Constructing Tree-based Index for Efficient and Effective Dense Retrieval

Recent studies have shown that Dense Retrieval (DR) techniques can significantly improve the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness, the application of DR is still limited. In contrast to statistic retrieval models that rely on highly efficient inverted index solutions, DR models build dense embeddings that are difficult to be pre-processed with most existing search indexing systems. To avoid the expensive cost of brute-force search, the Approximate Nearest Neighbor (ANN) algorithm and corresponding indexes are widely applied to speed up the inference process of DR models. Unfortunately, while ANN can improve the efficiency of DR models, it usually comes with a significant price on retrieval performance. To solve this issue, we propose JTR, which stands for Joint optimization of TRee-based index and query encoding. Specifically, we design a new unified contrastive learning loss to train tree-based index and query encoder in an end-to-end manner. The tree-based negative sampling strategy is applied to make the tree have the maximum heap property, which supports the effectiveness of beam search well. Moreover, we treat the cluster assignment as an optimization problem to update the tree-based index that allows overlapped clustering. We evaluate JTR on numerous popular retrieval benchmarks. Experimental results show that JTR achieves better retrieval performance while retaining high system efficiency compared with widely-adopted baselines. It provides a potential solution to balance efficiency and effectiveness in neural retrieval system designs.Comment: 10 pages, accepted at SIGIR 202

An exploration of the correlations between seven psychiatric disorders and the risks of breast cancer, breast benign tumors and breast inflammatory diseases: Mendelian randomization analyses

BackgroundPrevious observational studies have showed that certain psychiatric disorders may be linked to breast cancer risk, there is, however, little understanding of relationships between mental disorders and a variety of breast diseases. This study aims to investigate if mental disorders influence the risks of overall breast cancer, the two subtypes of breast cancer (ER+ and ER-), breast benign tumors and breast inflammatory diseases.MethodsDuring our research, genome-wide association study (GWAS) data for seven psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, post-traumatic stress disorder, panic disorder, obsessive-compulsive disorder and anorexia nervosa) from the Psychiatric Genomics Consortium (PGC) and the UK Biobank were selected, and single-nucleotide polymorphisms (SNPs) significantly linked to these mental disorders were identified as instrumental variables. GWAS data for breast diseases came from the Breast Cancer Association Consortium (BCAC) as well as the FinnGen consortium. We performed two-sample Mendelian randomization (MR) analyses and multivariable MR analyses to assess these SNPs’ effects on various breast diseases. Both heterogeneity and pleiotropy were evaluated by sensitivity analyses.ResultsWhen the GWAS data of psychiatric disorders were derived from the PGC, our research found that schizophrenia significantly increased the risks of overall breast cancer (two-sample MR: OR 1.05, 95%CI [1.03-1.07], p = 3.84 × 10−6; multivariable MR: OR 1.06, 95%CI [1.04-1.09], p = 2.34 × 10−6), ER+ (OR 1.05, 95%CI [1.02-1.07], p = 5.94 × 10−5) and ER- (two-sample MR: OR 1.04, 95%CI [1.01-1.07], p = 0.006; multivariable MR: OR 1.06, 95%CI [1.02-1.10], p = 0.001) breast cancer. Nevertheless, major depressive disorder only showed significant positive association with overall breast cancer (OR 1.12, 95%CI [1.04-1.20], p = 0.003) according to the two-sample MR analysis, but not in the multivariable MR analysis. In regards to the remainder of the mental illnesses and breast diseases, there were no significant correlations. While as for the data from the UK Biobank, schizophrenia did not significantly increase the risk of breast cancer.ConclusionsThe correlation between schizophrenia and breast cancer found in this study may be false positive results caused by underlying horizontal pleiotropy, rather than a true cause-and-effect relationship. More prospective studies are still needed to be carried out to determine the definitive links between mental illnesses and breast diseases

