Abstract
This paper presents an optimization framework to determine the optimal operating points of combined heat and power (CHP) units with nonlinear, nonconvex feasible operating region (FOR). The mentioned problem is the economic dispatch (ED) of heat-only units, thermal units, and CHP units. Also, the electric units are of thermal technology while their valve-point impact is taken into consideration. Also, the heat power curve of heat-only units is nonlinear. It is noted that the FOR of CHP units has been defined both as convex and nonconvex regions. For those with nonconvex characteristic, a method is proposed to convert it into a convex characteristic. Accordingly, a separate binary variable must be defined to determine the optimal operating point in each convex region. Thus, the presented problem in this paper is of mixed-integer nonlinear programming (MINLP) type modeled in General Algebraic Modeling System (GAMS) software. In this respect, different case studies have been presented to assess the optimality, feasibility, and the flexibility of the model. It is noteworthy that the valve-point effect of thermal units and different FORs of CHP units as well as the electrical power losses have been considered. © 2018 John Wiley & Sons, Ltd.

Abstract
This paper describes the results of a qualitative study to identify the key management initiatives in a successful university-industry (UI) collaborative funded program between the University of Minho (UMinho) and Bosch Car Multimedia Portugal (Bosch), named IC-HMI. The IC-HMI program embraced an overall investment of 54.7 M(sic) and involved around 500 people throughout the Program's duration (2015-2018). While the literature provides some advice on managing programs and projects, the specific context of UI R&D collaboration is being scarcely reported, demanding a strong research effort to produce effective guidelines. The IC-HMI is considered a successful program for several reasons, as evidenced by the decision of UMinho and Bosch partners to develop a subsequent R&D collaborative program from 2018 to 2021, doubling its investment. The success attained with the IC-HMI program could be somehow explained by key management initiatives adopted, such as the: creation of Program and Project Management Office, definition and communication of a Governance Model, creation of Project Charters, promotion of Alignment Stakeholders Workshops, Project Progress Meetings and creation of Project Transition Plans, among other key initiatives reported in this paper. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the CENTERIS -International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies.

Abstract
The lack of physical activity and poor nutrition triggers various diseases, among them is diabetes. In this context, several researches seek ways that can mitigate these diseases to provide a better quality of life for people. Therefore, the present work aims to analyze the possible inhibitors of the enzyme Dipeptidil Peptidase 4 that hypotheses will be stipulated for the creation of new drugs through molecular docking techniques, that is, a computational simulation of combinations of drugs of the family of gliptins with other antidiabetics (metformin, glyburide and cucurbitacin). Among the results, it was observed that the antidiabetic cucurbitacin combined with the gliptines obtained greater energy during the process.

Abstract
This study presents innovative analysis at the time, frequency and phase domain for lower limb joint angular coordination assessment at sagittal plane on human vertical countermovement (CM), comparing long CM on countermovement jump (CMJ) and short CM on drop jump (DJ) from 40 cm step with squat jump (SJ) in the absence of CM. Lower limb CM and muscle stretch-shortening cycle has been pointed as playing a key role on human gait efficiency as well as on run and jump performance with an open issue on objective and quantitative measures for lower limb joint angle coordination assessment at different CM in comparison with no CM condition. Case study is considered from subject specific with 20 years old, 84 kg of body mass and 1.84 m height, selected according to best performance criteria of maximum vertical jump height during CMJ, DJ and SJ from a small sample of n = 6 sports and physical education degree students with (21.5 ± 1.4) years old, (76.7 ± 9.3) kg mass and (1.79 ± 0.06) m height, with no previous injuries, specific sport abilities or training. Calibrated image system with two digital video cameras JVC GR-VL9800 operating at 100 Hz and direct linear transformation (DLT-11) was used along with Simi Motion System and Dempster adapted model with 14 segments to track 3D coordinates of joint marks and obtain joint angles, angular velocities and accelerations at sagittal plane by inverse kinematics. Entire signal analysis was implemented on complementary time, frequency and phase domains for lower limb joint angle coordination assessment at sagittal plane on human vertical jump for comparison of long, short and without CM condition. Comprehensive signal analysis allowed detection of distinct coordination at CMJ from DJ and SJ as well from untrained tested subjects to those reported on trained subjects namely with lower coordination at untrained subjects associated to inaptitude to potentiate short CM and thus presenting lower DJ performance than trained subjects. © Springer Nature Switzerland AG 2019.

Abstract
The prevalence and availability of cloud infrastructures has made them the de facto solution for storing and archiving data, both for organizations and individual users. Nonetheless, the cloud's wide spread adoption is still hindered by dependability and security concerns, particularly in applications with large data collections where efficient search and retrieval services are also major requirements. This leads to an increased tension between security, efficiency, and search expressiveness, which current state of the art solutions try to balance through complex cryptographic protocols that tradeoff efficiency and expressiveness for near optimal security. In this paper we tackle this tension by proposing BISEN, a new provably-secure boolean searchable symmetric encryption scheme that improves these three complementary dimensions by exploring the design space of isolation guarantees offered by novel commodity hardware such as Intel SGX, abstracted as Isolated Execution Environments (IEEs). BISEN is the first scheme to enable highly expressive and arbitrarily complex boolean queries, with minimal information leakage regarding performed queries and accessed data, and verifiability regarding fully malicious adversaries. Furthermore, by exploiting trusted hardware and the IEE abstraction, BISEN reduces communication costs between the client and the cloud, boosting query execution performance. Experimental validation and comparison with the state of art shows that BISEN provides better performance with enriched search semantics and security properties. © 2019 IEEE.

Abstract
Developing autonomous assistants to help with domestic tasks is a vital topic in robotics research. Among these tasks, garment folding is one of them that is still far from being achieved mainly due to the large number of possible configurations that a crumpled piece of clothing may exhibit. Research has been done on either estimating the pose of the garment as a whole or detecting the landmarks for grasping separately. However, such works constrain the capability of the robots to perceive the states of the garment by limiting the representations for one single task. In this paper, we propose a novel end-to-end deep learning model named GarmNet that is able to simultaneously localize the garment and detect landmarks for grasping. The localization of the garment represents the global information for recognising the category of the garment, whereas the detection of landmarks can facilitate subsequent grasping actions. We train and evaluate our proposed GarmNet model using the CloPeMa Garment dataset that contains 3,330 images of different garment types in different poses. The experiments show that the inclusion of landmark detection (GarmNet-B) can largely improve the garment localization, with an error rate of 24.7% lower. Solutions as ours are important for robotics applications, as these offer scalable to many classes, memory and processing efficient solutions.