An innovative food system approach to diversifying protein intake: Protein-I: Shared Island sustainable healthy nutrition.

There is a need to transform our current food system if we are to feed the rapidly expanding global population while maintaining planetary health. Within the island of Ireland, there is an urgent need to diversify the foods that currently contribute to our populations' protein intake. A Shared Island Innovative Food System approach is required to achieve this in a manner that is sustainable and provides benefits to producers, consumers and other supply chain participants. The Protein-I project employs such an approach, with the paradigm focusing on production of plant food through to human health, while paying particular attention to the development of the rural bioeconomy. Using an interdisciplinary approach, the team will develop strategies to maximise sustainable plant protein production in a traceable/transparent fashion and assess the impact of changes to existing value chains and the development of new value chains for the rural economy. A smart supply chain technology solution tailored to the needs of the agri-food industry will be developed and tested. Additionally, we will co-design consumer-led approaches to diversify plant protein intake, model the impact of changes at the population level and perform human interventions to demonstrate efficacy in terms of achieving adequate nutrition and improved health. Comprehensive engagement with stakeholders is embedded throughout the whole project to embrace the multi-actor approach. Overall, the project will be a key step towards future-proofing our food system on the island of Ireland and moving towards protecting planetary and population health, within the context of a just transition.

Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management.

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.

Design and Implementation of a Smart Home in a Box to Monitor the Wellbeing of Residents With Dementia in Care Homes.

There is a global challenge related to the increasing number of People with Dementia (PwD) and the diminishing capacity of governments, health systems, and caregivers to provide the best care for them. Cost-effective technology solutions that enable and ensure a good quality of life for PwD via monitoring and interventions have been investigated comprehensively in the literature. The objective of this study was to investigate the challenges with the design and deployment of a Smart Home In a Box (SHIB) approach to monitoring PwD wellbeing within a care home. This could then support future SHIB implementations to have an adequate and prompt deployment allowing research to focus on the data collection and analysis aspects. An important consideration was that most care homes do not have the appropriate infrastructure for installing and using ambient sensors. The SHIB was evaluated via installation in the rooms of PwD with varying degrees of dementia at Kirk House Care Home in Belfast. Sensors from the SHIB were installed to test their capabilities for detecting Activities of Daily Living (ADLs). The sensors used were: (i) thermal sensors, (ii) contact sensors, (iii) Passive Infrared (PIR) sensors, and (iv) audio level sensors. Data from the sensors were collected, stored, and handled using a 'SensorCentral' data platform. The results of this study highlight challenges and opportunities that should be considered when designing and implementing a SHIB approach in a dementia care home. Lessons learned from this investigation are presented in addition to recommendations that could support monitoring the wellbeing of PwD. The main findings of this study are: (i) most care home buildings were not originally designed to appropriately install ambient sensors, and (ii) installation of SHIB sensors should be adapted depending on the specific case of the care home where they will be installed. It was acknowledged that in addition to care homes, the homes of PwD were also not designed for an appropriate integration with ambient sensors. This study provided the community with useful lessons, that will continue to be applied to improve future implementations of the SHIB approach.

Semi-Automated Data Labeling for Activity Recognition in Pervasive Healthcare.

Activity recognition, a key component in pervasive healthcare monitoring, relies on classification algorithms that require labeled data of individuals performing the activity of interest to train accurate models. Labeling data can be performed in a lab setting where an individual enacts the activity under controlled conditions. The ubiquity of mobile and wearable sensors allows the collection of large datasets from individuals performing activities in naturalistic conditions. Gathering accurate data labels for activity recognition is typically an expensive and time-consuming process. In this paper we present two novel approaches for semi-automated online data labeling performed by the individual executing the activity of interest. The approaches have been designed to address two of the limitations of self-annotation: (i) The burden on the user performing and annotating the activity, and (ii) the lack of accuracy due to the user labeling the data minutes or hours after the completion of an activity. The first approach is based on the recognition of subtle finger gestures performed in response to a data-labeling query. The second approach focuses on labeling activities that have an auditory manifestation and uses a classifier to have an initial estimation of the activity, and a conversational agent to ask the participant for clarification or for additional data. Both approaches are described, evaluated in controlled experiments to assess their feasibility and their advantages and limitations are discussed. Results show that while both studies have limitations, they achieve 80% to 90% precision.

A hybrid rule and machine learning based generic alerting platform for smart environments.

Existing smart environment based alert solutions have adopted a relatively complex and tailored approach to supporting individuals. These solutions have involved sensor based monitoring, activity recognition and assistance provisioning. Traditionally they have suffered from a number of issues, rooted in scalability and performance, associated with complex activity recognition processes. This paper introduces a generic approach to realizing an alerting platform within a smart environment. The core concept of this approach is presented and placed within the context of related work. A description of the approach is provided, followed by an evaluation. This evaluation shows the approach offers reasonable accuracy, future work will increase accuracy.

