Environmental Policy and the Macroeconomy in the Presence of Ecological Thresholds

We study the environmental and economic effects of public abatement in the presence of multiple stable steady-state ecological equilibria. Under shallow-lake dynamics (SLD), the isocline for the stock of pollution features two stable branches, a good and a bad one. Assuming that the ecology is initially located on the upper (bad) branch of the isocline, the ecological equilibrium is hysteretic and a suitably designed temporary abatement policy can be used to steer the environment from the bad to the good equilibrium. In all models considered in this paper, a “cold turkey” abatement policy is optimal, i.e. the largest feasible shock should be administered for the shortest possible amount of time. Depending on the particular model used to characterize the economic system, there is a capital feedback effect that either helps or hinders the attainment of a successful abatement policy.Shallow-lake dynamics, Bifurcation, Environmental policy, Overlapping generations

Mental health nurses’ support to caregivers of older adults with severe mental illness : a qualitative study

Background: Literature has shown the serious impact of severe mental illness on the daily life of caregivers. We studied reported caregiver support practices by mental health nurses for use in the development of a nursing intervention. We aimed to explore current caregiver support practices by mental health nurses. Methods: Twenty-one participants completed semi-structured interviews, and 17 participants attended two focus groups. All interviews were audio-taped, transcribed and coded for qualitative analysis. Results: The diversity in caregiver support could best be described by three prototypes: the tolerator, the preventer and the concerner, representing three approaches of involvement with caregivers. At one end of the spectrum are mental health nurses (MHN) who are essentially only concerned with the wellbeing of the care recipient and see the caregiver as a potential impediment in reaching the client’s goals. We call these the tolerators. At the other end of the spectrum are the MHNs who see the caregiver and the care recipient as inextricably connected with each other. In these cases the MHN directs her/his intervention towards both the informal caregiver and the care recipient. We call these the concerners. In the middle position are MHNs who realize that caregivers are important agents in the achievement of the client’s goals, and therefore consider preventing them from becoming overburdened as an important goal. We call these the preventers. Conclusions: Based on the extent to which the MHNs believe that the informal caregiver plays a necessary role in the client’s support system, and the degree to which they feel responsible for the caregiver’s wellbeing, three MHN prototypes can be distinguished. These prototypes determine how the nurses’ vision directs their understanding of their role and responsibilities and the content of their behaviour. This implies that a change in behaviour needs to be preceded by a change in vision. Therefore, promoting family support cannot be achieved by one-size-fits-all-programmes

Circulating cell death products predict clinical outcome of colorectal cancer patients.

BackgroundTumor cell death generates products that can be measured in the circulation of cancer patients. CK18-Asp396 (M30 antigen) is a caspase-degraded product of cytokeratin 18 (CK18), produced by apoptotic epithelial cells, and is elevated in breast and lung cancer patients.MethodsWe determined the CK18-Asp396 and total CK18 levels in plasma of 49 colorectal cancer patients, before and after surgical resection of the tumor, by ELISA. Correlations with patient and tumor characteristics were determined by Kruskal-Wallis H and Mann-Whitney U tests. Disease-free survival was determined using Kaplan-Meier methodology with Log Rank tests, and univariate and multivariate Cox proportional hazard analysis.ResultsPlasma CK18-Asp396 and total CK18 levels in colorectal cancer patients were related to disease stage and tumor diameter, and were predictive of disease-free survival, independent of disease-stage, with hazard ratios (HR) of patients with high levels (> median) compared to those with low levels (< or = median) of 3.58 (95% CI: 1.17-11.02) and 3.58 (95% CI: 0.97-7.71), respectively. The CK18-Asp396/CK18 ratio, which decreased with tumor progression, was also predictive of disease-free survival, with a low ratio (< or = median) associated with worse disease-free survival: HR 2.78 (95% CI: 1.06-7.19). Remarkably, the plasma CK18-Asp396 and total CK18 levels after surgical removal of the tumor were also predictive of disease-free survival, with patients with high levels having a HR of 3.78 (95% CI: 0.77-18.50) and 4.12 (95% CI: 0.84-20.34), respectively, indicating that these parameters can be used also to monitor patients after surgery.ConclusionCK18-Asp396 and total CK18 levels in the circulation of colorectal cancer patients are predictive of tumor progression and prognosis and might be helpful for treatment selection and monitoring of these patients

