Related Pairs Research Articles

Adult age differences in specific and gist associative episodic memory across short- and long-term retention intervals.

Age-related deficits in associative episodic memory have been widely reported, but recent research suggests that some of these deficits occur for highly specific but not gist representations. It remains undetermined whether older adults' deficits in specific associative episodic memory, observed in long-term memory, are also present in short-term memory. We used a continuous associative recognition task to address this question. Fifty young and 50 older adults studied face-scene pairs, with memory tests occurring in both short-term and long-term memory. Memory tests featured intact (old) pairs, related (similar) pairs, and unrelated (dissimilar) pairs. On short-term memory tests, older adults were less accurate in classifying related pairs, which was manifest by age-related reductions in the probability of retrieving specific memory to engage in recollection rejection. However, older adults were capable of remembering specific details in short-term memory for intact probes but were less likely to remember specific details in long-term memory. Finally, older adults were always as capable as younger adults of remembering gist details. Results suggest that older adults do at least partially encode specific representations in short-term memory, and their access to these specific representations is cue dependent-they can do so when there is a large correspondence between encoding and retrieval conditions but are less likely to engage in deeper elaboration at retrieval. This limits their ability to remember specific details of associations to suppress false recognitions in short-term memory and to engage in veridical recognition in long-term memory. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

EP16.01-022 A Signature of B Cells-Related Gene Pairs Predicts Oncologic Outcomes and Response to Immunotherapy in NSCLC Patients

Tumor-infiltrating B cells accompanying several widely used B cell-related biomarkers, such as CD19 and CD20, have inconsistent clinical prognostic values in non-small-cell lung cancer (NSCLC) patients. Considering only one B cell-related biomarker could not distinguish the anti-tumor and pro-tumor B cell subsets in tumor, we aimed to construct a more accurate B-cells related gene pairs (BRGPs) prognostic model and evaluate its potential predictive ability to immunotherapy in NSCLC patients.

The Impact of Depth of Encoding on the Transfer of Test Enhanced Learning.

The mediator effectiveness hypothesis states the benefit of retrieval practice is a consequence of the activation of mediators linking cue and target items during review. Evidence has found that mediators are more effective at prompting recall of target words than words not associated with the original cue, a pattern that is larger following testing than restudy. The benefit of testing for unstudied cues at the final test is referred to as transfer of test-enhanced learning. The current study examined whether the activation of mediators is moderated by the depth of processing completed at encoding. During an initial study of weakly related word pairs (e.g., Mother-CHILD), participants completed an encoding task that directed deep, shallow, or no specific depth of processing. During review, participants restudied the pairs or attempted to recall the target given the original cue (e.g., Mother). On the final test, participants were presented with unstudied cues that were related to either the original cue (mediators, e.g., Father) or the target (target-related cues, e.g., Baby). The results found mediator generation during review to be greatly impaired by shallow processing tasks completed during encoding. In contrast, the effectiveness of target-related cues was not affected by depth of processing tasks.

Response of the reproductive fitness and population density of Gammarus fossarum Koch, 1836 (Amphipoda: Gammaridae) to damming: a case study from the dammed sub-mountain stretch of Čierny Váh River, Slovakia

Abstract The plasticity of some biological and ecological characteristics of Gammarus fossarum Koch, 1836, a species widely distributed in the rivers of continental Europe, has been the subject of many scientific studies. The effects of river damming are reflected in the disruption of the natural environmental continuum of rivers, which has been demonstrated in this and other studies. We aimed to investigate the variability of population characteristics (relative reproductive fitness, pairing success, and fecundity), and population density in six local populations distributed along Čierny Váh River, Slovakia, a sub-mountain dammed river. Our results showed that the population inhabiting the site immediately downstream of the reservoir had significantly higher density, but its individuals had lower body size, pairing success, and fecundity compared to individuals at the other sites. As a result, the lower values of these characteristics were reflected in a different distribution pattern of relative reproductive fitness among individuals at the sites. Individuals at sites downstream of the reservoir, particularly those immediately below the reservoir, had lower mean fitness values. Our study demonstrated that the disturbance in the river environment caused by the dam not only affects the structure of the aquatic community, but can also alter population-level characteristics.

Identification of miRNA-mRNA Pairs in Relation to TNF-α/IL-1β Induced Inflammatory Response in Intervertebral Disc Degeneration.

