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Traditional power reduction techniques such as DVFS or RAPL are challenging to use with web services because they significantly affect the services' latency and throughput. Previous work suggested the use of controllers based on control theory or machine learning to reduce performance degradation under constrained power. However, generating these controllers is challenging as every web service app

An increased frequency of droughts due to anthropogenic climate change can lead to considerable stress for soil microorganisms and their functioning within northern peatlands. A better understanding of the diversity and relative abundance of methane producing and oxidizing taxa, and their functional genes, can help predict the functional potential of peatlands and how the microorganisms respond to

Connected Autonomous Vehicles (AVs) have the potential to revolutionize Intelligent Transportation Systems (ITS) by addressing urban transport challenges, such asAutonomous Intersection Management (AIM). However, the assumption of highly accurate positioning in most ITS applications does not align with real-life situations. While extensive research has been conducted to improve positioning accurac

In recent years, since the cloud can provide tremendous advantages regarding storage and computing resources, the industry has been motivated to move industrial control systems to the cloud. However, the cloud also introduces significant security challenges since moving control systems to the cloud can enable attackers to infiltrate the system and establish an attack that can lead to damages and d

Assessing effects of climate change on agricultural systems and the potential for ecological intensification to increase food security in developing countries is essential to guide management, policy-making and future research. ‘Push-pull’ technology (PPT) is a poly-cropping design developed in eastern Africa that utilizes plant chemicals to mediate plant–insect interactions. PPT application yield

The state-of-the-art machine learning techniques come with limited, if at all any, formal correctness guarantees. This has been demonstrated by adversarial examples in the deep learning domain. To address this challenge, here, we propose a scalable robustness verification framework for Deep Neural Networks (DNNs). The framework relies on Linear Programming (LP) engines and builds on decades of adv

Sustainability of Swedish meat consumption is assessed from the perspectives of nutrition, health, climate and land use. Our results suggest that more sustainable food systems can be achieved via changes in Swedish meat consumption and that our multidimensional approach can be useful in identifying such changes.

To have a successful career in engineering, students need both technical engineering skills and non-technical engineering skills (NTES) in the transition to professional life. To address NTES in engineering education, the concept of six compulsory ‘engineering days’ were introduced in two engineering programs at the undergraduate level. The importance of different NTES for industry has been evalua

Tool wear intensity is one of the major performance and economic indicators of metal cutting processes. Understanding and control of tool wear and its governing mechanisms enables effective and sustainable manufacturing. Known wear mechanisms include abrasive, adhesive, chemical and diffusional, where their individual or combined action leads to an overall tool degradation. In this study, we prese

High latitude mires are key ecosystems in the context of climate change since they store large amounts of carbon while constituting an important natural source of methane (CH4). However, while a growing number of studies have investigated methane fluxes (FCH4) at the plot- (~1 m2) and ecosystem-scale (~0.1–0.5 km2) across the boreal biome, variations of FCH4 magnitudes and drivers at the mesoscale

While many studies have examined carbon dynamics of boreal ecosystems following wildfire, research on forest-atmosphere carbon fluxes during widespread smoke events from adjacent active wildfires is limited. We examined eddy covariance carbon exchange adjacent to the May 2011 Utikuma Complex wildfire in central Alberta, Canada. Over a one-week period while the wildfire was burning <10 km from the

The future role of boreal forests in the global carbon cycle is uncertain given the rapid climate change in high latitudes. At the landscape scale, heterogeneity in stand age and land cover, contributions from terrestrial and aquatic fluxes, and harvest export may create complex carbon cycle-climate interactions. However, the integrated response of the net landscape carbon balance (NLCB) to inter-

Deposition of phosphorus (P) is important for the nutrient supply to forests and open land but also contributes to the eutrophication of surface waters. Deposition to open land can be measured as bulk deposition while deposition to forests cannot be measured directly, due to internal circulation of P within forest canopies. This study aimed to quantify the total deposition of P to open land and fo

Impacts of elevated tropospheric ozone on mountain birch leaves reveals higher vulnerability in young leaves compared to old. The leaf recovery after high concentration exposure is affected with lower photosynthetic rate and increased stress-related sesquiterpene emissions.

With the growing demand for efficient, safe and sustainable transportation systems, the imperative to design intelligent routing and traffic management solutions within urban settings, requiring minimal data exchange and ensuring scalability, becomes evident. This paper introduces an innovative paradigm for traffic management. By seamlessly integrating machine learning and Autonomous Intersection

The immune cell component of the tumor microenvironment is an important modulator of tumor progression. In patients with breast cancer, tumor-infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLS) represent core aspects of anti-tumor immunity, both increasingly recognized for clinical relevance. In this study, we evaluated immune-related histology features using whole slide H&E

This study examines how one may detect Parkinson’s disease (PD) by analyzing voice recordings made with a mobile phone. The key objectives include creating a model that ensures fair and unbiased predictions while maintaining interpretability that is consistent with the existing literature on PD. We introduce a novel group-wise scaling method to address typical age and biological sex biases in the

Motivation: Pollinators play a crucial role in maintaining Earth's terrestrial biodiversity. However, rapid human-induced environmental changes are compromising the long-term persistence of plant-pollinator interactions. Unfortunately, we lack robust, generalisable data capturing how plant-pollinator communities are structured across space and time. Here, we present the EuPPollNet (European Plant-