Journal Articles, Multidisciplinary Digital Publishing Institute (MDPI)

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The Effects of Low-Impact Development Best Management Practices on Reducing Stormwater Caused by Land Use Changes in Urban Areas: A Case Study of Tehran City, Iran
Rostamzadeh, Sajedeh; Malekmohammadi, Bahram; Mashhadimohammadzadehvazifeh, Fatemeh; Arsanjani, Jamal Jokar (MDPI, 2024-12-27)
Urbanization growth and climate change have increased the frequency and severity of floods in urban areas. One of the effective methods for reducing stormwater volume and managing urban floods is the low-impact development best management practice (LID-BMP). This study aims to mitigate flood volume and peak discharge caused by land use changes in the Darabad basin located in Tehran, Iran, using LID-BMPs. For this purpose, land use maps were extracted for a period of 23 years from 2000 to 2022 using Landsat satellite images. Then, by using a combination of geographic information system-based multi-criteria decision analysis (GIS-MCDA) method and spatial criteria, four types of LID-BMPs, including bioretention basin, green roof, grass swale, and porous pavement, were located in the study area. Next, rainfall–runoff modeling was applied to calculate the changes in the mentioned criteria due to land use changes and the application of LID-BMPs in the area using soil conservation service curve number (SCS-CN) method. The simulation results showed that the rise in built-up land use from 43.49 to 56.51 percent between the period has increased the flood volume and peak discharge of 25-year return period by approximately 60 percent. The simulation results also indicated that the combined use of the four selected types of LID-BMPs will lead to a greater decrease in stormwater volume and peak discharge. According to the results, LID-BMPs perform better in shorter return periods in a way that the average percentage of flood volume and peak discharge reduction in a 2-year return period were 36.75 and 34.96 percent, while they were 31.37 and 26.5 percent in a 100-year return period.
Describing and Modelling Stem Form of Tropical Tree Species with Form Factor: A Comprehensive Review
Oluwajuwon, Tomiwa V.; Ogbuka, Chioma E.; Ogana, Friday N.; Hossain, Md. Sazzad; Israel, Rebecca; Lee, David J. (MDPI, 2024-12-27)
The concept of tree or stem form has been central to forest research for over a century, playing a vital role in accurately assessing tree growth, volume, and biomass. The form factor is an essential component for expressing the shape of a tree, enabling more accurate volume estimation, which is vital for sustainable forest management and planning. Despite its simplicity, flexibility, and advantages in volume estimation, the form factor has received less attention compared to other measures like taper equations and form quotient. This review summarizes the concept, theories, and measures of stem form, and describes the factors influencing its variation. It focuses on the form factor, exploring its types, parameterization, and models in the context of various tropical species and geographic conditions. The review also discusses the use of the form factor in volume estimation and the issues with using default or generic values. The reviewed studies show that tree stem form and form factor variations are influenced by multiple site, tree, and stand characteristics, including site quality, soil type, climate conditions, tree species, age, crown metrics, genetic factors, stand density, and silviculture. The breast height form factor is the most adopted among the three common types of form factors due to its comparative benefits. Of the five most tested form factor functions for predicting tree form factors, Pollanschütz’s function is generally considered the best. However, its performance is often not significantly different from other models. This review identifies the “Hohenadl” method and mixed-effects modelling as overlooked yet potentially valuable approaches for form factor modelling. Using the form factor, especially by diameter or age classes, can enhance tree volume estimation, surpassing volume equations. However, relying on default or generic form factors can lead to volume and biomass estimation errors of up to 17–35%, underscoring the need to limit variation sources in form factor modelling and application. Further recommendations are provided for improving the statistical techniques involved in developing form factor functions.
