Ministry of Trade, Industry and Energy

The eco-industrial park (EIP), which aims to minimize by-product and unused energy via reuse and recycling within the industrial complex, offers an innovative pathway to realize regional eco-industrial development. As an environmental, as well as business, innovation, the EIP enables changing the perception of industries and create new business values via the whole supply chain, but such evidences have been less reported to date. As one of the world famous promoter on EIPs, the Republic of Korea (ROK) initiated a national EIP project to enhance its competitiveness and solve environmental problems. While the existing literature reviewed and highlighted its economic outcomes in terms of direct performances of firms within the project, the indirect impacts on the supply chain of national economy were less investigated. Within this circumstance, this study performed a first attempt to apply an input-output analysis (IOA) to investigate the effects of the EIP project on the whole economic system of Korea, via an exogenous specification of the EIP sector in the input-output tables (IOTs). General economic effects in terms of value-added change, employment generation, as well as specific effects like the inducement effects and effects of supply shortage and price pervasiveness were evaluated based on the IOA approach (including demand-driven, supply-driven, and Leontief price models). Results highlighted that, from the supply chain perspective, implementing the EIP project made production and value-added grow by around 1264 billion KRW and 272 billion KRW, respectively (with a unit induction coefficient of 1.6201 and 0.3489 for production and value-added). While generating a direct employment around 1000, an indirect employment was also created of over 5000 persons in the whole supply chain (with an employment inducement effect of 6.4512 persons per 1 billion KRW investment). The production shortage cost from 1 KRW of supply failure is 1.1230 KRW. In summary, EIP was proved to be not environmentally friendly, but also a driver to improve the overall economic performance of upstream and downstream industries in the whole supply chain. As a first attempt to link IOA with EIP, the results of this paper are expected to enlighten policy-makers to forward continued improvement on EIP promotion and combine the EIP idea within national economic system reform and planning.

Double half‐Heuslers comprising two aliovalent half‐Heuslers are promising candidates for thermoelectric materials because of their intrinsically low lattice thermal conductivity; however, poor electronic transport properties need to be overcome. Herein, the effects of Sn doping on the electronic and thermal transport properties of p‐type Ti 2 FeNiSb 2 to enhance the thermoelectric performance via the compositional tuning route are investigated. The power factor is significantly improved owing to the synergetic effect of the increase in the density‐of‐states effective mass and the carrier concentration. In addition, the lattice thermal conductivity is slightly reduced, benefitted from intensified phonon scattering due to lattice disordering by Sn substitution at the Sb‐site. A peak figure of merit ( zT ) of ≈0.28 is obtained at 973 K in Ti 2 FeNiSb 1.8 Sn 0.2 , which is almost twice higher than that of the pristine Ti 2 FeNiSb 2 .

Special Economic Zones have played an
\n important role in the economic growth of many developing and
\n advanced-developing nations, including Bangladesh, Brazil,
\n India, Republic of Korea, Thailand, Turkey and Vietnam.
\n These zones provide tailored infrastructure and business
\n services, and they have become a successful model for
\n large-scale job creation, transfer of skills and technology,
\n export diversification, and industrial development led by
\n foreign direct investment. In the next era of industrial
\n zone development, sustainability and eco-industrial growth
\n play paramount roles in minimizing environmental and social
\n risks while generating profits for firms. It has become
\n urgent to explore these models and to understand the
\n contexts in which they can tackle the environmental and
\n ecological challenges of our times while retaining their
\n role as production hubs and growth centers. This report,
\n based primarily on a global conference Eco-Industrial Parks
\n (EIP) 2015, held in Seoul, Republic of Korea in October
\n 2015, provides the latest thinking on eco-industrial parks,
\n bringing together experiences from different countries and
\n providing a vision on how these initiatives can be scaled up
\n or mainstreamed. It will provide policy makers with insight
\n conceptualizing EIPs and what different factors need to be
\n considered in putting together an EIP program. The report
\n builds the basis for further development of guidelines and
\n step-by-step approaches on how to develop a national program
\n on EIPs.

