Abstract
Guerrilla marketing is an innovative approach to communicate with customers and to capture their attention essentially due to its inherent creativity, unconventional media, and low cost. Despite the interesting contributions in the literature on this topic, most of what is known about guerrilla marketing is confined to its use and impact on consumers. This study aims to fill a gap identified in the guerrilla marketing literature by conducting an exploratory research study on the propensity of performing guerrilla marketing campaigns in a Business-to-Business (B2B) context. The research objectives of this paper are (i) identifying the perceptions of B2B managers on guerrilla marketing campaigns and (ii) exploring determinants of the adoption of guerrilla marketing campaigns targeted at corporate customers.We present the results of a qualitative research study comprising 12 semi-structured interviews with managers of different business areas. A content analysis was performed using Nvivo software.Participants in this study demonstrated that B2B managers recognize and value the advantages associated with guerrilla communication, which is in many instances seen as useful and viable for the B2B sector. The propensity for adoption is dependent on internal factors such as corporate culture, managers’ and collaborators’ profiles, risk-proneness, market share, and product innovativeness, but also on the sector’s usual practices of innovation and communication. Guerrilla marketing campaigns are more appropriate for attracting new B2B customers and need to be carefully adapted to the targets' profiles and preferences.

Abstract
It is reported a new optical sensing system, based on long period fiber gratings (LPFGs) coated with cuprous oxide (Cu2O), for the quantification of ethanol concentration in ethanol-gasoline mixtures. The detection principle is based on the spectral features dependence of the Cu2O coated LPFGs on the refractive index of the surrounding medium. The chemical constitution of the ethanol-gasoline samples was obtained by gas chromatography mass spectrometry (GC) and GC thermal conductivity detection. Two different modes of operation are presented, wavelength shift and optical power shift mode of operation, with good linear relations between ethanol concentration and the corresponding spectral features of the LPFGs, R-2 = 0.999 and 0.996, respectively. In the range of ethanol concentration up to 30% v/v, the sensitivities were 0.76 +/- 0.01 nm/% v/v and 0.125 +/- 0.003 dB/% v/v with resolutions of 0.21% v/v and 0.73% v/v and limits of detection of 1.63% v/v and 2.10% v/v, for the for the same operation modes, respectively.

Abstract
There are many man-made structures near the ocean, in the so called splash zone. These structures are submitted to corrosion and need to be inspected periodically, which is difficult to be performed by humans. Therefore, automated solutions should be devised, able to withstand the conditions found there. Given that some animals live in this environment, the authors propose the development of a biological inspired robot for achieving such inspection tasks. With this purpose, a biomechanical study of the spider crab was developed, focusing on the anatomy and locomotion of this animal, using the Matlab/Simulink SimMechanics toolbox. © 2018 by World Scientific Publishing Co. Pte. Ltd.

Abstract
Microgrid (MG) is a relatively new concept for the integration of distributed generation (DG) along with the loads in a distribution system. Islanded microgrid can be considered as a weak grid that has less inertia compared with the conventional power system. This reality makes the microgrid vulnerable to contingencies. Towards a flexible, safe and secure operation of an islanded MG, researchers have introduced a hierarchical control structure comprising tertiary, secondary and primary control. The primary control plays an important role in maintaining the voltage and frequency stability by sharing the loads among the DGs. This paper reviews and categorizes various primary control methods that have been introduced to control the voltage and frequency of inverter-based microgrids. Moreover, the reviewed methods in terms of their potential advantages and disadvantages are compared. Finally, the future trends are presented.

Abstract
In wireless networking R&D we typically depend on experimentation to further evaluate a solution, as simulation is inherently a simplification of the real-world. However, experimentation is limited in aspects where simulation excels, such as repeatability and reproducibility. Real wireless experiments are hardly repeatable. Given the same input they can produce very different output results, since wireless communications are influenced by external random phenomena such as noise, interference, and multipath. Real experiments are also difficult to reproduce due to testbed operational constraints and availability. We have previously proposed the Trace-based Simulation (TS) approach, which uses the TraceBasedPropagationLossModel to successfully reproduce past experiments. Yet, in its current version, the TraceBasedPropagationLossModel only supports point-to-point scenarios. In this paper, we introduce a new version of the model that supports Multiple Access wireless scenarios. To validate the new version of the model, the network throughput was measured in a laboratory testbed. The experimental results were then compared to the network throughput achieved using the ns-3 trace-based simulation and a pure ns-3 simulation, confirming the TS approach is valid for multiple access scenarios too.

Abstract
Software developers are more and more eager to understand their code's energy performance. However, even with such knowledge it is difficult to know how to improve the code. Indeed, little tool support exists to understand the energy consumption profile of a software system and to eventually (automatically) improve its code. In this paper we present a tool termed jStanley which automatically finds collections in Java programs that can be replaced by others with a positive impact on the energy consumption as well as on the execution time. In seconds, developers obtain information about energy-eager collection usage. jStanley will further suggest alternative collections to improve the code, making it use less time, energy, or a combination of both. The preliminary evaluation we ran using jStanley shows energy gains between 2% and 17%, and a reduction in execution time between 2% and 13%. A video can be seen at https://greensoftwarelab.github.io/jStanley. © 2018 Association for Computing Machinery.