Objective The determination of miRNA-mRNA pairs for intervertebral disc degeneration (IVDD) regulated by pro-inflammatory cytokines were investigated. Methods Two dataset (accession number GSE27494 and GSE41883 from platform GPL1352) of expression profiling was downloaded from Gene Expression Omnibus (GEO). The annulus cells were isolated from annulus fibrosus in patients with degenerative disc disease. The cells were then cultured in a three-dimensional (3D) collagen containing with/without proinflammatory cytokines (tumor necrosis factor alpha (TNF-α) or interleukin beta (IL-1β)). After being cultured for 14 days, the isolated total RNA was analyzed via microarray, and the expression array data were obtained using BRB-Array Tools followed by analyzing the differentially expressed genes (DEGs) and the prediction of potential miRNA targets of hub genes through online database. Results Firstly, 52 and 296 DEGs were found in IL-1β- and TNF-α-induced annulus cells, respectively, of these there had 42 common DEGs (co-DEGs) with 34 increased transcripts and 8 reduced ones. Based on the GO and KEGG software, these co-DEGs were mainly enriched in the response to lipopolysaccharide (LPS) and molecule of bacterial origin, the regulation of receptor ligand activity and signaling receptor activator activity, as well as the following signaling pathways, including TNF signaling pathway, IL-17 signaling pathway, and NF-κB signaling pathway. Top hub genes (CXCL1, CXCL2, CXCL8, IL1Β and PTGS2) regulated by several potential microRNAs were involved in TNF-α/IL-1β treated annulus cells. Conclusions Several candidate genes regulated by miRNAs caused by TNF-α/IL-1β in the annulus cells were found, which will guide diagnosis and treatment for degenerative disc disease.

Improving discrimination capacity through rapidly mutating Y-STRs in structured populations from the African continent

Y chromosome short tandem repeats (Y-STRs) typing is becoming increasingly popular in forensic casework mainly because it allows the recovery of male-specific genetic information from severely unbalanced male-female DNA mixtures. The relatively low discrimination power of conventional Y-STR multiplexes, due to linkage disequilibrium among polymorphic loci, has been partially overcome by the introduction of rapidly mutating Y microsatellites (RM Y-STRs) with mutation rates exceeding 1 × 10-2/generation. In previous works, we reported an unexpectedly high level of haplotype sharing among African males using the Yfiler Plus PCR Amplification kit, the most powerful commercially available system, including 19 conventional Y-STRs and 6 RM Y-STRs. In particular, analyzing 1370 males from northern, eastern and central Africa, 240 subjects were found to share 100 Y-STR haplotypes. We attributed the relatively low discrimination capacity to several factors including patrilocality, endogamy, sampling bias and degree of urbanization. In the present study, using a blind search analysis based on 16 autosomal STRs, we first investigated the kinship between pairs of African males previously found to share the Yfiler Plus haplotype; then, we evaluated the improvement in identification capacity allowed by a PCR multiplex assay (RM-YPlex) based on 13 “first generation” RM Y-STR, seven of which are not included in the Yfiler Plus multiplex. Among 228 pairs of males sharing a Yfiler Plus haplotype, we detected 134 related (cousins or closer) and 94 unrelated (or distantly related) pairs of subjects. By using the RM-YPlex, we observed a full genotype concordance for the six loci shared with the Yfiler Plus, while the additional seven RM Y-STRs allowed the discrimination among 58.2 % related pairs and 84.0 % unrelated pairs. The discrimination capacity increased from 0.898 to 0.958, while the proportion of males sharing a haplotype decreased from 17.5 % to 8.0 %. These findings further highlight the capability of RM Y-STRs to distinguish males even in close kinship scenarios and in sub-structured populations as African ones, but at the same time call for the discovery and testing of additional RM Y-STRs to fully differentiate male relatives.

Morphological Priming Effects in L2 English Verbs for Japanese-English Bilinguals.