Interfacial effects on single-layer graphene (SLG) or multilayer graphene (MLG) properties greatly affect device performance. Thus, the effect of the interface on the temperature coefficient of resistance (TCR) on SLG and MLG due to surface-deposited core-shell metallic nanoparticles (MNPs) and various substrates was experimentally investigated. Observed substrates included glass, SiO2, and Si3N4. We show that these modifications can be used to strongly influence SLG interface effects, thus increasing the TCR up to a 0.456% per K resistance change when in contact with the SiO2 substrate at the bottom surface and MNPs on the top surface. However, these surface interactions are muted in MLG due to the screening effect of nonsuperficial layers, only achieving a −0.0998% per K resistance change in contact with the bottom Si3N4 substrate and the top MNPs. We also demonstrate contrary thermal sensitivity responses between SLG and MLG after the addition of MNP to the surface.

to enhance its electrochemical performance. A Schottky junction barrier is formed at the anode to avoid short circuit problems and facilitate the ionic transportation at the anode/electrolyte interface. This study indicates that wide-band gap semiconductors with suitable element-doping can be tuned to be promising ionic conductors for advanced fuel cell applications.

In recent days as rapid changes in markets and technologies are increasingly to shorten the lifetime of products. It is becoming essential for firms to constantly develop the new products into markets. Technology roadmaps, therefore, are considered to be efficient, effective tool of connecting both product and technology planning's collectively, thus being widely accepted by firms. However, those roadmaps and their methodologies hitherto proposed generally tend to have overstated the qualitative, expert-dependent knowledge rather than incorporating objective information. In addition, useful methodologies are often observed to lack, to facilitate a large variety of decision-makings faced in roadmapping processes. Consequently, this paper proposes a new approach: keyword-based technology roadmapping method by using the patents which contains relatively objective information, a quantitative method to support the reliable decision-making processes. Hence, text-mining technique is utilized in this study to extract the relevant information on which the portfolio analysis, co-word analysis and network analysis are carried out, resulting in three different types of product-technology maps. Also, these maps demonstrate the applicability as to where to be applied usefully in a specific step of roadmapping processes. These techniques are highly expected to reflect the objective, quantitative information to roadmapping, and to effectively help improve the overall roadmap quality at the end.

Abstract This study examines the participation and interaction of relevant individuals in the process of developing an accounting standard for South Korea’s emission trading scheme (ETS). Despite the enormous accounting implications of such schemes, there is a paucity of research on the development and application of ETS accounting. Ulrich Beck’s and Anthony Giddens’s risk society framework is utilised to scrutinise the process of setting accounting standards—from the agenda-setting stage all the way to the final publication of the standard. In this case study, we take an interpretive approach in analysing the rich data collected through face-to-face interviews with prominent standard-setters, accounting experts and representatives of industry and government. Participant observation and relevant documents were also considered. The findings highlight the political nature of accounting standard-setting and identify the risks and responsibilities of the key agents in the process along with the means of sub-political action taken to influence decisions. We reveal that the agents involved in standard-setting attempted to balance their anthropocentric priorities with ecocentric responsibilities and prioritised the production of a standard with minimal impact on economic, reputational, and operational risk. Having authority as a standard-setter, referring frequently to precedents and, perhaps most importantly, engaging actively with the stakeholders throughout the process seem to have contributed to a widely accepted standard, which can serve as a benchmark for future attempts to factor in ETSs.

Electrical stimulation such as transcranial direct current stimulation (tDCS) is widely used to treat neuropsychiatric diseases and neurological disorders. Computational modeling is an important approach to understand the mechanisms underlying tDCS and optimize treatment planning. When applying computational modeling to treatment planning, uncertainties exist due to insufficient conductivity information inside the brain. In this feasibility study, we performed in vivo MR-based conductivity tensor imaging (CTI) experiments on the entire brain to precisely estimate the tissue response to the electrical stimulation. A recent CTI method was applied to obtain low-frequency conductivity tensor images. Subject-specific three-dimensional finite element models (FEMs) of the head were implemented by segmenting anatomical MR images and integrating a conductivity tensor distribution. The electric field and current density of brain tissues following electrical stimulation were calculated using a conductivity tensor-based model and compared to results using an isotropic conductivity model from literature values. The current density by the conductivity tensor was different from the isotropic conductivity model, with an average relative difference | rD | of 52 to 73%, respectively, across two normal volunteers. When applied to two tDCS electrode montages of C3-FP2 and F4-F3, the current density showed a focused distribution with high signal intensity which is consistent with the current flowing from the anode to the cathode electrodes through the white matter. The gray matter tended to carry larger amounts of current densities regardless of directional information. We suggest this CTI-based subject-specific model can provide detailed information on tissue responses for personalized tDCS treatment planning.

In this paper, we present actual condition of Korean e- Health from an industrial aspect. We have investigated the status of e-Health industry from 326 companies in Korea. The questionnaire consisted of four categories which are: the potential of e-Health industry, the key domain of e-Health industry, the bottleneck in the government's policies, and the importance of national policy for developing e-Health. As a result of this investigation, we have found out that many businesses have expected that e-Health industry will be a powerful industry in the next generation, and mobile healthcare domain will be expected as a core technology.

