Journal Articles, Multidisciplinary Digital Publishing Institute (MDPI)

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Automated Calibration of SWMM for Improved Stormwater Model Development and Application
Ahmadi, Hossein; Scott, Durelle T.; Sample, David J.; Shahed Behrouz, Mina (MDPI, 2025-05-25)
The fast pace of urban development and increasing intensity of precipitation events have made managing urban stormwater an increasingly difficult challenge. Hydrologic models are commonly used to predict flows and assess the performance of stormwater controls, often based on a hypothetical yet standardized design storm. The Storm Water Management Model (SWMM) is widely used for simulating runoff in urban watersheds. However, calibration of SWMM, as with all hydrologic models, is often plagued with issues such as subjectivity, and an abundance of model parameters, leading to delays and inefficiencies in model development and application. Further development of modeling and simulation tools to aid in design is critical in improving the function of stormwater management systems. To address these issues, we developed an integration of PySWMM (a Python wrapper (tool) for SWMM) and Pymoo (a Python package for multi-objective optimization) to automate the SWMM calibration process. The tool was tested using a case study urban watershed in Fredericksburg, VA. This tool can employ either a single-objective or multi-objective approach to calibrate a SWMM model by minimizing the error between prediction and observed values. This tool uses performance metrics including Nash-Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), and Root Mean Square Error (RMSE) Standardized Ratio (RSR) for both single-event and long-term continuous rainfall-runoff processes. During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. Additionally, in the single-objective optimization test case, the model yielded NSE values of 0.68 and 0.73 for the calibration and validation, respectively. The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. The tool successfully calibrated the SWMM model, delivering reliable results with suitable computational performance.
DataToCare: Predicting Treatments for Intensive Care Unit Patients Based on Similarity of Abnormalities
Randhawa, Shan; Shojaee, Abbas; Sorrentino, Elisa; Li, Yifan; Abouzied, Azza; Shasha, Dennis (MDPI, 2025-05-26)
Clinical decision-making lies at the heart of health care. Medical data collection has made it possible for clinical decision-making to be data-driven. However, data-driven systems for decision-making have so far worked only for a limited set of clinical conditions. It is still unclear whether a pure data-driven clinical decision-making system can work for a wide set of clinical conditions in real-time environments such as Intensive Care Units. Our DataToCare system receives demographic information, initial diagnoses and measurements from the first hours of a patient’s arrival in an Intensive Care Unit. From that information, DataToCare suggests treatments to offer the patient, based on the treatments given to similar patients. Patients are considered similar if they have abnormal measurements in common. This paper describes the analytics pipeline and the results of its evaluation. DataToCare has the potential to increase patient safety and transfer expertise across medical teams. Though we apply these ideas in the context of Intensive Care Units, the approach could potentially be applied more broadly within medicine.
Biosecurity and Vaccines for Emerging Aquatic Animal RNA Viruses
Ahmadivand, Sohrab; Savage, Carla Phillips; Palic, Dušan (MDPI, 2025-05-28)
Emerging RNA viruses pose a critical threat to aquatic animals, leading to significant ecological and economic consequences. Their high mutation rates and genetic adaptability drive rapid evolution, cross-species transmission, and expanding host ranges, complicating disease management. In aquaculture, RNA viruses are responsible for major outbreaks in fish, while DNA viruses predominate in crustaceans. Marine mammals are increasingly affected by morbilliviruses and highly pathogenic avian influenza (HPAI) H5N1, which has caused widespread mortality events in pinniped and cetacean populations, raising concerns about zoonotic spillover. The absence of effective antiviral treatments and the complexity of vaccine development highlight the urgent need for enhanced biosecurity measures. Furthermore, novel vaccine approaches, such as self-assembling protein nanocage platforms, offer promising solutions for RNA virus mitigation. This review provides a comprehensive analysis of the emergence and significance of RNA viruses in aquatic animals over the last two decades, with a particular focus on biosecurity and vaccine development.