For native (L1) English readers, masked presentations of past-tense verb primes (e.g., fell and looked) produce faster lexical decision latencies to their present-tense targets (e.g., FALL and LOOK) than orthographically related (e.g., fill and loose) or unrelated (e.g., master and bank) primes. This facilitation observed with morphologically related prime-target pairs (morphological priming) is generally taken as evidence for strong connections based on morphological relationships in the L1 lexicon. It is unclear, however, if similar, morphologically based, connections develop in non-native (L2) lexicons. Several earlier studies with L2 English readers have reported mixed results. The present experiments examine whether past-tense verb primes (both regular and irregular verbs) significantly facilitate target lexical decisions for Japanese-English bilinguals beyond any facilitation provided by prime-target orthographic similarity. Overall, past-tense verb primes facilitated lexical decisions to their present-tense targets relative to both orthographically related and unrelated primes. Replicating previous masked priming experiments with L2 readers, orthographically related primes also facilitated target recognition relative to unrelated primes, confirming that orthographic similarity facilitates L2 target recognition. The additional facilitation from past-tense verb primes beyond that provided by orthographic primes suggests that, in the L2 English lexicon, connections based on morphological relationships develop in a way that is similar to how they develop in the L1 English lexicon even though the connections and processing of lower level, lexical/orthographic information may differ. Further analyses involving L2 proficiency revealed that as L2 proficiency increased, orthographic facilitation was reduced, indicating that there is a decrease in the fuzziness in orthographic representations in the L2 lexicon with increased proficiency.

An individualized functional magnetic resonance imaging protocol to assess semantic congruency effects on episodic memory in an aging multilingual population.

The cognitive stimulation induced by multilingualism may slow down age-related memory impairment. However, a suitable neuroscientific framework to assess the influence of multilingualism on age-related memory processes is missing. We propose an experimental paradigm that assesses the effects of semantic congruency on episodic memory using functional magnetic resonance imaging (fMRI). To this end, we modified the picture-word interference (PWI) task to be suitable for the assessment of older multilingual subjects undergoing fMRI. In particular, stimulus materials were prepared in multiple languages (French, German, Luxembourgish, English) and closely matched in semantic properties, thus enabling participants to perform the experiment in a language of their choice. This paradigm was validated in a group (n = 62) of healthy, older participants (over 64 years) who were multilingual, all practicing three or more languages. Consistent with the engagement of semantic congruency processes, we found that the encoding and recognition of semantically related vs. unrelated picture-word pairs evoked robust differences in behavior and the neural activity of parietal-temporal networks. These effects were negligibly modulated by the language used to perform the task. Based on this validation in a multilingual population, we conclude that the proposed paradigm will allow future studies to evaluate whether multilingualism aptitude engages neural systems in a manner that protects long-term memory from aging-related decline.

Effects of emotion and semantic relatedness on recognition memory: Behavioral and electrophysiological evidence.

Some aspects of our memory are enhanced by emotion, whereas others can be unaffected or even hindered. Previous studies reported impaired associative memory of emotional content, an effect termed associative "emotional interference". The current study used EEG and an associative recognition paradigm to investigate the cognitive and neural mechanisms associated with this effect. In two experiments, participants studied negative and neutral stimulus-pairs that were either semantically related or unrelated. In Experiment 1 emotions were relevant to the encoding task (valence judgment) whereas in Experiment 2 emotions were irrelevant (familiarity judgment). In a subsequent associative recognition test, EEG was recorded while participants discriminated between intact, rearranged, and new pairs. An associative emotional interference effect was observed in both experiments, but was attenuated for semantically related pairs in Experiment 1, where valence was relevant to the task. Moreover, a modulation of an early associative memory ERP component (300-550 ms) occurred for negative pairs when valence was task-relevant (Experiment 1), but for semantically related pairs when valence was irrelevant (Experiment 2). A later ERP component (550-800 ms) showed a more general pattern, and was observed in all experimental conditions. These results suggest that both valence and semantic relations can act as an organizing principle that promotes associative binding. Their ability to contribute to successful retrieval depends on specific task demands.

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

Objective:The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods:The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results:With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions:The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Complex kinship analysis with a combination of STRs, SNPs, and indels

Complex kinship analysis has been widely applied in disaster victim identification and criminal investigations. A larger number of genetic markers is required to improve the discrimination power of the system in complex kinship analysis compared to that in paternity testing, as distant relatives share fewer genetic segments. Genetic markers, including short tandem repeats (STRs), single-nucleotide polymorphisms (SNPs), and insertions-deletions (indels), play complementary roles in kinship analysis. Few studies have systematically analyzed the system discrimination power of a new combination of different types of genetic markers before using these markers in practice. Here, we tested the ability of a set of 56 STRs available in commercial panels on complex kinship analysis. We next introduced a combination marker set of STRs, indels, and SNPs and evaluated the system discrimination power of 72 indels + 52 SNPs to improve the weight of 56 STRs. Statistical analysis of complex kinship within third-degree kinship testing was performed to compare 56 STRs or 72 indels + 52 SNPs alone. True samples were assessed, including 99 full siblings, 112 uncle/aunt-nephew/niece, 43 grandfather/grandmother-grandson/granddaughter, 63 first cousins, and 5931 unrelated pairs. Simulation was also performed using 10,000 pairs of relatives and 10,000 unrelated individuals. The effectiveness of the three marker sets in kinship testing was ranked as follows: 56 STRs + 72 indels + 52 SNPs > 56 STRs > 72 indels + 52 SNPs. All three marker sets were powerful in first-degree kinship testing; 56 STRs and 56 STRs + 72 indels + 52 SNPs could distinguish most second-degree relatives from unrelated pairs. However, only a portion of third-degree relatives was correctly determined from unrelated individuals using 56 STRs + 72 indels + 52 SNPs. In relationship testing, 56 STRs and 56 STRs + 72 indels + 52 SNPs were powerful enough to distinguish first-degree relatives from second-degree or third-degree relatives. Our results provide a strategy and guidance applicable in forensic practice for complex kinship analysis by combining STRs, SNPs, and indels.

