Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation

The Differentiable Search Index (DSI) is an emerging paradigm for information retrieval. Unlike traditional retrieval architectures where index and retrieval are two different and separate components, DSI uses a single transformer model to perform both indexing and retrieval. In this paper, we identify and tackle an important issue of current DSI models: the data distribution mismatch that occurs between the DSI indexing and retrieval processes. Specifically, we argue that, at indexing, current DSI methods learn to build connections between the text of long documents and the identifier of the documents, but then retrieval of document identifiers is based on queries that are commonly much shorter than the indexed documents. This problem is further exacerbated when using DSI for cross-lingual retrieval, where document text and query text are in different languages. To address this fundamental problem of current DSI models, we propose a simple yet effective indexing framework for DSI, called DSI-QG. When indexing, DSI-QG represents documents with a number of potentially relevant queries generated by a query generation model and re-ranked and filtered by a cross-encoder ranker. The presence of these queries at indexing allows the DSI models to connect a document identifier to a set of queries, hence mitigating data distribution mismatches present between the indexing and the retrieval phases. Empirical results on popular mono-lingual and cross-lingual passage retrieval datasets show that DSI-QG significantly outperforms the original DSI model.Comment: 11 page

Typos-aware Bottlenecked Pre-Training for Robust Dense Retrieval

Current dense retrievers (DRs) are limited in their ability to effectively process misspelled queries, which constitute a significant portion of query traffic in commercial search engines. The main issue is that the pre-trained language model-based encoders used by DRs are typically trained and fine-tuned using clean, well-curated text data. Misspelled queries are typically not found in the data used for training these models, and thus misspelled queries observed at inference time are out-of-distribution compared to the data used for training and fine-tuning. Previous efforts to address this issue have focused on \textit{fine-tuning} strategies, but their effectiveness on misspelled queries remains lower than that of pipelines that employ separate state-of-the-art spell-checking components. To address this challenge, we propose ToRoDer (TypOs-aware bottlenecked pre-training for RObust DEnse Retrieval), a novel re-training strategy for DRs that increases their robustness to misspelled queries while preserving their effectiveness in downstream retrieval tasks. ToRoDer utilizes an encoder-decoder architecture where the encoder takes misspelled text with masked tokens as input and outputs bottlenecked information to the decoder. The decoder then takes as input the bottlenecked embeddings, along with token embeddings of the original text with the misspelled tokens masked out. The pre-training task is to recover the masked tokens for both the encoder and decoder. Our extensive experimental results and detailed ablation studies show that DRs pre-trained with ToRoDer exhibit significantly higher effectiveness on misspelled queries, sensibly closing the gap with pipelines that use a separate, complex spell-checker component, while retaining their effectiveness on correctly spelled queries.Comment: 10 pages, accepted at SIGIR-A

Numerical Investigation of the Transient Behavior of a Hot Gas Duct under Rapid Depressurization

A hot gas duct is an indispensable component for the nuclear-process heat applications of the Very-High-Temperature Reactor (VHTR), which has to fulfill three requirements: to withstand high temperature, high pressure, and large pressure transient. In this paper, numerical investigation of pressure transient is performed for a hot gas duct under rapid depressurization. System depressurization imposes an imploding pressure differential on the internal structural elements of a hot gas duct, the structural integrity of which is susceptible to being damaged. Pressure differential and its imposed duration, which are two key factors to evaluate the damage severity of a hot gas duct under depressurization, are examined in regard to depressurization rate and insulation packing tightness. It is revealed that depressurization rate is a decisive parameter for controlling the pressure differential and its duration, whereas insulating-packing tightness has little effect on them

Submarine groundwater discharge in Dongshan Bay, China: A master regulator of nutrients in spring and potential national significance of small bays

Despite over 90% of China’s coastal bays have an area less than 500 km2, the geochemical effects of SGD on those ecosystems are ambiguous. Based on mapping and time-series observations of Ra isotopes and nutrients, a case study of small bays (<500 km2), we revealed that submarine groundwater discharge (SGD) predominately regulated the distribution of nutrients and fueled algal growth in Dongshan Bay, China. On the bay-wide scale, the SGD rate was estimated to be 0.048 ± 0.022 m day−1 and contributed over 95% of the nutrients. At the time-series site where the bay-wide highest Ra activities in the bottom water marked an SGD hotspot with an average rate an order of magnitude greater, the maximum chlorophyll concentration co-occurred, suggesting that SGD may support the algal bloom. The ever-most significant positive correlations between 228Ra and nutrients throughout the water column (P< 0.01, R2 > 0.90 except for soluble reactive phosphorus in the surface) suggested the predominance of SGD in controlling nutrient distribution in the bay. Extrapolated to a national scale, the SGD-carried dissolved inorganic nitrogen flux in small bays was twice as much as those in large bays (>2,000 km2). Thus, the SGD-carried nutrients in small bays merit immediate attention in environmental monitoring and management

