Digital Commons Network^™

Medicaid Expansion Expectations, Deborah Farringer

Law Faculty Scholarship

Although financial stability in rural hospitals has been a relatively long-standing national problem, in the last decade, hospital closures and the incidence of highly distressed hospitals in rural areas have disproportionately impacted certain states. States that have not expanded their Medicaid programs under the Affordable Care Act, which implemented a program to extend additional federal support to cover adults living below 138% of the federal poverty line (referred to herein as “Medicaid Expansion”), are bearing the brunt of this crisis. Although the reason for hospital closures is multi-faceted and complex, health policy experts have consistently identified the lack of Medicaid …

Insider Trading Restrictions And Real Activities Earnings Management: International Evidence, Yuanto Kusnadi, Yuanto Kusnadi, Jiwei Wang, Yujie Wang

Research Collection School Of Accountancy

We examine the implications of insider trading restrictions on firms’ real activities earnings management in an international setting. Using a sample of 28 countries over the period from 1992 to 2007, we find evidence that is supportive of the substitution hypothesis, in that managers have incentives to substitute accruals earnings management for real activities earnings management. This effect is found to be more pronounced for firms in countries with more restrictive insider trading regulation. Our result is robust to alternative measures of real activities earnings management and insider trading restrictions, alternative sub-samples, alternative regression specifications, and controlling for endogeneity. In …

Contextualizing The Organizational Mindset, Joseph A. Carpini, Burak Oc

Research Collection Lee Kong Chian School Of Business

Although Schneider and Pulakos (2022, p. 2) call for scholars to adopt an “organizational mindset,” which includes “an increased organizational frame of reference on variables of interest,” the authors have overlooked the importance of contextualizing such a mindset. Contextualizing “entails linking observations to a set of relevant facts, events, or points of view that make possible research and theory that form part of a larger whole” (Rousseau & Fried, 2001, p. 1). Contextualizing is essential because it provides a common vernacular that facilitates the valid and reliable extension of the industrial-organizational (I-O) mindset to the study of organizational differences and …

Employer Image Within And Across Industries: Moving Beyond Assessing Points-Of-Relevance To Identifying Points-Of-Difference, Greet Van Hoye, Filip Lievens, Bert Weijters, Saartje Cromheecke

Research Collection Lee Kong Chian School Of Business

This study draws from brand positioning research to introduce the notions of points-of-relevance and points-of-difference to employer image research. Similar to prior research, this means that we start by investigating the relevant image attributes (points-of-relevance) that potential applicants use for judging organizations' attractiveness as an employer. However, we go beyond past research by examining whether the same points-of-relevance are used within and across industries. Next, we further extend current research by identifying which of the relevant image attributes also serve as points-of-difference for distinguishing between organizations and industries. The sample consisted of 24 organizations from 6 industries (total N = …

Distinctive Features Of Nonverbal Behavior And Mimicry In Application Interviews Through Data Analysis And Machine Learning, Sanne Rogiers, Elias Corneillie, Filip Lievens, Frederik Anseel, Peter Veelaert, Wilfried Philips

Research Collection Lee Kong Chian School Of Business

This paper reveals the characteristics and effects of nonverbal behavior and human mimicry in the context of application interviews. It discloses a novel analyzation method for psychological research by utilizing machine learning. In comparison to traditional manual data analysis, machine learning proves to be able to analyze the data more deeply and to discover connections in the data invisible to the human eye. The paper describes an experiment to measure and analyze the reactions of evaluators to job applicants who adopt specific behaviors: mimicry, suppress, immediacy and natural behavior. First, evaluation of the applicant qualifications by the interviewer reveals …

Corporate Actions And The Manipulation Of Retail Investors In China: An Analysis Of Stock Splits, Sheridan Titman, Chi Shen Wei, Bin Zhao

Research Collection Lee Kong Chian School Of Business

We identify a group of “suspicious” firms that use stock splits, perhaps along with other activities, to artificially inflate their share prices. Following the initiation of suspicious splits, share prices temporarily increase, and subsequently decline below their presplit levels. Using account level data from the Shanghai Stock Exchange, we find that small retail investors acquire shares in firms initiating suspicious splits, while more sophisticated investors accumulate positions before suspicious split announcements and sell in the postsplit period. We also find that insiders sell large blocks of shares and obtain loans using company stock as collateral around the initiation of suspicious …

Fractile Graphical Analysis In Finance: A New Perspective With Applications, Anil K. Bera, Aurobindo Ghosh

Research Collection Lee Kong Chian School Of Business

Fractile Graphical Analysis (FGA) was proposed by Prasanta Chandra Mahalanobis in 1961 as a method for comparing two distributions at two different points (of time or space) controlling for the rank of a covariate through fractile groups. We use bootstrap techniques to formalize the heuristic method used by Mahalanobis for approximating the standard error of the dependent variable using fractile graphs from two independently selected “interpenetrating network of subsamples.” We highlight the potential and revisit this underutilized technique of FGA with a historical perspective. We explore a new non-parametric regression method called Fractile Regression where we condition on the ranks …

Reaching For Rigor And Relevance: Better Marketing Research For A Better World, Shilpa Madan, Et. Al.

