University of Louisiana at Lafayette

Smoothed cepstral peak prominence (CPPs) is a measurement of the distance from the prominent cepstral peak to the linear regression line directly beneath it. Variations of CPPs data acquisition and analysis lead to the complexity of the clinical cut-off values, and there are no agreeable values for a specific voice disorder, such as hypokinetic dysarthria associated with Parkinson’s disease (PD). This study examined the CPPs in people with hypokinetic dysarthria associated with PD compared with healthy participants. Results demonstrated significant differences in speech tasks of sustained vowel and connected speech, with CPPs of connected speech more sensitive to dysphonia and gender difference in PD participants. Males in PD participants presented higher CPPs for sustained vowels and lower CPPs for connected speech than females. It is implied that a consistent clinical application protocol is necessary, and multiple acoustic measures are needed to ensure the accuracy of clinical decisions.

The public’s attitudes can affect the experience of stuttering of people who stutter. This study investigated the attitudes held by the public about people who stutter in China. A web-based written survey with closed and open-ended questions was implemented to develop a rich understanding. One hundred and two respondents in 26 provinces and 3 municipalities provided comments on people who stutter in their life aspects such as personality, speech, social life, work, life participation, education, dating and marriage, capability, and communication skills. The predominantly negative attitudes towards the overall domains were identified. Attitudes to people who stutter varied according to the different sources of knowledge. Familiarity with people who stutter might reduce stereotypes. However, knowledge from the media might aggravate stereotypes. Implications and future research orientation were also discussed.

In this paper, we numerically investigate the impact of shape factor (k) on the mode properties of graded-index ring-core fiber (GIRCF). A 50 mol% Ge-doped GIRCF with shape factor of 2 is devised to generate supercontinuum (SC) carrying orbital angular momentum (OAM) modes, which possesses flat dispersion with a minor variation of < ± 30 ps/nm/km from 1090 to 2590 nm. The generated supercontinuum (SC) in the designed GIRCF carrying OAM1,1 mode covers 2305-nm wavelength range from 750 to 3055 nm at − 40 dB level. The graded refractive index profile (RIP), introduced as a new parameter, offers an additional dimension for the design of ring-core fiber (RCF) supporting OAM modes. The graded RIP contributes to the creation of flat and near-zero dispersion in the RCF structures and reduces the spin–orbit coupling (SOC) effect at the material boundary, leading to broader spectral coverage and higher mode purity in the output spectra.

Hyperdimensional computing (HDC) has emerged as a promising paradigm offering lightweight yet powerful computing capabilities with inherent learning characteristics. By leveraging binary hyperdimensional vectors, HDC facilitates efficient and robust data processing, surpassing traditional machine learning (ML) approaches in terms of both speed and resilience. This letter addresses key challenges in HDC systems, particularly the conversion of data into the hyperdimensional domain and the integration of HDC with conventional ML frameworks. We propose a novel solution, the hyperdimensional vector quantized variational auto encoder (HDVQ-VAE), which seamlessly merges binary encodings with codebook representations in ML systems. Our approach significantly reduces memory overhead while enhancing training by replacing traditional codebooks with binary (−1, +1) counterparts. Leveraging this architecture, we demonstrate improved encoding-decoding procedures, producing high-quality images within acceptable peak signal-to-noise ratio (PSNR) ranges. Our work advances HDC by considering efficient ML system deployment to embedded systems.

Substantial evidence suggests that biodiversity can stabilize ecosystem function, but how it does this is less clear. In very general terms, the hypothesis is that biodiversity stabilizes function because having more species increases the role of compensatory dynamics, which occur when species in a community show different responses to the environment. Here, we focus on two forms of compensatory dynamics, cross‐scale redundancy (CSR) and response diversity (RD). CSR occurs when species respond to a disturbance at different scales such that scale‐specific disturbances do not negatively affect all species. RD occurs when species contributing to the same function show different responses to an environmental change. We developed a new analytical approach that can compare the strength of CSR and RD in the same dataset and used it to study native bee pollination of blueberry at 16 farms that varied in surrounding agricultural land use. We then asked whether CSR and RD among bee species are associated with the stability of blueberry pollination. Although CSR and RD were both present, only RD was associated with higher stability of pollination. Furthermore, the effects of RD on stability were due to a single widespread species, Andrena bradleyi, that is a specialist on blueberry and, unlike other bee species, was highly abundant at farms surrounded by intensive blueberry agriculture. Thus, the stabilizing effect we observed was attributable to an “identity effect” more than to species richness per se. Our results demonstrate how CSR and RD can be empirically measured and compared and highlight how the theoretical expectations of the biodiversity–ecosystem functioning field are not always upheld when confronted with real‐world data.

