1,989 research outputs found
DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances
Recent advances in pre-trained language models have significantly improved
neural response generation. However, existing methods usually view the dialogue
context as a linear sequence of tokens and learn to generate the next word
through token-level self-attention. Such token-level encoding hinders the
exploration of discourse-level coherence among utterances. This paper presents
DialogBERT, a novel conversational response generation model that enhances
previous PLM-based dialogue models. DialogBERT employs a hierarchical
Transformer architecture. To efficiently capture the discourse-level coherence
among utterances, we propose two training objectives, including masked
utterance regression and distributed utterance order ranking in analogy to the
original BERT training. Experiments on three multi-turn conversation datasets
show that our approach remarkably outperforms the baselines, such as BART and
DialoGPT, in terms of quantitative evaluation. The human evaluation suggests
that DialogBERT generates more coherent, informative, and human-like responses
than the baselines with significant margins.Comment: Published as a conference paper at AAAI 202
Continuous Decomposition of Granularity for Neural Paraphrase Generation
While Transformers have had significant success in paragraph generation, they
treat sentences as linear sequences of tokens and often neglect their
hierarchical information. Prior work has shown that decomposing the levels of
granularity~(e.g., word, phrase, or sentence) for input tokens has produced
substantial improvements, suggesting the possibility of enhancing Transformers
via more fine-grained modeling of granularity. In this work, we propose a
continuous decomposition of granularity for neural paraphrase generation
(C-DNPG). In order to efficiently incorporate granularity into sentence
encoding, C-DNPG introduces a granularity-aware attention (GA-Attention)
mechanism which extends the multi-head self-attention with: 1) a granularity
head that automatically infers the hierarchical structure of a sentence by
neurally estimating the granularity level of each input token; and 2) two novel
attention masks, namely, granularity resonance and granularity scope, to
efficiently encode granularity into attention. Experiments on two benchmarks,
including Quora question pairs and Twitter URLs have shown that C-DNPG
outperforms baseline models by a remarkable margin and achieves
state-of-the-art results in terms of many metrics. Qualitative analysis reveals
that C-DNPG indeed captures fine-grained levels of granularity with
effectiveness.Comment: Accepted to be published in COLING 202
Isolation and characterization of the outer membrane of Escherichia coli with autodisplayed Z-domains
Abstract“Autodisplay technology” is an expression technique used to display the various recombinant proteins on the outer membrane (OM) of Escherichia coli. The resulting autodisplayed Z-domain has been used to improve the sensitivity of immunoassays. In this work, a facile isolation method of the OM fraction of E. coli with autodisplayed Z-domains was presented using (1) an enzyme reaction for the hydrolysis of the peptidoglycan layer and (2) short centrifugation steps. The purity of the isolated OM fraction was analyzed. For the estimation of contamination with bacterial proteins from other parts of E. coli, Western blots of marker proteins for the OM (OmpA), periplasm (β-lactamase), inner membrane (SecA), and cytoplasm (β-galactosidase) were performed. Additionally, assays of marker components or enzymes from each part of E. coli were carried out including the OM (KDO), inner membrane (NADH oxidase), periplasm (β-lactamase), and cytoplasm (β-galactosidase). The yield of OM isolation using this new method was determined to be 80% of the total OM amount, with less than 1% being contaminants from other parts of E. coli
Stochastic Study of the Effect of Ionic Strength on Noncovalent Interactions in Protein Pores
Salt plays a critical role in the physiological activities of cells. We show that ionic strength significantly affects the kinetics of noncovalent interactions in protein channels, as observed in stochastic studies of the transfer of various analytes through pores of wild-type and mutant α-hemolysin proteins. As the ionic strength increased, the association rate constant of electrostatic interactions was accelerated, whereas those of both hydrophobic and aromatic interactions were retarded. Dramatic decreases in the dissociation rate constants, and thus increases in the overall reaction formation constants, were observed for all noncovalent interactions studied. The results suggest that with the increase of salt concentration, the streaming potentials for all the protein pores decrease, whereas the preferential selectivities of the pores for either cations or anions drop. Furthermore, results also show that the salt effect on the rate of association of analytes to a pore differs significantly depending on the nature of the noncovalent interactions occurring in the protein channel. In addition to providing new insights into the nature of analyte-protein pore interactions, the salt-dependence of noncovalent interactions in protein pores observed provides a useful means to greatly enhance the sensitivity of the nanopore, which may find useful application in stochastic sensing
A novel de novo mutation in the serine-threonine kinase STK11 gene in a Korean patient with Peutz-Jeghers syndrome
