Journal Articles, Multidisciplinary Digital Publishing Institute (MDPI)

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Optimizing Lumber Densification for Mitigating Rolling Shear Failure in Cross-Laminated Timber (CLT)
Pradhan, Suman; Mohammadabadi, Mostafa; Seale, Roy Daniel; Thati, Manikanta; Entsminger, Edward D.; Nkeuwa, William Nguegang (MDPI, 2024-04-04)
Rolling shear in cross-laminated timber (CLT) has been identified as the governing factor influencing design value. Likewise, densification has been found to be an effective method of enhancing the rolling shear strength of lumber and in turn, CLT. In this study, utilizing knowledge of material properties, optimization of the compression ratio for densification has been presented. Three-layered CLT beams made from non-densified lumber, grade #1 loblolly pine (Pinus taeda L.), were subjected to a bending load at a span-to-depth ratio of eight and had a rolling shear failure at the mid-layer with a shear strength of 3 MPa. Assuming the same modulus of rupture (MOR) for both lumber and CLT made from the same species and grade, the MOR of lumber was used to calculate the minimum required shear strength (MRSS) of the transverse mid-layer to change the failure mode of the CLT beam from rolling shear to tensile failure. Using the relationship between the compression ratio and the increase in rolling shear strength, the optimized compression ratio for densification was calculated. This procedure resulted in a compression ratio of 16.67% for densification of the mid-layer to avoid rolling shear in the case of CLT beams with a span-to-depth ratio of eight. To verify this process, CLT beams with mid-layers densified at 16.67% were fabricated and submitted to a bending test. Rolling shear failure was mitigated and densified CLT beams failed in tension with a MOR similar to that of lumber, 47.45 MPa. Likewise, rolling shear strength was observed to increase by 48% for CLT that had a densified mid-layer at 16.67%.
Hemp Seed Yield Responses to Nitrogen Fertility Rates
Podder, Swarup; Shafian, Sanaz; Thomason, Wade E.; Wilson, T. Bain; Fike, John H. (MDPI, 2024-04-11)
Industrial hemp (Cannabis sativa L.) holds promise as a crop for more sustainable supply chains given its potential as a source of high-strength fibers, adsorbents, and nutrient-dense feedstuffs. Developing nutrient management guidelines for hemp will be an important part of optimizing the crop’s sustainability attributes. This study measured hemp seed yield in response to N fertilization rate (0, 60, 120, 180, and 240 kg N ha⁻¹). Treatments were tested with four hemp cultivars (‘Joey’ and ‘Grandi’ in 2020, 2021, and 2022 and ‘NWG 2463’ and ‘NWG 4113’ in 2023) in Virginia. Nitrogen input influenced (p ≤ 0.0177) seed yield in all four experimental years, although the pattern of response varied substantially. In 2020, following delayed seeding, hemp showed a weak quadratic (p = 0.0113) response to N inputs, with peak yield (1640 kg ha⁻¹) occurring with 120 kg N ha⁻¹. In 2021, hemp displayed a strong linear (p < 0.0001) response to N inputs, with the highest seed yield (2510 kg ha⁻¹) at 240 kg N ha⁻¹. In 2022, a season characterized by low precipitation and high weed pressure, a weak, linear (p = 0.0111) response to the N rate was observed. The greatest seed yield (380 kg ha⁻¹) was again observed with 240 kg N ha⁻¹. In 2023, weed pressure remained an issue, but the response to N was strong and linear (p < 0.0001), with the greatest seed yield (831 kg ha⁻¹) again measured at 240 kg N ha⁻¹. These findings indicate hemp can be quite responsive to N inputs but that the magnitude of response is sensitive to other factors such as available soil moisture, weed pressure, and growing period.