BioRED: a rich biomedical relation extraction dataset.

Automated relation extraction (RE) from biomedical literature is critical for many downstream text mining applications in both research and real-world settings. However, most existing benchmarking datasets for biomedical RE only focus on relations of a single type (e.g. protein–protein interactions) at the sentence level, greatly limiting the development of RE systems in biomedicine. In this work, we first review commonly used named entity recognition (NER) and RE datasets. Then, we present a first-of-its-kind biomedical relation extraction dataset (BioRED) with multiple entity types (e.g. gene/protein, disease, chemical) and relation pairs (e.g. gene–disease; chemical–chemical) at the document level, on a set of 600 PubMed abstracts. Furthermore, we label each relation as describing either a novel finding or previously known background knowledge, enabling automated algorithms to differentiate between novel and background information. We assess the utility of BioRED by benchmarking several existing state-of-the-art methods, including Bidirectional Encoder Representations from Transformers (BERT)-based models, on the NER and RE tasks. Our results show that while existing approaches can reach high performance on the NER task (F-score of 89.3%), there is much room for improvement for the RE task, especially when extracting novel relations (F-score of 47.7%). Our experiments also demonstrate that such a rich dataset can successfully facilitate the development of more accurate, efficient and robust RE systems for biomedicine.Availability: The BioRED dataset and annotation guidelines are freely available at https://ftp.ncbi.nlm.nih.gov/pub/lu/BioRED/.

Age-Dependent Dispersal and Relatedness in Tiger Sharks (Galeocerdo cuvier)

Understanding dispersal in large marine fauna is necessary for conservation, but movement patterns often vary widely by sex and life stage. In sharks, genetic studies have shown evidence of widespread male-biased dispersal, though tagging and tracking studies on the same populations show both sexes using site fidelity, including philopatry, and moving similar distances. We used a suite of microsatellite loci and DNA samples from 362 previously-tagged tiger sharks (Galeocerdo cuvier) in the northwestern Atlantic, including a large number of residential juveniles, to evaluate reproductive dispersal in light of demographic and published tracking data. We found that lumping size classes together resulted in genetic panmixia across sites, but systematic removal of large individuals showed significant population-level differentiation and three separate population clusters among juveniles less than 260 cm total length. Tests for relatedness found that 8.9% of our sample set was composed of first-order related pairs (N = 16), including several full siblings from different litters, a sign of multi-cycle genetic monogamy which carries implications for effective population size. By mapping genetic assignments of juveniles, we identified a signature of fine-scale genetic structure suggesting broad biparental site fidelity to reproductive habitat in the northeast Gulf of Mexico, which is concordant with both genetic and tracking data. Taken together, these findings demonstrate how lumping individuals from different life stages in genetic studies may obscure fine-scale genetic structure, confounding future conservation efforts.

The Typology of Alcohol Use Disorder: Latent Class Analyses of a Population-Based Swedish Sample.