BACKGROUND: Peutz-Jeghers syndrome (PJS) is an unusual autosomal dominant disorder characterized by mucocutaneous pigmentation and multiple gastrointestinal hamartomatous polyps. Patients with PJS are at an increased risk of developing multi-organ cancer, most frequently those involving the gastrointestinal tract. Germline mutation of the STK11 gene, which encodes a serine-threonine kinase, is responsible for PJS. METHODS: Using DNA samples obtained from the patient and his family members, we sequenced nine exons and flanking intron regions of the STK11 gene using polymerase chain reaction (PCR) and direct sequencing. RESULTS: Sequencing of the STK11 gene in the proband of the family revealed a novel 1-base pair deletion of guanine (G) in exon 6 (c.826delG; Gly276AlafsX11). This mutation resulted in a premature termination at codon 286, predicting a partial loss of the kinase domain and complete loss of the C-terminal domain. We did not observe this mutation in both parents of the PJS patient. Therefore, it is considered a novel de novo mutation. CONCLUSION: The results presented herein enlarge the spectrum of mutations of the STK11 gene by identifying a novel de novo mutation in a PJS patient and further support the hypothesis that STK11 mutations are disease-causing mutations for PJS with or without a positive family history
Decreased expression of extracellular matrix proteins and trophic factors in the amygdala complex of depressed mice after chronic immobilization stress
BACKGROUND: The amygdala plays an essential role in controlling emotional behaviors and has numerous connections to other brain regions. The functional role of the amygdala has been highlighted by various studies of stress-induced behavioral changes. Here we investigated gene expression changes in the amygdala in the chronic immobilization stress (CIS)-induced depression model. RESULTS: Eight genes were decreased in the amygdala of CIS mice, including genes for neurotrophic factors and extracellular matrix proteins. Among these, osteoglycin, fibromodulin, insulin-like growth factor 2 (Igf2), and insulin-like growth factor binding protein 2 (Igfbp2) were further analyzed for histological expression changes. The expression of osteoglycin and fibromodulin simultaneously decreased in the medial, basolateral, and central amygdala regions. However, Igf2 and Igfbp2 decreased specifically in the central nucleus of the amygdala. Interestingly, this decrease was found only in the amygdala of mice showing higher immobility, but not in mice displaying lower immobility, although the CIS regimen was the same for both groups. CONCLUSIONS: These results suggest that the responsiveness of the amygdala may play a role in the sensitivity of CIS-induced behavioral changes in mice
Problematic Use of Alcohol and Online Gaming as Coping Strategies During the COVID-19 Pandemic: A Mini Review
The COVID-19 (coronavirus disease 2019) pandemic has dramatically changed our daily lives and activities, including those originally intended to serve for leisure and pleasure. Drinking and online gaming became coping behaviors used to rescue ourselves from the stress and restricted lifestyle during the COVID-19 pandemic. However, frequent drinking and gaming can result in the pathological consequences of addiction. Those affected use the stimuli not to obtain pleasure, but rather to avoid the displeasure induced by stress and previous use, often unsuccessfully. This review aims to provide an overview of recent longitudinal cohort studies on alcohol and gaming use during the COVID-19 pandemic, as well as to analyze how the pandemic has affected alcohol and gaming use. There was a substantial risk of alcohol and online gaming overuse during the lockdown, which may depend on the pandemic's duration or overuse patterns. Previous studies have shown that increased alcohol consumption and online gaming are associated with heightened stress and anxiety levels caused by social isolation/quarantine. Over time, frequent or excessive alcohol consumption and gaming could lead to an increased risk of more serious mental health problems. Every effort should be made to mitigate mental health problems and ensure adequate adaptation to these exceptional circumstances. Therefore, it would be helpful to encourage physical activity, social interaction, and collaboration to facilitate psychological and physical health. © Copyright © 2021 Xu, Park, Kang, Choi and Koo.1
The elbow is the load-bearing joint during arm swing
Background Arm swing plays a role in gait by accommodating forward movement through trunk balance. This study evaluates the biomechanical characteristics of arm swing during gait. Methods The study performed computational musculoskeletal modeling based on motion tracking in 15 participants without musculoskeletal or gait disorder. A three-dimensional (3D) motion tracking system using three Azure Kinect (Microsoft) modules was used to obtain information in the 3D location of shoulder and elbow joints. Computational modeling using AnyBody Modeling System was performed to calculate the joint moment and range of motion (ROM) during arm swing. Results Mean ROM of the dominant elbow was 29.7°±10.2° and 14.2°±3.2° in flexion–extension and pronation–supination, respectively. Mean joint moment of the dominant elbow was 56.4±12.7 Nm, 25.6±5.2 Nm, and 19.8±4.6 Nm in flexion–extension, rotation, and abduction–adduction, respectively. Conclusions The elbow bears the load created by gravity and muscle contracture in dynamic arm swing movement. Level of evidenceLevel IV
Wireless thin film transistor based on micro magnetic induction coupling antenna
A wireless thin film transistor (TFT) structure in which a source/drain or a gate is connected directly to a micro antenna to receive or transmit signals or power can be an important building block, acting as an electrical switch, a rectifier or an amplifier, for various electronics as well as microelectronics, since it allows simple connection with other devices, unlike conventional wire connections. An amorphous indium gallium zinc oxide (α-IGZO) TFT with magnetic antenna structure was fabricated and studied for this purpose. To enhance the induction coupling efficiency while maintaining the same small antenna size, a magnetic core structure consisting of Ni and nanowires was formed under the antenna. With the micro-antenna connected to a source/drain or a gate of the TFT, working electrical signals were well controlled. The results demonstrated the device as an alternative solution to existing wire connections which cause a number of problems in various fields such as flexible/wearable devices, body implanted devices, micro/nano robots, and sensors for the 'internet of things' (IoT).1
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