Implementation of Numerical Model for Prediction of Temperature Distribution for Metallic-Coated Firefighter Protective Clothing
Naeem, Jawad; Mazari, Adnan; Kus, Zdenek; Havelka, Antonin; Abdelkader, Mohamed (MDPI, 2024-05-21)
The aim of this study is to predict the distribution of temperature at various positions on silver-coated firefighter protective clothing when subjected to external radiant heat flux. This will be helpful in the determination of thermal protective performance. Firefighter clothing consists of three layers, i.e., the outer shell, moisture barrier and thermal liner. The outer shell is the exposed surface, which was coated with silver particles through a physical vapor deposition process called magnetron sputtering. Afterwards, these uncoated and silver-coated samples were exposed to radiant heat transmission equipment at 10 kW/m² as per the ISO 6942 standard. Silver-coated samples displayed better thermal protective performance as the rate of temperature rise in silver-coated samples slowed. Later, a numerical approach was employed, contemplating the impact of metallic coating on the exterior shell. The finite difference method was utilized for solving partial differential equations and the implicit method was employed to discretize the partial differential equations. The numerical model displayed a good prediction of the distribution of temperature at different nodes with respect to time. The comparison of time vs. temperature graphs at different nodes for uncoated and silver-coated samples acquired from numerical solutions showed similar patterns, as witnessed in the experimental results.
Assessing Economic Contributions of the Virginia Seafood Industry: An Estimation Framework Utilizing Primary Data
Gonçalves, Fernando H.; van Senten, Jonathan; Schwarz, Michael H.; Hegde, Shraddha (MDPI, 2024-05-26)
With a focus on seafood industries, this study provides a framework for economic contribution assessments, outlines Virginia’s seafood supply chain components, and evaluates the direct, indirect, and induced economic impacts of Virginia’s seafood industry in 2019. Utilizing an analysis-by-parts method in IMPLAN, primary expenditure data from watermen, aquaculture farmers, processors, and distributors were collected through surveys. The efficacy of obtaining primary data through stakeholder surveys heavily relies on the investigator’s interpersonal skills to establish trust and elucidate the study’s benefits, particularly its potential to inform policy decisions. In 2019, the Virginia seafood industry’s estimated total economic contributions amounted to USD 1.1 billion, supporting 7187 individuals. This impact encompasses 6050 direct jobs, 523 indirect jobs, and 614 induced jobs, primarily benefiting watermen and coastal communities. Furthermore, the industry’s influence extends beyond its immediate economic sphere, supporting diverse sectors such as polystyrene foam manufacturing, boat building, sporting and athletic goods, and commercial and industrial machinery. Wages and salaries disbursed throughout the seafood supply chain ripple to Virginia’s economy, benefiting nondepository credit intermediation, owner-occupied dwellings, and real estate sectors. Future research focusing on seafood sales in restaurants and retail outlets will complete the understanding of the seafood industry’s broader economic impact on the state.
Structural Impediments Impacting Early-Career Women of Color STEM Faculty Careers
Woods, Johnny C.; Lane, Tonisha B.; Huggins, Natali; Leggett Watson, Allyson; Jan, Faika Tahir; Johnson Austin, Saundra; Thomas, Sylvia (MDPI, 2024-05-28)
Women of Color faculty continue to experience many challenges in their careers, especially in the science, technology, engineering, and mathematics (STEM) fields. As such, more research is needed that considers structural issues inhibiting their success. Using structuration theory and critical race feminism as a conceptual framework, we conducted semi-structured interviews with 19 faculty and administrators in STEM departments at higher education institutions to investigate their perceptions of structural impediments impacting early-career Women of Color STEM faculty careers. Our findings revealed the need to establish policies that are clear, documented, and transparent. Additionally, incremental approaches to tenure and promotion evaluations should be reconsidered, especially when this approach may position Women of Color faculty to appear as if they are underperforming, when the opposite may be true. Furthermore, as higher education institutions endeavor to diversify the professoriate, this study is significant in enabling institutions and STEM departments to be aware of systemic issues confronting them to make significant inroads in retaining and advancing Women of Color faculty in these disciplines.
