Computing Aviation Sparing Policies: Solving a Large Nonlinear Integer Program

Deployed US Navy aircraft carriers must stock a large number of spare parts to support the various types of aircraft embarked on the ship. The sparing policy determines the spares that will be stocked on the ship to keep the embarked aircraft ready to fly. Given a fleet of ten or more aircraft carriers and a cost of approximately 50 million dollars per carrier plus the cost of spares maintained in warehouses in the United States, the sparing problem constitutes a significant portion of the Navy’s resources. The objective of this work is to find a minimum-cost sparing policy that meets the readiness requirements of the embarked aircraft. This is a very large, nonlinear, integer optimization problem. The cost function is piecewise linear and convex while the constraint mapping is highly nonlinear. The distinguishing characteristics of this problem from an optimization viewpoint are that a large number of decision variables are required to be integer and that the nonlinear constraint functions are essentially “black box” functions; that is, they are very difficult (and expensive) to evaluate and their derivatives are not available. Moreover, they are not convex. Integer programming problems with a large number of variables are difficult to solve in general and most successful approaches to solving nonlinear integer problems have involved linear approximation and relaxation techniques that, because of the complexity of the constraint functions, are inappropriate for attacking this problem. We instead employ a pattern search method to each iteration of an interior point-type algorithm to solve the relaxed version of the problem. From the solution found by the pattern search on each interior point iteration, we begin another pattern search on the integer lattice to find a good integer solution. The best integer solution found across all interations is returned as the optimal solution. The pattern searches are distributed across a local area network of non-dedicated, heterogeneous computers in an office environment, thus, drastically reducing the time required to find the solution.     

Phase separation of p53 precedes aggregation and is affected by oncogenic mutations and ligands

Mutant p53 tends to form aggregates with amyloid properties, especially amyloid oligomers inside the nucleus, which are believed to cause oncogenic gain-of-function (GoF). The mechanism of the formation of the aggregates in the nucleus remains uncertain. The present study demonstrated that the DNA-binding domain of p53 (p53C) underwent phase separation (PS) on the pathway to aggregation under various conditions. p53C phase separated in the presence of the crowding agent polyethylene glycol (PEG). Similarly, mutant p53C (M237I and R249S) underwent PS; however, the process evolved to a solid-like phase transition faster than that in the case of wild-type p53C. The data obtained by microscopy of live cells indicated that transfection of mutant full-length p53 into the cells tended to result in PS and phase transition (PT) in the nuclear compartments, which are likely the cause of the GoF effects. Fluorescence recovery after photobleaching (FRAP) experiments revealed liquid characteristics of the condensates in the nucleus. Mutant p53 tended to undergo gel- and solid-like phase transitions in the nucleus and in nuclear bodies demonstrated by slow and incomplete recovery of fluorescence after photobleaching. Polyanions, such as heparin and RNA, were able to modulate PS and PT in vitro. Heparin apparently stabilized the condensates in a gel-like state, and RNA apparently induced a solid-like state of the protein even in the absence of PEG. Conditions that destabilize p53C into a molten globule conformation also produced liquid droplets in the absence of crowding. The disordered transactivation domain (TAD) modulated both phase separation and amyloid aggregation. In summary, our data provide mechanistic insight into the formation of p53 condensates and conditions that may result in the formation of aggregated structures, such as mutant amyloid oligomers, in cancer. The pathway of mutant p53 from liquid droplets to gel-like and solid-like (amyloid) species may be a suitable target for anticancer therapy.

Mutant p53 tends to form aggregates with amyloid properties, especially amyloid oligomers inside the nucleus, which are believed to cause oncogenic gain-of-function (GoF).     

Optically activated functionalization reactions in Si quantum dots

Using ab initio calculations, we have studied the influence of optical activation on functionalization reactions of silicon quantum dots with unsaturated hydrocarbons. We find that the energy barrier for the replacement of silicon-hydrogen with silicon-carbon bonds is dramatically reduced if the silicon dot is optically excited. These results provide an explanation for recent experiments on optically excited porous silicon. In addition, our calculations point at the existence of an intermediate spin-polarized state formed by the dot and an alkene or alkyne, upon relaxation after absorbing a photon. This state could be detected experimentally, by, for example, electron spin resonance measurements. Based on the results of our calculations as a function of the dot size, varied from 0.8 to 1.5 nm, we propose that light activated reactions could be used to functionalize and size select silicon quantum dots at the same time.     

