Linkage Structure Research Articles

국내 바이오산업의 산업연계구조와 연구개발투자의 경제적 파급효과 분석 : Ritz-Spaulding 모형의 산출-산출승수를 활용한 2006년과 2013년 비교분석

최근 바이오기술이 발전하고 타 산업과 융합이 활발해지면서 연관 산업과의 지식교류 및 확산을 파악할 필요성이 증가하고 있다. 이에 본 연구는 바이오산업을 7개의 세부부문으로 구분하고 이를 반영한 36개 산업의 산업연관표를 재작성하여 산업연관분석을 실시하였다. 또한 기존의 외생부문과 내생부문 간 관계를 매개하는 기본 투입산출모형의 제약사항을 극복하고자 모형을 확장하여 내생부문 간 관계를 매개하는 산출-산출 승수를 도출하였다. 이를 기반으로 분석한 결과 바이오산업은 바이오의약산업 규모가 상대적으로 매우 커 의존적인 형태로 나타났다. 또한, 2006년과 2013년 사이에 수요유발효과는 증가하고 공급지장효과는 낮아졌다. 연구개발비용에 대한 파급효과는 전·후방산업에서 상이하게 나타났는데 전방산업에 대한 파급력은 바이오산업의 세부별로 일부 증가, 일부 감소한 형태로 나타났다. 반면 후방산업은 연구개발비용의 증가폭에 따라 2006년과 2013년 간 영향력이 다르게 나타났다. 본 논문은 데이터와 산업연관분석의 한계점에도 불구하고 바이오산업을 7개의 세부산업으로 정의해 바이오산업의 산업연계구조를 분석하는 한편, 8개의 R&D 투자 시나리오에 따라 파급효과를 측정했다는 점에서 의의가 있다고 하겠다.

Selection, Linkage, and Population Structure Interact To Shape Genetic Variation Among Threespine Stickleback Genomes.

The outcome of selection on genetic variation depends on the geographic organization of individuals and populations as well as the organization of loci within the genome. Spatially variable selection between marine and freshwater habitats has had a significant and heterogeneous impact on patterns of genetic variation across the genome of threespine stickleback fish. When marine stickleback invade freshwater habitats, more than a quarter of the genome can respond to divergent selection, even in as little as 50years. This process largely uses standing genetic variation that can be found ubiquitously at low frequency in marine populations, can be millions of years old, and is likely maintained by significant bidirectional gene flow. Here, we combine population genomic data of marine and freshwater stickleback from Cook Inlet, Alaska, with genetic maps of stickleback fish derived from those same populations to examine how linkage to loci under selection affects genetic variation across the stickleback genome. Divergent selection has had opposing effects on linked genetic variation on chromosomes from marine and freshwater stickleback populations: near loci under selection, marine chromosomes are depauperate of variation, while these same regions among freshwater genomes are the most genetically diverse. Forward genetic simulations recapitulate this pattern when different selective environments also differ in population structure. Lastly, dense genetic maps demonstrate that the interaction between selection and population structure may impact large stretches of the stickleback genome. These findings advance our understanding of how the structuring of populations across geography influences the outcomes of selection, and how the recombination landscape broadens the genomic reach of selection.

Characterization of the Salmonella Typhimurium core oligosaccharide and its reducing end 3-deoxy-d-manno-oct-2-ulosonic acid used for conjugate vaccine production

