Sequential Symbolic Regression with Genetic Programming

This chapter describes the Sequential Symbolic Regression (SSR) method, a new strategy for function approximation in symbolic regression. The SSR method is inspired by the sequential covering strategy from machine learning, but instead of sequentially reducing the size of the problem being solved, it sequentially transforms the original problem into potentially simpler problems. This transformation is performed according to the semantic distances between the desired and obtained outputs and a geometric semantic operator. The rationale behind SSR is that, after generating a suboptimal function f via symbolic regression, the output errors can be approximated by another function in a subsequent iteration. The method was tested in eight polynomial functions, and compared with canonical genetic programming (GP) and geometric semantic genetic programming (SGP). Results showed that SSR significantly outperforms SGP and presents no statistical difference to GP. More importantly, they show the potential of the proposed strategy: an effective way of applying geometric semantic operators to combine different (partial) solutions, avoiding the exponential growth problem arising from the use of these operators

Charmonium spectral functions in pˉA\bar p A collision

We study the in-medium propagation of low-lying charmonium states: $J/\Psi$, $\Psi$(3686), and $\Psi$(3770) in a $\bar p$ Au $10$ GeV collision. This energy regime will be available for the PANDA experiment. The time evolution of the spectral functions of the charmonium states is studied with a BUU type transport model. We observe a substantial effect of the medium in the dilepton spectrum.Comment: 6 pages, 4 figures, Presented at Excited QCD 2017, Sintra, Portuga

Some functional equations related to the characterizations of information measures and their stability

The main purpose of this paper is to investigate the stability problem of some functional equations that appear in the characterization problem of information measures.Comment: 36 pages. arXiv admin note: text overlap with arXiv:1307.0657, arXiv:1307.0631, arXiv:1307.0664, arXiv:1307.065

Extending the applicability of the adaptive comfort model to the control of air-conditioning systems

Extensive studies have been done on adaptive thermal comfort for naturally ventilated buildings. However, further studies of the adaptive comfort model are needed to develop a control method for buildings with the air-conditioning systems. This study aims to extend the application of the adaptive comfort model by developing an adaptive comfort control (ACC) for air-conditioning systems. Special attention is given to testing the acceptability of the ACC to the occupants of the office buildings. Two extensive longitudinal field studies were carried out that involved 807 office workers and a total of 13,523 individual comfort votes were collected. This study reveals that it is possible to develop statistically and substantively significant adaptive comfort models for the cooling operation of air-conditioned buildings. This field study provides scientific evidence that the adaptive comfort model can be used to control an air-conditioning system without sacrificing occupants’ thermal comfort. Further field studies on air-conditioned buildings are warranted to quantify the energy use implications of the ACC.Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT and Future Planning (Grant ID: 2014R1A1A2054494)This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.buildenv.2016.05.02

Dual Drug-Loaded Biofunctionalized Amphiphilic Chitosan Nanoparticles: Enhanced Synergy between Cisplatin and Demethoxycurcumin against Multidrug-Resistant Stem-Like Lung Cancer Cells

Lung cancer kills more humans than any other cancer and multidrug resistance (MDR) in cancer stem-like cells (CSC) is emerging as a reason for failed treatments. One concept which addresses this root cause of treatment failure is the utilization of nanoparticles to simultaneously deliver dual drugs to cancer cells with synergistic performance, easy to envision - hard to achieve. It is challenging to simultaneously load drugs of highly different physicochemical properties into one nanoparticle, release kinetics may differ between drugs and general requirements for biomedical nanoparticles apply. Here self-assembled nanoparticles of amphiphilic carboxymethyl-hexanoyl chitosan (CHC) were shown to present nano-microenvironments enabling simultaneous loading of hydrophilic and hydrophobic drugs. This was expanded into a dual-drug nano-delivery system to treat lung CSC. CHC nanoparticles were loaded/chemically modified with the anticancer drug cisplatin and the MDR-suppressing Chinese herbal extract demethoxycurcumin, followed by biofunctionalization with CD133 antibody for enhanced uptake by lung CSC, all in a feasible one-pot preparation. The nanoparticles were characterized with regard to chemistry, size, zeta potential and drug loading/release. Biofunctionalized and non-functionalized nanoparticles were investigated for uptake by lung CSC. Subsequently the cytotoxicity of single and dual drugs, free in solution or in nanoparticles, was evaluated against lung CSC at different doses. From the dose response at different concentrations the degree of synergy was determined through Chou-Talalay's Plot. The biofunctionalized nanoparticles promoted synergistic effects between the drugs and were highly effective against MDR lung CSC. The efficacy and feasible one-pot preparation suggest preclinical studies using relevant disease models to be justified

