# Virginia Tech (Virginia Polytechnic Institute and State University)

• Blacksburg, Virginia, United States
Recent publications
Due to piezoelectric softening and dissipative nonlinearities, the piezoelectric cantilever energy harvester exhibits nonlinear hysteresis when subjected to large excitation. These nonlinearities have brought significant challenges to the modeling and response prediction of randomly excited piezoelectric energy harvesting systems. In this study, the voltage responses of the nonlinear piezoelectric cantilever energy harvester under random excitation are initially assumed to follow the Gaussian distribution which is experimentally validated later. The equivalent linear transfer function are derived from the approximate linearization of the stiffness and damping using the statistical linearization (SL) technique. The mathematical expectations of the voltage responses are calculated from the multivariate normal distributions. Frequency sweep experiments are conducted to a cantilever energy harvester to identify the nonlinear piezoelectric material properties. The statistically linearized model was experimentally validated under random base acceleration excitation by comparing the probability density function of the predicted voltage responses and average power against the experimental measurements. The advantage of the SL technique lies in allowing one to use an iterative procedure to estimate the equivalent linear terms while the analytical expressions are unattainable because of the complex nonlinearity in the governing equations. The results show that the prediction of the SL model to the random base acceleration excitation agrees with experimental measurements with a broadband frequency range, although only the fundamental mode of the beam is considered.
Dimensionality reduction techniques (DR) enhance data interpretability and reduce space complexity, though at the cost of information loss. Such methods have been prevalent in the Structural Health Monitoring (SHM) anomaly detection literature. While DR is favorable in supervised anomaly detection, where possible novelties are known a priori, the efficacy is less clear in unsupervised detection. In this work, we perform a detailed assessment of the DR performance trade-offs to determine whether the information loss imposed by DR can impact SHM performance for previously unseen novelties. As a basis for our analysis, we rely on an SHM anomaly detection method operating on input signals’ fast Fourier transform (FFT). FFT is regarded as a raw, frequency-domain feature that allows studying various DR techniques. We design extensive experiments comparing various DR techniques, including neural autoencoder models, to capture the impact on two SHM benchmark datasets exclusively. Results imply the loss of information to be more detrimental, reducing the novelty detection accuracy by up to 60% with autoencoder-based DR. Regularization can alleviate some of the challenges though unpredictable. Dimensions of substantial vibrational information mostly survive DR; thus, the regularization impact suggests that these dimensions are not reliable damage-sensitive features regarding unseen faults. Consequently, we argue that designing new SHM anomaly detection methods that can work with high-dimensional raw features is a necessary research direction and present open challenges and future directions.
The recycling of end-of-life (EoL) electronic products is motivated by the enormous investment of resources in their creation and the environmental concerns associated with electronic waste (e-waste). Hydrometallurgical methods that utilize conventional leaching and solvent extraction are often applied to extract target materials from e-waste; however, these techniques have significant technical and economic limitations when extracting high-value, low concentration metals from complex waste streams. This study proposes and evaluates a novel process based on gas-assisted microflow extraction (GAME) that efficiently recovers precious metals from waste printed circuit boards (WPCBs). An economic analysis is conducted to verify the economic feasibility of the GAME-based process at an industrial scale. The economic outputs are further investigated to identify the most cost-effective production strategies, particularly with respect to the plant feedstock rate. It is envisioned that this study may establish a paradigm for making economically-informed decisions for sustainable technologies.
The intrinsic biophysical properties of cells, such as mechanical, acoustic, and electrical properties, are valuable indicators of a cell's function and state. However, traditional single-cell biophysical characterization methods are hindered by limited measurable properties, time-consuming procedures, and complex system setups. This study presents acousto-dielectric tweezers that leverage the balance between controllable acoustophoretic and dielectrophoretic forces applied on cells through surface acoustic waves and alternating current electric fields, respectively. Particularly, the balanced acoustophoretic and dielectrophoretic forces can trap cells at equilibrium positions independent of the cell size to differentiate between various cell-intrinsic mechanical, acoustic, and electrical properties. Experimental results show our mechanism has the potential for applications in single-cell analysis, size-insensitive cell separation, and cell phenotyping, which are all primarily based on cells' intrinsic biophysical properties. Our results also show the measured equilibrium position of a cell can inversely determine multiple biophysical properties, including membrane capacitance, cytoplasm conductivity, and acoustic contrast factor. With these features, our acousto-dielectric tweezing mechanism is a valuable addition to the resources available for biophysical property-based biological and medical research.
