Data Exchange Markets via Utility Balancing

This paper explores the design of a balanced data-sharing marketplace for entities with heterogeneous datasets and machine learning models that they seek to refine using data from other agents. The goal of the marketplace is to encourage participation for data sharing in the presence of such heterogeneity. Our market design approach for data sharing focuses on interim utility balance, where participants contribute and receive equitable utility from refinement of their models. We present such a market model for which we study computational complexity, solution existence, and approximation algorithms for welfare maximization and core stability. We finally support our theoretical insights with simulations on a mean estimation task inspired by road traffic delay estimation.Comment: To appear in WWW 202

The Lysine Demethylase KDM5B Regulates Islet Function and Glucose Homeostasis

Aims. Posttranslational modifications of histones and transcription factors regulate gene expression and are implicated in beta-cell failure and diabetes. We have recently shown that preserving H3K27 and H3K4 methylation using the lysine demethylase inhibitor GSK-J4 reduces cytokine-induced destruction of beta-cells and improves beta-cell function. Here, we investigate the therapeutic potential of GSK-J4 to prevent diabetes development and examine the importance of H3K4 methylation for islet function. Materials and Methods. We used two mouse models of diabetes to investigate the therapeutic potential of GSK-J4. To clarify the importance of H3K4 methylation, we characterized a mouse strain with knockout (KO) of the H3K4 demethylase KDM5B. Results. GSK-J4 administration failed to prevent the development of experimental diabetes induced by multiple low-dose streptozotocin or adoptive transfer of splenocytes from acutely diabetic NOD to NODscid mice. KDM5B-KO mice were growth retarded with altered body composition, had low IGF-1 levels, and exhibited reduced insulin secretion. Interestingly, despite secreting less insulin, KDM5B-KO mice were able to maintain normoglycemia following oral glucose tolerance test, likely via improved insulin sensitivity, as suggested by insulin tolerance testing and phosphorylation of proteins belonging to the insulin signaling pathway. When challenged with high-fat diet, KDM5B-deficient mice displayed similar weight gain and insulin sensitivity as wild-type mice. Conclusion. Our results show a novel role of KDM5B in metabolism, as KDM5B-KO mice display growth retardation and improved insulin sensitivity.Fil: Backe, Marie Balslev. Universidad de Copenhagen; DinamarcaFil: Jin, Chunyu. Universidad de Copenhagen; DinamarcaFil: Andreone, Luz. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; ArgentinaFil: Sankar, Aditya. Universidad de Copenhagen; Dinamarca. The Novo Nordisk Foundation Center for Stem Cell Biology; DinamarcaFil: Agger, Karl. Universidad de Copenhagen; Dinamarca. The Novo Nordisk Foundation Center for Stem Cell Biology; DinamarcaFil: Helin, Kristian. Universidad de Copenhagen; Dinamarca. The Novo Nordisk Foundation Center for Stem Cell Biology; DinamarcaFil: Madsen, Andreas N.. Universidad de Copenhagen; DinamarcaFil: Poulsen, Steen S.. Universidad de Copenhagen; DinamarcaFil: Bysani, Madhusudhan. Lund University; SueciaFil: Bacos, Karl. Lund University; SueciaFil: Ling, Charlotte. Lund University; SueciaFil: Perone, Marcelo Javier. Universidad de Copenhagen; Dinamarca. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; ArgentinaFil: Holst, Birgitte. Universidad de Copenhagen; DinamarcaFil: Mandrup Poulsen, Thomas. Universidad de Copenhagen; Dinamarc

Dynamically mapping tasks with priorities and multiple deadlines in a heterogeneous environment

Includes bibliographical references (pages 166-167).In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is essential to assign the resources to tasks (match) and order the execution of tasks on each resource (schedule) to exploit the heterogeneity of the resources and tasks. Dynamic mapping (defined as matching and scheduling) is performed when the arrival of tasks is not known a priori. In the heterogeneous environment considered in this study, tasks arrive randomly, tasks are independent (i.e., no inter-task communication), and tasks have priorities and multiple soft deadlines. The value of a task is calculated based on the priority of the task and the completion time of the task with respect to its deadlines. The goal of a dynamic mapping heuristic in this research is to maximize the value accrued of completed tasks in a given interval of time. This research proposes, evaluates, and compares eight dynamic mapping heuristics. Two static mapping schemes (all arrival information of tasks are known) are designed also for comparison. The performance of the best heuristics is 84% of a calculated upper bound for the scenarios considered

