Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p <0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p <0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management

Exceptionally large room-temperature ferroelectric polarization in the novel PbNiO3 multiferroic oxide

We present a study based on several advanced First-Principles methods, of the recently synthesized PbNiO3 [J. Am. Chem. Soc 133, 16920 (2011)], a rhombohedral antiferromagnetic insulator which crystallizes in the highly distorted R3c crystal structure. We find this compound electrically polarized, with a very large electric polarization of about 100 (\muC/cm)^2, thus even exceeding the polarization of well-known BiFeO3. PbNiO3 is a proper ferroelectric, with polarization driven by large Pb-O polar displacements along the [111] direction. Contrarily to naive expectations, a definite ionic charge of 4+ for Pb ion can not be assigned, and in fact the large Pb 6s-O 2p hybridization drives the ferroelectric distortion through a lone-pair mechanism similar to that of other Pb- and Bi-based multiferroic

Backtracking based iterated tabu search for equitable coloring

An equitable k  -coloring of an undirected graph G=(V,E)G=(V,E) is a partition of its vertices into k disjoint independent sets, such that the cardinalities of any two independent sets differ by at most one. As a variant of the graph coloring problem (GCP), the equitable coloring problem (ECP) concerns finding a minimum k for which an equitable k-coloring exists. In this work, we propose a backtracking based iterated tabu search (BITS) algorithm for solving the ECP approximately. BITS uses a backtracking scheme to define different k-ECP instances, an iterated tabu search approach to solve each particular k-ECP instance for a fixed k, and a binary search approach to find a suitable initial value of k. We assess the algorithm׳s performance on a set of commonly used benchmarks. Computational results show that BITS is very competitive in terms of solution quality and computing efficiency compared to the state-of-the-art algorithm in the literature. Specifically, BITS obtains new upper bounds for 21 benchmark instances, while matching the previous best upper bound for the remaining instances. Finally, to better understand the proposed algorithm, we study how its key ingredients impact its performance

The Properties of H{\alpha} Emission-Line Galaxies at z = 2.24

Using deep narrow-band $H_2S1$ and $K_{s}$-band imaging data obtained with CFHT/WIRCam, we identify a sample of 56 H$\alpha$ emission-line galaxies (ELGs) at $z=2.24$ with the 5$\sigma$ depths of $H_2S1=22.8$ and $K_{s}=24.8$ (AB) over 383 arcmin$^{2}$ area in the ECDFS. A detailed analysis is carried out with existing multi-wavelength data in this field. Three of the 56 H$\alpha$ ELGs are detected in Chandra 4 Ms X-ray observation and two of them are classified as AGNs. The rest-frame UV and optical morphologies revealed by HST/ACS and WFC3 deep images show that nearly half of the H$\alpha$ ELGs are either merging systems or with a close companion, indicating that the merging/interacting processes play a key role in regulating star formation at cosmic epoch z=2-3; About 14% are too faint to be resolved in the rest-frame UV morphology due to high dust extinction. We estimate dust extinction from SEDs. We find that dust extinction is generally correlated with H$\alpha$ luminosity and stellar mass (SM). Our results suggest that H$\alpha$ ELGs are representative of star-forming galaxies (SFGs). Applying extinction correction for individual objects, we examine the intrinsic H$\alpha$ luminosity function (LF) at $z=2.24$, obtaining a best-fit Schechter function characterized by a faint-end slope of $\alpha=-1.3$. This is shallower than the typical slope of $\alpha \sim -1.6$ in previous works based on constant extinction correction. We demonstrate that this difference is mainly due to the different extinction corrections. The proper extinction correction is thus key to recovering the intrinsic LF as the extinction globally increases with H$\alpha$ luminosity. Moreover, we find that our H$\alpha$ LF mirrors the SM function of SFGs at the same cosmic epoch. This finding indeed reflects the tight correlation between SFR and SM for the SFGs, i.e., the so-called main sequence.Comment: 15 pages, 12 figures, 2 tables, Received 2013 October 11; accepted 2014 February 13; published 2014 March 18 by Ap

A study of two evolutionary/tabu search approaches for the generalized max-mean dispersion problem

Evolutionary computing is a general and powerful framework for solving difficult optimization problems, including those arising in expert and intelligent systems. In this work, we investigate for the first time two hybrid evolutionary algorithms incorporating tabu search for solving the generalized max-mean dispersion problem (GMaxMeanDP) which has a variety of practical applications such as web page ranking, community mining, and trust networks. The proposed algorithms integrate innovative search strategies that help the search to explore the search space effectively. We report extensive computational results of the proposed algorithms on six types of 160 benchmark instances, demonstrating their effectiveness and usefulness. In addition to the GMaxMeanDP, the proposed algorithms can help to better solve other problems that can be formulated as the GMaxMeanDP

Laser-induced charging of microfabricated ion traps

Electrical charging of metal surfaces due to photoelectric generation of carriers is of concern in trapped ion quantum computation systems, due to the high sensitivity of the ions' motional quantum states to deformation of the trapping potential. The charging induced by typical laser frequencies involved in doppler cooling and quantum control is studied here, with microfabricated surface electrode traps made of aluminum, copper, and gold, operated at 6 K with a single Sr$^+$ ion trapped 100 $\mu$m above the trap surface. The lasers used are at 370, 405, 460, and 674 nm, and the typical photon flux at the trap is 10$^{14}$ photons/cm$^2$/sec. Charging is detected by monitoring the ion's micromotion signal, which is related to the number of charges created on the trap. A wavelength and material dependence of the charging behavior is observed: lasers at lower wavelengths cause more charging, and aluminum exhibits more charging than copper or gold. We describe the charging dynamic based on a rate equation approach.Comment: 8 pages, 8 figure

A two-phase tabu-evolutionary algorithm for the 0–1 multidimensional knapsack problem

The 0–1 multidimensional knapsack problem is a well-known NP-hard combinatorial optimization problem with numerous applications. In this work, we present an effective two-phase tabu-evolutionary algorithm for solving this computationally challenging problem. The proposed algorithm integrates two solution-based tabu search methods into the evolutionary framework that applies a hyperplane-constrained crossover operator to generate offspring solutions, a dynamic method to determine search zones of interest, and a diversity-based population updating rule to maintain a healthy population. We show the competitiveness of the proposed algorithm by presenting computational results on the 281 benchmark instances commonly used in the literature. In particular, in a computational comparison with the best algorithms in the literature on multiple data sets, we show that our method on average matches more than twice the number of best known solutions to the harder problems than any other method and in addition yields improved best solutions (new lower bounds) for 4 difficult instances. We investigate two key ingredients of the algorithm to understand their impact on the performance of the algorithm