Does ‘a couple’ pattern with scalars or numbers - Insights from inference and ‘so’ tasks

Previous research establishes that paucal quantifiers like ‘a couple’ are ambiguous between the literal meaning of ‘at least two’ and the enriched meaning understood as conveying a restriction on quantity, the latter of which can be explained by a pragmatic phenomenon, i.e. scalar inference (SI). To address whether this ambiguity patterns with that of scalars or numbers, our Experiment 1 explored the behaviours of ‘a couple’ and scalars with two types of probe questions in inference tasks, and Experiment 2 continued this theme by testing the naturalness rating for ‘a couple’ and scalars in an ‘X so not Y’ construction. The results of our experiments indicate two natures of ‘a couple’: a non-monotonic /cardinal (approximately two) and proportional (a small proportion of)

Does ‘a couple’ pattern with scalars or numbers - Insights from inference and ‘so’ tasks

Previous research establishes that paucal quantifiers like ‘a couple’ are ambiguous between the literal meaning of ‘at least two’ and the enriched meaning understood as conveying a restriction on quantity, the latter of which can be explained by a pragmatic phenomenon, i.e. scalar inference (SI). To address whether this ambiguity patterns with that of scalars or numbers, our Experiment 1 explored the behaviours of ‘a couple’ and scalars with two types of probe questions in inference tasks, and Experiment 2 continued this theme by testing the naturalness rating for ‘a couple’ and scalars in an ‘X so not Y’ construction. The results of our experiments indicate two natures of ‘a couple’: a non-monotonic /cardinal (approximately two) and proportional (a small proportion of)

Repeated administration of L-alanine to mice, reduces behavioural despair and increases hippocampal mTOR signalling: analysis of gender and metabolic effects

Background: The amino acid, L-alanine, has been shown to be elevated in biofluids in major depression but its relevance remains unexplored. Aim: We have investigated the effects of repeated L-alanine administration on emotional behaviours and central gene expression in mice. Methods: Mice received a daily, 2-week intraperitoneal injection of either saline or alanine at 100mg/kg or 200mg/kg, and exposed to the open field, light-dark box and forced swim test. The expression of L-alanine transporters (asc-1, ASCT2), glycine receptor subunits (GlyRs), NMDA receptor subunits (GluNs) mRNAs were measured, together with western blots of the signalling protein mTOR. Since L-alanine modulates glucose homeostasis, peripheral and central metabolomes were evaluated with 1H-NMR. Results: L-alanine administration at 100mg/kg, but not at 200mg/kg, to both male and female mice increased latency to float and reduced floating time in the forced swim test, but had no effect on anxious behaviour in the open field and light-dark box tests. There was a significant reduction in mRNAs encoding asc-1 and ASCT2 and GluN2B in the hippocampus of mice following 100mg/kg L-alanine only. On western blots, hippocampal GluN2B immunoreactivity was reduced but, mTOR signalling was increased in the 100mg/kg L-alanine group. 1H-NMR revealed gender-specific changes in the forebrain, plasma and liver metabolomes only at 200mg/kg of L-alanine. Conclusions: Our data suggest that L-alanine may have antidepressant-like effect that may involve the modulation of glutamate neurotransmission independently of metabolism. In major depression, therefore, elevated L-alanine may be a homeostatic response to pathophysiological processes, though this will require further investigation

Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification

Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. Utilising a dataset of 2,322,513 ECGs collected from 1,558,772 patients with 7 years of follow-up, we developed a deep learning model with state-of-the-art granularity for the interpretable diagnosis of cardiac abnormalities, gender identification, and hyper- tension screening solely from ECGs, which are then used to stratify the risk of mortality. The model achieved the area under the receiver operating characteristic curve (AUC) scores of 0.998 (95% confidence interval (CI), 0.995-0.999), 0.964 (0.963-0.965), and 0.839 (0.837-0.841) for the three diagnostic tasks separately. Using ECG-predicted results, we find high risks of mortality for subjects with sinus tachycardia (adjusted hazard ratio (HR) of 2.24, 1.96-2.57), and atrial fibrillation (adjusted HR of 2.22, 1.99-2.48). We further use salient morphologies produced by the deep learning model to identify key ECG leads that achieved similar performance for the three diagnoses, and we find that the V1 ECG lead is important for hypertension screening and mortality risk stratification of hypertensive cohorts, with an AUC of 0.816 (0.814-0.818) and a univariate HR of 1.70 (1.61-1.79) for the two tasks separately. Using ECGs alone, our developed model showed cardiologist-level accuracy in interpretable cardiac diagnosis, and the advancement in mortality risk stratification; In addition, the potential to facilitate clinical knowledge discovery for gender and hypertension detection which are not readily available

sIFITM1, sIFITM3, and sViperin antiviral proteins as inactivated CSFV vaccine adjuvants

Vaccine adjuvants are now widely utilized in vaccine formulations. The IFN-Stimulated Genes (ISGs) family, play crucial roles in immune regulation and exhibit broad-spectrum antiviral activity. However, limited studies have investigated the potential of ISGs as vaccine adjuvants. Here, three swine ISGs fusion proteins were induced and purified from Escherichia coli, including IFITM1, IFITM3 and Viperin (sIFITM1, sIFITM3, and sViperin). Furthermore, sIFITM1, sIFITM3, and sViperin inhibited the replication of pseudorabies virus (PRV) in swine (PK-15 and 3D4/21) and murine (NIH/3 T3 and C57/B6-L) cells. Importantly, these fusion proteins effectively enhanced the immunogenicity of inactivated classical swine fever virus (CSFV) vaccine and improved the immune response in vaccinated mice. Our evidence indicates that, compared with the CSFV vaccine group, the co-administration of sIFITM1, sIFITM3, and sViperin with CSFV vaccine significantly improved humoral immunity, increased T lymphocyte proliferation in the spleen, and elevated serum IgG antibody levels. In conclusion, this study successfully prepared sIFITM1, sIFITM3, and sViperin fusion proteins, confirming their ability to inhibit PRV replication and suggesting their potential as vaccine adjuvants

The Interaction of TPH2 and 5-HT2A Polymorphisms on Major Depressive Disorder Susceptibility in a Chinese Han Population: A Case-Control Study

Purpose: TPH2 and 5-HT2A appear to play vital roles in the homeostatic regulation of serotonin levels in the brain, their genetic variations may lead to impaired homeostatic regulation of serotonin resulting in abnormal levels of serotonin in the brain, thus predisposing individuals to MDD. However, research studies have yet to confirm which gene-gene interaction effect between TPH2 and 5-HT2A polymorphisms results in increased susceptibility to MDD.Methods: A total of 565 participants, consisting of 278 MDD patients and 287 healthy controls from the Chinese Han population, were recruited for the present study. Six single nucleotide polymorphisms (SNPs) of TPH2/5-HT2A were selected to assess their interaction by use of a generalized multifactor dimensionality reduction method.Results: A-allele carriers of rs11178997 and rs120074175 were more likely to suffer from MDD than T-allele carriers of rs11178997, or G-allele carriers of rs120074175. The interaction between TPH2 (rs120074175, rs11178997) and 5-HT2A (rs7997012) was considered as the best multi-locus model upon the MDD susceptibility.Conclusions: Our data identified an important effect of TPH2 genetic variants (rs11178997 and rs120074175) upon the risk of MDD, and suggested that the interaction of TPH2/5-HT2A polymorphism variants confer a greater susceptibility to MDD in Chinese Han population

Application research of artificial intelligence English audio translation system based on fuzzy algorithm