One of the strategies adopted for the development of a bivalent conjugate vaccine against invasive nontyphoidal Salmonella consists of linking the O-antigen component of S. Typhimurium and S. Entertidis lipopolysaccharides to the carrier protein CRM197, a non-toxic variant of diphtheria toxin. The conjugation reaction uses the reducing end residue 3-deoxy-d-manno-oct-2-ulosonic acid (Kdo) of the core to which the O-antigen chain is bound (OAg-core). OAg-core chains are cleaved from the lipid A directly in the fermentation broth by mild acid treatment. Kdo has been reported to undergo structural changes under these conditions and therefore the Kdo at the reducing end was thoroughly analysed to verify its structural integrity. For this purpose, low molecular mass OAg-core chains extracted from S. Typhimurium wild type bacteria and core oligosaccharides extracted from S. Typhimurium bacteria mutated not to produce O-antigen repeats were characterized by GLC-MS, MALDI-TOF-MS and NMR spectroscopy. Moreover, a combination of 1H–1H and 1H–13C experiments confirmed the linkage positions, sequence and structure of the octasaccharide core with 5-linked Kdo present at the reducing end in its native structure: α-GlcpNAc-(1→2)-α-Glcp-(1→2)-α-Galp-(1→3)-[α-Galp-(1→6)]-α-Glcp-(1→3)-[α-Hepp-(1→7)]-α-Hepp-(1→3)-α-Hepp-(1→5)-Kdo.

Control of nanostructures and fracture toughness of epoxy/acrylic block copolymer blends using in situ manipulation of the epoxy matrix reaction type

The effect of small amounts of curing catalysts on the nanostructures and mechanical properties of epoxy/acrylic block copolymer blends were investigated. Poly(methyl methacrylate)-b-poly(n-butyl acrylate)-b-poly (methyl methacrylate) (PMMA-b-PnBA-b-PMMA) triblock copolymer (acrylic BCP) was blended with diglycidyl ether of bisphenol-A epoxy thermosets. The blends were cured using phenol novolac (PN) with curing catalysts at less than 1 wt%. Three different curing catalysts, triphenylphosphine (TPP), 2,4,6-tris(dimethyl amino methyl)phenol (DMP), and 1,2-dimethylimidazole (DMIz), were compared. A polyol-type linkage structure was formed in the cured epoxy matrix using TPP, whereas both polyether-type linkage structure and polyol-type linkage structure were formed when DMP and DMIz were used. As a result, different nanostructures were formed in response to the different linkage structures in the epoxy matrix originated from the same blend composition of epoxy/acrylic BCP/PN. The TPP catalyst gave a spherical nanostructure, while the DMP and DMIz catalysts gave branched cylindrical nanostructures in the epoxy/acrylic BCP/PN blends. The compatibility of the PMMA-block chains of the acrylic BCPs to the cured epoxy matrix was a key factor that determined the nanostructures. The fracture toughness of the cured blends was dependent on both the nanostructures in the blends and the ductility (extent of cross-linking density) of the epoxy matrix.

Learning and Searching Pseudo-Boolean Surrogate Functions from Small Samples.

When searching for input configurations that optimise the output of a system, it can be useful to build a statistical model of the system being optimised. This is done in approaches such as surrogate model-based optimisation, estimation of distribution algorithms, and linkage learning algorithms. This article presents a method for modelling pseudo-Boolean fitness functions using Walsh bases and an algorithm designed to discover the non-zero coefficients while attempting to minimise the number of fitness function evaluations required. The resulting models reveal linkage structure that can be used to guide a search of the model efficiently. It presents experimental results solving benchmark problems in fewer fitness function evaluations than those reported in the literature for other search methods such as EDAs and linkage learners.

A Unified Framework for De-Duplication and Population Size Estimation (with Discussion)

Data de-duplication is the process of detecting records in one or more datasets which refer to the same entity. In this paper we tackle the de-duplication process via a latent entity model, where the observed data are perturbed versions of a set of key variables drawn from a finite population of N different entities. The main novelty of our approach is to consider the population size N as an unknown model parameter. As a result, a salient feature of the proposed method is the capability of the model to account for the de-duplication uncertainty in the population size estimation. As by-products of our approach we illustrate the relationships between de-duplication problems and capture-recapture models and we obtain a more adequate prior distribution on the linkage structure. Moreover we propose a novel simulation algorithm for the posterior distribution of the matching configuration based on the marginalization of the key variables at population level. We apply our method to two synthetic data sets comprising German names. In addition we illustrate a real data application, where we match records from two lists which report information about people killed in the recent Syrian conflict.