Comparative Analysis of Restorative Interior Design Elements: Screen-Based Versus Virtual Reality Evaluations for Future Medical Treatment Prospects
Tural, Alp; Tural, Elif (MDPI, 2024-12-31)
Given the increasing prevalence of anxiety and depression, this research aims to identify design features that enhance the sense of restoration, with the goal of supporting mental and behavioral healthcare facility design. This study employed both screen-based and virtual reality (VR) stimuli to evaluate the perceived restorativeness of different interior settings. The key variables analyzed included window view access, view content, materiality, and room geometry. Thirty-five undergraduate and graduate students assessed 16 distinct interior environments. Findings indicate that the VR presentations generally produced higher restorativeness scores compared with screen-based presentations, though this effect varied across stimuli. Repeated-measures ANOVA revealed that larger windows consistently correlated with higher restorativeness scores in both presentation modes. Views of water were rated as most restorative, followed by wooded areas. Natural materials were perceived as significantly more restorative than other materials, particularly in VR presentations. Varied ceiling designs, especially vaulted ceilings, were associated with evaluations of higher restorativeness compared with flat ceiling designs, with this effect more pronounced in VR. This research underscores the potential of VR technology to simulate and assess interior design interventions, offering insights into creating more effective and personalized restorative environments in mental health treatment facilities. The findings can inform evidence-based design strategies for healthcare spaces, supporting treatment processes and patient well-being.
Heat Treatment Effect on the Corrosion Resistance of 316L Stainless Steel Produced by Laser Powder Bed Fusion
Sangoi, Kevin; Nadimi, Mahdi; Song, Jie; Fu, Yao (MDPI, 2025-01-04)
This study explores the effect of heat treatment on the microstructural characteristics and corrosion resistance of 316L stainless steels (SSs) produced via laser powder bed fusion (L-PBF), focusing on anisotropic corrosion behavior—a relatively less explored phenomenon in LPBF 316L SSs. By systematically analyzing the effects of varying heat treatment temperatures (500 °C, 750 °C, and 1000 °C), this work uncovers critical correlations between microstructural evolution and corrosion properties. The findings include the identification of anisotropic corrosion resistance between horizontal (XY) and vertical (XZ) planes, with the vertical plane demonstrating higher pitting and repassivation potentials but greater post-repassivation current densities. Furthermore, this study highlights reductions in grain size, dislocation density, and melt pool boundaries with increasing heat treatment temperatures, which collectively diminishes corrosion resistance. These insights advance the understanding of processing–structure–property relationships in additively manufactured metals, providing practical guidelines for optimizing thermal post-processing to enhance material performance in corrosive environments.
Numerical Simulation of Impact of Different Redox Couples on Flow Characteristics and Electrochemical Performance of Deep Eutectic Solvent Electrolyte Flow Batteries
Xiao, Zhiyuan; Zhang, Ruiping; Lu, Mengyue; Ma, Qiang; Li, Zhuo; Su, Huaneng; Li, Huanhuan; Xu, Qian (MDPI, 2025-01-07)
A comprehensive, three-dimensional, macro-scale model was developed to simulate non-aqueous deep eutectic solvent (DES) electrolyte flow batteries. The model’s feasibility was validated by comparing the simulated polarization data with the experimental results. Utilizing this model, the work reported here compared the flow characteristics and electrochemical properties of electrolytes with different redox couples within the porous electrodes of the batteries. Despite variations in the active materials, the distribution of the electrolyte flow rate showed uniformity due to consistent electrode and flow channel designs, indicating that the structural design of electrodes and channels has a more significant impact on electrolyte flow than the physicochemical properties of the electrolytes themselves. This study also highlighted that TEMPO and Quinoxaline DES electrolytes exhibited less flow resistance and more uniform concentration distributions, which helped reduce overpotentials and enhance battery energy efficiency. Furthermore, this research identified that the highest average overpotentials occurred near the membrane for all the redox couples, demonstrating that electrochemical reactions in DES electrolyte flow batteries primarily occur in the region close to the membrane. This finding underscores the importance of optimizing active redox ions transport in electrolytes to enhance electrochemical reactions in the proximal membrane region, which is crucial for improving flow battery performance.
