University of Tennessee
  • Knoxville, TN, United States
Recent publications
The development of multifunctional and efficient electromagnetic wave absorbing materials is a challenging research hotspot. Here, the magnetized Ni flower/MXene hybrids are successfully assembled on the surface of melamine foam (MF) through electrostatic self-assembly and dip-coating adsorption process, realizing the integration of microwave absorption, infrared stealth, and flame retardant. Remarkably, the Ni/MXene-MF achieves a minimum reflection loss (RL min ) of − 62.7 dB with a corresponding effective absorption bandwidth (EAB) of 6.24 GHz at 2 mm and an EAB of 6.88 GHz at 1.8 mm. Strong electromagnetic wave absorption is attributed to the three-dimensional magnetic/conductive networks, which provided excellent impedance matching, dielectric loss, magnetic loss, interface polarization, and multiple attenuations. In addition, the Ni/MXene-MF endows low density, excellent heat insulation, infrared stealth, and flame-retardant functions. This work provided a new development strategy for the design of multifunctional and efficient electromagnetic wave absorbing materials.
This paper describes a system for automated identification of the optimal stable cutting parameters in milling through Bayesian machine learning and closed-loop control. The closed-loop control system consists of a process monitoring architecture, an analysis framework, and a feedback mechanism. The analysis framework consists of a Bayesian machine learning algorithm that learns a stability map given test results. The learned stability map is used to select parameters for stability testing using an expected improvement in the material removal rate criterion. The test parameters are communicated to the machine controller to complete the test cut through a feedback mechanism. The test cuts were monitored using an audio signal; the stability of the test cut was determined by analyzing the frequency content of the audio signal. The test result was fed back to the Bayesian learning algorithm to complete the loop. Experimental results demonstrate that the system can identify the optimal stable parameters without information about the cutting force model or the structural dynamics. The system provides a low-cost method for optimal stable parameter identification in an industrial environment.
Background Cotton ( Gossypium hirsutum L.) is often grown in locations characterized by high atmospheric evaporative demand. It has been hypothesized that plants which resist hydraulic flow under this condition will limit water use and conserve soil water. Therefore, in a series of controlled environment experiments ten cotton cultivars were exposed to two different temperature and vapor pressure deficit (VPD) conditions (i.e., 38 °C, > 3 kPa and 32 °C, 1∼1.5 kPa) as well as a progressive soil drying. Then, individual differences in shoot hydraulic conductance (K shoot ) was measured using a hydraulic conductance flow meter (HCFM). Physiological parameters were reported included leaf area, dry leaf weight, stomatal conductance (g s ), and water use efficiency coefficient (WUE k ). Results Differences were observed in K shoot among cultivars under the 38 °C, > 3 kPa but not the 32 °C, 1∼1.5 kPa environment. Under the 38 °C, > 3 kPa environment, correlations were found between K shoot , stomatal conductance (g s ), VPD breakpoint, WUE k , total leaf area, dry leaf weight, fraction transpirable soil water (FTSW) threshold, and slope of TR decline after FTSW threshold. Conclusion Results show that the ability of some cotton cultivars to restrict water loss under high evaporative demand through early stomatal closure is associated with the cultivars’ K shoot . The K shoot is influential in the limitation of TR trait under high temperature and VPD.
High entropy alloys (HEAs) are promising materials for various applications including nuclear reactor environments. Thus, understanding their behavior under irradiation and exposure to different environments is important. Here, two sets of near-equiatomic CoCrCuFeNi thin films grown on either SiO 2 /Si or Si substrates were irradiated at room temperature with 11.5 MeV Au ions, providing similar behavior to exposure to inert versus corrosion environments. The film grown on SiO 2 had relatively minimal change up to peak damage levels above 500 dpa, while the film grown on Si began intermixing at the substrate–film interface at peak doses of 0.1 dpa before transforming into a multi-silicide film at higher doses, all at room temperature with minimal thermal diffusion. The primary mechanism is radiation-enhanced diffusion via the inverse Kirkendall and solute drag effects. The results highlight how composition and environmental exposure affect the stability of HEAs under radiation and give insights into controlling these behaviors.
