We investigate the impact of stellar rotation on the formation of black holes (BHs) by means of our population synthesis code sevn. Rotation affects the mass function of BHs in several ways. In ...massive metal-poor stars, fast rotation reduces the minimum zero-age main sequence (ZAMS) mass for a star to undergo pair instability and pulsational pair instability. Moreover, stellar winds are enhanced by rotation, peeling off the entire hydrogen envelope. As a consequence of these two effects, the maximum BH mass we expect from the collapse of a rotating metal-poor star is only ∼45 M , while the maximum mass of a BH born from a nonrotating star is ∼60 M . Furthermore, stellar rotation reduces the minimum ZAMS mass for a star to collapse into a BH from ∼18-25 M to ∼13-18 M . Finally, we have investigated the impact of different core-collapse supernova (CCSN) prescriptions on our results. While the threshold value of compactness for direct collapse and the fallback efficiency strongly affect the minimum ZAMS mass for a star to collapse into a BH, the fraction of the hydrogen envelope that can be accreted onto the final BH is the most important ingredient in determining the maximum BH mass. Our results confirm that the interplay between stellar rotation, CCSNe and pair instability plays a major role in shaping the BH mass spectrum.
This paper introduces technical solutions devised to support the Deployment Site - Regione Emilia Romagna (DS-RER) of the ACTIVAGE project. The ACTIVAGE project aims at promoting IoT (Internet of ...Things)-based solutions for Active and Healthy ageing. DS-RER focuses on improving continuity of care for older adults (65+) suffering from aftereffects of a stroke event. A Wireless Sensor Kit based on Wi-Fi connectivity was suitably engineered and realized to monitor behavioral aspects, possibly relevant to health and wellbeing assessment. This includes bed/rests patterns, toilet usage, room presence and many others. Besides hardware design and validation, cloud-based analytics services are introduced, suitable for automatic extraction of relevant information (trends and anomalies) from raw sensor data streams. The approach is general and applicable to a wider range of use cases; however, for readability's sake, two simple cases are analyzed, related to bed and toilet usage patterns. In particular, a regression framework is introduced, suitable for detecting trends (long and short-term) and labeling anomalies. A methodology for assessing multi-modal daily behavioral profiles is introduced, based on unsupervised clustering techniques. The proposed framework has been successfully deployed at several real-users' homes, allowing for its functional validation. Clinical effectiveness will be assessed instead through a Randomized Control Trial study, currently being carried out.
Artificial Intelligence in combination with the Internet of Medical Things enables remote healthcare services through networks of environmental and/or personal sensors. We present a remote healthcare ...service system which collects real-life data through an environmental sensor package, including binary motion, contact, pressure, and proximity sensors, installed at households of elderly people. Its aim is to keep the caregivers informed of subjects’ health-status progressive trajectory, and alert them of health-related anomalies to enable objective on-demand healthcare service delivery at scale. The system was deployed in 19 households inhabited by an elderly person with post-stroke condition in the Emilia–Romagna region in Italy, with maximal and median observation durations of 98 and 55 weeks. Among these households, 17 were multi-occupancy residences, while the other 2 housed elderly patients living alone. Subjects’ daily behavioral diaries were extracted and registered from raw sensor signals, using rule-based data pre-processing and unsupervised algorithms. Personal behavioral habits were identified and compared to typical patterns reported in behavioral science, as a quality-of-life indicator. We consider the activity patterns extracted across all users as a dictionary, and represent each patient’s behavior as a ‘Bag of Words’, based on which patients can be categorized into sub-groups for precision cohort treatment. Longitudinal trends of the behavioral progressive trajectory and sudden abnormalities of a patient were detected and reported to care providers. Due to the sparse sensor setting and the multi-occupancy living condition, the sleep profile was used as the main indicator in our system. Experimental results demonstrate the ability to report on subjects’ daily activity pattern in terms of sleep, outing, visiting, and health-status trajectories, as well as predicting/detecting 75% hospitalization sessions up to 11 days in advance. 65% of the alerts were confirmed to be semantically meaningful by the users. Furthermore, reduced social interaction (outing and visiting), and lower sleep quality could be observed during the COVID-19 lockdown period across the cohort.
