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Surface-subsurface flow models for hydrological applications solve a coupled multiphysics problem. This usually consists of some form of the Richards and shallow water equations. A typical setup couples these two nonlinear partial differential equations in a partitioned approach via boundary conditions. Full interaction between the subsolvers is ensured by an iterative coupling procedure. This can
A combination of searches for a new resonance decaying into a Higgs boson pair is presented, using up to 139 fb^{-1} of pp collision data at sqrt[s]=13 TeV recorded with the ATLAS detector at the LHC. The combination includes searches performed in three decay channels: bb[over ¯]bb[over ¯], bb[over ¯]τ^{+}τ^{-}, and bb[over ¯]γγ. No excess above the expected Standard Model background is observed
This chapter presents an interpretation of Bernard Williams’s significant and substantial contributions on the topic of free will and moral responsibility. Williams’s fundamental objective, it is argued, is to vindicate moral responsibility by way of freeing it from distortions and misrepresentations imposed on it by “the morality system.” Although his earlier work is primarily concerned with the
BackgroundThere is a need to enhance access to and support for self-management of activities in everyday life after a stroke. Internet-based solutions have the potential to contribute to this development. Consequently, an internet-based intervention called Strategies for Empowering Activities in Everyday Life (SEE) was developed. The intervention aims to assist clients in developing management str
Time-series of high throughput gene sequencing data intended for gene regulatory network (GRN) inference are often short due to the high costs of sampling cell systems. Moreover, experimentalists lack a set of quantitative guidelines that prescribe the minimal number of samples required to infer a reliable GRN model. We study the temporal resolution of data vs. quality of GRN inference in order to
Petrochemical production is tightly entangled with fossil fuel extraction and constitutes the primary driver of oil demand growth. Therefore, scholars have increasingly started exploring the linkages between fossil fuels and chemicals, tracing their importance for the political economy of energy transitions. A defining feature in the global petrochemical industry is that the majority of the recent
Purpose Pain in conjunction with surgery for ulnar nerve entrapment at the elbow is seldom highlighted in the literature. This study aimed to explore patients' experiences of living with chronic pain (≥3 months duration) in conjunction with surgery for ulnar nerve entrapment at the elbow, the consequences and the coping strategies applied. Material and methods In-depth interviews were conducted wi
Ongoing climate variability and change are increasing the burden of diarrhoeal disease worldwide. Meaningful early warning systems with adequate lead times (weeks to months) are needed to guide public health decision–making and enhance community resilience against health threats posed by climate change. Toward this goal, we trained various machine-learning models to predict diarrhoeal disease rate
Objective: To evaluate radiographic knee osteoarthritis (OA) progression, development of knee OA, patient-reported outcomes and knee muscle strength at 10-year follow-up after arthroscopic partial meniscectomy (APM) or exercise therapy for degenerative meniscal tears. Methods: Randomised controlled trial including 140 participants, with a degenerative meniscal tear and no or minimal radiographic O
In this study, a combined workflow of computational methodologies is introduced to explore the transformative landscape of the ancient city of Savatra (Central Anatolia Region, Türkiye), which faces long-term risks stemming from natural and anthropogenic threats. Emphasis was placed on regional and local scale landscape analysis, employing aerial and ground-based remote-sensing techniques to unrav
Beamforming technology plays a significant role in source localization and quantification. As traditional delay-and-sum beamformers generally yield low spatial resolution, as well as suffer from the occurrence of spurious sources, different forms of deconvolution methods have been proposed in the literature. In this work, we propose two approaches based on a sparse reconstruction framework combine
This paper investigates the stabilization of underactuated vehicles moving in a three-dimensional vector space. The vehicle's model is established on the matrix Lie group SE(3), which describes the configuration of rigid bodies globally and uniquely. We focus on the kinematic model of the underactuated vehicle, which features an underactuation form that has no sway and heave velocity. To compensat
Background: Among sarcomas, which are rare cancers, many types are exceedingly rare; however, a definition of ultra-rare cancers has not been established. The problem of ultra-rare sarcomas is particularly relevant because they represent unique diseases, and their rarity poses major challenges for diagnosis, understanding disease biology, generating clinical evidence to support new drug developmen
Background: Standard biopsy for prostate cancer diagnosis is an unpleasant and sometimes painful procedure with a detection rate as low as around 50%. Consequently, an accurate blood-based test would be highly desirable to improve the predictive accuracy. However, the clinical value of a new blood test for diagnosing prostate cancer depends on its sensitivity and specificity, in relation to the se
The decomposition of nonlinear chirp modes is a challenging task, typically requiring prior knowledge of the number of modes a signal contains. In this work, we present a greedy nonlinear chirp mode estimation (NCME) technique that forms the used decomposition basis from the signal itself, using an arctangent demodulation technique. The resulting decomposition is formed by considering the residual
The aluminium industry is facing a challenge in meeting the goal of halved greenhouse gas emissions by 2050, while the demand for aluminium is estimated to increase 2–3 times by the same year. Energy efficiency will play an important part in achieving the goal. The paper's aim was to investigate possible production-related energy efficiency measures in the aluminium industry. Mining of bauxite and
Landslides often cause significant casualties and economic losses, and therefore landslide susceptibility mapping (LSM) has become increasingly urgent and important. The potential of deep learning (DL) like convolutional neural networks (CNN) based on landslide causative factors has not been fully explored yet. The main target of this study is the investigation of a GIS-based LSM in Zanjan, Iran a
A novel search for exotic decays of the Higgs boson into pairs of long-lived neutral particles, each decaying into a bottom quark pair, is performed using 139 fb−1 of s = 13 TeV proton-proton collision data collected with the ATLAS detector at the LHC. Events consistent with the production of a Higgs boson in association with a leptonically decaying Z boson are analysed. Long-lived particle (LLP)