The purpose of this study was to clarify the clinical heterogeneity of alcohol use disorder (AUD) in a national Swedish sample of affected individuals using latent class analysis. Using a Swedish population-based sample of AUD cases ascertained from medical, criminal, and pharmacy registries (n = 217,071), we applied latent class analysis to sex, externalizing and internalizing syndromes before first registration, and age at first registration. The resulting types were evaluated against 15 diverse validators and degree of resemblance in relative pairs concordant for AUD. A three-class solution was preferred by fit indices. The three classes were as follows: type 1 (male preponderant, externalizing; 32%), type 2 (minimal prior psychopathology; 46%), and type 3 (mixed-sex internalizing; 23%). Repeated split-half analyses revealed the statistical stability of these solutions. Meaningful differences emerged between the classes on many validators. Type 1 had the greatest family disruption, lowest educational levels, most AUD registrations, highest rates of criminal registration, and highest genetic risk for externalizing disorders and AUD. Type 2 had the least social dysfunction. Type 3 had the highest educational attainment, genetic liability to internalizing disorders, and proportion of women. All types significantly aggregated in affected pairs of relatives. Meaningful and reproducible subtypes of AUD, consistent with prior typological results, can be obtained from national registry-based samples. Using a range of external validators and patterns of familial aggregation, our results suggest that our three-class solution captured a meaningful proportion of the clinical heterogeneity of AUD.

Significant familial clustering of Peyronie's disease in close and distant relatives.

Peyronie's disease (PD) has previously been observed to co-aggregate in a small number of first-degree relative pairs (e.g., father-son). However, the familial aggregation of PD in more distant relatives, as well as the aggregation of Dupuytren's disease (DD) in probands and relatives, has not been thoroughly investigated. This study explored the evidence for familial clustering of PD and DD in close and distant relatives. The Utah Population Database, which includes genealogy information linked to electronic medical records (available since 1995), was used to identify men and their relatives with PD and DD based on ICD9/10 codes. All cases were required to have high-quality genealogy data. We estimated relative risk (RR) of PD and DD in first- through fifth-degree relatives compared to matched population rates of disease. We also investigated the average relatedness of cases compared to the average relatedness of sets of matched controls. Outcome measures include estimation of relative risk and excessive relatedness as measured by a Genealogical Index of Familiality (GIF) analysis. We analyzed 307 individuals with PD, and their first- through fifth-degree relatives. Approximately 0.12% of the population had PD, 95% of these were diagnosed over the age of 30 years (age range: 10-92 years), and 1.3% of PD probands had a comorbid diagnosis of DD. RR estimates for PD were significant for first- and fifth-degree relatives. RR estimates for DD were significant only for probands. The average relatedness of cases was significantly greater than matched controls, even after removing first- and second-degree relatives. We also found that 74.9% of identified PD probands belonged to pedigrees with a statistical excess of PD. Despite the low prevalence of PD in our healthcare records, the results provide evidence that support a genetic contribution to at least a subset of PD cases.

High-performance thin-layer chromatography – antibacterial assay first reveals bioactive clerodane diterpenes in giant goldenrod (Solidago gigantea Ait.)

The present work introduces a high-performance thin-layer chromatography (HPTLC)–direct bioautography method using the Gram-positive plant pathogenic bacterium, Rhodococcus fascians. The screening and isolation procedure comprised of a non-targeted high-performance thin-layer chromatography-effect-directed analysis (HPTLC–EDA) against Bacillus subtilis, B. subtilis subsp. spizizenii, R. fascians, and Aliivibrio fischeri, a targeted HPTLC–mass spectrometry (MS), and bioassay-guided column chromatographic (preparative flash and semi-preparative HPLC) fractionation and purification. The developed new separation methods enabled the discovery of four bioactive cis-clerodane diterpenes, solidagoic acid H (1), solidagoic acid E (2), solidagoic acid I (3), and solidagoic acid F (4), in the n-hexane extract of giant goldenrod (Solidago gigantea Ait.) leaf for the first time. These compounds were identified by 1D and 2D nuclear magnetic resonance (NMR) spectroscopy. The initially used HPTLC method (chloroform – ethyl acetate – methanol 15:3:2, V/V/V) was changed (to n-hexane – isopropyl acetate – methanol – acetic acid 29:20:1:1, V/V/V/V) to achieve the separation of the closely related isomer pairs (1–2 and 3–4). Compounds 1 and 3 exhibited moderate antibacterial activity against the Gram-positive B. subtilis subsp. spizizenii and R. fascians bacterial strains in microdilution assays with half-maximal inhibitory concentration (IC50) values in the range of 32.3–64.4 µg/mL. The mass spectrometric fragmentation of the isolated compounds was interpreted and their previously published NMR assignments lacking certain resonances were completed.

Combining Machine Learning with a Rule-Based Algorithm to Detect and Identify Related Entities of Documented Adverse Drug Reactions on Hospital Discharge Summaries.

