Reading Through the Life Span:Individual Differences in Psycholinguistic Effects

The effects of psycholinguistic variables are critical to the evaluation of theories about the cognitive reading system. However, reading research has tended to focus on the impact of key variables on average performance. We report the first investigation examining variation in psycholinguistic effects across the life span, from childhood into old age. We analyzed the performance of a sample of 535 readers, aged 8-83 years in lexical decision and pronunciation tasks. Our findings show that the effects on reading of two key variables, frequency and AoA, decrease in size with increasing age over the life span. We observed the systematic modulation by age and reading ability of these and other psycholinguistic effects alongside a global U-shaped effect of age. Diffusion model analyses suggest that developmental speed-up in decision responses can be attributed to the increasing quality of evidence accumulation in reaction to words, while the ageing-related slowing can be attributed to decreasing efficiency of stimulus encoding or response execution processes. An analysis of spoken response durations furnishes a consistent picture in which the slowing of pronunciation responses with age can be attributed to slowing articulatory processes. We think our findings can be explained by theoretical accounts that incorporate learning as the basis for the development of structure in the reading system. However, an adequate theory shall have to include assumptions about both developmental learning and later ageing. Our results warrant a life span theory of reading

The global and regional impacts of climate change under Representative Concentration Pathway forcings and Shared Socioeconomic Pathway socioeconomic scenarios

This paper presents an evaluation of the global and regional consequences of climate change for heat extremes, water resources, river and coastal flooding, droughts, agriculture and energy use. It presents change in hazard and resource base under different rates of climate change (Representative Concentration Pathways: RCP), and socio-economic impacts are estimated for each combination of RCP and Shared Socioeconomic Pathway. Uncertainty in the regional pattern of climate change is characterised by CMIP5 climate model projections. The analysis adopts a novel approach using relationships between level of warming and impact to rapidly estimate impacts under any climate forcing. The projections provided here can be used to inform assessments of the implications of climate change. At the global scale all the consequences of climate change considered here are adverse, with large increases under the highest rates of warming. Under the highest forcing the global average annual chance of a major heatwave increases from 5% now to 97% in 2100, the average proportion of time in drought increases from 7% to 27%, and the average chance of the current 50-year flood increases from 2% to 7%. The socio-economic impacts of these climate changes are determined by socio-economic scenario. There is variability in impact across regions, reflecting variability in projected changes in precipitation and temperature. The range in the estimated impacts can be large, due to uncertainty in future emissions and future socio-economic conditions and scientific uncertainty in how climate changes in response to future emissions. For the temperature-based indicators, the largest source of scientific uncertainty is in the estimated magnitude of equilibrium climate sensitivity, but for the indicators determined by precipitation the largest source is in the estimated spatial and seasonal pattern of changes in precipitation. By 2100 the range across socio-economic scenario is often greater than the range across the forcing levels

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

The climatic impact‐driver framework for assessment of risk‐relevant climate information

The climate science and applications communities need a broad and demand-driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the “climatic impact-driver” (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as “physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions.” We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co-developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises

The Lancet Countdown is an international collaboration, established to provide an independent, global monitoring system dedicated to tracking the emerging health profile of the changing climate. The 2020 report presents 43 indicators across five sections: climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. This report represents the findings and consensus of the 35 leading academic institutions and UN agencies that make up the Lancet Countdown, and draws on the expertise of climate scientists, geographers, and engineers; of energy, food, and transport experts; and of economists, social and political scientists, data scientists, public health professionals, and doctors

Utveckling och Validering av Metoder för Karaktärisering av Flerkomponentsystem vid Preparativ Vätskekromatografi

This thesis concerns the development and validation of methods for characterization of multi-component preparative LC systems. Measurements of competitive adsorption isotherms are performed to gain detailed information about the interactions inside the chromatography column. This information increases our understanding of the separation process and makes it possible to perform computer simulations and numerical optimizations to find optimal operating conditions. The methods under focus are called “the tracer-pulse method”, “the inverse method”, and “the inverse method on plateaus”. They are extensions of existing methods, with new experimental and numerical procedures to enable rapid and accurate multi-component adsorption isotherm determination. In the validation it was shown that they can produce results agreeing with traditional methods and that the acquired adsorption isotherm parameters can be used in simulations to accurately predict the outcome of preparative LC separations. The methods were used to characterize several complex LC systems and two phenomena were discovered and theoretically treated: 1) The presence of invisible deformed peaks in single-component systems. 2) Peak deformations encountered with modern chiral stationary phases, caused by strongly adsorbed eluent additives. The latter type of deformation was highly tuneable and it was possible to adjust the enantiomer peak shapes so that the peaks tailed in opposite directions with the sharp sides in between, yielding baseline resolution at remarkably high sample loads. In a final applied study both the LC-based perturbation peak method and a biosensor method based on surface plasmon resonance (SPR) were used for the first time for detailed characterization of chiral drug-protein interactions. The fundamental properties of the two very different methods were compared and it was found that the LC method is more suitable for multi-component analysis and that the SPR method is more suitable for stronger interactions

Utveckling och Validering av Metoder för Karaktärisering av Flerkomponentsystem vid Preparativ Vätskekromatografi

This thesis concerns the development and validation of methods for characterization of multi-component preparative LC systems. Measurements of competitive adsorption isotherms are performed to gain detailed information about the interactions inside the chromatography column. This information increases our understanding of the separation process and makes it possible to perform computer simulations and numerical optimizations to find optimal operating conditions. The methods under focus are called “the tracer-pulse method”, “the inverse method”, and “the inverse method on plateaus”. They are extensions of existing methods, with new experimental and numerical procedures to enable rapid and accurate multi-component adsorption isotherm determination. In the validation it was shown that they can produce results agreeing with traditional methods and that the acquired adsorption isotherm parameters can be used in simulations to accurately predict the outcome of preparative LC separations. The methods were used to characterize several complex LC systems and two phenomena were discovered and theoretically treated: 1) The presence of invisible deformed peaks in single-component systems. 2) Peak deformations encountered with modern chiral stationary phases, caused by strongly adsorbed eluent additives. The latter type of deformation was highly tuneable and it was possible to adjust the enantiomer peak shapes so that the peaks tailed in opposite directions with the sharp sides in between, yielding baseline resolution at remarkably high sample loads. In a final applied study both the LC-based perturbation peak method and a biosensor method based on surface plasmon resonance (SPR) were used for the first time for detailed characterization of chiral drug-protein interactions. The fundamental properties of the two very different methods were compared and it was found that the LC method is more suitable for multi-component analysis and that the SPR method is more suitable for stronger interactions