The Role of Proactive Adaptation in International Climate Change Mitigation Agreements

This paper investigates the role of proactive adaptation in international mitigation coalition formation. Adaptation is introduced into a three stage cartel game of coalition formation. We analytically derive the optimal level of mitigation and proactive adaptation for the singletons and coalition members. We introduce the AD-STACO model which is constructed based on the STACO model, which is an applied three-stage cartel formation model with 12 heterogenous regions. Simulating all possible coalitions (4084) and checking for internal and external stability, we investigate how different levels of proactive adaptation will affect the payoffs in Grand coalition and the incentives to freeride. We examine which stable coalitions are found with different levels of proactive adaptation and whether regions can gain from overadaptation in the best performing stable coalition. We find that though payoffs increase in the Grand coalition with lower adaptation, incentives to leave increase. Coalition members can increase their payoffs through overadaptation.N/A

Seasonal adjustment and the business cycle in unemployment

Several recent studies show that seasonal variation and cyclical variation in unemployment are correlated. A common finding is that seasonality tends to differ across the business cycle stages of recessions and expansions. Since seasonal adjustment methods assume that the two sources of variation can somehow be separated, the present study examines the impact of seasonal adjustment on the analysis of cyclical patterns. Seasonally adjusted quarterly unemployment data for 5 G-7 countries are modeled by a Smooth Transition Autoregression [STAR] while the corresponding unadjusted data are modeled by a so-called Seasonal STAR [SEASTAR]. A comparison of the implied estimated peaks and troughs shows that there is substantial agreement on the business cycle chronologies, albeit that for seasonally adjusted data recessionary periods tend to last longer

Seasonal smooth transition autoregression

In this paper we put forward a new time series model, which describes nonlinearity and seasonality simultaneously. We discuss its representation, estimation of the parameters and inference. This seasonal STAR (SEASTAR) model is examined for its practical usefulness by applying it to 18 quarterly industrial production series. The data are tested for smooth-transition nonlinearity and for time-varying seasonality. We find that the model fits the data well for 14 of the 18 series. We also consider out-of-sample forecasting where we compare forecasts from the SEASTAR models with forecasts from nested models. It turns out that the SEASTAR model sometimes outperforms the other models, particularly for large horizons. Finally, we compare the SEASTAR models with STAR models for the 14 corresponding seasonally adjusted series, and we find that the estimated business cycle chronologies can be markedly different

Cost-effectiveness of a nurse-based intervention (AIMS) to improve adherence among HIV-infected patients : Design of a multi-centre randomised controlled trial

Peer reviewedPublisher PD

Процедура селекции ридж-регрессионных моделей

Исследована эффективность процедуры селекции регрессионных моделей в случае неопределённости структуры модели, аппроксимируемой ридж-регрессией.Досліджена ефективність процедури селекції регресійних моделей в разі невизначеності структури моделі, що апроксимується рідж-регресією.Efficiency of procedure of selection of regressive models is investigational in the case of vagueness of model structure, by the approximated ridge-regression

Port Protocols for Deadlock-Freedom of Component Systems

In component-based development, approaches for property verification exist that avoid building the global system behavior of the component model. Typically, these approaches rely on the analysis of the local behavior of fixed sized subsystems of components. In our approach, we want to avoid not only the analysis of the global behavior but also of the local behaviors of the components. Instead, we consider very small parts of the local behaviors called port protocols that suffice to verify properties.Comment: In Proceedings ICE 2010, arXiv:1010.530

Effectiveness and cost-effectiveness of a nurse-delivered intervention to improve adherence to treatment for HIV : a pragmatic, multicentre, open-label, randomised clinical trial