Identification of Potential Vectors and Detection of Rift Valley Fever Virus in Mosquitoes Collected Before and During the 2022 Outbreak in Rwanda
Nsengimana, Isidore; Hakizimana, Emmanuel; Mupfasoni, Jackie; Hakizimana, Jean Nepomuscene; Chengula, Augustino A.; Kasanga, Christopher J.; Eastwood, Gillian (MDPI, 2025-01-08)
Rift Valley fever virus (RVFV) is an emerging mosquito-borne arbovirus of One Health importance that caused two large outbreaks in Rwanda in 2018 and 2022. Information on vector species with a role in RVFV eco-epidemiology in Rwanda is scarce. Here we sought to identify potential mosquito vectors of RVFV in Rwanda, their distribution and abundance, as well as their infection status. Since an outbreak of RVF occurred during the study period, data were obtained both during an interepidemic period and during the 2022 Rwanda RVF outbreak. Five districts of the eastern province of Rwanda were prospected using a combination of unbaited light traps and Biogents (BG Sentinel and Pro) traps baited with an artificial human scent during three periods, namely mid-August to mid-September 2021, December 2021, and April to May 2022. Trapped mosquitoes were morphologically identified and tested for viral evidence using both RT-PCR and virus isolation methods on a Vero cell line. A total of 14,815 adult mosquitoes belonging to five genera and at least 17 species were collected and tested as 765 monospecific pools. Culex quinquefasciatus was the most predominant species representing 72.7% of total counts. Of 527 mosquito pools collected before the 2022 outbreak, a single pool of Cx. quinquefasciatus showed evidence of RVFV RNA. Of 238 pools collected during the outbreak, RVFV was detected molecularly from five pools (two pools of Cx. quinquefasciatus, two pools of Anopheles ziemanni, and one pool of Anopheles gambiae sensu lato), and RVFV was isolated from the two pools of Cx. quinquefasciatus, from Kayonza and Rwamagana districts, respectively. Minimum infection rates (per 1000 mosquitoes) of 0.4 before the outbreak and 0.6–7 during the outbreak were noted. Maximum-likelihood phylogenetic analysis indicates that RVFV detected in these mosquitoes is closely related to viral strains that circulated in livestock in Rwanda and in Burundi during the same RVF outbreak in 2022. The findings reveal initial evidence for the incrimination of several mosquito species in the transmission of RVFV in Rwanda and highlight the need for more studies to understand the role of each species in supporting the spread and persistence of RVFV in the country.
Flexible Reconfiguration for Optimal Operation of Distribution Network Under Renewable Generation and Load Uncertainty
Esmaeilnezhad, Behzad; Amini, Hossein; Noroozian, Reza; Jalilzadeh, Saeid (MDPI, 2025-01-09)
The primary objective when operating a distribution network is to minimize operating costs while taking technical constraints into account. Minimizing the operational costs is difficult when there is a high penetration of renewable resources and variability of loads, which introduces uncertainty. In this paper, a flexible, dynamic reconfiguration model is developed that enables a distribution network to minimize operating costs on an hourly basis. The model fitness function is to minimize the system costs, including power loss, voltage deviation, purchased power from the upstream network, renewable generation, and switching costs. The uncertainty of the load and generation from renewable energies is planned to use their probability density functions via a scenario-based approach. The suggested optimization problem is solved using a metaheuristic approach based on the coati optimization algorithm (COA) due to the nonlinearity and non-convexity of the problem. To evaluate the performance of the presented approach, it is validated on the IEEE 33-bus radial system and TPC 83-bus real system. The simulation results show the impact of dynamic reconfiguration on reducing operation costs. It is found that dynamic reconfiguration is an efficient solution for reducing power losses and total energy drawn from the upstream network by increasing the number of switching operations.
