Showing papers by "University of North Carolina at Charlotte published in 2014"

Energy applications of ionic liquids

Abstract: Ionic liquids offer a unique suite of properties that make them important candidates for a number of energy related applications. Cation–anion combinations that exhibit low volatility coupled with high electrochemical and thermal stability, as well as ionic conductivity, create the possibility of designing ideal electrolytes for batteries, super-capacitors, actuators, dye sensitised solar cells and thermo-electrochemical cells. In the field of water splitting to produce hydrogen they have been used to synthesize some of the best performing water oxidation catalysts and some members of the protic ionic liquid family co-catalyse an unusual, very high energy efficiency water oxidation process. As fuel cell electrolytes, the high proton conductivity of some of the protic ionic liquid family offers the potential of fuel cells operating in the optimum temperature region above 100 °C. Beyond electrochemical applications, the low vapour pressure of these liquids, along with their ability to offer tuneable functionality, also makes them ideal as CO2 absorbents for post-combustion CO2 capture. Similarly, the tuneable phase properties of the many members of this large family of salts are also allowing the creation of phase-change thermal energy storage materials having melting points tuned to the application. This perspective article provides an overview of these developing energy related applications of ionic liquids and offers some thoughts on the emerging challenges and opportunities.

The importance of the viable but non-culturable state in human bacterial pathogens.

Abstract: Many bacterial species have been found to exist in a viable but non-culturable (VBNC) state since its discovery in 1982. VBNC cells are characterized by a loss of culturability on routine agar, which impairs their detection by conventional plate count techniques. This leads to an underestimation of total viable cells in environmental or clinical samples, and thus poses a risk to public health. In this review, we present recent findings on the VBNC state of human bacterial pathogens. The characteristics of VBNC cells, including the similarities and differences to viable, culturable cells and dead cells, and different detection methods are discussed. Exposure to various stresses can induce the VBNC state, and VBNC cells may be resuscitated back to culturable cells under suitable stimuli. The conditions that trigger the induction of the VBNC state and resuscitation from it are summarized and the mechanisms underlying these two processes are discussed. Last but not least, the significance of VBNC cells and their potential influence on human health are also reviewed.

Principal component analysis: a method for determining the essential dynamics of proteins.

Abstract: It has become commonplace to employ principal component analysis to reveal the most important motions in proteins. This method is more commonly known by its acronym, PCA. While most popular molecular dynamics packages inevitably provide PCA tools to analyze protein trajectories, researchers often make inferences of their results without having insight into how to make interpretations, and they are often unaware of limitations and generalizations of such analysis. Here we review best practices for applying standard PCA, describe useful variants, discuss why one may wish to make comparison studies, and describe a set of metrics that make comparisons possible. In practice, one will be forced to make inferences about the essential dynamics of a protein without having the desired amount of samples. Therefore, considerable time is spent on describing how to judge the significance of results, highlighting pitfalls. The topic of PCA is reviewed from the perspective of many practical considerations, and useful recipes are provided.

Time series classification using multi-channels deep convolutional neural networks

Abstract: Time series (particularly multivariate) classification has drawn a lot of attention in the literature because of its broad applications for different domains, such as health informatics and bioinformatics. Thus, many algorithms have been developed for this task. Among them, nearest neighbor classification (particularly 1-NN) combined with Dynamic Time Warping (DTW) achieves the state of the art performance. However, when data set grows larger, the time consumption of 1-NN with DTW grows linearly. Compared to 1-NN with DTW, the traditional feature-based classification methods are usually more efficient but less effective since their performance is usually dependent on the quality of hand-crafted features. To that end, in this paper, we explore the feature learning techniques to improve the performance of traditional feature-based approaches. Specifically, we propose a novel deep learning framework for multivariate time series classification. We conduct two groups of experiments on real-world data sets from different application domains. The final results show that our model is not only more efficient than the state of the art but also competitive in accuracy. It also demonstrates that feature learning is worth to investigate for time series classification.

