Beyond the Veil: A Contemporary Reimagining of Chinese Shadow Puppetry

Chinese shadow puppetry is a traditional art-form of storytelling that requires highly-skilled craftsmanship. Though it enjoyed great prestige in the past, at present Chinese shadow puppetry struggles to survive as it is difficult to recruit apprentices and to appeal to contemporary audiences. This honors project explores how to adapt the art-form with alternative materials and performance techniques, so that it may welcome younger generations as practitioners and spectators. For example, a simpler crafting process makes the art-form more accessible for novice puppeteers while preserving key traditional elements; or a Chinese horror-themed story that tailors more towards the youth’s interest

On Competition for Undergraduate Co-op Placement: A Graph Approach

The objective of this thesis is to improve the co-operative (co-op) education process by analyzing the relationships among academic programs in the context of the co-op job market. To do this, we propose and apply a novel graph-mining methodology. The input to our problem consists of student-job interview pairs, with each student labelled with his or her academic program. From this input, we build a weighted directed graph, which we refer to as a program graph, in which nodes correspond to academic programs and edge weights denote the percentage of jobs that interviewed at least one student from both programs. For example, a directed edge from the Computer Engineering program to the Electrical Engineering program with weight 0.36 means that of all the jobs that interviewed at least one Computer Engineering student, 36 percent of those jobs also interviewed at least one Electrical Engineering student. Thus, the larger the edge weight, the stronger the relationship and competition between particular programs. The output consists of various graph properties and analyses, particularly those which find nodes forming clusters or communities, nodes that are connected to few or many clusters, and nodes that are strongly connected to their immediate neighbours. As we will show, these properties have natural interpretations in terms of the relationships among academic programs and competition for co-op jobs. We applied the proposed methodology on one term of co-op interview data from a large Canadian university. We obtained interesting new insights that have not been reported in prior work. These insights can be beneficial to students, employers and academic institutions. Characterizing closely connected programs can help employers broaden their search for qualified students and can help students select programs of study that better correspond to their desired career. Students seeking a multi-disciplinary education can choose programs that are connected to other programs from many different clusters. Additionally, institutions can attend to programs that are strongly connected to (and face competition from) other programs by attracting more employers offering jobs in this area

Comprehensive Analysis, Discussion and Suggestion on the Current Situation of Cardiopulmonary Resuscitation and Automatic External Defibrillator in General Public in China

The number of sudden cardiac death (SCD) has increased year by year, which has become one of the main causes of death in China. Timely cardiopulmonary resuscitation (CPR) and timely and accurate use of automatic external defibrillator (AED) can greatly improve the survival rate of patients with sudden cardiac death. Because the large probability of sudden cardiac death occurs outside the hospital, it is very important for the general public to master first aid skills. This paper will mine all kinds of data from multi-dimensional and multi-angle, analyze the mastery of public first aid skills in China, and provide practical suggestions and ideas for popularizing first aid skills in the future

Molecular oxygen-assisted in defect-rich ZnO for catalytic depolymerization of polyethylene terephthalate

Polyethylene terephthalate (PET) is the most produced polyester plastic; its waste has a disruptive impact on the environment and ecosystem. Here, we report a catalytic depolymerization of PET into bis(2-hydroxyethyl) terephthalate (BHET) using molecule oxygen (O2)−assisted in defect-rich ZnO. At air, the PET conversion rate, the BHET yield, and the space-time yield are 3.5, 10.6, and 10.6 times higher than those in nitrogen, respectively. Combining structural characterization with the results of DFT calculations, we conclude that the (100) facet of defect-rich ZnO nanosheets conducive to the formation of reactive oxygen species (∗O2−) and Zn defect, promotes the PET breakage of the ester bond and thus complete the depolymerization processed. This approach demonstrates a sustainable route for PET depolymerization by molecule-assisted defect engineering.publishedVersio

Insights into the Roles of Midazolam in Cancer Therapy

With its high worldwide mortality and morbidity, cancer has gained increasing attention and novel anticancer drugs have become the focus for cancer research. Recently, studies have shown that most anesthetic agents can influence the activity of tumor cells. Midazolam is a γ-aminobutyric acid A (GABAA) receptor agonist, used widely for preoperative sedation and as an adjuvant during neuraxial blockade. Some studies have indicated the potential for midazolam as a novel therapeutic cancer drug; however, the mechanism by which midazolam affects cancer cells needs to be clarified. This systematic review aims to summarize the progress in assessing the molecular mechanism of midazolam as an anticancer agent

