Kwang Su Kim

The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed tha

The scientific community is focussed on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data collected from the same specimen (throat / nasal swabs or nasopharyngeal / sputum / tracheal aspirate), we compare within-host dynamics for patients infected in the current

Two milliliters of contrast solution can provide optimal dispersion of contrast in a ventral and longitudinal spread.

Graphene-based electrochemical impedance sensors have recently received much attention due to their outstanding sensing capability and economic viability. In this study, we present a novel means of constructing an impedance sensing platform via harnessing intrinsic π-stacking interactions between probe protein molecules and reduced graphene oxide (RGO) substrate, obviating the need for introducing external chemical groups often required for covalent anchoring of the probes. To achieve this goal,

The duration of viral shedding is determined by a balance between de novo infection and removal of infected cells. That is, if infection is completely blocked with antiviral drugs (100% inhibition), the duration of viral shedding is minimal and is determined by the length of virus production. However, some mathematical models predict that if infected individuals are treated with antiviral drugs with efficacy below 100%, viral shedding may last longer than without treatment because further de nov

In this study, a channel and feature selection methodology is devised for brain‐computer interface (BCI) applications using functional near‐infrared spectroscopy (fNIRS). A graph convolutional network (GCN) is employed to select the appropriate and correlated fNIRS channels. Furthermore, in the feature extraction phase, the performance of two filter‐based feature selection algorithms, (i) the minimum redundancy maximum relevance (mRMR) and (ii) ReliefF, is investigated. The five most commonly us

Cancer virotherapy is studied in mathematical modeling to improve tumor elimination. Since various oncolytic viruses are used for cancer therapy and virus selection is an important research problem, we, therefore, constructed deterministic and stochastic models of cancer-virus dynamics. We investigated virus characteristic parameter sensitivities using a reproduction ratio. Locally and globally asymptotically stable equilibrium points that are respectively related to therapy failure/partial succ

We propose a mathematical model describing tumor-immune interactions under immune suppression. These days evidences indicate that the immune suppression related to cancer contributes to its progression. The mathematical model for tumor-immune interactions would provide a new methodology for more sophisticated treatment options of cancer. To do this we have developed a system of 11 ordinary differential equations including the movement, interaction, and activation of NK cells, CD8(+)T-cells, CD4(

Gecko-like dry adhesive using high aspect ratio polymeric nanohairs has insuperable limitations, although it has huge potential in many applications. Repeated harsh contacts on a target substrate lead to physical collapse of nanohairs and significant degradation of the adhesion property, because the polymeric nanohairs are quite fragile due to poor mechanical robustness. Herein, we demonstrate a highly robust gecko-like dry adhesive with unidirectionally stooped polymeric nanohairs (diameter 100

Brain tumors are among the deadliest diseases in the modern world. This study proposes an optimized machine-learning approach for the detection and identification of the type of brain tumor (glioma, meningioma, or pituitary tumor) in brain images recorded using magnetic resonance imaging (MRI). The Gaussian features of the image are extracted using speed-up robust features (SURF), whereas its non-linear features are obtained using KAZE, owing to their high performance against rotation, scaling,

Nanofabrication is an indispensable process in nanoscience and nanotechnology. Unconventional lithographic techniques are often used for fabrication as alternatives to photolithography because they are faster, more cost‐effective, and simpler to use. However, these techniques are limited in scalability and utility because of the collapse of preprinted structures during step‐and‐repeat processes. This study proposes a new class of temperature‐controllable polymeric molds that are coated with a me

Controlling the number of tumor cells leads us to expect more efficient strategies for treatment of tumor. Towards this goal, a tumor‐immune model with state‐dependent impulsive treatments is established. This model may give an efficient treatment schedule to control tumor’s abnormal growth. By using the Poincaré map and analogue of Poincaré criterion, some conditions for the existence and stability of a positive order‐1 periodic solution of this model are obtained. Moreover, we carry out numeri