Gender and perceptions of leadership effectiveness: a meta-analysis of contextual moderators

Abstract: Despite evidence that men are typically perceived as more appropriate and effective than women in leadership positions, a recent debate has emerged in the popular press and academic literature over the potential existence of a female leadership advantage. This meta-analysis addresses this debate by quantitatively summarizing gender differences in perceptions of leadership effectiveness across 99 independent samples from 95 studies. Results show that when all leadership contexts are considered, men and women do not differ in perceived leadership effectiveness. Yet, when other-ratings only are examined, women are rated as significantly more effective than men. In contrast, when self-ratings only are examined, men rate themselves as significantly more effective than women rate themselves. Additionally, this synthesis examines the influence of contextual moderators developed from role congruity theory (Eagly & Karau, 2002). Our findings help to extend role congruity theory by demonstrating how it can be supplemented based on other theories in the literature, as well as how the theory can be applied to both female and male leaders. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Surface-Energy-Assisted Perfect Transfer of Centimeter-Scale Monolayer and Few-Layer MoS2 Films onto Arbitrary Substrates

Abstract: The transfer of synthesized 2D MoS2 films is important for fundamental and applied research. However, it is problematic to translate the well-established transfer processes for graphene to MoS2 due to different growth mechanisms and surface properties. Here we demonstrate a surface-energy-assisted process that can perfectly transfer centimeter-scale monolayer and few-layer MoS2 films from original growth substrates onto arbitrary substrates with no observable wrinkles, cracks, and polymer residues. The unique strategies used in this process include leveraging the penetration of water between hydrophobic MoS2 films and hydrophilic growth substrates to lift off the films and dry transferring the film after the lift off. This is in stark contrast with the previous transfer process for synthesized MoS2 films, which explores the etching of the growth substrate by hot base solutions to lift off the films. Our transfer process can effectively eliminate the mechanical force caused by bubble generations, the attac...

The environmental controls that govern the end product of bacterial nitrate respiration

Abstract: In the biogeochemical nitrogen cycle, microbial respiration processes compete for nitrate as an electron acceptor. Denitrification converts nitrate into nitrogenous gas and thus removes fixed nitrogen from the biosphere, whereas ammonification converts nitrate into ammonium, which is directly reusable by primary producers. We combined multiple parallel long-term incubations of marine microbial nitrate-respiring communities with isotope labeling and metagenomics to unravel how specific environmental conditions select for either process. Microbial generation time, supply of nitrite relative to nitrate, and the carbon/nitrogen ratio were identified as key environmental controls that determine whether nitrite will be reduced to nitrogenous gas or ammonium. Our results define the microbial ecophysiology of a biogeochemical feedback loop that is key to global change, eutrophication, and wastewater treatment.

Microbial genomic analysis reveals the essential role of inflammation in bacteria-induced colorectal cancer

Abstract: Enterobacteria, especially Escherichia coli, are abundant in patients with inflammatory bowel disease or colorectal cancer (CRC). However, it is unclear whether cancer is promoted by inflammation-induced expansion of E. coli and/or changes in expression of specific microbial genes. Here we use longitudinal (2, 12 and 20 weeks) 16S rRNA sequencing of luminal microbiota from ex-germ-free mice to show that inflamed Il10(-/-) mice maintain a higher abundance of Enterobacteriaceae than healthy wild-type mice. Experiments with mono-colonized Il10(-/-) mice reveal that host inflammation is necessary for E. coli cancer-promoting activity. RNA-sequence analysis indicates significant changes in E. coli gene catalogue in Il10(-/-) mice, with changes mostly driven by adaptation to the intestinal environment. Expression of specific genes present in the tumour-promoting E. coli pks island are modulated by inflammation/CRC development. Thus, progression of inflammation in Il10(-/-) mice supports Enterobacteriaceae and alters a small subset of microbial genes important for tumour development.