Research Collection Lee Kong Chian School Of Business

Over the past several decades, scholars have highlighted the obligations and opportunities for marketing as a discipline to play a role in creating a better world — or risk becoming irrelevant for the largest problems facing consumers and society. This paper provides a framework to enhance the relevance and rigor of research in marketing that not only contributes new knowledge to science, but also makes a positive difference in the world. To that end, we urge authors and reviewers to foster cross-fertilization from different theoretical and methodological silos, bolster robustness through multiple methods, and expand the domain of research to …

Prioritization Of Invasive Alien Species With The Potential To Threaten Agriculture And Biodiversity In Kenya Through Horizon Scanning, Joseph Mulema, Roger Day, Winnie Nunda, Komivi Senyo Akutse, Anani Y. Bruce, Sospeter Gachamba, Solveig Haukeland, Ruth Kahuthia-Gathu, Staline Kibet, Asenath Koech, Thomas Kosiom, Douglas Watuku Miano, George Momanyi, Lucy Kananu Murungi, James Wanjohi Muthomi, Julianna Mwangi, Maina Mwangi, Nicholas Mwendo, John Huria Nderitu, Johnson Nyasani, Miriam Otipa, Sarah Wambugu, Eric Were, Fernadis Makale, Laura Doughty, Steve Edgington, Ivan Rwomushana, Marc Kenis

All Peer-Reviewed Publications

Invasive alien species (IAS) rank among the most significant drivers of species extinction and ecosystem degradation resulting in significant impacts on socio-economic development. The recent exponential spread of IAS in most of Africa is attributed to poor border biosecurity due to porous borders that have failed to prevent initial introductions. In addition, countries lack adequate information about potential invasions and have limited capacity to reduce the risk of invasions. Horizon scanning is an approach that prioritises the risks of potential IAS through rapid assessments. A group of 28 subject matter experts used an adapted methodology to assess 1700 potential IAS …

Health Care Utilization And Costs Associated With Functional Status In Patients With Psoriatic Arthritis, Alexis Ogdie, Mark Hwang, Phani Veeranki, Alexandria Portelli, Steven Sison, Jason Shafrin, Sofia Pedro, Steven Hass, Peter Hur, Nina Kim, Esther Yi, Kaleb Michaud

Faculty, Staff and Student Publications

BACKGROUND: The Health Assessment Questionnaire Disability Index (HAQ-DI) has been validated and widely used in psoriatic arthritis (PsA) clinical trials for the assessment of patient functional status. Significant improvements in the HAQ-DI have been reported in response to therapeutic interventions; however, few US studies have evaluated the economic impact of functional disability in patients with PsA.

OBJECTIVE: To evaluate the association of functional status with health care resource utilization (HCRU) and total health care costs in US patients diagnosed with PsA.

METHODS: This retrospective study included adult patients with PsA enrolled in FORWARD between July 2009 and June 2019 who …

Development Of A Novel Pharmacophore Model To Screen Specific Inhibitors For The Serine-Threonine Protein Phosphatase Calcineurin, Abhisek Mukherjee, Karina Cuanalo-Contreras, Abha Sood, Claudio Soto

Faculty, Staff and Student Publications

Calcineurin (CaN) is a calcium/calmodulin-dependent serine/threonine phosphatase with a crucial role in cellular homeostasis. It is also the target of the Food and Drug Administration (FDA) approved immunosuppressant drugs FK506 and cyclosporine A. Recent work from our group and others indicated that an uncontrolled increase in CaN activity causes synaptic dysfunction and neuronal death in various models of neurodegenerative diseases associated with calcium dysregulation. Furthermore, pharmacological normalization of CaN activity can prevent disease progression in animal models. However, none of the FDA-approved CaN inhibitors bind CaN directly, leading to adverse side effects. The development of direct CaN inhibitors is required …

Legacy Refworks Will Be Retired September 30, 2022, Joanne Romano

TMC Library Newsletter (2015-)

The Texas Medical Center Library will be retiring user accounts in the Legacy version of RefWorks on September 30, 2022.

