The Distribution of Lianas and Their Change in Abundance in Temperate Forests Over the Past 45 Years

Lianas (woody vines) are an important and dynamic component of many forests throughout the world, and increases in CO2, mean winter temperature, and forest fragmentation may promote their growth and proliferation in temperate forests. In this study, we used a 45‐year data set to test the hypothesis that lianas have increased in abundance and basal area in the interiors of 14 deciduous temperate forests in Wisconsin (USA) since 1959. We also censused woody plants along a gradient from the forest edge to the interior in seven of these forests to test the hypothesis that the abundance of lianas declines significantly with increasing distance from the forest edge. We found that lianas did not increase in abundance within the interiors of temperate forests in Wisconsin over the last 45 years. However, relative and absolute liana abundance decreased sharply with increasing distance from forest edges. Our findings suggest that forest fragmentation, not climate change, may be increasing the abundance of lianas in northern deciduous temperate forests, and that lianas may further increase in abundance if the severity of forest fragmentation intensifies

AI Hazard Management: A framework for the systematic management of root causes for AI risks

Recent advancements in the field of Artificial Intelligence (AI) establish the basis to address challenging tasks. However, with the integration of AI, new risks arise. Therefore, to benefit from its advantages, it is essential to adequately handle the risks associated with AI. Existing risk management processes in related fields, such as software systems, need to sufficiently consider the specifics of AI. A key challenge is to systematically and transparently identify and address AI risks' root causes - also called AI hazards. This paper introduces the AI Hazard Management (AIHM) framework, which provides a structured process to systematically identify, assess, and treat AI hazards. The proposed process is conducted in parallel with the development to ensure that any AI hazard is captured at the earliest possible stage of the AI system's life cycle. In addition, to ensure the AI system's auditability, the proposed framework systematically documents evidence that the potential impact of identified AI hazards could be reduced to a tolerable level. The framework builds upon an AI hazard list from a comprehensive state-of-the-art analysis. Also, we provide a taxonomy that supports the optimal treatment of the identified AI hazards. Additionally, we illustrate how the AIHM framework can increase the overall quality of a power grid AI use case by systematically reducing the impact of identified hazards to an acceptable level

The application of target trials with longitudinal targeted maximum likelihood estimation to assess the effect of alcohol consumption in adolescence on depressive symptoms in adulthood

Time-varying confounding is a common challenge for causal inference in observational studies with time-varying treatments, long follow-up periods, and participant dropout. Confounder adjustment using traditional approaches can also be limited by data sparsity, weight instability and computational issues. The Nicotine Dependence in Teens (NDIT) study is a prospective cohort study involving 24 data collection cycles to date, among 1,294 students recruited from 10 high schools in Montreal, Canada, including follow-up into adulthood. Our aim is to estimate associations between the timing of alcohol initiation and the cumulative duration of alcohol use on depression symptoms in adulthood. Based on the target trials framework, we define intention-to-treat and as-treated parameters in a marginal structural model with sex as a potential effect-modifier. We then use the observational data to emulate the trials. For estimation, we use pooled longitudinal target maximum likelihood estimation (LTMLE), a plug-in estimator with double robust and local efficiency properties. We describe strategies for dealing with high-dimensional potential drinking patterns and practical positivity violations due to a long follow-up time, including modifying the effect of interest by removing sparsely observed drinking patterns from the loss function and applying longitudinal modified treatment policies to represent the effect of discouraging drinking

Cooling Rate Controlled Aging of a Co-Free Fe-Ni-Cr-Mo-Ti-Al Maraging Steel

Maraging steels are high-strength steels that are hardened by the formation of precipitates during an isothermal aging heat treatment. Depending on the aging temperature and time the cooling rate after holding can play a significant factor on the development of the microstructure and mechanical properties. This study seeks to show how the cooling time influences the precipitation hardening effect, austenite reversion and the development of hardness and impact toughness. The material was aged at a constant temperature using holding times of 0 h, 4 h and 15 h and cooled with different cooling rates resulting in cooling times of 7 h, 28 h and 56 h. The microstructure was characterized using a combination of electron backscatter diffraction, X-ray diffraction and atom probe tomography with cluster-based precipitate analysis. It is shown that the effect of the cooling time is strongly dependent on the holding time and that a longer cooling time can improve hardness and impact toughness

Microstructure and Local Mechanical Properties of the Heat-Affected Zone of a Resistance Spot Welded Medium-Mn Steel

