Association Between Atrial Fibrillation and Long-term Mortality in Acute MI Patients.

Background: AF is a common complication of an acute MI (AMI) and goes along with adverse events. Nevertheless, the therapeutical guidelines and pharmacological possibilities have improved over the past years. Therefore, this contemporary study aimed to clarify the effect of AF on long-term mortality in patients with incident AMI.

Blessing and curse of bioclimatic variables: A comparison of different calculation schemes and datasets for species distribution modeling within the extended Mediterranean area.

Bioclimatic variables (BCVs) are the most widely used predictors within the field of species distribution modeling, but recent studies imply that BCVs alone are not sufficient to describe these limits. Unfortunately, the most popular database, WorldClim, offers only a limited selection of bioclimatological predictors; thus, other climatological datasets should be considered, and, for data consistency, the BCVs should also be derived from the respective datasets. Here, we investigate how well the BCVs are represented by different datasets for the extended Mediterranean area within the period 1970-2020, how different calculation schemes affect the representation of BCVs, and how deviations among the datasets differ regionally.

Achieving Brazil's Deforestation Target Will Reduce Fire and Deliver Air Quality and Public Health Benefits.

Climate, deforestation, and forest fires are closely coupled in the Amazon, but models of fire that include these interactions are lacking. We trained machine learning models on temperature, rainfall, deforestation, land-use, and fire data to show that spatial and temporal patterns of fire in the Amazon are strongly modified by deforestation. We find that fire count across the Brazilian Amazon increases by 0.

3D-printed autoclavable plant holders to facilitate large-scale protein production in plants.

The Australian tobacco plant is becoming increasingly popular as a platform for protein production and metabolic engineering. In this system, gene expression is achieved transiently by infiltrating plants with suspensions of carrying vectors with the target genes. To infiltrate larger numbers of plants, vacuum infiltration is the most efficient approach known, which is already used on industrial scale.

Climate Change, Pollution, Deforestation, and Mental Health: Research Trends, Gaps, and Ethical Considerations.

Climate change, pollution, and deforestation have a negative impact on global mental health. There is an environmental justice dimension to this challenge as wealthy people and high-income countries are major contributors to climate change and pollution, while poor people and low-income countries are heavily affected by the consequences. Using state-of-the art data mining, we analyzed and visualized the global research landscape on mental health, climate change, pollution and deforestation over a 15-year period.

Dung-visiting beetle diversity is mainly affected by land use, while community specialization is driven by climate.

Dung beetles are important actors in the self-regulation of ecosystems by driving nutrient cycling, bioturbation, and pest suppression. Urbanization and the sprawl of agricultural areas, however, destroy natural habitats and may threaten dung beetle diversity. In addition, climate change may cause shifts in geographical distribution and community composition.

Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation.

Machine learning models can emulate chemical transport models, reducing computational costs and enabling more experimentation. We developed emulators to predict annual-mean fine particulate matter (PM) and ozone (O) concentrations and their associated chronic health impacts from changes in five major emission sectors (residential, industrial, land transport, agriculture, and power generation) in China. The emulators predicted 99.

Using Clustering, Statistical Modeling, and Climate Change Projections to Analyze Recent and Future Region-Specific Compound Ozone and Temperature Burden Over Europe.

High ground-level ozone concentrations and high air temperatures present two health-relevant natural hazards. The most severe health outcomes are generally associated with concurrent elevated levels of both variables, representing so-called compound ozone and temperature (o-t-) events. These o-t-events, their relationship with identified main meteorological and synoptic drivers, as well as ozone and temperature levels themselves and the linkage between both variables, vary temporally and with the location of sites.

Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor.

Forest and vegetation fires, used as tools for agriculture and deforestation, are a major source of air pollutants and can cause serious air quality issues in many parts of Asia. Actions to reduce fire may offer considerable, yet largely unrecognized, options for rapid improvements in air quality. In this study, we used a combination of regional and global air quality models and observations to examine the impact of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south-eastern China).

Large Air Quality and Public Health Impacts due to Amazonian Deforestation Fires in 2019.

Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA).

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China.

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs.

Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement.

The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university.

Structure and Relationships of University Instructors' Achievement Goals.

The present study examines the achievement goals of university instructors, particularly the structure of such goals, and their relationship to biographic characteristics, other aspects of instructors' motivation, and teaching quality. Two hundred and fifty-one university instructors (184 without Ph.D.

Deciphering acoustic emission signals in drought stressed branches: the missing link between source and sensor.

When drought occurs in plants, acoustic emission (AE) signals can be detected, but the actual causes of these signals are still unknown. By analyzing the waveforms of the measured signals, it should, however, be possible to trace the characteristics of the AE source and get information about the underlying physiological processes. A problem encountered during this analysis is that the waveform changes significantly from source to sensor and lack of knowledge on wave propagation impedes research progress made in this field.

Interactive graphics: exemplified with real data applications.

Graphics are widely used in modern applied statistics because they are easy to create, convenient to use, and they can present information effectively. Static plots do not allow interacting with graphics. User interaction, on the other hand, is crucial in exploring data.