Between Purity, Sexual Corruption and Maternity -- Sexual and Ethnic Ambiguities in Love with the Proper Stranger (1963)

2020 Pamela J. Mackintosh Undergraduate Research Awards, Single-term, 3rd Place"Love with the Proper Stranger" tells the story of an Italian-American young woman Angie, who finds herself pregnant after having a romantic encounter with an Italian-American musician Rocky, and she asks him to find a doctor for her. In their thwarted attempt to abort the child, the two of them begin to develop some affections, and after some twists and turns, the story ends with Rocky’s proposal to Angie. While Mulligan lightly summarized it as a story of “falling in love in reverse,” and the screenwriter Arnold Schulman also joked it as “A funny thing happened on the way to the abortionist . . .”, the film was actually quite bold in the time of its release, and shed light upon larger themes including ethnicity and gender. Although it ends with a potential marriage, the story is based on a premarital sex that results in pregnancy, and despite the strained effort to reframe the “one night stand” in a marriage, the film makes breakthroughs in terms of its shaping of its female protagonist, embodying up-to-date ideas about gender and sex while providing us with a somehow fresh view of third-generation Italian-American families. This paper will argue that by depicting Angie, a third-generation Italian American woman’s story, this film expresses some of America’s cultural anxieties in a period of transitions of 1960s. The Italian ethnicity of the main characters helps the film to construct the conflicts between family and individual, between the good old values and the new liberalist beliefs.Meanwhile, the film leaves much ambiguous space in terms of Angie’s Italianness and sexuality. By rendering her Italian ethnic marks almost invisible, as well as hiding her romantic sexual encounter behind her pure image, the film represents a time of rapid changes, where ideological and moral problems are left unresolved.https://deepblue.lib.umich.edu/bitstream/2027.42/156025/1/Research_Feiyang_Zhang.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/156025/2/Bibliography_Feiyang_Zhang.pdfDescription of Research_Feiyang_Zhang.pdf : PaperDescription of Bibliography_Feiyang_Zhang.pdf : Bibliograph

Characterization and Correction of the Scattering Background Produced by Dust on the Objective Lens of the Lijiang 10-cm Coronagraph

Scattered light from the objective lens, directly exposed to the intense sunlight, is a dominant source of stray light in internally occulted coronagraphs. The variable stray light, such as the scatter from dust on the objective lens, can produce varying scattering backgrounds in coronal images, significantly impacting image quality and data analysis. Using data acquired by the Lijiang 10-cm Coronagraph, the quantitative relationship between the distribution of dust on the objective lens and the resulting scattering backgrounds background is analyzed. Two empirical models for the scattering background are derived, and used to correct the raw coronal data. The second model, which depends on three parameters and performs better, shows that the scattering-background distribution varies with angle, weakens with increasing height, and enhances with increasing dust level on the objective lens. Moreover, we find that the dust on the center of the objective lens can contribute more significantly to the scattering background than on the edge. This study not only quantitatively confirms the significant impact of the stray light produced by dust on the objective lens of the coronagraph, but also corrects the coronal data with this stray light for the first time. Correcting for dust-scattered light is crucial for the high-precision calibration of ground-based coronagraph data, enabling a more accurate analysis of coronal structures. Furthermore, our model is envisioned to support the provision of reliable observational data for future routine coronal magnetic-field measurements using ground-based coronagraphs.Comment: 18 pages, 14 figrue

Sustainable development in natural resources industry: is geopolitical risk a catalyst for corporate excess cash holdings?

With the outbreak of the Russia-Ukraine conflict, combined with the COVID-19 epidemic and the Federal Reserve’s interest rate hike, geopolitical risks have increased sharply, which has brought great pressure on the sustainable development of natural resources industry. This study aims to discuss the impact of geopolitical risk (GPR) on corporate excess cash holdings in China’s natural resources industry. The findings suggest that GRP can encourage enterprises in the natural resources industry to hold more excess cash. The findings still hold with a suite of robustness tests. The study also evidences that the above effect is more significant for state-owned enterprises, enterprises in the mining industry, and large-scale enterprises. Finally, further results show that with the increase of GPR, enterprises with strong risk-taking capacity tend to hold more excess cash, while enterprises registered in higher market-oriented regions are inclined to retain less excess cash. These findings can conduce to a deep understanding of the influence of GPR on corporate excess cash holdings and serve as a reference for policy-makers to adjust policies

Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution

Optimal execution is a sequential decision-making problem for cost-saving in algorithmic trading. Studies have found that reinforcement learning (RL) can help decide the order-splitting sizes. However, a problem remains unsolved: how to place limit orders at appropriate limit prices? The key challenge lies in the "continuous-discrete duality" of the action space. On the one hand, the continuous action space using percentage changes in prices is preferred for generalization. On the other hand, the trader eventually needs to choose limit prices discretely due to the existence of the tick size, which requires specialization for every single stock with different characteristics (e.g., the liquidity and the price range). So we need continuous control for generalization and discrete control for specialization. To this end, we propose a hybrid RL method to combine the advantages of both of them. We first use a continuous control agent to scope an action subset, then deploy a fine-grained agent to choose a specific limit price. Extensive experiments show that our method has higher sample efficiency and better training stability than existing RL algorithms and significantly outperforms previous learning-based methods for order execution

Anomalous Sound Detection Using Self-Attention-Based Frequency Pattern Analysis of Machine Sounds

Different machines can exhibit diverse frequency patterns in their emitted sound. This feature has been recently explored in anomaly sound detection and reached state-of-the-art performance. However, existing methods rely on the manual or empirical determination of the frequency filter by observing the effective frequency range in the training data, which may be impractical for general application. This paper proposes an anomalous sound detection method using self-attention-based frequency pattern analysis and spectral-temporal information fusion. Our experiments demonstrate that the self-attention module automatically and adaptively analyses the effective frequencies of a machine sound and enhances that information in the spectral feature representation. With spectral-temporal information fusion, the obtained audio feature eventually improves the anomaly detection performance on the DCASE 2020 Challenge Task 2 dataset.Comment: Published in INTERSPEECH 202