Exploring Students’ Experiences with Mindfulness Meditations in a First-Year General Engineering Course
Martini, Larkin; Huerta, Mark Vincent; Jurkiewicz, Jazmin; Chan, Brian; Bairaktarova, Diana (MDPI, 2024-05-29)
With growing mental health concerns among college students, they need to effectively develop skills to alleviate stress amidst the demands of university life. Teaching mindfulness skills to engineering students early in their programs, such as during introductory courses, may provide students with the tools they need to effectively cope with academic stressors, support well-being, and mitigate mental health concerns. This study aimed to understand the variation in experiences of engineering students who participated in weekly mindfulness meditation during a first-year cornerstone engineering course. This study used a thematic analysis approach to analyze students’ in-class, weekly reflections from eight meditation exercises across two course sections. The frequency of codes and themes were then analyzed across meditation types to identify trends in student experiences. Our results show that the most common student experience from engaging in mindfulness meditation was feeling less stressed, calmer, and more relaxed. Other positive experiences include feeling more energized and focused. Some students, however, did report some negative experiences, such as distress and tiredness. The Dynamic Breathing exercise, in particular, showed higher rates of negative experiences than other meditation types. The results also demonstrate that different types of meditations produce different student experiences. Meditation exercises with open monitoring components showed higher rates of insight/awareness and difficulty focusing attention than focused attention meditations. These findings indicate that utilizing weekly mindfulness exercises in introductory engineering courses can benefit students’ overall mental health and well-being when adequately implemented.
Cost Comparison for Emerging Technologies to Haul Round Bales for the Biorefinery Industry
Cundiff, John S.; Grisso, Robert D.; Webb, Erin G. (MDPI, 2024-05-30)
Between 20 and 30% of the feedstock delivered cost is the highway hauling. In order to achieve maximum truck productivity, and thus minimize hauling cost, the hauling technology needs to provide for rapid loading and unloading. Three prototype technologies have been proposed to address the hauling issue. The first was developed by Stinger to secure a load of large rectangular bales, and it is identified as the Advanced Load Securing System (ALSS). For this study, the ALSS technology is applied on two trailers hooked in tandem (ALSS-2) loaded with 20 bales each. The second technology (Cable), is a cable system for securing a load of bales (round or rectangular) on a standard flatbed trailer. With the third technology (Rack), bales are loaded into a 20-bale rack at an SSL, and this rack is unloaded as a unit at the biorefinery. Bales remain in the rack until processed, thus avoiding single-bale handling at the receiving facility. A cost comparison, which begins with bales in single-layer ambient storage in SSLs and ends with bales in single file on a conveyor into the biorefinery, was done for the three hauling technologies paired with three load-out technologies. Cost for the nine options ranged from 48.56 USD/Mg (11 load-outs, Cable hauling) to 34.90 USD/Mg (8 loads-outs, ALSS-2 hauling). The most significant cost issue was the reduction in truck cost; 25.54 USD/Mg (20 trucks, Cable) and 15.15 USD/Mg (10 trucks, Rack).
Silicon Improves Heat and Drought Stress Tolerance Associated with Antioxidant Enzyme Activity and Root Viability in Creeping Bentgrass (Agrostis stolonifera L.)
