• STI Policy Review
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• v.3 no.2
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• pp.130-151
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• 2012

Fraunhofer was founded in 1949 and grew into Europe's largest application-oriented research organization. Fraunhofer currently employs over 20,000 members in Germany, is internationally networked, and manages an R&D budget of over 1,8 Billion Euros per year. An important step for Fraunhofer to become an integral component of the German innovation system was the introduction of the Fraunhofer Model of financing based on a performance-related system of financial management. The underlying model of the allocation and distribution of public funding to Fraunhofer that is subsequently allotted to specific research groups is one of the success factors of Fraunhofer. Fraunhofer is proud of its decentralized organizational model. Fraunhofer is comprised of 60 Institutes in Germany working in different fields, under one legal framework, and with a strong brand value. Every Fraunhofer Institute is affiliated with a German University and every institute director simultaneously holds a chair at the affiliated university. It is a challenge for the headquarter organization to balance the intended competition of individual Fraunhofer Institutes with complementarity cooperation in science among Fraunhofer-Institutes, especially when coming from different knowledge domains; however, this goal results in a significant advantage. The unique strengths of Fraunhofer offer system solutions in a world with increasingly complex R&D challenges. While growing to become the largest organization on Europe to focus on applied research it is the challenge to remain an agile organization that is flexible in organizational structure. Fraunhofer has reached a well-recognized position in the European innovation landscape. It is often referred to by science and governments as a role model for innovation policy and a key element of the latest successes in the German economy that has recovered quicker from the latest economic crisis than most other western economies. The paper explains Fraunhofer as an organizational paradigm and its underlying management model to elaborate on the challenges of managing a research organization. We wish to show how it is possible to transfer the management model and philosophy of Fraunhofer to innovation systems with different framework conditions and challenges. A universal conclusion may be drawn based on the description of Fraunhofer; however, changes in existing structures and innovation systems cannot be implemented over night.

• The Journal of Internal Korean Medicine
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• v.43 no.6
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• pp.1089-1104
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• 2022

Objective: The aim of this study was to identify the efficacy and underlying mechanism of cloves as an osteoarthritis (OA) treatment in a monosodium iodoacetate (MIA)-induced rat OA model. Osteoarthritis (OA) is nowadays one of the most prevalent degenerative joint diseases. Methods: Sprague-Dawley rats treated with MIA (50 μL; 80 mg/mL) were used as in vivo OA models. Cloves (100 and 200 mg/kg b.w.) were administered orally once daily for 2 weeks from 7 days after MIA injection. Changes in hindpaw weight distribution (HWD) were measured as a joint discomfort index. Activation markers related to inflammatory responses and cartilage degeneration in the right knee joints were evaluated by serum analysis and western blotting. Results: HWD decreased in the MIA control group but showed a dose-dependent elevation after clove treatment. Clove treatment inhibited inflammatory factors by PI3K/Akt/NF-κB signaling pathways, while also activating antioxidant factors through Sirt1/AMPK signaling pathways. Clove treatment also suppressed matrix metalloproteinase (MMP) overexpression and significantly increased the levels of tissue inhibitors of metalloproteinases (TIMPs). Conclusions: Treatment with cloves effectively reversed MIA-induced effects. Therefore, clove treatment could have the potential to protect against or treat OA.

• Korean Circulation Journal
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• v.54 no.8
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• pp.468-481
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• 2024

Background and Objectives: Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue-based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Methods: Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography-mass spectrometry. Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. Results: The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Conclusions: Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

• Journal of the Korea Concrete Institute
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• v.19 no.4
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• pp.449-456
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• 2007

This research was conducted to analyze the features of the critical tensile stresses at the top and bottom of the concrete slab in the jointed concrete pavement (JCP) when subjected to both the environmental and vehicle loads. First, the stress distribution in JCP was analyzed when the system was subjected to only the environmental loads or the vehicle loads by using the finite element model of JCP. Then, the stresses were analyzed when the system was subjected to the environmental and vehicle loads at the same time. From this study, it was found that the critical tensile stresses at the slab bottom under the vehicle loads were almost constant regardless of the loading positions once the loads were applied at the positions having some distance from the transverse joint. The critical tensile stresses at the slab bottom could be obtained using the model consisting of normal springs for underlying layers by adding the critical stresses due to the environmental loads and the vehicle loads for the curled-down slab, and by subtracting the critical stress due to the environmental loads from that due to the vehicle loads for the curled-up slab. The critical tensile stresses at the top of the slab could be obtained using the model consisting of tensionless springs for underlying layers by adding the critical stress due to the environmental loads and the stress at the middle of the slab under the vehicle loads applied at the joint for the curled-up slab. An alternative to obtain the critical stresses at the top of the slab for the curled-up slab was to use the critical stresses under only the environmental loads obtained from the model having normal springs for underlying layers.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.6135-6140
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• 2013

