Abstract
Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.

Abstract

Abstract
Information Technology (IT) plays an increasingly important role for small and medium-sized enterprises. It has become fundamental for these companies to protect information and IT assets in relation to risks and threats that have grown in recent years. This study aims to understand the importance and structure of an information security policy, using a quantitative study that intends to identify the most important and least relevant elements of an information security policy document. The findings of this study reveal that the top three most important elements in the structure of a security policy are the asset management, security risk management and define the scope of the policy. On the other side, the three least relevant elements include the executive summary, contacts and manual inspection. Additionally, the study reveals that the importance given to each element of the security policy is slightly changed according to the sectors of activity. The elements that show the greatest variability are the review process, executive summary and penalties. On the other side, the purpose of the policy and the asset management present a stable importance for all sectors of activity.

Abstract
Most modern design suites include HLS tools that rise the design abstraction level and provide a fast and direct flow to programmable devices, getting rid of manually coding at the RTL. While HLS greatly reduces the design productivity gap, non-negligible problems arise. For instance, the co-simulation strategy may not provide trustworthy results due to the variable accuracy of simulation, especially when considering dynamic reconfiguration and access to system busses. This work proposes mechanisms aimed at improving the verification accuracy using a real device and a testing framework. One of the mechanisms is the inclusion of physical configuration macros (e.g., clock rate configuration macro) and test assertions based on physical parameters in the verification environment (e.g., timing assertions). In addition it is possible to change some of those parameters, such as clock speed rate, and check the behavior of a hardware component into an overclocking or underclocking scenario. Our on-board testing flow allows faster FPGA iterations to ensure the design intent and the hardware-design behavior match. This flow uses a real device to carry out the verification process and synthesizes only the DUT generating its partial bitstream in a few minutes. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract

Abstract
Phenological models for predicting the grapevine flowering were tested using phenological data of 15 grape varieties collected between 1990 and 2014 in Vinhos Verdes and Lisbon Portuguese wine regions. Three models were tested: Spring Warming (Growing Degree Days - GDD model), Spring Warming modified using a triangular function - GDD triangular and UniFORC model, which considers an exponential response curve to temperature. Model estimation was performed using data on two grape varieties (Loureiro and Fernao Pires), present in both regions. Three dates were tested for the beginning of heat unit accumulation (t(0)( )date): budburst, 1 January and 1 September. The best overall date was budburst. Furthermore, for each model parameter, an intermediate range of values common for the studied regions was estimated and further optimized to obtain one model that could he used for a diverse range of grape varieties in both wine regions. External validation was performed using an independent data set from 13 grape varieties (seven red and six white), different from the two used in the estimation step. The results showed a high coefficient of determination (R-2 : 0.59-0.89), low Root Mean Square Error (RMSE: 3-7 days) and Mean Absolute Deviation (MAD: 2-6 days) between predicted and observed values. The UniFORC model overall performed slightly better than the two GDD models, presenting higher R-2 (0.75) and lower RMSE (4.55) and MAD (3.60). The developed phenological models presented good accuracy when applied to several varieties in different regions and can be used as a predictor tool of flowering date in Portugal.