This study objective to assess the effects of Waste Engine Oil (WEO) and Sasobit on improving the rheological and physicochemical properties of Reclaimed Asphalt Pavement (RAP), both of which are considered waste materials. Seven asphalt mixes were prepared with varying percentages of these materials. The study included rheological testing, Fourier Transform Infrared Spectroscopy (FTIR) analysis, cost-benefit analysis, and final stage to select blend selection. Highway agencies typically limit RAP usage to 20% due to concerns such as fatigue and low-temperature cracking. To address these issues and increase the RAP content, rejuvenators are often required to soften the aged binder. This study investigated the use of WEO and Sasobit as rejuvenators, with WEO added at dosages of 4% and 8%, and Sasobit at 1%, 2%, and 3%. The penetration and viscosity methods were employed to determine the optimal amounts of WEO and Sasobit. The selected mixtures were tested for rutting resistance, fatigue performance, and low-temperature cracking susceptibility. FTIR was used to further analyze the blends, along with a cost analysis. The results indicated that 4% WEO was effective in rejuvenating 25% of the reclaimed binder, offering a cost-effective solution. While Sasobit did not function as a rejuvenator, it proved beneficial as a viscosity reducer.

Biological invasions significantly impact native ecosystems, altering ecological processes and community behaviors through predation and competition. The introduction of non-native species can lead to either coexistence or extinction within local habitats. Our research develops a lizard population model that integrates aspects of competition, intraguild predation, and the dispersal behavior of intraguild prey. We analyze the model to determine the existence and stability of various ecological equilibria, uncovering the potential for bistability under certain conditions. By employing the dispersal rate as a bifurcation parameter, we reveal complex bifurcation dynamics associated with the positive equilibrium. Additionally, we conduct a two-parameter bifurcation analysis to investigate the combined impact of dispersal and intraguild predation on ecological structures. Our findings indicate that intraguild predation not only influences the movement patterns of brown anoles but also plays a crucial role in sustaining the coexistence of different lizard species in diverse habitats.

This paper addresses the pressing issue of diabetes, which is a widespread condition affecting a huge population worldwide. As cells become less responsive to insulin or fail to produce it adequately, blood sugar levels rise. This has the potential to cause severe health complications including kidney disease, vision impairment and heart conditions. Early diagnosis is paramount in mitigating the risk and severity of diabetes-related complications. To tackle this, we proposed a robust framework for diabetes prediction using Synthetic Minority Over-sampling Technique (SMOTE) with ensemble machine learning techniques. Our approach incorporates strategies such as imputation of missing values, outlier rejection, feature selection using correlation analysis and class distribution balancing using SMOTE. The extensive experimentation shows that the proposed combination of AdaBoost and XGBoost shows exceptional performance, with an impressive AUC of 0.968+/-0.015. This outperforms not only alternative methodologies presented in our study but also surpasses current state-of-the-art results. We anticipate that our model will significantly improve diabetes prediction, offering a promising avenue for improved healthcare outcomes in diabetes management.

Community structure and ecosystem function may be driven by the size or the energy within a given habitat, but these metrics (space and energy) are difficult to separate, especially in systems where the habitat itself is also food, such as detritus. Only a handful of studies have attempted to isolate potential mechanisms experimentally, which has left a notable knowledge gap in understanding the drivers of community structure and function. Here, we tested whether fine woody debris (FWD) affects leaf litter communities primarily as a source of space or energy. We used a crossed factor design to isolate the effects of FWD as space and energy, with four treatments: (1) no FWD, (2) only energy‐providing FWD (sawdust), (3) only space‐providing synthetic wood debris, and (4) a combination of both space and energy. We hypothesized that the highest levels of diversity, carnivore:detritivore ratio, and decomposition rate would occur on plots supplied with sawdust (representing energy), synthetic woody debris (representing space), or a combination of both, depending on the relative significance of FWD as a source of either energy or space. After 7 months, FWD as a source of energy but not space led to decreased decomposer abundance and richness. Conversely, increased proportion of carnivores and labile substrate decomposition was primarily driven by FWD as a source of space. However, the fastest decomposition of more recalcitrant substrates required both space and energy (additive), and the synergy of space and energy supported the greatest proportion of carnivores. These results suggest that the presence of FWD in forest ecosystems supports increased diversity and decomposition through a synergistic interaction of space and energy and the maintenance of deadwood like FWD in forest ecosystems can thus significantly contribute to forest ecosystem function.