Compositional tuning is one of the important approaches to enhance the electronic and thermal transport properties of thermoelectric materials since it can generate point defects as well as control the phase evolution behavior. Herein, we investigated the Ti addition effect on the grain growth during melt spinning and thermoelectric transport properties of Hf0.5Zr0.5NiSn0.98Sb0.02 half-Heusler compound. The characteristic grain size of melt-spun ribbons was reduced by Ti addition, and very low lattice thermal conductivity lower than 0.27 W m−1 K−1 was obtained within the whole measured temperature range (300–800 K) due to the intensified point defect (substituted Ti) and grain boundary (reduced grain size) phonon scattering. Due to this synergetic effect on the thermal transport properties, a maximum thermoelectric figure of merit, zT, of 0.47 was obtained at 800 K in (Hf0.5Zr0.5)0.8Ti0.2NiSn0.98Sb0.02.

All over the world, states are renegotiating international investment agreements at a rapid clip. Largely unnoticed, clauses in investment agreements that authorize or mandate renegotiation under specified conditions have facilitated these efforts. This article is the first to describe and analyze the variation in these renegotiation clauses. We develop a typology of renegotiation clauses in which such clauses vary along two dimensions. They range on a continuum from a full commitment to renegotiate to only a partial commitment. Renegotiation clauses can also call for full scope renegotiation or partial scope renegotiation. The literature on renegotiating international agreements has heretofore overlooked the existence and purposes of provisions requiring partial scope renegotiation. Partial scope renegotiation represents a departure from the ‘single undertaking’ model of negotiations common to international economic law. By altering both the scope of, and commitment to, renegotiation, parties can conclude agreements today while deferring resolution of difficult issues to the future. At the same time, they can also constrain the possibility of opportunism by limiting the subject matter under renegotiation. Most importantly, partial scope renegotiation offers a method to reduce the critical tension underlying the modern international economic order: the pace and degree to which non-Western style economies are required to liberalize their markets.

Large-scale datasets, which have sufficient and identical quantities of data in each class, are the main factor in the success of deep-learning-based classification models for vision tasks. A shortage of sufficient data and interclass imbalanced data distribution, which often arise in the medical domain, cause modern deep neural networks to suffer greatly from imbalanced learning and overfitting. A diagnostic model of diabetic retinopathy (DR) that is trained from such a dataset using supervised learning is severely biased toward the majority class. To enhance the efficiency of imbalanced learning, the proposal of this study is to leverage retinal fundus images without human annotations by self-supervised or semi-supervised learning. The proposed approach to DR detection is to add an auxiliary procedure to the target task that identifies DR using supervised learning. The added process uses unlabeled data to pre-train the model that first learns features from data using self-supervised or semi-supervised learning, and then the pre-trained model is transferred with the learned parameter to the target model. This wrapper algorithm of learning from unlabeled data can help the model gain more information from samples in the minority class, thereby improving imbalanced learning to some extent. Comprehensive experiments demonstrate that the model trained with the proposed method outperformed the one trained with only the supervised learning baseline utilizing the same data, with an accuracy improvement of 4~5%. To further examine the method proposed in this study, a comparison is conducted, and our results show that the proposed method also performs much better than some state-of-the-art methods. In the case of EyePaCS, for example, the proposed method outperforms the customized CNN model by 9%. Through experiments, we further find that the models trained with a smaller but balanced dataset are not worse than those trained with a larger but imbalanced dataset. Therefore, our study reveals that utilizing unlabeled data can avoid the expensive cost of collecting and labeling large-scale medical datasets.

This study examines the factors that influence pro-environmental behaviour intention (PEBI) in manufacturing small- and medium-sized enterprises (SMEs). The data were collected from 517 executives and chief technology officers of Korean SMEs and analysed using a comprehensive research model. The model includes variables such as awareness of consequences (ACs), ascription of responsibility (AR), personal norms (PNs), extrinsic motivation (EM), subjective norms (SNs) and realistic values (RVs). The results show significant relationships between these factors and PEBI. In particular, ACs and AR have positive effects on PNs, with AR having a stronger effect. PNs are the most important predictor of PEBI. EM has a positive impact on behaviour intention, while SNs do not have a significant impact. Interestingly, RVs have a negative impact. These findings have practical implications for encouraging pro-environmental behaviour in manufacturing SMEs. Policymakers and business planners should focus on increasing awareness of environmental consequences and individual responsibility to reinforce PNs. Moreover, offering extrinsic rewards and benefits can motivate pro-environmental behaviour in these firms. Understanding these factors can help design targeted strategies for promoting sustainability practices within manufacturing SMEs. By addressing these aspects, businesses can contribute to environmental innovation and sustainable development.

