Identidade visual da Biblioteca da Embrapa Florestas: uma proposta de sinalização.

Organizado por Patricia Póvoa de Mattos, Celso Garcia Auer, Rejane Stumpf Sberze, Katia Regina Pichelli e Paulo César Botosso

Consensus Needs Broadcast in Noiseless Models but can be Exponentially Easier in the Presence of Noise

Consensus and Broadcast are two fundamental problems in distributed computing, whose solutions have several applications. Intuitively, Consensus should be no harder than Broadcast, and this can be rigorously established in several models. Can Consensus be easier than Broadcast? In models that allow noiseless communication, we prove a reduction of (a suitable variant of) Broadcast to binary Consensus, that preserves the communication model and all complexity parameters such as randomness, number of rounds, communication per round, etc., while there is a loss in the success probability of the protocol. Using this reduction, we get, among other applications, the first logarithmic lower bound on the number of rounds needed to achieve Consensus in the uniform GOSSIP model on the complete graph. The lower bound is tight and, in this model, Consensus and Broadcast are equivalent. We then turn to distributed models with noisy communication channels that have been studied in the context of some bio-inspired systems. In such models, only one noisy bit is exchanged when a communication channel is established between two nodes, and so one cannot easily simulate a noiseless protocol by using error-correcting codes. An $\Omega(\epsilon^{-2} n)$ lower bound on the number of rounds needed for Broadcast is proved by Boczkowski et al. [PLOS Comp. Bio. 2018] in one such model (noisy uniform PULL, where $\epsilon$ is a parameter that measures the amount of noise). In such model, we prove a new $\Theta(\epsilon^{-2} n \log n)$ bound for Broadcast and a $\Theta(\epsilon^{-2} \log n)$ bound for binary Consensus, thus establishing an exponential gap between the number of rounds necessary for Consensus versus Broadcast

Deep Chandra Observations of HCG 16 - I. Active Nuclei, Star formation and Galactic Winds

We present new, deep Chandra X-ray and Giant Metrewave Radio Telescope 610~MHz observations of the spiral-galaxy-rich compact group HCG 16, which we use to examine nuclear activity, star formation and the high luminosity X-ray binary populations in the major galaxies. We confirm the presence of obscured active nuclei in NGC 833 and NGC 835, and identify a previously unrecognized nuclear source in NGC 838. All three nuclei are variable on timescales of months to years, and for NGC 833 and NGC 835 this is most likely caused by changes in accretion rate. The deep Chandra observations allow us to detect for the first time an Fe-K$\alpha$ emission line in the spectrum of the Seyfert 2 nucleus of NGC 835. We find that NGC 838 and NGC 839 are both starburst-dominated systems, with only weak nuclear activity, in agreement with previous optical studies. We estimate the star formation rates in the two galaxies from their X-ray and radio emission, and compare these results with estimates from the infra-red and ultra-violet bands to confirm that star formation in both galaxies is probably declining after galaxy-wide starbursts were triggered ~400-500 Myr ago. We examine the physical properties of their galactic superwinds, and find that both have temperatures of ~0.8 keV. We also examine the X-ray and radio properties of NGC 848, the fifth largest galaxy in the group, and show that it is dominated by emission from its starburst.Comment: 18 pages, 11 figures, 11 tables, accepted for publication in ApJ; updated references and fixed typos identified at proof stag

Resultados do ensaio nacional de sorgo granífero - 1975/76 e 1976/77.

Sorgo granifero; Variedade; Sorghum bicolor; Varieties.bitstream/item/43238/1/Bol-tec-1.pd

An IoT Measurement System Based on LoRaWAN for Additive Manufacturing

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible

Elicitation and accumulation of stilbene phytoalexins in grapevine berries infected by Botrytis cinerea

At three developmental stages berries of field-grown Castor (interspecific crossing) and Huxelrebe (V. vinifera L. crossing) were in vitro inoculated with two strains of Botrytis cinerea Pers. to investigate the response of berries to fungal infection With respect to the time course of phytoalexin (trans-resveratrol, ε-viniferin and pterostilbene) accumulation and Visual disease symptoms. In infected berries the amounts of ε-viniferin dominated over pterostilbene. The stilbene phytoalexin content decreased during berry development and sugar accumulation. Grape varieties reacted differently to B. cinerea strains with regard to stilbene response and Visual symptoms. Mechanical damage of the berry skin induced uninfected berries to synthesize low amounts of phytoalexins. It can be assumed that after extraction and degradation ε-viniferin of mature berries is a source of resveratrol in wine

Characterizing web pornography consumption from passive measurements

Web pornography represents a large fraction of the Internet traffic, with thousands of websites and millions of users. Studying web pornography consumption allows understanding human behaviors and it is crucial for medical and psychological research. However, given the lack of public data, these works typically build on surveys, limited by different factors, e.g. unreliable answers that volunteers may (involuntarily) provide. In this work, we collect anonymized accesses to pornography websites using HTTP-level passive traces. Our dataset includes about $15\,000$ broadband subscribers over a period of 3 years. We use it to provide quantitative information about the interactions of users with pornographic websites, focusing on time and frequency of use, habits, and trends. We distribute our anonymized dataset to the community to ease reproducibility and allow further studies.Comment: Passive and Active Measurements Conference 2019 (PAM 2019). 14 pages, 7 figure

Fast Distributed Approximation for Max-Cut

Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their neighbors according to the underlying graph, known as the $\mathcal{LOCAL}$ or $\mathcal{CONGEST}$ models. We amend this by obtaining almost optimal algorithms for Max-Cut on a wide class of graphs in these models. In particular, for any $\epsilon > 0$, we develop randomized approximation algorithms achieving a ratio of $(1-\epsilon)$ to the optimum for Max-Cut on bipartite graphs in the $\mathcal{CONGEST}$ model, and on general graphs in the $\mathcal{LOCAL}$ model. We further present efficient deterministic algorithms, including a $1/3$-approximation for Max-Dicut in our models, thus improving the best known (randomized) ratio of $1/4$. Our algorithms make non-trivial use of the greedy approach of Buchbinder et al. (SIAM Journal on Computing, 2015) for maximizing an unconstrained (non-monotone) submodular function, which may be of independent interest

Migration, family history and pension: the second release of the SHARE Job Episodes Panel

Data about working life histories collected in the third wave of the SHARE survey, called SHARELIFE, were organized into a retrospective panel as described in Brugiavini, Cavapozzi, Pasini, Trevisan (2013). We now enrich such a publicly available dataset adding information on migration histories, fertility histories and marriage/cohabitation histories. Based on this information, we are able to link individual data to institutional features of pensions systems SHARE respondents were exposed to in each year of their working life. We add to the retrospective panel nine variables accounting for statutory retirement age, early retirement age and benefit reduction, contribution rate by the employer and the employee during working life, minimum and maximum pension benefit entitlements