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Collection Of Self-Research Papers Analyzing The Enhancement Of Uae-China Cooperation Through Public Policy Lenses, Jiaming Lu

Theses

This thesis examines how UAE public policies can align with China’s commercial and political interests to strengthen the current strategic partnership between the two nations, with a focus on bilateral business cooperation encompassing diplomatic collaboration, free zone trade, and energy sector corporate governance. The primary objective of this thesis is to analyze whether this comprehensive relationship can be sustained or elevated to “allweather, all-round, strategic, and future-oriented” strategic partnership amid global challenges. To achieve this objective, multiple analytical models were employed to assess relevant public policies and their implementation mechanisms, including historical analysis, dynamic modeling, and socio-legal analysis. The findings …

Test Of Strategies For Production And Harvest Of Edible Roots From Hydroponic Plants, Mariam Yaslem Albreiki

Theses

Hydroponic plant cultivation is becoming increasingly popular in the UAE, especially for leafy greens and fruit vegetables. By the end of the growing cycle, the roots of hydroponic plants are usually treated as crop residues, even though roots of several species are potentially edible and could be processed into food or nutraceuticals. Root crops like sweet potato or carrot might even be grown in hydroponic systems for the primary purpose of producing edible fibrous or tuberous roots. However, the use of hydroponic systems for the production of root biomass is not yet common, and most farmers strive to produce plants …

Implementation Of A Cascade Training Model To Enhance Emergency Care Capacity Of Healthcare Workers During The Covid-19 Outbreak In Uganda, Sulaiman Bugosera Wasukira, Carl Trevor Kambugu, Judith S. Nanyondo, Emmanuel Candia, Stephen Emmanuel Aporu, Cliff Asher Aliga

School of Nursing & Midwifery, East Africa

Introduction

Methods

Support Needs For Registered Nurses To Bachelor Of Science In Nursing Students In Kenyan Universities, Gladys Mbuthia, Gisela H. Van Rensburg, Sheila Shaibu

School of Nursing & Midwifery, East Africa

Higher percentages of the registered nurses (RN) workforce with a bachelor's degree have been associated with better patient outcomes. RN with a diploma in nursing who are upgrading their qualifications to a bachelor's degree in nursing enter universities in Kenya as mature and part-time students. Studies have shown that mature and part-time students in universities have a higher attrition than their full-time peers. They are less likely to access extra support and personal development opportunities available at university, have a history of campus isolation, and fewer opportunities to engage with campus peers. The purpose of the study was to explore …

Functional Grammar And Artificial Intelligence: A Vision For Enhancing The Teaching Of Arabic In Universities For Non-Specialists, Dr. Fathi Ahmed Alshormani

Faculty Peer-Reviewed Papers | بحوث هيئة التدريس المحكمة

No abstract provided.

'Reciprocal' Tariffs: What's In A Word, Petros C. Mavroidis

Faculty Scholarship

On 13 February 2025, President Trump released a memorandum announcing his intention to impose “reciprocal tariffs” under the Fair and Reciprocal Plan (FRP). The plan does not operate under a reasonable definition of reciprocity, is illegal under World Trade Organisation (WTO) law, would damage both the United States and its trading partners and could trigger reactions that would bring an end to the international trading system as we know it.

Acute-On-Chronic Liver Failure (Aclf): The ‘Kyoto Consensus’-Steps From Asia, A S Soin, Abdul Kadir Dokmeci, Abhijeet Chowdhury, Abraham Koshy, Ajay Duseja, Ajay Kumar, Ajay Kumar Mishra, Ajay Kumar Patwa, Ajit Sood, Akash Roy, Akash Shukla, Albert Chan, Aleksander Krag, Amar Mukund, Ameet Mandot, Amit Goel, Amna Subhan Butt, Amrish Sahney, Ananta Shrestha, Andrés Cárdenas, Angelo Di Giorgio, Anil Arora, Anil Chandra Anand, Anil Dhawan, Ankur Jindal, Anoop Saraya, Anshu Srivastava, Anupam Kumar, Apichat Kaewdech, Apurva Pande, Archana Rastogi, Arun Valsan, Ashish Goel, Ashish Kumar, Ashwani K Singal, Atsushi Tanaka, Audrey Coilly, Ayaskanta Singh, Babu Lal Meena, Barath Jagadisan, Barjesh Chander Sharma, Bikrant Bihari Lal, C E Eapen, Cesar Yaghi, Chandan Kumar Kedarisetty, Chang Wook Kim, Charles Panackel, Chen Yu, Chetan R Kalal, Chhagan Bihari, Chien Hao Huang, Chitranshu Vasishtha, Christian Jansen, Christian Strassburg, Chun Yen Lin, Constantine J Karvellas, Cosmas Rinaldi Adithya Lesmana, Cyriac Abby Philips, Debbie Shawcross, Dharmesh Kapoor, Dhiraj Agrawal, Diana Alcantara Payawal, Dibya Lochan Praharaj, Dinesh Jothimani, Do Seon Song, Dong Joon Kim, Dong-Sik Kim, Duan Zhongping, Fazal Karim, Francois Durand, Gamal E Shiha, Gennaro D'Amico, George K Lau, Girish Kumar Pati, Graciela Elia Castro Narro, Guan-Huei Lee, Gupse Adali, Guru Prasad Dhakal, Gyongyi Szabo, H C Lin, Hai Li, Hari Kumar Nair, Harshad Devarbhavi, Harshvardhan Tevethia, Hasmik Ghazinian, Hemamala Ilango, Hong Ling Yu, Irsan Hasan, J Fernandez, Jacob George, Jaideep Behari, James Fung, Jasmohan Bajaj, Jaya Benjamin, Jennifer C Lai, Jidong Jia, Jin Hua Hu, Jin Jun Chen, Jin Lin Hou, Jin Mo Yang, Johannes Chang, Jonel Trebicka, Jörg C Kalf, Jose D Sollano, Joy Varghese, Juan Pablo Arab, Jun Li, K Rajender Reddy, Kaiser Raja, Kalpana Panda, Kamal Kajal, Karan Kumar, Kaushal Madan, Kemal Fariz Kalista, Kessarin Thanapirom, Khin Maung Win, Ki Tae Suk, Krishnadas Devadas, Laurentius A Lesmana, Lubna Kamani, Madhumita Premkumar, Madunil A Niriella, Mamun Al Mahtab, Man Fung Yuen, Manal Hel Sayed, Manasa Alla, Manav Wadhawan, Manoj Kumar Sharma, Manoj Sahu, Manya Prasad, Mark Dhinesh Muthiah, Martin Schulz, Meenu Bajpai, Mettu Srinivas Reddy, Michael Praktiknjo, Ming Lung Yu, Mithra Prasad, Mithun Sharma, Mohamed Elbasiony, Mohammed Eslam, Mohd Golam Azam, Mohd Rela, Moreshwar S Desai, Mukul Vij, Nadim Mahmud, Narendra Singh Choudhary, Navin Kumar Marannan, Necati Ormeci, Neeraj Saraf, Nipun Verma, Nobuaki Nakayama, Norifumi Kawada, Oidov Baatarkhuu, Omesh Goyal, Osamu Yokosuka, P N Rao, Paolo Angeli, Pathik Parikh, Patrick S Kamath, Paul J Thuluvath, Philipp Lingohr, Piyush Ranjan, Prashant Bhangui, Pravin Rathi, Puja Sakhuja, Puneet Puri, Qin Ning, R K Dhiman, Rahul Kumar, Rajan Vijayaraghavan, Rajeev Khanna, Rakhi Maiwall, Ravi Mohanka, Richard Moreau, Rino Alvani Gani, Rohit Loomba, Rohit Mehtani, Ruveena Bhavani Rajaram, S S Hamid, Sachin Palnitkar, Sadhna Lal, Sagnik Biswas, Sakkarin Chirapongsathorn, Samagra Agarwal, Sanjeev Sachdeva, Sanjiv Saigal, Santhosh E Kumar, Sargsyan Violeta, Satender Pal Singh, Satoshi Mochida, Saurabh Mukewar, Seema Alam, Seng Gee Lim, Shahinul Alam, Shalimar, Shantan Venishetty, Shikha S Sundaram, Shiran Shetty, Shobna Bhatia, Shweta A Singh, Shyam Kottilil, Simone Strasser, S M Shasthry, Soe Thiha Maung, Soek Siam Tan, Sombat Treeprasertsuk, Sonal Asthana, Steffen Manekeller, Subhash Gupta, Subrat Kumar Acharya, Sudhamshu K C, Sudhir Maharshi, Sumeet Asrani, Sunil Dadhich, Sunil Taneja, Suprabhat Giri, Surender Singh, Tao Chen, Tarana Gupta, Tatsuo Kanda, Tawesak Tanwandee, Teerha Piratvishuth, Ulrich Spengler, V G Mohan Prasad, Vandana Midha, Venera Rakhmetova, Vicente Arroyo, Vikrant Sood, Vinay Kumar Br, Vincent Wai-Sun Wong, Viniyendra Pamecha, Virendra Singh, Vishwa Mohan Dayal, Vivek A Saraswat, Wray Kim, Wasim Jafri, Wenyi Gu, Wong Yu Jun, Xiaolong Qi, Yogesh K Chawla, Yoon Jun Kim, Yu Shi, Zaigham Abbas, Guresh Kumar, Shuichiro Shiina, Lai Wei, Masao Omata, Shiv Kumar Sarin, Apasl-Aclf Research Consortium (Aarc) For Apasl-Aclf Working Party

