Carotenoid triplet state formation in Rhodobacter sphaeroides R-26 reaction centers exchanged with modified bacteriochlorophyll pigments and reconstituted with spheroidene

Triplet state electron paramagnetic resonance (EPR) experiments have been carried out at X-band on Rb. sphaeroides R-26 reaction centers that have been reconstituted with the carotenoid, spheroidene, and exchanged with 132-OH-Zn-bacteriochlorophyll a and [3-vinyl]-132-OH-bacteriochlorophyll a at the monomeric, lsquoaccessoryrsquo bacteriochlorophyll sites BA,B or with pheophytin a at the bacteriopheophytin sites HA,B. The primary donor and carotenoid triplet state EPR signals in the temperature range 95–150 K are compared and contrasted with those from native Rb. sphaeroides wild type and Rb. sphaeroides R-26 reaction centers reconstituted with spheroidene. The temperature dependencies of the EPR signals are strikingly different for the various samples. The data prove that triplet energy transfer from the primary donor to the carotenoid is mediated by the monomeric, BChlB molecule. Furthermore, the data show that triplet energy transfer from the primary donor to the carotenoid is an activated process, the efficiency of which correlates with the estimated triplet state energies of the modified pigments

Anisotropic Galactic Outflows and Enrichment of the Intergalactic Medium. I: Monte Carlo Simulations

We have developed an analytical model to describe the evolution of anisotropic galactic outflows. With it, we investigate the impact of varying opening angle on galaxy formation and the evolution of the IGM. We have implemented this model in a Monte Carlo algorithm to simulate galaxy formation and outflows in a cosmological context. Using this algorithm, we have simulated the evolution of a comoving volume of size [12h^(-1)Mpc]^3 in the LCDM universe. Starting from a Gaussian density field at redshift z=24, we follow the formation of ~20,000 galaxies, and simulate the galactic outflows produced by these galaxies. When these outflows collide with density peaks, ram pressure stripping of the gas inside the peak may result. This occurs in around half the cases and prevents the formation of galaxies. Anisotropic outflows follow the path of least resistance, and thus travel preferentially into low-density regions, away from cosmological structures (filaments and pancakes) where galaxies form. As a result, the number of collisions is reduced, leading to the formation of a larger number of galaxies. Anisotropic outflows can significantly enrich low-density systems with metals. Conversely, the cross-pollution in metals of objects located in a common cosmological structure, like a filament, is significantly reduced. Highly anisotropic outflows can travel across cosmological voids and deposit metals in other, unrelated cosmological structures.Comment: 32 pages, 9 figures (2 color). Revised version accepted in Ap

Function Allocation for Humans and Automation in the Context of Team Dynamics

AbstractWithin Human Factors Engineering, a decision-making process called function allocation (FA) is used during the design life cycle of complex systems to distribute the system functions, typically identified through a functional requirements analysis, to all human and automated machine agents (or teammates) involved in controlling the system. Most FA methods make allocation decisions primarily by comparing the capabilities of humans and automation, and then by considering secondary factors such as cost, regulations, and the health and safety of workers. The primary analysis of the strengths and weaknesses of humans and machines, however, is almost always considered in terms of individual human or machine capabilities. Yet, FA is fundamentally about teamwork in that the goal of the FA decision-making process is to determine the optimal allocations of functions among agents. Given this framing of FA, and the increasing use of and sophistication of automation, there are two related social psychological issues that current FA methods need to address more thoroughly. First, many principles for effective human teamwork are not considered as central decision points or in the iterative hypothesis and testing phase in most FA methods, despite the fact that social factors have numerous positive and negative effects on individual and team capabilities. Second, social psychological factors affecting team performance can be difficult to translate to automated agents, and most FA methods currently do not account for this effect. The implications for these issues are discussed

