Phrasal Paraphrase Based Question Reformulation for Archived Question Retrieval

Lexical gap in cQA search, resulted by the variability of languages, has been recognized as an important and widespread phenomenon. To address the problem, this paper presents a question reformulation scheme to enhance the question retrieval model by fully exploring the intelligence of paraphrase in phrase-level. It compensates for the existing paraphrasing research in a suitable granularity, which either falls into fine-grained lexical-level or coarse-grained sentence-level. Given a question in natural language, our scheme first detects the involved key-phrases by jointly integrating the corpus-dependent knowledge and question-aware cues. Next, it automatically extracts the paraphrases for each identified key-phrase utilizing multiple online translation engines, and then selects the most relevant reformulations from a large group of question rewrites, which is formed by full permutation and combination of the generated paraphrases. Extensive evaluations on a real world data set demonstrate that our model is able to characterize the complex questions and achieves promising performance as compared to the state-of-the-art methods.     

The Optimal Solution of a Non-Convex State-Dependent LQR Problem and Its Applications

This paper studies a Non-convex State-dependent Linear Quadratic Regulator (NSLQR) problem, in which the control penalty weighting matrix in the performance index is state-dependent. A necessary and sufficient condition for the optimal solution is established with a rigorous proof by Euler-Lagrange Equation. It is found that the optimal solution of the NSLQR problem can be obtained by solving a Pseudo-Differential-Riccati-Equation (PDRE) simultaneously with the closed-loop system equation. A Comparison Theorem for the PDRE is given to facilitate solution methods for the PDRE. A linear time-variant system is employed as an example in simulation to verify the proposed optimal solution. As a non-trivial application, a goal pursuit process in psychology is modeled as a NSLQR problem and two typical goal pursuit behaviors found in human and animals are reproduced using different control weighting . It is found that these two behaviors save control energy and cause less stress over Conventional Control Behavior typified by the LQR control with a constant control weighting , in situations where only the goal discrepancy at the terminal time is of concern, such as in Marathon races and target hitting missions.     

Tampering with cancer chemoresistance by targeting the TGM2-IL6-autophagy regulatory network

Macroautophagy/autophagy is a well-established process involved in maintaining cellular homeostasis, but its role in cancer is complex and even controversial. Many studies have reported a correlative relationship between increased autophagy and evolving cancer cells under stress conditions such as nutrient or oxygen deprivation; however, there has been a lack of a plausible mechanistic link to properly target the autophagy process in the context of this microenvironment. We recently unveiled a positive regulatory loop involving TGM2 (transglutaminase 2)-NFKB/NF-κB signaling, IL6 and autophagy in cancer using mantle cell lymphoma (MCL) as a model system. These pathways are functionally connected to each other, thereby promoting malignant B cell survival and leading to enhanced lymphoma progression both in mice and in patients. Disruption of this network could provide an opportunity to increase the efficacies of current therapies and to reduce MCL drug resistance.     

Methylation of KvDMR1 involved in regulating the imprinting of CDKN1C gene in cattle

The CDKN1C gene encodes a cyclin‐dependent kinase inhibitor and is one of the key genes involved in the development of Beckwith–Wiedemann syndrome and cancer. In this study, using a direct sequencing approach based on a single nucleotide polymorphism (SNP) at genomic DNA and cDNA levels, we show that CDKN1C exhibits monoallelic expression in all seven studied organs (heart, liver, spleen, lung, kidney, muscle and subcutaneous fat) in cattle. To investigate how methylation regulates imprinting of CDKN1C in cattle, allele‐specific methylation patterns in two putative differential methylation regions (DMRs), the CDKN1C DMR and KvDMR1, were analyzed in three tissues (liver, spleen and lung) using bisulfite sequencing PCR. Our results show that in the CDKN1C DMR both parental alleles were unmethylated in all three analyzed tissues. In contrast, KvDMR1 was differentially methylated between the two parental alleles in the same tissues. Statistical analysis showed that there is a significant difference in the methylation level between the two parental alleles (P < 0.01), confirming that this region is the DMR of KvDMR1 and that it may be correlated with CDKN1C imprinting.     

Rapid improvement of rice eating and cooking quality through gene editing toward glutelin as target

Rice eating and cooking quality (ECQ) is a major concern of breeders and consumers, determining market competitiveness worldwide. Rice grain protein content (GPC) is negatively related to ECQ, making it possible to improve ECQ by manipulating GPC. However, GPC is genetically complex and sensitive to environmental conditions; therefore, little progress has been made in traditional breeding for ECQ. Here, we report that CRISPR/Cas9-mediated knockout of genes encoding the grain storage protein glutelin rapidly produced lines with downregulated GPC and improved ECQ. Our finding provides a new strategy for improving rice ECQ.