Context Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs. Objective We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits. Methods We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the same label, we have consensus. Results We estimate that between 17% and 32% of all changes in bug fixing commits modify the source code to fix the underlying problem. However, when we only consider changes to the production code files this ratio increases to 66% to 87%. We find that about 11% of lines are hard to label leading to active disagreements between participants. Due to confirmed tangling and the uncertainty in our data, we estimate that 3% to 47% of data is noisy without manual untangling, depending on the use case. Conclusion Tangled commits have a high prevalence in bug fixes and can lead to a large amount of noise in the data. Prior research indicates that this noise may alter results. As researchers, we should be skeptics and assume that unvalidated data is likely very noisy, until proven otherwise.
Water quality impairment linked to household septic systems presents a significant challenge for environmental management professionals given the costs and complexity of encouraging residents to convert to sewer systems. Septic-to-sewer conversion programs may be more effective if they employ innovative techniques such as social marketing to accelerate engagement, but there is a lack of the necessary formative audience research available on which to promote sanitation-related technologies and behaviors using these types of strategies. We used Diffusion of Innovations theory as a lens through which to view support for septic-to-sewer conversion programs, considering perceptions of relative advantage, compatibility, complexity, and observability as factors (i.e., barriers, motivators) in the decision to convert to sewer. We collected data from 518 septic system owners in the state of Florida, USA. Four out of ten respondents indicated there were septic-to-sewer conversion plans in place in their community, and most of these individuals reported the plans were voluntary rather than mandatory. Residents with plans in place had more favorable perceptions than those without such plans and were largely supportive of septic-to-sewer conversion programs. Ordinal regression revealed compatibility and observability were significant predictors of residents' support for septic-to-sewer conversion. When conversion project status variables were added to the final ordinal model, compatibility remained a significant predictor, and completed conversion status also predicted support. Environmental management professionals should consider using characteristics of compatibility and observability to bolster engagement in septic-to-sewer conversion programs, and consider integrating the influences of other communities with completed conversion programs.
Low electrical conductivity and poor accessibility of MoS2 reaction sites raise great challenges in maximizing the triple-phase-boundary (TPB) sites of MoS2-based electrodes and minimizing ohmic losses for efficient hydrogen evolution reaction (HER) in practical proton exchange membrane (PEM) water electrolysis. Herein, we report a scalable hydrothermal approach to fabricate ionomer-free integrated electrodes with engineered 1 T-2 H heterophase and defect-rich MoS2 nanosheets (MoS2NSs) in-situ grown onto the carbon fiber paper (CFP). With an ultralow loading of 0.14 mg/cm², a small voltage of 2.25 V was obtained at 2000 mA/cm² in a practical cell with Nafion115 membrane, which outperforms all previously reported high-loading non-precious catalyst-based electrodes. Impressively, it shows 44 times higher mass activity than a high-loading and ionomer-mixed MoS2 assemblies electrode. This work builds a bridge from catalyst optimization to electrode fabrication and provides a promising direction for improving intrinsic catalytic activity, electrode conductivity and stability for practical PEM water electrolysis.
This study examines the relationships between energy use intensity (EUI), which is considered to be an indicator of energy efficiency, and dwelling or housing characteristics, technology (appliances), socio-demographic characteristics, geographic factors, and energy-related behavioral actions. Additionally, it explores whether these relationships vary across low-, medium-, and high-income households. The study is based on regression analyses conducted on a representative sample of households, the 2015 U.S. Residential Energy Consumption Survey. Overall, the analysis revealed two important findings. First, residential energy use intensity is shaped significantly by housing characteristics, socio-demographic factors, technology, and energy-related behavioral actions. Second, the relationships between the factors examined and energy use intensity vary quite substantially across income groups. Lower income households have a higher EUI than higher income households. The policy implications of these findings are that reducing EUI in the residential sector, which may help with addressing energy burdens and poverty among low-income households, will require paying careful attention to these factors and their dynamic impacts across income groups.
