• Molecules and Cells
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• v.45 no.7
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• pp.444-453
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• 2022

Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.

• Clinical and Experimental Pediatrics
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• v.65 no.5
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.369-375
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• 2022

The article substantiates the need and shows the features of introducing SMART management into the system of public management of regional development in the context of strengthening the national security of Ukraine. Disclosed are such provisions as: goal-setting; state mission; state mission in Ukraine; goals of the Ukrainian state; strategic management priorities in Ukraine. Differences between the purpose of the organization and the purpose of the state are determined. The characteristic of the goal at the state level is given. The management standards in SMART management are characterized. The issues of the exhaustibility of existing SMART criteria are reviewed and it is proposed to supplement them with two such as: inspiration (inspiration) and ity (ethics). Two main principles are defined (evaluated (assessment), reviewed (review)), which must be observed when introducing SMART management into the system of public management of regional development in the context of strengthening the national security of Ukraine.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.50-56
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• 2022

In order to process a vast amount of data, there is demand for a new system with higher processing speed and lower energy consumption. To prevent 'memory wall' in von Neumann architecture, RRAM, which is a neuromorphic device, has been researched. In this paper, we summarize the features of RRAM and propose the device structure for characteristic improvement. RRAM operates as a synapse device using a change of resistance. In general, the resistance characteristics of RRAM are nonlinear and random. As synapse device, linearity and uniformity improvement of RRAM is important to improve learning recognition rate because high linearity and uniformity characteristics can achieve high recognition rate. There are many method, such as TEL, barrier layer, NC, high oxidation properties, to improve linearity and uniformity. We proposed a new device structure of TiN/Al doped TaO_x/AlO_x/Pt that will achieve high recognition rate. Also, with simulation, we prove that the improved properties show a high learning recognition rate.

• BMB Reports
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• v.55 no.9
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• pp.429-438
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• 2022

Cervical cancer is the fourth most common malignancy in women worldwide. Although infection from human papillomavirus (HPV) has been the leading cause of cervical cancer, HPV-negative cervical cancer accounts for approximately 3-8% of all cases. Previous research studies on cervical cancer have focused on HPV-positive cervical cancer due to its prevalence, resulting in HPV-negative cervical cancer receiving considerably less attention. As a result, HPV-negative cervical cancer is poorly understood. Its etiology remains elusive mainly due to limitations in research methodology such as lack of defined markers and model systems. Moreover, false HPV negativity can arise from inaccurate diagnostic methods, which also hinders the progress of research on HPV-negative cervical cancer. Since HPV-negative cervical cancer is associated with worse clinical features, greater attention is required to understand HPV-negative carcinoma. In this review, we provide a summary of knowledge gaps and current limitations of HPV-negative cervical cancer research based on current clinical statistics. We also discuss future directions for understanding the pathogenesis of HPV-independent cervical cancer.

• Fourth Industrial Review
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• v.1 no.1
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• pp.31-40
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• 2021

Purpose - According to the importance of business simulation learning as a new type of business learning tool, this study reviews the dimensions of business education and a brief history of business education simulation. At the end Capsim strategic management simulation program is introduce with its feature. Research design, data, and methodology - This study has been analyzed in a way that reviews at previous literature on simulation learning and looks at examples and features of Capsim simulation, online business simulation tools which has been used in the global market. Result - Capsim simulations are designed to offer focused opportunities for deep practice. That's why they are often more effective than passive tools such as textbooks, videos, or lectures. By the way, 'deep practice' is very different from 'ordinary practice'. After commuters who drive to school or work can accumulate thousands of hours of driving, but that doesn't make them expert drivers. The key to deep practice is self-awareness. That is, paying attention to what you are doing well and not so well. This is so important to learn that scientists use a specific term for it: 'metacognition', or thinking about the way you think and learn. Conclusion - The use of business simulation learning, such as Capsim, which is a given case, can create similar local systems by potentially engaging a large number of users in the virtual market. It could also be used as an individual to complete business training for students and those who are active in the business field of business.

