Large pseudoscalar Yukawa couplings in the complex 2HDM

We start by presenting the current status of a complex flavour conserving two-Higgs doublet model. We will focus on some very interesting scenarios where unexpectedly the light Higgs couplings to leptons and to b-quarks can have a large pseudoscalar component with a vanishing scalar component. Predictions for the allowed parameter space at end of the next run with a total collected luminosity of $300 \, fb^{-1}$ and $3000 \, fb^{-1}$ are also discussed. These scenarios are not excluded by present data and most probably will survive the next LHC run. However, a measurement of the mixing angle $\phi_\tau$, between the scalar and pseudoscalar component of the 125 GeV Higgs, in the decay $h \to \tau^+ \tau^-$ will be able to probe many of these scenarios, even with low luminosity. Similarly, a measurement of $\phi_t$ in the vertex $\bar t t h$ could help to constrain the low $\tan \beta$ region in the Type I model.Comment: 21 pages, 10 figure

Mobile Application for Real-Time Food Plan Management for Alzheimer Patients through Design-Based Research

Alzheimer’s disease is a type of dementia that affects many individuals, mainly in an older age group. Over time, it leads to other diseases that affect their autonomy and independence. The quality of food ingestion is a way to mitigate the disease and preserve the patient’s well-being, which substantially impacts their health. Many existing applications for food plan management focus on the prescription of food plans but do not provide feedback to the nutritionist on the real amount of ingested calories. It makes these applications inadequate for these diseases, where monitoring and control are most important. This paper proposed the design and development of a mobile application to monitor and control the food plans of Alzheimer’s patients, focused on informal caregivers and respective patients. It allows both the realistic visualization of the food plans and users to adjust their consumption and register extra meals and water consumption. The interface design process comprises a two-level approach: the user centered design methodology that accounts for users’ needs and requirements and the user experience questionnaire to measure user satisfaction. The results show that the interface is intuitive, visually appealing, and easy to use, adjusted for users that require a particular level of understanding regarding specific subjects.info:eu-repo/semantics/publishedVersio

Nutrition Control System Based on Short-term Personal Demands

Personalized nutrition considers an individual’s unique genetic, metabolic, and lifestyle factors to create a customized dietary plan tailored to their needs. People seeking to optimize their health and wellness through diet and lifestyle changes can benefit from technological advances in machine learning and deep learning approaches to create personalized models of nutritional requirements that override traditional food plans. These models will provide users with an unprecedented decision tool for informing them of the impact of specific food intake and exercise on their goals. This article presents the architecture, implementation, and preliminary results of a deep learning-based control system for nutrition. It allows users to understand the impact of their food and exercise immediate choices on their goals while reducing user interaction demands. Preliminary results have shown that it is possible to predict BMI (Body Mass Index) accurately within a time window of three days.info:eu-repo/semantics/publishedVersio

Multi-Device Nutrition Control

Precision nutrition is a popular eHealth topic among several groups, such as athletes, 1 people with dementia, rare diseases, diabetes, and overweight. Its implementation demands tight 2 nutrition control, starting with nutritionists who build up food plans for specific groups or individuals. 3 Each person then follows the food plan by preparing meals and logging all food and water intake. 4 However, the discipline demanded to follow food plans and log food intake turns out into high 5 dropout rates. This article presents the concepts, requirements, and architecture of a solution that 6 assists the nutritionist in building up and revising food plans and the user following them. It does 7 so by minimizing human-computer interaction by integrating the nutritionist and user systems 8 and introducing off-the-shelf IoT devices in the system, such as temperature sensors, smartwatches, 9 smartphones, and smart bottles. An interaction time analysis using the Keystroke Level Model 10 provides a baseline for comparison in future work addressing both the use of machine learning and 11 IoT devices to reduce the interaction effort of users.info:eu-repo/semantics/publishedVersio

Enhancing quality of life: Human-centered design of mobile and smartwatch applications for assisted ambient living

Background: Assisted ambient living interfaces are technologies designed to improve the quality of life for people who require assistance with daily activities. They are crucial for individuals to maintain their independence for as long as possible. To this end, these interfaces have to be user-friendly, intuitive, and accessible, even for those who are not techsavvy. Research in recent years indicates that people find it uncomfortable to wear invasive or large intrusive devices to monitor health status, and poor user interface design implies a lack of user engagement. Methods: This paper presents the design and implementation of non-intrusive mobile and smartwatch applications for detecting older adults when executing their routines. The solution uses an intuitive mobile application to set up beacons and incorporates biometric data acquired from the smartwatch to measure bio-signals correlated to the user’s location. User testing and interface evaluation are carried out using the User Experience Questionnaire (UEQ). Results: Six older adults participated in the evaluation of the interfaces. Results show that users found the interaction to be excellent in all the parameters of the UEQ in the evaluation of the mobile interface. For the smartwatch application, results vary from above average to excellent. Conclusions: The applications are intuitive and easy to use, and data obtained from integrating systems is essential to link information and provide feedback to the user.info:eu-repo/semantics/publishedVersio

CP in the dark

We build a model containing two scalar doublets and a scalar singlet with a specific discrete symmetry. After spontaneous symmetry breaking, the model has Standard Model-like phenomenology, as well as a hidden scalar sector which provides a viable dark matter candidate. We show that CP violation in the scalar sector occurs exclusively in the hidden sector, and consider possible experimental signatures of this CP violation.We acknowledge the contribution of the research training group GRK1694 'Elementary particle physics at highest energy and highest precision'. PF and RS are supported in part by the National Science Centre, Poland, the HARMONIA project under contract UMO-2015/18/M/ST2/00518 and by a CERN fund grant CERN/FIS-PAR/0002/2017. JW gratefully acknowledges funding from the PIER Helmholtz Graduate School.info:eu-repo/semantics/publishedVersio

Prediction of road accident severity using the ordered probit model

The ordered probit model is used to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents. The estimated results suggest that motor-vehicle occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy-vehicles, at one-way roads, and on wet road surfaces. Additionally, the driver's seat is clearly the safest seating position, urban areas seem to originate less serious accidents than rural areas, and women tend to be more likely to suffer serious or fatal injuries than men