Evaluation of Fluridone in Rice

The increasing pressure of Palmer amaranth [Amaranthus palmeri (S.) Watson] in rice (Oryza sativa L.) fields demands new chemical control options to manage this weed. The recent labeling of fluridone on this crop from the three-leaf rice stage offers an additional residual herbicide for battling Palmer amaranth; however, research is needed to evaluate its effectiveness and rice tolerance. Field experiments were conducted to evaluate Palmer amaranth control and rice tolerance to fluridone across different locations in Arkansas in 2022, 2023, and 2024. Preemergence (PRE) applications of fluridone at 168 g ai ha⁻1; (1× label rate) and 336 g ai ha⁻1; (2× label rate) caused severe crop injury to several rice cultivars, leading to grain yield reductions of up to 49% in eight of the most commonly grown cultivars in Arkansas in a flooded rice production. The cultivar DG263L exhibited injury levels of up to 50% and 32% following PRE and three-leaf applications at the 1× rate, respectively, with yield reductions observed at both application timings, indicating low tolerance to fluridone. When comparing ten application timings from 20 days preplant to postflood applications, the treatments near planting caused the greatest injury to rice grown in a delayed-flood system and the applications at PRE and delayed-preemergence decreased rice grain yield. Therefore, fluridone should not be used at early rice stages, as indicated by the label. Additionally, fluridone applied in mixture with standard rice herbicides at the three-leaf growth stage increased injury by up to 8 percentage points compared to the standard herbicide alone. No yield or groundcover reductions were detected with the addition of fluridone, indicating this herbicide can be applied with other rice herbicides for improved weed control while posing minimal risk to the crop. In a furrow-irrigated rice system, PRE applications of fluridone at the 2× label rate caused 8% to 34% injury; however, no yield reduction was observed. In the same system, fluridone at the 1× and 2× label rates reduced Palmer amaranth density by at least 65% and 88%, respectively, four weeks after treatment compared to the nontreated control. Furthermore, the addition of florpyrauxifen-benzyl postemergence following a PRE application of fluridone at 0.5×, 1×, or 2× label rates reduced Palmer amaranth escapes and decreased seed production by at least 94% compared to fluridone alone at rice maturity. Although florpyrauxifen-benzyl resulted in lower weed densities at the end of the season, the presence of remaining weeds likely contributed to lower rice grain yield compared to treatments where no weeds were present. Thus, sequential applications of other effective herbicides are necessary for season-long Palmer amaranth management

Assessing Biochar and Industrial Hemp to Remediate Heavy-metal-contaminated Soil

Environmental degradation is becoming increasingly prevalent as global industrialization runs rampant. Anthropogenic activity, such as mining, deposits inorganic pollutants into the environment, leading to potential soil and water contamination. Traditional, engineering-based remediation and containment procedures alter soil structure and aggregate stability and affect the biological function of the area impacted by mining activities. Phytoremediation is a more energy-efficient, and therefore cost-effective, method of environmental restoration. Phytoremediation, on its own, works in soils that are less contaminated so that the selected plant can actually grow. Soil amendments, such as biochar, can be added to improve remediation potential in more contaminated soils. The objective of this study was to evaluate the effects of soil-contamination level (i.e., low, medium, and high), industrial hemp (Cannabis sativa L.) cultivar (i.e., \u27Carmagnola\u27and \u27Jinma\u27), Douglas fir (Pseudotsuga menziesii)-derived biochar rate (i.e., 0, 2, 5, and 10% by volume), and their interactions on root tissue Cd, Pb, and Zn concentrations and uptakes, whole-plant Cd, Pb, and Zn uptakes, and translocation factors after 90 days of hemp growth in contaminated soil from the Tar Creek Superfund Site near Picher, Oklahoma. Hemp removal of Cd, Pb, and Zn differed among soil-contamination levels (P \u3c 0.01), but was unaffected (P\u3e 0.05) by hemp cultivar or biochar rate, except for total Zn uptake. Total Cd uptake was greatest from the high- (0.0058 mg cm-2), which did not differ from the medium-, and was significantly greater than from the low-contaminated soil (0.0004 mg cm-2). Total Pb uptake was greatest from the high- (0.09 mg cm-2) than the other two soils, while the medium- (0.0084 mg cm-2) was also greater than from the low-contaminated soil (0.0031 mg cm-2). Total Zn uptake was affected (P = 0.02) by biochar rate in the medium- and high-contaminated soils, where total plant Zn uptake in the high- was numerically largest with 10% biochar (0.28 mg cm-2) and, in the medium- was numerically largest with 2% biochar (0.07 mg cm-2), but was unaffected (P \u3e 0.05) by biochar rate in the low-contaminated soil. The translocation factor for Zn uptake in the low and medium soils was \u3e 1, indicating industrial hemp as a potential Zn hyperaccumulator up to a threshold soil-contamination level. Results demonstrate that biochar amendment has the potential to enhance hemp’s ability to remediate heavy-metal-contaminated soils