Zhang, Xunzhong; Goatley, Mike; Wang, Kehua; Goddard, Ben; Harvey, Rose; Brown, Isabel; Kosiarski, Kelly (MDPI, 2024-05-30)
Creeping bentgrass (Agrostis stolonifera L.) is an important cool-season turfgrass species widely used for golf course putting greens; however, it experiences summer stress and quality decline in the U.S. transition zone and other regions with similar climates. Silicon (Si) may improve the abiotic stress of creeping bentgrass, but the mechanism of its impact on plant drought and heat tolerance is not well understood, and a few studies have reported on the effects of Si on creeping bentgrass drought and heat tolerance. The objectives of this study were to determine the effects of Ortho-silicic acid (Ortho-Si) on antioxidant metabolism and root growth characteristics and viability in creeping bentgrass under drought and heat-stress conditions. The three treatments, including control, Ortho-Si at 0.16 mL m⁻² and 0.32 mL m⁻², were applied biweekly to creeping bentgrass. Foliar application of the Ortho-Si exhibited beneficial effects on turf quality, physiological fitness, and root growth in creeping bentgrass. The Ortho-Si application at 0.16 mL m⁻² and 0.32 mL m⁻² improved turf quality ratings by 9.5% and 11.1%, respectively, photochemical efficiency (PE) by 6.9% and 8.5%, respectively, chlorophyll content by 27.1% and 29.9%, and carotenoids content by 25.5% and 27.2%, respectively, when compared to the control at the end of the trial. The Ortho-Si treatments enhanced antioxidant enzyme activity; the highest amount, in particular, increased superoxide dismutase (SOD) activity by 32.8%, catalase (CAT) by 12.8%, and ascorbate peroxidase (APX) activity by 37.4%, as compared to the control. The Ortho-Si application reduced leaf hydrogen peroxide (H₂O₂) concentration relative to the control. In addition, exogenous Ortho-Si improved leaf Si concentration. The Ortho-Si application at 0.32 mL m⁻² increased root biomass by 52.7% and viability by 89.3% relative to the control. Overall, Ortho-Si at 0.32 mL m⁻² had greater beneficial effects than the low rate (0.16 mL m⁻²). Exogenous Si may improve drought and heat tolerance by protecting photosynthetic function, enhancing the activities of leaf antioxidant enzymes, and stimulating root growth, viability, and Si uptake. The results of this study suggest that foliar application of Ortho-Si at 0.32 mL m⁻² may be considered to be an effective approach to improve turf quality and physiological fitness of creeping bentgrass during the summer months in the U.S. transition zone and other regions with similar climates.
Built On-Orbit Robotically Assembled Gigatruss (BORG): Ground Robotic Demonstration
Chapin, Samantha; Everson, Holly; Chapin, William; Komendera, Erik (MDPI, 2024-05-31)
The next generation of large space infrastructure will require crucial advancements in current technology. Current methodologies focus on large deployable structures folded into cramped payload fairings or revolutionary assembly techniques requiring many moving components. Utilizing both in-space assembly and deployable concepts, a hybrid mixed assembly scheme was posed using smaller deployable units interspersed with rigid connecting elements to assemble these large architectures. The Built On-Orbit Robotically Assembled Gigatruss (BORG) structure allows for modularity in assembly and repair with the number of separate elements comprising the structure to be reduced, compared to strut-by-strut assembly. The following documents the process of constructing and running physical trials on a prototype BORG architecture. Additionally, a Semantic and Fiducial Aided Graph Simultaneous Localization and Mapping (SF-GraphSLAM) approach is taken to verify the relation of assembled and deployed truss elements to aid in error evaluation and state estimation. This technology demonstration stands as a proof of concept in verifying the viability of the BORG architecture as a method for large structure assembly.
An Analysis of Radio Frequency Transfer Learning Behavior
Wong, Lauren J.; Muller, Braeden; McPherson, Sean; Michaels, Alan J. (MDPI, 2024-06-03)
Transfer learning (TL) techniques, which leverage prior knowledge gained from data with different distributions to achieve higher performance and reduced training time, are often used in computer vision (CV) and natural language processing (NLP), but have yet to be fully utilized in the field of radio frequency machine learning (RFML). This work systematically evaluates how the training domain and task, characterized by the transmitter (Tx)/receiver (Rx) hardware and channel environment, impact radio frequency (RF) TL performance for example automatic modulation classification (AMC) and specific emitter identification (SEI) use-cases. Through exhaustive experimentation using carefully curated synthetic and captured datasets with varying signal types, channel types, signal to noise ratios (SNRs), carrier/center frequencys (CFs), frequency offsets (FOs), and Tx and Rx devices, actionable and generalized conclusions are drawn regarding how best to use RF TL techniques for domain adaptation and sequential learning. Consistent with trends identified in other modalities, our results show that RF TL performance is highly dependent on the similarity between the source and target domains/tasks, but also on the relative difficulty of the source and target domains/tasks. Results also discuss the impacts of channel environment and hardware variations on RF TL performance and compare RF TL performance using head re-training and model fine-tuning methods.