Cellulose-Based Pickering Emulsion-Templated Edible Oleofoam: A Novel Approach to Healthier Solid-Fat Replacers
Lee, Sang Min; Hong, Su Jung; Shin, Gye Hwa; Kim, Jun Tae (MDPI, 2025-05-28)
As health concerns and regulatory pressures over saturated and trans fats grow, there is a growing need for healthier alternatives to traditional solid fats, such as butter and hydrogenated oils, that are still widely used in the food system. In this study, cellulose particle-based Pickering emulsions (CP-PEs) were prepared from microcrystalline cellulose and ethylcellulose and then foamed to obtain edible oleofoams (CP-EOs) as a solid-fat replacer. The average size of CP-PE droplets without surfactant was 598 ± 69 nm, as confirmed by confocal and transmission electron microscopy. Foaming with citric acid/NaHCO₃ and structuring with ≥6% glyceryl monostearate resulted in CP-EOs with an overrun of 147 ± 4% and volumetric stability for 72 h. Micro-computed tomography showed a uniform microcellular network, while the rheological analysis showed solid-like behavior with a storage modulus higher than butter. Differential scanning calorimetry showed a melting enthalpy similar to unsalted butter (10.1 ± 0.9 J/g). These physicochemical properties demonstrate that CP-EOs can closely mimic the firmness, thermal profile, and mouth-feel of conventional solid fats and may provide a promising solid-fat replacer.
Discourse Within the Interactional Space of Literacy Coaching
Dunham, Valerie; Robertson, Dana A. (MDPI, 2025-06-04)
Reviews of literacy coaching show positive outcomes for teaching and learning, yet also that coaching’s impact varies widely, especially at increased scale. Thus, some scholars argue the quality of coaching interactions may matter more than broad coaching actions (e.g., co-planning, observing). Situated within Habermas’s notion of “public sphere”, we used discourse analysis to examine video-recorded pre- and post-interviews, coaching meetings, and coach retrospective think-aloud protocols of a literacy coach and elementary school teacher who described their partnership as “successful”. We examined participants’ values expressed about coaching; how each participant positioned themselves, each other, and the coaching context; and the nature of the coach–teacher discourse therein to answer the following question: what occurs in the interactional space between a coach and teacher when engaged in coaching meetings? We found four categories of values focused on participatory choice, their sense of connectedness, knowledge development, and their approach to working with/as a coach. Further, participants’ positionings signified agency for both the coach and teachers in the interactional space. While bracketing and leveraging their own authority, the coach’s language choices promoted teachers’ agency within the interactional space, providing insight into how language functions to shape the “public sphere” of coaching interactions.
Embryonic Thermal Manipulation Affects Body Performance Parameters and Cecum Microbiome in Broiler Chickens in Response to Post-Hatch Chronic Heat Stress Challenge
Dahadha, Rahmeh; Hundam, Seif; Al-Zghoul, Mohammad Borhan; Alanagreh, Lo’ai; Ababneh, Mustafa; Mayyas, Mohammad; Alghizzawi, Daoud; Mustafa, Minas A.; Gerrard, David E.; Dalloul, Rami A. (MDPI, 2025-06-06)
Rising global temperatures challenge poultry production by disrupting the cecal microbiota, which is essential for chicken health. Thermal manipulation (TM) during embryogenesis is a potential strategy to enhance thermotolerance in broilers. This study examined TM’s effects on the cecal microbiome, body weight (BW), and body temperature (BT) under chronic heat stress (CHS). Fertile Indian River eggs (n = 800) were incubated under control (37.8 °C, 56% RH) or TM conditions (39 °C, 65% RH for 18 h per day from embryonic day 10 to 18). On post-hatch day 18, male chicks were assigned to either CHS (35 ± 0.5 °C for five days) or thermoneutral conditions (24 ± 0.5 °C). The CHS-TM group showed a significantly higher BW than the CHS-CON group (p < 0.05). Under thermoneutral conditions, TM chicks had a lower BT on day 1 (p < 0.05), while the CHS-TM group exhibited a non-significant BT reduction compared to the CHS-CON group under heat stress (p > 0.05). An analysis of the gut microbiome showed that the beta diversity analysis (PERMANOVA, p < 0.05) indicated distinct microbial shifts. Firmicutes and Bacteroidota dominated the phylum level, with CHS increased Bacilli and Lactobacillus while reducing Lachnospirales in the CHS-TM group. These findings suggest that TM modulates gut microbiota and mitigates BW loss, offering a potential strategy to enhance broilers’ resilience to heat stress.
