Prediction of SMEs' R&D performances by machine learning for project selection.

To improve the efficiency of government-funded research and development (R&D) programs for small and medium enterprises, it is necessary to make the process of selecting beneficiary firm objective. We aimed to develop machine learning models to predict the performances of individual R&D projects in advance, and to present an objective method that can be utilized in the project selection. We trained our models on data from 1771 R&D projects conducted in South Korea between 2011 and 2015.

Artificial intelligence-based decision support model for new drug development planning.

New drug development guarantees a very high return on success, but the success rate is extremely low. Pharmaceutical companies have attempted to use various strategies to increase the success rate of drug development, but this goal has been difficult to achieve. In this study, we developed a model that can guide effective decision-making at the planning stage of new drug development by leveraging machine learning.

Young people are not blameworthy: the generation's awareness of COVID-19 and behavioral responses.

At a time when the COVID-19 pandemic has been ongoing for more than a year, young people have been the subject of vigilant scrutiny and criticism regarding their active engagement in social activities. We posed the question of whether young people's response to COVID-19 was different from that of other generations and analyzed awareness and behavior to investigate this question. Specifically, we examined internet searches for information on COVID-19 and credit card consumption in South Korea among young people in their 20s and compared them to a reference group of people in their 50s.

The impact of the pandemic declaration on public awareness and behavior: Focusing on COVID-19 google searches.

The unprecedented outbreaks of epidemics such as the coronavirus has caused major socio-economic changes. To analyze public risk awareness and behavior in response to the outbreak of epidemic diseases, this study focuses on RSV (Relative Search Volume) provided by Google Trends. This study uses the social big data provided by Google RSV to investigate how the WHO's pandemic declaration affected public awareness and behavior.

Disease burden metrics and the innovations of leading pharmaceutical companies: a global and regional comparative study.

Background: The recent innovation activities of global top-tier pharmaceutical companies in accordance with global and regional health concerns were investigated in order to identify their innovations contributing to population health.

Methods: "Innovation activity" was defined as the number of drugs for which R&D activities have been reported within the last three years. Such activities were measured by collecting the data on drug developments and classifying them by developer company, phase of development, therapeutic use, and the country in which the development conducted.

The relationship between government research funding and the cancer burden in South Korea: implications for prioritising health research.

Background: In this study, we aimed to assess health research funding allocation in South Korea by analysing the relationship between government funding and disease burden in South Korea, specifically focusing on cancers.

Methods: The relationship between research funding and the cancer burden, measured in disability-adjusted life-years (DALYs), was analysed using a linear regression method over a 10-year interval. Funding information on 25 types of cancer was obtained from the National Science and Technology Information Service portal in South Korea.

Analysis of trends and prospects regarding stents for human blood vessels.

Background: The purpose of this paper is to provide technology trends and information regarding market and prospects in stents used for human blood vessels in Korea and the world.A stent is a medical device in the form of a cylindrical metal net used to normalize flow when blood or other bodily fluids such as biliary fluids are obstructed in blood vessels, gastrointestinal tracts, etc. by inserting the stent into a narrowed or clogged area.

Luminescence properties and energy transfer of site-sensitive Ca(6-x-y)Mg(x-z)(PO(4))(4):Eu(y)(2+),Mn(z)(2+) phosphors and their application to near-UV LED-based white LEDs.

On the basis of the structural information that the host material has excellent charge stabilization, blue-emitting Ca(6-x-y)Mg(x)(PO(4))(4):Eu(y)(2+) (CMP:Eu(2+)) phosphors were synthesized and systematically optimized, and their photoluminescence (PL) properties were evaluated. Depending upon the amount of Mg added, the emission efficiency of the phosphors could be enhanced. The substitution of Eu(2+) affected their maximum wavelength (lambda(max)) and thermal stability because the substitution site of Eu(2+) could be varied.

Self-assembled SiO2 photonic crystal infiltrated by Ormosil:Eu(DBM)(3)phen phosphor and its enhanced photoluminescence.

Luminescence films were prepared by infiltration of the tris(dibenzoylmethane) mono(1, 10-phenanthroline) europium incorporated ormosil into colloidal SiO(2) photonic crystal templates. Because a stopband of the template was not overlapped with the PL excitation and emission bands, the stopband did not suppress the PL intensity. The PL intensity of the infiltrated film into the template was about 13.

Luminescent and structural properties of (Sr(1-x),Ba(x))3MgSi2O8:Eu2+: effects of Ba content on the Eu2+ site preference for thermal stability.

A blue-color-emitting phosphor, (Sr(1-x),Ba(x))(3)MgSi(2)O(8):Eu(2+) (SB(x)MS:Eu(2+)), with various Ba contents, was synthesized, and its thermal stability was evaluated. Depending upon the Ba content, the dominant emission wavelength of the SB(x)MS:Eu(2+) phosphor could be tuned, and good photoluminescence (PL) properties were obtained under an excitation by a 147 nm source. The PL behavior showed that the thermal stability of SB(x)MS:Eu(2+) baked at 500 degrees C was dependent upon the Ba content.