A portable and spring-guided hand exoskeleton for exercising flexion/extension of the fingers

In this paper, we developed a portable and spring-guided hand exoskeleton system for exercising flexion/extension of the fingers. The exoskeleton was designed with a simple structure to aid finger motion with one degree of freedom (DOF). The desired joint trajectory of the exoskeleton was determined based on the user joint ROM and general finger motion obtained by the hand flexion/extension experiments. The design of the linkage structure was optimized to maximally satisfy the desired trajectory. A spring attached to the structure generates the force to guide the fingers toward the desired posture when they deviate from the desired position. We used a finite element method (FEM) to analyze the transmitted moments for MCP and PIP joints. A prototype of the device was fabricated, and the performance of the system was experimentally verified. The experimental results of the finger motion indicated that the proposed system provided good guidance for flexion/extension of the fingers. Furthermore, the results of the force distribution experiment verified that the joint moments by the system are matched to the expected moments by FEM analysis. Thus, the CPM device successfully guided the users fingers along the desired trajectory and distributed the expected moments to the joints.

Inter-Intra Information Preserving Attributed Network Embedding

To alleviate the problem caused by the sparsity of network structure which is often the case in large-scale network, attributed network embedding has attracted an increasing amount of attention. Some existing attributed network embedding models integrate linkage structure and node attribute by adding a consistency criterion on the structure representation and attribute representation, whereby the similarity between them can be ensured. However, to enforce the structure and attribute representations to be similar may cause the information distortion due to the inherent difference between these two kinds of information. Additionally, the existing models mainly focus on learning the inter-relation between structure and attribute information, while the intra-characteristic of each information is ignored, leading to the information loss. To address the above two problems, we propose a novel model named Inter-Intra Information Preserving Attributed Network Embedding (IINE) to effectively learn the node representations of attributed network, which can not only capture the inter-relation between structure and attribute information with less information distortion but also effectively preserve the intra-characteristic of each information. The proposed model is composed of a primary model named coupled autoencoder and two auxiliary models named structure miner and attribute miner. The coupled autoencoder trains the node representation by smoothly combining both structure and attribute information, while the structure miner and attribute miner are utilized to further mine the intra-characteristic from the corresponding information so as to assist the primary model. The Extensive experiments are conducted on seven real-world datasets, and the results confirm the superior performance of IINE over several state-of-the-art models.

Butterfly‐Inspired Triboelectric Nanogenerators with Spring‐Assisted Linkage Structure for Water Wave Energy Harvesting

AbstractThe exploration of water wave energy to generate electric power is a promising and valuable way to solve global energy crisis. Triboelectric nanogenerators (TENGs) are considered as one of the most promising approaches for harvesting water wave energy. Here, a butterfly‐inspired triboelectric nanogenerator (B‐TENG) with spring‐assisted four‐bar linkage is fabricated to acquire multidirectional water wave energy from different types of movements generated by the device. The arc‐shaped outer shell can efficiently absorb the impact force of water wave and inner spring‐assisted four‐bar linkage can induce multiple contact–separation motion of TENG module, both of which allow the B‐TENG to harvest energy from different types of low‐frequency waves. The short‐circuit current and open‐circuit voltage of this B‐TENG device can reach 75.35 µA and 707.01 V, while a maximum output power density of 9.559 W m−3 can be achieved and 180 light‐emitting diodes can be directly lightened up by this B‐TENG. The energy generated from this B‐TENG can also be stored in a capacitor and to drive some marine sensor devices, such as an electronic thermometer. This proposed B‐TENG device is specially designed for multidirectional water energy harvesting and it may have good application prospects for ocean information monitoring and power supply to oceanic islands.