Effects of yttrium on the microstructure, texture, and magnetic properties of non-oriented 6.5 wt% Si steel sheets by a rolling process

Non-oriented 6.5 wt% Si steel thin sheets with three different yttrium (Y) contents (0, 0.012, and 0.03 wt%) were prepared by hot rolling, warm rolling, intermediate annealing, cold rolling and final annealing processes. The effects of the Y content on the microstructure, texture, and magnetic properties of cold-rolled 6.5 wt% Si steel sheets were studied by optical microscopy, scanning electron microscopy, energy-dispersive x-ray spectroscopy, and electron backscattered diffraction. The results showed that the sample with 0.012 wt% Y had the lowest volume fraction of inclusions, and Y played a role in purifying steel. The final average grain size of sheets decreased upon increasing the Y content. As the Y content increased, the {100} texture continuously weakened, and the overall intensity of the η (〈100〉//RD) texture increased first and then decreased, while the intensity of the detrimental γ (〈111〉//ND) texture decreased first and then increased. Adding an appropriate amount of Y optimized the recrystallization texture by promoting the occurrence of shear bands, which provided more nucleation sites for η - fiber oriented grains. When the Y content was 0.012 wt%, the magnetic induction B _50 reached the maximum (1.64655 T) due to the enhanced η texture and weakened γ texture. The sample with 0.012 wt% Y showed the lowest core loss at high frequencies (>5 kHz) because of the favorable grain size. The addition of excess Y increased the number of inclusions and increased γ -fiber oriented grain nucleation, which deteriorated the magnetic properties of non-oriented 6.5 wt%Si steel

Sintering Behavior and Mechanical Properties of Mullite Fibers/Hydroxyapatite Ceramic

The effect of fiber content and sintering temperature on sintering behavior and mechanical properties of mullite fibers/hydroxyapatite composites was studied. The composites were fabricated by hydrothermal synthesis and pressureless sintering. The amount of fibers was varied from 5 wt % to 15 wt % through hydrothermal synthesis, mullite fibers and hydroxyapatite composite powders were subsequently sintered at temperatures of 1150, 1250, and 1350 °C. The composites presented a more perturbed structure by increasing fiber content. Moreover, the composites experienced pore coalescence and exhibited a dense microstructure at elevated temperature. X-ray diffraction indicated that the composites underwent various chemical reactions and generated silicate glasses. The generation of silicate glasses increased the driving force of particle rearrangement and decreased the number of pores, which promoted densification of the composites. Densification typically leads to increased hardness and bending strength. The study proposes a densification mechanism and opens new insights into the sintering properties of these materials

Biogas upgrading by CO₂ removal with a highly selective natural amino acid salt in gas–liquid membrane contactor

For biogas upgrading, a natural amino acid salt, potassium l-argininate (PA) is studied in a membrane contactor to capture CO₂ from biogas. CO₂ removal performance in terms of the overall volumetric gas phase mass transfer coefficient, membrane selectivity towards CO₂ and the economic cost factor is systematically investigated. It is shown that PA is a highly CO₂ selective absorbent and has a better affinity towards CO₂ than monoethanolamine (MEA). The highest CH₄ content in the upgraded biogas can reach about 99.15 vol% by using PA, fully meeting the requirement of biogas upgrading. Furthermore, lower solvent concentration, lower liquid velocity and higher reaction temperature may be adopted when using PA in comparison to MEA. PA also has a better flexibility to the change of CO₂ partial pressure and biogas flow rate than MEA. Regarding the economic cost factor of membrane process, CO₂ loading of the lean PA solution can be optimized to 0.69–0.78 mol/mol as the suitable range. Moreover, CO₂ removal performance of l-arginine (ARG) is also explored. Due to the large amounts of bicarbonate other than carbamate formed in CO₂-rich ARG solution, ARG has a lower biogas upgrading capability than diethanolamine (DEA) but higher than triethanolamine (TEA).11 page(s