Liquid-Liquid Crystal Phase Separation in Solutions of Binary Rod-like Systems

Liquid-liquid crystalline phase separation (LLCPS) is an intricate phenomenon observed in the presence of LC-forming molecule governed by intricate molecular interactions and thermodynamic forces. LLCPS manifests as the demixing of a solution into two distinct phases: a dense phase enriched with LC-forming components coexisting with a supernatant phase depleted in LC content. In this study, we highlight the interplay between lyotropic chromonic liquid crystals (LCLCs) and other rod-like molecules, leading to LLCPS. We note that the phase separation can be associative or segregative. Associative phase separation, more commonly known as complex coacervation, arises due to an attractive interaction such as charge-based interactions, hydrogen bonding, hydrophobic interactions, and π-π interactions between two molecules. The basic form of LC coacervation consists of an LC-forming molecule and an oppositely charged polyelectrolyte. Here, the dense (coacervate phase) consists of the LC-forming molecule and the polyelectrolyte, while the supernatant is mostly water. We uncover surprising LC coacervate droplets with sensitive and unique optical properties that can be influenced by external stimuli. We exploit chiral LCLCs – induced by chiral molecules dopants to explore the role of chirality in the type of complex formed (isotropic or nematic). The primary mechanism that drives segregative LLCPS is the entropic depletion force, which arises when large particles are placed in a solution of smaller ones and sterically constrained to avoid them. Existing studies have however largely focused on understanding LLCPS from the lens of the participating polymers/particles being spherical/isotropic, rather than rod-shaped, despite the prevalence of rod-shaped biopolymers participating in LLCPS in vivo. We harnessed the LLCPS phenomena of rod-shaped particles to eventuate the development of biosensors for DNA. We emphasize that the biosensing mechanism and/or the sensitivity achieved with rod-shaped particles is unattainable with their spherical counterparts

Parole Predictions: Estimating the Likelihood a Humanitarian Parole Group will Receive a Status Adjustment

Humanitarian parole is an immigration policy that allows paroled individuals to enter or remain in the United States temporarily. The standard pathway for parolees to gain legal permanent residency (LPR) is limited by a number of requirements and restrictions, i.e., sponsorship from a family member or employer is usually required. However, in some instances, laws have been passed that grant an automatic adjustment to LPR status for select groups of parolees. This study is intended to investigate the circumstances that lead some groups to receive a status adjustment while other groups are denied a dedicated pathway to legal permanent residency. Specifically, this paper asks what variables best predict if a group paroled into the United States will receive a status adjustment. Using logit regression, I find that the group majority religion and group majority ethnicity have no statistically significant relationship with the granting of a status adjustment. Data analysis indicates that as the polarization level during the year a parole group is recognized increases, the probability that a group will receive a status adjustment decreases

Analyzing the Imposition of Colonial Culture: The Case of French Colonial Education in Senegal

This paper analyzes the implications of the implementation of colonial education through a focus on French West Africa, specifically Senegal. Through analyzing works regarding to colonial and post-colonial era, this paper works to understand how French colonial education systems have impacted education in Senegal. It provides background on French colonialism and the Senegalese education system while exploring and comparing both Anglophone and Francophone works to identify how the literature can work together to further research in the field