Reaction of dichloroketene and sulfene with N,N-disubstituted α-aminomethyleneketones. Synthesis of pyrano[2,3-e]indazole and 1,2-oxathiino[6,5-e]indazole derivatives

The polar 1,4-cycloaddition of dichloroketene to N,N-disubstituted (E)-5-aminomethylene-1,5,6,7-tetrahydro-(1-methyl)(1-phenyl)-4H-indazol-4-ones V, prepared from 1,5,6,7-tetrahydro-(1-methyl)(1-phenyl)-4H-indazol-4-ones via the 5-hydroxymethylene derivatives, gave in good yield N,N-disubstituted 4-amino-3,3-dichloro-4,5,6,7-tetrahydro-(7-methyl)(7-phenyl)pyrano[2,3-e]indazol-(3H)ones VI, which are derivatives of the new heterocyclic system pyrano[2,3-e]indazole. Dehydrochlorination of VI with DBN afforded N,N-disubstituted 4-amino-3-chloro-6,7-dihydro(7-methyl)(7-phenyl)pyrano[2,3-e]indazol-2(5H]-ones VII generally in satisfactory yield. Full aromatization with DDQ of VII was tried only in the case of dimethylamino derivatives, giving a moderate yield of 3-chloro-4-dimethylamino(7-methyl)(7-phenyl)pyrano[2,3-e]indazol-2(7H)-ones. Cycloaddition of sulfene to V occurred only in the case of aliphatic N-substitution to give in moderate yield 4-dialkylamino-4,5,6,7-tetrahydro-(7-methyl)(7-phenyl)-3H-1,2-oxathiino[6,5-e]indazole 2,2-dioxides, which are derivatives of the new heterocyclic system 1,2-oxathiino[6,5-e]indazole.     

Copper(II) interaction with unstructured prion domain outside the octarepeat region: speciation, stability, and binding details of copper(II) complexes with PrP106-126 peptides

Copper(II) complexes of the neurotoxic peptide fragments of human and chicken prion proteins were studied by potentiometric, UV-vis, CD, and EPR spectroscopic and ESI-MS methods. The peptides included the terminally blocked native and scrambled sequences of HuPrP106-126 (HuPrPAc106-126NH2 and ScrHuPrPAc106-126NH2) and also the nona- and tetrapeptide fragments of both the human and chicken prion proteins (HuPrPAc106-114NH2, ChPrPAc119-127NH2, HuPrPAc109-112NH2, and ChPrPAc122-125NH2). The histidyl imidazole-N donor atoms were found to be the major copper(II) binding sites of all peptides; 3N and 4N complexes containing additional 2 and 3 deprotonated amide-N donors, respectively, are the major species in the physiological pH range. The complex formation processes for nona- and tetrapeptides are very similar, supporting the fact that successive deprotonation and metal ion coordination of amide functions go toward the N-termini in the form of joined six- and five-membered chelates. As a consequence, the peptide sequences investigated here, related to the neurotoxic region of the human PrP106-126 sequence, show a higher metal-binding affinity than the octarepeat fragments. In the case of the HuPrP peptide sequences, a weak pH-dependent binding of the Met109 residue was also detected in the 3N-coordinated complexes.     

The detection of oxygen in magneto-optical layers with SIMS

The detection of oxygen in magneto-optical layers is of fundamental importance for the characterization of the stability of RE-TM material. The magnetic properties are directly influenced by oxide formation. Oxygen depth profiles are carried out by using the SIMS technique. A comparison with magnetic measurements showed a clear conformity. We were able to study the oxidation behaviour of various layers at room temperature and at higher values up to 250° C for several hours. It could be shown that aluminum is a successful material for the protection of RE-films against oxidation. The difficulties of translating SIMS counting rates into concentration values were overcome by using EPMA. Specially prepared reference samples were measured by this technique and could then be used as standard samples for SIMS.     

