The Davis Strait crust - a transform margin between two oceanic basins

The Davis Strait is located between Canada and Greenland and connects the Labrador Sea and the Baffin Bay basins. Both basins formed in Cretaceous to Eocene time and were connected by a transform fault system in the Davis Strait. Whether the crust in the central Davis Strait is oceanic or continental has been disputed. This information is needed to understand the evolution of this transform margin during the separation of the North American plate and Greenland. We here present a 315-km-long east–west-oriented profile that crosses the Davis Strait and two major transform fault systems—the Ungava Fault Complex and the Hudson Fracture Zone. By forward modelling of data from 12 ocean bottom seismographs, we develop a P-wave velocity model.We compare thismodel with a density model from ship-borne gravity data. Seismic reflection and magnetic anomaly data support and complement the interpretation. Most of the crust is covered by basalt flows that indicate extensive volcanism in the Davis Strait. While the upper crust is uniform, the middle and lower crust are characterized by higher P-wave velocities and densities at the location of the Ungava Fault Complex. Here, P-wave velocities of the middle crust are 6.6 km s−1 and of the lower crust are 7.1 km s−1 compared to 6.3 and 6.8 km s−1 outside this area; densities are 2850 and 3050 kg m−3 compared to 2800 and 2900 kg m−3. We here interpret a 45-km-long section as stretched and intruded crust or as new igneous crust that correlates with oceanic crust in the southern Davis Strait. A high-velocity lower crust (6.9–7.3 km s−1) indicates a high content of mafic material. This mantle-derived material gradually intruded the lower crust of the adjacent continental crust and can be related to the Iceland mantle plume. With plate kinematic modelling, we can demonstrate the importance of two transform fault systems in the Davis Strait: the Ungava Fault Complex with transpression and the Hudson Fracture Zone with pure strike-slip motion. We show that with recent poles of rotation, most of the relative motion between the North American plate and Greenland took place along the Hudson Fracture Zone

Machine Learning in Transaction Monitoring: The Prospect of xAI

Banks hold a societal responsibility and regulatory requirements to mitigate the risk of financial crimes. Risk mitigation primarily happens through monitoring customer activity through Transaction Monitoring (TM). Recently, Machine Learning (ML) has been proposed to identify suspicious customer behavior, which raises complex socio-technical implications around trust and explainability of ML models and their outputs. However, little research is available due to its sensitivity. We aim to fill this gap by presenting empirical research exploring how ML supported automation and augmentation affects the TM process and stakeholders' requirements for building eXplainable Artificial Intelligence (xAI). Our study finds that xAI requirements depend on the liable party in the TM process which changes depending on augmentation or automation of TM. Context-relatable explanations can provide much-needed support for auditing and may diminish bias in the investigator's judgement. These results suggest a use case-specific approach for xAI to adequately foster the adoption of ML in TM.Comment: Proceedings of the 56th Hawaii International Conference on System Sciences, 2023 https://hdl.handle.net/10125/10305

Machine Learning in Transaction Monitoring: The Prospect of xAI

Banks hold a societal responsibility and regulatory requirements to mitigate the risk of financial crimes. Risk mitigation primarily happens through monitoring customer activity through Transaction Monitoring (TM). Recently, Machine Learning (ML) has been proposed to identify suspicious customer behavior, which raises complex socio-technical implications around trust and explainability of ML models and their outputs. However, little research is available due to its sensitivity. We aim to fill this gap by presenting empirical research exploring how ML supported automation and augmentation affects the TM process and stakeholders’ requirements for building eXplainable Artificial Intelligence (xAI). Our study finds that xAI requirements depend on the liable party in the TM process which changes depending on augmentation or automation of TM. Context-relatable explanations can provide much-needed support for auditing and may diminish bias in the investigator’s judgement. These results suggest a use case-specific approach for xAI to adequately foster the adoption of ML in TM

Robotically driven construction of buildings: Exploring on-demand building components production