Energy and internet insecurity are exacerbated by the compounding of multiple forms of social-economic disadvantage during extreme events. This study demonstrates the effects of concentrated disadvantage on internet and energy burdens and utility hardships in the United States during the COVID-19 pandemic in 2021. Based on 1991 online respondents, we found that internet and energy burdens are higher in Florida than in California, but utility hardship is greater in California. Women, renters, low-income households, and people of color have higher internet and energy burdens than their counterparts. Unique to this study, people with higher energy medical needs are more likely to suffer from energy and internet insecurity than people without such needs. Low-income women, low-income homeowners, and homeowners of color with more energy medical needs have-higher energy burdens than their counterparts. Low-income men, people of color, and Black/Latino residents with higher levels of energy medical needs, and renters with disabilities and homeowners with medical needs affected by heating and cooling experienced higher levels of utility hardship than their counterparts. These findings suggest that energy insecurity is not just determined by income but by other social and health factors. The findings provide policy implications.
Whole class discussions (WCDs) are an important pedagogical tool for mathematics classes but are challenging to characterize across large numbers of observations because of their dynamic and complex nature. In this paper, we report on an exploratory method to characterize WCDs in mathematics classes across large numbers of observations that we refer to as Conversation Profile Analysis (CPA). CPA uses Latent Class Modeling (LCM) with live observation data to generate profiles of WCDs in middle-grade mathematics classes. We report on our exploratory use of CPA to analyze observation data from 259 WCDs about data and statistics in middle school classes making use of an innovative approach to instruction called Data Modeling. We identified 4 profiles of WCDs and found that these profiles varied in likelihood across time and were associated with different ways students talked about key mathematical ideas. We also discuss broader implications of the CPA approach to studying WCDs in math classes.
Background Cytoplasmic and nuclear maturation of oocytes, as well as interaction with the surrounding cumulus cells, are important features relevant to the acquisition of developmental competence. Methods Here, we utilized Brilliant cresyl blue (BCB) to distinguish cattle oocytes with low activity of the enzyme Glucose-6-Phosphate Dehydrogenase, and thus separated fully grown (BCB positive) oocytes from those in the growing phase (BCB negative). We then analyzed the developmental potential of these oocytes, mitochondrial DNA (mtDNA) copy number in single oocytes, and investigated the transcriptome of single oocytes and their surrounding cumulus cells of BCB positive versus BCB negative oocytes. Results The BCB positive oocytes were twice as likely to produce a blastocyst in vitro compared to BCB- oocytes ( P < 0.01). We determined that BCB negative oocytes have 1.3-fold more mtDNA copies than BCB positive oocytes ( P = 0.004). There was no differential transcript abundance of genes expressed in oocytes, however, 172 genes were identified in cumulus cells with differential transcript abundance (FDR < 0.05) based on the BCB staining of their oocyte. Co-expression analysis between oocytes and their surrounding cumulus cells revealed a subset of genes whose co-expression in BCB positive oocytes ( n = 75) and their surrounding cumulus cells ( n = 108) compose a unique profile of the cumulus-oocyte complex. Conclusions If oocytes transition from BCB negative to BCB positive, there is a greater likelihood of producing a blastocyst, and a reduction of mtDNA copies, but there is no systematic variation of transcript abundance. Cumulus cells present changes in transcript abundance, which reflects in a dynamic co-expression between the oocyte and cumulus cells.
Laser powder bed fusion is a promising technology for local deposition and microstructure control, but it suffers from defects such as delamination and porosity due to the lack of understanding of melt pool dynamics. To study the fundamental behavior of the melt pool, both geometric and thermal sensing with high spatial and temporal resolutions are necessary. This work applies and integrates three advanced sensing technologies: synchrotron X-ray imaging, high-speed IR camera, and high-spatial-resolution IR camera to characterize the evolution of the melt pool shape, keyhole, vapor plume, and thermal evolution in Ti-6Al-4V and 410 stainless steel spot melt cases. Aside from presenting the sensing capability, this paper develops an effective algorithm for high-speed X-ray imaging data to identify melt pool geometries accurately. Preprocessing methods are also implemented for the IR data to estimate the emissivity value and extrapolate the saturated pixels. Quantifications on boundary velocities, melt pool dimensions, thermal gradients, and cooling rates are performed, enabling future comprehensive melt pool dynamics and microstructure analysis. The study discovers a strong correlation between the thermal and X-ray data, demonstrating the feasibility of using relatively cheap IR cameras to predict features that currently can only be captured using costly synchrotron X-ray imaging. Such correlation can be used for future thermal-based melt pool control and model validation.