Abstract The shift in industrial paradigms toward achieving global carbon neutrality and strengthening national material security may initially appear unrelated; however, both domains share a crucial intermediary: critical minerals. Despite global initiatives aimed at securing critical minerals through established supply chains, persistent challenges have arisen owing to resource depletion, geopolitical instability, and intricate international dynamics. Eco‐industrial parks (EIPs) are instrumental in mitigating these challenges by facilitating the recycling of resources embedded within waste and by‐products. This strategy is essential to minimize resource consumption and foster resilient domestic supply chains, particularly in resource‐scarce nations. This study evaluates the recovery potential of nickel, a critical material for green technologies, within a closed‐loop system utilizing an industrial symbiosis development framework with public and open‐source data of industry. This approach enhances supply‐ and demand‐matching schemes within industrial symbiosis networks, specifically focusing on nickel recovery technologies within the Korean EIP project. The findings revealed that these networks within industrial complexes encompassed 86% of the manufacturing industry, thus establishing a cohesive framework for the development of a nickel integration network. Notably, among the 190 companies across 74 industrial complexes, 135 of the 27 designated EIPs participated in the recycling network. This indicates that EIPs could serve as a viable alternative for resource recovery to secure critical minerals. The implementation of such networks in concentrated industrial complexes with diverse manufacturing sectors is expected to significantly enhance critical mineral self‐sufficiency in high‐demand countries.

There is lack of a clear vision of the environmental impacts resulting from using the alternative Liquified Natural Gas (LPG) as a fuel for vehicles instead of the current diesel and gasoline in the city of Baghdad. Conversion to LPG is the installation of a second fuel system, including an LPG tank, a new electronic control unit and different fittings. Such modifications allow the vehicles to run on both fuels. LPG is preferred as it regarded a clean fuel that do not pollute the environment. This confirmed fact was an incentive for energy experts to explore new avenues, which make it an alternative to other hydrocarbons. The five air pollutants (SO2, NO2, NOx PM10 and CO) relationship and the LPG vehicles ratio will be analyzed by panel data analysis. RStudio programming language is used to do this analysis using a package called PLM. Results show that PM10 and CO is slightly significantly decreased with an increase in the LPG vehicles ratio. SO2 and NO2 reveal no statistically significant relationship with LPG vehicles' ratio. Nevertheless, inconsistent outcomes of the remaining pollutants indicate that the efficacy of implementing the LPG vehicles program seems to be different by city.

Abstract This study is the first attempt to fabricate a heat‐resistant hollow fiber ultrafiltration membrane using poly( m ‐phenylene isophthalamide) (PMIA) polymer material, which has rarely been used as conventional polymeric membrane materials. Multi‐walled carbon nanotubes (MWCNTs) are incorporated as reinforcing agents. The PMIA polymer synthesized for this study exhibited an inherent viscosity of 1.6 dL/g, confirming its suitability for membrane fabrication, and successful synthesis was verified through Fourier‐transform infrared analysis. To enhance the dispersibility of MWCNTs during dope solution preparation and their interaction with the PMIA matrix, MWCNTs were acid‐treated and surface characteristics of the acid‐treated MWCNTs were confirmed through x‐ray photoelectron spectroscopy analysis. Scanning electron microscope analysis revealed that the introduction of MWCNTs resulted in thicker PMIA hollow fiber ultrafiltration membranes with symmetrical finger‐like and sponge‐like pore structures. Interestingly, unlike the typical polymer composite systems containing MWCNTs, which often show a dependence on MWCNT content, the mechanical properties of the PMIA/MWCNT membranes in this study seem to exhibit high variability and are not contingent on the MWCNT content. Additionally, filtration performance studies demonstrated that the introduction of MWCNTs substantially increased water permeability, particularly at 1.0 wt% MWCNT content, resulting in a remarkable 130% enhancement compared to pristine PMIA membrane. Simultaneously, even with a small quantity of MWCNTs, the rejection performance of the PMIA/MWCNT membrane witnessed significant improvement due to the reduction in average pore size, effectively overcoming the commonly observed trade‐off phenomenon. In summary, this study clearly showed the effects and changes on the structure and properties of a heat‐resistant PMIA‐based hollow fiber ultrafiltration membranes due to the introduction of MWCNTs. Highlights Heat‐resistant poly( m ‐phenylene isophthalamide)‐based hollow fiber ultrafiltration membranes Introduction of multi‐walled carbon nanotubes (MWCNTs) into PMIA membrane as a reinforcing agent Unique structural changes of PMIA membrane originated from the MWCNTs Enhanced tensile strength of PMIA/MWCNT membranes Simultaneous improvement of filtration performance due to MWCNTs