DEFEM Method and Its Application in Pebble Flows

Based on the concept of embedded discrete elements (EDEs), the discrete element-embedded finite element model (DEFEM) is extended in this work. The new method can be used to calculate the motion and stress variation of particles. This work discusses its application in granular flow simulation for particle motions with small deformations. The updated Lagrangian finite element method is used to obtain the coupling solution of the internal stress and the overall motion of particles in the DEFEM. The computation of deformation displacement is based on the concepts of displacement decomposition (translational and rotational motions and deformation displacement). The deformation displacement is the difference between particles and template particles [rigid body, using the discrete element method (DEM) to calculate translational and rotational displacements]. It is used to calculate the dynamic stress distribution of particles and the internal force of the node. Therefore, it has a wide scope of application (for example, it can be extended to non-spherical particles). The software validation proves the accuracy of this method. The application of the DEFEM in the accumulation process of particles is given. The motion characteristics and deformation of particles are discussed, and the stress distribution and force chain structure in particle accumulation are obtained

One-Pot Visual Detection of African Swine Fever Virus Using CRISPR-Cas12a

African swine fever virus (ASFV) is a leading cause of worldwide agricultural loss. ASFV is a highly contagious and lethal disease for both domestic and wild pigs, which has brought enormous economic losses to a number of countries. Conventional methods, such as general polymerase chain reaction and isothermal amplification, are time-consuming, instrument-dependent, and unsatisfactorily accurate. Therefore, rapid, sensitive, and field-deployable detection of ASFV is important for disease surveillance and control. Herein, we created a one-pot visual detection system for ASFV with CRISPR/Cas12a technology combined with LAMP or RPA. A mineral oil sealing strategy was adopted to mitigate sample cross-contamination between parallel vials during high-throughput testing. Furthermore, the blue fluorescence signal produced by ssDNA reporter could be observed by the naked eye without any dedicated instrument. For CRISPR-RPA system, detection could be completed within 40 min with advantageous sensitivity. While CRISPR-LAMP system could complete it within 60 min with a high sensitivity of 5.8 × 102 copies/μl. Furthermore, we verified such detection platforms display no cross-reactivity with other porcine DNA or RNA viruses. Both CRISPR-RPA and CRISPR-LAMP systems permit highly rapid, sensitive, specific, and low-cost Cas12a-mediated visual diagnostic of ASFV for point-of-care testing (POCT) applications

A discussion on the validity domain of the weighted residuals model including the Marangoni effect for a thin film flowing down a uniformly heated plate

In this paper, the validity of the Weighted Residuals Model (WRM), including the Marangoni effect, is investigated through linear stability analyses and two-dimensional nonlinear numerical simulations. The linear stability analyses with the WRM show that the model's accuracy decreases nearly linearly with the Marangoni number for each Reynolds number and achieves a maximum at approximately ${\rm {Re}} = 4$ for each Marangoni number. This is quite different from the isothermal case, for which the error increases monotonically with the Reynolds number and remains small for small-to-moderate Reynolds numbers. This is very important for application of the WRM but has yet to be reported or investigated. The effects of the Reynolds number and Marangoni number on the nonlinear evolution of film layers are then investigated through numerical simulations. At small Reynolds number, it is found that the error caused by the Marangoni effect in predicting the phase speed can be ignored if the Marangoni number is small ( ${\rm {Ma}}=5$ ) or makes the wave in the spatial numerical simulation considerably out of phase if the Marangoni number is large ( ${\rm {Ma}}=50$ ). On the other hand, the saturation states can be generated by the WRM no matter whether the Marangoni number is small or large. When the Reynolds number is increased to a moderate value and the Marangoni number is taken as zero, it is found that the saturation wave produced by the WRM is very similar to the experimental one, except for the amplitude of the wave being somewhat larger and the wave speed as well as the wavelength being slightly smaller. Hence, it can be inferred that the WRM predicts the saturation waves well for small-to-moderate Reynolds numbers if the Marangoni numbers are limited to a small range depending on the Reynolds numbers