For Whom is She Singing? The Songs of Electra in Euripides’ and Sophocles’ Electra

The Electra plays of both Euripides and Sophocles respond to Aeschylus’ Choephori. While Choephori belongs to the Oresteia trilogy that narrates an intergenerational curse sealed by divine forces, Euripides and Sophocles concentrate more on the characterization of human beings, especially Electra. In each play, Electra becomes helpless and despairing after Agamemnon’s death at the hands of Clytemnestra and Aegisthus; Orestes’ return and reunion with Electra liberate her from her desperation and signal the revenge against Clytemnestra and Aegisthus that takes place after the recognition. While Sophocles spends a larger portion of his Electra on the depiction of Orestes’ homecoming, Euripides concentrates on the revenge. The different emphases of the two plays invite scholars to examine the two playwrights’ different characterizations of Electra. Long-lasting scholarly controversies surround the character of Electra in both plays. These controversies are closely related to Euripides’ and Sophocles’ attitudes towards the vengeful matricide. This work argues that an awareness of musical patterns can help us respond to those scholarly controversies and also to debates about how Greek theatrical music worked. I examine the sung parts of each play that are associated with Electra: the first songs, including the parodos and the lyric part leading up to it; the songs at the recognition scene; and the kommos after a death that is either just reported or just happened: in Sophocles’ Electra the kommos sung after the fake report of Orestes’ death; in Euripides’ Electra the kommos sung after Clytemnestra’s murder. I pay special attention to the correspondence between words and meters, the rhythm of specific meters, the distribution of lyric parts, and the musical communication between different characters. By examining metrical patterns, performance aspects, and the structure of these lyric parts and by viewing them in parallel, I show that in both plays Electra’s music and musical performances do much to determine her character, and that Euripides and Sophocles created distinct heroines through music

Emergent Communication in Interactive Sketch Question Answering

Vision-based emergent communication (EC) aims to learn to communicate through sketches and demystify the evolution of human communication. Ironically, previous works neglect multi-round interaction, which is indispensable in human communication. To fill this gap, we first introduce a novel Interactive Sketch Question Answering (ISQA) task, where two collaborative players are interacting through sketches to answer a question about an image in a multi-round manner. To accomplish this task, we design a new and efficient interactive EC system, which can achieve an effective balance among three evaluation factors, including the question answering accuracy, drawing complexity and human interpretability. Our experimental results including human evaluation demonstrate that multi-round interactive mechanism facilitates targeted and efficient communication between intelligent agents with decent human interpretability.Comment: Accepted by NeurIPS 202

Latency-Aware Collaborative Perception

Collaborative perception has recently shown great potential to improve perception capabilities over single-agent perception. Existing collaborative perception methods usually consider an ideal communication environment. However, in practice, the communication system inevitably suffers from latency issues, causing potential performance degradation and high risks in safety-critical applications, such as autonomous driving. To mitigate the effect caused by the inevitable latency, from a machine learning perspective, we present the first latency-aware collaborative perception system, which actively adapts asynchronous perceptual features from multiple agents to the same time stamp, promoting the robustness and effectiveness of collaboration. To achieve such a feature-level synchronization, we propose a novel latency compensation module, called SyncNet, which leverages feature-attention symbiotic estimation and time modulation techniques. Experiments results show that the proposed latency aware collaborative perception system with SyncNet can outperforms the state-of-the-art collaborative perception method by 15.6% in the communication latency scenario and keep collaborative perception being superior to single agent perception under severe latency.Comment: 14 pages, 11 figures, Accepted by European conference on computer vision, 202

Customising General Large Language Models for Specialised Emotion Recognition Tasks

The advent of large language models (LLMs) has gained tremendous attention over the past year. Previous studies have shown the astonishing performance of LLMs not only in other tasks but also in emotion recognition in terms of accuracy, universality, explanation, robustness, few/zero-shot learning, and others. Leveraging the capability of LLMs inevitably becomes an essential solution for emotion recognition. To this end, we further comprehensively investigate how LLMs perform in linguistic emotion recognition if we concentrate on this specific task. Specifically, we exemplify a publicly available and widely used LLM -- Chat General Language Model, and customise it for our target by using two different modal adaptation techniques, i.e., deep prompt tuning and low-rank adaptation. The experimental results obtained on six widely used datasets present that the adapted LLM can easily outperform other state-of-the-art but specialised deep models. This indicates the strong transferability and feasibility of LLMs in the field of emotion recognition

Near-Field Sparse Channel Estimation for Extremely Large-Scale RIS-Aided Wireless Communications

A significant increase in the number of reconfigurable intelligent surface (RIS) elements results in a spherical wavefront in the near field of extremely large-scale RIS (XL-RIS). Although the channel matrix of the cascaded two-hop link may become sparse in the polar-domain representation, their accurate estimation of these polar-domain parameters cannot be readily guaranteed. To tackle this challenge, we exploit the sparsity inherent in the cascaded channel. To elaborate, we first estimate the significant path-angles and distances corresponding to the common paths between the BS and the XL-RIS. Then, the individual path parameters associated with different users are recovered. This results in a two-stage channel estimation scheme, in which distinct learning-based networks are used for channel training at each stage. More explicitly, in stage I, a denoising convolutional neural network (DnCNN) is employed for treating the grid mismatches as noise to determine the true grid index of the angles and distances. By contrast, an iterative shrinkage thresholding algorithm (ISTA) based network is proposed for adaptively adjusting the column coherence of the dictionary matrix in stage II. Finally, our simulation results demonstrate that the proposed two-stage learning-based channel estimation outperforms the state-of-the-art benchmarks.Comment: This paper has been accepted for publication in the IEEE GLOBECOM 2023 Workshops Proceeding