Effect of the Gel Drying Method on Properties of Semicrystalline Aerogels Prepared with Different Network Morphologies
Spiering, Glenn A.; Godshall, Garrett F.; Moore, Robert B. (MDPI, 2025-06-10)
The purpose of this study was to investigate the effect of different drying methods on the structure and properties of semicrystalline polymer aerogels. Aerogels, consisting of either globular or strut-like morphologies, were prepared from poly(ether ether ketone) (PEEK) or poly(phenylene sulfide) (PPS) and dried using vacuum drying, freeze-drying, or supercritical CO₂ extraction. Vacuum drying was found to result in aerogels with a higher shrinkage, smaller mesopores (with pore widths of 2–50 nm), and smaller surface areas compared to the use of supercritical extraction as the drying method. Freeze-dried aerogels tended to have properties between those of vacuum-dried aerogels and aerogels prepared with supercritical extraction. High network connectivity was found to lead to improved gel modulus, which increased the ability of aerogels to resist network deformation due to stresses induced during drying. The PEEK and PPS aerogel networks consisting of highly connected strut-like features were considerably stiffer than those composed of globular features, and thus shrank less under the forces induced by vacuum drying or freeze-drying. The aerogels prepared from PPS were found to have larger mesopores and smaller surface areas than the aerogels prepared from PEEK. The larger mesopores of the PPS aerogels induced lower capillary stresses on the aerogel network, and thus shrank less. This work demonstrates that preparing PEEK and PPS gels with strut-like features can allow aerogel processing with simpler evaporative drying methods rather than the more complex supercritical drying method.
Building Transdisciplinary Research and Curricula: A Model for Developing Cross-Disciplinary Communities Among Faculty in Higher Education
Amelink, Catherine T.; Nicewonger, Todd (MDPI, 2025-06-10)
Knowledge and problem-solving approaches that span disciplinary boundaries and involve diverse communities are foundational aspects of transdisciplinarity. Transdisciplinary approaches in research efforts are needed to address complex problems of global importance. At the same time education systems should be preparing graduates to enter the workforce with complex problem-solving skills. Students need to have learning experiences that allow for the acquisition of cross-disciplinary systematic reasoning if they are expected to engage in addressing these complex problems. Recent reports have underscored the need to create university structures and incentives that allow for dynamic and responsive approaches to this global need for transdisciplinary discovery and learning efforts; however, little is known about the efficacy of the approaches and models that have been implemented to create large-scale change in higher education and how they help in achieving transdisciplinary goals. Through an ethnographic case study analysis, this paper examines how a faculty-led community of practice model is being used to build transdisciplinary research capacity and transdisciplinary curricula at a Research I university. Given the unique nature of this transdisciplinary community of practice model, this qualitative and descriptive study sought to examine what elements of the model facilitated faculty participation in transdisciplinary research and curricular efforts. More specifically, this study intended to respond to recent calls to better understand the systematic approach that would need to be employed by higher education institutions if they are adequately engaging faculty in addressing complex problems in their research efforts, as well as engaging faculty in the adequate development of the future workforce through pedagogical transdisciplinary approaches. The findings indicate that the transdisciplinary community of practice model is useful for initially motivating and incentivizing faculty participation. The results also indicate that the inclusive internal support networks that were part of the model facilitated faculty engagement.
Silicon Enhances Antioxidant Capacity and Photochemical Efficiency in Drought-Stressed Creeping Bentgrass (Agrostis stolonifera L.) Putting Greens
Zhang, Xunzhong; Roberson, Travis; Goatley, Mike; Flanary, Taylor; McCall, David (MDPI, 2025-06-11)
Creeping bentgrass (Agrostis stolonifera L.) is an important cool-season turfgrass species that is not well understood. The objective of this study was to determine the effects of the mechanisms underlying silicon (Si) on creeping bentgrass drought tolerance under field conditions from 2022 to 2023. Five treatments, including a control (potassium silicate at 0.95 and 1.90 mL m⁻²), Dyamin-OSA at 0.64 and 1.28 mL m⁻², and Agsil 21 at 0.35 mL m⁻², were arranged in a randomized block design with four replications and applied biweekly to creeping bentgrass putting greens during summer months. Deficit irrigation was applied to induce drought stress in June and July. The Si treatments exhibited beneficial effects on turf quality, physiological fitness, and root viability. K-silicate at 1.90 mL m⁻² and Agsil 21 at 0.35 mL m⁻² increased the leaf Si content by 32.0% and 22.8%, respectively, when compared to the control, as measured at the end of the trial. Among the treatments, K-silicate at 1.90 mL m⁻², Dyamin-OSA at 0.64 mL m⁻², and Agsil 21 at 0.35 mL m⁻² tended to have greater beneficial effects than other Si treatments. Exogenous Si may improve drought tolerance by enhancing root growth and viability, Si uptake by roots, and antioxidant capacity and by protecting photosynthetic function.
Impact of Thermal Manipulation of Broiler Eggs on Growth Performance, Splenic Inflammatory Cytokine Levels, and Heat Shock Protein Responses to Post-Hatch Lipopolysaccharide (LPS) Challenge
Al-Zghoul, Mohammad Borhan; Hundam, Seif; Mayyas, Mohammad; Gerrard, David E.; Dalloul, Rami A. (MDPI, 2025-06-12)
Thermal manipulation (TM) during embryogenesis is a promising non-pharmacological strategy to enhance physiological resilience in broiler chickens. This study evaluated the impact of thermal conditioning of fertile eggs on growth performance, inflammatory responses, and molecular stress markers following a post-hatch lipopolysaccharide (LPS) challenge. Fertilized eggs (average weight 62 ± 3 g) were obtained from 35-week-old Indian River broiler breeder hens. A total of 720 eggs were randomly assigned to either the control group (n = 360) or the TM group (n = 360), with each group consisting of two replicates of 180 eggs. Control eggs were maintained under standard incubation conditions (37.8 °C, 56% RH), while TM eggs were subjected to elevated temperature (38.8 °C, 65% RH) for 18 h daily from embryonic day 10 to 18. On post-hatch day 15, control and TM groups were administered either saline or LPS via intraperitoneal (IP) injection. Body weight and temperature, internal organ weights, and splenic mRNA expression levels of inflammatory cytokines, toll-like receptors, transcription factors, and heat shock proteins were assessed. TM did not alter hatchability (p = 0.633), but significantly shortened hatch time (p < 0.05) and improved feed efficiency (p < 0.05). While LPS induced marked inflammatory responses in all birds, those subjected to TM exhibited attenuated proinflammatory cytokine expression, enhanced anti-inflammatory signaling, and differential regulation of stress-associated genes, including nuclear factor kappa B (NF-κB), heat shock protein 70 (HSP70), and heat shock factors (HSFs). These findings suggest that TM during incubation promotes a more regulated immune response and improved stress adaptation post-hatch. This approach offers a potential antibiotic-free intervention to enhance broiler health, performance, and resilience under immunological stress.
Intentional Weight Gain Strategies in Young Adult Athletic Individuals
Sanchez, Allison D.; Larson-Meyer, D. Enette (MDPI, 2025-04-02)
Athletic individuals may intentionally aim to gain weight, primarily as lean body mass, to improve athletic performance or to better match opponents’ size. This study aimed to investigate the self-reported nutrition- and exercise-related behaviors of athletic individuals aiming to gain weight. Cross-sectional data were drawn from an online survey of athletic adults recruited locally, nationally, and internationally. In total, 168 athletic participants (24 ± 5 years; 29% female, 71% male) completed the survey and were actively attempting or had attempted weight gain in the last 12 months to gain muscle mass (87.5%), for aesthetic reasons (66.1%), or to improve athletic performance (63.7%). The most prevalent dietary strategies reported to increase weight gain were consuming more energy than usual (88.0%) from mainly protein foods (83.9%) and using protein powders (67.3%). In total, 9.6% of participants reported using anabolic hormones. The main exercise change was increased resistance training (81.5%). Our results confirm that both male and female athletic individuals intentionally attempt to gain weight. Nutrition and exercise professionals may use the findings to be aware of these common dietary and exercise strategies and to better educate their athletic clients on appropriate methods that are evidence-based and not detrimental to health.
