Showing papers by "Wichita State University published in 2015"

The beetle tree of life reveals that Coleoptera survived end‐Permian mass extinction to diversify during the Cretaceous terrestrial revolution

Abstract: © 2015 The Authors. Systematic Entomology published by John Wiley & Sons Ltd on behalf of Royal Entomological Society This is an open access article under the terms of the Creative Commons AttributionߚNonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Realizing underwater communication through magnetic induction

Abstract: The majority of the work on underwater communication has mainly been based on acoustic communication. Acoustic communication faces many known problems, such as high propagation delays, very low data rates, and highly environment-dependent channel behavior. In this article, to address these shortcomings, magnetic induction is introduced as a possible communication paradigm for underwater applications. Accordingly, all research challenges in this regard are explained. Fundamentally different from the conventional underwater communication paradigm, which relies on EM, acoustic, or optical waves, the underwater MI communications rely on the time varying magnetic field to covey information between the transmitting and receiving parties. MI-based underwater communications exhibit several unique and promising features such as negligible signal propagation delay, predictable and constant channel behavior, sufficiently long communication range with high bandwidth, as well as silent and stealth underwater operations. To fully utilize the promising features of underwater MI-based communications, this article introduces the fundamentals of underwater MI communications, including the MI channel models, MI networking protocols design, and MI-based underwater localization.

The contextualized self: how team-member exchange leads to coworker identification and helping OCB

Abstract: This article develops the argument that team–member exchange (TMX) relationships operate at both between- and within-group levels of analysis to influence an employee’s sense of identification with coworkers in the group and their helping organizational citizenship behavior (OCB) directed at coworkers. Specifically, we propose that relatively higher quality TMX relationships of an employee as compared with other members of the group influence an employee’s sense of positive uniqueness, whereas higher average level of TMX quality in the group creates a greater sense of belonging. Multilevel modeling analysis of field data from 236 bank managers and their subordinates supports the hypotheses and demonstrates 3 key findings. First, team members identify more with their coworkers when they have high relative TMX quality compared with other group members and are also embedded in groups with higher average TMX. Second, identification with coworkers is positively related to helping OCB directed toward team members. Finally, identification with coworkers mediates the interactive effect of relative TMX quality and group average TMX quality on helping. When TMX group relations allow individuals to feel a valued part of the group, but still unique, they engage in higher levels of helping. Overall moderated mediation analysis demonstrates that the mediated relationship linking relative TMX quality with helping OCB via identification with coworkers is stronger when group average TMX is high, but not present when group average TMX is low. We discuss theoretical and practical implications and recommend future research on multilevel conceptualizations of TMX.

Thermal, Electrical and Surface Hydrophobic Properties of Electrospun Polyacrylonitrile Nanofibers for Structural Health Monitoring.

Abstract: This paper presents an idea of using carbonized electrospun Polyacrylonitrile (PAN) fibers as a sensor material in a structural health monitoring (SHM) system. The electrospun PAN fibers are lightweight, less costly and do not interfere with the functioning of infrastructure. This study deals with the fabrication of PAN-based nanofibers via electrospinning followed by stabilization and carbonization in order to remove all non-carbonaceous material and ensure pure carbon fibers as the resulting material. Electrochemical impedance spectroscopy was used to determine the ionic conductivity of PAN fibers. The X-ray diffraction study showed that the repeated peaks near 42° on the activated nanofiber film were α and β phases, respectively, with crystalline forms. Contact angle, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FTIR) were also employed to examine the surface, thermal and chemical properties of the carbonized electrospun PAN fibers. The test results indicated that the carbonized PAN nanofibers have superior physical properties, which may be useful for structural health monitoring (SHM) applications in different industries.

