15064 research outputs found
Sort by
Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization
No full textMotivated by online decision making in time-varying combinatorial environments, we study the problem of transforming offline algorithms to their online counterparts. We focus on offline combinatorial problems that are amenable to a constant factor approximation using a greedy algorithm that is robust to local errors. For such problems, we provide a general framework that efficiently transforms offline robust greedy algorithms to online ones using Blackwell approachability. We show that the resulting online algorithms have O(T^0.5) (approximate) regret under the full information setting. We further introduce a bandit extension of Blackwell approachability that we call Bandit Blackwell approachability. We leverage this notion to transform greedy robust offline algorithms into a O(T^{2/3}) (approximate) regret in the bandit setting. Demonstrating the flexibility of our framework, we apply our offline-to-online transformation to several problems at the intersection of revenue management, market design, and online optimization, including product ranking optimization in online platforms, reserve price optimization in auctions, and submodular maximization. We also extend our reduction to greedy-like first-order methods used in continuous optimization, such as those used for maximizing continuous strong DR monotone submodular functions subject to convex constraints. We show that our transformation, when applied to these applications, leads to new regret bounds or improves the current known bounds. We complement our theoretical studies by conducting numerical simulations for two of our applications, in both of which we observe that the numerical performance of our transformations outperforms the theoretical guarantees in practical instances
Theoretical modeling of hepatitis C acute infection in liver-humanized mice support pre-clinical assessment of candidate viruses for controlled-human-infection studies
Get PDFDesigning and carrying out a controlled human infection (CHI) model for hepatitis C virus (HCV) is critical for vaccine development. However, key considerations for a CHI model protocol include understanding of the earliest viral-host kinetic events during the acute phase and susceptibility of the viral isolate under consideration for use in the CHI model to antiviral treatment before any infections in human volunteers can take place. Humanized mouse models lack adaptive immune responses but provide a unique opportunity to obtain quantitative understanding of early HCV kinetics and develop mathematical models to further understand viral and innate immune response dynamics during acute HCV infection. We show that the models reproduce the measured HCV kinetics in humanized mice, which are consistent with early acute HCV-host dynamics in immunocompetent chimpanzees. Our findings suggest that humanized mice are well-suited to support development of a CHI model. In-silico and in-vivo modeling estimates provide a starting point to characterize candidate viruses for testing in CHI model studies
Effect of sign language learning on temporal resolution of visual attention
Get PDFThe visual environment of sign language users is markedly distinct in its spatiotemporal parameters compared to that of non-signers. Although the importance of temporal and spectral resolution in the auditory modality for language development is well established, the spectrotemporal parameters of visual attention necessary for sign language comprehension remain less understood. This study investigates visual temporal resolution in learners of American Sign Language (ASL) at various stages of acquisition to determine how experience with sign language affects perceptual sampling. Using a flicker paradigm, we assessed the accuracy of identifying out-of-phase visual flicker objects at frequencies up to 60 Hz. Our findings reveal that third-semester ASL learners show increased accuracy in detecting high-frequency flicker, indicating enhanced temporal resolution. Interestingly, as learners achieve higher proficiency in ASL, their perceptual sampling reverts to typical levels, likely because of a shift toward predictive processing mechanisms in sign language comprehension. These results suggest that the temporal resolution of visual attention is malleable and can be influenced by the process of learning a visual language
The unequal adoption of ChatGPT exacerbates existing inequalities among workers
Get PDFWe study the adoption of ChatGPT, the icon of Generative AI, using a large-scale survey linked to comprehensive register data in Denmark. Surveying 18,000 workers from 11 exposed occupations, we document that ChatGPT is widespread, especially among younger and less-experienced workers. However, substantial inequalities have emerged. Women are 16 percentage points less likely to have used the tool for work. Furthermore, despite its potential to lift workers with less expertise, users of ChatGPT earned slightly more already before its arrival, even given their lower tenure. Workers see a substantial productivity potential in ChatGPT but are often hindered by employer restrictions and a perceived need for training
Social media addiction and borderline personality disorder: A survey study
Get PDFBackground and aims: Borderline personality disorder (BPD) is a serious and difficult to treat psychiatric condition characterized by affective and interpersonal instability, impulsivity, and self-image disturbances. Although the relationship between BPD and substance use disorders has been well-established, there has been considerably less research regarding behavioral addictions in this population. The purpose of this study is to determine the prevalence of social media addiction (SMA) among individuals with BPD and to explore whether it is related to aspects of disorder symptomology. Methods: 300 adults completed an online survey via Prolific. Individuals completed the McLean Screening Instrument for BPD (MSI-BPD), along with the Bergen Social Media Addiction Scale (BSMAS). Additionally, all participants reported how often they use social media for the following reasons: distraction from interpersonal problems, reassurance seeking, self-confidence issues, and anger/revenge. Results: Of the 289 subjects that completed all measures, 38 (13.1%) screened positive for BPD. Individuals screening positive for BPD were more likely to meet criteria for SMA than controls, and they were more likely to report using social media for interpersonal distraction, reassurance seeking, self-confidence issues, and anger/revenge seeking than controls. Among individuals with BPD, SMA was positively associated with the frequency of each of these behaviors, except for anger/revenge seeking. Discussion and conclusion: The results of this study demonstrate that SMA is common among the BPD population and may be related to aspects of disorder symptomology. Whether SMA worsens BPD symptoms or whether addressing SMA could lead to improvements in the BPD remains to be seen and is an important area for future research.</p
Multivalued Wess-Zumino-Novikov functional and chiral anomaly in hydrodynamics
Get PDFWe present a hydrodynamic framework derived from the action of a perfect fluid, modified by the hydrodynamic analog of Novikov’s multivalued functional. This modification introduces spin degrees of freedom into the fluid. The structure closely resembles the Abelian version of the Wess-Zumino functional, commonly applied in field theories with chiral anomalies. The deformation incorporates transport properties of Weyl fermions and, in the case of a charged fluid, exhibits the chiral anomaly. It is also consistent with Onsager’s semiclassical quantization of circulation. Additionally, we discuss the hydrodynamic analog of instantons and related topological invariants
New OMB’s Race and Ethnicity Standards Will Affect How Americans Self-Identify
Get PDFIn March 2024, the U.S. Office of Management and Budget (OMB) approved major changes to the ethnic and racial self-identification questions used by all federal agencies, including the U.S. Census Bureau. These modifications include merging the separate race and Hispanic ethnicity questions into a single combined question and adding a Middle Eastern and North African category. Government officials and researchers have requested evidence on how Americans might react to these changes. We conducted a survey experiment with a nationally representative sample of 7,350 adult Americans. Participants were randomly assigned to answer either the existing separate race and ethnicity questions or a combined question proposed by the OMB. We find that the combined question decreases the percentage of Americans identifying as white and as some other race. We identify the key mechanism driving these effects: Hispanics decrease their identification in other categories when a Hispanic category is available in the combined question format. This results in statistically significant decreases in key minority populations, including Afro-Latinos and indigenous Latinos
Prognostic, biological, and structural implications of <i>FLT3</i>-JMD point mutations in acute myeloid leukemia: An analysis of Alliance studies
Get PDFThe FLT3 gene frequently undergoes mutations in acute myeloid leukemia (AML), with internal tandem duplications (ITD) and tyrosine kinase domain (TKD) point mutations (PMs) being most common. Recently, PMs and deletions in the FLT3 juxtamembrane domain (JMD) have been identified, but their biological and clinical significance remains poorly understood. We analyzed 1660 patients with de novo AML and found FLT3-JMD mutations, mostly PMs, in 2% of the patients. Patients with FLT3-JMD mutations had a higher relapse rate and shorter disease-free survival than those with FLT3-TKD, whereas their relapse rate, disease-free and overall survival were not significantly different from those of FLT3-ITD-positive patients. In vitro experiments showed that FLT3-JMD PMs transformed hematopoietic cells and responded well to type I and II FLT3 inhibitors. Molecular dynamics simulations were used to explore the conformational changes of JMD PMs relative to wild-type FLT3. These mutations exhibited constrained domain motions with wider gate openings, potentially enhancing drug binding. Altered residue interactions and structural changes shed light on their unique functional mechanisms, with increased allosteric pathways suggesting reduced interactions with other residues. We conclude that patients with FLT3-JMD PMs represent uncommon but important subset with distinct molecular and biological features, and may benefit from FLT3 inhibitors
Unlocking Mesoscopic Disorder in Graphitic Carbon with Spectroelectrochemistry
Get PDFIntrinsic structural and oxidic defects activate graphitic carbon electrodes towards electrochemical reactions underpinning energy conversion and storage technologies. Yet, these defects can also disrupt the long-range and periodic arrangement of carbon atoms, thus, the characterization of graphitic carbon electrodes necessitates in-situ atomistic differentiation of graphitic regions from mesoscopic bulk disorder. Here, we leverage the combined techniques of in-situ attenuated total reflectance infrared spectroscopy and first-principles calculations to reveal that graphitic carbon electrodes exhibit electric-field dependent infrared activity that is sensitive to the bulk mesoscopic intrinsic disorder. With this platform, we identify graphitic regions from amorphous domains by discovering that they demonstrate opposing electric-field-dependent infrared activity under electrochemical conditions. Our work provides a roadmap for identifying mesoscopic disorder in bulk carbon materials under potential bias
Cell Recognition in 3D+t Microscopy Image Sequences with Machine Learning
No full textThe simple model organism C. elegans provides an ideal platform for addressing critical questions in neuroscience, developmental biology, and systems biology. By tracing the cell lineage --- the developmental history of cells in C. elegans --- researchers can uncover profound insights into cellular behaviors such as division, migration, fate differentiation, signaling, and gene expression patterns, with significant implications for understanding higher organisms, including humans. The most common approach for lineage tracing in C. elegans is cell tracking. However, this approach has notable limitations, including resource inefficiency, computational intensity, and the need for extensive manual labor as it involves processing all imaging frames back to the four-cell stage of embryonic development and demands time-consuming manual annotation and correction. In this thesis, I address the challenges of cell lineage tracing --- or equivalently, the problem of cell recognition --- from novel perspectives, proposing two innovative methods to overcome these limitations with machine learning. First, we demonstrated that nuclei can be accurately detected and segmented throughout 3D+t imaging sequences of C. elegans embryos using a well-trained deep learning model. Building on this, we approached the cell recognition problem using point-cloud representations of nuclei, rather than raw images. Leveraging the invariant lineage of C. elegans, we developed two methods for cell recognition in pre-twitching embryos that require less information and significantly reduce computational costs and resources compared to cell tracking approaches. The first method is a machine learning-based cell classification approach that predicts cellular identities using spatiotemporal features from a cell's available frames. This approach achieved exceptional performance, exceeding 91% accuracy, and directly predicts cell names. The second method is an atlas/template-based cell recognition approach that identifies cells from a single image frame using point-cloud registration. This method achieved high accuracy >= 80% for most pre-twitching time points without looking at any additional image frames or requiring extra information. These two methods open new avenues for cell recognition in C. elegans embryos beyond cell tracking, offering significant improvements in efficiency and applicability. We envision that these methods will benefit the C. elegans research community and inspire further advancements in the field