Standalone Operation of Inverter-Based Variable Speed Wind Turbines on DC Distribution Network
Amini, Hossein; Noroozian, Reza (MDPI, 2025-04-10)
This paper discusses the operation and control of a low-voltage DC (LVDC) isolated distribution network powered by distributed generation (DG) from a variable-speed wind turbine induction generator (WTIG) to supply unbalanced AC loads. The system incorporates a DC-DC storage converter to regulate network voltages and interconnect battery energy storage with the DC network. The wind turbines are equipped with a squirrel cage induction generator (IG) to connect a DC network via individual power inverters (WTIG inverters). Loads are unbalanced ACs and are interfaced using transformerless power inverters, referred to as load inverters. The DC-DC converter is equipped with a novel control strategy, utilizing a droop regulator for the DC voltage to stabilize network operation. The control system is modeled based on Clark and Park transformations and is developed for the load inverters to provide balanced AC voltage despite unbalanced load conditions. The system employs the perturbation and observation (P&O) method for maximum power point tracking (MPPT) to optimize wind energy utilization, while blade angle controllers maintain generator performance within rated power and speed limits under high wind conditions. System operation is analyzed under two scenarios: normal operation with varying wind speeds and the effects of load variations. Simulation results using PSCAD/EMTDC demonstrate that the proposed LVDC isolated distribution network (DC) achieves a stable DC bus voltage within ±5% of the nominal value, efficiently delivers balanced AC voltages with unbalanced levels below 2%, and operates with over 90% wind energy utilization during varying wind speeds, confirming LVDC network reliability and robustness.
Follicular Fluid from Cows That Express Estrus During a Fixed-Time Artificial Insemination Protocol Promotes Blastocyst Development
Harl, Audra W.; Negrón-Pérez, Verónica M.; Stewart, Jacob W.; Perry, George A.; Ealy, Alan D.; Rhoads, Michelle L. (MDPI, 2025-04-25)
It is not yet understood why cows that exhibit estrus and ovulate are more likely to become pregnant than those that ovulate but do not exhibit estrus during a fixed-time artificial insemination (FTAI) protocol. The objective of this work was to determine whether the follicular fluid from cows that exhibit estrus contributes to the increased likelihood of pregnancy. Lactating crossbred cows were subjected to an FTAI estrous synchronization protocol. Estrous behavior was observed and recorded prior to transvaginal follicle aspiration from cows that did (estrus, n = 7) or did not exhibit estrus (non-estrus, n = 6). Follicular fluid (25%) was then added to in vitro maturation media for the maturation of oocytes (n = 1489) from slaughterhouse ovaries. Cleavage rates were not affected by the estrous status of the cows from which the follicular fluid was collected. Blastocyst rates, however, were greater following maturation in the presence of follicular fluid from estrus cows compared to non-estrus cows (p ≤ 0.01). This difference in blastocyst rates was not related to blastocyst cell numbers (inner cell mass, trophoblast, and total), as they did not differ between estrus and non-estrus animals. This study demonstrates that the follicular fluid, and thus, the follicular environment just prior to ovulation does indeed contribute to improved pregnancy rates following FTAI.
Integrating Equation Coding with Residual Networks for Efficient ODE Approximation in Biological Research
Yi, Ziyue (MDPI, 2025-04-27)
Biological research traditionally relies on experimental methods, which can be inefficient and hinder knowledge transfer due to redundant trial-and-error processes and difficulties in standardizing results. The complexity of biological systems, combined with large volumes of data, necessitates precise mathematical models like ordinary differential equations (ODEs) to describe interactions within these systems. However, the practical use of ODE-based models is limited by the need for curated data, making them less accessible for routine research. To overcome these challenges, we introduce LazyNet, a novel machine learning model that integrates logarithmic and exponential functions within a Residual Network (ResNet) to approximate ODEs. LazyNet reduces the complexity of mathematical operations, enabling faster model training with fewer data and lower computational costs. We evaluate LazyNet across several biological applications, including HIV dynamics, gene regulatory networks, and mass spectrometry analysis of small molecules. Our findings show that LazyNet effectively predicts complex biological phenomena, accelerating model development while reducing the need for extensive experimental data. This approach offers a promising advancement in computational biology, enhancing the efficiency and accuracy of biological research.