Selection criteria for patients with chronic ankle instability in controlled research: a position statement of the International Ankle Consortium

Abstract: While research on chronic ankle instability (CAI) and awareness of its impact on society and health care systems has grown substantially in the last 2 decades, the inconsistency in participant or patient selection criteria across studies presents a potential obstacle to addressing the problem properly. This major gap within the literature limits the ability to generalize this evidence to the target patient population. Therefore, there is a need to provide standards for patient or participant selection criteria in research focused on CAI with justifications using the best available evidence. The International Ankle Consortium provides this position paper to present and discuss an endorsed set of selection criteria for patients with CAI based on the best available evidence to be used in future research and study designs. These recommendations will enhance the validity of research conducted in this clinical population with the end goal of bringing the research evidence to the clinician and patient.

The effects of tai chi on depression, anxiety, and psychological well-being: a systematic review and meta-analysis.

Abstract: Tai chi, also called taiji or tai chi chuan, is a form of mind–body exercise that originated from China. It combines Chinese martial arts and meditative movements that promote balance and healing of the mind and body, involving a series of slowly performed, dance-like postures that flow into one another. As it comprises mental concentration, physical balance, muscle relaxation, and relaxed breathing, tai chi shows great potential for becoming widely integrated into the prevention and rehabilitation of a number of medical and psychological conditions. A growing body of clinical research has begun to evaluate the efficacy of tai chi as a therapy for a variety of health issues. A systematic review and meta-analysis were carried out on randomized controlled trials (RCTs) and quasi-experimental (Q-E) trials that studied the effects of tai chi on psychological well-being. Drawn from English and Chinese databases, 37 RCTs and 5 Q-E studies published up to May 31, 2013 were included in the systematic review. The methodological quality of the RCTs was evaluated based on the following criteria: adequate sequence generation, allocation concealment, blinding, completeness of outcome data, selective reporting, and other potential biases. Statistical analyses were performed using Review Manager version 5.0. The studies in this review demonstrated that tai chi interventions have beneficial effects for various populations on a range of psychological well-being measures, including depression, anxiety, general stress management, and exercise self-efficacy. Meta-analysis was performed on three RCTs that used depression as an outcome measure (ES = −5.97; 95 % CI −7.06 to −4.87), with I 2 = 0 %. In spite of the positive outcomes, the studies to date generally had significant methodological limitations. More RCTs with rigorous research design are needed to establish the efficacy of tai chi in improving psychological well-being and its potential to be used in interventions for populations with various clinical conditions.

Quantifying the Creativity Support of Digital Tools through the Creativity Support Index

Abstract: Creativity support tools help people engage creatively with the world, but measuring how well a tool supports creativity is challenging since creativity is ill-defined. To this end, we developed the Creativity Support Index (CSI), which is a psychometric survey designed for evaluating the ability of a creativity support tool to assist a user engaged in creative work. The CSI measures six dimensions of creativity support: Exploration, Expressiveness, Immersion, Enjoyment, Results Worth Effort, and Collaboration. The CSI allows researchers to understand not just how well a tool supports creative work overall, but what aspects of creativity support may need attention. In this article, we present the CSI, along with scenarios for how it can be deployed in a variety of HCI research settings and how the CSI scores can help target design improvements. We also present the iterative, rigorous development and validation process used to create the CSI.

Demographic Patterns of Cumulative Arrest Prevalence by Ages 18 and 23

Abstract: In this study, we examine race, sex, and self-reported arrest histories (excluding arrests for minor traffic violations) from the 1997 National Longitudinal Survey of Youth (NLSY; N = 7,335) for the period 1997 through 2008 covering cumulative arrest histories through ages 18 and 23. The analysis produces three key findings: (1) males have higher cumulative prevalence of arrest than females; and (2) there are important race differences in the probability of arrest for males but not for females. Assuming the missing cases are missing at random, about 30% of black males have experienced at least one arrest by age 18 (vs. about 22% for white males); by age 23 about 49% of black males have been arrested (vs. about 38% for white males). Earlier research using the NLSY showed that the risk of arrest by age 23 was 30%, with nonresponse bounds [25.3%, 41.4%]. This study indicates that the risk of arrest is not evenly distributed across the population. Future research should focus on the identification and management of collateral risks that often accompany arrest experiences.

