Precise Measurement of Gravity Variations During a Total Solar Eclipse

The variations of gravity were measured with a high precision LaCoste-Romberg D gravimeter during a total solar eclipse to investigate the effect of solar eclipse on the gravitational field. The observed anomaly $(7.0 \pm 2.7) \times 10^{-8}$ m/s$^2$ during the eclipse implies that there may be a shielding property of gravitation

A Note on Noncommutative Brane Inflation

In this paper, we investigate the noncommutative KKLMMT D3/anti-D3 brane inflation scenario in detail. Incorporation of the brane inflation scenario and the noncommutative inflation scenario can nicely explain the large negative running of the spectral index as indicated by WMAP three-year data and can significantly release the fine-tuning for the parameter $\beta$. Using the WMAP three year results (blue-tilted spectral index with large negative running), we explore the parameter space and give the constraints and predictions for the inflationary parameters and cosmological observables in this scenario. We show that this scenario predicts a quite large tensor/scalar ratio and what is more, a too large cosmic string tension (assuming that the string coupling $g_s$ is in its likely range from 0.1 to 1) to be compatible with the present observational bound. A more detailed analysis reveals that this model has some inconsistencies according to the fit to WMAP three year results.Comment: 20 pages, 5 figures; accepted for publication in JCA

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios

A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy

A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a benchmark composed by 15 instances has been also proposed. In the design of this benchmark, real geographical positions have been used, located in the province of Bizkaia, Spain. For the proper treatment of this AC-VRP-SPDVCFP, a discrete firefly algorithm (DFA) has been developed. This application is the first application of the firefly algorithm to any rich vehicle routing problem. To prove that the proposed DFA is a promising technique, its performance has been compared with two other well-known techniques: an evolutionary algorithm and an evolutionary simulated annealing. Our results have shown that the DFA has outperformed these two classic meta-heuristics

On the Bounds of Function Approximations

Within machine learning, the subfield of Neural Architecture Search (NAS) has recently garnered research attention due to its ability to improve upon human-designed models. However, the computational requirements for finding an exact solution to this problem are often intractable, and the design of the search space still requires manual intervention. In this paper we attempt to establish a formalized framework from which we can better understand the computational bounds of NAS in relation to its search space. For this, we first reformulate the function approximation problem in terms of sequences of functions, and we call it the Function Approximation (FA) problem; then we show that it is computationally infeasible to devise a procedure that solves FA for all functions to zero error, regardless of the search space. We show also that such error will be minimal if a specific class of functions is present in the search space. Subsequently, we show that machine learning as a mathematical problem is a solution strategy for FA, albeit not an effective one, and further describe a stronger version of this approach: the Approximate Architectural Search Problem (a-ASP), which is the mathematical equivalent of NAS. We leverage the framework from this paper and results from the literature to describe the conditions under which a-ASP can potentially solve FA as well as an exhaustive search, but in polynomial time.Comment: Accepted as a full paper at ICANN 2019. The final, authenticated publication will be available at https://doi.org/10.1007/978-3-030-30487-4_3

Two Prp19-Like U-Box Proteins in the MOS4-Associated Complex Play Redundant Roles in Plant Innate Immunity

Plant Resistance (R) proteins play an integral role in defense against pathogen infection. A unique gain-of-function mutation in the R gene SNC1, snc1, results in constitutive activation of plant immune pathways and enhanced resistance against pathogen infection. We previously found that mutations in MOS4 suppress the autoimmune phenotypes of snc1, and that MOS4 is part of a nuclear complex called the MOS4-Associated Complex (MAC) along with the transcription factor AtCDC5 and the WD-40 protein PRL1. Here we report the immuno-affinity purification of the MAC using HA-tagged MOS4 followed by protein sequence analysis by mass spectrometry. A total of 24 MAC proteins were identified, 19 of which have predicted roles in RNA processing based on their homology to proteins in the Prp19-Complex, an evolutionarily conserved spliceosome-associated complex containing homologs of MOS4, AtCDC5, and PRL1. Among these were two highly similar U-box proteins with homology to the yeast and human E3 ubiquitin ligase Prp19, which we named MAC3A and MAC3B. MAC3B was recently shown to exhibit E3 ligase activity in vitro. Through reverse genetics analysis we show that MAC3A and MAC3B are functionally redundant and are required for basal and R protein–mediated resistance in Arabidopsis. Like mos4-1 and Atcdc5-1, mac3a mac3b suppresses snc1-mediated autoimmunity. MAC3 localizes to the nucleus and interacts with AtCDC5 in planta. Our results suggest that MAC3A and MAC3B are members of the MAC that function redundantly in the regulation of plant innate immunity

Metaheuristic optimization of reinforced concrete footings

The primary goal of an engineer is to find the best possible economical design and this goal can be achieved by considering multiple trials. A methodology with fast computing ability must be proposed for the optimum design. Optimum design of Reinforced Concrete (RC) structural members is the one of the complex engineering problems since two different materials which have extremely different prices and behaviors in tension are involved. Structural state limits are considered in the optimum design and differently from the superstructure members, RC footings contain geotechnical limit states. This study proposes a metaheuristic based methodology for the cost optimization of RC footings by employing several classical and newly developed algorithms which are powerful to deal with non-linear optimization problems. The methodology covers the optimization of dimensions of the footing, the orientation of the supported columns and applicable reinforcement design. The employed relatively new metaheuristic algorithms are Harmony Search (HS), Teaching-Learning Based Optimization algorithm (TLBO) and Flower Pollination Algorithm (FPA) are competitive for the optimum design of RC footings

IDN2 and Its Paralogs Form a Complex Required for RNA–Directed DNA Methylation

IDN2/RDM12 has been previously identified as a component of the RNA–directed DNA methylation (RdDM) machinery in Arabidopsis thaliana, but how it functions in RdDM remains unknown. By affinity purification of IDN2, we co-purified two IDN2 paralogs IDP1 and IDP2 (IDN2 PARALOG 1 and 2). The coiled-coil domain between the XS and XH domains of IDN2 is essential for IDN2 homodimerization, whereas the IDN2 C-terminal XH domain but not the coiled-coil domain is required for IDN2 interaction with IDP1 and IDP2. By introducing the wild-type IDN2 sequence and its mutated derivatives into the idn2 mutant for complementation testing, we demonstrated that the previously uncharacterized IDN2 XH domain is required for the IDN2-IDP1/IDP2 complex formation as well as for IDN2 function. IDP1 is required for de novo DNA methylation, siRNA accumulation, and transcriptional gene silencing, whereas IDP2 has partially overlapping roles with IDP1. Unlike IDN2, IDP1 and IDP2 are incapable of binding double-stranded RNA, suggesting that the roles of IDP1 and IDP2 are different from those of IDN2 in the IDN2-IDP1/IDP2 complex and that IDP1 and IDP2 are essential for the functioning of the complex in RdDM