MESH : a flexible manifold-embedded semantic hashing for cross-modal retrieval

Hashing based methods for cross-modal retrieval has been widely explored in recent years. However, most of them mainly focus on the preservation of neighborhood relationship and label consistency, while ignore the proximity of neighbors and proximity of classes, which degrades the discrimination of hash codes. And most of them learn hash codes and hashing functions simultaneously, which limits the flexibility of algorithms. To address these issues, in this article, we propose a two-step cross-modal retrieval method named Manifold-Embedded Semantic Hashing (MESH). It exploits Local Linear Embedding to model the neighborhood proximity and uses class semantic embeddings to consider the proximity of classes. By so doing, MESH can not only extract the manifold structure in different modalities, but also can embed the class semantic information into hash codes to further improve the discrimination of learned hash codes. Moreover, the two-step scheme makes MESH flexible to various hashing functions. Extensive experimental results on three datasets show that MESH is superior to 10 state-of-the-art cross-modal hashing methods. Moreover, MESH also demonstrates superiority on deep features compared with the deep cross-modal hashing method. © 2013 IEEE

No Provisioned Concurrency: Fast RDMA-codesigned Remote Fork for Serverless Computing

Serverless platforms essentially face a tradeoff between container startup time and provisioned concurrency (i.e., cached instances), which is further exaggerated by the frequent need for remote container initialization. This paper presents MITOSIS, an operating system primitive that provides fast remote fork, which exploits a deep codesign of the OS kernel with RDMA. By leveraging the fast remote read capability of RDMA and partial state transfer across serverless containers, MITOSIS bridges the performance gap between local and remote container initialization. MITOSIS is the first to fork over 10,000 new containers from one instance across multiple machines within a second, while allowing the new containers to efficiently transfer the pre-materialized states of the forked one. We have implemented MITOSIS on Linux and integrated it with FN, a popular serverless platform. Under load spikes in real-world serverless workloads, MITOSIS reduces the function tail latency by 89% with orders of magnitude lower memory usage. For serverless workflow that requires state transfer, MITOSIS improves its execution time by 86%.Comment: To appear in OSDI'2

Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering

Recently, the development of large language models (LLMs) has attracted wide attention in academia and industry. Deploying LLMs to real scenarios is one of the key directions in the current Internet industry. In this paper, we present a novel pipeline to apply LLMs for domain-specific question answering (QA) that incorporates domain knowledge graphs (KGs), addressing an important direction of LLM application. As a real-world application, the content generated by LLMs should be user-friendly to serve the customers. Additionally, the model needs to utilize domain knowledge properly to generate reliable answers. These two issues are the two major difficulties in the LLM application as vanilla fine-tuning can not adequately address them. We think both requirements can be unified as the model preference problem that needs to align with humans to achieve practical application. Thus, we introduce Knowledgeable Preference AlignmenT (KnowPAT), which constructs two kinds of preference set called style preference set and knowledge preference set respectively to tackle the two issues. Besides, we design a new alignment objective to align the LLM preference with human preference, aiming to train a better LLM for real-scenario domain-specific QA to generate reliable and user-friendly answers. Adequate experiments and comprehensive with 15 baseline methods demonstrate that our KnowPAT is an outperforming pipeline for real-scenario domain-specific QA with LLMs. Our code is open-source at https://github.com/zjukg/KnowPAT.Comment: Work in progress. Code is available at https://github.com/zjukg/KnowPA

Algorithm to changing bistatic imaging geometric model for TH-2 satellite

Imaging geometric model of master and slave satellite directly affects many steps in InSAR data processsing, such as complex image rough registration, flat plain effect removing, InSAR location, baseline calibration, block adjustment and ortho-rectification. In order to keep unified algorithm in imageing, both master and slave satellite of TH-2 use bistatic imaging geometric model. For complex image rough registration, flat plain effect removing and InSAR location step, bistatic imaging geometric model just increase algorithm complexity, but for baseline calibration, it brings new chanlleges. On one hand, most current baseline calibration algorithms are based on monostatic imaging geometric model and can not be used in TH-2; on the other hand, pair position combines to form four baselines, and four baselines exist correlation in calibration, which leads to difficulty for baseline calibration. In order to keep accuracy of baseline calibration, the paper presents algorithm to chang bistatic geometric model into monostatic model and anlyses the transformation accuracy for slave satellite. It's proved that the algorithm has high accuracy and the brought error can be ignored by theoretical analysis and test