New One Button Recording Studio, Katie Prentice

TMC Library Newsletter (2015-)

For more information consult the One Button Studio page.

Jove Videos For Science Education And Research — Now Available, Joanne Romano

TMC Library Newsletter (2015-)

The Texas Medical Center Library now subscribes to all JoVE videos for both Research and Education. JoVE’s 15,000+ instructional videos combine high-impact animations with real-life experimentation to help accelerate learning and allow you to refresh skill sets independently. Content can be accessed 24/7 and translations are included.

Executive Summaries

The Foundation Review

No abstract provided.

Media Relations Strategies Of Philanthropic Foundations: A Longitudinal Analysis Of News Releases Produced By Top U.S. Foundations, Richard D. Waters, Giselle Auger, Kelly Husted

The Foundation Review

Given their role in funding programs and services provided by nonprofit organizations, foundations have a critical role as advocates for social change. However, grant money is by itself not enough to create that change. Agenda-setting theory highlights the critical role of organizations in bringing change issues to the attention of the media and, therefore, the public. This article uses content analysis to compare two sets of a random sample of news releases from 20 of the largest foundations in the United States. The two sets are seven years apart, from 2014 and 2021, to allow comparison of the maturation of …

Book Review: In Defence Of Philanthropy, Nabih Haddad

The Foundation Review

No abstract provided.

Concrete Dust Versus Angel's Wings? Sacralization Of The “Victory Monument” And Postcolonial Memory Politics In Latvia, Deniss Hanovs

Occasional Papers on Religion in Eastern Europe

The article analyzes the current state of memory politics in Latvian society in the frame of Baltic postcolonial studies. The dominant traumatic experience of contemporary Latvian society is the period of Soviet occupation (1940, renewed 1944, lasting until 1991) and WWII. The so-called “Monument of Victory” in Riga was the central site of memory, loaded with mnemonic tension and ambiguity of collective memories of the Russian-speakers in the restored nation state. After it was toppled on August 25, 2022, the monument continues to exist in Russian-speakers’ digital imagination and is framed by the semiotics of a sacred site of memory. …

The Orthodox Theology Of Modernity: Problem Statement And Prospective Tasks, Hennadii Khrystokin, Vasyl Lozovytskyi

Occasional Papers on Religion in Eastern Europe

The article studies the problem of Orthodoxy's attitude to modernity. The concept of the theology of modernity–a new section of the social theology of the church, which considers the specifics, main trends, problems, and tendencies of modernity–is proposed. The theology of modernity raises questions about the possibilities, boundaries, and ways of renewal of the church. The concept of the theology of modernity is a set of methods, approaches, and discourses that allow us to comprehend modernity, carry out its assessment by means of Orthodox theology, and find its religious potential for the actualization of Christianity in our time. The analysis …

Acid Mine Drainage In The Shamokin Creek Watershed: A Spatial Analysis Of Economic And Environmental Consequences Of Coal Mining, Ben Shimer

Student Project Reports

No abstract provided.

An Efficient Electronic Payment Using Biometric Authentication, Ahmed A. Talib, Aymen D.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Traditional identification techniques for electronic payments, such as the Personal Identification Number (PIN), are becoming outdated and unsafe, while mobile payments are becoming more popular and widely used. It presents a risk to Issuers since there is no reliable consumer verification method available, and the lack of safe and reliable e-payment systems is one of the key Issues restricting progress. As a result, efforts have been made to develop and maintain a unified payment system that is well-organized, efficient, dependable, and secure. This system avoids the need for physical cash while also still satisfying all payment and identification requirements, a …

Robust Sensor Fault Estimation For Control Systems Affected By Friction Force, Ruaa Hameed Ahmed, Montadher Sami

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The paper presents an observer-based estimation of sensor fault for control systems affected by friction force. In such systems, the non-linearity of friction force leads to deteriorating sensor fault estimation capability of the observer. Hence, the challenge is to design an observer capable of attaining robust sensor fault estimation while avoiding the effects of friction. To overcome the highlighted challenge, an Unknown Input Observer (UIO) is designed to decouple the effects of friction as well as to estimate the state and sensor fault.The benefit of proposing UIO is to guarantee robust sensor fault estimation despite the highly non-linear disturbance in …

Rcae_Bfv: Retrieve Encrypted Images Using Convolution Autoencoder And Bfv, Emad M. Alsaedi, Alaa Kadhim