With the development of globalization, people’s demand for English audio interaction is increasing. In order to overcome the shortcomings of traditional translation methods in grammatical variables, such as semantic ambiguity, quantifier errors, low translation accuracy, improve the quality and speed of English translation, and get more accurate and speed guaranteed translation, this study proposes an artificial intelligence English audio translation cross language system based on fuzzy algorithm. In this experiment, the collected analog speech signal is converted into a digital speech signal, and then, the speech features are modeled and digitized, and the whole set of speech samples are integrated and modified to eliminate the interference caused by noise as far as possible. After that, the collected voice will be stored in the text format, and then the text will be translated to achieve English audio translation. The DNN-HMM speech recognition model and the traditional GMM-HMM speech recognition model are used to preprocess the original corpus, and the accuracy of the corpus processing is compared. After that, the accuracy and utilization of the fuzzy algorithm are evaluated between the first type TSK and the second type TSK. For speech synthesis in which the corpus lacks language, it is meaningful to explore the least amount of training data for the synthesis of acceptable speech. The experimental results show that the accuracy of the fuzzy algorithm is about 97.34%, and the utilization rate is about 98.14%. The accuracy rate of type 1 and type 2 algorithms are about 85.77% and 76.87% respectively, and the utilization rate is about 83.25% and 78.63% respectively. The fuzzy algorithm based artificial intelligence English audio translation cross language system is obviously better than the other two algorithms.</jats:p

Design of Optoelectronic Hybrid Switching High Performance Computing Internet

Optoelectronic hybrid network technology is mixed with pure electric packet switching network, which can improve network capacity and reduce power consumption. However, the long configuration time and complex management of optical circuit switch affect the performance of optoelectronic hybrid network. Therefore, a new optoelectronic hybrid network architecture (BET) is designed. The network architecture consists of Ethernet electric packet switching network and optical wavelength routing network. The signal receiving and dispatching of optical routing network is realized by circular arrayed waveguide grating router. Based on the characteristics of wavelength cycling routing, there is no need to adjust the routing of optical signals to the destination port, that is, there is no need to configure the optical wavelength routing network. At the same time, an intelligent node dynamic reconfiguration (RG) algorithm is designed to improve the resource utilization of optical nodes. In this method, the network link utilization, cache occupancy, and network load are taken into account to adjust the distribution of optical nodes in the optoelectronic hybrid network. In the process of the experiment, by changing the message length, it is found that the optical wavelength routing network can achieve large capacity and new-type transmission and effectively reduce the delay at the same time; on the optoelectronic hybrid network, with the help of Hadoop platform, distributed cluster is built and used to transmit an XML data encoding (ED code), solve the finite state transducers (FST) and encode them. Compared with the traditional electric packet switching network, the transmission delay of ED code is greatly reduced after the introduction of optical circuit switch, and the efficiency of FST solution and coding calculation is improved by at least 30%.</jats:p

English-Assisted Teaching Evaluation System Based on Artificial Intelligence and Rasch Model

In order to improve the effect of English teaching in colleges and universities, this paper analyzes the English teaching process and combines the English teaching evaluation system and the Rasch model to construct an English teaching evaluation system. Moreover, this paper analyzes the needs of English teaching evaluation and uses the mixed Rasch model in the item reflection theoretical model to study the potential classification problems of teaching. At the same time as the optimal parameter estimation, the potential optimal classification ratio is found, and it is used as the basis for the classification of English teaching grades. In addition, this paper combines the Rasch model to construct the English-assisted teaching evaluation system and analyzes the system framework and workflow. The experimental research shows that the evaluation system of college English teaching process based on the Rasch model proposed in this paper has a good effect

English-Assisted Teaching Evaluation System Based on Artificial Intelligence and Rasch Model

In order to improve the effect of English teaching in colleges and universities, this paper analyzes the English teaching process and combines the English teaching evaluation system and the Rasch model to construct an English teaching evaluation system. Moreover, this paper analyzes the needs of English teaching evaluation and uses the mixed Rasch model in the item reflection theoretical model to study the potential classification problems of teaching. At the same time as the optimal parameter estimation, the potential optimal classification ratio is found, and it is used as the basis for the classification of English teaching grades. In addition, this paper combines the Rasch model to construct the English-assisted teaching evaluation system and analyzes the system framework and workflow. The experimental research shows that the evaluation system of college English teaching process based on the Rasch model proposed in this paper has a good effect.</jats:p