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Although high-performance computing (HPC) systems have been scaled to meet the exponentially growing demand for scientific computing, HPC performance variability remains a major challenge in computer science. Statistically, performance variability can be characterized by a distribution. Predicting performance variability is a critical step in HPC performance variability management. In this article, we propose a new framework to predict performance distributions. The proposed framework is a modified Gaussian process that can predict the distribution function of the input/output (I/O) throughput under a specific HPC system configuration. We also impose a monotonic constraint so that the predicted function is nondecreasing, which is a property of the cumulative distribution function. Additionally, the proposed model can incorporate both quantitative and qualitative input variables. We predict the HPC I/O distribution using the proposed method for the IOzone variability data. Data analysis results show that our framework can generate accurate predictions, and outperform existing methods. We also show how the predicted functional output can be used to generate predictions for a scalar summary of the performance distribution, such as the mean, standard deviation, and quantiles. Our prediction results can further be used for HPC system variability monitoring and optimization. This article has online supplementary materials.

 

Complex systems can exhibit sudden transitions or regime shifts from one stable state to another, typically referred to as critical transitions. It becomes a great challenge to identify a robust warning sufficiently early that action can be taken to avert a regime shift. We employ landscape-flux theory from nonequilibrium statistical mechanics as a general framework to quantify the global stability of ecological systems and provide warning signals for critical transitions. We quantify the average flux as the nonequilibrium driving force and the dynamical origin of the nonequilibrium transition while the entropy production rate as the nonequilibrium thermodynamic cost and thermodynamic origin of the nonequilibrium transition. Average flux, entropy production, nonequilibrium free energy, and time irreversibility quantified by the difference in cross-correlation functions forward and backward in time can serve as early warning signals for critical transitions much earlier than other conventional predictors. We utilize a classical shallow lake model as an exemplar for our early warning prediction. Our proposed method is general and can be readily applied to assess the resilience of many other ecological systems. The early warning signals proposed here can potentially predict critical transitions earlier than established methods and perhaps even sufficiently early to avert catastrophic shifts. 

ABSTRACT This note describes improvements of UV oxidation method that is used to measure carbon isotopes of dissolved organic carbon (DOC) at the National Ocean Sciences Accelerator Mass Spectrometry Facility (NOSAMS). The procedural blank is reduced to 2.6 ± 0.6 μg C, with Fm of 0.42 ± 0.10 and δ 13 C of –28.43 ± 1.19‰. The throughput is improved from one sample per day to two samples per day. 

The search for more effective and highly selective C–H bond oxidation of accessible hydrocarbons and biomolecules is a greatly attractive research mission. The elucidating of mechanism and controlling factors will, undoubtedly, help to broaden scope of these synthetic protocols, and enable discovery of more efficient, environmentally benign, and highly practical new C–H oxidation reactions. Here, we reveal the stepwise intramolecular S_N2 nucleophilic substitution mechanism with the rate-limiting C–O bond formation step for the Pd(II)-catalyzed C(sp³)–H lactonization in aromatic 2,6-dimethylbenzoic acid. We show that for this reaction, the direct C–O reductive elimination from both Pd(II) and Pd(IV) (oxidized by O₂oxidant) intermediates is unfavorable. Critical factors controlling the outcome of this reaction are the presence of the η³-(π-benzylic)–Pd and K⁺–O(carboxylic) interactions. The controlling factors of the benzylic vs ortho site-selectivity of this reaction are the: (a) difference in the strains of the generated lactone rings; (b) difference in the strengths of the η³-(π-benzylic)–Pd and η²-(π-phenyl)–Pd interactions, and (c) more pronounced electrostatic interaction between the nucleophilic oxygen and K⁺cation in the ortho-C–H activation transition state. The presented data indicate the utmost importance of base, substrate, and ligand in the selective C(sp³)–H bond lactonization in the presence of C(sp²)–H.

 

We report a molecular switching ensemble whose states may be regulated in synergistic fashion by both protonation and photoirradiation. This allows hierarchical control in both a kinetic and thermodynamic sense. These pseudorotaxane-based molecular devices exploit the so-called Texas-sized molecular box (cyclo[2]-(2,6-di(1H-imidazol-1-yl)pyridine)[2](1,4-dimethylenebenzene); 1⁴⁺, studied as its tetrakis-PF₆⁻salt) as the wheel component. Anions of azobenzene-4,4′-dicarboxylic acid (2H⁺•2) or 4,4′-stilbenedicarboxylic acid (2H⁺•3) serve as the threading rod elements. The various forms of 2 and 3 (neutral, monoprotonated, and diprotonated) interact differently with 1⁴⁺, as do the photoinducedcisortransforms of these classic photoactive guests. The net result is a multimodal molecular switch that can be regulated in synergistic fashion through protonation/deprotonation and photoirradiation. The degree of guest protonation is the dominating control factor, with light acting as a secondary regulatory stimulus. The present dual input strategy provides a complement to more traditional orthogonal stimulus-based approaches to molecular switching and allows for the creation of nonbinary stimulus-responsive functional materials.