159 research outputs found

    On First-person Narration In The Disguise of Shƍjo ——An Analysis of Dazai Osamu’s “Joseito” and Kon Satoshi’s Perfect Blue

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    Senior Project submitted to The Division of Languages and Literature of Bard College

    Intermittent Continuance of Smart Health Devices: A Zone-of-Tolerance Perspective

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    Smart health and wearable devices have recently received widespread attention from practitioners and scholars. However, intermittent continuance behavior of users is considered to be one of the most important reasons hindering the development of smart health. To address this issue, the current study employs the zone-of-tolerance theory to explore the mechanisms through which intermittent continuance is evoked. In particular, this study develops two new constructs (i.e., performance superiority and performance adequacy), and proposes that they affect intermittent continuance via satisfaction and neutral satisfaction, respectively. Results demonstrated that the effects of the two new variables on intermittent continuance of smart health devices had been fully mediated. This study concludes with theoretical and practical implications

    Ferroptosis Contributes to Isoflurane Neurotoxicity

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    The underlying mechanisms of isoflurane neurotoxicity in the developing brain remain unclear. Ferroptosis is a recently characterized form of programmed cell death distinct from apoptosis or autophagy, characterized by iron-dependent reactive oxygen species (ROS) generation secondary to failure of glutathione-dependent antioxidant defenses. The results of the present study are the first to demonstrate in vitro that ferroptosis is a central mechanism contributing to isoflurane neurotoxicity. We observed in embryonic mouse primary cortical neuronal cultures (day-in-vitro 7) that 6 h of 2% isoflurane exposure was associated with decreased transcription and protein expression of the lipid repair enzyme glutathione peroxidase 4. In parallel, isoflurane exposure resulted in increased ROS generation, disruption in mitochondrial membrane potential, and cell death. These effects were significantly attenuated by pre-treatment with the selective ferroptosis inhibitor ferrostatin-1 (Fer-1). Collectively, these observations provide a novel mechanism for isoflurane-induced injury in the developing brain and suggest that pre-treatment with Fer-1 may be a potential clinical intervention for neuroprotection

    Improved Attacks on LowMC with Algebraic Techniques

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    The LowMC family of SPN block cipher proposed by Albrecht et al. was designed specifically for MPC-/FHE-/ZKP-friendly use cases. It is especially used as the underlying block cipher of PICNIC, one of the alternate third-round candidate digital signature algorithms for NIST post-quantum cryptography standardization. The security of PICNIC is highly related to the difficulty of recovering the secret key of LowMC from a given plaintext/ciphertext pair, which raises new challenges for security evaluation under extremely low data complexity. In this paper, we improve the attacks on LowMC under low data complexity, i.e. 1 or 2 chosen plaintext/ciphertext pairs. For the difference enumeration attack with 2 chosen plaintexts, we propose new algebraic methods to better exploit the nonlinear relation inside the introduced variables based on the attack framework proposed by Liu et al. at ASIACRYPT 2022. With this technique, we significantly extend the number of attack rounds for LowMC with partial nonlinear layers and improve the success probability from around 0.5 to over 0.9. The security margin of some instances can be reduced to only 3/4 rounds. For the key-recovery attack using a single plaintext, we adopt a different linearization strategy to reduce the huge memory consumption caused by the polynomial methods for solving multivariate equation systems. The memory complexity reduces drastically for all 5-/6-round LowMC instances with full nonlinear layers at the sacrifice of a small factor of time complexity. For 5-round LowMC instances with a block size of 129, the memory complexity decreases from 286.462^{86.46} bits to 248.182^{48.18} bits while the time complexity even slightly reduces. Our results indicate that the security for different instances of LowMC under extremely low data complexity still needs further exploration

    Improved Attacks on LowMC with Algebraic Techniques

    Get PDF
    The LowMC family of SPN block cipher proposed by Albrecht et al. was designed specifically for MPC-/FHE-/ZKP-friendly use cases. It is especially used as the underlying block cipher of PICNIC, one of the alternate third-round candidate digital signature algorithms for NIST post-quantum cryptography standardization. The security of PICNIC is highly related to the difficulty of recovering the secret key of LowMC from a given plaintext/ciphertext pair, which raises new challenges for security evaluation under extremely low data complexity. In this paper, we improve the attacks on LowMC under low data complexity, i.e. 1 or 2 chosen plaintext/ciphertext pairs. For the difference enumeration attack with 2 chosen plaintexts, we propose new algebraic methods to better exploit the nonlinear relation inside the introduced variables based on the attack framework proposed by Liu et al. at ASIACRYPT 2022. With this technique, we significantly extend the number of attack rounds for LowMC with partial nonlinear layers and improve the success probability from around 0.5 to over 0.9. The security margin of some instances can be reduced to only 3/4 rounds. For the key-recovery attack using a single plaintext, we adopt a different linearization strategy to reduce the huge memory consumption caused by the polynomial methods for solving multivariate equation systems. The memory complexity reduces drastically for all 5-/6-round LowMC instances with full nonlinear layers at the sacrifice of a small factor of time complexity. For 5-round LowMC instances with a block size of 129, the memory complexity decreases from 286.46 bits to 248.18 bits while the time complexity even slightly reduces. Our results indicate that the security for different instances of LowMC under extremely low data complexity still needs further exploration

    Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training

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    We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference. Our method incorporates a gating mechanism and LID loss, enabling transformer experts to learn language-specific information. By combining gated transformer experts with shared transformer layers, we construct multilingual transformer blocks and utilize linear experts to effectively regularize the joint network. The curriculum training scheme leverages LID to guide the gated experts in improving their respective language performance. Experimental results on a bilingual task involving English and Spanish demonstrate significant improvements, with average relative word error reductions of 12.5% and 7.3% compared to the baseline bilingual and monolingual models, respectively. Notably, our method achieves performance comparable to the upper-bound model trained and inferred with oracle LID. Extending our approach to trilingual, quadrilingual, and pentalingual models reveals similar advantages to those observed in the bilingual models, highlighting its ease of extension to multiple languages

    Development and validation of cuproptosis-related lncRNAs associated with pancreatic cancer immune microenvironment based on single-cell

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    BackgroundCuproptosis, a novel mode of cell death associated with the tricarboxylic acid (TCA) cycle, is relevant to the development of cancer. However, the impact of single-cell-based Cuproptosis-associated lncRNAs on the Tumor immune microenvironment (TIME) of Pancreatic adenocarcinoma (PAAD) and its potential value for individualized immunotherapy has not been clarified.Methods14 immune-related CRGs were screened by exploring the interaction between differentially expressed Immune-Related Genes (IRGs) and Cuproptosis-Related Genes (CRGs) in PAAD. Next, the expression amount and expression distribution of CRGs in single-cell samples were analyzed by focusing on 7-CRGs with significant expressions. On the one hand, MAP2K2, SOD1, and VEGFA, which were significantly differentially expressed between PAAD sites and normal tissues adjacent to them, were subjected to immunohistochemical validation and immune landscape analysis. On the other hand, from these 7-CRGs, prognostic signatures of lncRNAs were established by co-expression and LASSO-COX regression analysis, and their prognostic value and immune relevance were assessed. In addition, this study not only validated the hub CRGs and the lncRNAs constituting the signature in a PAAD animal model treated with immunotherapy-based combination therapy using immunohistochemistry and qRT-PCR but also explored the potential value of the combination of targeted, chemotherapy and immunotherapy.ResultsBased on the screening of 7-CRGs significantly expressed in a PAAD single-cell cohort and their co-expressed Cuproptosis-Related lncRNAs (CRIs), this study constructed a prognostic signature of 4-CRIs named CIR-score. A Nomogram integrating the CIR-score and clinical risk factors was constructed on this basis to predict the individualized survival of patients. Moreover, high and low-risk groups classified according to the median of signatures exhibited significant differences in clinical prognosis, immune landscape, bioenrichment, tumor burden, and drug sensitivity. And the immunohistochemical and qRT-PCR results of different mouse PAAD treatment strategies were consistent with the trend of inter-group variability in drug sensitivity of hub CRGs and CIR-score. The combination of immunotherapy, targeted therapy, and chemotherapy exhibited a better tumor suppression effect.ConclusionCIR-score, as a Cuproptosis-related TIME-specific prognostic signature based on PAAD single cells, not only predicts the prognosis and immune landscape of PAAD patients but also provides a new strategy for individualized immunotherapy-based combination therapy

    Zebrafish in dermatology: a comprehensive review of their role in investigating abnormal skin pigmentation mechanisms

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    Skin pigmentation abnormalities, ranging from aesthetic concerns to severe hyperpigmentation disease, have profound implications for individuals’ psychological and economic wellbeing. The intricate etiology of hyperpigmentation and our evolving comprehension of its underlying mechanisms underscore the need for robust animal models. Zebrafish, renowned for their transparent embryos and genetic parallels to humans, have been spotlighted as a pivotal model for skin pigmentation studies. This review offers a concise overview of zebrafish skin attributes, highlighting the shared melanin production pathways with humans. We systematically dissect the diverse strategies to craft zebrafish models of abnormal skin pigmentation, spanning physical, chemical, and genetic interventions, while critically appraising the merits and constraints of each approach. Additionally, we elucidate the metrics employed to gauge the efficacy of these models. Concluding, we cast a visionary gaze on prospective breakthroughs in the domain, aiming to steer forthcoming efforts in refined zebrafish models for skin pigmentation research
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