Earticle

Korean textbooks teaching the Chinese language have heretofore shown little variety in translating casual markers from Chinese original into Korean equivalents. Specifically, most if not all casual markers have been rendered as hayekum(let/allow) in the target text of Chinese-Korean translation. Causative verbs appear with great frequency in Chinese. Providing more diversity, therefore, when translating from or into causative Chinese verbs would result in a smoother text that does not sound too monotonous. Korean and Chinese languages use different strategies when encoding situations into causative verbs. In Korean, whether a causer/causee is animate or inanimate determines to a large extent the subject of a sentence, along with the direction of an agent’s action. Generally, Korean grammar prefers not to use inanimate causers when writing sentences. This rule is less than clear-cut, however, in real-world conversations. In such communication, specific contextual information on speakers’ intention and the direction of discourse could yield a wide range of forms, semantics, animacy and controlling force for causative verbs. Taking these grammatical factors into account would help translators working on these verbs to produce texts that read like an original.

시조는 우리의 삶에 역동적이고 정격화 된 치유의 활력을 제공한다. 본 연구는 시조가 명사로 끝나는 부분에서 발화하는 문학치료의 기능을 살펴보고자 하였다. 연구의 결과 시조의 종장에 사용된 명사는 서술어의 기능을 발화시키는 것이었다. 이 시조는 한 음보 단축된 11음보로 응집되면서도 12음보의 기능으로 발화되는 것이다. 이러한 시조의 기능 발화는 문학치료의 부호화에 대한 치료적 서술이다. 그래서 시조나 언어에서 서술하지 않고 명사만 언급해도 치유적인 부호화를 활성화시킬 수 있다. 그 이유는 시조의 명사가 인체에 끼어들어 주어가 되고 인체의 뉴런이 서술어가 되어 문장을 만들어내기 때문이다. 이때 뉴런의 핵이 명사로 들어온 정보를 분석하여 새로운 문장을 만들어낸 것을 인체가 인식하는 것으로 판단된다. 이러한 인식이 또한 인체에서 발화하는 치료의 기능인 부호화의 과정이다.

The Sijo provides dynamic rated therapeutic activities in our life. This study aims to search for the literary therapeutic function secreted from the Sijo that ends with a noun. As a result, the noun used at the final sentence secretes a predicative function. This kind of Sijo functions as twelve sound steps, even though it is condensed of just eleven sound steps with one sound step omitted. This functional secretion of Sijo is therapeutic predicate concerned with encoding of literary therapy. Thus it become possible to activate the therapeutic encoding in Sijo or a language by uttering only noun, instead of the predicate. That's because the noun in the last sentence of Sijo permeated in the human body and is done subject, and neuron of the body becomes a predicate, so that the Sijo's subject and the neuron's predicate are fused into a sentence. During the course the human body seems to recognize that the neuron's nucleus analyzes the information of the noun and makes a new sentence. This recognition might also be regarded as a process of encoding that has therapeutic functions secreted from the human body.

본고는 300여개의 언어를 바탕으로 하여, 수여 사태가 언어적으로 표현되는 방식에 있어서의 언어간 변이를 조사하였다. 한국어의 ‘주-’, 영어의 ‘give’, 프랑스어 의 ‘donner’처럼 하나의 단순 동사 어근으로 표현하는 것이 지역과 계통을 넘어서 가장 지배적인 방책이지만, 그 외의 대안적 방책들도 발견된다. 포괄적인 ‘give’ 동사가 존재하는 유형에도 단순 어근, 복합 어근, 영 어근의 세 하위유형이 존재하고, 포괄적인 ‘give’ 동사가 부재하는 유형에도, 다중 동사 방책, 일반화 방책, 비동사 방책(부치사, 접사) 등이 있다.

This paper is a working report of a survey on cross-linguistic variation in how the generic and basic concept of the transfer event, represented by three-place predicates such as Korean cwu-, English give or French donner, is linguistically encoded, on the basis of the sample of about 300 languages. The dominant strategy is encoding the 'give' event as a simple root, but one can find many alternative strategies, which include complex root (plain and discontinuous), zero root, multiple encoding, general verb, non-verbal encoding, etc.

Named entity recognition (NER) is a crucial task for NLP, which aims to extract information from texts. To build NER systems, deep learning (DL) models are learned with dictionary features by mapping each word in the dataset to dictionary features and generating a unique index. However, this technique might generate noisy labels, which pose significant challenges for the NER task. In this paper, we proposed DL-dictionary features, and evaluated them on two datasets, including the OntoNotes 5.0 dataset and our new infectious disease outbreak dataset named GFID. We used (1) a Bidirectional Long Short-Term Memory (BiLSTM) character and (2) pre-trained embedding to concatenate with (3) our proposed features, named the Convolutional Neural Network (CNN), BiLSTM, and self-attention dictionaries, respectively. The combined features (1-3) were fed through BiLSTM - Conditional Random Field (CRF) to predict named entity classes as outputs. We compared these outputs with other predictions of the BiLSTM character, pre-trained embedding, and dictionary features from previous research, which used the exact matching and partial matching dictionary technique. The findings showed that the model employing our dictionary features outperformed other models that used existing dictionary features. We also computed the F1 score with the GFID dataset to apply this technique to extract medical or healthcare information.

When training neural networks with softmax outputs, one-hot target encoding is commonly used due to its simplicity. This strategy does not incorporate the probability that an input sample belongs to a certain class but adopts "one" or "zero" as the desired output values of neural networks. Instead of the most prevalent one-hot encoding, this paper proposes a probabilistic target encoding to prevent the overfitting of neural networks to training samples. This effect brings about the accuracy improvement of test samples. We demonstrated the effectiveness of the proposed target encoding through simulations of multi-layer perceptrons and convolutional neural networks for various classification problems such as handwritten-digit recognition, isolated-word recognition, image classification, and object recognition tasks. The simulation results show that the proposed probabilistic target encoding is superior to one-hot encoding as it prevents the overfitting of neural networks to training samples.

This paper examines the Encoding Specificity Principle (ESP) and the related retrieval model (Synergistic Ecphoric Model of Retrieval) and assumption of the distinction between episodic and semantic memory. With the examination some difficulties with ESP and the related retrieval model and assumption are discussed.

Spiking Neural Networks (SNNs) offer promising solutions for efficient real-time processing of time-series data by closely emulating biological neuronal dynamics. However, existing encoding methods for converting raw input data into spike trains often introduce significant temporal distortions, complexity, or limitations in learnability, hindering their practical deployment. In this study, we propose the Filtered Temporal-Population (FTP) encoding method, a novel technique that integrates filtering operations into SNN encoding. FTP encoding effectively captures both temporal and spatial correlations within data segments while aligning inputs directly with the temporal axis, making it highly suitable for real-time applications. Evaluations on the MIT-BIH electrocardiogram dataset and other time-series datasets demonstrate that FTP encoding outperforms traditional encoding methods in terms of accuracy, speed, and robustness. Our findings highlight FTP encoding’s potential as a practical and effective solution for real-time SNN-based time-series classification tasks.

Cinnamyl alcohol dehydrogenase (CAD, EC 1.1.1.95), catalyzes the reduction of hydroxycinnamaldehydes to give hydroxycinnamyl alcohols, or "monolignols," the monomeric precursors of lignin. Lignins are important components of cell walls and lignified secondary cell walls play crucial roles in long distance transport of water and nutrients during plant growth and development and in plant defense against biotic and abiotic stresses. Here a cDNA clone containing a CAD gene, named as PgCAD, was isolated from a commercial medicinal plant Panax ginseng. PgCAD is predicted to encode a precursor protein of 177 amino acid residues, and its sequence shares high homology with a number of other plant CADS. The expression of PgCAD in adventitious roots and hairy roots of P. ginseng was analyzed using reverse transcriptase (RT)- PCR under various abiotic stresses such as salt, salicylic acid, wounding and chilling treatment that triggered a significant induction of PgCAD at different time points within 2-48 h post-treatment. This study revealed that PgCAD may help the plants to survive against various abiotic stresses.

