In dit artikel zal getoetst worden of de WOZ-waarde valide en betrouwbaar is als marktwaarde-indicator van de vastgoedportefeuilles van het Rijksvastgoedbedrijf (RVB). De belangrijkste bijdrage van onderhavig onderzoek is dat uit de uitkomsten van het empirische onderzoek blijkt dat er in het kader van de Wet WOZ sprake is van een significante overwaardering ten opzichte van de marktwaarde (transactieprijs). Gemeenten hebben moeite om de WOZ-waarden van de objecten zoals die in de vastgoedportefeuilles van het Rijk voorkomen, correct vast te stellen. Zeker gezien de bredere toepassing van de WOZ-waarde kan dit onderzoek aanleiding zijn tot een hernieuwde afweging van het gebruik, met name waar het minder courant vastgoed betreft.
Objective: To predict mortality with the Tilburg Frailty Indicator (TFI) in a sample of community-dwelling older people, using a follow-up of 7 years. Setting and Participants: 479 Dutch community-dwelling people aged 75 years or older. Measurements: The TFI, a self-report questionnaire, was used to collect data about total, physical, psychological, and social frailty. The municipality of Roosendaal (a town in the Netherlands) provided the mortality dates. Conclusions and Implications: This study has shown the predictive validity of the TFI for mortality in community-dwelling older people. Our study demonstrated that physical and psychological frailty predicted mortality. Of the individual TFI components, difficulty in walking consistently predicted mortality. For identifying frailty, using the integral instrument is recommended because total, physical, psychological, and social frailty and its components have proven their value in predicting adverse outcomes of frailty, for example, increase in health care use and a lower quality of life.
MULTIFILE
Abstract: Due to rapidly aging human populations, frailty has become an essential concept, as it identifies older people who have higher risk of adverse outcomes, such as disability, institutionalization, lower quality of life, and premature death. The Tilburg Frailty Indicator (TFI) is a user-friendly questionnaire based on a multidimensional approach to frailty, assessing physical, psychologic, and social aspects of human functioning. This review aims to explore the efficiency of the TFI in assessing frailty as a means to carry out research into the antecedents and consequences of frailty, and its use both in daily practice and for future intervention studies. Using a multidimensional approach to frailty, in contexts where health care professionals or researchers may have no time to interview or examine the client, we recommend employing the TFI because there is robust evidence of its reliability and validity and it is easy and quick to administer. More studies are needed to establish whether the TFI is suitable for intervention studies not only in the community, but also for specific groups such as patients in the hospital or admitted to an emergency department. We conclude that it is important to not only determine the deficits that frail older people may have, but also to assess their balancing strengths and resources. In order to be able to meet the individual needs of frail older persons, traditional and often fragmented elderly care should be developed toward a more proactive elderly care, in which frail older persons and their informal network are in charge.
De glastuinbouw in Nederland is wereldwijd toonaangevend en loopt voorop in automatisering en data-gedreven bedrijfsvoering. Voor de data-gedreven teelt wordt, naast het monitoren van de kas-parameters ook het monitoren van gewasparameters steeds meer gevraagd. De sector is daarbij vooral geïnteresseerd in niet-destructieve, contactloze en persoonsonafhankelijk monitoring van gewassen. Optische sensortechnologie, zoals spectrale afbeeldingstechnologie, kan veel waardevolle informatie opleveren over de staat van een gewas of vrucht, bijvoorbeeld over het suikergehalte, maar ook de aanwezigheid van plantziektes of insecten. Echter is dit vaak een te kostbare oplossing voor zowel de technologiebedrijven die oplossingen leveren als voor de telers zelf. In dit project onderzoeken wij de mogelijkheid om spectrale beeldvorming tegen lagere kosten te realiseren. Het beoogde resultaat is een prototype van een instrument dat tegen lage kosten met spectrale beeldvorming een of meerdere gewaseigenschappen kan kwantificeren. Realisatie van dit prototype heeft een sterke Fotonica-component (expertise Haagse Hogeschool) maakt gebruik van Machine Learning (expertise perClass) en is bedoeld voor toepassing op scout robots in de glastuinbouw (expertise Mythronics). Een betaalbare oplossing betekent in potentie voor de teler een betere controle over kwaliteit van het gewas en automatisering voor detectie van ziekte-uitbraken. Bij een succesvol prototype kan deze innovatie leiden tot betere voedselkwaliteit en minder verspilling in de glastuinbouw.
The overall purpose of this consultancy was to support the activities under the Environmental Monitoring and Assessment Programme of the UN Economic Commission for Europe (UNECE) in developing the 7th pan-European environmental assessment, an indicator based and thematic assessment, implemented jointly with the United Nations Environment Programme (UNEP) and in support of the 2030 Agenda for Sustainable Development. The series of environmental assessments of the pan-European region provide up to-date and policy-relevant information on the interactions between the environment and society. This consultancy was to:> Draft the input on drivers and developments to chapter 1.2 of the assessment related to the environmental theme “4.2 Applying principles of circular economy to sustainable tourism”.> Suggest to UNECE and UNEP the most policy relevant indicators from UNECE-environmental, SDG indicators and from other indicator frameworks such as EEA or OECD for the environmental theme for the sub-chapter 4.2.> Assess the current state, trends and recent developments and prepare the substantive part of sub-chapter 4.2 (summary - part I) and an annex (part II) with the detailed analysis and findings.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