Biodiversity of network modules drives ecosystem functioning in biochar-amended paddy soil

IntroductionSoil microbes are central in governing soil multifunctionality and driving ecological processes. Despite biochar application has been reported to enhance soil biodiversity, its impacts on soil multifunctionality and the relationships between soil taxonomic biodiversity and ecosystem functioning remain controversial in paddy soil.MethodsHerein, we characterized the biodiversity information on soil communities, including bacteria, fungi, protists, and nematodes, and tested their effects on twelve ecosystem metrics (including functions related to enzyme activities, nutrient provisioning, and element cycling) in biochar-amended paddy soil.ResultsThe biochar amendment augmented soil multifunctionality by 20.1 and 35.7% in the early stage, while the effects were diminished in the late stage. Moreover, the soil microbial diversity and core modules were significantly correlated with soil multifunctionality.DiscussionOur analysis revealed that not just soil microbial diversity, but specifically the biodiversity within the identified microbial modules, had a more pronounced impact on ecosystem functions. These modules, comprising diverse microbial taxa, especially protists, played key roles in driving ecosystem functioning in biochar-amended paddy soils. This highlights the importance of understanding the structure and interactions within microbial communities to fully comprehend the impact of biochar on soil ecosystem functioning in the agricultural ecosystem

Comparison and analysis of two baseline calibration models for TH-2 satellite

The two equivalent satellites in the TH-2 satellite system formed a flying-around formation in early July 2019, and began to obtain global radar interference data using the one-transmit and double-receiving system. The precise interference baseline is to realize the production of high-precision surveying and mapping products. This article gives the definition of the baseline in the antenna phase center (APC) coordinate system of the main radar. It introduces the single-scene data baseline calibration model based on the slave radar range modification equation and doppler equation under the one-transmit and double-receiving system, and a joint near-far beam positions calibration model of obtaining parallel and effective baseline errors by steps. According to the principle of baseline error intersection, a control points selection strategy is given, that is, the strategy of selecting control points in the near and far sub strips. The 17 times Xinjiang calibration field data acquired by TH-2 was used to carry out single-scene data and near-far beam positions joint baseline calibration experiments, and the ground positioning precision analysis of the two baseline calibration models after calibration was carried out. The experiments show that the average horizontal baseline error is -2.74 mm, and the average vertical baseline error is -5.49 mm calibrated by the single-scene data model. The average horizontal baseline error is -1.95 mm, and the average vertical baseline error is -5.84 mm calibrated by the near-far beam positions joint model. The ground positioning precision of the system after the near-far beam positions joint baseline calibration is higher than that of the single-scene data baseline calibration

Detecting and pyramiding target QTL for plant- and grain-related traits via chromosomal segment substitution line of rice

IntroductionPlant height and grain length are important agronomic traits in rice, exhibiting a strong effect on plant architecture and grain quality of rice varieties.MethodsMethods: A novel rice chromosomal segment substitution line (CSSL), i.e., CSSL-Z1357, with significantly increased plant height (PH) and grain length (GL) was identified from CSSLs constructed by using Nipponbare as a receptor and a restorer line Xihui 18 as a donor. Seven agronomic traits of PH, PL, GL, GW, GPP, SPP, and TGW were phenotyped, and REML implemented in HPMIXED of SAS were used to detect the QTL for these traits. Secondary CSSLs were screened out via marker-assisted selection (MAS) to estimate the additive and epistatic effects of detected QTLs, evaluating the potential utilization of pyramiding the target QTLs for yield and quality improvement of rice varieties.Results and DiscussionResults and Discussion: CSSL-Z1357 carried nine segments from Xihui 18 with an average segment length of 4.13 Mb. The results show that the long grain of CSSL-Z1357 was caused by the increased number of surface cells and the length of the inner glume. Thirteen quantitative trait loci were identified via the F2 population of Nipponbare/CSSL-Z1357, including three each for GL (qGL-3, qGL-6, and qGL-7) and PH (qPH-1, qPH-7, and qPH-12I), among which qGL-3 increased GL by 0.23 mm with synergistic allele from CSSL-Z1357. Additionally, three single (S1 to S3), two double (D1, D2), and one triple segment (T1) substitution lines were developed in F3 via MAS. Results show that pyramiding the segments from Chr.3 (qGL-3 and qPH-3), Chr.6 (qGL-6 and qPH-6), and Chr.7 (Null and qPH-7) tended to result in better phenotype of increased GL and PH and decreased grain width, providing a potential basis for enhancing grain yield and quality in rice breeding