Agencies reporting on disease outbreaks face many choices about what to report and the scale of its dissemination. Reporting impacts an epidemic by influencing individual decisions directly, and the social network in which they are made. We simulated a dynamic multiplex network model—with coupled infection and communication layers—to examine behavioral impacts from the nature and scale of epidemiological information reporting. We explored how adherence to protective behaviors (social distancing) can be facilitated through epidemiological reporting, social construction of perceived risk, and local monitoring of direct connections, but eroded via social reassurance. We varied reported information (total active cases, daily new cases, hospitalizations, hospital capacity exceeded, or deaths) at one of two scales (population level or community level). Total active and new case reporting at the population level were the most effective approaches, relative to the other reporting approaches. Case reporting, which synergizes with test-trace-and-isolate and vaccination policies, should remain a priority throughout an epidemic.
Problem definition: We study the emerging practice of using opaque selling to dispose of leftover inventory in vertically differentiated markets. With this selling strategy, a firm offers a synthetic product (after the regular selling season) for which consumers do not know the exact identity until after purchase. Academic/practical relevance: This opaque-selling strategy is implemented in several industries—for example, travel and retail. However, its mechanisms are yet to be fully understood, as the extant literature considers other settings wherein opaque selling’s mechanisms do not carry over to ours. Methodology: We develop a game-theoretic model featuring a firm’s inventory and dynamic selling strategies and consumers’ strategic waiting. We characterize the optimal inventory levels, product offerings, and prices. Results: We find that, compared with last-minute selling (i.e., selling leftover inventory separately), opaque selling increases regular-season profits by softening intertemporal cannibalization from sales-season products to high-quality products sold in the regular season. However, it may decrease sales-season profits, as products with different qualities are probabilistically allocated to all purchasing consumers, irrespective of their valuations. We further demonstrate that these mechanisms are fundamentally different from those identified in the literature for other settings, and this contrast generates opposite recommendations as for the optimal usage of opaque selling. With endogenous inventory, interestingly, opaque selling is even more attractive, and it prompts the firm to procure fewer high-quality products than under last-minute selling. Managerial implications: We demonstrate the value of opaque selling as an inventory-clearance strategy in vertical markets. We show that a firm can further strengthen its profitability by combining opaque selling with inventory management. We also provide guidelines on managing inventory and illustrate the nontrivial impact of opaque selling.
The fall armyworm ( Spodoptera frugiperda ) is a highly polyphagous lepidopteran pest of relevant food and fiber staple crops. In the Americas, transgenic corn and cotton producing insecticidal proteins from the bacterium Bacillus thuringiensis (Bt) have controlled and reduced the damage caused by S. frugiperda . However, cases of field-evolved S. frugiperda resistance to Bt corn producing the Cry1F insecticidal protein have been documented in North and South America. When characterized, field resistance to Cry1F is linked to insertions and mutations resulting in a modified or truncated ABC transporter subfamily C2 ( SfABCC2 ) protein that serves as Cry1F receptor in susceptible S. frugiperda . In this work, we present detection of a large genomic deletion (~ 8 kb) affecting the SfABCC2 and an ABC transporter gene subfamily 3 –like gene ( SfABCC3 ) as linked to resistance to Cry1F corn in a S . frugiperda strain from Florida (FL39). Monitoring for this genomic deletion using a discriminatory PCR reaction in field-collected S. frugiperda moths detected individuals carrying this allele in Florida, but not in surrounding states. This is the first report of a large genomic deletion being involved in resistance to a Bt insecticidal protein.
The current approaches toward synthesis of conjugated microporous polymers (CMPs) functionalized by aza‐fused functionalities are still limited to solution‐based procedures or ionothermal polymerizations, which requires monomers with rigid/high steric hindrance structures and multiple reactive sites and extra arene‐based cross‐linkers, and generated CMPs with low content of aza‐fused functionalities. Herein, a facile mechanochemistry‐driven procedure is developed capable of affording a series of CMPs composed of abundant aza‐fused functionalities via a homocoupling process. Simple and linear aromatic bromide monomers with phenanthroline or bipyridine cores are deployed as the starting materials, which can coordinate on the metal surface to form 3D assembly and be polymerized in the presence of catalytic amount of magnesium powder driven by mechanochemical treatment under solvent‐ and additive‐free conditions. CMPs composed of solely phenanthroline or bipyridine moieties being connected by C–C bonds are afforded with high surface areas (up to 789 m² g‐1), permanent and hierarchical porous architectures (micro‐ and mesopores), abundant aza‐fused moieties, and π‐conjugated networks. All these unique features made them promising candidates as supercapacitors, which exhibit outstanding electrocapacitive performance with a capacitance of 296 F g‐1 at 0.3 A g‐1 and capacitance retention of 103% for 5000 cycles at 5 A g‐1.
