GNSS occultation sounding for climate monitoring

Considerable efforts are currently invested into the setup of a Global Climate Observing System (GCOS) for monitoring climate change over the coming decades, which is of high relevance given concerns on increasing human influences. A promising potential contribution to the GCOS is a suite of spaceborne Global Navigation Satellite System (GNSS) occultation sensors for global long-term monitoring of atmospheric change in temperature and other variables with high vertical resolution and accuracy. Besides the great importance with respect to climate change, the provision of high quality data is essential for the improvement of numerical weather prediction and for reanalysis efforts. We review the significance of GNSS radio occultation sounding in the climate observations context. In order to investigate the climate change detection capability of GNSS occultation sensors, we are currently performing an end-to-end GNSS occultation observing system simulation experiment over the 25-year period 2001 to 2025. We report on this integrated analysis, which involves in a realistic manner all aspects from modeling the atmosphere via generating a significant set of stimulated measurements to an objective statistical analysis and assessment of 2001–2025 temporal trends.

Options for support to agriculture and food security under climate change

Agriculture and food security are key sectors for intervention under climate change. Agricultural production is highly vulnerable even to 2C (low-end) predictions for global mean temperatures in 2100, with major implications for rural poverty and for both rural and urban food security. Agriculture also presents untapped opportunities for mitigation, given the large land area under crops and rangeland, and the additional mitigation potential of aquaculture. This paper presents a summary of current knowledge on options to support farmers, particularly smallholder farmers, in achieving food security through agriculture under climate change. Actions towards adaptation fall into two broad overlapping areas: (1) accelerated adaptation to progressive climate change over decadal time scales, for example integrated packages of technology, agronomy and policy options for farmers and food systems, and (2) better management of agricultural risks associated with increasing climate variability and extreme events, for example improved climate information services and safety nets. Maximization of agriculture’s mitigation potential will require investments in technological innovation and agricultural intensification linked to increased efficiency of inputs, and creation of incentives and monitoring systems that are inclusive of smallholder farmers. Food systems faced with climate change need urgent, broad-based action in spite of uncertainties.

Children as caregivers

Caregiving is usually associated with adults’ responsibilities. Official statistics and research have demonstrated, however, that many children and young people in the global North and South have substantial, regular caring responsibilities for family members with chronic illnesses, impairments or other care needs. This chapter conceptualises children’s roles as ‘caregivers’ and the care work they do. It then analyses the available evidence on outcomes of children’s caregiving and the factors and processes influencing their involvement. While research reveals that caregiving may have positive as well as negative outcomes for children’s well-being, formal and informal safety nets are needed, especially in resource-limited settings, to alleviate children’s care work. Children’s and families’ experiences suggest that social protection measures and support for those being cared for as well as those providing care would help to ensure that caregiving does not have long-term negative impacts on children’s personal development, education, health, family relations, peer interactions, social participation, employment opportunities and socially expected transitions to adulthood.

Modelling capability and affordance as properties of human/machine resource systems

Understanding how and why the capability of one set of business resources, its structural arrangements and mechanisms compared to another works can provide competitive advantage in terms of new business processes and product and service development. However, most business models of capability are descriptive and lack formal modelling language to qualitatively and quantifiably compare capabilities, Gibson’s theory of affordance, the potential for action, provides a formal basis for a more robust and quantitative model, but most formal affordance models are complex and abstract and lack support for real-world applications. We aim to understand the ‘how’ and ‘why’ of business capability, by developing a quantitative and qualitative model that underpins earlier work on Capability-Affordance Modelling – CAM. This paper integrates an affordance based capability model and the formalism of Coloured Petri Nets to develop a simulation model. Using the model, we show how capability depends on the space time path of interacting resources, the mechanism of transition and specific critical affordance factors relating to the values of the variables for resources, people and physical objects. We show how the model can identify the capabilities of resources to enable the capability to inject a drug and anaesthetise a patient.

Behaviour models clarify definitions of affordance and capability

There is ongoing work on conceptual modelling of such busi- ness notions as Affordance and Capability. We have found that such business notions as Affordance and Capability are constructively defned using elements and properties of exe- cutable behaviour models. In this paper, we clarify the def- initions of Affordance and Capability using Coloured Petri Nets and Protocol models.The illustrating case is the process of drug injection. We show that different behaviour modelling techniques provide different precision for definition of Affordance and Capability and clarify the conceptual models of these notions. We generalise that the behaviour models can be used to improve the precision of conceptualization.