Background: Breast cancer is a common malignant tumor which affects health of women and multidrug resistance (MDR) is one of the main factors leading to failure of chemotherapy. This study was conducted to establish paclitaxel-resistant breast cancer cell line and nude mice models to explore underlying mechanisms of MDR. Methods: The breast cancer drug-sensitive cell line MCF-7 (MCF-7/S) was exposed in stepwise escalating paclitaxel (TAX) to induce a resistant cell line MCF-7/TAX. Cell sensitivity to drugs and growth curves were measured by MTT assay. Changes of cell morphology and ultrastructure were examined by optical and electron microscopy. The cell cycle distribution was determined by flow cytometry. Furthermore, expression of proteins related to breast cancer occurrence and MDR was tested by immunocytochemistry. In Vivo, nude mice were injected with MCF-7/S and MCF-7/TAX cells and weights and tumor sizes were observed after paclitaxel treatment. In addition, proteins involved breast cancer and MDR were detected by immunohistochemistry. Results: Compared to MCF-7/S, MCF-7/TAX cells had a higher resistance to paclitaxel, cross-resistance and prolonged doubling time. Moreover, MCF-7/TAX showed obvious alterations of ultrastructure. Estrogen receptor (ER) expression was low in drug resistant cells and tumors while expression of human epidermal growth factor receptor 2 (HER2) and Ki-67 was up-regulated. P-glycoprotein (P-gp), lung resistance-related protein (LRP) and glutathione-S-transferase-${\pi}$ (GST-${\pi}$) involved in the MDR phenotype of resistant cells and tumors were all overexpressed. Conclusion: The underlying MDR mechanism of breast cancer may involve increased expression of P-gp, LRP and GST-${\pi}$.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.403-407
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• 2006

This research aims to reduce severe damages to human beings and properties from floods that ravage Korea every year, by estimating right time to hydraulic structures based on the characteristics of variations in flood flows. To establish this permanent means for the flood mitigation, this research analyse design floods of various dams and hydraulic structures in connection with time of occurrence of the weather abnormalities in Korea. This research was derived the optimal regionalization of the precipitation data which can be classified by the climatologically and geographically homogeneous regions in Korea. Using the L-moment ratios and Kolmogorov-Smimov test, the underlying regional probability distribution was identified to be the GEV distribution among applied distributions. The regional and at-site analyses using L-moment for the design rainfall were tested by Monte Carlo simulation. Error tests were computed and compared with those resulting from at-site Monte Carlo simulation. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.659-668
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• 2006

The uncertainty of the risk of failure of hydraulic structures can be determined by estimating the variance of the risk of failure based on the methods of moments, probability weighted moments, and maximum likelihood assuming that the underlying model is the Gumbel distribution. In this paper, the variance of the risk of failure was derived. Monte Carlo simulation was peformed to verify the characteristics of the derived formulas for various sample size, design life, nonexceedance probability, and variation coefficient. As the results, PWM showed the smallest relative bias and root mean square error than the others while ML showed the smallest ones for relatively large sample siBes regardless of design life and nonexceedance probability. Also, it was found that variation coefficient does not effect on the relative bias and relative root mean square error.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.821-831
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• 2014

Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

• Journal of Distribution Science
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• v.22 no.4
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• pp.11-22
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• 2024

Purpose: This research delves into the various factors that influence the performance of restaurant businesses on social commerce platforms in Bangkok, Thailand. The study considers both internal and external factors, including but not limited to business characteristics and location. Moreover, this research also analyzes the effects of employing multiple social commerce platforms on business efficiency and explores the underlying reasons for such effects. Research design, data, and methodology: Restaurants can be classified into different price ranges: low, medium, and high. To further investigate, we employed natural language processing AI to analyze online reviews and evaluate algorithm performance using machine learning techniques. We aimed to develop a model to gauge customer satisfaction with restaurants across different price categories effectively. Results: According to the research findings, several factors significantly impact restaurant groups in the low and mid-price ranges. Among these factors are population density and the number of seats at the restaurant. On the other hand, in the mid-and high-price ranges, the price levels of the food and drinks offered by the restaurant play a crucial role in determining customer satisfaction. Furthermore, the correlation between different social commerce platforms can significantly affect the business performance of high-price range restaurant groups. Finally, the level of online review sentiment has been found to influence customer decision-making across all restaurant types significantly. Conclusions: The study emphasizes that restaurants' characteristics based on their price level differ significantly, and social commerce platforms have the potential to affect one another. It is worth noting that the sentiment expressed in online reviews has a more significant impact on customer decision-making than any other factor, regardless of the type of restaurant in question.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.277-284
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• 2011

The limitations of existing Markov chain model for reproducing extreme rainfalls are a known problem, and the problems have increased the uncertainties in establishing water resources plans. Especially, it is very difficult to secure reliability of water resources structures because the design rainfall through the existing Markov chain model are significantly underestimated. In this regard, aims of this study were to develop a new daily rainfall simulation model which is able to reproduce both mean and high order moments such as variance and skewness using a piecewise Kernel-Pareto distribution. The proposed methods were applied to summer and fall season rainfall at three stations in Han river watershed in Korea. The proposed Kernel-Pareto distribution based Markov chain model has been shown to perform well at reproducing most of statistics such as mean, standard deviation and skewness while the existing Gamma distribution based Markov chain model generally fails to reproduce high order moments. It was also confirmed that the proposed model can more effectively reproduce low order moments such as mean and median as well as underlying distribution of daily rainfall series by modeling extreme rainfall separately.