Alkaline extraction and characterization of residual hemicellulose in dissolving pulp

Residual hemicellulose in dissolving pulp is known as a reason for deterioration of final product quality and processability problems during cellulose derivative production. However, the issue caused by the residual hemicellulose is not fully understood and is primarily based on industrial experience. To better understand the effect of hemicellulose on cellulose derivative process, hemicellulose in prehydrolysis kraft hardwood dissolving pulp was extracted and its glycosidic linkage structure was thoroughly analysed. Two-stage alkaline extraction, consisting of 24 wt% KOH solution and 18 wt% NaOH with 4 wt% H3BO3 solution, was found effective for the sequential extraction of high purity xylan and glucomannan from the dissolving pulp. Considering the purity and yield of extracted xylan, room temperature for Stage-1 KOH extraction condition was preferred, while 1 °C was preferred for Stage-2 NaOH extraction. Mechanical refining treatment at a mild condition improved the extraction yield of hemicellulose, although the molecular weight of the cellulose was reduced with severe refining condition. Glycosidic linkage analysis showed that native 4-O-methylglucuronic acid side groups were removed during pulping process, resulting in a linearized xylan structure, while a high amount of glucuronic acid was detected in commercial beechwood xylan. The extracted hemicellulose from the second stage showed relatively high number of branched backbone unit e.g., 1,4,6-linked mannose and 1,4,6-linked glucose. The protocol developed in this study should be useful for hemicellulose-related applications.

In Search of a Causal Model of the Organization–Public Relationship in Public Relations

I explored the underlying linkage structure between relational indicators in the organization–public relationship setting to establish which dimension takes precedence over the others, and whether there is a cause-and-effect relationship among the various dimensions. The results showed that control mutuality was the primary relationship indicator, affecting trust and satisfaction. As predicted, satisfaction affected trust. Finally, trust significantly affected commitment. In the university–student relationship setting, the results showed that trust and satisfaction played a mediating role among the dimensions. If it is accepted that the operative effect of relationship management is to initiate, maintain, and enhance the organization's relationship with the strategic public, then control mutuality might play an antecedent role in the development of satisfaction and trust. Thus, sharing the decision-making process with the public is more likely to increase the level of trust and satisfaction.

Surveying silicon nitride nanopores for glycomics and heparin quality assurance

Polysaccharides have key biological functions and can be harnessed for therapeutic roles, such as the anticoagulant heparin. Their complexity—e.g., >100 monosaccharides with variety in linkage and branching structure—significantly complicates analysis compared to other biopolymers such as DNA and proteins. More, and improved, analysis tools have been called for, and here we demonstrate that solid-state silicon nitride nanopore sensors and tuned sensing conditions can be used to reliably detect native polysaccharides and enzymatic digestion products, differentiate between different polysaccharides in straightforward assays, provide new experimental insights into nanopore electrokinetics, and uncover polysaccharide properties. We show that nanopore sensing allows us to easily differentiate between a clinical heparin sample and one spiked with the contaminant that caused deaths in 2008 when its presence went undetected by conventional assays. The work reported here lays a foundation to further explore polysaccharide characterization and develop assays using thin-film solid-state nanopore sensors.

Connectives and discourse markers in Ancient Greek

Abstract The Ancient Greek particle atár has been described as a connective device that encodes either an adversative or a progressive relation between sentences. The purpose of this paper is to revise the description of this particle by framing its analysis within a consistent and theoretically up-to-date model of clause linkage and discourse structure. Starting from previous findings on the function of atár in Homer, I undertake a corpus analysis of atár in Euripides and Aristophanes. This analysis reveals differences in usage at different stages of the language that have been previously neglected. Whereas in Homer, atár largely behaves as a connective and encodes a semantic relation of oppositive contrast between sentences, in later texts it rather behaves as a discourse marker and contributes to the management of both thematic continuity and interactional practices. These differences point to a specific diachronic path of grammaticalization that accounts for the changes undergone by atár.