Charge qubits based on ultra-thin topological insulator films

We study how to use the surface states in a Bi$_{2}$Se$_{3}$ topological insulator ultra-thin film that are affected by finite size effects for the purpose of quantum computing. We demonstrate that: (i) surface states under the finite size effect can effectively form a two-level system where their energy levels lie in between the bulk energy gap and a logic qubit can be constructed, (ii) the qubit can be initialized and manipulated using electric pulses of simple forms, (iii) two-qubit entanglement is achieved through a $\sqrt{\text{SWAP}}$ operation when the two qubits are in a parallel setup, and (iv) alternatively, a Floquet state can be exploited to construct a qubit and two Floquet qubits can be entangled through a Controlled-NOT operation. The Floquet qubit offers robustness to background noise since there is always an oscillating electric field applied, and the single qubit operations are controlled by amplitude modulation of the oscillating field, which is convenient experimentally.Comment: 12 pages, 9 figures, submitted to the journal Frontiers of Physic

Bridge Decomposition of Restriction Measures

Motivated by Kesten's bridge decomposition for two-dimensional self-avoiding walks in the upper half plane, we show that the conjectured scaling limit of the half-plane SAW, the SLE(8/3) process, also has an appropriately defined bridge decomposition. This continuum decomposition turns out to entirely be a consequence of the restriction property of SLE(8/3), and as a result can be generalized to the wider class of restriction measures. Specifically we show that the restriction hulls with index less than one can be decomposed into a Poisson Point Process of irreducible bridges in a way that is similar to Ito's excursion decomposition of a Brownian motion according to its zeros.Comment: 24 pages, 2 figures. Final version incorporates minor revisions suggested by the referee, to appear in Jour. Stat. Phy

Forecasting Particulate Matter Concentrations: Use of Unorganized Machines

Air pollution is an environmental issue studied worldwide, as it has serious impacts on human health. Therefore, forecasting its concentration is of great importance. Then, this study presents an analysis comprising the appliance of Unorganized Machines – Extreme Learning Machines (ELM) and Echo State Networks (ESN) aiming to predict particulate matter with aerodynamic diameter less than 2.5 m (PM2.5) and less than 10 m (PM10). The databases were from Kallio and Vallilla stations in Helsinki, Finland. The computational results showed that the ELM presented best results to PM2.5, while the ESN achieved the best performance to PM10

Indicadores biofísicos de sistemas agroflorestais.

Palestra

Gender difference and effect of pharmacotherapy: findings from a smoking cessation service

Background: Smoking cessation services are available in England to provide assistance to those wishing to quit smoking. Data from one such service were analysed in order to investigate differences in quit rate between males and females prescribed with different treatments. Methods: A logistic regression model was fitted to the data using the binary response of self-reported quit (failed attempt = 0, successful attempt = 1), validated by Carbon Monoxide (CO) monitoring, 4 weeks after commencing programme. Main effects fitted were: client gender; age; region; the type of advisory sessions; and pharmacotherapy, Nicotine Replacement Therapy (NRT) or Varenicline. A second model was fitted including all main effects plus two-way interactions except region. These models were repeated using 12-week self-reported quit as the outcome. Results: At 4 weeks, all main effects were statistically significant, with males more likely (odds ratio and 95 % CI, females v males = 0.88 [0.79–0.97]), older smokers more likely (adjusted odds ratios [OR] and 95 % confidence interval [CI] respectively for groups 20–29, 30–49, 50–69 and 70+ vs 12–19 age group: 1.79 [1.39–2.31], 2.12 [1.68–2.68], 2.30 [1.80–2. 92] and 2.47 [1.81–3.37] and for overall difference between groups, χ 2 (4) = 53.5, p < 0.001) and clients being treated with Varenicline more likely to have successfully quit than those on NRT (adjusted OR and 95 % CI for Varenicline vs NRT = 1.41 [1.21–1.64]). Statistically significant interactions were observed between (i) gender and type of counselling, and (ii) age and type of counselling. Similar results were seen in relation to main effects at 12 weeks except that type of counselling was non-significant. The only significant interaction at this stage was between gender and pharmacotherapy (adjusted OR and 95 % CI for females using Varenicline versus all other groups = 1.43 [1.06–1.94]). Conclusion: Gender and treatment options were identified as predictors of abstinence at both 4 and 12 weeks after quitting smoking. Furthermore, interactions were observed between gender and (i) type of counselling received (ii) pharmacotherapy. In particular, the quit rate in women at 12 weeks was significantly improved in conjunction with Varenicline use. These findings have implications for service delivery