Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling

To capture the relationship between samples and labels, conditional generative models often inherit spurious correlations from the training dataset. This can result in label-conditional distributions that are imbalanced with respect to another latent attribute. To mitigate this issue, which we call spurious causality of conditional generation, we propose a general two-step strategy. (a) Fairness Intervention (FI): emphasize the minority samples that are hard to generate due to the spurious correlation in the training dataset. (b) Corrective Sampling (CS): explicitly filter the generated samples and ensure that they follow the desired latent attribute distribution. We have designed the fairness intervention to work for various degrees of supervision on the spurious attribute, including unsupervised, weakly-supervised, and semi-supervised scenarios. Our experimental results demonstrate that FICS can effectively resolve spurious causality of conditional generation across various datasets.Comment: TMLR 202

Characterization of Alginate/Silver Nanobiocomposites Synthesized by Solution Plasma Process and Their Antimicrobial Properties

Solution plasma process (SPP) was adopted to prepare alginate/silver nanoparticle (AL/AgNP) biocomposites. The biocomposites were synthesized in solutions of varying concentrations of AgNO3 (1−5 mM) and alginate (0.1−0.3%, w/w) by discharging plasma for 7 min at 800 V with 30 kHz frequency using a pulsed unipolar power supply. The AL/AgNP emulsion was fabricated into 3D scaffolds by freeze drying and lyophilization and then stabilized by cross-linking via UV irradiation. UV-Vis spectroscopy of the biocomposites showed a characteristic absorbance at the maximum of 415–440 nm with increase in the intensity of the peaks as the concentration of AgNO3 increased. FE-SEM analysis showed that the 3D scaffolds had microporous structures with fine and uniform pores of 3–9 ± 2.0 μm in diameter. TEM analysis revealed that AgNPs in the biocomposites were in spherical shape with size range of 5–40±2.0 nm (AL0.3/Ag5) and well distributed in the matrix. The AL/AgNP biocomposites showed microbicidal activity against 9 human pathogens with MIC of 9.6–21 μg/mL for bacteria and 85–425 μg/mL for fungi. Almost all of the E. coli cells (99.8%) were killed by the treatment with 42.5 μg/mL of AgNPs at room temperature for 1 h

Virmid: accurate detection of somatic mutations with sample impurity inference

Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing data from breast cancer and hemimegalencephaly demonstrate the power of our model. A software implementation of our method is available at http://sourceforge.net/projects/virmid/

A Pan-Dengue Virus Reverse Transcription-Insulated Isothermal PCR Assay Intended for Point-of-Need Diagnosis of Dengue Virus Infection by Use of the POCKIT Nucleic Acid Analyzer

Dengue virus (DENV) infection is considered a major public health problem in developing tropical countries where the virus is endemic and continues to cause major disease outbreaks every year. Here, we describe the development of a novel, inexpensive, and user-friendly diagnostic assay based on a reverse transcription-insulated isothermal PCR (RT-iiPCR) method for the detection of all four serotypes of DENV in clinical samples. The diagnostic performance of the newly established pan-DENV RT-iiPCR assay targeting a conserved 3′ untranslated region of the viral genome was evaluated. The limit of detection with a 95% confidence was estimated to be 10 copies of in vitro-transcribed (IVT) RNA. Sensitivity analysis using RNA prepared from 10-fold serial dilutions of tissue culture fluid containing DENVs suggested that the RT-iiPCR assay was comparable to the multiplex real-time quantitative RT-PCR (qRT-PCR) assay for DENV-1, -3, and -4 detection but 10-fold less sensitive for DENV-2 detection. Subsequently, plasma collected from patients suspected of dengue virus infection (n = 220) and individuals not suspected of dengue virus infection (n = 45) were tested by the RT-iiPCR and compared to original test results using a DENV NS1 antigen rapid test and the qRT-PCR. The diagnostic agreement of the pan-DENV RT-iiPCR, NS1 antigen rapid test, and qRT-PCR tests was 93.9%, 84.5%, and 97.4%, respectively, compared to the composite reference results. This new RT-iiPCR assay along with the portable POCKIT nucleic acid analyzer could provide a highly reliable, sensitive, and specific point-of-need diagnostic assay for the diagnosis of DENV in clinics and hospitals in developing countries

