Southern Illinois University Carbondale

Fieldwork at Amarna in 2022 included excavation at the Great Aten Temple and the North Desert Cemetery, and the continuation of several post-excavation projects. Those post-excavation projects reported on here are the study of skeletal materials, pottery, plant and organic remains, and inscriptions from the North Desert Cemetery; pottery, plant and other organic remains from the North Cliffs Cemetery; and digital modelling of the North Desert Cemetery. A programme of community outreach in collaboration with the Amarna Visitor Centre also recommenced. [Formula: see text]

Objective This study investigates gender differences in the effect of parents' deaths on sibling tension among bereaved adult children. Background Previous scholarship on adult sibling relations following the deaths of parents presents inconsistent results. These disparate findings may stem from past studies not taking into consideration the gender of both the deceased parent and the bereaved child. Method Analyses are based on three harmonized waves of quantitative and qualitative data collected from 654 adult children nested within 303 families as part of the Within‐Family Differences Study. Results Multilevel models revealed that for daughters, but not sons, mothers' deaths in the past 5 years were associated with increases in sibling tension, whereas fathers' deaths did not predict changes in either sons' or daughters' sibling tension, regardless of timing. Qualitative analyses showed marked differences by child's gender in perceptions of patterns of shared work and support surrounding parents' deaths. Typically, sons expressed solidarity with siblings when mothers died and felt that the division of caregiving prior to mothers' deaths and arrangements following their deaths were fair. In contrast, daughters expressed increased solidarity with sisters surrounding mothers' deaths and disdain toward brothers who failed to contribute caregiving, support, or instrumental tasks. Conclusion These findings underscore how gender of both parents and adult children differentially shape changes in adult children's relationships with their siblings in the face parental deaths, much as they do in other contexts across the life course.

Objective This study utilizes geospatial analytic techniques to examine HIV hotspots in Alabama leveraging Medicaid utilization data. Methods This cross-sectional study leveraged Medicaid utilization data from Alabama’s 67 counties, averaging 9,861 Medicaid recipients aged > 18 years old per county. We used Alabama Medicaid administrative claims data from January 1, 2016, to December 31, 2020, to identify individuals with HIV. Using Microsoft SQL Server, we obtained the average annual count of HIV Medicaid claims in each of the 67 Alabama counties (numerator) and the number of adult Medicaid recipients in each county (denominator), and standardized with a multiplier of 100,000. We also examined several other area-level summary variables (e.g., non-high school completion, income greater than four times the federal poverty level, social associations, urbanicity/rurality) as social and structural determinants of health. County-boundary choropleth maps were created representing the geographic distribution of HIV rates per 100,000 adult Medicaid recipients in Alabama. Leveraging ESRI ArcGIS and local indicators of spatial association (LISA), results were examined using local Moran’s I to identify geographic hotspots. Results Eleven counties had HIV rates higher than 100 per 100,000. Three were hotspots. Being an HIV hotspot was significantly associated with relatively low educational attainment and less severe poverty than other areas in the state. Conclusions Findings suggesting that the HIV clusters in Alabama were categorized by significantly less severe poverty and lower educational attainment can aid ongoing efforts to strategically target resources and end the HIV epidemic in U.S.’ Deep South.

This study applied behavioral economic methods to assess the effects of regulatory cost on demand for the opportunity to practice behavior analysis in Ontario using a hypothetical purchase task. The provincial government of Ontario recently passed legislation to expand the psychology regulatory body to include behavior analysts. Professional regulation has been a key longstanding priority for many professionals in the province and the Ontario Association for Behaviour Analysis (ONTABA, 2021) alike. This is an important step in public protection policy, the professionalization of the practice of applied behavior analysis (ABA), and standards of practice in the province. This study aimed to inform part of the process using an operant demand framework because fees are required to operate regulatory bodies, which implies that professionals interested in becoming regulated health professionals must pay initial and ongoing fees. Demand was analyzed using the exponentiated model of demand. Participants included 60 practitioners, who indicated they were board certified behavior analysts and Ontario residents. The findings indicated that participants’ mean Pmax value (the price at which consumption becomes elastic) was $624.65 at the aggregate level. These results may indicate Ontario behavior analysts’ perceptions of the acceptability of varying costs associated with regulation. Further, the study demonstrates the applied utility of behavioral economic methods to assess demand for commodities within behavior analysis.