A stochastic multi-criteria decision analysis for sustainable biomass crop selection

Abstract: We propose a stochastic analytical hierarchy process (SAHP) method.Sustainable biomass crop selection has economic, environmental, and social dimensions.Switchgrass is found to be the most sustainable crop type for biofuel production.Wheat and corn get high scores if economic factor is emphasized in decision making.The proposed SAHP model can utilize imprecise expert opinions in decision making. Selecting the most sustainable biomass crop type for biofuel production is a multi-criteria decision-making (MCDM) problem involving various conflicting criteria. In this paper, we propose a unique stochastic analytical hierarchy process (AHP) that can handle uncertain information and identify weights of criteria in the MCDM problem. By utilizing the beta distribution and approximating its median, we convert various types of expert evaluations including imprecise values into crisp values. We ensure consistency in each evaluation matrix before aggregating expert judgments. We then demonstrate use of the model by applying it to sustainable biomass crop selection. In order to define a comprehensive list of the selection criteria, we utilize the existing literature and opinions of experts including farmers, government specialists from the U.S. Department of Agriculture (USDA), and faculty members in the areas of biomass and bioenergy. The evaluation model includes three main sustainability criteria defined as economic, environmental, and social aspects associated with a total of 16 sub-criteria. We apply the proposed model to biomass alternatives including switchgrass, Miscanthus, sugarcane, corn, and wheat in Kansas. Results show the weights of economic, environmental, and social aspects to be 0.59, 0.26, and 0.15, respectively. The sensitivity analysis indicates that the score of switchgrass increases if environmental criteria are emphasized. On the other hand, wheat and corn become more favorable than other alternatives if priority is given to economic factors. The most sustainable biomass sources in different regions can be determined by applying the presented selection hierarchy. The proposed stochastic AHP methodology can also be utilized for other complex multi-criteria decision-making problems with uncertain information and multiple stakeholders.

Smartphone text input method performance, usability, and preference with younger and older adults

Abstract: OBJECTIVE: User performance, perceived usability, and preference for five smartphone text input methods were compared with younger and older novice adults. BACKGROUND: Smartphones are used for a variety of functions other than phone calls, including text messaging, e-mail, and web browsing. Research comparing performance with methods of text input on smartphones reveals a high degree of variability in reported measures, procedures, and results. This study reports on a direct comparison of five of the most common input methods among a population of younger and older adults, who had no experience with any of the methods. METHOD: Fifty adults (25 younger, 18-35 years; 25 older, 60-84 years) completed a text entry task using five text input methods (physical Qwerty, onscreen Qwerty, tracing, handwriting, and voice). Entry and error rates, perceived usability, and preference were recorded. RESULTS: Both age groups input text equally fast using voice input, but older adults were slower than younger adults using all other methods. Both age groups had low error rates when using physical Qwerty and voice, but older adults committed more errors with the other three methods. Both younger and older adults preferred voice and physical Qwerty input to the remaining methods. Handwriting consistently performed the worst and was rated lowest by both groups. CONCLUSION: Voice and physical Qwerty input methods proved to be the most effective for both younger and older adults, and handwriting input was the least effective overall. APPLICATION: These findings have implications to the design of future smartphone text input methods and devices, particularly for older adults. Language: en

Small firm growth as a function of both learning orientation and entrepreneurial orientation

Abstract: Purpose – The purpose of this paper is to investigate the relationship between learning orientation (LO), entrepreneurial orientation (EO), and firm growth in small- and medium-sized firms (SMEs). The authors theoretically argue for a mediation effect of EO on the relationship between LO and growth. The study considered how companies that value learning enact actions to affect firm outcomes. This is particularly important for small firms that may not be capable of withstanding significant shocks in the marketplace. Design/methodology/approach – The research design employed the survey method for data gathering and resulted in 105 completed responses from CEOs/presidents of SMEs. To examine the construct validity of the measurement dimensions the authors used a multistage process. Additionally, the authors employed a competing models analytic design to determine the presence and strength of mediating effects of the EO construct. Findings – The findings empirically demonstrate the notion that firm cultural va...