Revisiting the Replication Crisis and the Untrustworthiness of Empirical Evidence
Spanos, Aris (MDPI, 2025-05-20)
The current replication crisis relating to the non-replicability and the untrustworthiness of published empirical evidence is often viewed through the lens of the Positive Predictive Value (PPV) in the context of the Medical Diagnostic Screening (MDS) model. The PPV is misconstrued as a measure that evaluates ‘the probability of rejecting H0 when false’, after being metamorphosed by replacing its false positive/negative probabilities with the type I/II error probabilities. This perspective gave rise to a widely accepted diagnosis that the untrustworthiness of published empirical evidence stems primarily from abuses of frequentist testing, including p-hacking, data-dredging, and cherry-picking. It is argued that the metamorphosed PPV misrepresents frequentist testing and misdiagnoses the replication crisis, promoting ill-chosen reforms. The primary source of untrustworthiness is statistical misspecification: invalid probabilistic assumptions imposed on one’s data. This is symptomatic of the much broader problem of the uninformed and recipe-like implementation of frequentist statistics without proper understanding of (a) the invoked probabilistic assumptions and their validity for the data used, (b) the reasoned implementation and interpretation of the inference procedures and their error probabilities, and (c) warranted evidential interpretations of inference results. A case is made that Fisher’s model-based statistics offers a more pertinent and incisive diagnosis of the replication crisis, and provides a well-grounded framework for addressing the issues (a)–(c), which would unriddle the non-replicability/untrustworthiness problems.
Developing a Fatigue Detection Model for Hospital Nurses Using HRV Measures and Machine Learning
Hafiz, Wynona Salsabila; Puspasari, Maya Arlini; Fitriani, Dewi Yunia; Hanowski, Richard J.; Syaifullah, Danu Hadi; Arista, Salsabila Annisa (MDPI, 2025-05-22)
Fatigue among hospital nurses, resulting from demanding workloads and irregular shift schedules, presents significant risks to both healthcare workers and patient safety. This study developed a fatigue detection model using heart-rate variability (HRV) and investigated its relationship with the Swedish Occupational Fatigue Inventory (SOFI) among nurses. Sixty nurses from a hospital in Depok, Indonesia, participated with HRV data collected via Polar H10 monitors before and after shifts alongside SOFI questionnaires. A mixed ANOVA revealed no significant between-subjects differences in HRV across morning, afternoon, and night shifts. However, within-subjects analyses showed pronounced parasympathetic rebound (elevated Mean RR) and sympathetic withdrawal (reduced Mean HR) post-shift, particularly after afternoon and night shifts, contrasting with stable profiles in morning shifts. Correlation analysis showed significant associations between SOFI dimensions, specifically lack of motivation and sleepiness, with HRV measures, indicating autonomic dysfunction and elevated stress levels. Several machine-learning classifiers were used to develop a fatigue detection model and compare their accuracy. The Fine Gaussian Support Vector Machine (SVM) model achieved the highest performance with 81.48% accuracy and an 81% F1 score, outperforming other models. These findings suggest that HRV-based fatigue detection integrated with machine learning provides a promising approach for continuous nurse fatigue monitoring.