Rethinking Productivity Evaluation in Precision Forestry through Dominant Height and Site Index Measurements Using Aerial Laser Scanning LiDAR Data
Raigosa-García, Iván; Rathbun, Leah C.; Cook, Rachel L.; Baker, Justin S.; Corrao, Mark V.; Sumnall, Matthew J. (MDPI, 2024-06-07)
Optimizing forest plantation management has become imperative due to increasing forest product demand, higher fertilization and management costs, declining land availability, increased competition for land use, and the growing demands for carbon sequestration. Precision forestry refers to the ability to use data acquired with technology to support the forest management decision-making process. LiDAR can be used to assess forest metrics such as tree height, topographical position, soil surface attributes, and their combined effects on individual tree growth. LiDAR opens the door to precision silviculture applied at the tree level and can inform precise treatments such as fertilization, thinning, and herbicide application for individual trees. This study uses ALS LiDAR and other ancillary data to assess the effect of scale (i.e., stand, soil type, and microtopography) on dominant height and site index measures within loblolly pine plantations across the southeastern United States. This study shows differences in dominant height and site index across soil types, with even greater differences observed when the interactions of microtopography were considered. These results highlight how precision forestry may provide a unique opportunity for assessing soil and microtopographic information to optimize resource allocation and forest management at an individual tree scale in a scarce higher-priced fertilizer scenario.
Phenotypic Dissection of Drought Tolerance in Virginia and Carolinas within a Recombinant Inbred Line Population Involving a Spanish and a Virginia-Type Peanut Lines
Kumar, Naveen; Haak, David C.; Dunne, Jeffrey C.; Balota, Maria (MDPI, 2024-06-08)
Peanut (Arachis hypogaea L.) is a rainfed crop grown in both tropical and subtropical agro-climatic regions of the world where drought causes around 20% yield losses per year. In the United States, annual losses caused by drought are around $50 million. The objective of this research was to (1) identify genetic variation for the normalized difference vegetation index (NDVI), canopy temperature depression (CTD), relative chlorophyll content by SPAD reading (SCMR), CO₂ assimilation rate, and wilting among recombinant inbred lines (RILs) derived from two diverse parents N08086olJCT and ICGV 86015, to (2) determine if the physiological traits can be used for expediting selection for drought tolerance, and (3) experimental validation to identify lines with improved yield under water-limited conditions. Initially, 337 lines were phenotyped under rainfed production and a selected subset of 52 RILs were tested under rainout shelters, where drought was imposed for eight weeks during the midseason (July and August). We found that under induced drought, pod yield was negatively correlated with wilting and CTD, i.e., cooler canopy and high yield correlated positively with the NDVI and SPAD. These traits could be used to select genotypes with high yields under drought stress. RILs #73, #56, #60, and #31 performed better in terms of yield under both irrigated and drought conditions compared to check varieties Bailey, a popular high-yielding commercial cultivar, and GP-NC WS 17, a drought-tolerant germplasm.
Dietary Phosphorus Levels Influence Protein-Derived Uremic Toxin Production in Nephrectomized Male Rats
Cladis, Dennis P.; Burstad, Kendal M.; Biruete, Annabel; Jannasch, Amber H.; Cooper, Bruce R.; Hill Gallant, Kathleen M. (MDPI, 2024-06-08)
Gut microbiota-derived uremic toxins (UT) accumulate in patients with chronic kidney disease (CKD). Dietary phosphorus and protein restriction are common in CKD treatment, but the relationship between dietary phosphorus, a key nutrient for the gut microbiota, and protein-derived UT is poorly studied. Thus, we explored the relationship between dietary phosphorus and serum UT in CKD rats. For this exploratory study, we used serum samples from a larger study on the effects of dietary phosphorus on intestinal phosphorus absorption in nephrectomized (Nx, n = 22) or sham-operated (sham, n = 18) male Sprague Dawley rats. Rats were randomized to diet treatment groups of low or high phosphorus (0.1% or 1.2% w/w, respectively) for 1 week, with serum trimethylamine oxide (TMAO), indoxyl sulfate (IS), and p-cresol sulfate (pCS) analyzed by LC-MS. Nx rats had significantly higher levels of serum TMAO, IS, and pCS compared to sham rats (all p < 0.0001). IS showed a significant interaction between diet and CKD status, where serum IS was higher with the high-phosphorus diet in both Nx and sham rats, but to a greater extent in the Nx rats. Serum TMAO (p = 0.24) and pCS (p = 0.34) were not affected by dietary phosphorus levels. High dietary phosphorus intake for 1 week results in higher serum IS in both Nx and sham rats. The results of this exploratory study indicate that reducing dietary phosphorus intake in CKD may have beneficial effects on UT accumulation.