A powder neutron diffraction study of the metallic ferromagnet Co3Sn2S2

Variable-temperature powder neutron diffraction data reveal that Co3Sn2S2 crystallizes in the shandite structure (space group R (3) over barm, a = 5.36855(3)angstrom, c = 13.1903(1) angstrom at 300 K). The structural relationship between Co3Sn2S2 and the intermetallic compound CoSn, both of which contain Kagome nets of cobalt atoms, is discussed. Resistivity and Seebeck coefficient measurements for Co3Sn2S2 are consistent with metallic behaviour. Magnetic susceptibility measurements indicate that Co3Sn2S2 orders ferromagnetically at 180(10) K, with a saturation moment of 0.29 mu(B) per cobalt atom at 5 K. The onset of magnetic ordering is accompanied by marked anomalies in the electrical transport properties. (c) 2008 Elsevier Masson SAS. All rights reserve

Bathymetric distribution of the shrimp Rimapenaeus constrictus (Stimpson, 1874) (Decapoda, Penaeidae) in two locations off the southeastern Brazilian coast

The distribution of benthic organisms is directly or indirectly associated with the physical and chemical properties of the water and sediment. This study analysed the spatial and temporal distribution of Rimapenaeus constrictus in unconsolidated sublittoral sediments of two areas off the northern coast of the state of Sao Paulo, Brazil. We also analysed the association of environmental factors with the occurrence of this species. Shrimp were collected monthly from July 2001 to June 2003, with a fishing boat equipped with two double-rig nets, in the regions of Ubatuba (UBA) and Caraguatatuba (CA). The collections were made during the day, along five transects with mean depths of 5, 10, 15, 20, 25, 30, and 35 m. We obtained a total of 5478 individuals, 3403 (UBA = 2025 and CA = 1378) during the first year, and 2075 (UBA = 875 and CA = 1200) during the second year. Significant differences in abundance were observed in relation to depth, season of the year, and also in the interaction between region and depth. Higher abundances occurred in fall and winter, independently of the sampling year. The largest numbers of shrimp were caught on the 20-m transect in UBA and the 25-m transect in CA. It is concluded that the distribution pattern of this species is closely related to environmental factors, and the temperature of the bottom water and the sediment texture were the most significant variables affecting the distribution.

Edge effects as the principal cause of area effects on birds in fragmented secondary forest

Bird communities in tropical forests are strongly affected by both patch area and habitat edges. The fact that both effects are intrinsically confounded in space raises questions about how these two widely reported ecological patterns interact, and whether they are independent or simply different spatial manifestations of the same phenomenon. Moreover, do small patches of secondary forest, in landscapes where the most sensitive species have gone locally extinct, exhibit similar patterns to those previously observed in fragmented and continuous primary forests? We addressed these questions by testing edge-related differences in vegetation structure and bird community composition at 31 sites in fragmented and continuous landscapes in the imperilled Atlantic forest of Brazil. Over a two-year period, birds were captured with mist nets to a standardized effort of 680 net-hours at each site (similar to 22 000 net-hours resulting in 3381 captures from 114 species). We found that the bird community in patches of secondary forest was degraded in species composition compared to primary continuous forest, but still exhibited a strong response to edge effects. In fragmented secondary forests, edge and area effects also interacted, such that the magnitude of edge to interior differences on bird community composition declined markedly with patch size. The change in bird species composition between forest interiors and edges was similar to the change in community composition between large and small patches (because species had congruent responses to edge and area), but after controlling for edge effects community composition was no longer affected by patch area. Our results show that although secondary forests hold an impoverished bird community, ecological patterns such as area and edge effects are similar to those reported for primary forests. Our data provide further evidence that edge effects are the main drivers of area effects in fragmented landscapes.

