Abstract
Grid-connected photovoltaic (PV) systems are considered as the best options for home solar electric system applications. Compared to other alternatives, grid-connected PV systems offer the least expensive and lowest-maintenance choice for residential usage. The PV systems are constructed using some solar cells to extract the energy from sun radiations and power converters to convert the output DC voltage into AC one. In the present study a hybrid scheme is suggested to control the grid-connected PV converters. The developed scheme is able to inject the power created by solar arrays into the network. Also, it can rectify the problems associated with the reactive power and load harmonics in the system. Moreover, the suggested technique can secure the load active and reactive power during the network failure conditions. One of the contributions of the proposed method is that it can manage the power of solar arrays to supply the load, filter the harmonics and compensate the reactive power in a situation where the power produced by solar arrays is less than the power of converters. In this condition, the proposed technique can make the current drawn from the grid completely sine at unity power factor.

Abstract
Currently, the use of free and open-source software is increasing. The flexibility, availability, and maturity of this software could be a key driver to develop useful and interesting solutions. In general, open-source solutions solve specific tasks that can replace commercial solutions, which are often very expensive. This is even more noticeable in areas requiring analysis and manipulation/visualization of a large volume of data. Considering that there is a major gap in the development of web applications for photogrammetric processing, based on open-source technologies that offer quality results, the application presented in this article is intended to explore this niche. Thus, in this article a solution for photogrammetric processing is presented, based on the integration of MicMac, GeoServer, Leaflet, and Potree software. The implemented architecture, focusing on open-source software for data processing and for graphical manipulation, visualization, measuring, and analysis, is presented in detail. To assess the results produced by the proposed web application, a case study is presented, using imagery acquired from an unmanned aerial vehicle in two different areas.

Abstract
The precise production of 4.5 µm off-axis first order FBG in an SMF-28e fiber through femtosecond laser direct writing is demonstrated. The off-axis FBG potential as sensing head for torsion sensing was successfully explored. © 2021 The Author(s).

Abstract
Saliency maps have been used as one possibility to interpret deep neural networks. This method estimates the relevance of each pixel in the image classification, with higher values representing pixels which contribute positively to classification. The goal of this study is to understand how the complexity of the network affects the interpretabilty of the saliency maps in classification tasks. To achieve that, we investigate how changes in the regularization affects the saliency maps produced, and their fidelity to the overall classification process of the network. The experimental setup consists in the calculation of the fidelity of five saliency map methods that were compare, applying them to models trained on the CIFAR-10 dataset, using different levels of weight decay on some or all the layers. Achieved results show that models with lower regularization are statistically (significance of 5%) more interpretable than the other models. Also, regularization applied only to the higher convolutional layers or fully-connected layers produce saliency maps with more fidelity.

Abstract
Abstract Background: Analysis of locomotion is often used as a measure for impairment and recovery following experimental peripheral nerve injury. Compared to rodents, sheep offer several attractive features as an experimental model for studying peripheral nerve regeneration. There are no studies on locomotion outcomes after peripheral nerve injury and repair in the sheep model. In the present study, we performed and compared two-dimensional (2D) and, for the first time, three-dimensional (3D) hindlimb kinematics during obstacle avoidance in the ovine model. This study aimed to obtain kinematic data to serve as a template for an objective assessment of the ankle joint motion in future studies of common peroneal nerve (CP) injury and repair in the ovine model. Results: The strategy used by the sheep to bring the hindlimb over a moderately high obstacle, set to 10% of its hindlimb length, was the pronounced knee, ankle and metatarsophalangeal flexion when approaching and clearing the obstacle. Despite the overall time course kinematic patterns about the hip, knee, ankle, and metatarsophalangeal were identical, we found significant differences between values of the 2D and 3D joint angular motion. Conclusions: Our results show that the most apparent changes that occurred during the gait cycle were for the ankle and metatarsophalangeal joints, whereas the hip and knee joints were much less affected. Data and techniques described here are likely to be useful for an objective assessment of altered gait after CP injury and repair in an ovine model.

Abstract
Residential consumers have been adopting distributed energy resources (DER) like photovoltaics (PV), electric vehicles (EV) as well as electric heating, ventilation and air conditioning devices (HVAC) in recent years - thus substantially reshaping power systems. This study is dedicated to the analysis of such adopters in continental Portugal, using both spatial analysis tools and census data with information theoretic criteria. Results suggest that the current uptake of EV, PV, and HVAC is characterised by spatially auto-correlated adoption patterns. The analysis of census variables, on the other hand, reveals that Portuguese EV, PV, and HVAC adopters exhibit a few surprising, unrecorded characteristics compared with previous studies. Comparing different dataset resolutions, EV and HVAC adopters are found to be most similar across all three aggregation levels considered. Results further show that fewer adopter groups tend to own both EV-HVAC and PV-HVAC, reducing per se synergy potentials that may arise behind the metre. One of the main outcomes from this work is that studies describing energy technology adopters using census variables might receive very unstable results across different data aggregation levels. This may lead to adverse effects on studies' conclusiveness and energy policy design choices.