Attribute-Guided Network for Cross-Modal Zero-Shot Hashing

Zero-shot hashing (ZSH) aims at learning a hashing model that is trained only by instances from seen categories but can generate well to those of unseen categories. Typically, it is achieved by utilizing a semantic embedding space to transfer knowledge from seen domain to unseen domain. Existing efforts mainly focus on single-modal retrieval task, especially image-based image retrieval (IBIR). However, as a highlighted research topic in the field of hashing, cross-modal retrieval is more common in real-world applications. To address the cross-modal ZSH (CMZSH) retrieval task, we propose a novel attribute-guided network (AgNet), which can perform not only IBIR but also text-based image retrieval (TBIR). In particular, AgNet aligns different modal data into a semantically rich attribute space, which bridges the gap caused by modality heterogeneity and zero-shot setting. We also design an effective strategy that exploits the attribute to guide the generation of hash codes for image and text within the same network. Extensive experimental results on three benchmark data sets (AwA, SUN, and ImageNet) demonstrate the superiority of AgNet on both cross-modal and single-modal zero-shot image retrieval tasks

Simultaneous Improvement and Genetic Dissection of Salt Tolerance of Rice (Oryza sativa L.) by Designed QTL Pyramiding

Breeding of multi-stress tolerant rice varieties with higher grain yields is the best option to enhance the rice productivity of abiotic stresses prone areas. It also poses the greatest challenge to plant breeders to breed rice varieties for such stress prone conditions. Here, we carried out a designed QTL pyramiding experiment to develop high yielding “Green Super Rice” varieties with significantly improved tolerance to salt stress and grain yield. Using the F4 population derived from a cross between two selected introgression lines, we were able to develop six mostly homozygous promising high yielding lines with significantly improved salt tolerance and grain yield under optimal and/or saline conditions in 3 years. Simultaneous mapping using the same breeding population and tunable genotyping-by-sequencing technology, we identified three QTL affecting salt injury score and leaf chlorophyll content. By analyzing 32M SNP data of the grandparents and graphical genotypes of the parents, we discovered 87 positional candidate genes for salt tolerant QTL. According to their functional annotation, we inferred the most likely candidate genes. We demonstrated that designed QTL pyramiding is a powerful strategy for simultaneous improvement and genetic dissection of complex traits in rice

QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study

Background:Ferrous iron (Fe) and zinc (Zn) at high concentration in the soil cause heavy metal toxicity andgreatly affect rice yield and quality. To improve rice production, understanding the genetic and molecularresistance mechanisms to excess Fe and Zn in rice is essential. Genome-wide association study (GWAS) is aneffective way to identify loci and favorable alleles governing Fe and Zn toxicty as well as dissect the geneticrelationship between them in a genetically diverse population.Results:A total of 29 and 31 putative QTL affecting shoot height (SH), root length (RL), shoot fresh weight (SFW),shoot dry weight (SDW), root dry weight (RDW), shoot water content (SWC) and shoot ion concentrations (SFe orSZn) were identified at seedling stage in Fe and Zn experiments, respectively. Five toxicity tolerance QTL (qSdw3a,qSdw3b,qSdw12andqSFe5/qSZn5) were detected in the same genomic regions under the two stress conditionsand 22 candidate genes for 10 important QTL regions were also determined by haplotype analyses.Conclusion:Rice plants share partial genetic overlaps of Fe and Zn toxicity tolerance at seedling stage. Candidategenes putatively affecting Fe and Zn toxicity tolerance identified in this study provide valuable information forfuture functional characterization and improvement of rice tolerance to Fe and Zn toxicity by marker-assistedselection or designed QTL pyramiding

Higher Dispersion Measures of Conduction and Repolarization in Type 1 Compared to Non-type 1 Brugada Syndrome Patients: An Electrocardiographic Study From a Single Center

Background: Brugada syndrome (BrS) is a cardiac ion channelopathy that predisposes affected individuals to sudden cardiac death (SCD). Type 1 BrS is thought to take a more malignant clinical course than non-type 1 BrS. We hypothesized that the degrees of abnormal repolarization and conduction are greater in type 1 subjects and these differences can be detected by electrocardiography (ECG).Methods: Electrocardiographic data from spontaneous type 1 and non-type 1 BrS patients were analyzed. ECG parameters were measured from leads V1 to V3. Values were expressed as median [lower quartile-upper quartile] and compared using Kruskal-Wallis ANOVA.Results: Compared to non-type 1 BrS patients (n = 29), patients with spontaneous type 1 patterns (n = 22) showed similar (P > 0.05) heart rate (73 [64–77] vs. 68 [62–80] bpm), QRS duration (136 [124–161] vs. 127 [117–144] ms), uncorrected QT (418 [393–443] vs. 402 [386–424] ms) and corrected QT intervals (457 [414–474] vs. 430 [417–457] ms), JTpeak intervals (174 [144–183] vs. 174 [150–188] ms), Tpeak− Tend intervals (101 [93–120] vs. 99 [90–105] ms), Tpeak− Tend/QT ratios (0.25 [0.23–0.27] vs. 0.24 [0.22–0.27]), Tpeak− Tend/QRS (0.77 [0.62–0.87] vs. 0.77 [0.69–0.86]), Tpeak− Tend/(QRS × QT) (0.00074 [0.00034–0.00096] vs. 0.00073 [0.00048–0.00012] ms−1), index of Cardiac Electrophysiological Balance (iCEB, QT/QRS, marker of wavelength: 3.14 [2.56–3.35] vs. 3.21 [2.85–3.46]) and corrected iCEB (QTc/QRS: 3.25 [2.91–3.73] vs. 3.49 [2.99–3.78]). Higher QRS dispersion was seen in type 1 subjects (QRSd: 34 [24–66] vs. 24 [12–34] ms) but QT dispersion (QTd: 48 [39–71] vs. 43 [22–94] ms), QTc dispersion (QTcd: 52 [41–79] vs. 46 [23–104] ms), JTpeak dispersion (44 [23–62] vs. 45 [30–62] ms), Tpeak− Tend dispersion (28 [15–34] vs. 29 [22–53] ms) or Tpeak− Tend/QT dispersion (0.06 [0.03–0.08] vs. 0.08 [0.04–0.12]) did not differ between the two groups. Type 1 subjects showed higher (QRSd × Tpeak− Tend)/QRS (25 [19–44] vs. 19 [9–30] ms) but similar iCEB dispersion (0.83 [0.49–1.14] vs. 0.61 [0.34–0.92]) and iCEBc dispersion (0.93 [0.51–1.15] vs. 0.65 [0.39–0.96]).Conclusion: Higher levels of dispersion in conduction and repolarization are found in type 1 than non-type 1 BrS patients, potentially explaining the higher incidence of ventricular arrhythmias in the former group