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Content-Based Image Retrieval (CBIR) is an actual application in computer vision, which retrieves similar images from a database. Deep Learning (DL) is essential in many applications, including image retrieval applications. However, encryption techniques are used to protect data privacy because these data are vulnerable to being viewed by unauthorized parties while being transmitted over unsecured channels. This paper includes two parts for images retrieval. In the first part, features of all images of a Canadian Institute for Advanced Research CIFAR-10 dataset were extracted and stored on the Server-side. In the second part, the Brakerski/Fan-Vercauteren (BFV) homomorphic encryption scheme method for …

Intelligent Parameter Tuning Using Deep Q-Network In Adaptive Queue Management Systems, Ayman Basheer Yousif, Hassan Jaleel, Ghaida Muttasher

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Network traffic has risen in recent years to the point that it is obviously and astonishingly in 2020, with the increase predicted to double in the following days. Up to 23 Teraa bit every month is an incredible amount. The Active Queue Management (AQM) algorithm is one of the most significant study areas in network congestion control; nevertheless, new self-learning network management algorithms are needed on nodes to cope with the huge quantity of traffic and minimize queuing latency, used reinforcement learning for automatic adaptive parameter with the AQM algorithm for effective network management, and present a novel AQM algorithm …

Hybridized Dimensionality Reduction Method For Machine Learning Based Web Pages Classification, Thabit Sulaiman Sabbah

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Feature space high dimensionality is a well-known problem in text classification and web mining domains, it is caused mainly by the large number of vocabularies contained within web documents. Several methods were applied to select the most useful and important features over the years; however, the performance of such methods is still improvable from different aspects such as the computational cost and accuracy. This research presents an enhanced cosine similarity-based hybridization of two efficient feature selection methods for higher classification performance. The reduced feature sets are generated using the Random Projection (RP) and the Principal Component Analysis (PCA) methods, individually, …

Unmasking Deepfakes Based On Deep Learning And Noise Residuals, Wildan J. Hadi, Suhad M., Ayad R. Abbas

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The main reason for the emergence of a deepfake (deep learning and fake) term is the eVolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light ConVolution …

Automatic Quality Of Experience Measuring For Video Conference In Real-Time, Roaa E. Alhassany, Rana F.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

In recent years, especially with COVID-19, video conference applications have become very important. Millions of peoples around the world have become to communicate with each other through using video conference applications. The most critical factor in the performance success of video conference applications is the user's perception of the quality of the experience. In this work, an Extreme Learning Machine (ELM) model was proposed for predicting video quality of experience. The proposed system extracts several features from videos that have a significant impact on the quality of the experience. The model performance was validated with unseen data. Spearman’s Rank Correlation …

Optimizing Artificial Neural Networks Using Levychaotic Mapping On Wolf Pack Optimization Algorithm For Detect Driving Sleepiness, Sarah Saadoon Jasim, Alia Karim, Scott Turner

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Artificial Neural Networks (ANNs) are utilized to solve a variety of problems in many domains. In this type of network, training and selecting parameters that define networks architecture play an important role in enhancing the accuracy of the network's output; Therefore, Prior to training, those parameters must be optimized. Grey Wolf Optimizer (GWO) has been considered one of the efficient developed approaches in the Swarm Intelligence area that is used to solve real-world optimization problems. However, GWO still faces a problem of the slump in local optimums in some places due to insufficient diversity. This paper proposes a novel algorithm …

The Techniques Of Based Internet Key Exchange (Ike) Protocol To Secure Key Negotiation, Zainab Kareem Mahyob, Raheem Abdulsahib, Suhiar Mohammed Zeki

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The Internet is a massive network that connects millions of users from all over the world and the data transmitted via it needs great protection, especially since that are in the age of big data. To solve part of this problem, IPsec was utilized, which is a set of protocols necessary to offer security to units of the Internet in general and the IP layer in particular. It is mostly based on major exchange protocols. The most frequent mechanism for transferring key materials and establishing security linkages between two entities is Internet Key Exchange (IKE). In the present work, it …

A Convolutional Neural Network For Detecting Covid-19 From Chest X-Ray Images, Basma Wael Abdullah, Hanaa Mohsin

Iraqi Journal of Computers, Communications, Control and Systems Engineering

since the global pandemic of COVID-19 has spread out, the use of Artificial Intelligence to analyze Chest X-Ray (CXR) image for COVID-19 diagnosis and patient treatment is becoming more important. This research hypothesized that using COVID19 radiographic changes in the X-Ray images. Artificial Intelligence (AI) systems may extract certain graphical elements regarding COVID-19 and offer a clinical diagnosis ahead of pathogenic test; therefore, saving vital time for disease prevention. Employing 2614 CXR radiographs from Kaggle data collection of verified COVID-19 cases and healthy persons, a new ConVolutional Neural Network (CNN) model that is inspired by the Xception architecture was presented …