School Segregation, Educational Attainment and Crime Evidence from the end of busing in Charlotte-Mecklenburg

Abstract: We study the end of race-based busing in Charlotte-Mecklenburg schools (CMS). In 2001, school boundaries in CMS were redrawn dramatically, and half of students received a new assignment. Using addresses measured prior to the policy change, we compare students in the same neighborhood that lived on opposite sides of a newly drawn boundary. We find that both white and minority students score lower on high school exams when they are assigned to schools with more minority students. We also find decreases in high school graduation and four-year college attendance for whites and large increases in crime for minority males. We conclude that the end of race-based busing widened racial inequality, despite efforts by CMS to mitigate the effect of segregation through compensatory resource allocation. JEL Codes: I20, I24.

The Emergence, Development, and Future of the Framing Perspective: 25+ Years Since "Frame Alignment"

Abstract: It has been more than twenty-five years since publication of David Snow, Burke Rochford, Steven Worden, and Robert Benford's article, "Frame Alignment Processes, Micromobilization, and Movement Participation" in the American Sociological Review (1986). Here we consider the conceptual and empirical origins of the framing perspective, how its introduction fundamentally altered and continues to influence the study of social movements, and where scholarly research on social movement framing is still needed.

Partially coherent beam propagation in atmospheric turbulence [invited].

Abstract: Partially coherent beams hold much promise in free-space optical communications for their resistance to the deleterious effects of atmospheric turbulence. We describe the basic theoretical and computational tools used to investigate these effects, and review the research to date.

Mobile app recommendations with security and privacy awareness

Abstract: With the rapid prevalence of smart mobile devices, the number of mobile Apps available has exploded over the past few years. To facilitate the choice of mobile Apps, existing mobile App recommender systems typically recommend popular mobile Apps to mobile users. However, mobile Apps are highly varied and often poorly understood, particularly for their activities and functions related to privacy and security. Therefore, more and more mobile users are reluctant to adopt mobile Apps due to the risk of privacy invasion and other security concerns. To fill this crucial void, in this paper, we propose to develop a mobile App recommender system with privacy and security awareness. The design goal is to equip the recommender system with the functionality which allows to automatically detect and evaluate the security risk of mobile Apps. Then, the recommender system can provide App recommendations by considering both the Apps' popularity and the users' security preferences. Specifically, a mobile App can lead to security risk because insecure data access permissions have been implemented in this App. Therefore, we first develop the techniques to automatically detect the potential security risk for each mobile App by exploiting the requested permissions. Then, we propose a flexible approach based on modern portfolio theory for recommending Apps by striking a balance between the Apps' popularity and the users' security concerns, and build an App hash tree to efficiently recommend Apps. Finally, we evaluate our approach with extensive experiments on a large-scale data set collected from Google Play. The experimental results clearly validate the effectiveness of our approach.

Tumor-induced STAT3 activation in monocytic myeloid-derived suppressor cells enhances stemness and mesenchymal properties in human pancreatic cancer