Risk and protective factors for depressive symptoms among American Indian older adults: Adverse childhood experiences and social support

Abstract: Objectives: Despite efforts to promote health equity, many American Indian and Alaska Native (AI/AN) populations, including older adults, experience elevated levels of depression. Although adverse childhood experiences (ACE) and social support are well-documented risk and protective factors for depression in the general population, little is known about AI/AN populations, especially older adults. The purpose of this study was to examine factors related to depression among a sample of AI older adults in the midwest.Method: Data were collected using a self-administered survey completed by 233 AIs over the age of 50. The survey included standardized measures such as the Geriatric Depression Scale-Short Form, ACE Questionnaire, and the Multidimensional Scale of Perceived Social Support. Hierarchical multivariate regression analyses were conducted to evaluate the main hypotheses of the study.Results: Two dimensions of ACE (i.e., childhood neglect, household dysfunction) were positively associated with depressi...

Controlled Electric Vehicle Charging for Mitigating Impacts on Distribution Assets

Abstract: This paper proposes a two-step methodology for scheduling electric vehicle (EV) charging, which limits the burden on distribution and transmission assets while ensuring all the vehicles are charged. In the first step, the number of vehicles to be charged during each hour is optimized based on day-ahead requests for charging. The second step determines the maximum number of vehicles that can be charged based on operating conditions during the next hour to ensure distribution reliability requirements are met. A numerical example is given to illustrate the EV charging management scheme. This technique will limit the effects of EV charging on distribution assets.

(Smart)watch your taps: side-channel keystroke inference attacks using smartwatches

Abstract: In this paper, we investigate the feasibility of keystroke inference attacks on handheld numeric touchpads by using smartwatch motion sensors as a side-channel. The proposed attack approach employs supervised learning techniques to accurately map the uniqueness in the captured wrist movements to each individual keystroke. Experimental evaluation shows that keystroke inference using smartwatch motion sensors is not only fairly accurate, but also better than similar attacks previously demonstrated using smartphone motion sensors.

Optimization approaches to volumetric modulated arc therapy planning

Abstract: Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed.

Broad-Spectrum Inhibitors against 3C-Like Proteases of Feline Coronaviruses and Feline Caliciviruses

Abstract: Feline infectious peritonitis and virulent, systemic calicivirus infection are caused by certain types of feline coronaviruses (FCoVs) and feline caliciviruses (FCVs), respectively, and are important infectious diseases with high fatality rates in members of the Felidae family. While FCoV and FCV belong to two distinct virus families, the Coronaviridae and the Caliciviridae, respectively, they share a dependence on viral 3C-like protease (3CLpro) for their replication. Since 3CLpro is functionally and structurally conserved among these viruses and essential for viral replication, 3CLpro is considered a potential target for the design of antiviral drugs with broad-spectrum activities against these distinct and highly important viral infections. However, small-molecule inhibitors against the 3CLpro enzymes of FCoV and FCV have not been previously identified. In this study, derivatives of peptidyl compounds targeting 3CLpro were synthesized and evaluated for their activities against FCoV and FCV. The structures of compounds that showed potent dual antiviral activities with a wide margin of safety were identified and are discussed. Furthermore, the in vivo efficacy of 3CLpro inhibitors was evaluated using a mouse model of coronavirus infection. Intraperitoneal administration of two 3CLpro inhibitors in mice infected with murine hepatitis virus A59, a hepatotropic coronavirus, resulted in significant reductions in virus titers and pathological lesions in the liver compared to the findings for the controls. These results suggest that the series of 3CLpro inhibitors described here may have the potential to be further developed as therapeutic agents against these important viruses in domestic and wild cats. This study provides important insights into the structure and function relationships of 3CLpro for the design of antiviral drugs with broader antiviral activities. IMPORTANCE Feline infectious peritonitis virus (FIPV) is the leading cause of death in young cats, and virulent, systemic feline calicivirus (vs-FCV) causes a highly fatal disease in cats for which no preventive or therapeutic measure is available. The genomes of these distinct viruses, which belong to different virus families, encode a structurally and functionally conserved 3C-like protease (3CLpro) which is a potential target for broad-spectrum antiviral drug development. However, no studies have previously reported a structural platform for the design of antiviral drugs with activities against these viruses or on the efficacy of 3CLpro inhibitors against coronavirus infection in experimental animals. In this study, we explored the structure-activity relationships of the derivatives of 3CLpro inhibitors and identified inhibitors with potent dual activities against these viruses. In addition, the efficacy of the 3CLpro inhibitors was demonstrated in mice infected with a murine coronavirus. Overall, our study provides the first insight into a structural platform for anti-FIPV and anti-FCV drug development.