Introduction Campylobacter spp. infections are responsible for significant diarrheal disease burden across the globe, with prevalence thought to be increasing. Although wild avian species have been studied as reservoirs of Campylobacter spp., our understanding of the role of wild mammalian species in disease transmission and persistence is limited. Host factors influencing infection dynamics in wild mammals have been neglected, particularly life traits, and the role of these factors in zoonotic spillover risk is largely unknown. Methods Here, we conducted a systematic literature review, identifying mammalian species that had been tested for Campylobacter spp. infections (molecular and culture based). We used logistic regression to evaluate the relationship between the detection of Campylobacter spp. in feces and host life traits (urban association, trophic level, and sociality). Results Our analysis suggest that C. jejuni transmission is associated with urban living and trophic level. The probability of carriage was highest in urban-associated species ( p = 0.02793) and the most informative model included trophic level. In contrast, C. coli carriage appears to be strongly influenced by sociality ( p = 0.0113) with trophic level still being important. Detection of Campylobacter organisms at the genus level, however, was only associated with trophic level ( p = 0.0156), highlighting the importance of this trait in exposure dynamics across host and Campylobacter pathogen systems. Discussion While many challenges remain in the detection and characterization of Camploybacter spp., these results suggest that host life traits may have important influence on pathogen exposure and transmission dynamics, providing a useful starting point for more directed surveillance approaches.
The heterogeneity of produce production environments complicates the development of universal strategies for managing preharvest produce safety risks. Understanding pathogen ecology in different produce-growing regions is important for developing targeted mitigation strategies. This study aimed to identify environmental and spatiotemporal factors associated with isolating Salmonella and Listeria from environmental samples collected from 10 Virginia produce farms. Soil (n = 400), drag swab (n = 400), and irrigation water (n = 120) samples were tested for Salmonella and Listeria, and results were confirmed by PCR. Salmonella serovar and Listeria species were identified by the Kauffmann-White-Le Minor scheme and partial sigB sequencing, respectively. Conditional forest analysis and Bayesian mixed models were used to characterize associations between environmental factors and the likelihood of isolating Salmonella, Listeria monocytogenes (LM), and other targets (e.g., Listeria spp. and Salmonella enterica serovar Newport). Surrogate trees were used to visualize hierarchical associations identified by the forest analyses. Salmonella and LM prevalence was 5.3% (49/920) and 2.3% (21/920), respectively. The likelihood of isolating Salmonella was highest in water samples collected from the Eastern Shore of Virginia with a dew point of >9.4°C. The likelihood of isolating LM was highest in water samples collected in winter from sites where <36% of the land use within 122 m was forest wetland cover. Conditional forest results were consistent with the mixed models, which also found that the likelihood of detecting Salmonella and LM differed between sample type, region, and season. These findings identified factors that increased the likelihood of isolating Salmonella- and LM-positive samples in produce production environments and support preharvest mitigation strategies on a regional scale. IMPORTANCE This study sought to examine different growing regions across the state of Virginia and to determine how factors associated with pathogen prevalence may differ between regions. Spatial and temporal data were modeled to identify factors associated with an increased pathogen likelihood in various on-farm sources. The findings of the study show that prevalence of Salmonella and L. monocytogenes is low overall in the produce preharvest environment but does vary by space (e.g., region in Virginia) and time (e.g., season), and the likelihood of pathogen-positive samples is influenced by different spatial and temporal factors. Therefore, the results support regional or scale-dependent food safety standards and guidance documents for controlling hazards to minimize risk. This study also suggests that water source assessments are important tools for developing monitoring programs and mitigation measures, as spatiotemporal factors differ on a regional scale.
The present paper is devoted to characterizing the three-dimensional effects in a cavitating flow generated in a Venturi-type profile. Experimental measurements based on 2D3C(Two-dimensional-three-component) stereoscopic PIV(Particle Image Velocimetry) are conducted to obtain the three components of the velocity field in multiple vertical planes aligned with the main flow direction, from the center of the channel to the side walls. Time-resolved acquisitions are conducted, so not only time-averaged quantities but also velocity fluctuations can be discussed. The attention was focused on configurations of cloud cavitation, where the attached cavity experiences large-scale periodical oscillations and shedding of clouds of vapor. Although the water channel is purely two-dimensional, some significant flow velocities in the third direction (depth of the test section) were measured. Some of them were found to be related to small differences between the boundary conditions on the two sides, such as minor gaps between the sides and the bottom wall, while others reflect intrinsic three-dimensional mechanisms inside the cavitation area, such as side jets that contribute to the periodical instability process. These mechanisms are discussed, and a possible 3D(Three-dimensional) structure of the cavitating flow is proposed.
