Villanova University
  • Radnor, PA, United States
Recent publications
Over the past two years, face masks have been a critical tool for preventing the spread of COVID-19. While previous studies have examined the effects of masks on speech recognition, much of this work was conducted early in the pandemic. Given that human listeners are able to adapt to a wide variety of novel contexts in speech perception, an open question concerns the extent to which listeners have adapted to masked speech during the pandemic. In order to evaluate this, we replicated Toscano and Toscano (PLOS ONE 16(2):e0246842, 2021), looking at the effects of several types of face masks on speech recognition in different levels of multi-talker babble noise. We also examined the effects of listeners’ self-reported frequency of encounters with masked speech and the effects of the implementation of public mask mandates on speech recognition. Overall, we found that listeners’ performance in the current experiment (with data collected in 2021) was similar to that of listeners in Toscano and Toscano (with data collected in 2020) and that performance did not differ based on mask experience. These findings suggest that listeners may have already adapted to masked speech by the time data were collected in 2020, are unable to adapt to masked speech, require additional context to be able to adapt, or that talkers also changed their productions over time. Implications for theories of perceptual learning in speech are discussed.
Microfinance institutions (MFIs) must balance financial and social goals. When these coopetitive goals are under threat, which goals do MFIs prefer? Based on the theory of myopic loss aversion, our study aims to assess the immediate effect of the 2016 demonetization in India on MFIs and their loan portfolio performance and on unintended social outcomes. Using the 2016 demonetization in India as a quasi-experiment, we find that MFIs had a lower 30-day and 90-day portfolio at risk (PAR) and implemented better client protection terms. In addition, demonetization had a small but positive effect on developing start-up enterprises and serving more clients below the poverty line. Last, we find that MFIs investing in female client education presented a lower PAR after demonetization. Overall, our study sheds light on the unintended consequences on MFIs as a result of the demonetization event, and it provides policy implications for MFIs.
Intelligent buildings play a fundamental role in achieving efficient energy management in the building sector in many countries worldwide. Improving energy consumption within a building can represent significant financial savings and reduce carbon emissions. However, intelligent buildings may impose additional burdens and challenges in their energy use. Wireless sensor networks are essential for the control systems of most intelligent building systems. There are still opportunities to reduce the power supplied to their sensor nodes in these networks. These nodes require power levels that range from microwatts to milliwatts. Typically, primary non-rechargeable batteries provide power to the nodes. Replacing or replenishing these batteries could become an impractical activity with detrimental environmental impacts. Energy harvesters (EHs) appear as a potential solution to this problem, as they could complement the use of batteries while extending their lifetimes at the sensor nodes. This paper provides a comprehensive review of the energy harvesting technologies currently under an experimental or development phase. Thus, one of the objectives here is to study if EHs can power by themselves or support current battery-powered sensor nodes at the building level. The environmental sources considered for harvester power extraction were mechanical motion, thermal, light, radio-frequency, and fluid flow. Also, the potential sites and building systems for extracting power through these harvesters are presented and reported. This paper includes the review of the challenges and opportunities for EHs depending on the mounting location and the particular characteristics of each EH technology. The research findings in this paper demonstrate that harvesters at the buildings can generate enough power to partially supply the power requirements for sensor nodes and even completely cover the power demands of specific operation modes.
Suppose that R (red) and B (blue) are two graphs on the same vertex set of size n, and H is some graph with a red-blue coloring of its edges. How large can R and B be if R∪B does not contain a copy of H? Call the largest such integer mex(n,H). This problem was introduced by Diwan and Mubayi, who conjectured that (except for a few specific exceptions) when H is a complete graph on k+1 vertices with any coloring of its edges mex(n,H)=ex(n,Kk+1). This conjecture generalizes Turán's theorem. Diwan and Mubayi also asked for an analogue of Erdős-Stone-Simonovits theorem in this context. We prove the following upper bound on the extremal threshold in terms of the chromatic number χ(H) and the reduced maximum matching number M(H) of H.mex(n,H)≤(1−12(χ(H)−1)−M(H)9χ(H)2)n22. M(H) is, among the set of proper χ(H)-colorings of H, the largest set of disjoint pairs of color classes where each pair is connected by edges of just a single color. The result is also proved for more than 2 colors and is tight up to the implied constant factor. We also study mex(n,H) when H is a cycle with a red-blue coloring of its edges, and we show that mex(n,H)≲12(n2), which is tight.
