Bridging the Semantic Gap with SQL Query Logs in Natural Language Interfaces to Databases

A critical challenge in constructing a natural language interface to database (NLIDB) is bridging the semantic gap between a natural language query (NLQ) and the underlying data. Two specific ways this challenge exhibits itself is through keyword mapping and join path inference. Keyword mapping is the task of mapping individual keywords in the original NLQ to database elements (such as relations, attributes or values). It is challenging due to the ambiguity in mapping the user's mental model and diction to the schema definition and contents of the underlying database. Join path inference is the process of selecting the relations and join conditions in the FROM clause of the final SQL query, and is difficult because NLIDB users lack the knowledge of the database schema or SQL and therefore cannot explicitly specify the intermediate tables and joins needed to construct a final SQL query. In this paper, we propose leveraging information from the SQL query log of a database to enhance the performance of existing NLIDBs with respect to these challenges. We present a system Templar that can be used to augment existing NLIDBs. Our extensive experimental evaluation demonstrates the effectiveness of our approach, leading up to 138% improvement in top-1 accuracy in existing NLIDBs by leveraging SQL query log information.Comment: Accepted to IEEE International Conference on Data Engineering (ICDE) 201

Maximizing User Domain Expertise to Clarify Oblique Specifications of Relational Queries

While there is abundant access to data management technology today, working with data is still challenging for the average user. One common means of manipulating data is with SQL on relational databases, but this requires knowledge of SQL as well as the database's schema and contents. Consequently, previous work has proposed oblique query specification (OQS) methods such as natural language or programming-by-example to allow users to imprecisely specify their query intent. These methods, however, suffer from either low precision or low expressivity and, in addition, produce a list of candidate SQL queries that make it difficult for users to select their final target query. My thesis is that OQS systems should maximize user domain expertise to triangulate the user's desired query. First, I demonstrate how to leverage previously-issued SQL queries to improve the accuracy of natural language interfaces. Second, I propose a system allowing users to specify a query with both natural language and programming-by-example. Finally, I develop a system where users provide feedback on system-suggested tuples to select a SQL query from a set of candidate queries generated by an OQS system.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155114/1/cjbaik_1.pd

Geospatial analysis of BECCS deployment potential in the U.S.

Negative emissions from bioenergy with carbon capture and storage (BECCS) has been identified as a potentially important carbon mitigation technology. To date, much of the technical work and discussion on BECCS have focused on land use change and bioenergy potential, while the CCS components – including capacity, injectivity, and location of potential storage sites – have been overlooked. A geospatial analysis of biomass production and storage sites in the U.S. is conducted to discuss BECCS deployment in the U.S. across a range of biomass production scenarios. U.S. Department of Energy provides national annual biomass production data from 2015 to 2040. Extrapolating the production trends across different yield scenarios to 2100 shows average annual CO2 production from agricultural residue and energy crop of 720-1,220 Mt CO2 yr-1 and cumulative production of 27-47 Gt CO2. Considering that the estimated storage capacity in the U.S. is ~3,000 Gt CO2, absolute storage capacity is not likely to be a constraint on BECCS. However, collocation of high-density biomass (\u3e25 MW per 100×100 km2) and high injection rate storage sites (\u3e5 Mt CO2 yr-1) in 2040 yields biomass CO2 injection potential of 140-360 Mt CO2 yr-1. This represents 9-39% of the total biomass feedstock in the U.S. To achieve a biomass CO2 injection potential greater than 360 Mt CO2 yr-1, transportation networks of either biomass or CO2 will be needed. The geospatial analysis conducted in this study highlights the importance of previously overlooked CCS components in global BECCS assessments and provides a framework for future studies. Please click Additional Files below to see the full abstract

Non-invasive assessment of portal hypertension using quantitative magnetic resonance imaging

Background & Aims Hepatic venous pressure gradient (HVPG) measurement is currently the only validated technique to accurately evaluate changes in portal pressure. In this study, we evaluate the use of non-contrast quantitative magnetic resonance imaging (MRI) as a surrogate measure of portal pressure. Methods Thirty patients undergoing HVPG measurement were prospectively recruited. MR parameters of longitudinal relaxation time (T1), perfusion of the liver and spleen (by arterial spin labelling), and blood flow in the portal, splanchnic and collateral circulation (by phase contrast MRI) were assessed. We estimated the liver stiffness measurement (LSM) and enhanced liver fibrosis (ELF) score. The correlation of all non-invasive parameters with HVPG was evaluated. Results The mean (range) HVPG of the patients was 9.8 (1–22) mmHg, and 14 patients (48%) had clinically significant portal hypertension (CSPH, HVPG ⩾10 mmHg). Liver T1 relaxation time, splenic artery and superior mesenteric artery velocity correlated significantly with HVPG. Using multiple linear regression, liver T1 and splenic artery velocity remained as the two parameters in the multivariate model significantly associated with HVPG (R = 0.90, p <0.001). This correlation was maintained in patients with CSPH (R = 0.85, p <0.001). A validation cohort (n = 10) showed this linear model provided a good prediction of HVPG. LSM and ELF score correlated significantly with HVPG in the whole population but the correlation was absent in CSPH. Conclusions MR parameters related to both hepatic architecture and splanchnic haemodynamics correlate significantly with HVPG. This proposed model, confirmed in a validation cohort, could replace the invasive HVPG measurement

Desipramine Inhibits Histamine H1 Receptor-Induced Ca2+ Signaling in Rat Hypothalamic Cells

The hypothalamus in the brain is the main center for appetite control and integrates signals from adipose tissue and the gastrointestinal tract. Antidepressants are known to modulate the activities of hypothalamic neurons and affect food intake, but the cellular and molecular mechanisms by which antidepressants modulate hypothalamic function remain unclear. Here we have investigated how hypothalamic neurons respond to treatment with antidepressants, including desipramine and sibutramine. In primary cultured rat hypothalamic cells, desipramine markedly suppressed the elevation of intracellular Ca2+ evoked by histamine H1 receptor activation. Desipramine also inhibited the histamine-induced Ca2+ increase and the expression of corticotrophin-releasing hormone in hypothalamic GT1-1 cells. The effect of desipramine was not affected by pretreatment with prazosin or propranolol, excluding catecholamine reuptake activity of desipramine as an underlying mechanism. Sibutramine which is also an antidepressant but decreases food intake, had little effect on the histamine-induced Ca2+ increase or AMP-activated protein kinase activity. Our results reveal that desipramine and sibutramine have different effects on histamine H1 receptor signaling in hypothalamic cells and suggest that distinct regulation of hypothalamic histamine signaling might underlie the differential regulation of food intake between antidepressants

Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Background: Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke. Methods: We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515. Findings: Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p&lt;0·0001 for non-inferiority; p=0·0006 for superiority). The incidence of acute pancreatitis (ten patients in the albiglutide group and seven patients in the placebo group), pancreatic cancer (six patients in the albiglutide group and five patients in the placebo group), medullary thyroid carcinoma (zero patients in both groups), and other serious adverse events did not differ between the two groups. There were three (&lt;1%) deaths in the placebo group that were assessed by investigators, who were masked to study drug assignment, to be treatment-related and two (&lt;1%) deaths in the albiglutide group. Interpretation: In patients with type 2 diabetes and cardiovascular disease, albiglutide was superior to placebo with respect to major adverse cardiovascular events. Evidence-based glucagon-like peptide 1 receptor agonists should therefore be considered as part of a comprehensive strategy to reduce the risk of cardiovascular events in patients with type 2 diabetes. Funding: GlaxoSmithKline