Abstract: Pancreatic cancer (PC) mobilizes myeloid cells from the bone marrow to the tumor where they promote tumor growth and proliferation. Cancer stem cells (CSCs) are a population of tumor cells that are responsible for tumor initiation. Aldehyde dehydrogenase-1 activity in PC identifies CSCs, and its activity has been correlated with poor overall prognosis in human PC. Myeloid cells have been shown to impact tumor stemness, but the impact of immunosuppressive tumor-infiltrating granulocytic and monocytic myeloid-derived suppressor cells (Mo-MDSC) on ALDH1Bright CSCs and epithelial to mesenchymal transition is not well understood. In this study, we demonstrate that Mo-MDSC (CD11b+/Gr1+/Ly6G−/Ly6Chi) significantly increase the frequency of ALDH1Bright CSCs in a mouse model of PC. Additionally, there was significant upregulation of genes associated with epithelial to mesenchymal transition. We also found that human PC converts CD14+ peripheral blood monocytes into Mo-MDSC (CD14+/HLA-DRlow/−) in vitro, and this transformation is dependent on the activation of the STAT3 pathway. In turn, these Mo-MDSC increase the frequency of ALDH1Bright CSCs and promote mesenchymal features of tumor cells. Finally, blockade of STAT3 activation reversed the increase in ALDH1Bright CSCs. These data suggest that the PC tumor microenvironment transforms monocytes to Mo-MDSC by STAT3 activation, and these cells increase the frequency of ALDH1Bright CSCs. Therefore, targeting STAT3 activation may be an effective therapeutic strategy in targeting CSCs in PC.

BodyBeat: a mobile system for sensing non-speech body sounds

Abstract: In this paper, we propose BodyBeat, a novel mobile sensing system for capturing and recognizing a diverse range of non-speech body sounds in real-life scenarios. Non-speech body sounds, such as sounds of food intake, breath, laughter, and cough contain invaluable information about our dietary behavior, respiratory physiology, and affect. The BodyBeat mobile sensing system consists of a custom-built piezoelectric microphone and a distributed computational framework that utilizes an ARM microcontroller and an Android smartphone. The custom-built microphone is designed to capture subtle body vibrations directly from the body surface without being perturbed by external sounds. The microphone is attached to a 3D printed neckpiece with a suspension mechanism. The ARM embedded system and the Android smartphone process the acoustic signal from the microphone and identify non-speech body sounds. We have extensively evaluated the BodyBeat mobile sensing system. Our results show that BodyBeat outperforms other existing solutions in capturing and recognizing different types of important non-speech body sounds.

Ownership structure and innovation: An emerging market perspective

Abstract: Considerable attention has been focused on the ways in which emerging market firms can obtain and mobilize the knowledge and resources required for innovation. Innovation is a particular challenge in emerging markets because of inadequate external institutions. In this study, we focus on the importance of ownership structure, and in particular on ownership type diversity and ownership concentration. Using transaction cost and agency theories embedded in an emerging market context, we argue that ownership structure provides an important mechanism by which firms can assemble and direct the resources necessary for innovation in the context of inadequate external institutions. Specifically, we hypothesize that ownership type diversity improves innovation performance and that increasing ownership concentration has the same effect, but only up to a point. Using a panel dataset of 487 and 475 Chinese listed companies during 2004–2005 and 2005–2006 respectively, we find supportive empirical evidence for our hypotheses. Our findings also suggest that ownership type diversity is a more important factor in explaining innovation performance than ownership concentration, although most of the extant literature focuses on the latter.

Assessing Teamwork Skills for Assurance of Learning Using CATME Team Tools

Abstract: Colleges of business must meet assurance of learning requirements to gain or maintain AACSB accreditation under the new standards adopted April 8, 2013. Team skills are among the most important ski...

Functional interplay between ATM/ATR-mediated DNA damage response and DNA repair pathways in oxidative stress

Abstract: To maintain genome stability, cells have evolved various DNA repair pathways to deal with oxidative DNA damage. DNA damage response (DDR) pathways, including ATM-Chk2 and ATR-Chk1 checkpoints, are also activated in oxidative stress to coordinate DNA repair, cell cycle progression, transcription, apoptosis, and senescence. Several studies demonstrate that DDR pathways can regulate DNA repair pathways. On the other hand, accumulating evidence suggests that DNA repair pathways may modulate DDR pathway activation as well. In this review, we summarize our current understanding of how various DNA repair and DDR pathways are activated in response to oxidative DNA damage primarily from studies in eukaryotes. In particular, we analyze the functional interplay between DNA repair and DDR pathways in oxidative stress. A better understanding of cellular response to oxidative stress may provide novel avenues of treating human diseases, such as cancer and neurodegenerative disorders.