Investigation of Viscoelastic Guided Wave Properties in Anisotropic Laminated Composites Using a Legendre Orthogonal Polynomials Expansion–Assisted Viscoelastodynamic Model
Liu, Hongye; Huang, Ziqi; Yin, Zhuang; Sun, Maoxun; Bo, Luyu; Li, Teng; Tian, Zhenhua (MDPI, 2024-06-10)
This study investigates viscoelastic guided wave properties (e.g., complex–wavenumber–, phase–velocity–, and attenuation–frequency relations) for multiple modes, including different orders of antisymmetric, symmetric, and shear horizontal modes in viscoelastic anisotropic laminated composites. To obtain those frequency–dependent relations, a guided wave characteristic equation is formulated based on a Legendre orthogonal polynomials expansion (LOPE)–assisted viscoelastodynamic model, which fuses the hysteretic viscoelastic model–based wave dynamics and the LOPE–based mode shape approximation. Then, the complex–wavenumber–frequency solutions are obtained by solving the characteristic equation using an improved root–finding algorithm, which leverages coefficient matrix determinant ratios and our proposed local tracking windows. To trace the solutions on the dispersion curves of different wave modes and avoid curve–tracing misalignment in regions with phase–velocity curve crossing, we presented a curve–tracing strategy considering wave attenuation. With the LOPE–assisted viscoelastodynamic model, the effects of material viscosity and fiber orientation on different guided wave modes are investigated for unidirectional carbon–fiber–reinforced composites. The results show that the viscosity in the hysteresis model mainly affects the frequency–dependent attenuation of viscoelastic guided waves, while the fiber orientation influences both the phase–velocity and attenuation curves. We expect the theoretical work in this study to facilitate the development of guided wave–based techniques for the NDT and SHM of viscoelastic anisotropic laminated composites.
Flood Pulse Effects on the Growth of Pseudoplatystoma fasciatum in the Amazon Basin
Pereira, Luciana Alves; Castello, Leandro; Hallerman, Eric; Rodrigues, Edson Rubens Ferreira; Doria, Carolina Rodrigues da Costa; Duponchelle, Fabrice (MDPI, 2024-06-12)
Fish growth is a fundamental biological process driven by a multitude of intrinsic (within-individual) and extrinsic (environmental) factors that underpin individual fitness and population dynamics. Interannual variability in river hydrology regarding the intensity and duration of floods and droughts can induce interannual variations in the biotic and abiotic variables that regulate fish growth. However, the understanding of how interannual variability in river hydrology affects fish growth remains limited for most species and ecosystems. We evaluated how inter-annual hydrological variations within the Amazon River basin influence the growth of the catfish Pseudoplaystoma fasciatum. Our research questions were as follows: Do floods lead to the faster growth of P. fasciatum and droughts lead to the slower growth? And do floods and droughts affect all age classes in the same manner? We sampled 364 specimens of P. fasciatum from five sites in the Amazon basin, estimated their growth rates, and related the growth rates to indices of the intensity of floods and droughts. We fitted linear mixed-effects models to test the relationship between growth increments and hydrological indices (with F and D quantifying the intensities of floods and droughts, respectively), age as fixed effects, and basins and Fish ID as random effects. We found an inverse relationship between the increment width in the fish hard parts and hydrological indices. That is, intense floods and droughts negatively affected the growth rates. We also found that the growth of P. fasciatum was no different in years with intense and mild floods across age classes 1–5, although was different for age class 6. However, the growth of P. fasciatum was faster in years of mild droughts for all age classes. Our results showing that the growth of P. fasciatum was slower in years of intense droughts are supported by those of previous studies in the Amazon basin and elsewhere. However, our results showing for the first time that the growth of P. fasciatum is slower in years of intense flooding is the opposite of patterns found in other studies. These results thus suggest that the growth of P. fasciatum is maximized within an optimum range of hydrological conditions, where neither floods nor droughts are intense.
