Publications by authors named "H Mike Kim"

Objectives: The successes of local therapy for oligometastatic cancers cannot be extrapolated to oligoprogressive disease (OPD) because they are distinct clinical entities. Given the limited prospective data on OPD to date, summative analyses are urgently needed.

Methods: Inclusion criteria for this PRISMA-guided systematic review were as follows. First, only prospective data were included. Second, progression had to have occurred on active/ongoing systemic therapy. Third, the number of progressing areas of disease had to be explicitly listed and ≤5 in number. Fourth, all progressing sites had to undergo local therapy (radiotherapy/surgery/non-radiation ablative procedures).

Results: Eight trials met criteria (summing 290 patients), the vast majority of which utilized stereotactic radiotherapy as the local modality (most commonly, 19-20 Gy in 1 fraction, 27-33 Gy in 3 fractions, or 35-50 Gy in 5 fractions). A study on NSCLC demonstrated that stereotactic radiotherapy improved progression-free survival (PFS) and overall survival compared to historical values with systemic therapy alone. Two additional studies on EGFR-mutated NSCLC also showed acceptable PFS with local therapy, particularly in patients who oligoprogressed on osimertinib. The only randomized trial analyzed herein showed that local therapy improved PFS for NSCLC but not breast cancer. Two trials in castration-resistant prostate cancer illustrated that a substantial proportion of patients did not require any changes in hormonal therapy and/or delayed the need to change systemic therapies. Lastly, two trials of renal cell carcinoma showed high (90-100%) local control and median PFS of 9 months, and potentially a prolonged time to change systemic therapy. Lastly, from all patients in all trials, local therapy was tolerated well, with only 7 instances of grade 3+ toxicities.

Conclusions: Based on the limited data, local therapy for OPD is safe and yields encouraging short-term preliminary outcomes, but trials with larger sample sizes and longer follow-up are required for more robust conclusions.

Multiwalled carbon nanotube (MWCNT) have a great potential for advanced oxidation process as a metal free catalyst. However, there catalytic activity is very low and needs to be appropriately tuned. Herein, we demonstrate a novel synthesis method for tuning the defect and surface functionality of MWCNT using azo dyes and the catalytic performance was tested for the degradation of different organic contaminates using PMS as an oxidant. The content, type of heteroatom functional groups, and the defect parameters were optimized by varying the pH and concentration of the organic dye. The quenching effect showed that singlet oxygen (O) is the primary reactive species generated by graphitic nitrogen, which can be boosted by the degree of graphitic structure disruption in MWCNT. The Linear sweep voltammetry (LSV) also confirmed that extrinsic doping enhanced the non-radical degradation by increasing the direct charge transfer rate from MB to PMS. Moreover, the designed catalyst showed a fast degradation performance with 35.1 KJ/mol activation energy and achieved the highest dye degradation rate and even surpassed some state-of-the-art metal-based and metal-free catalysts. The effect of inorganic anions study has also confirmed its industrial applicability.

eXplainable Artificial Intelligence (XAI) is a new trend of machine learning. Machine learning models are used to predict or decide something, and they derive output based on a large volume of data set. Here, the problem is that it is hard to know why such prediction was derived, especially when using deep learning models. It makes the models unreliable in the case of reliability-critical applications. So, it is required to explain how they derived such output. It is a reliability-critical application for self-driving cars because the mistakes made by the computers inside them can lead to critical accidents. So, it is necessary to adopt XAI models in this field. In this paper, we propose an XAI method based on computing and explaining the difference of the output values of the neurons in the last hidden layer of convolutional neural networks. First, we input the original image and some modified images of it. Then we derive output values for each image and compare these values. Then, we introduce the Sensitivity Analysis technique to explain which parts of the original image are needed to distinguish the category. In detail, we divide the image into several parts and fill these parts with shades. First, we compute the influence value on the vector indicating the last hidden layer of the model for each of these parts. Then we draw shades whose darkness is in proportion to the influence values. The experimental results show that our approach for XAI in self-driving cars finds the parts needed to distinguish the category of these images accurately.

In this study, we compare various solvents with different Gutmann donor numbers as additives to improve the quality of perovskite films via an antisolvent-free process, using 2-methoxyethanol (2MOE) as the solvent. In 2MOE-based solutions, we found that the higher the donor number of the solvent, the lower the amount of the solvent required to form insoluble adducts. Furthermore, we found that -methyl-2-pyrrolidone (NMP), which has a relatively low donor number and vapor pressure, can be added without a limitation to precipitation, while the degree of the intermediate phase in the as-deposited film is controlled by the amount of NMP added. We obtained pinhole-free and planar perovskite films by optimizing the amount of NMP added and fabricated devices based on NMP-assisted MAPbI and MAPbICl films, with efficiencies of 18.80 and 20.39%, respectively.

Fluorination of a conjugated polymer backbone is an effective strategy to control the microstructure and electronic structure of a conjugated polymer. Although fluorination has been widely reported to increase charge carrier mobility, its effect on the operational stability of electronic devices has not been extensively investigated. Here, the effect of fluorination of a conjugated polymer backbone on charge trapping and the operational stability of organic field-effect transistors is investigated. The results show that the device based on a fluorinated conjugated polymer exhibits relatively poor operational stability despite its greater charge carrier mobility compared with that in the device based on its nonfluorinated polymer counterpart. Experimental results reveal that the low stability originates from the greater degree of shallow trapping of charge carriers within the fluorinated polymer thin film and that the shallow trapping is closely related to the presence of minority charge carriers. A mechanism of charge trapping is proposed.