The properties of the heat-affected zone (HAZ) are reported to have a great influence on the mechanical performance of resistance spot welded advanced high strength steels. Therefore, in the present work, the HAZ of a medium-Mn steel is characterized regarding its microstructure and its mechanical properties depending on the distance to the fusion zone (FZ). In order to obtain the local mechanical properties of the HAZ, samples were heat-treated in a joule-heating thermal simulator using different peak temperatures to physically simulate the microstructure of the HAZ. By comparing the microstructure and the hardness of these heat-treated samples and the HAZ, the local peak temperatures within the HAZ could be determined. Subsequently, tensile tests were conducted, and the austenite phase fraction was measured magnetically on the physically simulated HAZ samples in order to determine the local mechanical properties of the HAZ. As verified by energy-dispersive X-ray spectroscopy, peak temperatures above 1200 °C led to a uniform distribution of manganese, resulting in a predominantly martensitic microstructure with high strength and low total elongation after quenching. Below 1100 °C, the diffusion of manganese is restricted, and considerable fractions of austenite remain stable. The austenite fraction increases almost linearly with decreasing peak temperature, which leads to an increase of the total elongation and to a slight decrease in the strength, depending on the distance to the FZ. Temperatures below 700 °C exhibit hardly any effect on the initial microstructure and mechanical properties

Influence of partitioning parameters on the mechanical stability of austenite in a Q&P steel: A comparative in-situ study

The transformation-induced plasticity (TRIP)-effect is an efficient way to increase the formability in high performance steels. Hence, an optimal stability of the retained austenite is crucial to benefit the most from this effect. In the present work, in-situ high energy X-ray diffraction was used to study the austenite to martensite transformation upon uniaxial tensile loading of a TRIP-assisted steel produced by the quenching and partitioning (Q&P) process. A detailed analysis of the diffraction patterns recorded during deformation allowed to study the austenite stability with respect to the applied partitioning conditions. The austenite stability was found to strongly depend on the applied heat treatment, and could be mainly attributed to the carbon content and to the tempering degree of the surrounding martensitic matrix. Partitioning at 260 °C resulted in a poor austenite stability, while the austenite was almost too stable after partitioning at 360 °C. The optimal combination of strength and ductility was found for partitioning at 400 °C.The micromechanical behavior was analyzed by the evolution of individual lattice strains and the change of full width at half maximum (FWHM). Yielding of austenite could be clearly identified by an increase of FWHM. Martensite showed an unexpected peak narrowing upon yielding. In the case of 2-step Q&P, austenite started to yield after martensite, while yielding occurred almost simultaneously in the case of 1-step Q&P

Influence of the Cooling Time on the Microstructural Evolution and Mechanical Performance of a Double Pulse Resistance Spot Welded Medium-Mn Steel

In the present work, the influence of the cooling time on the mechanical performance, hardness, and microstructural features of a double pulse resistance spot welded medium-Mn steel are investigated. Curves of the electrical resistance throughout the welding revealed that the cooling time strongly influences the heat generation during the second pulse. A second pulse after a short cooling time re-melts the center, and heat treats the edge of the primary fusion zone. This desired in-process heat treatment leads to a modification of the cast-like martensitic structure by recrystallization illustrated by electron backscatter diffraction measurements and to a homogenization of manganese segregations, visualized by energy-dispersive X-ray spectroscopy, which results in an enhanced mechanical performance during the cross tension strength test. In contrast, during excessively long cooling times, the resistance drops to a level where the heat generation due to the second pulse is too low to sufficiently re-heat the edge of the primary FZ. As a consequence, the signs of recrystallization disappear, and the manganese segregations are still present at the edge of the fusion zone, which leads to a deterioration of the mechanical properties

Austenite decomposition and carbon partitioning during quenching and partitioning heat treatments studied via in-situ X-ray diffraction

High strength combined with excellent ductility can be achieved by quenching and partitioning (Q&P) microstructures containing martensite and a considerable amount of retained austenite. Since the mechanical properties are inherited from the microstructure, a thorough understanding of this relationship is indispensable. In the present work, in-situ synchrotron X ray diffraction was used to investigate the transformation kinetics during Q&P processing. The effect of different heat treatment conditions on the microstructural evolution was examined and correlated to the mechanical properties obtained by tensile testing. The results showed that austenite decomposition occurred for all Q&P cycles, especially at the beginning of partitioning. The extent of this decomposition was affected by a change of the quenching temperature, while the partitioning temperature showed no significant influence. Regardless of the heat treatment parameters, carbon partitioning was clearly visible during the 2-step cycles, which led to enhanced work hardening with increasing strain. In contrast, this was not observed in the case of 1-step processing due to negligible carbon diffusion, and thus insufficient chemical stabilization of the austenite