Fictional stories for children are often designed to teach new information such as vocabulary words and problem-solving solutions. Past work has shown that children can learn real-world information from these fictional sources, but we do not yet understand the full scope of how different variables affect this learning process. The articles in this special issue aimed to address this question, paying particular attention to the ways in which the fantastical elements that are so common in children’s media might affect their learning. In this editorial introduction, we draw out common themes from these articles and identify open questions in this field. Specifically, although there is clearly more work to be done, these articles demonstrate that fantasy can sometimes benefit children’s learning, that learning is affected by children’s prior knowledge and by how the educational information is integrated into the story, and that it is important to disentangle the type of target educational information (e.g., new facts vs. executive function strategies) from the type of fictional context used to teach it.
This conceptual study provides insight into the strategic behaviors of firms facing slow growth in times of economic stagnation. Recognizing the inevitability of periods of economic stagnation—with another downturn expected as early as 2022, we note that most industry classifications are considered mature and characterized by a few extremely large companies in each industry group. We introduce the Fortune 500 as an important cross-industry collective of these large firms and suggest that they now comprise an institutional field. This development explains their isomorphic behavior during the recession triggered by the financial crisis of 2008 as well as their subsequent motivation for change. Using the pertinent literature from institutional theory and organizational change, we posit that the appropriate firm-level response (strategic choice) during periods of slow growth is to maintain legitimacy and membership in the field by adopting a proactive approach that focuses on improving top-line growth. We synthesize frameworks found in the literature and provide a “menu” of five strategic options companies should consider to turn their firms around by redirecting growth from the short term to the long term. We discuss implications for boards and executives anticipating significant economic deceleration.
We present evidence on the effects of target firms’ accounting conservatism in a merger and acquisition transaction. Conservatism is distinct from other accounting or accrual quality constructs examined in prior work. Its unique features can lead to potential benefits for both the targets and the acquirers. The use of conservatism by targets reduces acquirers’ risks of acquiring underperforming assets or overpaying for well‐performing assets. In addition, targets’ conservatism results in greater production of verifiable information that can help the acquirers better estimate and realize synergies of the combined firm. Consistent with these arguments, we find that firms with greater accounting conservatism are more likely to receive a bid. We also find that targets’ conservatism increases the deal premium and the announcement returns of both the targets and the acquirers respectively. Overall, these results indicate that conservatism provides benefits to both sellers and buyers of equity in an acquisition transaction. This article is protected by copyright. All rights reserved.
Valid, reliable, and acceptable tools for assessing self-reported competence in evidence-informed decision-making (EIDM) are required to provide insight into the current status of EIDM knowledge, skills, attitudes/beliefs, and behaviours for registered nurses working in public health. The purpose of this study was to assess the validity, reliability, and acceptability of the EIDM Competence Measure. A psychometric study design was employed guided by the Standards for Educational and Psychological Testing and general measurement development principles. All registered nurses working across 16 public health units in Ontario, Canada were invited to complete the newly developed EIDM Competence Measure via an online survey. The EIDM Competence Measure is a self-reported tool consisting of four EIDM subscales: 1) knowledge; 2) skills; 3) attitudes/beliefs; and 4) behaviours. Acceptability was measured by completion time and percentage of missing data of the original 40-item tool. The internal structure of the tool was first assessed through item-subscale total and item-item correlations within subscales for potential item reduction of the original 40-item tool. Following item reduction which resulted in a revised 27-item EIDM Competence Measure, a principal component analysis using an oblique rotation was performed to confirm the four subscale structure. Validity based on relationships to other variables was assessed by exploring associations between EIDM competence attributes and individual factors (e.g., years of nursing experience, education) and organizational factors (e.g., resource allocation). Internal reliability within each subscale was analyzed using Cronbach’s alphas. Across 16 participating public health units, 201 nurses (mean years as a registered nurse = 18.1, predominantly female n = 197; 98%) completed the EIDM Competence Measure. Overall missing data were minimal as 93% of participants completed the entire original 40-item tool (i.e., no missing data), with 7% of participants having one or more items with missing data. Only one participant (0.5%) had >10% of missing data (i.e., more than 4 out of 40 items with data missing). Mean completion time was 7 minutes and 20 seconds for the 40-item tool. Extraction of a four-factor model based on the 27-item version of the scale showed substantial factor loadings (>0.4) that aligned with the four EIDM subscales of knowledge, skills, attitudes/beliefs, and behaviours. Significant relationships between EIDM competence subscale scores and education, EIDM training, EIDM project involvement, and supportive organizational culture were observed. Cronbach’s alphas exceeded minimum standards for all subscales: knowledge (α = 0.96); skills (α = 0.93); attitudes/beliefs (α = 0.80); and behaviours (α = 0.94).