HiFi4G: High-Fidelity Human Performance Rendering via Compact Gaussian Splatting

We have recently seen tremendous progress in photo-real human modeling and rendering. Yet, efficiently rendering realistic human performance and integrating it into the rasterization pipeline remains challenging. In this paper, we present HiFi4G, an explicit and compact Gaussian-based approach for high-fidelity human performance rendering from dense footage. Our core intuition is to marry the 3D Gaussian representation with non-rigid tracking, achieving a compact and compression-friendly representation. We first propose a dual-graph mechanism to obtain motion priors, with a coarse deformation graph for effective initialization and a fine-grained Gaussian graph to enforce subsequent constraints. Then, we utilize a 4D Gaussian optimization scheme with adaptive spatial-temporal regularizers to effectively balance the non-rigid prior and Gaussian updating. We also present a companion compression scheme with residual compensation for immersive experiences on various platforms. It achieves a substantial compression rate of approximately 25 times, with less than 2MB of storage per frame. Extensive experiments demonstrate the effectiveness of our approach, which significantly outperforms existing approaches in terms of optimization speed, rendering quality, and storage overhead

Causal associations between human gut microbiota and osteomyelitis: a Mendelian randomization study

BackgroundRecent studies have emphasized the role of gut microbiota in the onset and progression of osteomyelitis. However, the exact types of gut microbiota and their mechanisms of action remain unclear. Additionally, there is a lack of theoretical support for treatments that improve osteomyelitis by altering the gut microbiota.MethodsIn our study, we utilized the largest genome-wide association study (GWAS) meta-analysis to date from the MiBioGen consortium, involving 13,400 participants. The GWAS data for osteomyelitis were sourced from the UK Biobank, which included 4,836 osteomyelitis cases and 486,484 controls. We employed a two-sample Mendelian randomization framework for a detailed investigation into the causal relationship between gut microbiota and osteomyelitis. Our methods included inverse variance weighting, MR-Egger, weighted median, and weighted mode approaches. Additionally, we applied Cochran’s Q statistic to assess the heterogeneity of the instrumental variable.ResultsAt the class level, Bacilli and Bacteroidia were positively correlated with the risk of osteomyelitis. At the order level, only Bacteroidales showed a positive association with osteomyelitis. At the genus level, an increased abundance of Butyricimonas, Coprococcus3, and Tyzzerella3 was positively associated with the risk of osteomyelitis, whereas Lachnospira was negatively associated. Sensitivity analyses showed no evidence of heterogeneity or pleiotropy.ConclusionThis study reveals that classes Bacilli and Bacteroidia, order Bacteroidales, and genera Butyricimonas, Coprococcus3, and Tyzzerella3 are implicated in increasing the risk of osteomyelitis, while the genus Lachnospira is associated with a reduced risk. Future investigations are warranted to elucidate the precise mechanisms through which these specific bacterial groups influence the pathophysiology of osteomyeliti

How Does Online Information Influence Offline Transactions? Insights from Digital Real Estate Platforms

Digital platforms facilitate the flow of information and the execution of transactions. This study investigates the impact of signals from platform-provided online information regarding search and experience attributes of products on the prices of their offline transactions. We situate our theorizing and empirical work in the context of digital real estate platforms. Our results suggest that online information pertaining to properties’ experience attributes has a significant influence on the prices of offline property transactions. The amount of online information relating to experience attributes—specifically, length of textual property description and the number of photos—positively influences the sale price of a property. In contrast, the amount of online property information related to search attributes—specifically, facts and features—has no significant influence on the property’s sale price. In addition, online property information on experience attributes has a significant impact on the sale price of uncommon properties (those valued significantly above or below their neighborhood averages), whereas its impact on the price of common properties (those valued close to their neighborhood averages) is insignificant. The findings are robust to various model specifications and across property transactions in different years, seasons, and geographical regions. They are also neither subject to confounding effect of real estate agents’ service quality nor driven by unobserved property heterogeneities. The findings shed light on how signals from online property information are used by home buyers and sellers for different types of properties. The insights have implications for how real estate professionals can better utilize digital platforms to convey signals regarding properties and facilitate property transactions and for how the platforms can be designed to support the exchange of information that provides signals on the quality of offline goods that are highly risky and experiential.This accepted article is published as Zhengrui Jiang, Arun Rai, Hua Sun, Cheng Nie, Yuheng Hu (2023) How Does Online Information Influence Offline Transactions? Insights from Digital Real Estate Platforms. Information Systems Research 0(0). https://doi.org/10.1287/isre.2020.0658Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2020.0658. Copyright © 2023, INFORM