• Journal of Korea Trade
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• v.24 no.7
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• pp.107-124
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• 2020

Purpose - We assess the trade remedies rules in a host of Korea's FTAs to explore the trade policies for the effective implementation of FTA trade remedies rules. Also we develop the strategies of the future FTA negotiations of trade remedies rules. Design/methodology - After we review the key features of FTA trade remedies rules, we examine whether the rules are WTO-consistent or not. Next, we touch upon the WTO-plus characteristics of some provisions. Our main methodology is to compare the trade remedies rules in the numerous Korea's FTAs. Another methodology is to link those rules to the relevant WTO agreements and WTO dispute cases with a view to drawing lessons for trade policies and FTA negotiations. Findings - We find that most of the trade remedies rules are WTO-consistent. Moreover, we find that notification and consultation requirment, mandatory lesser duty rule, explicit prohibition of zeroing method, and public interest clause are WTO-plus. We also find that there are limitiations in the application of some global safeguard exclusion rules because of their non-mandatory nature. Originality/value - While most of previous studies focus mainly on the unique aspects of specific FTAs, our study analyzes comprehensively the trade remedies rules in the various Korea's FTAs. Based on the comprehensive analysis, we figure out the areas to be clarified and improved for the effective implementation of FTAs and the strategies for the future FTA trade remedies negotiations. As a consequence, our paper is expected to contribute to the academic research on FTA policies as well as the national economy.

• Archives of Plastic Surgery
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• v.49 no.1
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• pp.5-11
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• 2022

Facial feminization surgery (FFS) refers to a set of procedures aimed at altering the features of a masculine face to achieve a more feminine appearance. In the second part of this two-part series, assessment and operations involving the midface, mandible, and chin, as well as soft tissue modification of the nasolabial complex and chondrolaryngoplasty, are discussed. Finally, we provide a review of the literature on patient-reported outcomes in this population following FFS and suggest a path forward to optimize care for FFS patients.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1515-1526
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• 2022

Eukaryotic chromatin is highly organized in the 3D nuclear space and dynamically regulated in response to environmental stimuli. This genomic organization is arranged in a hierarchical fashion to support various cellular functions, including transcriptional regulation of gene expression. Like other host cellular mechanisms, viral pathogens utilize and modulate host chromatin architecture and its regulatory machinery to control features of their life cycle, such as lytic versus latent status. Combined with previous research focusing on individual loci, recent global genomic studies employing conformational assays coupled with high-throughput sequencing technology have informed models for host and, in some cases, viral 3D chromosomal structure re-organization during infection and the contribution of these alterations to virus-mediated diseases. Here, we review recent discoveries and progress in host and viral chromatin structural dynamics during infection, focusing on a subset of DNA (human herpesviruses and HPV) as well as RNA (HIV, influenza virus and SARS-CoV-2) viruses. An understanding of how host and viral genomic structure affect gene expression in both contexts and ultimately viral pathogenesis can facilitate the development of novel therapeutic strategies.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.4
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• pp.429-453
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• 2022

Numerical modeling and scenario composition are needed to characterize the geological environment of the disposal site and analyze the long-term evolution of natural barriers. In this study, processes and features of the hydro-mechanical behavior of natural barriers were categorized and represented using the interrelation matrix proposed by SKB and Posiva. A hydro-mechanical coupled model was evaluated for analyzing stress field changes and fracture zone re-activation. The processes corresponding to long-term evolution and the hydro-mechanical mechanisms that may accompany critical processes were identified. Consequently, practical numerical methods could be considered for these geological engineering issues. A case study using a numerical method for the stability analysis of an underground disposal system was performed. Critical stress distribution regime problems were analyzed numerically by considering the strata's movement. Another case focused on the equivalent continuum domain composition under the upscaling process in fractured rocks. Numerical methods and case studies were reviewed, confirming that an appropriate and optimized modeling technique is essential for studying the stress state and geological history of the Korean Peninsula. Considering the environments of potential disposal sites in Korea, selecting the optimal application method that effectively simulates fractured rocks should be prioritized.