EVOLUTIONARY BIOLOGY IN BIODIVERSITY SCIENCE, CONSERVATION, AND POLICY: A CALL TO ACTION

Evolutionary biologists have long endeavored to document how many species exist on Earth, to understand the processes by which biodiversity waxes and wanes, to document and interpret spatial patterns of biodiversity, and to infer evolutionary relationships. Despite the great potential of this knowledge to improve biodiversity science, conservation, and policy, evolutionary biologists have generally devoted limited attention to these broader implications. Likewise, many workers in biodiversity science have underappreciated the fundamental relevance of evolutionary biology. The aim of this article is to summarize and illustrate some ways in which evolutionary biology is directly relevant We do so in the context of four broad areas: (1) discovering and documenting biodiversity, (2) understanding the causes of diversification, (3) evaluating evolutionary responses to human disturbances, and (4) implications for ecological communities, ecosystems, and humans We also introduce bioGENESIS, a new project within DIVERSITAS launched to explore the potential practical contributions of evolutionary biology In addition to fostering the integration of evolutionary thinking into biodiversity science, bioGENESIS provides practical recommendations to policy makers for incorporating evolutionary perspectives into biodiversity agendas and conservation. We solicit your involvement in developing innovative ways of using evolutionary biology to better comprehend and stem the loss of biodiversity.

Why Implementing History and Philosophy in School Science Education is a Challenge: An Analysis of Obstacles

Teaching and learning with history and philosophy of science (HPS) has been, and continues to be, supported by science educators. While science education standards documents in many countries also stress the importance of teaching and learning with HPS, the approach still suffers from ineffective implementation in school science teaching. In order to better understand this problem, an analysis of the obstacles of implementing HPS into classrooms was undertaken. The obstacles taken into account were structured in four groups: 1. culture of teaching physics, 2. teachers` skills, epistemological and didactical attitudes and beliefs, 3. institutional framework of science teaching, and 4. textbooks as fundamental didactical support. Implications for more effective implementation of HPS are presented, taking the social nature of educational systems into account.

Constructive alignment in Computer Engineering and Informatics departments at Dalarna University : An empirical investigation

Background: Constructive alignment (CA) is a pedagogical approach that emphasizes the alignment between the intended learning outcomes (ILOs), teaching and learning activities (TLAs) and assessment tasks (ATs) as well as creation of a teaching/learning environment where students will be able to actively create their knowledge. Objectives: This paper aims at investigating the extent of constructively-aligned courses in Computer Engineering and Informatics department at Dalarna University, Sweden. This study is based on empirical observations of teacher’s perceptions of implementation of CA in their courses. Methods: Ten teachers (5 from each department) were asked to fill a paper-based questionnaire, which included a number of questions related to issues of implementing CA in courses. Results: Responses to the items of the questionnaire were mixed. Teachers clearly state the ILOs in their courses and try to align the TLAs and ATs to the ILOs. Computer Engineering teachers do not explicitly communicate the ILOs to the students as compared to Informatics teachers. In addition, Computer Engineering teachers stated that their students are less active in learning activities as compared to Informatics teachers. When asked about their subjective ratings of teaching methods all teachers stated that their current teaching is teacher-centered but they try to shift the focus of activity from them to the students. Conclusions: From teachers’ perspectives, the courses are partially constructively-aligned. Their courses are “aligned”, i.e. ILOs, TLAs and ATs are aligned to each other but they are not “constructive” since, according to them, there was a low student engagement in learning activities, especially in Computer Engineering department.

Teamwork in academia: an empirical study

The Bologna Process introduced some changes in the curriculum of higher education institutions (HEIs) and defined that academic learning should consider the needs of the labour market. HEIs and employers agree that personal skills are the most important set of competence of graduates (Pavlin, Akkuyunlu, Kovacic, & Svetlik, 2009). The goals of this work were to explore how the work experienced by teams of students in HEIs might help them improve their personal skills, namely empirically explore the perception of teamwork and personality into two groups of students. The study was based on the theoretical model of Team Evolution and Maturation (TEAM, Fransen, 2012). The sample consisted of 99 students of the 3rd year of the degree (1st cycle) in Computer Science (49 students) and the 2nd year of the Bachelor's Degree (1st cycle) in Psychology (50 students), from the University of Madeira, Portugal. Areas of personality and team collaboration were evaluated with a Pre- and Post-test. Findings show that the perception of the teamwork collaboration of students in Computer Science and Psychology majors seems to be influenced by their scientific area, by gender, by the selection method of the time-organiser, the self-perceived personality of the time-organiser, the self perceived personality of the non-time-organiser, and the size of the team. It is expected that this data will contribute to further theoretical and practical reflection on the teamwork among college students and their performance in the labour market.

An Optimum-Path Forest framework for intrusion detection in computer networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chemometrics in fuel science: demonstration of the feasibility of chemometrics analyses applied to physicochemical parameters to screen solvent tracers in Brazilian commercial gasoline

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Application of differential scanning calorimetry in hair samples as a possible tool in Forensic Science

A calorimetria Exploratória Diferencial (DSC) foi utilizada para estudar o comportamento térmico de amostras de cabelo e verificar a possibilidade de identificar um indivíduo com base nas curvas DSC de um banco de dados. Amostras de cabelo de estudantes e funcionários do Instituto de Química de Araraquara UNESP, foram obtidas para construir um banco de dados. Procurou-se assim identificar de um indivíduo sob incógnita, utilizando-se a curva DSC deste banco de dados.

Implementation of filters for image pre-processing for leaf analyses in plantations

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper. © 2008 Springer-Verlag Berlin Heidelberg.

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

Automatic classification of enzyme family in protein annotation

Most of the tasks in genome annotation can be at least partially automated. Since this annotation is time-consuming, facilitating some parts of the process - thus freeing the specialist to carry out more valuable tasks - has been the motivation of many tools and annotation environments. In particular, annotation of protein function can benefit from knowledge about enzymatic processes. The use of sequence homology alone is not a good approach to derive this knowledge when there are only a few homologues of the sequence to be annotated. The alternative is to use motifs. This paper uses a symbolic machine learning approach to derive rules for the classification of enzymes according to the Enzyme Commission (EC). Our results show that, for the top class, the average global classification error is 3.13%. Our technique also produces a set of rules relating structural to functional information, which is important to understand the protein tridimensional structure and determine its biological function. © 2009 Springer Berlin Heidelberg.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

How bioinformatics enables livestock applied sciences in the genomic era

This review paper presents the three main approaches currently used in livestock genomic sciences where the bioinfomatics plays a critical role. They are named as Genomic Selection (GS), Genome Wide Association Study (GWAS) and Signatures of Selection (SS). The subsides for the construction of this article were generated in a current project (started in 2011), so called Zebu Genome Consortium (ZGC), which joins researchers from different institutions and countries, aiming to scientifically explore genomic information of Bos taurus indicus cattle breeds and deliver useful information to breeders and academic community, specially from the tropical regions of the world. © 2012 Springer-Verlag.

Boosting optimum-path forest clustering through harmony Search and its applications for intrusion detection in computer networks

In this paper we propose a nature-inspired approach that can boost the Optimum-Path Forest (OPF) clustering algorithm by optimizing its parameters in a discrete lattice. The experiments in two public datasets have shown that the proposed algorithm can achieve similar parameters' values compared to the exhaustive search. Although, the proposed technique is faster than the traditional one, being interesting for intrusion detection in large scale traffic networks. © 2012 IEEE.