Inspiring Sustainability in Undergraduate Engineering Programs
Griesinger, Tina; Reid, Kenneth; Knight, David; Katz, Andrew; Somers, John (MDPI, 2024-06-13)
The number of engineers who are transitioning into environmental sustainability careers is growing, though a gap still exists between the supply and demand. This presents an opportunity for undergraduate engineering students to fulfill the demand as environmental sustainability professionals. This qualitative exploratory study investigated environmental sustainability learning experiences and future career interests in environmental sustainability. The social cognitive theory (SCCT) was utilized as a theoretical lens, exploring undergraduate students’ environmental sustainability interests, related learning experiences and their interest in pursuing a future career in environmental sustainability. Twenty-five undergraduate engineering students in various engineering disciplines were interviewed for this study. Data were analyzed to (1) identify the students’ interest in pursuing a career in environmental sustainability, (2) determine if the students’ interests have changed since they began their undergraduate studies, and (3) explore how learning experiences have impacted the students’ future career choices. The findings posit that exposure to environmental sustainability learning experiences is impactful and plays an important role, impacting the students’ interests in pursuing careers in sustainability. The results reveal that elements such as personal beliefs and salary considerations inspire career choices. This research contributes to addressing the demand for additional working professionals who are prepared to tackle environmental sustainability issues, highlighting the role of learning experiences in shaping students’ career interests.
From Individual Motivation to Geospatial Epidemiology: A Novel Approach Using Fuzzy Cognitive Maps and Agent-Based Modeling for Large-Scale Disease Spread
Song, Zhenlei; Zhang, Zhe; Lyu, Fangzheng; Bishop, Michael; Liu, Jikun; Chi, Zhaohui (MDPI, 2024-06-13)
In the past few years, there have been many studies addressing the simulation of COVID-19’s spatial transmission model of infectious disease in time. However, very few studies have focused on the effect of the epidemic environment variables in which an individual lives on the individual’s behavioral logic leading to changes in the overall epidemic transmission trend at larger scales. In this study, we applied Fuzzy Cognitive Maps (FCMs) to modeling individual behavioral logistics, combined with Agent-Based Modeling (ABM) to perform “Susceptible—Exposed—Infectious—Removed” (SEIR) simulation of the independent individual behavior affecting the overall trend change. Our objective was to simulate the spatiotemporal spread of diseases using the Bengaluru Urban District, India as a case study. The results show that the simulation results are highly consistent with the observed reality, in terms of trends, with a Root Mean Square Error (RMSE) value of 0.39. Notably, our approach reveals a subtle link between individual motivation and infection-recovery dynamics, highlighting how individual behavior can significantly impact broader patterns of transmission. These insights have potential implications for epidemiologic strategies and public health interventions, providing data-driven insights into behavioral impacts on epidemic spread. By integrating behavioral modeling with epidemic simulation, our study underscores the importance of considering individual and collective behavior in designing sustainable public health policies and interventions.
History of the Development of Knowledge about the Neuroendocrine Control of Ovulation—Recent Knowledge on the Molecular Background
Szabó, Flóra; Köves, Katalin; Gál, Levente (MDPI, 2024-06-13)
The physiology of reproduction has been of interest to researchers for centuries. The purpose of this work is to review the development of our knowledge on the neuroendocrine background of the regulation of ovulation. We first describe the development of the pituitary gland, the structure of the median eminence (ME), the connection between the hypothalamus and the pituitary gland, the ovarian and pituitary hormones involved in ovulation, and the pituitary cell composition. We recall the pioneer physiological and morphological investigations that drove development forward. The description of the supraoptic–paraventricular magnocellular and tuberoinfundibular parvocellular systems and recognizing the role of the hypophysiotropic area were major milestones in understanding the anatomical and physiological basis of reproduction. The discovery of releasing and inhibiting hormones, the significance of pulse and surge generators, the pulsatile secretion of the gonadotropin-releasing hormone (GnRH), and the subsequent pulsatility of luteinizing (LH) and follicle-stimulating hormones (FSH) in the human reproductive physiology were truly transformative. The roles of three critical neuropeptides, kisspeptin (KP), neurokinin B (NKB), and dynorphin (Dy), were also identified. This review also touches on the endocrine background of human infertility and assisted fertilization.