Implementation of Modular Depot Concept for Switchgrass Pellet Production in the Piedmont
Resop, Jonathan P.; Cundiff, John S.; Sokhansanj, Shahabaddine (MDPI, 2025-06-12)
In the bioenergy industry, highway hauling cost is typically 30%, or more, of the average cost of feedstock delivered to a biorefinery. Thus, truck productivity, in terms of Mg/d/truck, is a key issue in the design of a logistics system. One possible solution to this problem that is being explored is the utilization of modular pellet depots. In such a logistics system, raw biomass (i.e., low-bulk-density product) is converted into pellets (i.e., high-bulk-density product) by several smaller-scale modular pellet depots instead of by a single larger-capacity pellet depot. A truckload of raw biomass (e.g., round bales) is 16 Mg and a load of pellets is 34 Mg. The distribution of depots across a feedstock production area can potentially have an impact on the total truck operating hours (i.e., raw biomass hauling to a depot + pellet hauling from the depot to the biorefinery) required to deliver feedstock for annual operation of a biorefinery. This study examined three different distributions of depots across five feedstock production areas. The numbers of depots were one, two, and four per production area for totals of five, ten, and twenty depots. Increasing the number of depots from five to ten reduced raw biomass hauling hours by 12%, and increasing from five to twenty reduced these hours by 30%. Total hauling hours (raw biomass + pellets) were reduced by less than 1% with an increase from five to ten and by about 11% with an increase from five to twenty. The modular pellet depot concept demonstrated potential for providing improvements to biorefinery logistics systems, but more research is needed to optimize this balance.
Personality Emulation Utilizing Large Language Models
Kolenbrander, Jack; Michaels, Alan J. (MDPI, 2025-06-12)
Fake identities have proven to be an effective methodology for conducting privacy and cybersecurity research; however, existing models are limited in their ability to interact with and respond to received communications. To perform privacy research in more complex Internet domains, withstand enhanced scrutiny, and persist long-term, fake identities must be capable of automatically generating responses while maintaining consistent behavior and personality. This work proposes a method for assigning personality to fake identities using the widely accepted psychometric Big Five model. Leveraging this model, the potential application of large language models (LLMs) to generate email responses that emulate human personality traits is investigated to enhance fake identity capabilities for privacy research at scale.
Extreme Value Statistics of Community Detection in Complex Networks with Reduced Network Extremal Ensemble Learning (RenEEL)
Ghosh, Tania; Zia, Royce K. P.; Bassler, Kevin E. (MDPI, 2025-06-13)
Arguably, the most fundamental problem in Network Science is finding structure within a complex network. Often, this is achieved by partitioning the network’s nodes into communities in a way that maximizes an objective function. However, finding the maximizing partition is generally a computationally difficult NP-complete problem. Recently, a machine learning algorithmic scheme was introduced that uses information within a set of partitions to find a new partition that better maximizes an objective function. The scheme, known as RenEEL, uses Extremal Ensemble Learning. Starting with an ensemble of K partitions, it updates the ensemble by considering replacing its worst member with the best of L partitions found by analyzing a reduced network formed by collapsing nodes, which all the ensemble partitions agree should be grouped together, into super-nodes. The updating continues until consensus is achieved within the ensemble about what the best partition is. The original K ensemble partitions and each of the L partitions used for an update are found using a simple “base” partitioning algorithm. We perform an empirical study of how the effectiveness of RenEEL depends on the values of K and L and relate the results to the extreme value statistics of record-breaking. We find that increasing K is generally more effective than increasing L for finding the best partition.
Actuation and Control of Railcar-Mounted Sensor Systems
Craig, Caroline; Ahmadian, Mehdi (MDPI, 2025-06-13)
This study provides the design, analysis, and prototype fabrication of a remotely controlled actuation system for railcar-mounted sensors. Frequent railway inspections are essential for detecting and preventing major defects that could lead to train derailments or accidents. Integrating supplemental automated inspection systems into existing trains can aid inspection crews without interfering with standard railway operations. However, many sensors and cameras require protection during transit, motivating the need for a deployable mounting assembly. The feasibility of a deployable sensor system was successfully assessed by creating and demonstrating a functional prototype mounting assembly that can be used with future automated inspection systems. Typical loads and accelerations experienced by a train were used to design a lead screw and stepper motor system capable of working within desired tolerances. Optimized inputs controlling this motion with an Arduino Uno were found through the iterative testing of digital signals and direct port manipulation. Further research testing in a field-like environment is suggested.

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