Evolution of the linkage structure of ICT industry and its role in the economic system: the case of Korea

ABSTRACTWhen assessing the structural role of an industry sector within an economic system, considering its relationship to other sectors is crucial. Among others, Information and Communication Technology (ICT) industry, one of the innovation accelerators or key engines of economic growth, is evaluated. Specifically, we analyze inter-industry production inducement linkages within a qualitative input–output analysis framework, since it is useful for understanding the key structure of an economic system. Our purpose is to understand the significant spillover structure of the Republic of Korea’s ICT industry within the national production system, as it has played an important role in the national economy and grown dramatically over the years. The findings from the structural analysis, focused on changes in links, are as follows: First, ICT manufacturing showed a higher degree of heterogeneity than ICT service sectors in its sensitivity effects structure, an indication that this sector needs to be utilized in various other industries. Second, the spectrum of industries having significant production inducement linkages with the ICT industry is limited and furthermore, the influence effects of the ICT manufacturing sector diminished considerably although the ICT industry’s sensitivity effects increased. Finally, intra-industry linkages within the ICT industry are gradually strengthened especially between ICT services and manufacturing. These findings call for sustained policy efforts to promote the virtuous circle in the overall inter-industry production inducement system, by increasing the utilization of products and services from other sectors by ICT sectors (especially ICT manufacturing) as well as the application of ICT in other sectors.

Role of linkage structures in supply chain for managing greenhouse gas emissions

This study describes a structural decomposition analysis (SDA) of Japanese greenhouse gas (GHG) emissions from 1990 to 2005, focusing on four linkage structures in the Leontief inverse representing supply chains in Japan. The developed RAS-invariant decomposition was applied to Japanese linked input–output tables for the three 5-year periods studied. It examined the effect of the Leontief inverse on emissions changes into the specific effects of forward linkage, backward linkage, the average of forward/backward linkage and kernel structure. Our SDA method solves the problem of parameter independence completely. The accuracy of those effects has been improved mathematically compared with conventional methods. For example, it was detected that backward linkage contributes to an increase in GHG emissions, while conventional methods erroneously determine a decrease. The results of the SDA confirmed that forward linkage and kernel structure contributed to a rise in GHG emissions, and that backward linkage consistently increased emissions in the three periods. Some sectors have robust linkage in the supply chain with consistently increasing emissions, which should be preferentially improved to mitigate their indirect GHG emissions in Japan.

Spatially Coherent Feature Learning for Pose-Invariant Facial Expression Recognition

Feature learning has enjoyed much attention and achieved good performance in recent studies of image processing. Unlike the required training conditions often assumed there, far less labeled data is available for training emotion classification systems. In addition, current feature learning is typically performed on an entire face image without considering the dependency between features. These approaches ignore the fact that faces are structured and the neighboring features are dependent. Thus, the learned features lack the power to describe visually coherent facial images. Our method is therefore designed with the goal of simplifying the problem domain by removing expression-irrelevant factors from the input images, with a key region-based mechanism, which is an effort to reduce the amount of data required to effectively train the feature-learning methods. Meanwhile, we can construct geometric constraints between the key regions and its detected positions. To this end, we introduce a Spatially Coherent featurelearning method for Pose-invariant Facial Expression Recognition (SC-PFER). In our model, we first perform face frontalization through a 3D pose-normalization technique, which could normalize poses while preserving the identity information through synthesizing frontal faces for facial images with arbitrary views. Subsequently, we select a sequence of key regions around 51 key points in the synthetic frontal face images for efficient unsupervised feature learning. Finally, we introduce a linkage structure over the learning-based features and the corresponding geometry information of each key region to encode the dependencies of the regions. Our method, on the whole, does not require training multiple models for each specific pose and avoids separating training and parameter tuning for each pose. The proposed framework has been evaluated on two benchmark databases, BU-3DFE and SFEW, for pose-invariant Facial Expression Recognition (FER). The experimental results demonstrate that our algorithm outperforms current state-of-the-art FER methods. Specifically, our model achieves an improvement of 1.72% and 1.11% FER accuracy, on average, on BU-3DFE and SFEW, respectively.