Walleye Sander vitreus have been stocked throughout the Appalachian region to augment or restore populations of this economically and ecologically important species. Prior to the genetic identification of a native Eastern Highlands strain, Walleye from the Great Lakes were often used to supplement populations and create new populations. To assess the effect of stocking of Great Lakes‐strain Walleye, three Appalachian populations were sampled: two native populations (Rockcastle River, KY and New River, VA) and one population founded from the Great Lakes strain (Tygart Lake, WV). Walleye from Lake Erie were used as a reference for the Great Lakes strain. Utilization of a genotype‐by‐sequencing approach supported genome‐wide estimates of genetic diversity, population structure, and creation of two SNP assays that can be used to rapidly identify Great Lakes strain, native Eastern Highland strain, and F1 hybrid Walleye. Results indicate that the four populations we evaluated were genetically distinct from one another and that each population contains varying degrees of genetic differentiation relative to its source population. The stocked Tygart Lake population displayed lower genetic diversity in metrics such as nucleotide diversity (0.172 vs. 0.184), private alleles (4057 vs. 7623), and observed heterozygosity (0.163 vs. 0.204), likely indicative of genetic drift stemming from a founder effect. The two native populations displayed varying levels of genetic diversity. The New River population was found to have a higher ancestry of the Great Lakes strain in their genome than the Rockcastle River population, reflecting the known admixture of New River Walleye following historic stocking of Great Lakes‐derived Walleye. Our results provide molecular tools and show the need for further sampling across the region to identify Great Lakes strain ancestry in local populations and to identify pure native Eastern Highland populations that can be used for future augmentation and restoration of native Walleye.
With the introduction of new apple varieties, emerging diseases have been recorded including dry lenticel rot and white haze. Ramularia mali has been identified as the causal agent of dry lenticel rot, whereas species of Golubevia, Tilletiopsis and Entyloma have been associated to white haze, but the epidemiology of these pathogens remains unclear. In the present study, we measured fruit disease incidence and quality parameters, and we used metabarcoding to characterize both epiphytic and endophytic microbial communities of apple fruit of two commercial cultivars, ‘Opal’ and ‘Ambrosia’, across six time points from early fruit development up to the end of shelf life. R. mali first develops in both cultivars as an endophyte at BBCH (Biologische Bundesanstalt, Bundessortenamt and CHemical industry) phenological phase 73 (10–11% relative abundance), BBCH 77 (26–33% relative abundance) and BBCH 81 (1–7% relative abundance), then it appears as an epiphyte from BBCH 87 onward (1–2% relative abundance), when symptoms start to be visible. This was confirmed in endophytic samples through qPCR specific for R. mali. Among the genera associated to white haze, Golubevia was the most abundant epiphyte (2–4%) from BBCH 81 to the end of shelf life. Alpha and beta diversity analyses unveiled the presence of significant difference both in richness and composition among different tissue, time points and cultivars. In conclusion, the study helps to explain the epidemiology of white haze and dry lenticel rot, and to design a targeted crop protection strategy, reinforcing the hypothesis that fruit metabarcoding could be a valuable tool for assessment and prediction of postharvest diseases, before symptoms occurrence in fruit.
The demand for organic forage is increasing while information on appropriate forage species that influence soil properties and forage productivity is scarce. This study was conducted to understand the response of soil health to a diverse forage species in the transitioning stage of low-input organic forage systems. Soils were collected for two years after the forage establishment to analyze soil health indicators. Results showed that perennial mixtures generally had greater total nitrogen (N), mineral N, soil organic carbon (SOC), and microbial biomass carbon (MBC), while similar pH, extractable phosphorus (P), extractable potassium (K), and wet aggregate stability (WAS), compared to monocultures. Mean values of perennial mixtures vs. monocultures at 0–5 cm were 2.1 vs. 1.9 g kg⁻¹, 21.1 vs. 16.2 mg kg⁻¹, 21 vs. 19 g kg⁻¹, 352 vs. 290 mg kg⁻¹ for total N, mineral N, SOC and MBC, respectively. Among perennial mixtures, tall fescue (Schedonorus arundinaceus Schreb.)-legume mixtures showed higher pH, total N, mineral N, MBC, and soil quality index (SQI). Tall fescue-white clover (Trifolium repens L.) mixtures had highest pH (6.34 and 6.45), total N (2.09 and 1.69 g kg⁻¹), and mineral N (25.4 and 21.3 mg kg⁻¹) at 0–5 and 5–15 cm, respectively. The SQI in tall fescue- alfalfa (Medicago sativa L.) was higher than bermudagrass [Cynodon dactylon (L.) Pers.]- alfalfa mixture (77 vs. 71). Compared to perennials, the annual system had comparable or greater total N, mineral N, SOC, MBC, WAS, and SQI. In the 0–5 cm stratum, annual systems from two research sites had 2.01 and 2.21 g kg⁻¹ total N, 17.9 and 29.9 mg kg⁻¹ mineral N, 20.0 and 22.5 g kg⁻¹ SOC, 337 and 227 mg kg⁻¹ MBC, 72 % and 80 % for WAS, and 74 and 72 for SQI. However, the annual system had lower or comparable pH, P and K, compared to most perennial mixtures. After two-years of organic management, most treatments increased soil moisture, pH, MBC, and extractable P compared to the baseline data, while some treatments decreased SOC, mineral N, and K. This study suggested perennial mixtures, especially tall fescue-legume systems, had the greatest potential in improving soil health at the early stage of low-input organic pasture establishment. Despite the short-term management, low-input organic pastures improved some important soil properties such as moisture, pH, MBC, and extractable P. Long-term monitoring is needed to understand the full spectrum of ecosystem benefits when organic management is implemented in forage production systems.
Public acceptability appears an essential condition for the success of low-carbon transition policies. In this paper, we investigate the role of self-interest on citizens' preferences for the distribution of costs and environmental benefits of energy efficiency policies. Using a discrete choice experiment on nationally representative household samples of Sweden, Italy, and the United Kingdom, we first investigate preferences for national burden-sharing rules and for the distribution of environmental benefits accruing primarily in rural and/or urban areas. We examine the role of self-interest and self-serving bias in a correlational manner by looking at the effects of income and location of residency on preferences for these policy attributes. Moreover, we investigate the effect of self-serving bias on preferences for burden-sharing rules in a causal manner by experimentally priming randomly assigned groups of participants to feel either rich or poor. Our results suggest that the accountability rule is the most popular and the equal-amount rule the least popular burden-sharing rule. Further, policies with environmental benefits accruing primarily in rural areas are least preferred. We find some evidence for self-interest, especially through our correlational approach. Finally, across country samples, our results reveal heterogeneity in preferences for policy attributes and in the prevalence of self-interest.
Manufacturers are exploring the extent to which digital technology applications can support their sustainability efforts by helping to convert abstract sustainability goals, such as those of net-zero emissions and circular economy (CE), into feasible and practical actions, achievements, and ultimately, a sustainable competitive edge. This work adopts a resource-based view (RBV) to explore the potential role that digital technologies play in the cultivation of a manufacturing firm's competitive advantage, and the deployment of existing internal resources and core competencies to achieve net-zero manufacturing emissions and CE. Two questions are addressed: (1) What competitive advantage(s) may be derived from the integration of digital technologies to achieve net-zero manufacturing emissions, and (2) does adopting an RBV facilitate the development of meaningful (and novel) competitive advantage? Engaged scholarship is used to analyse and apply theory to an empirical, real-world dataset documenting the perspectives and experiences of 13 manufacturing firms. Applying the VRIO framework, 21 identified digital technology-based core competencies are categorised as forms of competitive advantage that may be possible for manufacturing firms pursuing net-zero emissions. Four scenarios of digital technology adoption pathways are proposed, differentiated by the degree of radical vs. incremental interests and options available to the firm. This study highlights the critical need for firms to incorporate intangible asset management and development, including the labour and supply chain relationships, as part of their digital transformation strategies. Further, we demonstrate the potential of RBV as a lens for evaluating the competitive advantage potential of corporate sustainability initiatives, and facilitating the development of related strategies.