Automatic Metadata Generation Through Analysis of Narration Within Instructional Videos.

Current activity recognition based assistive living solutions have adopted relatively rigid models of inhabitant activities. These solutions have some deficiencies associated with the use of these models. To address this, a goal-oriented solution has been proposed. In a goal-oriented solution, goal models offer a method of flexibly modelling inhabitant activity. The flexibility of these goal models can dynamically produce a large number of varying action plans that may be used to guide inhabitants. In order to provide illustrative, video-based, instruction for these numerous actions plans, a number of video clips would need to be associated with each variation. To address this, rich metadata may be used to automatically match appropriate video clips from a video repository to each specific, dynamically generated, activity plan. This study introduces a mechanism of automatically generating suitable rich metadata representing actions depicted within video clips to facilitate such video matching. This performance of this mechanism was evaluated using eighteen video files; during this evaluation metadata was automatically generated with a high level of accuracy.

NFC based provisioning of instructional videos to assist with instrumental activities of daily living.

Existing assistive living and prompting based solutions have adopted a relatively complex approach to supporting individuals. These solutions have involved sensor based monitoring, activity recognition and assistance provisioning. Traditionally they have suffered from a number of issues rooted in scalability and performance levels associated with the activity recognition process. This paper introduces a simplistic approach to assistive living within a user's residence through the use of NFC tags and smart devices. The core concept of this approach is presented and is subsequently placed within the context of related work. A description of the architecture is provided and results following technical evaluation of the first system prototype are discussed.

Acute pulmonary emboli in a patient on long-term dabigatran therapy.

OBJECTIVE: To describe the case of a patient who developed acute pulmonary emboli (PE) despite long-term anticoagulation with dabigatran. CASE SUMMARY: A 69-year-old obese woman was hospitalized for worsening shortness of breath, dyspnea on exertion, and left pleuritic chest pain. On admission, a computed tomography angiogram revealed acute bilateral PE, despite use of dabigatran for atrial fibrillation for approximately 5 years prior to admission. Dabigatran was stopped and therapeutic enoxaparin was initiated concomitantly with warfarin. An investigation into possible causes for the development of the PE, including hypercoagulability, was unrevealing. Since dabigatran should have protected against PE, the patient was questioned regarding adherence to her regimen. She stated that she was adherent but reported using a pillbox. The patient was discharged home on warfarin with an enoxaparin bridge until her international normalized ratio was at least 2.0. DISCUSSION: The underlying cause for the patient's acute PE is unknown but could possibly be attributed to obesity and reduced mobility. Although dabigatran should have prevented PE, the presence of interacting drugs, patient-specific pharmacokinetics, suboptimal medication storage, and laboratory abnormalities may have resulted in reduced dabigatran exposure and protection. This is a reasonable hypothesis; however, the patient did not develop a stroke while receiving dabigatran. CONCLUSIONS: Our patient developed acute bilateral PE despite receiving long-term anticoagulation with dabigatran. While it is possible that patient-specific factors resulted in reduced dabigatran exposure and efficacy, conclusions cannot be made.

Evidence for the presence of active cytochrome P450 systems in Schistosoma mansoni and Schistosoma haematobium adult worms.

Extracts of the adult worms of both Schistosoma mansoni and Schistosoma haematobium can metabolise some typical P450 substrates but to differing degrees. S. mansoni worm extracts displayed a approximately 12-fold higher specific activity for an aminopyrine substrate than rat liver microsomes. At 4 mM substrate concentration the demethylation reaction with N-nitrosodimethylamine (NDMA) (5 nmol HCHO/mg protein/min) was only half that of rat liver microsomes, whereas in extracts of S. haematobium, no detectable activity was found towards NDMA. Using ethylmorphine as substrate the demethylation activity of S. mansoni extracts (1.82 nmol HCHO/mg protein/min) was 5.5-fold lower than that of rat liver microsomes. Benzphetamine demethylase activity was also readily detectable in S. mansoni worm extracts at 6.79 nmol HCHO/mg protein/min compared with 10.20 nmol HCHO/mg protein/min in the case of rat liver microsomes. When aniline was used as substrate, surprisingly, no activity was found in worm extracts of either S. mansoni or S. haematobium, whereas rat liver microsomes showed high activity towards this amine. The anti-P450 2E1 and 2B1/2 cross-reacted with both worm homogenates and gave a specific band corresponding to a protein of molecular weight of approximately 50.0 kDa. A study with anti-P450 IVA antibody revealed that while this protein was strongly expressed in S. haematobium worm extracts, no immunoreactivity was observed with extracts of S. mansoni. Immunoblotting analyses with anti-P450 IIIA and P450 1A1 did not detect immunoreactive protein in either S. mansoni or S. haematobium.