Abstract
Introduction:The lack of engagement and the shortage of motivation and drive, also referred to as apathy, negatively impacts the effectiveness and adherence to treatment and the general well-being of people with neurocognitive disorders (NCDs), such as dementia. Methodology:The hypothesis raised states that the engagement of people with dementia during their non-invasive treatments for NCDs is affected by the noisy source levels and negative auditory stimuli present within environmental treatment settings. An online survey was conducted with the study objectives to assess 1) the engagement levels of dementia patients while interacting with others at home versus in therapy facilities, 2) the emotions perceived when interacting with people at home compared to therapy sessions, 3) the perceived loudness of the environment at home versus in therapy facilities, and 4) which source sounds negatively impact the patients at home and during therapy sessions. A purposive sampling (n=62) targeting relatives, friends, and caregivers of dementia patients was conducted via online community forums in the DACH region. Moreover, a recording session was conducted in a psychotherapist’s office to verify the answer tothe questionnaire on the noise sources perceived in therapy facilities. Results and Discussion:The raised hypothesis that disruptive auditory stimuli and noise levels influence the engagement levels of demented individuals during treatment is confirmed as the engagement is affected by the perceived noise disruptions when comparing perceived noise levels and engagement at home to those in treatment facilities.Significant statistical results were found between the lower engagement of demented individuals when interacting with people during therapy sessions compared to higher engagement in-home interactions. Furthermore, negatively perceived sound sources can be found in both therapy facilities and home settings. The noise sound sources identified, such as human voices, household appliances and household noises, while recording inthe psychotherapist’s office align with the questionnaire responses received on this topic. The findings indicate that the perceived heightened noise levels in therapy facilities stand in correlation with the lowered engagement rate perceived during the therapy session compared to the lower noise level and higher engagement encountered when demented individuals interact at home. Conclusion:If the identified noise elements are masked or replaced by other auditory stimuli that promote a soothing soundscape, the original disturbances encountered during therapy and the lack of engagement can possibly be minimized. Further studies need to be conducted in the prototyping of a noise intervention tool to analyze the impact on lack of engagement through noise disturbances.Keywords. Noise, Engagement, Dementia, Therapy, Apathy.INTRODUCTIONNeurocognitive disorders (NCDs) are a steadily rising global public health concern. In 2020, around 50 million people worldwide lived with major NCDs, specifically dementia, with nearly 10 million new cases per year1NCDs can be found in many diseases, including Alzheimer, Parkinson, Huntington, and Creutzfeldt-Jakob (Reith, 2018). The causes of NCDs are typically associated with advanced age. Still, it can occur from incidents such as traumatic brain injuries, infections, thyroid problems, damage to the blood vessels, and other causes (Kane et al., 2017), increasingly affecting a wide range of people and age groups. Successful treatment methods are limited and can be split into two main categories, invasive and non-invasive methods.Invasive treatment methods are surgical procedures, such as Deep Brain Stimulation (DBS), a neurosurgical procedure in which a neurotransmitter is placed in the brain to send electrical 1World Health Organization, Dementia [website] https://www.who.int/news-room/fact-sheets/detail/dementia(accessed 12 April 2021)

Abstract
This paper presents a scenario-based framework for energy hub (Ell) design considering the variable efficiencies of gas-fired converters, wind turbines and integrated demand response (MR) programs. The proposed hub is able to meet the electrical, heating and cooling demands and is also equipped with a power-to-gas (P2G) system. Electrical, cooling, and heating loads uncertainties have been taken into account and the final problem is modeled as a mixed-integer non-linear programming (MINLP) problem. The P2G system is precisely modeled and its impacts on hub planning, emission, and the efficiency of gas-fired converters are thoroughly investigated. The results demonstrate that the P2G system reduced CO2 emissions by 37.4% by consuming CO2 emitted by gas-fired units. In addition, the results indicate that the P2G system injects hydrogen into the gas-fired units and increases their efficiencies. Therefore, the generation rate of these units has increased and consequently a smaller capacity has been installed for them. Numerical results illustrate that the presence of the P2G system has led to a reduction of 7.7% and 16.2% of investment and operation costs, respectively. Finally, the results indicate that the implementation of the IDR program reduces the installed capacity of the equipment, thereby reducing 3.3% of total cost. Overall, the results prove that the implementation of IDR programs along with the installation of the P2G system lead to reduce costs and CO2 emissions.