Reactive oxygen species (ROS) in harvested fruit wound tissues result in an oxidative microenvironment. The pretreatment of some antagonistic yeasts with stress-ameliorating compounds has been shown to enhance tolerance to subsequent exposure to oxidative stress and thus improves biocontrol performance. The effect of caffeic acid (CA) on ROS in Candida oleophila was investigated after administration to kiwifruit wounds. CA treatment enhanced the tolerance of C. oleophila to the microenvironment of kiwifruit wounds. CA-treated yeast recovered from the microenvironment had lower ROS, less mitochondrial impairment and cellular oxidative damage, relative to non-CA (NCA) treated yeast. CA-treated yeast also exhibited improved biocontrol efficacy on kiwifruit against the decay fungi, Botrytis cinerea and Penicillium expansum, and more rapid growth in fruit wounds, than NCA-treated yeast. The antioxidant gene expression of C. oleophila was elicited by the CA treatment. In conclusion, the activation of antioxidant response induced by the by CA treatment of C. oleophila contributed to enhanced tolerance to oxidative stress and improved biocontrol efficacy against postharvest decay fungi.
Relative growth rates (RGR) have both intrigued and irritated many plant scientists since they were proposed as characteristics of growth performance in the early 20th century. Particularly, the common trend of RGR to decrease with increasing size, also referred to as ontogenetic drift, has given rise to many debates and much criticism. In this study, we showed that, with plants that germinated at the same time, it is common to obtain a linear relationship between RGR and size for each survey year which – when pulled together in one graph – eventually form a system of cascading elliptical point clouds over time. This system of data point clouds reflects the well-known exponential decline of RGR with size, the aforementioned ontogenetic drift. Using 12 individual-tree time series of Pinus radiata in Chile we studied the ontogenetic drift based on a new spatially explicit explanatory model allowing the reconstruction of individual-tree RGR trajectories. Favourable environmental conditions enforced the RGR decline over size and accelerated growth dynamics. Less favourable environmental conditions reduced the strength of the ontogenetic drift and slowed down growth. We also found that the model parameter estimates were more precise the stronger the RGR decline over size. Both, interpretable model parameters and evaluation characteristics, described the ontogenetic drift well. Interestingly, the slopes of the semi-major axes of the RGR-size data ellipses changed signs precisely at the time when smaller trees ceased to dominate population growth and larger trees started to contribute disproportionately to the overall growth processes.
Patch-burn grazing, a combination of fire and grazing, has been identified as a novel approach to maintaining biodiversity in the Great Plains of the United States. Many ranchers, however, are not aware of the practice and very few of them had adopted it on their land. Utilizing the data obtained from a survey of landowners residing in the southern Great Plains of the United State conducted in 2021, we analyzed the factors affecting the awareness and adoption of patch-burn grazing. Since an adoption behavior study might suffer from selection bias if the level of awareness is not appropriately accounted for, we used a bivariate probit model for data analysis. The study results indicated that repeated wildfires, nature conservancy, and university/county extension positively affected the probability of patch-burn grazing awareness while the effect of age and livestock membership had a negative impact. The research further revealed that larger landholding size, management objectives to control blackberry, repeated wildfires, and university/county extension positively influenced the likelihood of patch-burn grazing adoption. In contrast, the management objective to control red cedar, along with respondent age, and higher-income negatively influenced the patch-burn grazing adoption. Since many landowners are not convinced to adopt patch-burn grazing, study results suggest further extension needs to educate traditional and non-traditional ranchers on the ecological and production benefits of patch-burn grazing.
Chip size ( $\textit{A}_{\text{chip}}$ ) optimization is key to the accurate analysis of device and material costs and the design of multichip modules. It is particularly critical for wide bandgap (WBG) and ultrawide bandgap (UWBG) power devices due to high material cost. Moreover, the designs of $\textit{A}_{\text{chip}}$ and the drift region thickness ( $\textit{W}_{\text{dr}}$ ) and doping concentration ( $\textit{N}_{\text{dr}}$ ) are interdependent, requiring their co-optimization. Current design practices for $\textit{A}_{\text{chip}}$ , $\textit{W}_{\text{dr}}$ , and $\textit{N}_{\text{dr}}$ rely on optimizing electrical parameters. $^{^{^{}}}$ This work presents a new, holistic, electrothermal approach to optimize $\textit{A}_{\text{chip}}$ for a given set of target specifications, including breakdown voltage (BV), conduction current ( $\textit{I}_{\text{0}}$ ), and switching frequency ( $\textit{f}$ ). The conduction and switching losses of the device are considered as well as the heat dissipation in the chip and its package. For a given BV and $\textit{I}_{\text{o}}$ , the optimal $\textit{A}_{\text{chip}}$ , $\textit{W}_{\text{dr}}$ , and $\textit{N}_{\text{dr}}$ show a strong dependence on $\textit{f}$ and thermal management. Such dependencies are missing in prior $\textit{A}_{\text{chip}}$ design methods. This approach is applied to compare the optimal $\textit{A}_{\text{chip}}$ of WBG and UWBG devices up to a BV over 10 kV and $\textit{f}$ of 1 MHz. $^{^{^{}}}$ Our approach offers more accurate cost analysis and design guidelines for power modules.