A Network Based Method for Analysis of lncRNA-Disease Associations and Prediction of lncRNAs Implicated in Diseases

Abstract: Increasing evidence has indicated that long non-coding RNAs (lncRNAs) are implicated in and associated with many complex human diseases. Despite of the accumulation of lncRNA-disease associations, only a few studies had studied the roles of these associations in pathogenesis. In this paper, we investigated lncRNA-disease associations from a network view to understand the contribution of these lncRNAs to complex diseases. Specifically, we studied both the properties of the diseases in which the lncRNAs were implicated, and that of the lncRNAs associated with complex diseases. Regarding the fact that protein coding genes and lncRNAs are involved in human diseases, we constructed a coding-non-coding gene-disease bipartite network based on known associations between diseases and disease-causing genes. We then applied a propagation algorithm to uncover the hidden lncRNA-disease associations in this network. The algorithm was evaluated by leave-one-out cross validation on 103 diseases in which at least two genes were known to be involved, and achieved an AUC of 0.7881. Our algorithm successfully predicted 768 potential lncRNA-disease associations between 66 lncRNAs and 193 diseases. Furthermore, our results for Alzheimer's disease, pancreatic cancer, and gastric cancer were verified by other independent studies.

Achieving Differential Privacy of Data Disclosure in the Smart Grid

Abstract: The smart grid introduces new privacy implications to individuals and their family due to the fine-grained usage data collection. For example, smart metering data could reveal highly accurate real-time home appliance energy load, which may be used to infer the human activities inside the houses. One effective way to hide actual appliance loads from the outsiders is Battery-based Load Hiding (BLH), in which a battery is installed for each household and smartly controlled to store and supply power to the appliances. Even though such technique has been demonstrated useful and can prevent certain types of attacks, none of existing BLH works can provide probably privacy-preserving mechanisms. In this paper, we investigate the privacy of smart meters via differential privacy. We first analyze the current existing BLH methods and show that they cannot guarantee differential privacy in the BLH problem. We then propose a novel randomized BLH algorithm which successfully assures differential privacy, and further propose the Multitasking-BLH-Exp3 algorithm which adaptively updates the BLH algorithm based on the context and the constraints. Results from extensive simulations show the efficiency and effectiveness of the proposed method over existing BLH methods. Index Terms—Smart Grid, Smart Meter, Privacy, Differential Privacy, Data Disclosure

Financial Decision Making in Family Firms: An Adaptation of the Theory of Planned Behavior

Abstract: Adapting the theory of planned behavior to the area of financial choices in family firms, we argue that these choices in family firms are largely affected by family norms, attitude, perceived behavioral control, and behavioral intentions. A time-lagged sample, estimated via structural equation modeling of 118 German family firms, supports a behavioral approach to the study of financing decisions. Specifically, we show that family norms and attitude toward external debt and external equity affect behavioral intention to use the respective financing choices, which in turn affects financing behavior. Perceived behavioral control, however, was shown to negatively affect behavioral intentions to use external equity and was positively related to the use of internal funds. Implications of these capital structure decisions and ideas for future research are discussed.

A Cocktail Approach for Travel Package Recommendation

Abstract: Recent years have witnessed an increased interest in recommender systems. Despite significant progress in this field, there still remain numerous avenues to explore. Indeed, this paper provides a study of exploiting online travel information for personalized travel package recommendation. A critical challenge along this line is to address the unique characteristics of travel data, which distinguish travel packages from traditional items for recommendation. To that end, in this paper, we first analyze the characteristics of the existing travel packages and develop a tourist-area-season topic (TAST) model. This TAST model can represent travel packages and tourists by different topic distributions, where the topic extraction is conditioned on both the tourists and the intrinsic features (i.e., locations, travel seasons) of the landscapes. Then, based on this topic model representation, we propose a cocktail approach to generate the lists for personalized travel package recommendation. Furthermore, we extend the TAST model to the tourist-relation-area-season topic (TRAST) model for capturing the latent relationships among the tourists in each travel group. Finally, we evaluate the TAST model, the TRAST model, and the cocktail recommendation approach on the real-world travel package data. Experimental results show that the TAST model can effectively capture the unique characteristics of the travel data and the cocktail approach is, thus, much more effective than traditional recommendation techniques for travel package recommendation. Also, by considering tourist relationships, the TRAST model can be used as an effective assessment for travel group formation.