Ecological Interactions of Large Mammals in Luangwa, Zambia

The connection between mammalian behavior in national parks and human-driven environmental change is tenuous. National parks are often considered the last vestiges of natural space, yet they are created and maintained by humans. South Luangwa National Park (SLNP) within the southern East African Rift is a microcosm of this global conundrum and is also a region where stable isotope data is sparce. Understanding the mammalian diets of mammals in the SLNP via carbon and oxygen stable isotopes in teeth will provide a means of understanding variation in one aspect of mammal behavior that may be affected by changing animal-human relationships. Here, we present mammalian carbon and oxygen stable isotopes from enamel among large mammals including the hippopotamus, elephants, impala, and buffalo within South Luangwa National Park (n = 32 individuals). Based on carbon isotopes, elephants (Loxodonta africana) show evidence of more exclusive browsing than is common in regions like Mozambique. Buffalo (Syncerus caffer) are grazers, while impala (Aepyceros melampus) are mixed feeders, which is common across parks in Southern Africa. Hippopotamus (Hippopotamus amphibius) are classified as both grazers and mixed feeders. Oxygen isotopes in hippopotamus specimens are generally low but varies by more than 2%. These stable isotopes reveal animal interactions with the environment, but we will also interpret this ecological variation within the context of conservation practice and climate change. This ecological information has implications for human evolution, a discipline which relies heavily on isotope baselines from national parks, and conservation ecology.https://scholarworks.uark.edu/hnrcsturpc25/1013/thumbnail.jp

Subsurface Characterization Using Electrical Resistivity Tomography (ERT) Integrated with MASW, P-Wave Refraction, and Boring Results

Electrical resistivity tomography (ERT) has gained widespread application in geotechnical engineering as a non-invasive method for subsurface characterization. Despite its versatility, several challenges remain regarding its resolution capabilities, interpretive limitations, and integration with other investigative methods. This dissertation addresses three key applications of ERT, focusing on its effectiveness and limitations in resolving thin subsurface layers, detecting anomalies such as voids, and supporting environmental assessment in river restoration projects. The first study investigates the ability of ERT to resolve thin, discontinuous clay layers beneath levees, using the Melvin Price Reach of the Wood River Levee on the Mississippi River as a case study. ERT surveys were conducted along both longitudinal and transverse profiles and were compared with multichannel analysis of surface waves (MASW) and historical boring logs. Results showed that while ERT successfully identified broader stratigraphic trends, its resolution was insufficient to reliably detect thin clay layers critical for evaluating seepage potential and internal erosion risk. The second study evaluates the detectability of subsurface voids of varying sizes and depths in a karst terrain along Texas State Highway 29. A combination of ERT, seismic refraction tomography (SRT), and MASW were employed, along with ground-truthing through boreholes. ERT and SRT provided complementary information, with ERT responding to resistivity contrasts and SRT delineating structural anomalies. MASW, however, was found to be ineffective for this application. The results underscored the importance of a multi-method approach for anomaly detection in complex geological settings. The third study explores the use of ERT for subsurface characterization following dam removal at Little Sugar Creek in Bella Vista, Arkansas. ERT survey lines were integrated with boreholes to assess sediment layering, bedrock depth, and bank stability. ERT proved effective in delineating erodible fine-grained sediments, coarse gravel deposits, and shale or limestone bedrock. These results provided valuable input for restoration design, erosion risk assessment, and geomorphic modeling. Collectively, these studies highlight the potential and limitations of ERT in applied geotechnical and environmental settings. While ERT provides valuable spatial coverage and rapid data acquisition, it requires careful interpretation and is best used in conjunction with other geophysical and geotechnical tools. The findings contribute to improved practices for levee assessment, anomaly detection, and restoration planning, and offer practical recommendations for extending ERT to routine geotechnical investigations and infrastructure monitoring