Pancreatic β-cells are prone to endoplasmic reticulum (ER) stress due to their role in insulin secretion. They require sustainable and efficient adaptive stress responses to cope with this stress. Whether episodes of chronic stress directly compromise β-cell identity is unknown. We show here under reversible, chronic stress conditions β-cells undergo transcriptional and translational reprogramming associated with impaired expression of regulators of β-cell function and identity. Upon recovery from stress, β-cells regain their identity and function, indicating a high degree of adaptive plasticity. Remarkably, while β-cells show resilience to episodic ER stress, when episodes exceed a threshold, β-cell identity is gradually lost. Single cell RNA-sequencing analysis of islets from type 1 diabetes patients indicates severe deregulation of the chronic stress-adaptation program and reveals novel biomarkers of diabetes progression. Our results suggest β-cell adaptive exhaustion contributes to diabetes pathogenesis.
Infections by maternally inherited bacterial endosymbionts, especially Wolbachia , are common in insects and other invertebrates but infection dynamics across species ranges are largely under studied. Specifically, we lack a broad understanding of the origin of Wolbachia infections in novel hosts and the factors governing their spread. We used Genotype-by-Sequencing (GBS) data from previous population genomics studies for range-wide surveys of Wolbachia presence and genetic diversity in over 2,700 North American butterflies of the genus Lycaeides . As few as one sequence read identified by assembly to a Wolbachia pan-reference genome provided high accuracy in detecting infections as determined by confirmatory PCR tests. Using a conservative threshold of five reads, we detected Wolbachia in all but two of the 107 sampling localities spanning the continent, and with most localities having high infection frequencies (mean = 91\% infection rate). Three major lineages of Wolbachia were identified as separate strains that appear to represent three separate invasions of Lycaeides butterflies. Overall, we found extensive evidence for acquisition of Wolbachia through interspecific transfer between host lineages. Strain wLyc C was confined to a single butterfly taxon, hybrid lineages derived from it, and closely adjacent populations in other taxa. While the other two strains were detected throughout the rest of the continent, strain wLyc B almost always co-occurred with wLyc A. Our demographic modeling suggests wLyc B is a recent invasion. These results demonstrate the utility of using resequencing data from hosts to quantify Wolbachia genetic variation and provide evidence of multiple colonizations of novel hosts through hybridization between butterfly lineages and complex dynamics between Wolbachia strains.
Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive search and optimization problems. These algorithms excel at keeping large clusters fully utilized, but may sometimes inefficiently sample an excess of fast‐evaluating solutions at the expense of higher‐quality, slow‐evaluating ones. We have previously introduced a steady‐state parent selection strategy, SWEET (“Selection whilE EvaluaTing”), that sometimes selects individuals that are still being evaluated and allows them to reproduce early. We perform a takeover‐time analysis that confirms that this strategy gives slow‐evaluating individuals that have higher fitnesses an increased ability to multiply in the population. We also find that SWEET appears effective at improving optimization performance on problems in which solution quality is positively correlated with evaluation time. We evaluate our approach on six simulated real‐valued optimization problems and three real‐world applications: an autonomous vehicle controller problem that involves tuning a spiking neural network and two adversarial EA problems. We further evaluate SWEET versus a basic asynchronous process in a simulated setting. We present evidence that SWEET outperforms basic asynchronous processes in a use‐case in which performance is positively correlated with evaluation time, and performs comparably (and often better) than basic asynchronous processes in several use‐cases where performance is negatively correlated with evaluation time. That said, in the cases where performance and evaluation time are negatively correlated the variance of outcomes for SWEET is notably high.
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Francisco N. Barrera
  • Department of Biochemistry and Cellular and Molecular Biology
Dima Bolmatov
  • Department of Physics & Astronomy
University of Tennessee, 37996-4518, Knoxville, TN, United States