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As automation challenges labour markets across Europe, research in political science is pointing towards the socially corrosive link between such technological change and political dissatisfaction. In this paper, I extend this research agenda by looking at the relation between automation risk and incumbent support in 20 European countries between 2012 and 2018. I find strong support for the notion that workers with substantial exposure to automation risk are more likely to reject governments at the ballot box. Importantly, however, these findings indicate that this anti-incumbent voting is less prevalent among theoretically at-risk workers who enjoy some level of protection, in the form of permanent contracts, co-determination rights or higher educational attainment. As such, this paper argues that technological occupation risk should be seen as feeding into broader labour market risks faced by voters.

A barn’s climate is vital for animal welfare and emissions control, including greenhouse gases like methane (CH4) and carbon dioxide (CO2) and environmental gases like ammonia (NH3). The goal of this study was to investigate a developed low-cost online tool for monitoring barn climate and air pollutant emissions (OTICE) in naturally ventilated barns. OTICE employed a wireless sensor network with low-cost sensors for gases and climate variables, allowing scalable use across multiple barns. We evaluated the sensors for CO2, NH3, and CH4 for accuracy, both in controlled lab conditions and in a dairy barn in Germany, where measurements were carried out continuously for a duration of 12 days. For the averaged concentration levels over the measurement period, the low-cost sensors agreed well with the reference system, with relative deviations lower than 7% for all three gases, with maximum peak deviations up to 32% for CO2, 67% for NH3, and 65% for CH4, with strong Spearman correlations for CO2 and NH3 (ρCO2 = 0.8, ρNH3 = 0.68) and a rather weak correlation for CH4 with ρCH4 = 0.24. Further calibration and stability investigations are required, especially for CH4 sensing. However, the overall good results for NH3 and especially CO2 measurements indicate a huge potential of the low-cost system as a valuable tool for monitoring relative NH3 emission levels and the measurement of air exchange rates in naturally ventilated barns.

A barn's climate is vital for animal welfare and emissions control, including greenhouse gases like methane (CH4) and carbon dioxide (CO 2 ) and environmental gases like ammonia (NH 3 ). The goal of this study was to investigate a developed low-cost online tool for monitoring barn climate and air pollutant emissions (OTICE) in naturally ventilated barns. OTICE employed a wireless sensor network with low-cost sensors for gases and climate variables, allowing scalable use across multiple barns. We evaluated the sensors for CO 2 , NH 3 , and CH4 for accuracy, both in controlled lab conditions and in a dairy barn in Germany, where measurements were carried out continuously for a duration of 12 days. For the averaged concentration levels over the measurement period, the low-cost sensors agreed well with the reference system, with relative deviations lower than 7% for all three gases, with maximum peak deviations up to 32% for CO 2 , 67% for NH 3 , and 65% for CH 4 , with strong Spearman correlations for CO 2 and NH 3 ( ρ C O 2 = 0.8, ρ N H 3 = 0.68) and a rather weak correlation for CH4 with ρ C H 4 = 0.24. Further calibration and stability investigations are required, especially for CH4 sensing. However, the overall good results for NH 3 and especially CO 2 measurements indicate a huge potential of the low-cost system as a valuable tool for monitoring relative NH 3 emission levels and the measurement of air exchange rates in naturally ventilated barns. [ABSTRACT FROM AUTHOR]

The direct measurement of emissions from naturally ventilated dairy barns is challenging due to their large openings and the turbulent and unsteady airflow at the inlets and outlets. The aim of this study was to quantify the impacts of the number and positions of sensors on the estimation of volume flow rate and emissions. High resolution measurements of a naturally ventilated scaled building model in an atmospheric boundary layer wind tunnel were done. Tracer gas was released inside the model and measured at the outlet area, using a fast flame ionization detector (FFID). Additionally, the normal velocity on the area was measured using laser Doppler anemometry (LDA). In total, for a matrix of 65 × 4 sensor positions, the mean normal velocities and the mean concentrations were measured and used to calculate the volume flow rate and the emissions. This dataset was used as a reference to assess the accuracy while systematically reducing the number of sensors and varying the positions of them. The results showed systematic errors in the emission estimation up to +97%, when measurements of concentration and velocity were done at one constant height. This error could be lowered under 5%, when the concentrations were measured as a vertical composite sample.

Sarcoidosis is a multisystemic disease usually affecting the lungs and mediastinal lymph nodes. Other organs, such as the liver and the spleen, are less commonly involved. Patients usually present with mild nonspecific symptoms. On imaging, hepatosplenomegaly with or without multiple focal lesions within the spleen may be seen in the active disease stage. Rarely, the disease may evolve to cirrhosis and liver failure. We report such a rare case of hepatosplenic sarcoidosis complicated by acute esophageal bleeding due to portal hypertension.

Robotization of production challenges the status‐quo in the economy, some win, while others lose out. Literature has argued that automation causes redistribution, both between capital and labour as within either category. We also know that many economies have chosen to adopt cooperative institutions to negotiate the negative by‐products of such economic changes. What is, however, less clear is how such institutions influence rates of automation themselves. This article contributes to this debate by conducting a panel analysis of sectoral robotization rates and cooperative institutions in 25 OECD countries between 1993 and 2017 using an original institutional indicator. The findings suggest that aside from simply redistributing the costs and benefits of automation throughout the productive sector, cooperative institutions also meaningfully predict higher levels of robot density, showing that more institutionalized economies do not lag behind in terms of automation. What is more, these institutions also seem to co‐determine the rates of robotization occurring during recessions. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) emission is one of the major environmental issues in livestock farming. Gas measurements are required to study the emission process, to establish emission factors, and to assess the efficiency of emission reduction techniques. However, the current methods for acquiring reference measurements of NH3 are either high in cost or labor intensive. In this study, a cost-effective ammonia monitoring system (AMS) was constructed from a commercially-available gas analyzing module based on tunable diode laser absorption (TDLA) spectroscopy. To cope with the negative measurement biases caused by differing inlet pressures, a set of correction equations was formulated. Field validation of the AMS on NH3 measurement was conducted in a fattening pig barn, where the system was compared to a Fourier-transform infrared (FTIR) spectroscopy analyzer. Under two test conditions in a fattening pig barn, the absolute error of the AMS measurements with respect to the average obtained values between the AMS and the FTIR was respectively 0.66 and 0.08 ppmv, corresponding to 5.9% and 0.5% relative error. Potential sources of the measurement uncertainties in both the AMS and FTIR were discussed. The test results demonstrated that the AMS was capable of performing high-quality measurement with sub-ppm accuracy, making it a promising cost-effective tool for establishing NH3 emission factors and studying NH3 emission processes in pig houses.

This paper presents a market-price-based method to value sub-soil resources in environmental Cost-Benefit Analysis and Life Cycle Assessment. The market price incorporates the privileged information of the market agents, explicitly or implicitly anticipating future applications of the resource, future backstop technologies, recycling potentials, the evolution of reserves and extraction costs. The market price is therefore considered as the best available integrated information reflecting the actual values of these parameters. Our method is based on the Hotelling rule and the fact that private agents discount future costs and benefits at a higher rate than society as a whole. In practice, the price of the last resource unit sold is calculated with the Hotelling rule using a market discount rate. Then, the price at depletion is retropolated with a social discount rate smaller than the market discount rate. The resulting corrected “socially optimal” price is higher than the market price. The method allows to calculate the social cost of resource exhaustion, which is applicable in Cost-Benefit Analysis and Life Cycle Assessment. The method is applied to mineral and fossil resources and the results are compared with other recent methods that seek to place a monetary value on resource depletion.