The aim of the study was to estimate the rate of conversion from clinically isolated syndrome (CIS) to multiple sclerosis (MS) and to investigate variables predicting conversion in a cohort of ...patients presenting with symptoms suggestive of MS. Patients with a first symptom suggestive of MS in the preceding 6 months and exclusion of other diseases were enrolled in an observational prospective study from December 2004 through June 2007. Conversion from CIS to MS according to both McDonald and Clinically Defined Multiple Sclerosis (CDMS) criteria was prospectively recorded until March 2010. The multivariate Cox proportional hazard model was used to assess the best predictive factors of conversion from CIS to MS. Among 168 patients included in the analysis, 122 converted to MS according to McDonald criteria whereas 81 converted to MS according to CDMS criteria. The 2-year probability of conversion was 57 % for McDonald Criteria and 36 % for CDMS criteria. Variables at enrolment significantly associated with conversion according to McDonald criteria were age and positivity for Barkhof criteria, and according to Poser’s CDMS criteria, age, positivity for Barkhof criteria and no disease modifying therapy. In this large prospective cohort study the conversion rate from CIS to MS in patients presenting with recent symptoms suggestive of MS was within the range of previous observational studies and lower than that reported in the placebo arm of randomized trials. We confirm the prognostic value of MRI in addition to the previous experimental data on the protective role of disease-modifying therapies.
Systematic reviews call for well-designed trials with clearly described intervention components to support the effectiveness of educational campaigns to reduce patient delay in stroke presentation. ...We herein describe the systematic development process of a campaign aimed to increase stroke awareness and preparedness.
Campaign development followed Intervention Mapping (IM), a theory- and evidence-based tool, and was articulated in two phases: needs assessment and intervention development. In phase 1, two cross-sectional surveys were performed, one aiming to measure stroke awareness in the target population and the other to analyze the behavioral determinants of prehospital delay. In phase 2, a matrix of proximal program objectives was developed, theory-based intervention methods and practical strategies were selected and program components and materials produced.
In phase 1, the survey on 202 citizens highlighted underestimation of symptom severity, as in only 44% of stroke situations respondents would choose to call the emergency service (EMS). In the survey on 393 consecutive patients, 55% presented over 2 hours after symptom onset; major determinants were deciding to call the general practitioner first and the reaction of the first person the patient called. In phase 2, adult individuals were identified as the target of the intervention, both as potential "patients" and witnesses of stroke. The low educational level found in the patient survey called for a narrative approach in cartoon form. The family setting was chosen for the message because 42% of patients who presented within 2 hours had been advised by a family member to call EMS. To act on people's tendency to view stroke as an untreatable disease, it was decided to avoid fear-arousal appeals and use a positive message providing instructions and hope. Focus groups were used to test educational products and identify the most suitable sites for message dissemination.
The IM approach allowed to develop a stroke campaign integrating theories, scientific evidence and information collected from the target population, and enabled to provide clear explanations for the reasons behind key decisions during the intervention development process.
NCT01881152 . Retrospectively registered June 7 2013.
IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected ...infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions. The main objective of the current article is to present the successful completion of a collaborative multiscale research work, which addressed the complicated exercise of ethical decision making in IoT smart ecosystems for older adults. Our results reveal that among the strong enablers of the proposed ethical decision support model were the participatory and deliberative procedures complemented by a set of regulatory and non-regulatory tools to operationalize core ethical values such as transparency, trust, and fairness in real care settings for older adults and their caregivers.
We report the discovery of a transient equivalent hydrogen column density with an absorption edge at ∼3.8 kiloelectron volts in the spectrum of the prompt x-ray emission of gamma-ray burst (GRB) ...990705. This feature can be satisfactorily modeled with a photoelectric absorption by a medium located at a redshift of ∼0.86 and with an iron abundance of ∼75 times the solar one. The transient behavior is attributed to the strong ionization produced in the circumburst medium by the GRB photons. The high iron abundance points to the existence of a burst environment enriched by a supernova along the line of sight. The supernova explosion is estimated to have occurred about 10 years before the burst. Our results agree with models in which GRBs originate from the collapse of very massive stars and are preceded by a supernova event.
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