Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise

Recently, quantum classifiers have been known to be vulnerable to adversarial attacks, where quantum classifiers are fooled by imperceptible noises to have misclassification. In this paper, we propose one first theoretical study that utilizing the added quantum random rotation noise can improve the robustness of quantum classifiers against adversarial attacks. We connect the definition of differential privacy and demonstrate the quantum classifier trained with the natural presence of additive noise is differentially private. Lastly, we derive a certified robustness bound to enable quantum classifiers to defend against adversarial examples supported by experimental results.Comment: Submitted to IEEE ICASSP 202

Multiple model species selection for transcriptomics analysis of non-model organisms

Abstract Background Transcriptomic sequencing (RNA-seq) related applications allow for rapid explorations due to their high-throughput and relatively fast experimental capabilities, providing unprecedented progress in gene functional annotation, gene regulation analysis, and environmental factor verification. However, with increasing amounts of sequenced reads and reference model species, the selection of appropriate reference species for gene annotation has become a new challenge. Methods We proposed a novel approach for finding the most effective reference model species through taxonomic associations and ultra-conserved orthologous (UCO) gene comparisons among species. An online system for multiple species selection (MSS) for RNA-seq differential expression analysis was developed, and comprehensive genomic annotations from 291 reference model eukaryotic species were retrieved from the RefSeq, KEGG, and UniProt databases. Results Using the proposed MSS pipeline, gene ontology and biological pathway enrichment analysis can be efficiently achieved, especially in the case of transcriptomic analysis of non-model organisms. The results showed that the proposed method solved problems related to limitations in annotation information and provided a roughly twenty-fold reduction in computational time, resulting in more accurate results than those of traditional approaches of using a single model reference species or the large non-redundant reference database. Conclusions Selection of appropriate reference model species helps to reduce missing annotation information, allowing for more comprehensive results than those obtained with a single model reference species. In addition, adequate model species selection reduces the computational time significantly while retaining the same order of accuracy. The proposed system indeed provides superior performance by selecting appropriate multiple species for transcriptomic analysis compared to traditional approaches

Comparative Transcriptome Analysis of Organ-Specific Adaptive Responses to Hypoxia Provides Insights to Human Diseases

The common carp is a hypoxia-tolerant fish, and the understanding of its ability to live in low-oxygen environments has been applied to human health issues such as cancer and neuron degeneration. Here, we investigated differential gene expression changes during hypoxia in five common carp organs including the brain, the gill, the head kidney, the liver, and the intestine. Based on RNA sequencing, gene expression changes under hypoxic conditions were detected in over 1800 genes in common carp. The analysis of these genes further revealed that all five organs had high expression-specific properties. According to the results of the GO and KEGG, the pathways involved in the adaptation to hypoxia provided information on responses specific to each organ in low oxygen, such as glucose metabolism and energy usage, cholesterol synthesis, cell cycle, circadian rhythm, and dopamine activation. DisGeNET analysis showed that some human diseases such as cancer, diabetes, epilepsy, metabolism diseases, and social ability disorders were related to hypoxia-regulated genes. Our results suggested that common carp undergo various gene regulations in different organs under hypoxic conditions, and integrative bioinformatics may provide some potential targets for advancing disease research

RNA-Seq-mediated transcriptomic analysis of heat stress response in a polar Chlorella sp. (Trebouxiophyceae, Chlorophyta)

The current outlook on mitigation of global warming does not appear promising, with figures in the reduction of anthropogenic greenhouse gas emissions lagging far behind climate goals. A recent environmental report even postulated a high possibility of temperature increase of at least 3 °C by 2100. Despite the low number of human inhabitants in Antarctica, the Antarctic Peninsula was reported as one of the most rapidly warming locations on earth. Many studies have shown that heat stress modulates physiological performance in many species of microalgae; however, studies to elucidate the molecular mechanisms of high-temperature thermotolerance are generally focused on the model species, i.e. Chlamydomonas reinhardtii. Furthermore, previous transcriptomic work in this aspect generally employed the microarray technique and/or involved the tropical or temperate strains, and few were conducted on the polar strains. In this study, RNA-Seq-mediated transcriptomic analysis was undertaken to compare the whole transcriptome profile of an Antarctic Chlorella sp. grown at ambient (4 °C) versus stress-inducing high (33 °C) temperatures and harvested at the 120-h time point. The findings of this study indicated a coordinated response to fine tune balance between energy production and utilisation for biosynthesis by redirecting carbon provision, and the arrest of cell division as a coping mechanism for an intense and relatively long period of stress. The strategies undertaken by this alga in acclimation to heat stress are somewhat similar to the heat stress response of the model species