Gekkotan lizards of the genus Hemidactylus exhibit derived digital morphologies. These include heavily reduced antepenultimate phalanges of digits III and IV of the manus and digits III–V of the pes, as well as enigmatic cartilaginous structures called paraphalanges. Despite this well‐known morphological derivation, no studies have investigated the development of these structures. We aimed to determine if heterochrony underlies the derived antepenultimate phalanges of Hemidactylus. Furthermore, we aimed to determine if convergently evolved paraphalanges exhibit similar or divergent developmental patterns. Herein we describe embryonic skeletal development in the hands and feet of four gekkonid species, exhibiting a range of digital morphologies. We determined that the derived antepenultimate phalanges of Hemidactylus are the products of paedomorphosis. Furthermore, we found divergent developmental patterns between convergently evolved paraphalanges.
Polyhedral Graphic Statics (PGS) is an effective tool for form-finding and constructing complex yet efficient spatial funicular structures. The intrinsic planarity of polyhedral geometries can be leveraged for efficient fabrication and construction using flat sheet materials, such as glass. Our previous research used PGS for the form-finding of a 3 m-span, modular glass bridge prototype to be built with thirteen unique hollow glass units (HGUs) in a compression-only configuration. This paper reports its design optimization, fabrication, and subsequent modular assembly process. The computational modeling of the geometries is facilitated with the efficient half-face data structure provided by PolyFrame, a software that implements PGS. Regular float glass and acrylic are selected as the main structural materials, and they are fabricated using 5-axis water jet cutting and CNC milling techniques. With the help of 3 M™ Very High Bond tape, the glass parts and acrylic parts are bonded as HGUs, which serve as the basic structural and assembly modules. Surlyn sheets are used as interface material to prevent glass-to-glass direct contact between HGUs. The digital model is also simulated using ANSYS to ensure the effectiveness of the design. Due to the lightweight of the HGUs, the assembly of the bridge can be done by one person without the requirement of any heavy construction machinery.
The exponentially growing literature on Industry 4.0 technologies and their implications for supply chains exhibits valuable insights alongside considerable fragmentation. While prior systematic literature reviews (SLRs) started to consolidate the literature, an SLR that simultaneously (a) covers several core technologies of the Industry 4.0, (b) synthesizes their positive and negative implications for supply chain performance in a broad sense, and (c) accounts for the critical success factors that foster or impede these implications is still missing. We contribute to establishing a cumulative body of knowledge by conducting such an SLR. We synthesize 221 articles published on 11 Industry 4.0 technologies between 2005 and 2021. Rather than aggregate implications, our SLR presents the benefits, challenges, and critical success factors of each core technology vis-à-vis supply chain performance individually. We integrate our findings into a framework of Industry 4.0 supply chain performance and derive promising avenues for future research. Specifically, we call for more research on (a) the challenges and critical success factors of Industry 4.0 technologies; (b) hitherto underexplored core technologies of the Industry 4.0; (c) the interaction of multiple core technologies (are they complements or substitutes?); as well as for (d) further consolidation and interdisciplinary dissemination efforts.
Due to an editorial oversight, we would like to apologize for an error that occurred in the both print and online version of an editorial entitled “GSK-3 Inhibitors in the Regulation and Control of Colon Carcinoma. It was published without the co-authors’ names in the journal “Current Drug Targets” 2021; 22(13), 1485-1495. The original editorial can be found online at 10.2174/1389450122666210204203950
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3,224 members
Jeremy P. Carlo
  • Department of Physics
Anil K Bamezai
  • Department of Biology
Justinus Satrio
  • Department of Chemical Engineering
Philipp Wagner
  • Department of Biology
Robert Beck
  • Department of Computing Science
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