The role of smoking and alcohol in mediating the effect of gastroesophageal reflux disease on lung cancer: A Mendelian randomization study

Observational studies have suggested a positive association between gastroesophageal reflux disease and lung cancer, but due to the existence of confounders, it remains undetermined whether gastroesophageal reflux disease (GERD) has a causal association with lung cancer. Therefore, Mendelian randomization (MR) analyses were applied to investigate the relationship between the two conditions. Two-sample Mendelian randomization analysis was utilized with summary genetic data from the European Bioinformatics Institute (602,604 individuals) and International Lung Cancer Consortium, which provides information on lung cancer and its histological subgroups. Furthermore, we used two-step Mendelian randomization and multivariable Mendelian randomization to estimate whether smoking initiation (311,629 cases and 321,173 controls) and alcohol intake frequency (n = 462,346) mediate any effect of gastroesophageal reflux disease on lung cancer risk. The Mendelian randomization analyses indicated that gastroesophageal reflux disease was associated with and significantly increased the risk of lung cancer (ORIVW = 1.35, 95% CI = 1.18–1.54; p = 1.36 × 10–5). Smoking initiation and alcohol intake frequency mediated 35% and 3% of the total effect of gastroesophageal reflux disease on lung cancer, respectively. The combined effect of these two factors accounted for 60% of the total effect. In conclusion, gastroesophageal reflux disease is associated with an increased risk of lung cancer, and interventions to reduce smoking and alcohol intake may reduce the incidence of lung cancer

Fe/MOF based platform for NIR laser induced efficient PDT/PTT of cancer

Introduction: Photodynamic therapy (PDT) and photothermal therapy (PTT) are widely used in the treatment of tumors. However, their application in the treatment of clinical tumors is limited by the complexity and irreversible hypoxia environment generated by tumor tissues. To overcome this limitation, a nanoparticle composed of indocyanine green (ICG) and Fe-MOF-5 was developed.Methods: We prepared F-I@FM5 and measured its morphology, particle size, and stability. Its enzyme like ability and optical effect was verified. Then we used MTT, staining and flow cytometry to evaluated the anti-tumor effect on EMT-6 cells in vitro. Finally, the anti-tumor effect in vivo has been studied on EMT-6 tumor bearing mice.Results: For the composite nanoparticle, we confirmed that Fe-MOF-5 has the best nanozyme activity. In addition, it has excellent photothermal conversion efficiency and generates reactive oxygen species (ROS) under near-infrared light irradiation (808 nm). The composite nanoparticle showed good tumor inhibition effect in vitro and in vivo, which was superior to the free ICG or Fe-MOF-5 alone. Besides, there was no obvious cytotoxicity in major organs within the effective therapeutic concentration.Discussion: Fe-MOF-5 has the function of simulating catalase, which can promote the decomposition of excessive H2O2 in the tumor microenvironment and produce oxygen to improve the hypoxic environment. The improvement of tumor hypoxia can enhance the efficacy of PDT and PTT. This research not only provides an efficient and stable anti-tumor nano platform, but also has broad application prospects in the field of tumor therapy, and provides a new idea for the application of MOF as an important carrier material in the field of photodynamic therapy

Matrix Metalloproteinase-2 and -9 Secreted by Leukemic Cells Increase the Permeability of Blood-Brain Barrier by Disrupting Tight Junction Proteins

Central nervous system (CNS) involvement remains an important cause of morbidity and mortality in acute leukemia, the mechanisms of leukemic cell infiltration into the CNS have not yet been elucidated. The blood-brain barrier (BBB) makes CNS become a refugee to leukemic cells and serves as a resource of cells that seed extraneural sites. How can the leukemic cells disrupt this barrier and invasive the CNS, even if many of the currently available chemotherapies can not cross the BBB? Tight junction in endothelial cells occupies a central role in the function of the BBB. Except the well known role of degrading extracellular matrix in metastasis of cancer cells, here we show matrix metalloproteinase (MMP)-2 and -9, secreted by leukemic cells, mediate the BBB opening by disrupting tight junction proteins in the CNS leukemia. We demonstrated that leukemic cells impaired tight junction proteins ZO-1, claudin-5 and occludin resulting in increased permeability of the BBB. However, these alterations reduced when MMP-2 and -9 activities were inhibited by RNA interference strategy or by MMP inhibitor GM6001 in an in vitro BBB model. We also found that the disruption of the BBB in company with the down-regulation of ZO-1, claudin-5 and occludin and the up-regulation of MMP-2 and -9 in mouse brain tissues with leukemic cell infiltration by confocal imaging and the assay of in situ gelatin zymography. Besides, GM6001 protected all mice against CNS leukemia. Our findings suggest that the degradation of tight junction proteins ZO-1, claudin-5 and occludin by MMP-2 and -9 secreted by leukemic cells constitutes an important mechanism in the BBB breakdown which contributes to the invasion of leukemic cells to the CNS in acute leukemia

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients