Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies

Log data can reveal valuable information about how users interact with web search services, what they want, and how satisfied they are. However, analyzing user intents in log data is not easy, especially for new forms of web search such as AI-driven chat. To understand user intents from log data, we need a way to label them with meaningful categories that capture their diversity and dynamics. Existing methods rely on manual or ML-based labeling, which are either expensive or inflexible for large and changing datasets. We propose a novel solution using large language models (LLMs), which can generate rich and relevant concepts, descriptions, and examples for user intents. However, using LLMs to generate a user intent taxonomy and apply it to do log analysis can be problematic for two main reasons: such a taxonomy is not externally validated, and there may be an undesirable feedback loop. To overcome these issues, we propose a new methodology with human experts and assessors to verify the quality of the LLM-generated taxonomy. We also present an end-to-end pipeline that uses an LLM with human-in-the-loop to produce, refine, and use labels for user intent analysis in log data. Our method offers a scalable and adaptable way to analyze user intents in web-scale log data with minimal human effort. We demonstrate its effectiveness by uncovering new insights into user intents from search and chat logs from Bing

LDRD Project 52523 final report :Atomic layer deposition of highly conformal tribological coatings.

Friction and wear are major concerns in the performance and reliability of micromechanical (MEMS) devices. While a variety of lubricant and wear resistant coatings are known which we might consider for application to MEMS devices, the severe geometric constraints of many micromechanical systems (high aspect ratios, shadowed surfaces) make most deposition methods for friction and wear-resistance coatings impossible. In this program we have produced and evaluate highly conformal, tribological coatings, deposited by atomic layer deposition (ALD), for use on surface micromachined (SMM) and LIGA structures. ALD is a chemical vapor deposition process using sequential exposure of reagents and self-limiting surface chemistry, saturating at a maximum of one monolayer per exposure cycle. The self-limiting chemistry results in conformal coating of high aspect ratio structures, with monolayer precision. ALD of a wide variety of materials is possible, but there have been no studies of structural, mechanical, and tribological properties of these films. We have developed processes for depositing thin (<100 nm) conformal coatings of selected hard and lubricious films (Al2O3, ZnO, WS2, W, and W/Al{sub 2}O{sub 3} nanolaminates), and measured their chemical, physical, mechanical and tribological properties. A significant challenge in this program was to develop instrumentation and quantitative test procedures, which did not exist, for friction, wear, film/substrate adhesion, elastic properties, stress, etc., of extremely thin films and nanolaminates. New scanning probe and nanoindentation techniques have been employed along with detailed mechanics-based models to evaluate these properties at small loads characteristic of microsystem operation. We emphasize deposition processes and fundamental properties of ALD materials, however we have also evaluated applications and film performance for model SMM and LIGA devices

The contribution of X-linked coding variation to severe developmental disorders

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders

The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Secondary Stakeholder Influence on CSR Disclosure: An Application of Stakeholder Salience Theory

The aim of this study is to analyse how secondary stakeholders influence managerial decision-making on Corporate Social Responsibility (CSR) disclosure. Based on stakeholder salience theory, we empirically investigate whether differences in environmental disclosure among companies are systematically related to differences in the level of power, urgency and legitimacy of the environmental non-governmental organisations (NGOs) with which these companies are confronted. Using proprietary archival data for an international sample of 199 large companies, our results suggest that differences in environmental disclosures between companies are mainly associated with differences between their environmental stakeholders’ legitimacy. The effects of power and urgency are of an indirect nature, as they are mediated by legitimacy. This study improves our understanding of CSR disclosure by demonstrating that, next to the well-documented effect of company characteristics, stakeholder characteristics are also important. Besides, it provides scarce empirical evidence that not only primary stakeholders, but also secondary stakeholders are influential with regards to management decision-making. And more specifically, it offers insight into why some stakeholder groups are better able to influence disclosure decisions than other. The results also have important practical implications for managers of both environmental NGOs and large companies. For managers of environmental NGOs the results provide evidence of the most successful tactics for having their environmental information demands satisfied by companies. For company management the results provide insights into the most important stakeholder characteristics, on the basis of which they may develop strategies for proactively disclosing environmental information

Observation of the B0 → ρ0ρ0 decay from an amplitude analysis of B0 → (π+π−)(π+π−) decays

Proton–proton collision data recorded in 2011 and 2012 by the LHCb experiment, corresponding to an integrated luminosity of 3.0 fb−1 , are analysed to search for the charmless B0→ρ0ρ0 decay. More than 600 B0→(π+π−)(π+π−) signal decays are selected and used to perform an amplitude analysis, under the assumption of no CP violation in the decay, from which the B0→ρ0ρ0 decay is observed for the first time with 7.1 standard deviations significance. The fraction of B0→ρ0ρ0 decays yielding a longitudinally polarised final state is measured to be fL=0.745−0.058+0.048(stat)±0.034(syst) . The B0→ρ0ρ0 branching fraction, using the B0→ϕK⁎(892)0 decay as reference, is also reported as B(B0→ρ0ρ0)=(0.94±0.17(stat)±0.09(syst)±0.06(BF))×10−6