Faculty, Staff and Students Publications

Acute-on-chronic liver failure (ACLF) is a condition associated with high mortality in the absence of liver transplantation. There have been various definitions proposed worldwide. The first consensus report of the working party of the Asian Pacific Association for the Study of the Liver (APASL) set in 2004 on ACLF was published in 2009, and the "APASL ACLF Research Consortium (AARC)" was formed in 2012. The AARC database has prospectively collected nearly 10,500 cases of ACLF from various countries in the Asia-Pacific region. This database has been instrumental in developing the AARC score and grade of ACLF, the concept of the …

Exploring Key Factors Influencing Depressive Symptoms Among Middle-Aged And Elderly Adult Population: A Machine Learning-Based Method, Ngoc Doan Thu Tran, Yi Zhen Tan, Sapphire Lin, Fang Zhao, Yee Sien Ng, Dong Ma, Jeonggil Ko, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Objective: This paper aims to investigate the key factors, including demographics, socioeconomics, physical wellbeing, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most important predictors of depressive symptoms through the analysis, the findings can have important implications for early depression detection and intervention. Participants: For our cross-sectional study, we recruited a total of 976 volunteers, with a specific focus on individuals aged 50 and above. Each participant was requested to provide their demographic, socioeconomic information and undergo several physical health tests. Additionally, they were asked …

The Role Of Surprisal In Issue Trackers, James Caddy, Christoph Treude, Markus Wagner, Earl T. Barr

Research Collection School Of Computing and Information Systems

Context: Software development creates and relies on a large volume of information, yet the volume of this information can make it challenging for developers to maintain an overview of all goings-on that a team and external actors contribute to a project. We posit that unexpected or “surprising” events could serve as important signposts amidst this information overload. These unexpected events may indicate underlying anomalies or emergent situations that require immediate attention. To explore this premise, our study leverages the concept of ‘surprisal’ from information theory to identify and quantify these unusual occurrences from the issues and pull requests of popular …

