How to cluster in parallel with neural networks

Partitioning a set of N patterns in a d-dimensional metric space into K clusters - in a way that those in a given cluster are more similar to each other than the rest - is a problem of interest in astrophysics, image analysis and other fields. As there are approximately K(N)/K (factorial) possible ways of partitioning the patterns among K clusters, finding the best solution is beyond exhaustive search when N is large. Researchers show that this problem can be formulated as an optimization problem for which very good, but not necessarily optimal solutions can be found by using a neural network. To do this the network must start from many randomly selected initial states. The network is simulated on the MPP (a 128 x 128 SIMD array machine), where researchers use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also by starting the network from many initial states at once, thus obtaining many solutions in one run. Researchers obtain speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of speedups comensurate with human perceptual abilities

Supplemental irrigation management of rainfed grapevines under drought conditions using the CropSyst model

Aim of study: To determine how much water should be used and when it should be applied in rain-fed grapevine using a cropping system simulation model (CropSyst), and also the economic analysis of supplemental irrigation for rainfed grapevine.Area of study: This study was conducted at the School of Agriculture, Shiraz University, Shiraz, Iran, in 2012, 2013 and 2014.Material and methods: The CropSyst model was calibrated to predict the rainfed yields of ‘Askari’ and ‘Yaghooti’ grapevines in different climates using four amounts of SI: 250 L (I1), 500 L (I2), 1000 L (I3) and 0 (I4), five SI times: single in March (T1), single in April (T2), single in March + single in April (T3), single in May (T4) and single in June (T5).Main results: Treatment T3 increased the average simulated yield of ‘Askari’ by 15% to 40% at regions with P/ETo>0.6, 17% to 61% at 0.2<P/ETO<0.6, and 26% to 61% at P/ETO<0.2, while in ‘Yaghooti’ it increased about 2% to 41% at regions with P/ETo>0.6, 4% to 36% at 0.2<P/ETO<0.6 and 2% to 26% at P/ETO<0.2. By increasing the water price by 30% and 50%, net benefits for the ‘Askari’ decreased by about 31% and 54%, while 6% and 18%, for ‘Yaghooti’ respectively.Research highlights: The CropSyst model can successfully predict soil water content and grapevine yields. Application of SI in May increased significantly the grapevine yield as compared to other SI times

Mutual diffusion in concentrated liquid solutions: A new model based on cluster theory

In dilute solutions, diffusion is dominated by motion of single molecules. Conversely, in non-ideal concentrated solutions, mass transfer by diffusion can be heavily influenced by molecular clustering. Cluster theory in concentrated solutions can be approached using the Cussler model, which has been used to explain experimental mutual diffusion data in highly concentrated solutions. In this work, using the Cussler model and the critical point theory as a starting point, a new model for predictions of mutual diffusion coefficients in binary mixtures over the whole composition range was developed. The model is based on modifications of the concentration correlation function and explains well the experimental mutual diffusion data and their dependence on composition and activity coefficients. The model does not require any knowledge of intra-diffusion coefficients and can be used to predict mutual diffusion coefficients over the whole composition range

Mutual diffusion in concentrated liquid solutions: A new model based on cluster theory

In dilute solutions, diffusion is dominated by motion of single molecules. Conversely, in non-ideal concentrated solutions, mass transfer by diffusion can be heavily influenced by molecular clustering. Cluster theory in concentrated solutions can be approached using the Cussler model, which has been used to explain experimental mutual diffusion data in highly concentrated solutions. In this work, using the Cussler model and the critical point theory as a starting point, a new model for predictions of mutual diffusion coefficients in binary mixtures over the whole composition range was developed. The model is based on modifications of the concentration correlation function and explains well the experimental mutual diffusion data and their dependence on composition and activity coefficients. The model does not require any knowledge of intra-diffusion coefficients and can be used to predict mutual diffusion coefficients over the whole composition range

Multiple-Point and Multiple-Time Correlations Functions in a Hard-Sphere Fluid

A recent mode coupling theory of higher-order correlation functions is tested on a simple hard-sphere fluid system at intermediate densities. Multi-point and multi-time correlation functions of the densities of conserved variables are calculated in the hydrodynamic limit and compared to results obtained from event-based molecular dynamics simulations. It is demonstrated that the mode coupling theory results are in excellent agreement with the simulation results provided that dissipative couplings are included in the vertices appearing in the theory. In contrast, simplified mode coupling theories in which the densities obey Gaussian statistics neglect important contributions to both the multi-point and multi-time correlation functions on all time scales.Comment: Second one in a sequence of two (in the first, the formalism was developed). 12 pages REVTeX. 5 figures (eps). Submitted to Phys.Rev.