Nucleic acids consist of nucleobases characterized by unique structures crucial for maintaining their genomic functions and overall structure. This includes a conjugated π-system, a key element supporting the helical structure of double-helix DNA through π–π interactions. Despite this advantageous structural feature, the presence of π-electrons in organic molecules inevitably results in a bathochromic shift in their electronic absorption spectra compared to their saturated counterparts. Consequently, nucleobases may absorb wavelengths that penetrate Earth’s atmosphere, leading to electronic excitations that promote nucleic acid damage and potential cancer. Computational chemistry has proven indispensable in complementing experimental observations and elucidating the active mechanisms through which nucleic acid constituents manage the energy afforded from electronic excitation. A variety of computational methods, spanning static electronic structure calculations to multi- and full-dimensional molecular dynamics simulations, have been employed to offer accurate insights into the photophysics and photochemistry of active excited states in nucleic acid constituents. This chapter provides an overview of some widely used computational approaches for unraveling the fate of excited states in nucleic acid constituents, along with a review of how computational chemistry has revealed the active chemical mechanisms and dynamics involved in photoexcited nucleic acid constituents.

Speeding has been distinguished as one of the most frequent and persistent contributing factors and is a critical contributing factor to the degree of injury severity. In the United States, at least a quarter of nationwide annual fatal crashes during the last decade involved speeding. There is still a need for an overarching look at crashes involving speeding by considering a wider set of crashes, roadway, driver, and vehicle characteristics. Despite extensive research on speeding-related crashes, there is limited understanding of how collective variables in homogeneous crash clusters contribute to fatal speeding crashes. This paper addresses this gap by investigating these collective impacts using fatal crash data from the Fatality Analysis Reporting System (FARS). Using crash data from the 2015–2019 FARS repository, this study applies latent class clustering (LCC) to obtain homogeneous clusters of fatal speeding crashes, addressing the unobserved heterogeneity. Association rule mining (ARM) has been applied to homogeneous clusters to find hidden patterns. The finding of association rules, such as motorcycle speeding, single vehicle crashes during weekends, in dark, unlit conditions, etc. The results of this research and interpretative findings are expected to improve the knowledge of speeding-related crash mechanisms and to provide important insights on countermeasure development.

Previous scholarly investigations of the effectiveness of political lobbying are abundant but have not yet reached a consensus. This study incorporates the work of Adam Smith, Vernon Smith, and Deidre McCloskey to consider the question from a new perspective, that of humanomics, with its emphasis on the efficacy and significance of human relationships. In doing so, we test the proposition that lobbying is neither a one-time quid pro quo nor reducible to dollars and cents but most often is based on a relationship between the lobbyist and the lobbied that has developed over time. We explore the impact of a more powerful executive branch by analyzing the efforts to lobby people who are or may become governors of US states. We estimate the effect of new term limits for state legislators (adopted from 2000 to 2015) on political donations to governors, lieutenant governors, attorneys general, and secretaries of state. If, as we suspect, shorter terms of office for legislators undermine the likelihood of durable lobbyist-legislator relationships, it follows that lobbyists will shift their focus, proxied by repeat-contribution behavior, toward the executive branch. Our findings indicate that that, indeed, is what happens, offering empirical evidence that relationship-building over time is a key component of the effort to exercise political influence.

Injecting carbon dioxide (CO2) into subsea water zones where the in situ temperatures are below the hydrate‐forming temperature of CO2 has been recently proposed to lock CO2 inside the water zones in solid hydrate form. It is a common concern that CO2 may form hydrates during the injection period that will reduce well injectivity. CO2 injection into sandstone cores under simulated subsea temperatures of 2°C and 3°C was investigated in this study. Experimental result shows that, at 2°C temperature, flowing CO2 at Darcy velocity 0.033 cm/s begins to form hydrate in the sandstone core at about 3.06 MPa (450 psi), which is much higher than the minimum required pressure of 1.5 MPa (220 psi) for CO2 to form hydrate in static condition. The pressure ratio is 450/220 = 2.05. At 3°C temperature, flowing CO2 at Darcy velocity 0.045 cm/s begins to form hydrate in sandstone core at about 3.67 MPa (540 psi), which is much higher than the minimum required pressure of 1.87 MPa (275 psi) for CO2 to form hydrate in static conditions. The pressure ratio is 540/275 = 1.96. The reason why the required minimum pressure for CO2 to form hydrates in dynamic conditions is about double the required hydrate‐forming pressure in static conditions is not fully understood. It is speculated that the shear rate effect of flowing fluids should slow down the growth of hydrate crystals or break down hydrate films, resulting in delayed formation of bulk CO2 hydrates. More investigations in this area are needed in the future.