Dynamics of Hot QCD Matter -- Current Status and Developments

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Laboratory (BNL) in New York, USA, and the Large Hadron Collider (LHC), at CERN in Geneva, Switzerland but also analyze these data to unravel the mystery of this new phase of matter that filled a few microseconds old universe, just after the Big Bang. In the meantime, advancements in theoretical works and computing capability extend our wisdom about the hot-dense QCD matter and its dynamics through mathematical equations. The exchange of ideas between experimentalists and theoreticians is crucial for the progress of our knowledge. The motivation of this first conference named "HOT QCD Matter 2022" is to bring the community together to have a discourse on this topic. In this article, there are 36 sections discussing various topics in the field of relativistic heavy-ion collisions and related phenomena that cover a snapshot of the current experimental observations and theoretical progress. This article begins with the theoretical overview of relativistic spin-hydrodynamics in the presence of the external magnetic field, followed by the Lattice QCD results on heavy quarks in QGP, and finally, it ends with an overview of experiment results.Comment: Compilation of the contributions (148 pages) as presented in the `Hot QCD Matter 2022 conference', held from May 12 to 14, 2022, jointly organized by IIT Goa & Goa University, Goa, Indi

Genetic insights into biological mechanisms governing human ovarian ageing

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease

Interactive In-Situ Scene Capture on Mobile Devices

Thesis (Ph.D.)--University of Washington, 2017-12Architectural visualizations of indoor scenes enable compelling applications in several areas, such as real estate, interior design, cultural heritage preservation, and more recently, immersive virtual reality. Computer-Aided Design (CAD) tools have been invaluable for creating such visualizations. However, creating detailed, attractive visualizations of scenes remains a challenging task, particularly for non-experts. User interfaces for CAD tools tend to be complex and require significant manual effort to operate. These tools are also designed to be used ex-situ, or off-site, making it difficult to record and reproduce details faithfully. In this thesis, I propose novel techniques and systems for interactive in-situ scene capture on mobile devices that let non-expert users quickly and easily capture useful architectural visualizations of indoor scenes. These systems are built upon two key insights; 1) sensors on mobile devices can be leveraged to capture important aspects of the scene such as dimensions, room shape, furniture placement, etc., and 2) an in-situ user can assist in the modeling task by acting as a guide for reconstruction and object recognition algorithms. Based on these insights, the semi-automatic systems that I propose combine the strengths of the user, who is good at high-level semantic reasoning, and the computer, which excels at combinatorics and numerical optimization. I present three systems in this thesis. First, I present a smartphone application designed to visually capture homes, offices and other indoor scenes. The application leverages data from smartphone sensors such as the camera, accelerometer, gyroscope and magnetometer to help reconstruct the indoor scene. The output of the system is two-fold; first, an interactive visual tour of the scene is generated in real time that allows the user to explore each room and transition between connected rooms. Second, by marking distinct room features such as corners and doors, the system generates a 2D floor plan and accompanying 3D model of the scene, under a Manhattan-world assumption. This approach does not require any specialized equipment or training, and is able to produce accurate floor plans. I then describe an interactive system to capture CAD-like 3D models of indoor scenes, on a tablet device. The modeling proceeds in two stages: (1) The user captures the 3D shape and dimensions of the room. (2) The user then uses voice commands and an augmented reality sketching interface to insert objects of interest, such as furniture, artwork, doors and windows. The system recognizes the sketches and add a corresponding 3D model into the scene at the appropriate location. The key contributions of this work are the design of a multi-modal user interface to effectively capture the user's semantic understanding of the scene, a framework for sketch based model retrieval, and the underlying algorithms that process the input to produce useful reconstructions. Finally, I extend the in-situ modeling approach to 3D-aware mobile devices, an emerging class of devices that can more richly sense the 3D nature of our world using depth sensing and self-localization. I propose a novel interactive system to further simplify the process of indoor 3D CAD room modeling on such devices. The proposed system leverages the sensing capabilities of a 3D aware mobile device, recent advances in object recognition, and a novel augmented reality user interface, to author indoor 3D room models in-situ. With a few taps, a user can mark the surface of an object, take a photo, and the system automatically retrieves and places a matching 3D model into the scene, from a large online database -- a modality that proves to be faster, more accurate, and easier than using traditional desktop tools