Incorporating the Raft consensus protocol in containers managed by Kubernetes: an evaluation

Replication is a technique widely used to improve the reliability of applications. State machine replication is a special approach, where a set of computers are kept synchronised in the same state despite of failures that could occur in the system. The Raft algorithm can be used to implement a total order delivery protocol, delivering requests at the same order at all replicas, which is fundamental since in this approach all replicas must execute the same sequence of requests to present the same evolution in their states. Raft is easy to understand and implement, when compared to the Paxos algorithm. On the other hand, virtualisation can be seen as a technique that helps the development of reliable applications since it maintains each virtual machine (VM) isolated from the others. Virtualisation in data centres is changing from the traditional VMs to containers. In this context, this paper proposes KRaft, an incorporation of Raft in Kubernetes, a system that manages containers. After an evaluation of performance and resource consumption of KRaft, we found that it presents performance close to Raft executing on physical machines. Moreover, KRaft demands more network transmission while Raft executed in physical machines needs more processing power and memory.     

Hybrid methodology for precipitation estimation using Hydro-Estimator over Brazil

Rainfall measurement is a very important topic to society and for the understanding of the weather and climate, therefore needs to be calculated as accurately as possible. Counteracting the problem of the high temporal and spatial variability of precipitation, geostationary satellites sensors have been proved an excellent tool to this task, providing scans with high temporal resolution and detecting the growth and decay of rain cells. Using infra-red (IR) images obtained from the Geostationary Operational Environmental Satellites (GOES), the Hydro-Estimator (HYDRO) algorithm produces instantaneous precipitation estimates with 30 min temporal resolution and 4 km spatial resolution with a very low latency compared with other more sophisticated methodologies (i.e. passive microwave-based algorithms). However, the IR algorithm has some limitations to estimate precipitation on some cloud systems. In order to overcome this problem, the main objective of this study is to develop a light and fast algorithm, based on the histogram matching (HM) technique, to combine the superior sampling and low latency of the HYDRO IR product with more accurate active microwave-based products over Brazil. The adjusted HYDRO (AHYDRO) product was validated against Brazil rain gauge network for two years (2016–2017) and the performance was assessed by using standard statistical metrics and categorical indices. Results show that the HM technique is able to minimize the large variability and discrepancies among HYDRO and observed precipitation over Brazil. At same time, is able to generate a better bias performance while maintaining the same correlation levels before the adjustment.     

Why are most physicochemical parameters not useful in predicting the quality of sheep milk?

The impact of microbial growth on the physicochemical parameters of sheep milk was evaluated. The total bacterial counts (TBC) showed a lag phase of 4 h and µ‐max of 0.4 log/h. After 8.4 h, the TBC reached the limit established by European Community, pH had a reduction of 0.04, acidity had an increase in 0.04%, and no changes were observed in the ethanol stability. The milk became thermally unstable after 17 h (10⁹ cfu/mL), when the pH was 5.71, acidity was 0.36%, and ethanol stability was 21.3%. These results highlighted the extreme stability of sheep milk protein and that acidity may be the best physicochemical parameters to predict the quality of sheep milk.     

Experimental study of bubble formation in a glass-forming liquid doped with cerium oxide

This work aims to study the mechanisms of oxygen bubble formation coming from redox reaction of a polyvalent element incorporated in a glass melt. Borosilicate glass composition is selected for its use as a glass matrix for nuclear waste conditioning. Cerium is selected as a polyvalent element as it may be found in nuclear waste. The chosen material is characterized in terms of physical properties which influence bubble formation and growth. A postmortem optical microscope approach is used to observe bubbles in the investigated material after thermal treatment for varying temperatures (900°C-1100°C) and durations. To support the understanding of oxygen bubble formation, cerium speciation by X-ray absorption near-edge structure (XANES) and bubble gas composition are experimentally evaluated. In this article, we indicate how bubbles are formed in the investigated glass melt system. It is also demonstrated that the mechanisms that govern bubble evolution are fundamentally the same and that the plot's optimum points are strongly influenced by the temperature. These last statements are confirmed by considering some bubble features, such as bubble mean density and bubble mean diameter evolutions, and normalizing the experimental time using a characteristic residence time (t_η) obtaining thereafter a dimensionless time, which is a function of the glass melt properties obtained by the physical characterizations. The impact of temperature and time on bubble formation is described.     

Nanoemulsions of Acai Oil: Physicochemical Characterization for the Topical Delivery of Antifungal Drugs

Nanoemulsion-based acai oil was obtained by the phase inversion method using two nonionic surfactants, Ceteareth-20 (Brij™ CS20) and polyoxyethylene-hydrogenated castor oil (Croduret™ 50), with the concentration of each surfactant varying from 7 to 10 %. The formulation with 10 % Brij CS20 presented the best values for droplet size, zeta potential, and polydispersity index (PDI). Ketoconazole was incorporated into this formulation, with an encapsulation efficiency of 98.31 % and equally good zeta potential, droplet size, and PDI, and spherical shape when observed by transmission electron microscopy. Overall, nanoemulsions of acai oil proved to be a good vehicle for imidazole antifungals such as ketoconazole.