Ptm4tag+: Tag Recommendation Of Stack Overflow Posts With Pre-Trained Models, Junda He, Bowen Xu, Zhou Yang, Donggyun Han, Chengran Yang, Jiakun Liu, Zhipeng Zhao, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow is one of the most influential Software Question & Answer (SQA) websites, hosting millions of programming-related questions and answers. Tags play a critical role in efficiently organizing the contents on Stack Overflow and are vital to support various site operations, such as querying relevant content. Poorly chosen tags often lead to issues such as tag ambiguity and tag explosion. Therefore, a precise and accurate automated tag recommendation technique is needed. Inspired by the recent success of pre-trained models (PTMs) in natural language processing (NLP), we present PTM4Tag+, a tag recommendation framework for Stack Overflow posts that utilize PTMs …

Exploring & Exploiting High-Order Graph Structure For Sparse Knowledge Graph Completion, Tao He, Ming Liu, Yixin Cao, Zekun Wang, Zihao Zheng, Bing Qin

Research Collection School Of Computing and Information Systems

Sparse Knowledge Graph (KG) scenarios pose a challenge for previous Knowledge Graph Completion (KGC) methods, that is, the completion performance decreases rapidly with the increase of graph sparsity. This problem is also exacerbated because of the widespread existence of sparse KGs in practical applications. To alleviate this challenge, we present a novel framework, LR-GCN, that is able to automatically capture valuable long-range dependency among entities to supplement insufficient structure features and distill logical reasoning knowledge for sparse KGC. The proposed approach comprises two main components: a GNN-based predictor and a reasoning path distiller. The reasoning path distiller explores high-order graph …

Bridging Expert Knowledge With Deep Learning Techniques For Just-In-Time Defect Prediction, Xin Zhou, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features from commit contents. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent the semantic meaning of the commits. On the other hand, deep learning-based features used by complex models represent the semantic meaning of commits but may …

Proactive Conversational Ai: A Comprehensive Survey Of Advancements And Opportunities, Yang Deng, Lizi Liao, Wenqiang Lei, Grace Hui Yang, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Dialogue systems are designed to offer human users social support or functional services through natural language interactions. Traditional conversation research has put significant emphasis on a system's response-ability, including its capacity to understand dialogue context and generate appropriate responses. However, the key element of proactive behavior-a crucial aspect of intelligent conversations-is often overlooked in these studies. Proactivity empowers conversational agents to lead conversations towards achieving pre-defined targets or fulfilling specific goals on the system side. Proactive dialogue systems are equipped with advanced techniques to handle complex tasks, requiring strategic and motivational interactions, thus representing a significant step towards artificial general …

Wf-Ppg: A Wrist-Finger Dual-Channel Dataset For Studying The Impact Of Contact Pressure On Ppg Morphology, Matthew Yiwen Ho, Hung Manh Pham, Aaqib Saeed, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) is a simple optical technique widely used in wearable devices for continuous cardiac health monitoring. However, the quality of PPG signals, particularly their morphology, is influenced by the contact pressure between the skin and the sensor. This variability in signal quality complicates complex tasks that rely on high-quality signals, such as blood pressure and heart rate variability estimation, making them less reliable or even impossible. To address this issue, we present a novel dataset (termed WF-PPG) comprising PPG signals from the wrist measured under varying contact pressures, along with high-quality PPG signals from the fingertip captured simultaneously. Data …

Loco: Low-Bit Communication Adaptor For Large-Scale Model Training, Xingyu Xie, Zhijie Lin, Kim-Chuan Toh, Pan Zhou

Research Collection School Of Computing and Information Systems

To efficiently train large-scale models, low-bit gradient communication compresses full-precision gradients on local GPU nodes into low-precision ones for higher gradient synchronization efficiency among GPU nodes. However, it often degrades training quality due to compression information loss. To address this, we propose the Low-bit Communication Adaptor (LoCo), which compensates gradients on local GPU nodes before compression, ensuring efficient synchronization without compromising training quality. Specifically, LoCo designs a moving average of historical compensation errors to stably estimate concurrent compression error and then adopts it to compensate for the concurrent gradient compression, yielding a less lossless compression. This mechanism allows it to …

