GripRank: Bridging the Gap between Retrieval and Generation via the Generative Knowledge Improved Passage Ranking

Retrieval-enhanced text generation, which aims to leverage passages retrieved from a large passage corpus for delivering a proper answer given the input query, has shown remarkable progress on knowledge-intensive language tasks such as open-domain question answering and knowledge-enhanced dialogue generation. However, the retrieved passages are not ideal for guiding answer generation because of the discrepancy between retrieval and generation, i.e., the candidate passages are all treated equally during the retrieval procedure without considering their potential to generate the proper answers. This discrepancy makes a passage retriever deliver a sub-optimal collection of candidate passages to generate answers. In this paper, we propose the GeneRative Knowledge Improved Passage Ranking (GripRank) approach, addressing the above challenge by distilling knowledge from a generative passage estimator (GPE) to a passage ranker, where the GPE is a generative language model used to measure how likely the candidate passages can generate the proper answer. We realize the distillation procedure by teaching the passage ranker learning to rank the passages ordered by the GPE. Furthermore, we improve the distillation quality by devising a curriculum knowledge distillation mechanism, which allows the knowledge provided by the GPE can be progressively distilled to the ranker through an easy-to-hard curriculum, enabling the passage ranker to correctly recognize the provenance of the answer from many plausible candidates. We conduct extensive experiments on four datasets across three knowledge-intensive language tasks. Experimental results show advantages over the state-of-the-art methods for both passage ranking and answer generation on the KILT benchmark.Comment: 11 pages, 4 figure

Interim position emission tomography-computed tomography during multimodality treatment of locally advanced esophageal cancer: a scoping review.

BACKGROUND Among cancers, esophageal cancer (EC) has one of the highest incidences and mortality in Asia. As recognized in many national guidelines, functional imaging performed with position emission tomography is recommended for patients with locally advanced disease. This review evaluated evidence for the use of fluorodeoxyglucose (FDG) interim positron emission tomography (PETint) in bimodality (chemoradiation) and trimodality (chemoradiation followed by surgery) management of locally advanced esophageal cancer (LAEC), with a focus on its prognostic and predictive value. METHODS The MEDLINE database was searched from January 1, 2001, to January 1, 2022, as part of a scoping review. References of selected articles were manually checked to identify other articles meeting the inclusion criteria; only original articles were included, and reviews, guidelines, letters, editorials, and case reports were excluded. RESULTS A total of 63 articles were included in this review. PET-computed tomography (PET-CT) is recognized as having a significant role in the assessment of treatment response. Studies on the predictive PETint suggest that it has a certain value, particularly for early response. Identification of poor responders or nonresponders soon after commencement of multimodality treatment allows for treatment modification. CONCLUSIONS The scoping review indicated variable utility for the prognostic value of PETint. There is a need to improve its accuracy, which can likely be achieved through greater standardization of measurements and reporting and testing as well as combination with other promising measures of response to residual disease

The role of ARL4C in predicting prognosis and immunotherapy drug susceptibility in pan-cancer analysis

Background: ARLs, which are a class of small GTP-binding proteins, play a crucial role in facilitating tumor tumorigenesis and development. ARL4C, a vital member of the ARLs family, has been implicated in the progression of tumors, metastatic dissemination, and development of resistance to therapeutic drugs. Nevertheless, the precise functional mechanisms of ARL4C concerning tumor prognosis and immunotherapy drug susceptibility remain elusive.Methods: By combining the GTEx and TCGA databases, the presence of ARL4C was examined in 33 various types of cancer. Immunohistochemistry and immunofluorescence staining techniques were utilized to confirm the expression of ARL4C in particular tumor tissues. Furthermore, the ESTIMATE algorithm and TIMER2.0 database were utilized to analyze the tumor microenvironment and immune infiltration associated with ARL4C. The TISCH platform facilitated the utilization of single-cell RNA-seq datasets for further analysis. ARL4C-related immune escape was investigated using the TISMO tool. Lastly, drug sensitivity analysis was conducted to assess the sensitivity of different types of tumors to compounds based on the varying levels of ARL4C expression.Results: The study found that ARL4C was highly expressed in 23 different types of cancer. Moreover, the presence of high ARL4C expression was found to be associated with a poor prognosis in BLCA, COAD, KIRP, LGG, and UCEC. Notably, ARL4C was also expressed in immune cells, and its high expression was found to be correlated with cancer immune activation. Most importantly, the drug sensitivity analysis revealed a positive correlation between ARL4C expression and the heightened sensitivity of tumors to Staurosporine, Midostaurin, and Nelarabine.Conclusion: The findings from our study indicate that the expression level of ARL4C may exert an influence on cancer development, prognosis, and susceptibility to immunotherapy drugs. In addition, the involvement of ARL4C in the tumor immune microenvironment has expanded the concept of ARL4C-targeted immunotherapy

HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Pose Dataset with Household Objects in Realistic Scenarios

Estimating the 6D pose of objects is a major 3D computer vision problem. Since the promising outcomes from instance-level approaches, research heads also move towards category-level pose estimation for more practical application scenarios. However, unlike well-established instance-level pose datasets, available category-level datasets lack annotation quality and provided pose quantity. We propose the new category-level 6D pose dataset HouseCat6D featuring 1) Multi-modality of Polarimetric RGB and Depth (RGBD+P), 2) Highly diverse 194 objects of 10 household object categories including 2 photometrically challenging categories, 3) High-quality pose annotation with an error range of only 1.35 mm to 1.74 mm, 4) 41 large-scale scenes with extensive viewpoint coverage and occlusions, 5) Checkerboard-free environment throughout the entire scene, and 6) Additionally annotated dense 6D parallel-jaw grasps. Furthermore, we also provide benchmark results of state-of-the-art category-level pose estimation networks

Progress in the toxicological researches for quantum dots

Quantum dots (QDs) have received more and more attention as a novel example of nanomaterials. Due to their unique fluorescent characteristics, quantum dots have been successfully applied in biotechnology and medicine applications. Recently, the toxicity and the potential environmental effects of QDs have become a research hotspot. In this paper, toxicological effects of QDs are reviewed, and the prospects and research directions are given based on the analysis of this research field

Micro-Dosing of Fine Cohesive Powders Actuated by Pulse Inertia Force

Micro-dosing of fine cohesive powders is the key technology in additive manufacturing and especially in high-potency active pharmaceutical ingredients (HPAPI). However, high accuracy micro-dosing (<5 mg) of fine cohesive powder is less trivial and still remains a challenge because it is difficult to eliminate the aggregation phenomena caused by the strong interparticle cohesive forces (in small capillaries). This paper presents a novel micro-dose method of fine cohesive powders via a pulse inertia force system. A piezoelectric actuator is used to provide a high enough pulse inertia force for a tapered glass nozzle and drive powder particles in the nozzle to be discharged from the nozzle orifice with the help of particle self-gravity. The nozzles with outlet diameters in the range of 100–2000 µm were fabricated via a glass heating process. The α-lactose monohydrate powder is used as the micro-dosing powder. The influences of the tapered nozzle outlet diameter, amplitude of the applied pulse voltage, and angle of the nozzle axis on micro-dosing mass are researched. The minimum mean dose mass is 0.6 mg for a single pulse inertia force. The coefficient of variation of dose mass, which represents the micro-dosing stability, can be controlled below 5% when the dose mass is relatively small

Improved Point Dipole Model for Subwavelength Resolution Scattering Near-Field Optical Microscopy (SNOM)

High-resolution microscopy technique is of significant importance for studying nanomaterials. It is necessary to understand the near-field interaction between the probe and substrate materials in order to get the fine structure of the nanomaterial in the subwavelength scale. The numerical methods such as FDTD, FEM, and MoM are inefficient for the SNOM problems because of the illness of the impedance matrix. The analytic method can only be used for some simple objects such as sphere. Here, a quasianalytical method is developed, in which the analytic formula is refined to adapt to various shapes of the probe approaching the curve of SNOM. By this way, it is helpful in comparing the performance of different probes and giving us a direction to design a new type probe in SNOM. As an application, the developed method is used to study the contrast in the SNOM for the interface between the two different surfaces that have different materials and topography

An Improved Directional Relay Adapted to a Distribution Network with IIG Integration

The integration of distributed generation (DG) into a distribution network changes the network’s topology. Three-stage current protection for a radial distribution network cannot meet the requirements of relay protection for a distribution network with DG. A directional relay that is based on the positive sequence fault component (PSFC) can effectively identify faults in the positive and negative directions and can be used to solve the adaptability problem with three-stage current protection in a multi-source distribution network. However, DG and the traditional generators have different fault characteristics and are affected by different control strategies, which may lower the sensitivity of a directional relay based on the PSFC or even cause mal-operation. Focusing on this problem, this paper proposes an improved directional relay that is adapted to a distribution network with inverter-interfaced generation (IIG) integration. The improved scheme divides the operation zone of the directional relay based on the PSFC into sensitive and insensitive areas. If the result of a phase comparison is located in the insensitive area, further identification is needed according to a comparison of the current amplitudes. Simulation experiments are carried out based on PSCAD/EMTDC, and their results verify the correctness of the proposed scheme