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Abstract
Two major control design objectives are set-point tracking and disturbance rejection. How to design a control system to achieve the best possible performance for both objectives is a classical research issue. For most systems these design objectives are conflicting meaning that a single controller cannot cope in providing overall good performance. In this paper, a dual mode control system is reported using a feedforward controller to achieve optimum set-point tracking and PID control to deal with disturbance rejection. A particle swarm optimization algorithm is deployed to design the feedforward controller and the magnitude optimum multiple integration method applied to design the PI/PID controllers. The proposed control system is tested on a custom-made laboratory control temperature kit based on Arduino system. Preliminary results are presented showing the dual-mode control potential merits. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
Intraoperative neuromonitoring (IONM) techniques are usually implemented during spine surgery to avoid nefarious abuse of the nervous system, which can cause postoperative problems. A lack of bibliometric analysis on the topic of IONM in spine surgery has been identified. Therefore, the aims of this study are to provide information about the main contributors to this field and their publication dynamics, as well as conceptual and cooperative networks. Results have shown that a steady publication increase has been occurring since 1991, with high levels of citations in the first decade, but irregular publication rates have been recorded more recently. Research production by country seems to be in line with what is observed in other surgical fields, but research funding for IONM in spine surgery seems to be lower, even with the clear interest of private funding agencies. The conceptual networks have shown the importance of motor-evoked potential, electromyography, and the effect of anesthesia, particularly in scoliosis surgery.

Abstract
Relative humidity monitorization is of extreme importance on scientific and industrial applications, and fiber optics-based sensors may provide solutions where other types of sensors have limitations. In this work, fiber optics’ sensors were fabricated by combining Long-Period Fiber Gratings with three different humidity-responding polymers, namely Poly(vinyl alcohol), Poly(ethylene glycol) and Hydromed™ D4. The performance of the multiple sensors was experimentally tested and crossed with numerical simulations, which provide a comparison with the expected response given the optical properties of the materials.

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Aim Testing the validity and reliability of the Scale for the Environments Evaluation of Professional Nursing Practice (SEE-Nursing Practice). Background The environment of professional nursing practice is key to achieve better results for clients, nurses and institutions. Therefore, instruments enabling the assessment of all its attributes are required. Method Cross-sectional methodological study. The SEE-Nursing Practice, based on a previous qualitative study and literature review, was applied as a questionnaire. Exploratory and confirmatory factor analyses were used to assess construct validity. Results A total of 752 nurses participated in the study. Exploratory factor analysis of the SEE-Nursing Practice led to a factor solution with 93 items and three subscales. The Structure, Process and Outcome subscales, respectively, have 43, 37 and 13 items, loaded in 6 factors, 6 factors and 2 factors and explaining 62.6%, 59.2% and 67.4% of the total variance. Cronbach's alpha of the overall scale and of the 3 subscales was greater than 0.90. Confirmatory factor analysis showed a good fit. Conclusion SEE-Nursing Practice is a good valid and reliable instrument. Implications for nursing management The SEE-Nursing Practice enables assessing practice environments and is a tool for nursing managers in the definition of strategies ensuring favourable environments for nursing care quality.

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