Abstract
Purpose - The study aims to define a research agenda for creating resource-efficient supply chains (RESCs) by identifying and analysing their key characteristics as well as future research opportunities. Design/methodology/approach - We follow a systematic review method to analyse the literature and to understand RESC, taking a substantive theory approach. Our approach is grounded in a specific domain, the agri-food sector, because it is an intensive user of an extensive range of resources. Findings - The review shows that works of literature has looked at the use of resources primarily from the environmental impact perspective. There is a need to explore whether or not and how logistics/supply chain decisions will affect the overall configuration of future food supply chains in an era of resource scarcity and depletion and what the trade-offs will be. Research limitations/implications - The paper proposes an agenda for future research in the area of RESC. The framework proposed along with the key characteristics identified for RESC can be applied to other sectors. Practical implications - Our research should facilitate further understanding of the implications and trade-offs of supply chain decisions taken on the use of resources by supply chain managers. Originality/value - The paper explores the interaction between supply chains and natural resources and defines the key characteristics of RESC.

Abstract
A methodology based on Fourier transform infrared spectroscopy with attenuated total reflectance sampling technique, combined with multivariate analysis, was developed to monitor adulteration of extra virgin olive oil (EVOO) with peanut oil (PEO). Principal components regression (PCR), partial least squares regression (PLS-R), and linear discriminant analysis (LDA) allowed quantification of percentage of adulteration based on spectral data of 192 samples. Wavenumbers associated with the biochemical differences among several types of edible oils were investigated by principal component analysis. Two sets of frequencies were selected in order to establish a robust regression model. Set A consisted on the frequency regions from 600 to 1,800 cm-1 and from 2,750 to 3,050 cm-1. Set B comprised 17 discrete peak absorbance frequencies for which the communality value was higher than 0.6. Analysis of an external set of 25 samples allowed the validation and evaluation of the predictability of the models. When using a specific set of discrete peak absorbance frequencies, the R 2 coefficients for the prediction were 0.960 and 0.977, and the root mean square error (RMSE) were 1.49 and 1.05% V/V when using the PCR or PLS-R models, respectively. LDA was successful in the binary classification presence/absence of PEO in adulterated EVOO (with 5% V/V of less of PEO). LDA provided 92.3% correct classification for the calibration set and 88.3% correct classification when cross-validated. The lowest detectable concentration of PEO in EVOO was the lowest adulteration level studied, 0.5% V/V.

Abstract
This paper presents a management model developed to promote the sustainability of artisanal fisheries, considering socioeconomic and environmental dimensions. The management of artisanal fisheries faces many challenges, including the lack of appropriate tools to support policy makers and stakeholders in the decision-making process. The model presented in this study is based on system dynamics and allows the simulation of the behavior of the artisanal dredge fishery on the south coast of Portugal, including four main species and two fleets. Two scenarios were simulated to assess the impact of regulatory measures on the system sustainability: scenario 1 simulated a permanent reduction of fishing effort, returning an improvement of biologic and economic sustainability; scenario 2 simulated the closure of one species for a period of one year to allow its recovery. It was found that although the revenue of fisheries decreases in that year, the system is able to return to the average levels of revenue three years after the closure. The study aimed to guide decision makers in the selection of the most appropriate measures toward the preservation of marine ecosystems and socioeconomic stability of fishing communities. The developed system dynamics model, combining available data with knowledge of fisheries experts, proved to be a useful scientific tool to identify management policies and organizational structures leading to greater success. This technique can be applied to the study of other fishery systems worldwide.

Abstract
The objective of this study is to explore the effectiveness of three digital shopping platforms (Plain Interactive, Marker-based Augmented Reality and Markerless Augmented Reality), on the impressions and purchase intentions of consumers. The study is mainly interested in analysing whether intelligent shopping platforms with AR elements provide any added advantage to an advertised product in the form of favourable attitude or a stronger purchase impulse. During the tests with the three shopping platforms, quantitative data was collected via computerised questionnaire. High and Low class users were statistically extracted, corresponding to the high or low probability to buy or recommend the advertised brand. The results show that Markerless AR system clearly outperforms the Marker-based AR and the Plain Interactive in terms of positive attitude from the users. The second better performing system is the Marker-based AR, which closely follows the Markerless AR, while the Plain Interactive system obtains least approval.

Abstract
The distribution systems (DS) reconfiguration problem is formulated in this paper as a multi-objective mixed-integer linear programming (MILP) multi-period problem, enforcing that the obtained topology is radial in order to exploit several advantages those configurations offer. The effects of distributed generation (DG) and energy storage systems (ESS) are also investigated. To address the multi-objective problem, an improved implementation of the e-constraint method (AUGMECON-2) is used, providing an adequate representation of the Pareto set. The objective functions considered stand for the minimization of active power losses and the minimization of switching operations. The proposed methodology is tested using a real system based on the S. Miguel Island, Azores, Portugal. The potential uses of cloud-based engineering systems, both in terms of exploiting the enhanced decentralized computational opportunities they offer and of utilizing them in order to achieve communication and coordination between several entities that are engaged in DS, are thoroughly discussed.

Abstract
Development time and accuracy are measures that need to be taken into account when devising device models for a new technology. If complex circuits need to be designed immediately, then it is very important to reduce the time taken to realize the model. Solely based on data measurements, artificial neural networks (ANNs) modeling methodologies are capable of capturing small and large signal behavior of the transistor, with good accuracy, thus becoming excellent alternatives to more strenuous modeling approaches, such as physical and semi-empirical. This paper then addresses a static modeling methodology for amorphous Gallium-Indium-Zinc-Oxide - Thin Film Transistor (a-GIZO TFT), with different ANNs, namely: multilayer perceptron (MLP), radial basis functions (RBF) and least squares-support vector machine (LS-SVM). The modeling performance is validated by comparing the model outcome with measured data extracted from a real device. In case of a single transistor modeling and under the same training conditions, all the ANN approaches revealed a very good level of accuracy for large- and small-signal parameters (g(m) and g(d)), both in linear and saturation regions. However, in comparison to RBF and LS-SVM, the MLP achieves a very acceptable degree of accuracy with lesser complexity. The impact on simulation time is strongly related with model complexity, revealing that MLP is the most suitable approach for circuit simulations among the three ANNs. Accordingly, MLP is then extended for multiple TFTs with different aspect ratios and the network implemented in Verilog-A to be used with electric simulators. Further, a simple circuit (inverter) is simulated from the developed model and then the simulation outcome is validated with the fabricated circuit response.