Synthesis and reactivity of half-sandwich (η 5 -C 5 Me 5 )Ir(iii) complexes of a cyclometallated aryl phosphine ligand

Reaction of the Ir(iii) dimer [(η 5 -C 5 Me 5 )IrCl 2 ] 2 with PMeXyl 2 (Xyl = 2,6-C 6 H 3 Me 2 ), in the presence of the poorly coordinating base 2,2,6,6-tetramethyl piperidine, gives a chloride complex 1-Cl, resulting from hydrogen chloride elimination involving one of the phosphine benzylic hydrogen atoms and concomitant cyclometallation. Related compounds containing other halide or pseudohalide ligands, 1-Br, 1-Cl, 1-SCN, can be made, the latter featuring S-coordination of the ambidentate thiocyanate to the soft Ir(iii) Lewis acid centre, as suggested by IR data and demonstrated by X-ray crystallography. Hydride 2-H, and alkyl derivatives 3 (Me) and 4 (CH 2 SiMe 3 ) can also be prepared from 1-Cl and appropriate hydride and alkylating reagents. An interesting H/D exchange chemistry that occurs in the presence of CD 3 OD has been disclosed for 1-Cl, 1-Br and 2-H. For the halide derivatives, deuterium incorporation takes place into the methylene and methyl sites of their cyclometallated ligand, whereas for 2-H only the hydride and methylene (Ir-CH 2 ) protons participate in the exchange, which is strikingly accelerated by catalytic amounts of acids.Ministerio de Ciencia e Innovación CTQ2010-17476Consolider-Ingenio2010 CSD2007-0000Junta de Andalucia FQM-119, P09-FQM-483

Flipped Classroom Teaching in Organic Chemistry in the Context of CLIL

This paper proposes an experience that involves the methodological model of the flipped classroom with the introduction of foreign language teaching, to promote the acquisition of transversal and linguistic skills in three subjects of the Degree in Chemistry at the University of Huelva (Spain). This proposal includes the implementation of this methodology in different didactic units of each one of the subjects. The method is developed in 4 different phases, starting with the programming of the experience; elaboration of the teaching material for its development, based on the autonomous work of the students; to the classroom work and resolution of doubts that take place in the classroom. The implementation of this teachinglearning experience has been globally successful

Line-Strength Indices in Bright Spheroidals: Evidence for a Stellar Population Dichotomy between Spheroidal and Elliptical Galaxies

We present new measurements of central line-strength indices (namely Mg2, , and Hbeta and gradients for a sample of 6 bright spheroidal galaxies (Sph's) in the Virgo cluster. Comparison with similar measurements for elliptical galaxies (E's), galactic globular clusters (GGC's), and stellar population models yield the following results: (1) In contrast with bright E's, bright Sph's are consistent with solar abundance [Mg/Fe] ratios; (2) Bright Sph's exhibit metallicities ranging from values typical for metal-rich GGC's to those for E's; (3) Although absolute mean ages are quite model dependent, we find evidence that the stellar populations of some (if not all) Sph's look significantly younger than GGC's; and (4) Mg2 gradients of bright Sph's are significantly shallower than those of E galaxies. We conclude that the dichotomy found in the structural properties of Sph and E galaxies is also observed in their stellar populations. A tentative interpretation in terms of differences in star formation histories is suggested.Comment: 14 pages, LaTeX file + 2 PostScript figures, aasms4.sty require

Simultaneous Estimation of Vehicle Roll and Sideslip Angles through a Deep Learning Approach

Presently, autonomous vehicles are on the rise and are expected to be on the roads in the coming years. In this sense, it becomes necessary to have adequate knowledge about its states to design controllers capable of providing adequate performance in all driving scenarios. Sideslip and roll angles are critical parameters in vehicular lateral stability. The later has a high impact on vehicles with an elevated center of gravity, such as trucks, buses, and industrial vehicles, among others, as they are prone to rollover. Due to the high cost of the current sensors used to measure these angles directly, much of the research is focused on estimating them. One of the drawbacks is that vehicles are strong non-linear systems that require specific methods able to tackle this feature. The evolution in Artificial Intelligence models, such as the complex Artificial Neural Network architectures that compose the Deep Learning paradigm, has shown to provide excellent performance for complex and non-linear control problems. In this paper, the authors propose an inexpensive but powerful model based on Deep Learning to estimate the roll and sideslip angles simultaneously in mass production vehicles. The model uses input signals which can be obtained directly from onboard vehicle sensors such as the longitudinal and lateral accelerations, steering angle and roll and yaw rates. The model was trained using hundreds of thousands of data provided by Trucksim® and validated using data captured from real driving maneuvers using a calibrated ground truth device such as VBOX3i dual-antenna GPS from Racelogic®. The use of both Trucksim® software and the VBOX measuring equipment is recognized and widely used in the automotive sector, providing robust data for the research shown in this article.This work was supported by the Agencia Estatal de Investigacion (EAI) of the Ministry of Science and Innovation of the Government of Spain through the project RTI2018-095143-B-C21

Spectrophotometric study in the near-ir of a sample of MIPS selected galaxies at Z~2

Our main objective is to determine what kind of galaxies dominate the cosmic SFR density at z~2. Our sample consists of 24 galaxies in Chandra Deep Field South, a unique field for the study of galaxy evolution (12 observed with GNIRS/GEMINI and 12 with ISAAC/VLT). We use H alpha together with the already merged X-ray, ultraviolet, optical, near and mid-infrared imaging data to obtain estimations of SFRs, metallicities, stellar and dynamical masses, AGN activity, and extinction properties. We have obtained 15 Hα detections, 4 rotation curves, and SFR relationship for 7 galaxies. The metallicities obtained for 8 galaxies of the sample are compatible with the metallicities of local galaxies

Real-Time Vehicle Roll Angle Estimation Based on Neural Networks in IoT Low-Cost Devices

The high rate of vehicle-crash victims has a fatal economic and social impact in today's societies. In particular, road crashes where heavy vehicles are involved cause more severe damage because they are prone to rollover. For this reason, many researches are focused on developing RSC Roll Stability Control (RSC) systems. Concerning the design of RSC systems with an adequate performance, it is mandatory to know the dynamics of the vehicle. The main problem arises from the lack of ability to directly capture several required dynamic vehicle variables, such as roll angle, from low-cost sensors. Previous studies demonstrate that low-cost sensors can provide data in real-time with the required precision and reliability. Even more, other research works indicate that neural networks are efficient mechanisms to estimate roll angle. Nevertheless, it is necessary to assess that the fusion of data coming from low-cost devices and estimations provided by neural networks can fulfill hard real-time processing constraints, achieving high level of accuracy during circulation of a vehicle in real situations. In order to address this issue, this study has two main goals: (1) Design and develop an IoT based architecture, integrating ANN in low cost kits with different hardware architectures in order to estimate under real-time constraints the vehicle roll angle. This architecture is able to work under high dynamic conditions, by following specific best practices and considerations during its design; (2) assess that the IoT architecture deployed in low-cost experimental kits achieve the hard real-time performance constraints estimating the roll angle with the required calculation accuracy. To fulfil these objectives, an experimental environment was set up, composed of a van with two set of low-cost kits, one including a Raspberry Pi 3 Model Band the other having an Intel Edison System on Chip linked to a SparkFun 9 Degrees of Freedom module.This research was funded by Spanish Government through the projects TRA2013-48030-C2-1-R and TRA2008-05373/AUT