No-tillage and organic farming are important strategies to improve soil quality. This study aimed to quantify the effects of the tillage systems and organic management on total organic carbon (TOC), labile C (C L ), and biological indicators in an Acrisol in north-eastern Brazil. Five systems were studied: NV, native vegetation; NT/ORG, no-tillage plus organic fertiliser; NT/CHE, no-tillage plus chemical fertiliser; NT/CHE/ORG, no-tillage plus organic and chemical fertiliser; CT/CHE, conventional tillage plus chemical fertiliser. Soil samples were collected in the 0-0.10 and 0.10-0.20 m depths. TOC stocks were higher in NT/CHE/ORG (0-0.10 m, 14.0 Mg/ha; 0.10-0.20 m, 13.0 Mg/ha) and NT/ORG (0-0.10 m, 12.6 Mg/ha; 0.10-0.20 m, 11.6 Mg/ha) than in CT/CHE and NV systems. C L stocks were higher in NT/ORG (3.61 Mg/ha) at 0-0.10 m and in NT/ORG, NT/CHE, and NT/CHE/ORG at 0.10-0.20 m. At 0-0.10 m, microbial biomass C content was higher in the NT/CHE/ORG (190 mg/kg) and NT/ORG (155 mg/kg). Soil microbial respiration rate was similar in all systems. However, qCO 2 was higher in the NT/CHE and CT/CHE systems, suggesting a stress in the soil microbial biomass. No-tillage and organic management promoted positive changes in soil organic carbon and soil microbial properties and improved soil quality.

Teaching a programming language to a person who is deaf or hearing impaired (DHI) has, along with other challenges, the lack of signs to convey basic concepts in computing. This shortage of signs makes learning even harder for the DHI.The creation of signs from co-present discussions involving instructors, translators and the DHI can lead to regionalism, which might hinder their acceptance by members of other DHI communities throughout the country. A way to combat regionalism is through the asynchronous collaborative creation of signs, normally supported by web tools.But are the signs created through web discussions inferior in any way to those created via co-present discussions? This article presents a comparative study on the acceptance of signs created by both methods showing that acceptable and legitimate signs can also be produced using web discussions and the users can not distinguish from which method they come from.

Prostate cancer is one of the most common malignant tumors in males and it has become a major worldwide public health problem. This study characterizes the encapsulation of Nor-β-lapachone (NβL) in poly(D,L-lactide-co-glycolide) (PLGA) microcapsules and evaluates the cytotoxicity of the resulting drug-loaded system against metastatic prostate cancer cells. The microcapsules presented appropriate morphological features and the presence of drug molecules in the microcapsules was confirmed by different methods. Spherical microcapsules with a size range of 1.03˘0.46 µm were produced with an encapsulation efficiency of approximately 19%. Classical molecular dynamics calculations provided an estimate of the typical adsorption energies of NβL on PLGA. Finally, the cytotoxic activity of NβL against PC3M human prostate cancer cells was demonstrated to be significantly enhanced when delivered by PLGA microcapsules in comparison with the free drug.

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Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV positioning algorithm responsible for determining suitable positions for the UAVs, with the objective of a more balanced redistribution of traffic, to avoid saturated base stations and decrease the number of users without a connection. The tests performed with real data of user connections through base stations show that, in less restrictive network conditions, the algorithm to dynamically place the UAVs performs significantly better than in more restrictive conditions, reducing significantly the number of users without a connection. We also conclude that the accuracy of the prediction is a very important factor, not only in the reduction of users without a connection, but also on the number of UAVs deployed.