Background Because of swift climate change, drought is a primary environmental factor that substantially diminishes plant productivity. Furthermore, the increased use of chemical fertilizers has given rise to numerous environmental problems and health risks. Presently, there is a transition towards biofertilizers to enhance crops’ yield, encompassing medicinal and aromatic varieties. Methods This study aimed to explore the impacts of plant growth-promoting rhizobacteria (PGPR), both independently and in conjunction with arbuscular mycorrhizal fungi (AMF), on various morphological, physiological, and phytochemical characteristics of Dracocephalum kotschyi Boiss. This experimentation took place under different irrigation conditions. The irrigation schemes encompassed well watering (WW), mild water stress (MWS), and severe water stress (SWS). The study evaluated the effects of various biofertilizers, including AMF, PGPR, and the combined application of both AMF and PGPR (AMF + PGPR), compared to a control group where no biofertilizers were applied. Results The findings of the study revealed that under water-stress conditions, the dry yield and relative water content of D. kotschyi Boiss. experienced a decline. However, the application of AMF, PGPR, and AMF + PGPR led to an enhancement in dry yield and relative water content compared to the control group. Among the treatments, the co-application of AMF and PGPR in plants subjected to well watering (WW) exhibited the tallest growth (65 cm), the highest leaf count (187), and the most elevated chlorophyll a (0.59 mg g ⁻¹ fw) and b (0.24 mg g ⁻¹ fw) content. Regarding essential oil production, the maximum content (1.29%) and yield (0.13 g plant ⁻¹ ) were obtained from mild water stress (MWS) treatment. The co-application of AMF and PGPR resulted in the highest essential oil content and yield (1.31% and 0.15 g plant ⁻¹ , respectively). The analysis of D. kotschyi Boiss. essential oil identified twenty-six compounds, with major constituents including geranyl acetate (11.4–18.88%), alpha-pinene (9.33–15.08%), Bis (2-Ethylhexyl) phthalate (8.43-12.8%), neral (6.80–9.32%), geranial (9.23–11.91%), and limonene (5.56–9.12%). Notably, the highest content of geranyl acetate, geranial, limonene, and alpha-pinene was observed in plants subjected to MWS treatment following AMF + PGPR application. Furthermore, the co-application of AMF, PGPR, and severe water stress (SWS) notably increased the total soluble sugar (TSS) and proline content. In conclusion, the results indicate that the combined application of AMF and PGPR can effectively enhance the quantity and quality of essential oil in D. kotschyi Boiss., particularly when the plants are exposed to water deficit stress conditions.

A 35-year-old intramural male athlete presented to the athletic training staff with a 4.5cm x 2.2cm itchy, painful, swollen, and infected insidious skin lesion on his right lateral malleolus due to an underlying dermatological deficiency. Suspecting infection, the patient was referred to his nurse practitioner and was diagnosed with atopic dermatitis caused by a ceramide deficiency. He was placed on Cefalexin and Mupirocin 2% ointment but returned due to the lesion increasing to 8.5cm x 6cm although infection seemed controlled. He was instructed to use Ceravé™ topical cream, Clobetasol propionate 5%, and consume foods rich in healthy oils (omega-3s, olive oil). Unmitigated, this lesion could have resulted in severe infection and tissue damage. Atopic dermatitis is relatively common in the general population but the appearance in healthy athletes highlights that athletic trainers need to be well-versed in not just apparent causes of skin ailments (i.e., infection), but also root causes.