Behavioural and morphological observations of the Collared Crescentchest (Melanopareia torquata) in a Cerrado area of south-eastern Brazil

The Collared Crescentchest (Melanopareia torquata) is endemic to the Cerrado Biome, and distributed mainly in Brazil, but extending to Bolivia and Paraguay. Although considered of least concern globally, it is threatened in the state of Sao Paulo in south-eastern Brazil. In this study we examined the morphology and some aspects of behaviour of the Collared Crescentchest. Birds were captured with mist-nets using playback in September-December 2006 and October-November 2007. For each captured bird, we took a range of morphological measurements, looked for brood-patches and moult, and took a blood sample for genetic determination of sex. Of the 35 individuals captured, only five were female, probably as a result of behavioural differences between sexes, with males apparently responding more readily to the playback. Furthermore, birds with white dorsal patches exhibited more aggression or risk taking behaviour than birds without patches. However, there was no sexual dimorphism in any of the morphological or colour traits measured ( although the female sample was small). Brood-patches were present mainly in October and November, but we did not detect any cloacal protuberance. Among the four species that comprise the family Melanopareiidae, this is the first record of brood-patches in males.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Elementary Petri net inside RFID distributed database (PNRD)

Usually, a Petri net is applied as an RFID model tool. This paper, otherwise, presents another approach to the Petri net concerning RFID systems. This approach, called elementary Petri net inside an RFID distributed database, or PNRD, is the first step to improve RFID and control systems integration, based on a formal data structure to identify and update the product state in real-time process execution, allowing automatic discovery of unexpected events during tag data capture. There are two main features in this approach: to use RFID tags as the object process expected database and last product state identification; and to apply Petri net analysis to automatically update the last product state registry during reader data capture. RFID reader data capture can be viewed, in Petri nets, as a direct analysis of locality for a specific transition that holds in a specific workflow. Following this direction, RFID readers storage Petri net control vector list related to each tag id is expected to be perceived. This paper presents PNRD cornerstones and a PNRD implementation example in software called DEMIS Distributed Environment in Manufacturing Information Systems.

A neural networks study of quinone compounds with trypanocidal activity

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.

Essays on competition and returns of inside money

In an early paper, Cavalcanti and Wallace (2001) showed, using a computable version of Cavalcanti-Wallace model (CW-1999), that optimal regulation induces banks to pay interests, instead of contracting the money supply in an inside money allocation. Here, we generalize CW in two fashions, assuming inside money allocations, so that banks are supposed to issue money as they find a potential producer wishing to produce. The first generalization allows for seasonality due to real shocks on preferences with persistence and for monetary policy improvement. We found an asymmetric path for interest rates when constraints matter, even when shocks are independent. The second generalization allows for bank competition, in the sense that banks can choose between two different banking nets. We proof the existence of simple stable and unstable equilibria and also verify the existence of multiple equilibria.

À beira de um ataque de nervos: um dia na vida de executivos em São Paulo

Ainda que existam pesquisas sobre as funções dos executivos desde 1938 e, ainda que estes trabalhos já tenham desmistificado as atividades cotidianas destes profissionais, o mundo organizacional insiste em atribuir uma aura cheia de glamour ao trabalho de altos executivos. O número de pesquisas acadêmicas realizadas sobre este tema nos anos 80 e 90 não foi muito elevado, mas os recentes escândalos financeiros e as mudanças radicais nas empresas, fizeram ressurgir o interesse sobre o trabalho destes profissionais Este trabalho tem por objetivo mostrar como vivem e trabalham altos executivos em São Paulo, a partir de observação participante de um dia de trabalho de 10 altos executivos. Este relatório foi organizado da seguinte forma: na primeira parte apresenta-se uma revisão dos principais estudos sobre as funções dos executivos; na segunda parte, o trabalho de campo: o acompanhamento, a observação e o registro das atividades realizadas por estes executivos durante um dia típico de trabalho bem como as respostas obtidas a partir de entrevista semi-estruturada sobre aspectos do uso do tempo, funções e vida familiar dos participantes desta amostra, entrevista esta que foi conduzida ao final do acompanhamento do dia de trabalho. Na terceira parte, são discutidos os dados obtidos: ainda que a vida destas pessoas esteja absolutamente centrada em atividades de trabalho, não é possível dizer que elas estejam à beira de um ataque de nervos. Como estão no topo da carreira, seu trabalho consiste na cobrança dos resultados dos funcionários que estão sob seu comando e na construção de redes de relacionamentos que facilitam e ajudam a consolidar e a manter sua posição. Também foi possível observar que os executivos de empresas brasileiras dispõem de maior autonomia no estabelecimento de políticas e tomadas de decisão em comparação com executivos de empresas multinacionais. Além disso, apesar das supostas alterações decorrentes da globalização, nossos resultados não mostram diferenças significativas em relação a trabalhos realizados há mais de 50 anos.