in neutrino oscillations. This result leads to a correspondence in the study of these two descriptions that can be used to constrain the relevant parameters of one formalism by using the available bounds on parameters of the other. The correspondence is illustrated and explicitly used to determine first bounds on previously unexplored parameters in both formalisms., Comment: 8 pages

Low-energy experiments studying single beta decay can serve as sensitive probes of Lorentz invariance that can complement interferometric searches for deviations from this spacetime symmetry. Experimental signatures of a dimension-three operator for Lorentz violation that are unobservable in neutrino oscillations are described for the decay the polarized and unpolarized neutrons as well as for measurements of the spectral endpoint in beta decay., Comment: 7 pages

Neutrinos can be used to search for deviations from exact Lorentz invariance. The worldwide experimental program in neutrino physics makes these particles a remarkable tool to search for a variety of signals that could reveal minute relativity violations. This paper reviews the generic experimental signatures of the breakdown of Lorentz symmetry in the neutrino sector., Comment: 10 pages, 4 figures; Review article published in the special issue "Through Neutrino Eyes: The Search for New Physics" of Advances in High Energy Physics

Deviations from Lorentz and CPT invariance in the neutrino sector and their observable effects in double beta decay are studied. For two-neutrino double beta decay, a spectral distortion and its properties are characterized for different isotopes. Majorana couplings for Lorentz violation are studied and shown to trigger neutrinoless double beta decay even for negligible Majorana mass. Existing data are used to obtain first limits of $5 \times 10^{-9}$ for 18 individual coefficients and attainable sensitivities in current and future experiments are presented., Comment: 7 pages two-column REVTeX

The recent observation of high-energy astrophysical neutrinos can be used to constrain violations of Lorentz invariance emerging from a quantum theory of gravity. We perform threshold and Cherenkov analyses that improve existing bounds by factors ranging from about a million to 10^{20}., Comment: 5 pages two-column REVTeX

Searches for Lorentz and CPT violation using neutrino oscillations and the prospects for future tests using neutrino time-of-flight measurements and beta-decay experiments are presented., Comment: Presented at the Sixth Meeting on CPT and Lorentz Symmetry, Bloomington, Indiana, June 17-21, 2013

In some quantum theories of gravity, deviations from the laws of relativity could be comparatively large while escaping detection to date. In the neutrino sector, precision experiments with beta decay yield new and improved constraints on these countershaded relativity violations. Existing data are used to extract bounds of $3 \times 10^{-8}$ GeV on the magnitudes of two of the four possible coefficients, and estimates are provided of future attainable sensitivities in a variety of experiments., Comment: 5 pages two-column REVTeX, version published in Rapid Communications, Physical Review D

We establish a general mechanism for highly efficient quantum transport through finite, disordered 3D networks. It relies on the interplay of disorder with centro-symmetry and a dominant doublet spectral structure, and can be controlled by proper tuning of only coarse-grained quantities. Photosynthetic light harvesting complexes are discussed as potential biological incarnations of this design principle., Comment: 7 pages (incl. 2 pages of suppl. mat.), 3 figures

A general introduction to Lorentz and CPT violation is presented. The observable effects of the breakdown of such fundamental symmetries in neutrinos are outlined and different experimental searches of some of the key signals of Lorentz violation are discussed. A novel powerful method to study model-independent neutrino oscillations is reviewed and then used to illustrate a new global model of neutrino oscillations based on Lorentz violation consistent with atmospheric, accelerator, reactor, and solar neutrino data., Comment: 11 pages. Proceedings of DPF-2011, Providence, RI, August 2011

A class of calculable global models for neutrino oscillations based on Lorentz and CPT violation is presented. One simple example matches established neutrino data from accelerator, atmospheric, reactor, and solar experiments, using only two degrees of freedom instead of the usual five. A third degree of freedom appears in the model, and it naturally generates the MiniBooNE low-energy anomalies. More involved models in this class can also accommodate the LSND anomaly and neutrino-antineutrino differences of the MINOS type. The models predict some striking signals in various ongoing and future experiments., Comment: 17 pages two-column REVTeX

An important field of research in functional neuroimaging is the discovery of integrated, distributed brain systems and networks, whose different regions need to work in unison for normal functioning. The EEG is a non-invasive technique that can provide information for massive connectivity analyses. Cortical signals of time varying electric neuronal activity can be estimated from the EEG. Although such techniques have very high time resolution, two cortical signals even at distant locations will appear to be highly similar due to the low spatial resolution nature of the EEG. In this study a method for eliminating the effect of common sources due to low spatial resolution is presented. It is based on an efficient estimation of the whole-cortex partial coherence matrix. Using as a starting point any linear EEG tomography that satisfies the EEG forward equation, it is shown that the generalized partial coherences for the cortical grey matter current density time series are invariant to the selected tomography. It is empirically shown with simulation experiments that the generalized partial coherences have higher spatial resolution than the classical coherences. The results demonstrate that with as little as 19 electrodes, lag-connected brain regions can often be missed and misplaced even with lagged coherence measures, while the new method detects and localizes correctly the connected regions using the lagged partial coherences.