Corynebacterium sp. SCR221107 was isolated from the rumen fluid of healthy male Holstein dairy cows from a research farm at Suncheon, Jeollanam-do, Korea. Corynebacterium sp. SCR221107 is a functional probiotic candidate that produces vitamin B12. All Corynebacterium sp. SCR221107 was sequenced using the PacBio RS II and Illumina HiSeq platforms and assembled de novo. The complete genome sequence of Corynebacterium sp. SCR221107 contained one circular chromosome (3,043,024 bp) with a guanine + cytosine (GC) content of 60.1%. Annotation analysis showed the presence of 2,639 protein-coding sequences, 15 rRNA genes, and 57 tRNA genes. Genome analysis found that Corynebacterium sp. SCR221107 encodes various genes associated with vitamin B12 synthesis and transport. The genomic information provided a detailed understanding of Corynebacterium sp. SCR221107, suggesting that this isolate may have potential probiotic applications.

By leveraging the characteristics of both quantum encoding and classical data channel, we present a unique and novel multiuser optical communication system that utilizes fascinating properties of the structured light for information transmission. Specifically, we propose an indoor orbital angular momentum (OAM) multiuser multiple-input multiple-output (MIMO) optical communication system, where the quantum encoding is performed and the multiuser transmission is then analyzed from the context of the classical data channel. In the proposed system, as the OAM beam propagates, its angular spread is analyzed. In addition, we show that the variance of the beam divergence increases with the increasing OAM index mode on the basis of the derived MIMO channel impulse response for OAM carrying Laguerre?Gaussian beams. Comparative studies reveal that the proposed system significantly outperforms the conventional non-orthogonal multiple access (NOMA) applied with MIMO.

The Lactococcus taiwanensis strain K_LL004 was isolated from the gut of a grasshopper (Oxya chinensis sinuosa) collected from local farm in Korea. L. taiwanensis strain K_LL004 is the functional probiotic candidate with an ability to hydrolyse plant polysaccharides. The complete genome of the L. taiwanensis strain K_LL004 contains one circular chromosome (1,995,099 bp) with a guanine + cytosine (GC) content of 38.8%. Moreover, 1,929 Protein- coding sequence, 19 rRNA genes, and 62 tRNA genes were identified based on results of annotation. L. taiwanensis strain K_LL004 has a gene, which encodes hydrolytic enzymes such as beta-glucosidase and beta-xylosidase, that hydrolyzes plant polysaccharides.

Training neural networks with softmax outputs requires assigning target values to output nodes. Due to its simplicity, we often use one-hot encoding, which adopts "one" or "zero" as the desired output values. However, when training neural networks to minimize the cross-entropy error function between the desired and actual output node values, overfitting of neural networks to training samples becomes a significant issue. A probabilistic target encoding has been proposed to mitigate the overfitting. In this paper, we derive the optimal solutions for output nodes that minimize the cross-entropy error function using the probabilistic target encoding. In the extreme case of the probabilistic target encoding, the analysis corresponds to the cross-entropy error function with one-hot encoding. The statistical analyses conducted to derive the optimal solutions provide considerable insights, including the interval of target values for the Bayes classifier.

While motion estimation (ME) efficiently compresses video data by reducing temporal redundancy between frames, it does so at the cost of computational complexity. In particular, the complexity of sub-pixel ME (SME) is greatly limits fast video encoding because the SME requires a complexity-intensive interpolation process to generate imaginary pixels. Thus, this paper proposes a method that conditionally skips SME, including its interpolation process, by utilizing previously encoded motion information. Results show that the proposed method efficiently reduces both the total encoding time and memory access compared to the previous high efficiency video coding (HEVC) reference model.

Microsomal ?-3 fatty acid desaturase (FAD3) is an essential enzyme in the production of the n-3 polyunsaturated fatty acid α-linolonic acid during the seed developing stage. To understand the regulatory mechanism of the gene encoding the w-3 fatty acid desaturase, a genomic fragment corresponding to the previously isolated perilla seed PfFAD3 cDNA was amplified from perilla (Perilla frutescens Britt) by GenomeWalker PCR. Sequence analysis of the fragment provided with identification of a 1485-bp 5'- upstream region and a 241-bp intron in the open reading frame. To determine the tissue-specificity of the PfFAD3 gene expression, the 5'-upstream region was fused to the β-glucuronidase (GUS) gene and incorporated into Arabidopsis thaliana. Histochemical assay of the transgenic plants showed that GUS expression was restricted to seed and pollen, showing that PfFAD3 gene was exclusively expressed in those tissues.