Qultsf: Long-Term Time Series Forecasting With Quantum Machine Learning, Hari Hara Suthan Chittoor, Paul Robert Griffin, Ariel Neufeld, Jayne Thompson, Mile Gu

Research Collection School Of Computing and Information Systems

Long-term time series forecasting (LTSF) involves predicting a large number of future values of a time series based on the past values. This is an essential task in a wide range of domains including weather forecasting, stock market analysis and disease outbreak prediction. Over the decades LTSF algorithms have transitioned from statistical models to deep learning models like transformer models. Despite the complex architecture of transformer based LTSF models ‘Are Transformers Effective for Time Series Forecasting? (Zeng et al., 2023)’ showed that simple linear models can outperform the state-of-the-art transformer based LTSF models. Recently, quantum machine learning (QML) is evolving …

Siniel: Distributed Privacy-Preserving Zksnark, Yunbo Yang, Yuejia Cheng, Kailun Wang, Xiaoguo Li, Jianfei Sun, Jiachen Shen, Xiaolei Dong, Zhenfu Cao, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive, in which a prover convinces a verifier that a given statement is true without leaking any additional information. However, existing zkSNARKs suffer from high computation overhead in the proof generation. This limits the applications of zkSNARKs, such as private payments, private smart contracts, and anonymous credentials. Private delegation has become a prominent way to accelerate proof generation. In this work, we propose Siniel, an efficient private delegation framework for zkSNARKs constructed from polynomial interactive oracle proof (PIOP) and polynomial commitment scheme (PCS). Our protocol allows a computationally limited …

Impact Tracing: Identifying The Culprit Of Misinformation In Encrypted Messaging Systems, Zhongming Wang, Tao Xiang, Xiaoguo Li, Biwen Chen, Guomin Yang, Chuan Ma, Robert H. Deng

Research Collection School Of Computing and Information Systems

Encrypted messaging systems obstruct content moderation, although they provide end-to-end security. As a result, misinformation proliferates in these systems, thereby exacerbating online hate and harassment. The paradigm of “Reporting-then-Tracing” shows great potential in mitigating the spread of misinformation. For instance, message traceback (CCS’19) traces all the dissemination paths of a message, while source tracing (CCS’21) traces its originator. However, message traceback lacks privacy preservation for non-influential users (e.g., users who only receive the message once), while source tracing maintains privacy but only provides limited traceability. In this paper, we initiate the study of impact tracing. Intuitively, impact tracing traces influential …

Seven Hci Grand Challenges Revisited: Five-Year Progress, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Vincent G Duffy, Qin Gao, Waldemar Karwowski, Fiona Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Keng Siau, Jia Zhou

Research Collection School Of Computing and Information Systems

Motivated by the rapid technological advancements achieved in the last five years, and the pervasiveness of Artificial Intelligence, the paper investigates the evolving role of Human-Computer Interaction and revisits the seven grand challenges outlined in 2019: human-technology symbiosis, human-environment interactions, ethics, privacy and security, well-being, health and eudaimonia, accessibility and universal access, learning and creativity, and social organization and democracy. Through literature analysis, the paper reevaluates the status of each challenge and highlights emerging requirements. Key findings reveal the widespread impact of Artificial Intelligence across all domains and emphasize the need for improved AI transparency, alignment with human values, and …

Hotpatching On The Fly: Mitigating Drone Incidents Arising From Incorrect Configuration, Ruidong Han, Juanru Li, Zhuo Ma, David Lo, Arash Shaghaghi, Jianfeng Ma, Siqi Ma