Targeting Cellular Metabolism With CPI-613 Sensitizes Pancreatic Cancer Cells to Radiation Therapy

PURPOSE: Local tumor progression is a cause of significant morbidity and mortality in patients with pancreatic ductal adenocarcinoma (PDAC) with surgically unresectable disease. Novel and effective approaches to accomplish durable local control are urgently needed. We tested whether CPI-613 (devimistat), a first-in-class investigational small molecule inhibitor of mitochondrial metabolism, was capable of altering cancer cell energy metabolism and sensitizing PDAC cells to radiation therapy (RT). METHODS AND MATERIALS: The effect of a combined treatment of RT with CPI-613 on the viability of, clonogenic potential of, and cell death induction in PDAC cells (MiaPaCa-2 and Panc-1) was determined using a trypan blue dye exclusion assay, a colony formation assay, and a 7-amino-actinomycin D assay, respectively. The synergistic effects of CPI-613-RT and chemotherapeutic agents (gemcitabine or 5-fluorouracil) were measured in MiaPaCa-2 cells using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and spheroid formation assay. Changes in energy metabolism were determined by profiling metabolites treated with either RT, CPI-613, or both using liquid chromatography-mass spectrometry. RESULTS: This study demonstrates that a combination of single-fraction RT (2 and 10 Gy) with CPI-613 significantly inhibits PDAC cell growth compared with RT alone. Molecular analysis revealed inhibition of α-ketoglutarate dehydrogenase at the protein level. In addition, we demonstrate enhanced cell death of PDAC cells when treated with RT-CPI-613 combination. Targeted metabolomic analysis on PDAC cells post-CPI-613-RT treatment revealed alterations in key mitochondrial metabolites, with broader target engagement by the combination treatment, indicating the sensitization of CPI-613-treated PDAC cells to RT. Furthermore, a combination treatment of CPI-613 with either gemcitabine or 5-fluorouracil in the presence of 2 Gy RT synergistically inhibits PDAC cell proliferation. CONCLUSIONS: Our results support a novel combination of CPI-613-RT that warrants further preclinical and early-phase clinical investigations. A phase 1 trial designed to identify the maximum tolerated dose of CPI-613 in combination with chemo-RT in patients with PDAC was recently initiated (NCT05325281)

Generalized Boltzmann Equation for Lattice Gas Automata

In this paper, for the first time a theory is formulated that predicts velocity and spatial correlations between occupation numbers that occur in lattice gas automata violating semi-detailed balance. Starting from a coupled BBGKY hierarchy for the $n$-particle distribution functions, cluster expansion techniques are used to derive approximate kinetic equations. In zeroth approximation the standard nonlinear Boltzmann equation is obtained; the next approximation yields the ring kinetic equation, similar to that for hard sphere systems, describing the time evolution of pair correlations. As a quantitative test we calculate equal time correlation functions in equilibrium for two models that violate semi-detailed balance. One is a model of interacting random walkers on a line, the other one is a two-dimensional fluid type model on a triangular lattice. The numerical predictions agree very well with computer simulations.Comment: 31 pages LaTeX, 12 uuencoded tar-compressed Encapsulated PostScript figures (`psfig' macro), hardcopies available on request, 78kb + 52k

Mode-coupling theory for multiple-time correlation functions of tagged particle densities and dynamical filters designed for glassy systems

The theoretical framework for higher-order correlation functions involving multiple times and multiple points in a classical, many-body system developed by Van Zon and Schofield [Phys. Rev. E 65, 011106 (2002)] is extended here to include tagged particle densities. Such densities have found an intriguing application as proposed measures of dynamical heterogeneities in structural glasses. The theoretical formalism is based upon projection operator techniques which are used to isolate the slow time evolution of dynamical variables by expanding the slowly-evolving component of arbitrary variables in an infinite basis composed of the products of slow variables of the system. The resulting formally exact mode-coupling expressions for multiple-point and multiple-time correlation functions are made tractable by applying the so-called N-ordering method. This theory is used to derive for moderate densities the leading mode coupling expressions for indicators of relaxation type and domain relaxation, which use dynamical filters that lead to multiple-time correlations of a tagged particle density. The mode coupling expressions for higher order correlation functions are also succesfully tested against simulations of a hard sphere fluid at relatively low density.Comment: 15 pages, 2 figure

A phase I study of CPI-613 (devimistat) in combination with chemoradiation in patients with pancreatic adenocarcinoma

Background: Local tumor progression is a cause of significant mortality and morbidity in patients with unresectable pancreatic ductal adenocarcinoma (PDAC). Effective approaches to achieve durable local control are urgently needed. Metabolic reprogramming and enhanced mitochondrial function, both hallmarks of PDAC, are known contributors to chemo- and radio-resistance. CPI-613, a lipoic acid analog that selectively inhibits components of the Krebs cycle in tumors, showed promising preclinical synergy in combination with gemcitabine and radiation therapy (gem-RT). Methods: We describe a single-arm, single-center, open-label, phase I study designed to determine the maximumtolerated dose of CPI-613 when used concomitantly with gemcitabine and intensity modulated radiation therapy (IMRT) for local control of PDAC. CPI-613 will be administered once weekly by intravenous infusion over approximately 2 hours at a starting dose of 500 mg/m2 and dose-escalated/de-escalated using a Bayesian optimal interval design. Gemcitabine will be given once weekly at 400 mg/m2 dosage and IMRT as 54 Gray (Gy) in 30 fractions (1.8 Gy per fraction) with five fractions given per week. Up to 24 patients will be enrolled for the study after meeting the following main eligibility criteria, which include: pathologically confirmed PDAC; inoperable disease that by institutional pancreatic multidisciplinary tumor board or multidisciplinary review are considered to benefit from definitive local control of the primary tumor; ECOG of 0-2; and adequate organ and marrow function after completion of intended systemic chemotherapy. The secondary objectives are to determine the recommended phase II dose of CPI-613 when used with gem-RT, safety and tolerability of CPI-613-gem-RT, overall survival, local progression-free survival (PFS), overall PFS, patient-reported quality of life after treatment, and late gastrointestinal toxicities following treatment with CPI-613-gem-RT