Abstract

Abstract
The link prediction task has found numerous applications in real-world scenarios. However, in most of the cases like interactions, purchases, mobility, etc., links can re-occur again and again across time. As a result, the data being generated is excessively large to handle, associated with the complexity and sparsity of networks. Therefore, we propose a very fast, memory-less, and dynamic sampling-based method for predicting recurring links for a successive future point in time. This method works by biasing the links exponentially based on their time of occurrence, frequency, and stability. To evaluate the efficiency of our method, we carried out rigorous experiments with massive real-world graph streams. Our empirical results show that the proposed method outperforms the state-of-the-art method for recurring links prediction. Additionally, we also empirically analyzed the evolution of links with the perspective of multi-graph topology and their recurrence probability over time. © 2020 Cambridge University Press.

Abstract
Photodynamic therapy is a medical modality developed for the treatment of several diseases of oncological and non-oncological etiology that requires the presence of a photosensitizer, light and molecular oxygen, which combined will trigger physicochemical reactions responsible for reactive oxygen species production. Given the scarcity of photosensitizers that exhibit desirable characteristics for its potential application in this therapeutic strategy, the main aims of this work were the study of the photophysical and photochemical properties and the photobiological activity of several dicyanomethylene squaraine cyanine dyes. Thus, herein, the study of their aggregation character, photobleaching and singlet oxygen production ability, and the further application of the previously synthesized dyes in Caco-2 and HepG2 cancer cell lines, to evaluate their phototherapeutic effects, are described. Dicyanomethylene squaraine dyes exhibited moderate light-stability and, despite the low singlet oxygen quantum yields, were a core of dyes that exhibited relevant in vitro photodynamic activity, as there was an evident increase in the toxicity of some of the tested dyes exclusive to radiation treatments.

Abstract
Purpose In the vast majority of the individual robot installations, the robot arm is just one piece of a complex puzzle of components, such as grippers, jigs or external axis, that together compose an industrial robotic cell. The success of such installations is very dependent not only on the selection of such components but also on the layout and design of the final robotic cell, which are the main tasks of the system integrators. Consequently, successful robot installations are often empirical tasks owing to the high number of experimental combinations that could lead to exhaustive and time-consuming testing approaches. Design/methodology/approach A newly developed optimized technique to deal with automatic planning and design of robotic systems is proposed and tested in this paper. Findings The application of a genetic-based algorithm achieved optimal results in short time frames and improved the design of robotic work cells. Here, the authors show that a multi-layer optimization approach, which can be validated using a robotic tool, is able to help with the design of robotic systems. Originality/value To date, robotic solutions lack flexibility to cope with the demanding industrial environments. The results presented here formalize a new flexible and modular approach, which can provide optimal solutions throughout the different stages of design and execution control of any work cell.

Abstract
Background Decision-making in palliative care can be complex due to the uncertain prognosis and general fear surrounding decisions. Decision-making in palliative care may be influenced by spiritual and cultural beliefs or values. Determinants of the decision-making process are not completely understood, and spirituality is essential for coping with illness. Thus, this study aims to explore the influence of spirituality on the perception of healthcare decision-making in palliative care outpatients. Methods A cross-sectional study was developed. A battery of tests was administered to 95 palliative outpatients, namely: sociodemographic questionnaire (SQ), Decisional Conflict Scale (DCS), Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being scale (FACIT-Sp), and a semi-structured interview (SSI) to study one's perception of spirituality and autonomy in decision-making. Statistical analyses involved descriptive statistics for SQ and SSI. The Mann-Whitney test was used to compare scale scores between groups and correlations were used for all scales and subscales. The analysis of patients' definitions of spirituality was based on the interpretative phenomenological process. Results Spiritual wellbeing significantly correlated with greater levels of physical, emotional and functional wellbeing and a better quality of life. Greater spiritual wellbeing was associated with less decisional conflict, decreased uncertainty, a feeling of being more informed and supported and greater satisfaction with one's decision. Most patients successfully implemented their decision and identified themselves as capable of early decision-making. Patients who were able to implement their decision presented lower decisional conflict and higher levels of spiritual wellbeing and quality of life. Within the 16 themes identified, spirituality was mostly described through family. Patients who had received spiritual care displayed better scores of spiritual wellbeing, quality of life and exhibited less decisional conflict. Patients considered spirituality during illness important and believed that the need to receive spiritual support and specialised care could enable decision-making when taking into consideration ones' values and beliefs. Conclusion The impact of spiritual wellbeing on decision-making is evident. Spirituality is a key component of overall wellbeing and it assumes multidimensional and unique functions. Individualised care that promotes engagement in decision-making and considers patients' spiritual needs is essential for promoting patient empowerment, autonomy and dignity.

Abstract
We propose a pixel color amplification theory and family of enhancement methods to facilitate segmentation tasks on retinal images. Our novel re-interpretation of the image distortion model underlying dehazing theory shows how three existing priors commonly used by the dehazing community and a novel fourth prior are related. We utilize the theory to develop a family of enhancement methods for retinal images, including novel methods for whole image brightening and darkening. We show a novel derivation of the Unsharp Masking algorithm. We evaluate the enhancement methods as a pre-processing step to a challenging multi-task segmentation problem and show large increases in performance on all tasks, with Dice score increases over a no-enhancement baseline by as much as 0.491. We provide evidence that our enhancement preprocessing is useful for unbalanced and difficult data. We show that the enhancements can perform class balancing by composing them together. © Springer Nature Switzerland AG 2020.