Development of a dual university system health research partnership as a foundation for the Sustainable Development Goals

Abstract Background An innovative dual-system collaboration between the University of the West Indies and the State University of New York was created and implemented by a joint Health Research Faculty Task Force to establish a platform for education and research that would yield an integrated approach to the Sustainable Development Goals (SDGs). Methods Following the establishment of a joint Center for Leadership and Sustainable Development, a needs assessment was conducted to identify research and education priorities that would benefit from a dual-system linkage structure. Partnerships were facilitated using HUBzero—an open-source software platform with project-specific faculty and staff assigned to each development group. Findings Programmes in virology research; antimicrobial resistance and stewardship; liver, kidney, and metabolic diseases; and autoimmune diseases, together with the creation of a Clinical Research Center, were identified as highest priorities. Cannabinoid sciences and a joint effort in cancer research, natural products, and nanotechnology to identify indigenous compounds and develop nanomedicine were also key areas. A working group focused on a strategy for workforce planning through science, technology, engineering, and mathematics has also been implemented. Interpretation This programme uses innovative technology platforms to promote shared project development and is a novel alternative to the traditional model that requires travel and prolonged visits at different training sites. A framework is now established to enable the Joint Health Research Faculty Task Force to begin implementation of high-impact health research initiatives as a foundation for multiple SDGs and to drive regional timelines and milestones. These education and research programmes will be funded through competitive research grants and used to complete data analytics for budget forecasting to achieve the SDGs. Funding None.

Polarization-induced interference within electromagnetically induced transparency for atoms of double- V linkage

People have been paying attention to the role of atoms' complex internal level structures in the research of electromagnetically induced transparency (EIT) for a long time, where the various degenerate Zeeman levels usually generate complex linkage patterns for the atomic transitions. It turns out, with special choices of the atomic states and the atomic transitions' linkage structure, clear signatures of quantum interference induced by the probe and coupling light's polarizations can emerge from a typical EIT phenomena. We propose to study a four state system with double-V linkage pattern for the transitions and analyze the polarization induced interference under the EIT condition. We show that such interference arises naturally under mild conditions on the optical field and atom manipulation. Its anticipated properties and its potential application of all optical switching in polarization degree of freedom are also discussed. Moreover, we construct a variation form of double-M linkage pattern where the polarization induced interference enables polarization-dependent cross-modulation between incident lights that can be effective even at the few-photon level. The theme is to gain more insight into the essential question: how can we build non-trivial optical medium where incident lights will induce polarization-dependent non-linear optical interactions, covering a wide range of the incidence intensity from the many-photon level to the few-photon level, respectively.

Using Chemical Synthesis To Study and Apply Protein Glycosylation.

Protein glycosylation is one of the most common post-translational modifications and can influence many properties of proteins. Abnormal protein glycosylation can lead to protein malfunction and serious disease. While appreciation of glycosylation's importance is growing in the scientific community, especially in recent years, a lack of homogeneous glycoproteins with well-defined glycan structures has made it difficult to understand the correlation between the structure of glycoproteins and their properties at a quantitative level. This has been a significant limitation on rational applications of glycosylation and on optimizing glycoprotein properties. Through the extraordinary efforts of chemists, it is now feasible to use chemical synthesis to produce collections of homogeneous glycoforms with systematic variations in amino acid sequence, glycosidic linkage, anomeric configuration, and glycan structure. Such a technical advance has greatly facilitated the study and application of protein glycosylation. This Perspective highlights some representative work in this research area, with the goal of inspiring and encouraging more scientists to pursue the glycosciences.

Linkage Structure among Rural Tourist Spots and Challenges to Construct a Round Trip Package

Linkage Structure among Rural Tourist Spots and Challenges to Construct a Round Trip Package