Chasing Carbon: The Elusive Environmental Footprint of Computing

Given recent algorithm, software, and hardware innovation, computing has enabled a plethora of new applications. As computing becomes increasingly ubiquitous, however, so does its environmental impact. This paper brings the issue to the attention of computer-systems researchers. Our analysis, built on industry-reported characterization, quantifies the environmental effects of computing in terms of carbon emissions. Broadly, carbon emissions have two sources: operational energy consumption, and hardware manufacturing and infrastructure. Although carbon emissions from the former are decreasing thanks to algorithmic, software, and hardware innovations that boost performance and power efficiency, the overall carbon footprint of computer systems continues to grow. This work quantifies the carbon output of computer systems to show that most emissions related to modern mobile and data-center equipment come from hardware manufacturing and infrastructure. We therefore outline future directions for minimizing the environmental impact of computing systems

Medium Effects on Binary Collisions with the Delta Resonance

To facilitate the relativistic heavy-ion calculations based on transport equations, the binary collisions involving a $\Delta$ resonance in either the entrance channel or the exit channel are investigated within a Hamiltonian formulation of $\pi NN$ interactions. An averaging procedure is developed to define a quasi-particle $\Delta^*$ and to express the experimentally measured $NN\rightarrow \pi NN$ cross section in terms of an effective $NN\rightarrow N\Delta^\ast$ cross section. In contrast to previous works, the main feature of the present approach is that the mass and the momentum of the produced $\Delta^*$'s are calculated dynamically from the bare $\Delta \leftrightarrow \pi N$ vertex interaction of the model Hamiltonian and are constrained by the unitarity condition. The procedure is then extended to define the effective cross sections for the experimentally inaccessible $N\Delta^\ast \rightarrow NN$ and $N\Delta^\ast \rightarrow N\Delta^\ast$ reactions. The predicted cross sections are significantly different from what are commonly assumed in relativistic heavy-ion calculations. The $\Delta$ potential in nuclear matter has been calculated by using a Bruckner-Hartree-Fock approximation. By including the mean-field effects on the $\Delta$ propagation, the effective cross sections of the $NN\rightarrow N\Delta^\ast$, $N\Delta^\ast \rightarrow NN$ and $N\Delta^\ast \rightarrow N\Delta^\ast$ reactions in nuclear matter are predicted. It is demonstrated that the density dependence is most dramatic in the energy region close to the pion production threshold.Comment: 20 pages, RevTe

A variable star survey of the open cluster M37

A CCD photometric study of the dense galactic open cluster M37 is presented and discussed. The majority of the analysed data are time-series measurements obtained through an R_C filter. The observations were carried out on seven nights between December 1999 and February 2000, and have led to the discovery of 7 new variable stars in the field. Three of them have been unambiguously identified as W UMa-type eclipsing binaries, while two more are monoperiodic pulsating stars, most probably high-amplitude delta Scuti-type variables. The remaining two stars seem to be long-period eclipsing binaries without firm period determination. Johnson B and V frames have been used to construct a new colour-magnitude (CM) diagram of the cluster, and to find the locations of the new variable stars. The pulsating variables are most likely background objects. The CM diagram is fitted with recent isochrones yielding the main parameters of the cluster.Comment: 7 pages, 6 figures, accepted for publication in A&