Phronetic Planning’s Janus Face: Charting Elite Advantage in Tehran’s Land Use Decisions
Stephenson, Max O. Jr.; Panahi, Mohammadmehdi; Moayerian, Neda (MDPI, 2025-01-09)
This study employed a phronetic (practical wisdom) analytic framework to explore the Tehran, Iran, City Council’s Article 5 Commission’s land use decisions from 1999 to 2024. We argue that, during that period, the Commission nominally embraced practical wisdom in lieu of episteme or techne as the arbiter of its choice making. Nonetheless, during those years, its members disproportionately granted land use change permits to the Tehran Comprehensive Plan that principally benefited members of the city’s upper class. Our central finding underscores the Commission’s role in advancing elite rather than broader public interest needs. We conclude that even a nominally phronetic planning process can fall prey to willfully undemocratic choice making. In this case, this occurred when the discretionary powers delegated to the Commission to serve the broader public interest were instead employed routinely to serve the interests of an elite. Our analysis highlights the urgent need for more ethical, popularly accountable, and equitable planning practices to serve the general population of Tehran.
Assessing Methods to Measure Stem Diameter at Breast Height with High Pulse Density Helicopter Laser Scanning
Sumnall, Matthew J.; Raigosa-Garcia, Ivan; Carter, David R.; Albaugh, Timothy J.; Campoe, Otávio C.; Rubilar, Rafael A.; Alexander, Bart; Cohrs, Christopher W.; Cook, Rachel L. (MDPI, 2025-01-10)
Technological developments have allowed helicopter airborne laser scanning (HALS) to produce high-density point clouds below the forest canopy. We present a tree stem classification method that combines linear shape detection and model-based clustering, using four discrete methods to estimate stem diameter. Stem horizontal size was estimated every 25 cm below the living crown, and a cubic spline was used to estimate where there were gaps. Individual stem diameter at breast height (DBH) was estimated for 77% of field-measured trees. The root mean square error (RMSE) of DBH estimates was 7–12 cm using stem circle fitting. Adapting the approach to use an existing stem taper model reduced the RMSE of estimates (<1 cm). In contrast, estimates that were produced from a previously existing DBH estimation method (PREV) could be achieved for 100% of stems (DBH RMSE 6 cm), but only after location-specific error was corrected. The stem classification method required comparatively little development of statistical models to provide estimates, which ultimately had a similar level of accuracy (RMSE < 1 cm) to PREV. HALS datasets can measure broad-scale forest plantations and reduce field efforts and should be considered an important tool for aiding in inventory creation and decision-making within forest management.
Model-Free Resilient Grid-Forming and Grid-Following Inverter Control Against Cyberattacks Using Reinforcement Learning
Beikbabaei, Milad; Kwiatkowski, Brian Michael; Mehrizi-Sani, Ali (MDPI, 2025-01-13)
The U.S. movement toward clean energy generation has increased the number of installed inverter-based resources (IBR) in the grid, introducing new challenges in IBR control and cybersecurity. IBRs receive their set point through the communication link, which may expose them to cyber threats. Previous work has developed various techniques to detect and mitigate cyberattacks on IBRs, developing schemes for new inverters being installed in the grid. This work focuses on developing model-free control techniques for already installed IBR in the grid without the need to access IBR internal control parameters. The proposed method is tested for both the grid-forming and grid-following inverter control. Different detection and mitigation algorithms are used to enhance the accuracy of the proposed method. The proposed method is tested using the modified CIGRE 14-bus North American grid with seven IBRs in PSCAD/EMTDC. Finally, the performance of the detection algorithm is tested under grid normal transients, such as set point change, load change, and short-circuit fault, to make sure the proposed detection method does not provide false positives.