Public Perceptions of the Legitimacy of the Law and Legal Authorities: Evidence from the Caribbean

Abstract: Research on procedural justice and legitimacy has expanded greatly across the social sciences in recent years. The process-based model of regulation, which links people's assessments of procedural justice and legitimacy to their compliance with the law and legal authorities, has become particularly influential in criminology and sociolegal studies. A review of the previous research on perceived legitimacy highlights two important features. First, legitimacy has been conceptualized and measured in many different ways. Second, most of the research on legitimacy has focused on only a handful of developed nations. Using survey data from Trinidad and Tobago, this article examines the conceptualization and measurement of the perceived legitimacy of the law and legal authorities. The findings indicate that some of the prominent conceptual and measurement models used in previous research are not empirically valid in the Trinidadian context. The implications of the results for conceptualization, theory, and future research are discussed.With roots in philosophy, political theory, and social psychology, the idea of legitimacy occupies an important role in scholarship across the social sciences, including psychology (e.g., Lind and Tyler 1988), organizational theory (e.g., Elsbach 2001), political science (e.g., Easton 1979), and criminology and sociolegal studies (e.g., Smith 2007; Sunshine and Tyler 2003; Tyler 2006; Tyler and Huo 2002). Subjective assessments of the legitimacy of authority, whether in the form of individuals or institutions, are thought to influence a wide range of human behaviors, from child obedience and worker productivity, to decisions about whether to obey the law or comply with legal authorities. Legitimacy assessments play an increasingly important role in a diverse scholarly literature on how people think about and respond to authority.In criminology and sociolegal studies, a rapidly developing body of scholarship focuses on the antecedents and consequences of the perceived legitimacy of law and legal authorities. The most well-known causal model linking perceived legitimacy to its antecedents and consequences is Tyler's process-based model of regulation (e.g., Sunshine and Tyler 2003; Tyler 2006; Tyler and Huo 2002). In this model, perceived legitimacy mediates the relationship between people's perceptions of the procedural justice of legal authorities and their decisions about whether to obey the law or comply with the directives of legal authorities. According to this perspective, people assess the procedural justice employed by legal authorities like police officers, prosecutors, judges, and prison guards. These procedural justice judgments have a powerful influence on their more general assessments of the legitimacy of the law and legal institutions, which in turn influence people's willingness to obey the law and comply with the directives of legal authorities. Thus, according to the process-based model, when legal authorities treat people in a procedurally just manner, their behaviors promote the legitimacy of law and legal institutions and cultivate compliance and other beneficial outcomes like cooperation and support (Sunshine and Tyler 2003; Tankebe 2009; Tyler 2006; Tyler and Fagan 2008; Tyler and Huo 2002).The process-based model of regulation is appealing for many reasons. From a theoretical perspective, it proposes an elegant set of causal relationships between procedural justice, legitimacy, and compliance with the law and legal authorities. Moreover, it serves as a compelling counterweight to deterrence, the most common or instinctual explanation for why people obey the law (Tyler 2006). The process-based model is also inherently testable or refutable, thus satisfying a key condition for good scientific theory (Blumer 1954). The model is also appealing from a philosophical perspective because it suggests that authority figures should treat people fairly, not only because it can satisfy the Kantian imperative to do the right thing, but because it also satisfies utilitarian objectives by generating socially meaningful outcomes. …