A three-parameter model of neutrino oscillations based on a simple Lorentz- and CPT-violating texture is presented. The model is consistent with established data and naturally generates low-energy and neutrino-antineutrino anomalies of the MiniBooNE type. A one-parameter extension incorporates the MINOS anomaly, while a simple texture enhancement accommodates the LSND signal., Comment: 5 pages, accepted for publication in Physics Letters B

Neutrino oscillations in the presence of Lorentz violation can present novel observable signals in both long- and short-baseline experiments. In this talk we describe the theory and its different regimes depending on properties of the experiments. CPT violation, its systematic search and possible connections to latest results are also presented., Comment: Presented at the Fifth Meeting on CPT and Lorentz Symmetry, Bloomington, Indiana, June 28-July 2, 2010

Precise tests of Lorentz invariance can be executed using neutrino oscillations, which can provide sensitive measurements of suppressed signals of new physics. This talk describes the neutrino sector of the Standard-Model Extension, which represents a general modification of the Standard Model of massive neutrinos to include Lorentz and CPT violation. Attainable sensitivities as well as a framework to search for these violations are presented for existing and future long-baseline neutrino experiments. The applicability of this framework to short-baseline experiments is also discussed., Comment: 6 pages. To be published in the proceedings of DPF-2009, Detroit, MI, July 2009, eConf C090726

The effects of perturbative Lorentz and CPT violation on neutrino oscillations are studied. Features include neutrino-antineutrino oscillations, direction dependence, and unconventional energy behavior. Leading-order corrections arising from renormalizable operators are derived in the general three-flavor effective field theory. The results are applied to neutrino-beam experiments with long baselines, which offer excellent sensitivity to the accompanying effects. Key signatures of Lorentz and CPT violation using neutrino beams include sidereal variations in the oscillation probabilities arising from the breakdown of rotational symmetry, and CPT asymmetries comparing neutrino and antineutrino modes. Attainable sensitivities to coefficients for Lorentz violation are estimated for several existing and future experiments., Comment: 21 pages two-column REVTeX

The AdS/CFT correspondence has been tested through the reproduction of standard results. Following this approach, we use the correspondence to obtain the Hawking temperature of a black hole in 1+1 dimensions. Using an auxiliary Liouville field, the holographic energy-momentum tensor is found and compared with a radiation energy-momentum tensor, verifying that the correspondence gives the correct temperature. The information about the radiated field in the CFT sector is contained in the central charge, whereas in the radiation tensor this information is in the statistical distribution. This result allows to determine the radiation of scalar and Dirac fields easily and without the necessity of solving the corresponding Klein-Gordon or Dirac equation in a curved spacetime. In both cases, the correct temperature was obtained., Comment: 4 pages

The results from a series of experiments are presented whose purpose is to explore different schemes which may lead to the formation of pure metal plasmas in a capillary discharge with parameters appropriate for X ray lasing. The experiments were performed in ceramic wall capillary discharges at currents of up to 120 kA, with an available ID of between 3 and 8 mm and with lengths from 60 to 100 mm. Initial plasma conditions in the capillary exploit transient hollow cathode effects in a preionizing discharge. A laser focussed onto the back surface of the cathode initiates both beam activity in the capillary volume and plasma injection. To promote metal ablation into the pinch channel of elements other than the ceramic wall material, a number of graded ring schemes have been tried. The plasma is observed axially using both time and energy resolved soft X-ray pin hole images as well as from time resolved soft X-ray spectra. By varying the rate of rise of the current of the main discharge, and the preionizing conditions the diameter and the stability of the Z-pinch column are seen to be affected. The ratio of the species from the ablated wall material to the plasma formed from the graded ring structure is found to depend both on the capillary dimensions as well as the other operating conditions., Comment: 3 pages, 3 figures. Presented at 15th International Conference on High-Power Particle Beams (BEAMS-2004), St. Petersburg, Russia, 18-23 Jul 2004

The results of an extensive operation of a Vacuum Spark plasma using Titanium electrodes in a 120 ns 150 kA discharge are presented. The hot spots are found to form with a regular spacing in a zippering Z-pinch plasma, which forms close to the cathode and extends to approximately two thirds of the anode separation over a period of a few ns. The axis of the discharge is well defined by an initial plasma from a Nd:YAG laser focussed onto the cathode electrode surface. The statistics of the formation of the hot spots are given for the life of one anode electrode. Between one and three hotspots form and the favored positions are at 1.5 and 3.0 mm from the cathode and the strongest emission, as observed in a filtered X-ray pinhole camera, comes from the hot spot closest to the cathode. The emission spectra resolved between 50 and 350 \AA shows a wide range of Ti ionization which allows the temperatures of the anode blow off plasma, the Z-pinch and the hot spot plasma to be distinguished. These results are compared with filtered PIN diode signals and filtered pinhole images., Comment: 5 pages, 4 figures

