In this study, an artificial neural networks study was carried out to predict the quantity of ammonia gas (NH3) of Granulated Blast Furnace Slag (GBFS) cement mortar. A data set of a laboratory work, in which a total of 4 mortars were produced, was utilized in the Artificial Neural Networks (ANNs) study. The mortar mixture parameters were four different GBFS ratios (0%, 20%, 40% and 60%). Measu...

Greedy Best-First Search (GBFS) is a powerful algorithm at the heart of many state of the art satisficing planners. One major weakness of GBFS is its behavior in so-called uninformative heuristic regions (UHRs) parts of the search space in which no heuristic provides guidance towards states with improved heuristic values. This work analyzes the problem of UHRs in planning in detail, and propose...

Anisotropic gold nanostructures with unique plasmonic properties, specifically the strong absorption of light in the near-infrared region (650-900 nm) due to the excitation of plasmon oscillations, have been widely employed as photothermal conversion agents (PTCAs) for cancer photothermal therapy (PTT). However, the reported PTCAs show suboptimal photothermal conversion efficiency (η), even gol...

We present a novel gold bellflower (GBF) platform with multiple-branched petals, prepared by a liquid-liquid-gas triphase interface system, for photoacoustic imaging (PAI)-guided photothermal therapy (PTT). Upon near-infrared (NIR) laser irradiation, the GBFs, with strong NIR absorption, showed very strong PA response and an ultrahigh photothermal conversion efficiency (η, ∼74%) among the repor...

In satisficing planning where suboptimal plans are accepted, many planners use greedy best-first search (GBFS). Despite recent advances in automatic heuristic function generation, GBFS often suffers from performance degradation caused by inaccurate state evaluations. Diverse best-first search (DBFS) (Imai and Kishimoto 2011) avoids plateaus of search due to such inaccuracies by occasionally sel...

Recent enhancements to greedy best-first search (GBFS) such as DBFS, -GBFS, Type-GBFS improve performance by occasionally adopting a non-greedy node expansion policy, resulting in more exploratory behavior. However, previous exploratory mechanisms do not address exploration within the space sharing the same heuristic estimate (plateau). In this paper, we show these two modes of exploration, whi...

In action planning, greedy best-first search (GBFS) is one of the standard techniques if suboptimal plans are accepted. GBFS uses a heuristic function to guide the search towards a goal state. To achieve generality, in domain-independant planning the heuristic function is generated automatically. A well-known problem of GBFS are search plateaus, i. e., regions in the search space where all stat...

Functional cell-free systems may be excellent tools with which to investigate light-dependent signal transduction mechanisms in plants. By evacuolation of parsley protoplasts and subsequent silicon oil gradient centrifugation of lysed evacuolated protoplasts, we obtained a highly pure and concentrated plasma membrane-containing cytosol. Using GT- and G-box DNA elements, we were able to demonstr...

We obtain the nonexistence of generalized bent functions (GBFs) from (\ZZ/t\ZZ)^n to \ZZ/t\ZZ (called type [n,t]), for a large new class. Specifically, by showing certain quadratic norm form equations have no integral points, we obtain the universal nonexistence of GBFs with type [n, 2p^e] for all sufficiently large p with respect to n and (p-1)/\ord_2(p), and by computational methods with a we...

Suboptimal heuristic search algorithms such as weighted A* and greedy best-first search (GBFS) are widely used to solve problems for which guaranteed optimal solutions are too expensive to obtain. These algorithms crucially rely on a heuristic function to guide their search. However, most research on building heuristics addresses optimal solving. In this paper, we illustrate how established wis...