TiO2 nanotubes have been electrochemically reduced to form black TiO2 nanotube (BTNT) electrodes for improved loading and enhanced electrocatalytic properties of Fe2O3 nanoparticles for sensing dopamine. The nanoparticles were electrodeposited on the BTNTs by a chronoamperometric technique. The sensing electrodes were analyzed for their morphological, electrical, and chemical properties using scanning electron microscopy, UV–Vis spectroscopy, x-ray diffractometry, and x-ray photoelectron spectroscopy. All the electrochemical sensing properties of the electrodes were analyzed using cyclic voltammetry and chronoamperometry techniques. The Fe2O3 nanoparticles loaded on the BTNTs showed an excellent sensitivity of 0.81 mA mM−1 cm−2, which is more than 2 times higher compared to Fe2O3 nanoparticles deposited on unreduced TiO2 nanotubes. Further, the sensor was highly selective towards dopamine in comparison to glucose, ascorbic acid, uric acid, and l-cystine. The improved sensing properties are due to the increased electron transfer rate and reduced band gap of the BTNTs (2.9 eV), which provided a higher electrocatalytic current to the Fe2O3 nanoparticles for sensing dopamine. Overall, an efficient dopamine sensor can be developed by using simple electrochemical reduction and electrodeposition techniques.

Background Methamphetamine (meth) use is disproportionately high in rural settings and increased during COVID-19. While sterile syringes services are an evidence-based measure to reduce infectious disease transmission, little research exists around the value of smoking equipment, specifically pipes, in minimizing harms associated with rural drug use in the US. Methods Between March and June 2022, we conducted structured interviews with people who use methamphetamine (PWUM) living in rural Illinois who were at least 15 years old and used meth by any route in the past 30 days. Interview guides explored attitudes and behaviors regarding meth use routes, meth pipe use practice, and pipe access, and were refined by a peer-led Community Advisory Board. Interviews were audio recorded, transcribed, and coded in MAXQDA. The data were then analyzed for emergent themes using modified grounded theory. Results Nineteen participants, average age 37.1 (SD+8.7), were interviewed. Of these, 53% were women, and 89% were white. All reported smoking meth, and 84% injected meth. Participants reported that they often chose to smoke rather than inject to mitigate health concerns like wounds, pain, and infections. Smoking enabled them to use around others as opposed to using alone (as was typical when they injected). Participants expressed interest in pipe distribution through a harm reduction agency, e.g. according to one participant (a 31-year-old white male), “I’ve asked specifically if they had a pipe because I was trying to lay off the syringes.” They related that access to a harm reduction agency distributing pipes would connect people to other services such as HIV testing, naloxone, and safer sex supplies. Conclusion Distribution of meth pipes through harm reduction agencies represents a means for decreasing harm through circumvention of injection, decreased solitary drug use, and linkage to additional services related to overdose and disease prevention. Given increased rates of meth use in rural regions, this intervention could specifically address drug-related harms that impact rural PWUM. Future work should quantitatively explore the health impacts of pipe use as a harm reduction intervention. Disclosures All Authors: No reported disclosures

Intellectual functioning impacts defendants’ competence to stand trial, though research on this population remains limited. This study replicated and advanced prior work, focusing on defendants’ demographic, clinical, cognitive, and criminal justice variables and their association with length of hospitalization and restoration determinations. Participants were 74 male and female criminal defendants in a midwestern state who were adjudicated incompetent to stand trial, had a diagnosis related to intellectual deficits, and completed competency restoration. Most defendants (83.7%) were restored to competency. Demographic factors were unrelated to restoration outcomes; violence of alleged offense predicted shorter hospitalization. Receiver Operating Characteristic Curve analyses determined an IQ score cut-off of 63.5 for which participants were of greater likelihood to be determined restored, providing guidance on the likelihood of restoration for defendants with intellectual disability related diagnoses. Specifically, this score can be used with clinical data to inform competency determinations for defendants with cognitive deficits.