Methylsulfonylmethane (MSM) Supplementation in Adult Horses Supports Improved Skeletal Muscle Inflammatory Gene Expression Following Exercise
Barshick, Madison R.; Ely, Kristine M.; Mogge, Keely C.; Chance, Lara M.; Johnson, Sally E. (MDPI, 2025-01-14)
Methylsulfonylmethane (MSM) is a sulfur-containing molecule with reported anti-inflammatory and antioxidant activities. Exercise causes the formation of free radicals and stimulates inflammatory gene expression in leukocytes and skeletal muscle. The hypothesis that dietary supplementation with MSM alters the exercise-mediated inflammatory and oxidant response was assessed in unfit adult thoroughbred geldings. Ten geldings (6.7 ± 1.6 yr) were assigned to a diet supplemented without (CON, n = 5) or with 21 g of MSM (n = 5) for 30 days. Following the supplementation period, horses performed a standardized exercise test (SET) with blood collections before (t = 0), 10 min, 1 h, 4 h, and 24 h post-SET. Skeletal muscle biopsies were retrieved from the middle gluteus before and 1 h post-SET for total RNA isolation. All horses were rested for 120 days before the experiment was repeated in a cross-over design. Plasma total antioxidant capacity was unaffected (p > 0.05) by either exercise or MSM. Plasma glutathione peroxidase activity was less (p < 0.05) in MSM horses than in the CON. Plasma IL6, IL8, IL10, and TNFα were unaffected (p > 0.05) by either exercise or diet. Transcriptomic analysis of skeletal muscle revealed 35 genes were differentially expressed (DEG; p < 0.05) by 2-fold or more in response to exercise; no MSM DEGs were noted. A comparison of the exercise by diet contrasts revealed that horses supplemented with MSM contained a greater number of exercise-responsive genes (630; logFC > 0.2; q < 0.05) by comparison to the CON (237), with many of these mapping to the immune response (71) and cytokine signal transduction (60) pathways. These results suggest supplementation of MSM as a dietary aid for improved anti-inflammatory responses in skeletal muscle following exercise.
Forward/Backward Decomposition for Dispersive Wave Propagation Measurements
Corbin, Nicholas A.; Tarazaga, Pablo Alberto (MDPI, 2025-01-16)
Two complicating features commonly found in wave propagation applications include dispersion, i.e., frequency-dependent propagation velocity, and reflections, which introduce coherent noise. In this work, we present a signal processing technique which can be applied in a variety of applications to decompose signals into their forward- and backward-propagating components. The theory is presented, along with algorithmic implementation and experimental validation on a Timoshenko beam. The implications and potential utility of the method are briefly discussed.
Transforming Children’s Attitudes Toward Insects Through In-School Encounters
Miller, Kathleen M.; Beegle, Dana K.; Blevins Wycoff, Stephanie; Frank, Daniel L. (MDPI, 2025-01-17)
Each year, the Department of Entomology at Virginia Tech hosts an entomology-themed outreach event known as Hokie BugFest. This on-campus, festival-sized experience aims to educate the public about insects and other arthropods through hands-on activities, games, displays, and live arthropods. In 2021, due to the COVID-19 pandemic, Hokie BugFest and similar large public events were cancelled. In response, the department launched Hokie BugFest on the Go, which offered smaller-scale, in-person learning opportunities during these closures. Instead of hosting the community on campus, Virginia Tech’s Department of Entomology brought live arthropods, university experts, and the exciting science of entomology directly into schools, fostering small-group, hands-on learning experiences. In 2022, a playful assessment was added to the traveling outreach program to measure changes in student attitudes and perceptions of insects and other arthropods before and after the program. The assessment also gauged students’ favorite arthropods after seeing, and in some cases handling, them live during the program. Assessment results revealed valuable insights into how hands-on, applied learning experiences can shift children’s attitudes toward arthropods. Results showed that even after expressing trepidation and fears, students’ knowledge and comfort levels with insects and other arthropods increased as they interacted and learned throughout the program. These findings underscore the value of using engaging, hands-on, small-group approaches when designing entomology-themed outreach events for young audiences and offer guidance for future programs.