Effect of TiN Spray Coating on Cracking Susceptibility and Energy Absorption in Laser Welding of Aluminum Alloys

This paper reports on the effect of a TiN spray coating on aluminum to improve laser welding issues such as cracking susceptibility and laser absorption. A self-restraint hot cracking test and bead on plate test were employed to compare the laser weldability between the base material and TiN-coated material. The welds with the TiN coating can be fully penetrated without cracks at lower power than the welds without the coating. TiN-incorporated metal matrix composites were formed on the top layer irradiated with the laser. The layer increases the laser absorption to transfer energy efficiently and strengthens it to withstand higher stresses and strains. In addition, the welding mechanism of this process is such that the ceramic coating layer blocks direct interaction between the laser and the metal melting pool, so that a keyhole is not formed, and welding is performed by heat conduction through the TiN ceramic medium

Exploring molecular links between lymph node invasion and cancer prognosis in human breast cancer

BACKGROUND: Lymph node invasion is one of the most powerful clinical factors in cancer prognosis. However, molecular level signatures of their correlation are remaining poorly understood. Here, we propose a new approach, monotonically expressed gene analysis (MEGA), to correlate transcriptional patterns of lymph node invasion related genes with clinical outcome of breast cancer patients. RESULTS: Using MEGA, we scored all genes with their transcriptional patterns over progression levels of lymph node invasion from 278 non-metastatic breast cancer samples. Applied on 65 independent test data, our gene sets of top 20 scores (positive and negative correlations) showed significant associations with prognostic measures such as cancer metastasis, relapse and survival. Our method showed better accuracy than conventional two class comparison methods. We could also find that expression patterns of some genes are strongly associated with stage transition of pathological T and N at specific time. Additionally, some pathways including T-cell immune response and wound healing serum response are expected to be related with cancer progression from pathway enrichment and common motif binding site analyses of the inferred gene sets. CONCLUSIONS: By applying MEGA, we can find possible molecular links between lymph node invasion and cancer prognosis in human breast cancer, supported by evidences of feasible gene expression patterns and significant results of meta-analysis tests

Exploring molecular links between lymph node invasion and cancer prognosis in human breast cancer

Abstract Background Lymph node invasion is one of the most powerful clinical factors in cancer prognosis. However, molecular level signatures of their correlation are remaining poorly understood. Here, we propose a new approach, monotonically expressed gene analysis (MEGA), to correlate transcriptional patterns of lymph node invasion related genes with clinical outcome of breast cancer patients. Results Using MEGA, we scored all genes with their transcriptional patterns over progression levels of lymph node invasion from 278 non-metastatic breast cancer samples. Applied on 65 independent test data, our gene sets of top 20 scores (positive and negative correlations) showed significant associations with prognostic measures such as cancer metastasis, relapse and survival. Our method showed better accuracy than conventional two class comparison methods. We could also find that expression patterns of some genes are strongly associated with stage transition of pathological T and N at specific time. Additionally, some pathways including T-cell immune response and wound healing serum response are expected to be related with cancer progression from pathway enrichment and common motif binding site analyses of the inferred gene sets. Conclusions By applying MEGA, we can find possible molecular links between lymph node invasion and cancer prognosis in human breast cancer, supported by evidences of feasible gene expression patterns and significant results of meta-analysis tests

A public R&D resource allocation model for 5G mobile industry in Korea

5G needs to be viewed as a request for network upgrade driven by demands for innovative services, not only by demands for enhanced mobile networks per se. The R&D plan of the Korean government has been discordant with the vision of 5G, maintaining the tradition of sector- or issue-based R&D project support. This study proposed a strategic decision model for the 5G mobile industry, focusing on public R&D resource allocation, in response to the call for a revision of the ICT policy framework in Korea. The proposed model employed a criteriabased, quantitative, and comprehensive approach, using the AHP method, and an expert survey was conducted. The results showed that service platform is the critical layer that deserves priority in strategic public R&D resource input. Also, the ICT experts in Korea formed a consensus that upgrading physical networks per se is not the main driver of the next generation mobile industry, which verified the validity of the model