This trial was funded from public money by the Netherlands Organisation for Health Research and Development (ZonMW; grant number 171002208). Aardex provided support on the development of the study website. We thank all the HIV nurses and physicians from the seven HIV clinics involved in the AIMS study for their input and collaboration (Academic Medical Centre, Slotervaart hospital, and St. Lucas-Andreas hospital, all in Amsterdam; the Leiden University Medical Centre, Leiden; HAGA hospital, The Hague; Erasmus Medical Centre, Rotterdam; and Isala clinic, Zwolle), the study participants, and the Stichting HIV Monitoring (SHM) for their support in accessing the SHM database for identifying patient inclusion criteria and developing the Markov model. Finally, we thank and remember Herman Schaalma (deceased) for his contribution to the study design and grant application.Peer reviewedPostprin

Know Your Epidemic, Know Your Response: COVID-19 in the United States

We document that during the week of March 10-16, the Covid-19 pandemic fundamentally affected the perceptions of U.S. residents about the health risks and socioeconomic consequences entailed by the pandemic. During this week, it seems, everything changed. Not only did the pandemic progress rapidly across the United States, but U.S. residents started to realize that the threat was real: increasing Covid-19 caseloads heightened perceptions of infection risks and excess mortality risks, concerns about the economic implications increased substantially, and behavioral responses became widespread as the pandemic expanded rapidly in the U.S. In early to mid-March 2020, average perceptions about the coronavirus infection risks are broadly consistent with projections about the pandemic, while expectations about dying conditional on infection and expectations about Covid-19-related excess mortality during the next months are possibly too pessimistic. However, some aspects of Covid-19 perceptions are disconcerting from the perspective of implementing and sustaining an effective societal response to the pandemic. For instance, the education gradient in expected infection risks entails the possibility of having different perceptions of the reality of the pandemic between people with and without a college education, potentially resulting in two different levels of behavioral and policy-responses across individuals and regions. Unless addressed by effective health communication that reaches individuals across all social strata, some of the misperceptions about Covid-19 epidemic raise concerns about the ability of the United States to implement and sustain the widespread and harsh policies that are required to curtail the pandemic. Our analyses also reveal perceptions of becoming infected with the virus, and dying from Covid-19, were driven upwards by a rapidly increasing national caseload, and perceptions of the economic consequences and the adaptation of social distancing were affected by both national and state-level cases

Easy Wireless: broadband ad-hoc networking for emergency services

Wireless ad-hoc networks will enable emergency services to continuously overview and act upon the actual status of the situation by retrieving and exchanging detailed up-to-date information between the rescue workers. Deployment of high-bandwidth, robust, self-organising ad-hoc networks will enable quicker response to typical what/where/when questions, than the more vulnerable low-bandwidth communication networks currently in use. This paper addresses a number of results of the Easy Wireless project that enable high bandwidth robust ad-hoc networking. Most of the concepts presented here have been experimentally verified and/or prototyped

How and Why Do Students Use Learning Strategies? A Mixed Methods Study on Learning Strategies and Desirable Difficulties With Effective Strategy Users

In order to ensure long-term retention of information students must move from relying on surface-level approaches that are seemingly effective in the short-term to “building in” so called “desirable difficulties,” with the aim of achieving understanding and long-term retention of the subject matter. But how can this level of self-regulation be achieved by students when learning? Traditionally, research on learning strategy use is performed using self-report questionnaires. As this method is accompanied by several drawbacks, we chose a qualitative, in-depth approach to inquire about students' strategies and to investigate how students successfully self-regulate their learning. In order to paint a picture of effective learning strategy use, focus groups were organized in which previously identified, effectively self-regulating students (N = 26) were asked to explain how they approach their learning. Using a constructivist grounded theory methodology, a model was constructed describing how effective strategy users manage their learning. In this model, students are driven by a personal learning goal, adopting a predominantly qualitative, or quantitative approach to learning. While learning, students are continually engaged in active processing and self-monitoring. This process is guided by a constant balancing between adhering to established study habits, while maintaining a sufficient degree of flexibility to adapt to changes in the learning environment, assessment demands, and time limitations. Indeed, students reported using several strategies, some of which are traditionally regarded as “ineffective” (highlighting, rereading etc.). However, they used them in a way that fit their learning situation. Implications are discussed for the incorporation of desirable difficulties in higher education