Distributed Cross-Layer Protocol Design for Magnetic Induction Communication in Wireless Underground Sensor Networks

Abstract: Wireless underground sensor networks (WUSNs) enable many applications such as underground pipeline monitoring, power grid maintenance, mine disaster prevention, and oil upstream monitoring among many others. While the classical electromagnetic waves do not work well in WUSNs, the magnetic induction (MI) propagation technique provides constant channel conditions via small size of antenna coils in the underground environments. In this paper, instead of adopting currently layered protocols approach, a distributed cross-layer protocol design is proposed for MI-based WUSNs. First, a detailed overview is given for different communication functionalities from physical to network layers as well as the QoS requirements of applications. Utilizing the interactions of different layer functionalities, a distributed environment-aware protocol, called DEAP, is then developed to satisfy statistical QoS guarantees and achieve both optimal energy savings and throughput gain concurrently. Simulations confirm that the proposed cross-layer protocol achieves significant energy savings, high throughput efficiency and dependable MI communication for WUSNs.

Randomized Partition Trees for Nearest Neighbor Search

Abstract: The $$k$$ k -d tree was one of the first spatial data structures proposed for nearest neighbor search. Its efficacy is diminished in high-dimensional spaces, but several variants, with randomization and overlapping cells, have proved to be successful in practice. We analyze three such schemes. We show that the probability that they fail to find the nearest neighbor, for any data set and any query point, is directly related to a simple potential function that captures the difficulty of the point configuration. We then bound this potential function in several situations of interest: when the data are drawn from a doubling measure; when the data and query distributions are identical and are supported on a set of bounded doubling dimension; and when the data are documents from a topic model.

Testing optimal body mass theory: Evidence for cost of fat in wintering birds

Abstract: Optimal body mass models for small wintering birds are central to animal ecology, and offer insights into maximizing individual fitness in a complex environment. Such models assume both costs and benefits of fat deposition, and consider how they affect winter survival probability. Hypothesized mass-dependent costs of elevated fat include increased wing load and subsequent reduced ability to avoid predators, as well as increased predator exposure while feeding to fatten. A likely benefit of winter fat is increased fasting capacity during resource shortages. Here I test optimal body mass theory by searching for both cost and benefits of winter fattening, utilizing interspecific variation in winter fat in natural populations. If increased predation risk is a mass-dependent cost of fattening, wintering birds occupying dense (closed) winter habitat offering low exposure to predators should show (1) higher fat reserves, and (2) higher wing load, than wintering birds occupying less dense (open) habitat offering ...

A framework for quantifying the magnitude and variability of community responses to global change drivers

Abstract: A major challenge in global change ecology is to predict the trajectory and magnitude of community change in response to global change drivers (GCDs). Here, we present a new framework that not only increases the predictive power of individual studies, but also allows for synthesis across GCD studies and ecosystems. First, we suggest that by quantifying community dissimilarity of replicates both among and within treatments, we can infer both the magnitude and predictability of community change, respectively. Second, we demonstrate the utility of integrating rank abundance curves with measures of community dissimilarity to understand the species-level dynamics driving community changes and propose a series of testable hypotheses linking changes in rank abundance curves with shifts in community dissimilarity. Finally, we review six case studies that demonstrate how our new conceptual framework can be applied. Overall, we present a new framework for holistically predicting community responses to GCDs that has broad applicability in this era of unprecedented global change and novel environmental conditions.