Sentence voice does not change propositional structure but rearranges the proposition into a different information structure. The following experiment investigated previous research on the functional distinction in the encoding of active and passive sentences in terms of the given-new approach in relation to information structure. Furthemore, an attempt was made to test the hypothesis that the logical subject is the focus of the assertion in the passive and the active is presuppositionally neutral(Anisfeld and Klenbort, 1973; Klenbort and Anisfeld, 1974). The result of the experiment supported Klenbort and Anisfeld’s claim that the focal point of the information asserted by the sentence is the logical subject in the passive but failed to support their finding that the active is presuppositionally neutral. The test subjects’ responses indicate that the logical subject in both the active and the passive forms represents the assertional focus when the sentence is isolated from the context.

Recent deep learning models perform well in image and natural language processing. However, in tabular data, there is a problem that good performance is not achieved due to data-level problems. Recently, TabNet, a model that overcomes these shortcomings, has been widely used for tabular data learning. However, categorical variable data does not perform significantly in tabular data. To solve this problem, Catboost Encoding method is used to solve the problem. In the case of this model, the pre-processing of categorical variable data was well utilized to derive more performance than other models, and it showed better performance than other encoding techniques.

Paired box protein, PAX7, is a key molecule for the specification, maintenance and skeletal muscle regeneration of muscle satellite cells. In this study, we identified and characterized the cDNA and amino acid sequences of PAX7 from black sea bream (Acanthopagrus schlegelii ) via molecular cloning and sequence analysis. A. schlegelii PAX7 cDNA was comprised of 1,524 bp encoding 507 amino acids and multiple sequence alignment analysis of the translated amino acids showed that it contained three domains including paired DNA-binding domain, homeobox domain and OAR domain which were well conserved across various animal species investigated. Pairwise Sequence Alignment indicated that A. schlegelii PAX7 had the same amino acid sequences with that of yellowfin seabream (A. latus ) and 99.8% identity and similarity with that of gilt-head bream (Sparus aurata ). Molecular phylogenetic analysis confirmed that A. schlegelii PAX7 formed a monophyletic group with those of teleost and most closely related with those of the fish that belong to Sparidae family including A. latus and S. aurata . In the investigation of its tissue specific mRNA expression, the expression was specifically identified in skeletal muscle tissue and a weak expression was also shown in gonad tissue. The cultured cells derived from skeletal muscle tissues expressed PAX7 mRNA at early passage but the expression was not observed after several times of subculture.

본 연구의 목적은 학력에 따른 DAT(dementia of Alzheimer's type)환자의 인지 부호화 사용의 차이를 살펴보기 위해서 실시되었으며, 언어적(verbal), 시공간적(visual-spatial), 동작적(motoric) 부호화(encoding)를 중심으로 살펴보았다. 정상 노인 30명과 초기 DAT환자 30명을 단어 카드와 실생활에서 사용하는 물건을 사용하여 언어적, 시공간적, 동작적 부호화를 실시하고 회상하게 하였다. 연구 결과 DAT환자가 정상 노인에 비해 기억의 수행이 저조하였으며 저학력자가 고학력자에 비해서 전체적으로 수행이 저조하게 나타났다. 또한 정상 노인과 DAT환자 모두 동작적 부호화 상황에서는 학력의 고, 저에 따른 기억 수행에서 차이가 나타나지 않았으나, 언어적, 시공간적 부호화 방법에서는 고학력자가 저학력자 보다 기억 수행을 더 많이 하였다. 이러한 결과를 통해서 현재 노년층인 저학력 DAT환자에게 효율적인 인지 훈련 전략에 대한 방법을 모색할 수 있다.

The primary purpose of this study was to investigated the differences of cognitive encoding among DAT(Dementia of Alzheimer's Type) patients' according to their educational level. In order to achieve this goal, subjects were presented categorizable list of words or objects under three different encoding condition; verbal, visual-spacial, motoric encoding. As a result of this research, the DAT patients have less memory perform than normal old people. And people who had lower level of education have less memory performance than who had higher level of education. Moreover, there was no difference between normal group and DAT group using memory ability in motoric encoding method according to the level of educational. But, in terms of verbal encoding and visual-spatial encoding methods, people who had more education have more memory ability. The present results suggested to the possibility of different education effect on the encoding methods.