Research Collection School Of Computing and Information Systems

Manufacturers offer adjustable control parameters for flight control systems to accommodate diverse environments and missions. To ensure flight safety, they also develop established boundaries, i.e., range specifications for parameter values. However, even when the configuration parameters fall within the prescribed manufacturer range, they could still lead to instability or even severe incidents like crashes, which are referred to as Range Specification Bugs. Prior research has suggested shrinking the range of parameter values to protect drones from the adverse effects of such bugs. However, narrowing the range of parameters may only reduce the probability of errors and could potentially limit the …

Sovereignty, Sins, And The Reassertion Of Primary Taxing Rights By The United States, Michael J. Graetz

Faculty Scholarship

In this report, Graetz argues that the United States must reassert its primary taxing rights over income long conceded to other countries, especially income from intellectual property created in the United States, and he explains some changes necessary to make that happen.

Voices From The Field: Mental Health Therapists' Perceptions Of Collaboration With Child Protective Services Workers, Tamara P. Fields

Electronic Theses and Dissertations

The child welfare system in the United States requires collaboration across various agencies in the provision of services. Although collaboration between mental health therapists and state agencies is fundamental when the goal is to provide quality care and achieve positive outcomes for families involved with Child Protective Services (CPS), the system is characterized as complicated and fragmented. Using Bronstein’s 2003 model of interprofessional collaboration to understand the dynamics of collaboration between mental health therapists and CPS workers in Texas, this qualitative descriptive research study described mental health therapists’ perceptions of collaborating with CPS workers in delivering therapy services to CPS-involved …

Advisor Satisfaction To Support Online Student Retention, Erica K. Whiddon

Electronic Theses and Dissertations

In this dissertation, the researcher explored the relationship between satisfaction with academic advising and online student retention. Online student retention is a critical issue in the context of increasing competition for students in higher education institutions. The specific problem was that online students have lower retention rates, and the reasons students typically select online degree programs are also the reasons they drop out of their degree programs. The purpose was to identify whether students’ reported satisfaction with their advisors mediated the relationship between the existence of external personal life factors and retention. A quantitative nonexperimental causal-comparative and correlational research design …

Consumption Responses To Income Shocks Through Lottery Winning, Seonghoon Kim, Kanghyock Koh

Research Collection School Of Economics

We study the effects of lottery winning on consumption spending using newly available household survey data in Singapore. We find strong consumption responses to a transitory income shock via lottery wins. Lottery winners spend about half of their prizes within 12 months of winning. We show that consumption responses are stronger among households with more binding liquidity constraints and less risk aversion, which is consistent with the standard life-cycle model. The strong consumption response suggests that fiscal stimulus policies or other public transfer programs could be an effective means of boosting consumption spending of the economy in the short run.

Something In The Air: Does Air Pollution Affect Fund Managers’ Carbon Divestment?, Thanh Huynh, Frank Weikai Li, Ying Xia

Research Collection Lee Kong Chian School Of Business

We examine whether fund managers overestimate carbon risk when they are exposed to local air pollution. We find that air pollution causes managers to underweight stocks of high-emission firms. The effects are stronger for less salient scopes of carbon emissions, among managers located in pro-environmental states, and among those likely to be surprised by air pollution—consistent with the idea that managers revise their beliefs about climate-transition risk following their exposure to air pollution. Carbon-intensive stocks sold by managers who are exposed to air pollution subsequently outperform stocks that they buy, suggesting that such underweighting is costly to fund investors.