Molecular Mechanisms Underlying Social Learning in the Butterfly \u3ci\u3eBicyclus anynana\u3c/i\u3e

Learning plays a critical role in shaping behavior, such as influencing survival and reproduction. One particularly important form of learning is mate preference learning, which allows individuals to alter their mate preference based on prior social experience. Among the different types of mate preference learning, imprinting, where early exposure to specific mating cues influences later mate choice, has been widely studied. This process is important in the context of reproductive isolation and speciation, as learned preferences can reinforce or alter eventual mate choice, potentially leading to genetic divergence between populations. Despite its importance, the molecular mechanisms underlying mate preference learning remain largely unexplored. In this dissertation, I explore the genetic and neurogenomic basis of mate preference learning using Bicyclus anynana, a butterfly species that exhibits the ability to learn mate preferences based on early social exposure. I address four key questions: (1) How does the duration of social exposure influence mate preference learning and associated gene expression? (2) What are the molecular pathways underlying positive and negative valence attribution in learned mate preferences? (3) Does the pigmentation gene yellow, known for its pleiotropic role in coloration and courtship, also modulate mate preference learning? (4) How do temporal patterns of gene expression in antennae influence female antennal receptivity? To address these questions, I used behavioral assays, transcriptomic analyses, and genome editing. This integrative approach allows me to identify candidate genes and molecular pathways involved in mate preference learning. By elucidating the genetic architecture of mate preference learning, this research advances our understanding of how learned mate preferences can contribute to reproductive isolation and speciation at a molecular level

Overexpression and Biophysical and Functional Characterization of a Recombinant FGF21

Fibroblast growth factor 21 (FGF21) is an endocrine FGF that plays a vital role in regulating essential metabolic pathways. FGF21 increases glucose uptake by cells, promotes fatty acid oxidation, reduces blood glucose levels, and alleviates metabolic diseases. However, detailed studies on its stability and biophysical characteristics have not been reported. Herein, we present the overexpression, biophysical characterization, and metabolic activity of a soluble recombinant FGF21 (rFGF21). The far-UV circular dichroism spectra of rFGF21 show a negative trough at 215 nm, indicating that the protein’s backbone predominantly adopts a β sheet conformation. rFGF21 shows intrinsic tyrosine fluorescence at 305 nm. Thermal denaturation using differential scanning calorimetry reveals that rFGF21 is relatively thermally unstable, with a melting temperature of 46.8°C (±0.1°C). The urea-induced unfolding of rFGF21 is rapid, with a chemical transition midpoint of 0.4 M. rFGF21 is readily cleaved by trypsin in limited trypsin digestion assays. Isothermal titration calorimetry experiments show that rFGF21 does not bind to heparin. Interestingly, rFGF21 demonstrates proliferative activity in NIH/3T3 fibroblasts and enhances mitochondrial oxidative phosphorylation and fatty acid oxidation in 3T3-L1 adipocytes. These findings provide a crucial framework for the engineering of novel structure-based variants of FGF21 with improved stability and biological activity to treat metabolic disorders

Enhancing The University of Arkansas\u27 Operations Through Data Science

As universities navigate financial constraints and resource allocation challenges, data driven financial analysis has become increasingly important. Universities employ various methods to assess financial efficiency, predict future expenditures, and optimize student credit hour distribution. However, the approaches to financial analysis vary widely, with some institutions leveraging advanced predictive modeling and business intelligence tools, while others rely on traditional budgeting techniques and manual forecasting. This thesis examines how the University of Arkansas\u27 (“Uark”) financial analysis methods compare to those of other institutions and alternative data-driven approaches. Using four years of financial and student credit hour data, this study evaluates cost trends and student credit hour patterns in UArk’s financial management framework. Additionally, a comparative analysis is conducted to assess the strengths and limitations of different financial analysis methodologies. Through this comparison, this research identifies best practices in data-driven financial planning and provides insights into how the University of Arkansas can improve its utilization of data science. The findings contribute to the ongoing discourse on data science applications in institutional decision-making, offering a framework for universities seeking to enhance their budgeting, forecasting, and resource allocation processes