The TTL lies between the neutral buoyancy level (NBL) at ~350 K and the tropopause. Within the the TTL radiative heating drives ascent and air parcel supersaturation. Ticosonde measurements since 2005 show that the incidence ofsupersaturation in the TTL over Costa Rica is ~60%. This is due to diabatic ascent. The frequency is highest (68%) in summer, when convection is frequent. The TSL was defined by Selkirk et al. (2010) as the upper edge of the TTL. It isIn this layer that the final saturation of air parcels rising into the stratosphere occurs and thus the water vapor minima which define the so-called "writehead" of the Atmospheric Tape Recorder.

UNKNOWN

Observed sulfur dioxide (SO2)mixing ratios onboard unmanned aerial systems (UAS) duringMarch 11-13, 2013 are used to constrain the three-day averaged SO2 degassing flux fromTurrialba volcanowithin a Bayesian inverse modeling framework. A mesoscale model coupled with Lagrangian stochastic particle backward trajectories is used to quantify the source-receptor relationships at very high spatial resolutions (i.e., b1 km). The model shows better performance in reproducing the near-surface meteorological properties and observed SO2 variations when using a first-order closure non-local planetary boundary layer (PBL) scheme. The optimized SO2 degassing fluxes vary from 0.59 +/- 0.37 to 0.83 +/- 0.33 kt d−1 depending on the PBL scheme used. These fluxes are in good agreement with ground-based gas flux measurements, and correspond to corrective scale factors of 8-12 to the posteruptive SO2 degassing rate in the AeroCom emission inventory. The maximum a posteriori solution for the SO2 flux is highly sensitive to the specification of prior and observational errors, and relatively insensitive to the SO2 loss term and temporal averaging of observations. Our results indicate relatively low degassing activity but sustained sulfur emissions from Turrialba volcano to the troposphere during March 2013. This study demonstrates the utility of low-cost small UAS platforms for volcanic gas composition and flux analysis.

The summit of Volcan Turrialba (elev. 3340 m) lies less than 50 km upstream in the prevailing easterlies from the Ticosonde balloon launch site at San Jose, Costa Rica, where ECC ozone sondes have been launched regularly since 2005. In 2006 we began to see telltale notches in the ozone profiles in the altitude range between 2 and 6 km. Given the proximity of Turrialba, it seemed likely that SO2 in the volcano's plume was interfering in the chemical reaction in the ECC ozone sonde used to detect ozone. In early 2010, fumarolic activity in the Turrialba crater increased strongly, and the profile notches in our soundings increased in frequency as well, consistent with this hypothesis. In February 2012 we tested a dual ECC sonde system, where an additional sonde is flown on the same payload using a selective SO2 filter. The difference of the measurements in the dual sonde is a direct measure of the amount of SO2 encountered. This first dual sonde passed through the plume, and the data indicated a tropospheric SO2 column of 1.4 DU, comparing favorably with a total column of 1.7 DU in the OMI 3-km linear fit (LF) product at the sonde profile location and at nearly the same time. We are now launching dual sondes on a regular basis with 18 launches in the first 12 months through July 2014; 11 of these have detectable SO2 signals. These soundings have great potential for validation of the Aura OMI and the Suomi-NPP OMPS retrievals of SO2. Here we present the sonde measurements and compare them with two satellite datasets: the Aura OMI Linear Fit (LF) product and the Suomi-NPP OMPS Principal Components Analysis (PCA) boundary layer product. The PCA algorithm reduces retrieval noise and artifacts by more accurately accounting for various interferences in SO2 retrievals such as O3 absorption and rotational Raman scattering. The comparisons with the in situ observations indicate a significant improvement of the PCA algorithm in capturing relatively weak volcanic SO2 signals.

Balloon sonde measurements of tropical water vapor using the Cryogenic Frostpoint Hygrometer were initiated in Costa Rica in July 2005 and have continued to the present day. Over the nine years through July 2014, the Ticosonde program has launched 174 CFH payloads, representing the longest-running and most extensive single-site balloon dataset for tropical water vapor. In this presentation we present a seasonal climatology for water vapor and ozone at Costa Rica and examine the frequency of upper tropospheric supersaturation with comparisons to cloud fraction and cloud ice water content observations from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) on the CALIPSO mission. We then make a critical comparison of these data to water vapor measurements from the MLS instrument on board Aura in light of recently published work for other sites. Finally, we examine time series of 2-km altitude averages in the upper troposphere-lower stratosphere at Costa Rica in light of anomalies and trends seen in various large-scale indices of tropical water vapor.