Abstract
We present an online optimization method for time-evolving data streams that can automatically adapt the hyper-parameters of an embedding model. More specifically, we employ the Nelder-Mead algorithm, which uses a set of heuristics to produce and exploit several potentially good configurations, from which the best one is selected and deployed. This step is repeated whenever the distribution of the data is changing. We evaluate our approach on streams of real-world as well as synthetic data, where the latter is generated in such way that its characteristics change over time (concept drift). Overall, we achieve good performance in terms of accuracy compared to state-of-the-art AutoML techniques.

Abstract
Video games provide a means to improve a human's cognitive skills. There are several genres of games that affect different cognitive subcategory. The purpose of this paper is to determine whether video games could really improve cognitive skills and decision-making; and which video games genre affect which cognitive skills. The authors assess previous experiments related to video games and cognitive skills. The paper reviewed 27 experimental and literature review studies. The results of the review proved that video games do improve cognitive skills and decision-making. Cognitive skills such as perception, attentional control, and decision-making improves when subjects were trained with video games. In relation to video games genre, Real-time strategy (RTS) players outperforms First-person shooter (FPS) players on cognitive flexibility while FPS players tend to have lower switching cost in work. People with profession such as nurses and doctors showed improved decision-making and risk assessment when trained with serious simulation games. High school and undergraduate students who played video games exhibit better result when given tasks related to cognitive abilities compared to students who do not played video games. We encourage further studies to conduct a much bigger experiment to correlate with our findings. (C) 2021 The Authors. Published by Elsevier B.V.

Abstract
Secure databases have emerged to securely store and process sensitive data at untrusted infrastructures (e.g., Cloud Computing). To be secure and efficient, the encryption schemes used by these systems must be carefully chosen. Indeed, this task requires expertise both in databases and security, and is currently being done manually, which is time-consuming and error-prone and can lead to security violations, poor performance, or both. This paper presents ATOCS, a novel framework that analyses the applications' code and, from the inferred requirements, determines the best combination of encryption schemes and related configurations for the underlying secure NoSQL database. Its design is modular and extensible thus facilitating the support of different applications and database solutions. Our evaluation with real-world applications shows that ATOCS is fast (it takes 44 seconds to analyse more than 12K LoC), accurate, and simplifies the configuration of secure databases.

Abstract
The Giant Segmented Mirror Telescopes (GSMTs) including the Giant Magellan Telescope (GMT), the Thirty Meter Telescope (TMT), and the European Extremely Large Telescope (E-ELT), all have extreme adaptive optics (ExAO) instruments planned that will use pyramid wavefront sensors (PWFS). The ExAO instruments all have common features: a high-actuator-count deformable mirror running at extreme speeds (>1 kHz); a high-performance wavefront sensor (WFS); and a high-contrast coronagraph. ExAO WFS performance is currently limited by the need for high spatial sampling of the wavefront which requires large detectors. For ExAO instruments for the next generation of telescopes, alternative architectures of WFS are under consideration because there is a trade-off between detector size, speed, and noise that reduces the performance of GSMT-ExAO wavefront control. One option under consideration for a GSMT-ExAO wavefront sensor is a three-sided PWFS (3PWFS). The 3PWFS creates three copies of the telescope pupil for wavefront sensing, compared to the conventional four-sided PWFS (4PWFS), which uses four pupils. The 3PWFS uses fewer detector pixels than the 4PWFS and should therefore be less sensitive to read noise. Here we develop a mathematical formalism based on the diffraction theory description of the Foucault knife-edge test that predicts the intensity pattern after the PWFS. Our formalism allows us to calculate the intensity in the pupil images formed by the PWFS in the presence of phase errors corresponding to arbitrary Fourier modes. We use these results to motivate how we process signals from a 3PWFS. We compare the raw intensity (RI) method, and derive the Slopes Maps (SM) calculation for the 3PWFS, which combines the three pupil images of the 3PWFS to obtain the X and Y slopes of the wavefront. We then use the Object Oriented MATLAB Adaptive Optics toolbox (OOMAO) to simulate an end-to-end model of an AO system using a PWFS with modulation and compare the performance of the 3PWFS to the 4PWFS. In the case of a low read noise detector, the Strehl ratios of the 3PWFS and 4PWFS are within 0.01. When we included higher read noise in the simulation, we found a Strehl ratio gain of 0.036 for the 3PWFS using RI over the 4PWFS using SM at a stellar magnitude of 10. At the same magnitude, the 4PWFS RI also outperformed the 4PWFS SM, but the gain was only 0.012 Strehl. This is significant because 4PWFS using SM is how the PWFS is conventionally used for AO wavefront sensing. We have found that the 3PWFS is a viable WFS that can fully reconstruct a wavefront and produce a stable closed-loop with correction comparable to that of a 4PWFS, with modestly better performance for high read-noise detectors.