Discharge summaries contain valuable information about adverse drug reactions, but their unstructured nature makes them challenging to analyse and use as a signal source for pharmacovigilance. Machine learning has shown promise in identifying discharge summaries that contain related drug-adverse event pairs but has fared relatively poorer in entity extraction. A hybrid model is developed combining rule-based and machine learning algorithms using discharge summaries with the aim of maximising capture of related drug-adverse event pairs. The rule first identifies segments containing adverse event entities within a 100-character distance from a drug term; machine learning subsequently estimates the relatedness of the drug and adverse event entities contained. The approach is validated on four independent datasets that are temporally and geographically separated from model development data. The impact of restricted drug-adverse event pair detection on recall is evaluated by using two of the four validation datasets that do not impose rule-based restrictions to annotations. The hybrid model achieves a recall of 0.80 (fivefold cross validation), 0.80 (temporal) and 0.76 (geographical) on validation using datasets containing only pre-identified target text segments that fulfil the rule-based algorithm criteria. When tested on datasets that additionally contained drug-adverse event pairs not restricted by the rule-based criteria, recall of the model declines to 0.68 and 0.62 on temporally and geographically separated datasets, respectively. The proposed hybrid model demonstrates reasonable generalisability on external validation. Rule-based restriction of the detection space results in an approximately 12-14% reduction in recall but improves identification of the related drug and adverse event terms.

Two-dimensional paired topological superfluids of Rydberg Fermi gases

We systematically investigate the topological properties of spin polarized Rydberg-dressed fermionic atoms loaded in a bilayer optical lattice. Through tuning the Rydberg coupling strength and the interlayer tunneling amplitude, we identify different types of topological superfluid states generated from the interlayer pairing and relative pairing phase modulation of the coupled two-dimensional $p$-wave superfluids. These phases include gapped/gapless with/without time-reversal symmetry. One of the most interesting states is a gapless paired topological superfluid with both the time-reversal symmetry and particle-hole symmetry, which is a realization of a DIII gapless topological superconductor. The flexibility of experimental manipulation in such Rydberg-dressed fermionic systems therefore becomes a promising system for realizing interesting topological superfluids.

Multilabel Feature Selection Based on Relative Discernibility Pair Matrix

In multilabel learning, the curse of dimensionality is one of major challenges. Existing single-label feature selection methods cannot be directly applied to multilabel data, and multilabel feature selections have thus been widely studied. As an effective granular computing tool, rough set theory has been applied to multilabel feature selections for addressing various realistic applications. However, existing rough set-based methods not only cannot effectively characterize the ability of features to distinguish multilabel sample pairs, but also usually own high time complexity. In this article, we propose two novel multilabel feature selection methods from the perspective of discerning sample pairs. First, relative discernibility pair matrixes of features are defined in the framework of fuzzy rough set, where each element represents the degree of distinguishing the corresponding sample pair by features. On this basis, a novel evaluation measure of feature subsets is defined. Afterwards, a heuristic multilabel feature selection approach titled RDPM based on the proposed measure is put forward. Inspired by sampling and ensemble strategies, another efficient and robust multilabel feature selection approach titled RDPM_SE is proposed as well. Finally, extensive experiments on 13 real-world multilabel datasets are conducted, and experimental results show that the proposed algorithms outperform seven state-of-the-art methods in terms of performances and the running time.

Two-tier control structure design methodology applied to heat exchanger networks

Because of its paramount importance in the successful industrial control strategy of a given heat exchanger network (HEN), the control structure designs for providing appropriate manipulated variable (MV) and controlled variable pairings have received considerable attention. However, quite frequently HENs with such control structures face the problem of hard constraints, typically holding the HENs at less controlled operating space. So both the MV pairings and the above control pairings should be considered to design a control structure. This paper investigates the systematic incorporation of the two pairings, and presents a methodology for designing such two-tier control structure. This is developed based on the sequential strategy, coupling an indirect-tier with direct-tier control structure design, wherein the intention is realized in the former stage and the latter is implemented for further optimization. The MV identification and pairing are achieved through variations in heat load of heat exchangers to design the indirect-tier control structure. Then the direct-tier control structure is followed the relative gain array pairing rules. With the proposed methodology, on the one hand, it generates an explicit connection between the MV pairings and the HEN configuration, and the quantitative interaction measure is improved to avoid the multiple solutions to break the relationship among all the control pairings into individuals; on the other hand, a two-tier control structure reveals control potentials and control system design requirements, this may avoid complex and economically unfavourable control and HEN structures. The application of proposed framework is illustrated with two cases involving the dynamic simulation analysis, the quantitative assessment and the random test.