Robotically Driven Construction of Buildings (RDCB) is an exploration into design to production solutions for robotically driven construction of buildings initiated by the faculties of Civil Engineering and Architecture, TU Delft and Architecture, TU Eindhoven and implemented 2014 within the 3TU Lighthouse framework. The aim of was to involve the disciplines of architecture, robotics, materials science, and structural design in order to integrate knowledge from the individual disciplines and develop new numerically controlled manufacturing techniques and building-design optimisation methods for adding creative value to buildings in a cost-effective and sustainable way.RDCB builds up on expertise developed at Hyperbody with respect to applications of robotics in architecture and this paper presents the contribution of the Robotic Building team from Hyperbody, Faculty of Architecture, TU Delft to the RDCB project. The contribution is in line with Europe’s aim to improve material and energy efficiency of buildings and efficiency of construction processes. Robotically driven construction and customised building materials have the potential to realise this in a cost-effective way and at the same time reduce accidents and health hazards for workers in the building sector. In order to achieve this RDCB is distributing materials as needed and where needed. This requires exploration of a variety of techniques and implies working with customised materials and techniques while finding the best methods of applying materials in the logic of specific force flows or thermal dissipation patterns.RDCB advances multi- and trans-disciplinary knowledge in robotically driven construction by designing and engineering new building systems for the on-demand production of customisable building components (Bier, 2014). The main consideration is that in architecture and building construction the factory of the future employs building materials and components that can be on site robotically processed and assembled

Regulation of Coronary Blood Flow

The heart is uniquely responsible for providing its own blood supply through the coronary circulation. Regulation of coronary blood flow is quite complex and, after over 100 years of dedicated research, is understood to be dictated through multiple mechanisms that include extravascular compressive forces (tissue pressure), coronary perfusion pressure, myogenic, local metabolic, endothelial as well as neural and hormonal influences. While each of these determinants can have profound influence over myocardial perfusion, largely through effects on end-effector ion channels, these mechanisms collectively modulate coronary vascular resistance and act to ensure that the myocardial requirements for oxygen and substrates are adequately provided by the coronary circulation. The purpose of this series of Comprehensive Physiology is to highlight current knowledge regarding the physiologic regulation of coronary blood flow, with emphasis on functional anatomy and the interplay between the physical and biological determinants of myocardial oxygen delivery. © 2017 American Physiological Society. Compr Physiol 7:321-382, 2017

Oceanic Residual Depth Measurements, the Plate Cooling Model and Global Dynamic Topography

Convective circulation of the mantle causes deflections of the Earth's surface that vary as a function of space and time. Accurate measurements of this dynamic topography are complicated by the need to isolate and remove other sources of elevation, arising from flexure and lithospheric isostasy. The complex architecture of continental lithosphere means that measurement of present-day dynamic topography is more straightforward in the oceanic realm. Here, we present an updated methodology for calculating oceanic residual bathymetry, which is a proxy for dynamic topography. Corrections are applied that account for the effects of sedimentary loading and compaction, for anomalous crustal thickness variations, for subsidence of oceanic lithosphere as a function of age, and for non-hydrostatic geoid height variations. Errors are formally propagated to estimate measurement uncertainties. We apply this methodology to a global database of 1,936 seismic surveys located on oceanic crust and generate 2,297 spot measurements of residual topography, including 1,161 with crustal corrections. The resultant anomalies have amplitudes of ±1 km and wavelengths of ∼1,000 km. Spectral analysis of our database using cross-validation demonstrates that spherical harmonics up to and including degree 30 (i.e. wavelengths down to 1,300 km) are required to accurately represent these observations. Truncation of the expansion at a lower maximum degree erroneously increases the amplitude of inferred long-wavelength dynamic topography. There is a strong correlation between our observations and free-air gravity anomalies, magmatism, ridge seismicity, vertical motions of adjacent rifted margins, and global tomographic models. We infer that shorter wavelength components of the observed pattern of dynamic topography may be attributable to the presence of thermal anomalies within the shallow asthenospheric mantle.This research is supported by a BP-Cambridge collaboration