The frequency and duration of Late-Holocene hydrologic extremes in northern Guatemala were investigated using multiple sedimentological and geochemical proxies preserved in a sediment core collected from Lake Petén Itzá. A general trend of increasing aridity in the Maya Lowlands during the past 2000 years was punctuated by several multidecadal- to centennial-scale drought events recorded in the Petén Itzá sediments. In particular, the period spanning the Maya Terminal Classic Period and the Medieval Climate Anomaly (MCA), between 800 and 1300 CE, was marked by several extreme droughts and included the driest conditions of the past 2000 years between 950 and 1100 CE. Similarities between our data and other existing regional paleoclimate records suggest regional drying events during this time may have been driven by a common mechanism. Specifically, comparisons between these records and tropical Atlantic sea surface temperatures (SSTs) suggest that the dry intervals may have been driven by a westward expansion of the North Atlantic Subtropical High pressure system. This period was unique in the general agreement between regional proxy records, which are otherwise notably heterogeneous during the Late-Holocene. During the Little Ice Age (LIA; 1400–1800 CE) mean precipitation at Petén Itzá was further reduced, and multidecadal drying events were recorded between 1500–1530, 1600–1640, and 1770–1800 CE. However, regional hydroclimatic coherency was weaker during the LIA, suggesting that additional climatic mechanisms played a more important role in local-scale hydrology during that time.

The objective of this investigation is to produce maps identifying areas prone to landslides (LSMs) by utilizing multiple machine learning techniques, including the harmony search algorithm (HS), shuffled frog leaping algorithm (SFLA), evaporation rate water cycle algorithm (ERWCA), and whale optimization algorithm (WOA). To create a comprehensive inventory of landslide occurrences, high-resolution satellite imagery, topographic maps, historical records, and GPS data gathered through fieldwork were employed. In total, 402 known landslide sites were used for modeling and validating the landslide occurrences in the study area. Sixteen factors were integrated: topography, hydrology, soil type, geology, and ecology. The training dataset comprised 72% of all landslide locations, while the remaining 28% was used to validate the generated landslide occurrences. The different models were evaluated using the area under the receiver operating characteristic curve. The analysis of both the training and validation datasets was used to determine the model’s accuracy. To improve the performance of the multilayer perceptron neural network architecture, the HS, ERWCA, SFLA, and WOA algorithms were applied to improve its efficiency. The accuracy of the applied prediction models was evaluated using the area under the curve (AUC) measure before creating landslide vulnerability charts in a GIS framework. The results showed that the HS-MLP had the greatest estimated AUCs for population sizes in training databases equal to 50, with values of 0.9921 and 0.9828 for training databases and testing databases, respectively. Similar to this, in the training and testing databases, the AUC values for the ER_WCAMLP with a 200-swarm swarm size were determined to be 0.9998 and 0.9821, respectively. For population sizes of 150 and 500, respectively, the training and testing AUCs for the SFLA-MLP were determined to be 0.984 and 0.9821, and 0.9867 and 0.9873, respectively, for the WOA-MLP. The best solution was found after 50, 200, 150, and 500 iterations for the models that used the population in the best fit HS, ER_WCA, SFLA, and WOA algorithms, respectively. In light of these findings, managers and planners can benefit from this research's findings in pre-crisis management as it demonstrates how optimization algorithms have improved the neural network’s accuracy and performance in the evaluation and detection of problematic areas.

Populations wax and wane over time in response to an organism's interactions with abiotic and biotic forces. Numerous studies demonstrate that fluctuations in local populations can lead to shifts in relative population densities across the geographic range of a species over time. Fewer studies attempt to disentangle the causes of such shifts. Over four decades (1983–2022), we monitored populations of hibernating Indiana bats ( Myotis sodalis ) in two areas separated by ~110 km. The number of bats hibernating in the northern area increased from 1983 to 2011, while populations in the southern area remained relatively constant. We used simulation models and long‐term weather data to demonstrate the duration of time bats must rely on stored fat during hibernation has decreased in both areas over that period, but at a faster rate in the northern area. Likewise, increasing autumn and spring temperatures shortened the periods of sporadic prey (flying insect) availability at the beginning and end of hibernation. Climate change thus increased the viability of northern hibernacula for an increasing number of bats by decreasing energetic costs of hibernation. Then in 2011, white‐nose syndrome (WNS), a disease of hibernating bats that increases energetic costs of hibernation, was detected in the area. From 2011 to 2022, the population rapidly decreased in the northern area and increased in the southern area, completely reversing the northerly shift in population densities associated with climate change. Energy balance during hibernation is the singular link explaining the northerly shift under a changing climate and the southerly shift in response to a novel disease. Continued population persistence suggests that bats may mitigate many impacts of WNS by hibernating farther south, where insects are available longer each year.