Decompilation is currently a widely used tool in reverse engineering and exploit detection in binaries. Ghidra, developed by the National Security Agency, is one of the most popular decompilers. It decompiles binaries to high P-Code, from which the final decompilation output in C code is generated. Ghidra allows users to work with P-Code, so users can analyze the intermediate representation directly. Several projects make use of this to build tools that perform verification, decompilation, taint analysis and emulation, to name a few. P-Code lacks a formal semantics, and its documentation is limited. It has a notoriously subtle semantics, which makes it hard to do any sort of analysis on P-Code. We show that P-Code, as-is, cannot be given an executable semantics. In this paper, we augment P-Code and define a complete, executable, formal semantics for it. This is done by looking at the documentation and the decompilation results of binaries with known source code. The development of a formal P-Code semantics uncovered several issues in Ghidra, P-Code, and the documentation. We show that these issues affect projects that rely on Ghidra and P-Code. We evaluate the executability of our semantics by building a P-Code interpreter that directly uses our semantics. Our work uncovered several issues in Ghidra and allows Ghidra users to better leverage P-Code.
Objective: To investigate the relationship between invasively measured stroke volume (SV) and (1) esophageal Doppler-derived indices such as stroke distance (StrokeD), flow time corrected (FTc), stroke distance variation (SDV), and peak velocity variation (PVV); and (2) arterial load (AL) variables during evaluation of fluid responsiveness (FR) in anesthetized dogs undergoing sudden hemodynamic shifts in blood volume. Animals: 6 healthy male dogs. Procedures: Dogs were anesthetized with isoflurane, ventilated mechanically, and instrumented to undergo sequential, nonrandomized experimental stages. The dogs transitioned from normovolemia (NORMO-BL) to hypovolemia (30% blood loss; HYPO-30), followed by autologous blood transfusion, and then to hypervolemia (colloid bolus). During each stage, SV was quantified using pulmonary artery thermodilution and its relationship with StrokeD, FTc, SDV, and PVV; and AL variables such as effective arterial elastance (Ea), dynamic arterial elastance (Eadyn), and total arterial compliance (Ca) were established. Results: As SV decreased significantly during HYPO-30 compared to NORMO-BL, there was a significant (P < .001) decrease in StrokeD, FTc, and Ca, with simultaneous increases in SDV, PVV, Ea, and Eadyn. Upon restoration of blood volume, these values stabilized closer to NORMO-BL. A significant (P < .001) correlation was observed between SV and StrokeD, FTc, Ea, Eadyn, and Ca. Clinical relevance: Minimally invasive StrokeD, FTc, SDV, and PVV act as SV surrogates and help assess FR during different blood volume stages in healthy dogs. During hypovolemia-induced hypotension, Ea, Eadyn, and Ca may be able to guide therapeutic decisions favoring improvement in blood pressure and SV.
In this study, we investigated whether the relationship between pitch and politeness is mediated through iconic relationships between pitch and other talker attributes, and whether these relationships can differ across languages. US and South Korean listeners completed a speaker perception task in which they heard utterances and rated the speaker on a number of attributes, including politeness. The pitch of each utterance was unmanipulated, raised, or lowered. The results confirm previous work suggesting that in Korean, lower pitch is associated with politeness, which contrasts with both the English results we find, and claims of a universal association between higher pitch and politeness (i.e., Ohala’s Frequency Code). At the same time, the impact of pitch on attributes like perceived height, strength, and emotion are similar across listener groups: speakers in higher pitched guises are heard as shorter, weaker, and more emotional. Like others, we argue that pitch can be associated non-arbitrarily with a range of meanings, but additionally appeal to orders of indexicality (Silverstein, 2003) to account for the similarities between the groups, as well as the differences. Our results are of significance for researchers looking at non-arbitrary meaning of acoustic cues as well as the acoustics of politeness, especially in interaction with polite registers in Korean.
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