A Camelid-Derived STAT-Specific Nanobody Inhibits Neuroinflammation and Ameliorates Experimental Autoimmune Encephalomyelitis (EAE)
Mbanefo, Evaristus C.; Seifert, Allison; Yadav, Manoj Kumar; Yu, Cheng-Rong; Nagarajan, Vijayaraj; Parihar, Ashutosh; Singh, Sunanda; Egwuagu, Charles E. (MDPI, 2024-06-16)
Proinflammatory T-lymphocytes recruited into the brain and spinal cord mediate multiple sclerosis (MS) and currently there is no cure for MS. IFN-γ-producing Th1 cells induce ascending paralysis in the spinal cord while IL-17-producing Th17 cells mediate cerebellar ataxia. STAT1 and STAT3 are required for Th1 and Th17 development, respectively, and the simultaneous targeting of STAT1 and STAT3 pathways is therefore a potential therapeutic strategy for suppressing disease in the spinal cord and brain. However, the pharmacological targeting of STAT1 and STAT3 presents significant challenges because of their intracellular localization. We have developed a STAT-specific single-domain nanobody (SBT-100) derived from camelids that targets conserved residues in Src homolog 2 (SH2) domains of STAT1 and STAT3. This study investigated whether SBT-100 could suppress experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. We show that SBT-100 ameliorates encephalomyelitis through suppressing the expansion of Th17 and Th1 cells in the brain and spinal cord. Adoptive transfer experiments revealed that lymphocytes from SBT-100-treated EAE mice have reduced capacity to induce EAE, indicating that the immunosuppressive effects derived from the direct suppression of encephalitogenic T-cells. The small size of SBT-100 makes this STAT-specific nanobody a promising immunotherapy for CNS autoimmune diseases, including multiple sclerosis.
Identification and Genomic Characterization of Two Novel Hepatoviruses in Shrews from Yunnan Province, China
Tang, Yi; Zhao, Kai; Yin, Hong-Min; Yang, Li-Ping; Wu, Yue-Chun; Li, Feng-Yi; Yang, Ze; Lu, Hui-Xuan; Wang, Bo; Yang, Yin; Zhang, Yun-Zhi; Yang, Xing-Lou (MDPI, 2024-06-17)
Hepatitis A virus (HAV), a member of the genus Hepatovirus (Picornaviridae HepV), remains a significant viral pathogen, frequently causing enterically transmitted hepatitis worldwide. In this study, we conducted an epidemiological survey of HepVs carried by small terrestrial mammals in the wild in Yunnan Province, China. Utilizing HepV-specific broad-spectrum RT-PCR, next-generation sequencing (NGS), and QNome nanopore sequencing (QNS) techniques, we identified and characterized two novel HepVs provisionally named EpMa-HAV and EpLe-HAV, discovered in the long-tailed mountain shrew (Episoriculus macrurus) and long-tailed brown-toothed shrew (Episoriculus leucops), respectively. Our sequence and phylogenetic analyses of EpMa-HAV and EpLe-HAV indicated that they belong to the species Hepatovirus I (HepV-I) clade II, also known as the Chinese shrew HepV clade. Notably, the codon usage bias pattern of novel shrew HepVs is consistent with that of previously identified Chinese shrew HepV. Furthermore, our structural analysis demonstrated that shrew HepVs differ from other mammalian HepVs in RNA secondary structure and exhibit variances in key protein sites. Overall, the discovery of two novel HepVs in shrews expands the host range of HepV and underscores the existence of genetically diverse animal homologs of human HAV within the genus HepV.

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