Effective streaming feature selection in dynamic online environments is essential in numerous applications. However, most existing methods evaluate high-dimensional features individually and ignore the potentially pertainable group structures of features. Moreover, the class imbalance underlying streaming data may further decrease the discriminative efficacy of the selected features, resulting in deteriorated classification performance. Motivated by this observation, we propose a cost-sensitive sparse group online learning (CSGOL) framework and its proximal version (PCSGOL) to handle imbalanced and high-dimensional streaming data. We formulate this issue as a new cost-sensitive online optimization problem by leveraging the ℓ2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ell _2$$\end{document}-norm, ℓ1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ell _1$$\end{document}-norm, and groupwise sparsity constraints in the dual averaging regularization. Inspired by the proximal optimization, we further introduce the average weighted distance in CSGOL and develop the PCSGOL method to achieve stable prediction results. We mathematically derive closed-form solutions to the optimization problems with four modified hinge loss functions, leading to four variants of CSGOL and PCSGOL. Extensive empirical studies on real-world streaming datasets and online anomaly detection tasks demonstrate the effectiveness of our proposed methods.

A hemispherical‐shaped folded electrically small antenna (ESA) is a well‐known antenna where the radiating conductor is a wire or flat strip of variable width. This work analyzed the performance of strip‐based ESA for a constant strip width and focused on the fabrication procedure which utilizes the low‐cost dielectric material and ubiquitous 3‐D printer. The impact of additional dielectric support on the performance of ESA was investigated. This work also introduced conductive paint for the radiating part, along with metallic wire and strip. There is a good agreement between simulated and measured results. The 3‐D printing technique offers design flexibility, eases fabrication difficulty, reduces material cost, and improves the mechanical stability of the antenna.

Climate models predict that everwet western Amazonian forests will face warmer and wetter atmospheric conditions, and increased cloud cover. It remains unclear how these changes will impact plant reproductive performance, such as flowering, which plays a central role in sustaining food webs and forest regeneration. Warmer and wetter nights may cause reduced flower production, via increased dark respiration rates or alteration in the reliability of flowering cue‐based processes. Additionally, more persistent cloud cover should reduce the amounts of solar irradiance, which could limit flower production. We tested whether interannual variation in flower production has changed in response to fluctuations in irradiance, rainfall, temperature, and relative humidity over 18 yrs in an everwet forest in Ecuador. Analyses of 184 plant species showed that flower production declined as nighttime temperature and relative humidity increased, suggesting that warmer nights and greater atmospheric water saturation negatively impacted reproduction. Species varied in their flowering responses to climatic variables but this variation was not explained by life form or phylogeny. Our results shed light on how plant communities will respond to climatic changes in this everwet region, in which the impacts of these changes have been poorly studied compared with more seasonal Neotropical areas.

The southern root-knot nematode, Meloidogyne incognita (Kofoid and White, 1919) Chitwood, 1949, is one of the most important, yield-limiting pathogens of agronomic and vegetable crops in the United States and worldwide. It was first reported on cotton ( Gossypium hirsutum L.) in Alabama in the United States. Since then, it has been reported in many states across the United States. These reports include detections in greenhouses, nurseries, or home gardens but do not provide information on where this species persists from year to year in field soils. Furthermore, these reports do not provide distribution information within each state in individual counties. This report summarized the distribution of M. incognita on field crops (e.g., agronomic and vegetable crops) by county for each state across the continental United States.