Environmental effects on a prion's helix II domain: copper(II) and membrane interactions with PrP180-193 and its analogues

An abnormal interaction between copper and the prion protein is believed to play a pivotal role in the pathogenesis of prion diseases. Copper binding has been mainly attributed to the N-terminal domain of the prion protein, but this hypothesis has recently been challenged in some papers which suggest that the C-terminal domain might also compete for metal anchoring. In particular, the segment corresponding to the helix II region of the prion protein, namely PrP180-193, has been shown both to bind copper and to exhibit a copper-enhanced cytotoxicity, as well as to interact with artificial membranes. The present work is aimed at extending these results by choosing the most representative model of this domain and by determining its copper affinity. With this aim, the different role played by the electrostatic properties of the C- and N-termini of PrP180-193 (VNITIKQHTVTTTT) in determining its conformational behaviour, copper coordination and ability to perturb model membranes was investigated. Owing to the low solubility of PrP180-193, its copper affinity was evaluated by using the shorter PrPAc184-188NH2 (IKQHT) analogue as a model. ESI-MS, ESR, UV/Vis, and CD measurements were carried out on the copper(II)/PrPAc184-188NH2 and copper(II)/PrP180-193NH2 systems, and showed that PrPAc184-188NH2 is a reliable model for the metal interaction with the helix II domain. The affinity of copper(II) for the helix II fragment is higher than that for the octarepeat and PrP106-126 peptides. Finally, the different ability of PrP180-193 analogues to perturb the DPPC model membrane was assessed by DSC measurements. The possible biological consequences of these findings are also discussed briefly.     

Electron bombardment fragmentation of size selected molecular clusters

(CO₂) _n , (NO) _n and (NH₃) _n clusters are generated in a supersonic molecular beam and size selected by scattering from an He beam. By measurements of angular dependent mass spectra, TOF distributions and the angular dependence of the scattered signal quantitative information on the fragmentation probability by electron impact is derived. The van der Waals systems (CO₂) _n and (NO) _n appear only at masses which are simply multiples of the monomer mass. The preferred cluster ion is the monomer ion for all investigated cluster sizes withn=2 to 4. The fragment pattern for the quasi-hydrogen bonded (NH₃) _n -cluster shows, beside a large number of fragment masses, a preference for protonated ions. The results are explained in terms of simple models based on the structural change from the neutral to the ionized configuration and the fragmentation pattern of the monomer followed by ionmolecule reactions.     

X-ray spectroscopic characterization of Cu2+-phenanthroline complexes intercalated in α-zirconium phosphate

X-ray photoelectron spectroscopy provides evidence that when [Cu(phen)₂]²⁺(phen = 1,10-phenanthroline) is diffused between the layers of -zirconium phosphate, the complex species does not remain intact after intercalation, but some Cu-N bonds are broken, replaced with Cu-O bonds and the released nitrogen atoms can now interact with the PO₃-OH groups of the host. XPS also provides evidence for coordination of the Cu²⁺ ions when they are diffused by ion exchange in the phenanthroline--zirconium phosphate intercalation compound. Although Cu²⁺ and phen are in a 1 : 1 molar ratio in the interlayer region of the host, so that a 1 : 1 coordination could be expected between the two species, the characteristic peaks of the uncoordinated phenanthroline, even though at a low intensity, are still present. The differences between the two Cu(II)-intercalation compounds are discussed.     

Machine learning dielectric screening for the simulation of excited state properties of molecules and materials

Accurate and efficient calculations of absorption spectra of molecules and materials are essential for the understanding and rational design of broad classes of systems. Solving the Bethe–Salpeter equation (BSE) for electron–hole pairs usually yields accurate predictions of absorption spectra, but it is computationally expensive, especially if thermal averages of spectra computed for multiple configurations are required. We present a method based on machine learning to evaluate a key quantity entering the definition of absorption spectra: the dielectric screening. We show that our approach yields a model for the screening that is transferable between multiple configurations sampled during first principles molecular dynamics simulations; hence it leads to a substantial improvement in the efficiency of calculations of finite temperature spectra. We obtained computational gains of one to two orders of magnitude for systems with 50 to 500 atoms, including liquids, solids, nanostructures, and solid/liquid interfaces. Importantly, the models of dielectric screening derived here may be used not only in the solution of the BSE but also in developing functionals for time-dependent density functional theory (TDDFT) calculations of homogeneous and heterogeneous systems. Overall, our work provides a strategy to combine machine learning with electronic structure calculations to accelerate first principles simulations of excited-state properties.

Machine learning can circumvent explicit calculation of dielectric response in first principles methods and accelerate simulations of optical properties of complex materials at finite temperature.