Risk Perception in the Nigua River Basin: Key Determinants and Policy Implications
Maldonado-Santana, Casimiro; Torres-Valle, Antonio; Franco-Billini, Carol; Jauregui-Haza, Ulises Javier (MDPI, 2024-12-27)
The Nigua River basin in the Dominican Republic is a critical hydrographic area facing significant environmental challenges, including deforestation, soil erosion and pollution from mining and agricultural activities. This study explores the role of risk perception among local residents in shaping policies for the basin’s sustainable management. The research aims to identify the factors influencing risk perception and propose actionable strategies to improve environmental governance in the region. A “perceived risk profile” methodology was applied, using survey data from 1223 basin residents. The analysis identified key variables that influence risk perception, including demographic factors such as education, gender, and place of residence. The findings reveal that risk underestimation correlates with low awareness of risks, uncertainty about the origins of disasters, fatalism toward natural events, and low trust in institutions. In contrast, risk over-estimation is linked to infrequent risk communication, heightened catastrophism and a strong emphasis on the benefits of environmental protection. The study also highlights significant regional differences in risk perception, with residents of the lower basin exhibiting higher perceptions of risk due to cumulative pollution and frequent disaster impacts. Based on these insights, the study recommends targeted strategies to bridge risk perception gaps, including tailored risk communication, community-based environmental education and stronger institutional trust-building initiatives, all aimed at fostering more effective and inclusive environmental governance in the Nigua basin.
Molecular Basis of Oncogenic PI3K Proteins
Sheng, Zhi; Beck, Patrick; Gabby, Maegan; Habte-Mariam, Semhar; Mitkos, Katherine (MDPI, 2024-12-30)
The dysregulation of phosphatidylinositol 3-kinase (PI3K) signaling plays a pivotal role in driving neoplastic transformation by promoting uncontrolled cell survival and proliferation. This oncogenic activity is primarily caused by mutations that are frequently found in PI3K genes and constitutively activate the PI3K signaling pathway. However, tumorigenesis can also arise from nonmutated PI3K proteins adopting unique active conformations, further complicating the understanding of PI3K-driven cancers. Recent structural studies have illuminated the functional divergence among highly homologous PI3K proteins, revealing how subtle structural alterations significantly impact their activity and contribute to tumorigenesis. In this review, we summarize current knowledge of Class I PI3K proteins and aim to unravel the complex mechanism underlying their oncogenic traits. These insights will not only enhance our understanding of PI3K-mediated oncogenesis but also pave the way for the design of novel PI3K-based therapies to combat cancers driven by this signaling pathway.
Application of Various Hydrological Modeling Techniques and Methods in River Basin Management
Srivastava, Ankur; Sridhar, Venkataramana; Kumari, Nikul (MDPI, 2025-01-01)
The techniques of hydrological modeling have greatly improved in the recent past and have been instrumental in the management of river basins [...]
Modular Modeling of a Half-Vehicle System Using Generalized Receptance Coupling and Frequency-Based Substructuring (GRCFBS)
Hamedi, Behzad; Taheri, Saied (MDPI, 2024-11-11)
This paper presents an advanced modular modeling approach for vertical vibration analysis of dynamic systems using the Generalized Receptance Coupling and Frequency-Based Substructuring (GRCFBS) method. The focus is on a four-DoF half-vehicle model comprising three key subsystems: front suspension, rear suspension, and the vehicle’s trimmed body. The proposed technique is designed to predict dynamic responses in reconfigurable systems across various applications, including automotive, robotics, mechanical machinery, and aerospace structures. By coupling the receptance matrices (FRFs) of individual vehicle modules, the overall system receptance matrix is efficiently derived in a disassembled configuration. Two generalized coupling methods, originally developed by Jetmundsen and D.D. Klerk, are employed to determine the complete vehicle’s receptance matrix from its subsystems. Validation is achieved by comparing the results with established methods, such as direct solution and modal analysis, demonstrating high accuracy and reliability for complex dynamic systems. This modular approach allows for the creation of reduced-order models focused on key measurement points without the need for detailed system representation. The method offers significant advantages in early-stage vehicle development, providing critical insights into system vibration behavior.