This article empirically explores whether the Korean research and development (R&D) paradox has been intensified during the post-global financial crisis (2009–2018). We employ the augmented production function model to test the intensified R&D paradox, which is defined as a continuous decline in a firm’s output elasticity of R&D investment. Using a data set of 720 R&D-active firms, which have ever received more than one government funding, this study drew the following major conclusions on the whole sample firms and two sub-sample firms (smart convergence and conventional industries). First, the R&D paradox has been intensified in the post-global financial crisis over the past decade. Second, the smart convergence industry shows higher a firm’s output elasticity of R&D investment than the conventional one does. Third, in recent years, R&D investment failed to even have significant effect on the value-added. Last, a firm’s output elasticity of R&D investment was found to be much more vulnerable in large and semi-large firms than in SMEs in Korea. In sum, this study confirms the intensified Korean R&D paradox during the post-global financial crisis in Korea. We discuss the government’s role in resolving the R&D paradox in Korea.

Ionizing radiation delivers sufficient energy inside the human body to create ions, which kills cancerous tissues either by damaging the DNA directly or by creating charged particles that can damage the DNA. Recent magnetic resonance (MR)-based conductivity imaging shows higher sensitivity than other MR techniques for evaluating the responses of normal tissues immediately after irradiation. However, it is still necessary to verify the responses of cancer tissues to irradiation by conductivity imaging for it to become a reliable tool in evaluating therapeutic effects in clinical practice. In this study, we applied MR-based conductivity imaging to mouse brain tumors to evaluate the responses in irradiated and non-irradiated tissues during the peri-irradiation period. Absolute conductivities of brain tissues were measured to quantify the irradiation effects, and the percentage changes were determined to estimate the degree of response. The conductivity of brain tissues with irradiation was higher than that without irradiation for all tissue types. The percentage changes of tumor tissues with irradiation were clearly different than those without irradiation. The measured conductivity and percentage changes between tumor rims and cores to irradiation were clearly distinguished. The contrast of the conductivity images following irradiation may reflect the response to the changes in cellularity and the amounts of electrolytes in tumor tissues.

BACKGROUND/AIM: Breast cancer is a heterogenous disease characterized by complex molecular pathways that drive its progression. Despite advances in treatment strategies, the need for novel therapeutic targets remains critical. Replication factor C subunit 4 (RFC4) is an important component of the DNA replication machinery and repair pathways. Its precise regulation ensures genomic stability and its dysregulation is implicated in various cancers. However, its oncogenic role in breast cancer is unclear. Therefore, this study aimed to elucidate the biological role of RFC4 in breast cancer. MATERIALS AND METHODS: Breast cancer cell lines MCF7, BT-549, and MDA-MB-231 were transfected with control and RFC4 siRNA to investigate biological functions of RFC4 in breast cancer. Cell proliferation was measured using the MTT and colony formation assays. In addition, cell cycle analysis, migration, and invasion assays were performed on RFC4-depleted breast cancer cells. RESULTS: siRNA-mediated RFC4 knockdown inhibited breast cancer cell proliferation and cell cycle arrest, and reduced cell migration and invasion ability. CONCLUSION: Our findings highlight the critical role of RFC4 in breast cancer progression. The observed decrease in cell proliferation and clonogenic potential following RFC4 knockdown suggests its potential as a therapeutic target for breast cancer.

A funding agency, as a crucial agent in the government-sponsored R&D system, makes funding choices to enhance the output or outcome of the R&D projects in which it invests. This paper examines the impact a Korean funding agency can have to drive the output of R&D projects. Using a data set of 147 government-sponsored large-scale R&D projects, this study tests how choice variables of a funding agency or R&D consortium affect technological output. This study finds that a funding agency's choice variables - the amount of funding, duration, and the intensity of monitoring - are quite influential on the success score and the number of publications of R&D projects, but do not significantly impact the number of patent applications. The results suggest that the funding agency, as an innovation facilitator, needs to expand its entrepreneurial activities, including consulting toward commercialisation, besides its traditional tasks related to project evaluation and management.