The Diffusion of Local Differentiated Waste Disposal Taxes in the Netherlands

The diffusion of a novel taxing scheme (among Dutch municipalities over the period 1998-2005) is studied in which the waste disposal tax is increasing in the amount of waste a household produces. Inspection of the rise and spread of this tax shows that it is contagious: the probability of introduction is increasing in the number of neighboring municipalities that have already introduced this taxing scheme. A possible rationale is that the tax encourages the dumping of waste in neighboring municipalities. These municipalities may then introduce a similar tax to prevent dumping (spillover effect). Using panel data and a recently developed spatial probit approach (Elhorst et al. in J Appl Econom 32:422-439, 2017), it is possible to distinguish this spillover effect from time-specific effects. The results indicate the presence of strong spillovers

Reversible Environmental Catastrophes with Disconnected Generations

We study environmental policy in a stylized economy-ecology model featuring multiple deterministic stable steady-state ecological equilibria. The economy-ecology does not settle in either of the deterministic steady states as the environmental system is hit by random shocks. Individuals live for two periods and derive utility from the (stochastic) quality of the environment. They feature warm-glow preferences and engage in private abatement in order to weakly influence the stochastic process governing environmental quality. The government may also conduct abatement activities or introduce environmental taxes. We solve for the market equilibrium abstracting from public abatement and taxes and show that the ecological process may get stuck for extended periods of time fluctuating around the heavily polluted (low quality) deterministic steady state. These epochs are called environmental catastrophes. They are not irreversible, however, as the system typically switches back to the basin of attraction associated with the good (high quality) deterministic steady state. The paper also compares the stationary distributions for environmental quality and individuals' welfare arising under the unmanaged economy and in the first-best social optimum

Domain-adversarial neural networks to address the appearance variability of histopathology images

Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters. The parameters can vary between pathology labs and within the same lab over time, resulting in significant variability of the tissue appearance that hampers the generalization of automatic image analysis methods. Typically, this is addressed with ad-hoc approaches such as staining normalization that aim to reduce the appearance variability. In this paper, we propose a systematic solution based on domain-adversarial neural networks. We hypothesize that removing the domain information from the model representation leads to better generalization. We tested our hypothesis for the problem of mitosis detection in breast cancer histopathology images and made a comparative analysis with two other approaches. We show that combining color augmentation with domain-adversarial training is a better alternative than standard approaches to improve the generalization of deep learning methods.Comment: MICCAI 2017 Workshop on Deep Learning in Medical Image Analysi

Inferring a Third Spatial Dimension from 2D Histological Images

Histological images are obtained by transmitting light through a tissue specimen that has been stained in order to produce contrast. This process results in 2D images of the specimen that has a three-dimensional structure. In this paper, we propose a method to infer how the stains are distributed in the direction perpendicular to the surface of the slide for a given 2D image in order to obtain a 3D representation of the tissue. This inference is achieved by decomposition of the staining concentration maps under constraints that ensure realistic decomposition and reconstruction of the original 2D images. Our study shows that it is possible to generate realistic 3D images making this method a potential tool for data augmentation when training deep learning models.Comment: IEEE International Symposium on Biomedical Imaging (ISBI), 201

Transitions in a globalising world

The increasing complexity of our global society means that sustainable development cannot be addressed from a single perspective or scientific discipline. By using the concept of transitions, we examine current and future tensions between welfare, well-being and the environment, and focus on four major issues that are of global importance: two of our key natural resources, water and biodiversity; the health of human populations; and the developments related to global tourism. In our global assessment we base ourselves on the most recent scenario efforts of the Intergovernmental Panel on Climate Change (IPCC). Future developments are explored along the lines of four development paths (scenario groups), defined along two dimensions (global versus regional dynamics and emphasising economic objectives versus environmental and equity objectives

A state space model for exponential smoothing with group seasonality

We present an approach to improve forecast accuracy by simultaneously forecasting a group of products that exhibit similar seasonal demand patterns. Better seasonality estimates can be made by using information on all products in a group, and using these improved estimates when forecasting at the individual product level. This approach is called the group seasonal indices (GSI) approach, and is a generalization of the classical Holt-Winters procedure. This article describes an underlying state space model for this method and presents simulation results that show when it yields more accurate forecasts than Holt-Winters.Common seasonality; demand forecasting; exponential smoothing; Holt-Winters; state space model.