Geographic Distance And State's Grip: Information Asymmetry, State Inattention, And Firm Implementation Of State Policy, Xiyi Yang, Heli Wang, Xiaoyu Zhou

Research Collection Lee Kong Chian School Of Business

In this study, we develop the argument that geographic distance between the state and local governments undermines the state's capacity to influence the implementation of state policies by local organizations. Drawing from information economics and the attention-based view, we propose that physical distance reduces the state's monitoring effectiveness through two interrelated mechanisms: information asymmetry and state leaders' inattention to distant issues. Using data of Chinese public firms' implementation of environmental activities between 2008 and 2016, we find that firms conduct fewer environmental activities required by the state when they are regulated by local governments that are more geographically distant to …

Information Spillover And Corporate Policies: The Case Of Listed Options, Gennaro Bernile, Jianfeng Hu, Guangzhong Li, Roni Michaely

Research Collection Lee Kong Chian School Of Business

Information production associated with derivatives markets is not a sideshow; rather, it has significantly positive spillover effects on an array of corporate decisions of underlying firms. Using a regression-discontinuity design based on exogenous variation in options availability as an instrument for changes in the information environment, we show that options introductions have causal effects on corporate policies on both sides of the balance sheet. Through improved information efficiency, options availability reduces the need for debt and payout, increases efficient investment, and yields superior innovation. We conduct two independent experiments demonstrating that our instrument s impact is not derived from alternative …

Is Carbon Risk Priced In The Cross Section Of Corporate Bond Returns?, Tinghua Duan, Frank Weikai Li, Quan Wen

Research Collection Lee Kong Chian School Of Business

This article examines the pricing of a firm’s carbon risk in the corporate bond market. Contrary to the “carbon risk premium” hypothesis, bonds of more carbon-intensive firms earn significantly lower returns. This effect cannot be explained by a comprehensive list of bond characteristics and exposure to known risk factors. Investigating sources of the low carbon alpha, we find the underperformance of bonds issued by carbon-intensive firms cannot be fully explained by divestment from institutional investors. Instead, our evidence is most consistent with investor underreaction to the predictability of carbon intensity for firm cash-flow news, creditworthiness, and environmental incidents.

Dft Study Of The Mechanism Of Selective Hydrogenation Of Acetylene By Rhodium Single-Atom Catalyst Supported On Hy Zeolite, Melisa Su Yordanlı, Roberto Escobar, Jessica Meza, Deniz Akgül, Yuxin Zhao, Alper Uzun, Fatma Ahu Akin, Viktorya Aviyente, Abdurrahman Cagri Atesin, Tülay A. Ateşin

School of Earth, Environmental, & Marine Sciences Faculty Publications

The selectivity of acetylene hydrogenation by the Rh single-atom catalyst (SAC) supported on HY zeolite was investigated using density functional theory (DFT) and a 5/83T quantum mechanics/molecular mechanics (QM/MM) embedded cluster model. The calculated activation barrier (ΔG‡) for the oxidative addition of dihydrogen to the Rh metal center (15.9 kcal/mol) is lower in energy than that for the σ-bond metathesis of dihydrogen to the Rh—C bond (22.7 kcal/mol) and the Rh—O bond (28.4 kcal/mol). The activation barriers of the oxidative addition of subsequent dihydrogen molecules are significantly higher than that of the oxidative addition of the first dihydrogen molecule. These …

The Mc4r Agonist, Setmelanotide, Is Associated With An Improvement In Hypercapnic Chemosensitivity And Weight Loss In Male Mice, Sarah N. Framnes-Deboer, Deanna M. Arble, Athena Rivera

Biological Sciences Faculty Research and Publications

Obesity increases the risk of respiratory diseases that reduce respiratory chemosensitivity, such as Obesity Hypoventilation Syndrome and sleep apnea. Recent evidence suggests that obesity-related changes in the brain, including alterations in melanocortin signaling via the melanocortin-4 receptor (MC4R), may underly altered chemosensitivity. Setmelanotide, an MC4R agonist, causes weight loss in both humans and animal models. However, it is unknown the extent to which setmelanotide affects respiratory chemosensitivity independent of body weight loss. The present study uses diet-induced obese, male C57bl/6 J mice to determine the extent to which acute setmelanotide treatment affects the hypercapnic ventilatory response (HCVR). We find that …