Abstract
Retailers face increasing competitive pressure to determine how best to deliver products purchased online to the end customer. Grocery retailers often require attended home delivery where the customer must be present to receive the delivery. For attended home delivery to function, the retailer and customer must agree on a delivery time slot that works for both parties. Using online data from a grocery retailer, we observe customer preferences for three delivery service attributes associated with each time slot: speed, precision, and timing. We define speed as the expected time between the placement of an order and its delivery, precision as the duration of the offered time slot, and timing as the availability of choices across times of the day and days of the week. We show that customers not only value speed as an attribute of delivery service but that precision and timing are also key drivers of the customer's time slot selection process. We also observe substantial customer heterogeneity in the willingness of customers to pay for time slots. Customers that differ in their loyalty to the retailer, basket value, basket size, and basket composition exhibit distinct differences in their willingness to pay. We show that retailers with the capability to tailor their time slot offerings to specific customer segments have the potential to generate approximately 9% more shipping revenue than those who cannot. Our findings inform practitioners seeking to design competitive fulfillment strategies and academics customer behavior in the attended home context.

Abstract
Young, low-mass brown dwarfs orbiting early-type stars, with low mass ratios (q less than or similar to 0.01), appear to be intrinsically rare and present a formation dilemma: could a handful of these objects be the highest-mass outcomes of planetary formation channels (bottom up within a protoplanetary disk), or are they more representative of the lowest-mass failed binaries (formed via disk fragmentation or core fragmentation)? Additionally, their orbits can yield model-independent dynamical masses, and when paired with wide wavelength coverage and accurate system age estimates, can constrain evolutionary models in a regime where the models have a wide dispersion depending on the initial conditions. We present new interferometric observations of the 16 Myr substellar companion HD 136164 Ab (HIP 75056 Ab) made with the Very Large Telescope Interferometer (VLTI)/GRAVITY and an updated orbit fit including proper motion measurements from the Hipparcos-Gaia Catalog of Accelerations. We estimate a dynamical mass of 35 +/- 10 M-J (q similar to 0.02), making HD 136164 Ab the youngest substellar companion with a dynamical mass estimate. The new mass and newly constrained orbital eccentricity (e = 0.44 +/- 0.03) and separation (22.5 +/- 1 au) could indicate that the companion formed via the low-mass tail of the initial mass function. Our atmospheric fit to a SPHINX M-dwarf model grid suggests a subsolar C/O ratio of 0.45 and 3 x solar metallicity, which could indicate formation in a circumstellar disk via disk fragmentation. Either way, the revised mass estimate likely excludes bottom-up formation via core accretion in a circumstellar disk. HD 136164 Ab joins a select group of young substellar objects with dynamical mass estimates; epoch astrometry from future Gaia data releases will constrain the dynamical mass of this crucial object further.

Abstract
METIS, the Mid-Infrared ELT Imager and Spectrograph is a first-generation ELT instrument scheduled to see first light in 2029. Its two main science modules are supported by an adaptive optics system featuring a pyramid sensor with 90x90 sub-apertures working in H- and K-band. The wavefront control concept for METIS' singleconjugate adaptive optics relies on a synthetic calibration that uses a model of the telescope and instrument to generate the interaction and control matrices, as well as the final projection on a modal command vector. This concept is enforced owing to the absence of a calibration source in front of the ELT's main deformable mirror. The core of the synthetic calibration functionality is the Command Matrix Optimiser module, which consists of several components providing models for various parts and aspects of the instrument, as well as the entire reconstructor. Many are present in the simulation environment used during the design phases, but need to be re-written and/or adapted for real-life use. In this paper, we present the design of the full command matrix optimisation module, the status of these efforts and the overall final concept of METIS' soft real-time system.

Abstract

Abstract
Ground Penetrating Radar (GPR) is a geophysical imaging technique used for the characterization of a sub surface’s electromagnetic properties, allowing for the detection of buried objects. The characterization of an object’s parameters, such as position, depth and radius, is possible by identifying the distinct hyperbolic signature of objects in GPR B-scans. This paper proposes an automated system to detect and characterize the presence of buried objects through the analysis of GPR data, using GPR and computer vision data pro cessing techniques and YOLO segmentation models. A multi-channel encoding strategy was explored when training the models. This consisted of training the models with images where complementing data processing techniques were stored in each image RGB channel, with the aim of maximizing the information. The hy perbola segmentation masks predicted by the trained neural network were related to the mathematical model of the GPR hyperbola, using constrained least squares. The results show that YOLO models trained with multi-channel encoding provide more accurate models. Parameter estimation proved accurate for the object’s position and depth, however, radius estimation proved inaccurate for objects with relatively small radii.

Abstract
The Seventh International Workshop on Narrative Extraction from Texts (Text2Story'24) was held on March 24 th , 2024, in conjunction with the 46 th European Conference on Information Retrieval (ECIR 2024) in Glasgow, Scotland. Over the day, more than 50 attendees engaged in discussions and presentations focused on recent advancements in narrative representation, extraction, and generation. The workshop featured two invited keynote addresses, fourteen research paper presentations, and a poster session. The workshop proceedings are available online. 1 Date : 24 March 2024. Website : https://text2story24.inesctec.pt/.