A GNN-Based QSPR Model for Surfactant Properties
Ham, Seokgyun; Wang, Xin; Zhang, Hongwei; Lattimer, Brian; Qiao, Rui (MDPI, 2024-11-19)
Surfactants are among the most versatile molecules in the chemical industry because they can self-assemble in bulk solutions and at interfaces. Predicting the properties of surfactant solutions, such as their critical micelle concentration (CMC), limiting surface tension (γcmc), and maximal packing density (Γmax) at water–air interfaces, is essential to their rational design. However, the relationship between surfactant structure and these properties is complex and difficult to predict theoretically. Here, we develop a graph neural network (GNN)-based quantitative structure–property relationship (QSPR) model to predict the CMC, γcmc, and Γmax. Ninety-two surfactant data points, encompassing all types of surfactants—anionic, cationic, zwitterionic, and nonionic—are fed into the model, covering a temperature range of [20–30 °C], which contributes to its generalization across all surfactant types. We show that our models have high accuracy (R² = 0.87 on average in tests) in predicting the three parameters across all types of surfactants. The effectiveness of the QSPR model in capturing the variation of CMC, γcmc, and Γmax with molecular design parameters are carefully assessed. The curated dataset, developed model, and critical assessment of the developed model will contribute to the development of improved surfactants QSPR models and facilitate their rational design for diverse applications.
Potential of Stem-Cell-Induced Peripheral Nerve Regeneration: From Animal Models to Clinical Trials
Wynne, Taylor M.; Fritz, Virginia Grey; Simmons, Zachary T.; Zahed, Malek; Seth, Ananya; Abbasi, Tamir; Reymundi, Michael J.; Roballo, Kelly C. S. (MDPI, 2024-11-23)
Peripheral nerve injury has become an increasingly prevalent clinical concern, causing great morbidity in the community. Although there have been significant advancements in the treatment of peripheral nerve damage in recent years, the issue of long-term nerve regeneration remains. Furthermore, Wallerian degeneration has created an obstacle to long-term nerve regeneration. For this reason, there has been extensive research on the use of exogenous and endogenous stem cells as an adjunct or even primary treatment option for peripheral nerve injury. The plasticity and inducibility of stem cells make them an enticing option for initiating neuronal cell regrowth and optimal sensory and functional nerve regeneration. Peripheral nerve injury has a broad range of causative factors and etiologies. As such, unique stem cell-induced peripheral nerve treatments are being investigated to ameliorate the damage incited by all causes, including trauma, neuropathy, and systemic neurodegenerative diseases. This review is oriented to outline the potential role of stem cell therapies in peripheral nerve injury versus the current standards of care, compare the benefits and drawbacks of specific stem cell lines under investigation, and highlight the current models of stem cell therapy in the peripheral nervous system, with the ultimate goal of narrowing down and optimizing the role and scope of stem cell therapy in peripheral nerve injury.
Energy Backflow in Unidirectional Monochromatic and Space–Time Waves
Saari, Peeter; Besieris, Ioannis M. (MDPI, 2024-11-29)
Backflow, or retropropagation, is a counterintuitive phenomenon whereby for a forward-propagating wave the energy locally propagates backward. In the context of backflow, physically most interesting are the so-called unidirectional waves, which contain only forward-propagating plane wave constituents. Yet, very few such waves possessing closed-form analytic expressions for evaluation of the Poynting vector are known. In this study, we examine energy backflow in a novel (2+time)-dimensional unidirectional monochromatic wave and in a (2+1)D spatiotemporal wavepacket, analytic expressions which we succeeded to find. We also present a detailed study of the backflow in the “needle” pulse. This is an interesting model object because well-known superluminal non-diffracting space–time wave packets can be derived from its simple factored wave function. Finally, we study the backflow in an unidirectional version of the so-called focus wave mode—a pulse propagating luminally and without spread, which is the first and most studied representative of the (3+1)D non-diffracting space–time wave packets (also referred to as spatiotemporally localized waves).

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