Dynamic environmental conditions, such as climate change and host availability, have greatly influenced the expansion of medically relevant tick vectors into new regions throughout the southeastern United States of America. As tick populations migrate into new areas, it has been suggested they can exhibit a phenomenon known as incomplete feeding. With this phenomenon, tick vectors feed on more than one host at each life stage, thus increasing the likelihood of pathogen transmission. Although this behavior is not well understood, it presents an important threat to human health. Here we present evidence of incomplete feeding behaviors in multiple tick species in South Carolina. Engorged, blood-fed female ticks were collected from feral dogs at animal shelters across South Carolina in 2022. All ticks were tested for human blood meals using rapid stain identification blood tests. Approximately one third (33.78%) of all ticks tested positive for a human blood meal, with various patterns seen across species, geographic location, and collection month. The results of this pilot study follow the current national trend of increasing rates of tick-borne disease incidence in the southeastern United States of America and warrant further investigation into the relationship between seasonality, geographic distribution, species, and incomplete feeding among tick populations in South Carolina. Full article

Monitoring heart conditions through electrocardiography (ECG) has been the cornerstone of identifying cardiac irregularities. Cardiologists often rely on a detailed analysis of ECG recordings to pinpoint deviations that are indicative of heart anomalies. This traditional method, while effective, demands significant expertise and is susceptible to inaccuracies due to its manual nature. In the realm of computational analysis, Artificial Neural Networks (ANNs) have gained prominence across various domains, which can be attributed to their superior analytical capabilities. Conversely, Spiking Neural Networks (SNNs), which mimic the neural activity of the brain more closely through impulse-based processing, have not seen widespread adoption. The challenge lies primarily in the complexity of their training methodologies. Despite this, SNNs offer a promising avenue for energy-efficient computational models capable of displaying a high-level performance. This paper introduces an innovative approach employing SNNs augmented with an attention mechanism to enhance feature recognition in ECG signals. By leveraging the inherent efficiency of SNNs, coupled with the precision of attention modules, this model aims to refine the analysis of cardiac signals. The novel aspect of our methodology involves adapting the learned parameters from ANNs to SNNs using leaky integrate-and-fire (LIF) neurons. This transfer learning strategy not only capitalizes on the strengths of both neural network models but also addresses the training challenges associated with SNNs. The proposed method is evaluated through extensive experiments on two publicly available benchmark ECG datasets. The results show that our model achieves an overall accuracy of 93.8% on the MIT-BIH Arrhythmia dataset and 85.8% on the 2017 PhysioNet Challenge dataset. This advancement underscores the potential of SNNs in the field of medical diagnostics, offering a path towards more accurate, efficient, and less resource-intensive analyses of heart diseases. Full article

In this paper, we propose a novel, vision-transformer-based end-to-end pose estimation method, LidPose, for real-time human skeleton estimation in non-repetitive circular scanning (NRCS) lidar point clouds. Building on the ViTPose architecture, we introduce novel adaptations to address the unique properties of NRCS lidars, namely, the sparsity and unusual rosetta-like scanning pattern. The proposed method addresses a common issue of NRCS lidar-based perception, namely, the sparsity of the measurement, which needs balancing between the spatial and temporal resolution of the recorded data for efficient analysis of various phenomena. LidPose utilizes foreground and background segmentation techniques for the NRCS lidar sensor to select a region of interest (RoI), making LidPose a complete end-to-end approach to moving pedestrian detection and skeleton fitting from raw NRCS lidar measurement sequences captured by a static sensor for surveillance scenarios. To evaluate the method, we have created a novel, real-world, multi-modal dataset, containing camera images and lidar point clouds from a Livox Avia sensor, with annotated 2D and 3D human skeleton ground truth. Full article

Protein hydrolysates (PH) and humic substances (HS) are biostimulants that promote crop growth. Despite the widening of knowledge and insights provided by research activities over the past thirty years, there are still uncertainties concerning the possible direct absorption by plants of organic nitrogen as amino acids (AA) delivered as PH and the role of HS. This study aimed to assess the impact of PH treatment on the amino acid profile of maize seedlings and the influence of HS on amino acid uptake. Maize seedlings were treated with either PH from the yeast of the sugarcane fermentation process or a synthetic mixture of amino acids mimicking the PH composition using dual-labeled amino acids (¹³C, ¹⁵N glutamic acid) combined with commercially available humic substances. The amino acid profile was analyzed using HPLC, and plant tissues were examined for ¹⁵N using nuclear magnetic resonance (NMR) and mass spectrometry. The application of PH stimulated maize growth, with a more significant effect observed in the presence of humic substances. The treatments significantly altered the plants’ total amino acid content and composition profile. Maize seedlings actively uptake amino acids, representing 21% of the total nitrogen composition. The ascertained improvement of amino acid uptake stimulated by humic substances is associated with their effect on the differential expression of amino permease transporters and plasma membrane H⁺-ATPase. PH and amino acids enhance maize growth by significantly increasing amino acid uptake. The addition of humic substances further improved the biostimulant effects. Full article

Binge alcohol consumption during adolescence can produce lasting deficits in learning and memory while also increasing the susceptibility to substance use disorders. The adolescent intermittent ethanol (AIE) rodent model mimics human adolescent binge drinking and has identified the nucleus basalis magnocellularis (NbM) as a key site of pathology. The NbM is a critical regulator of prefrontal cortical (PFC) cholinergic function and attention. The cholinergic phenotype is controlled pro/mature neurotrophin receptor activation. We sought to determine if p75NTR activity contributes to the loss of cholinergic phenotype in AIE by using a p75NTR modulator (LM11A-31) to inhibit prodegenerative signaling during ethanol exposure. Male and female rats underwent 5 g/kg ethanol (AIE) or water (CON) exposure following 2-day-on 2-day-off cycles from postnatal day 25–57. A subset of these groups also received a protective dose of LM11A-31 (50 mg/kg) during adolescence. Rats were trained on a sustained attention task (SAT) and behaviorally relevant acetylcholine (ACh) activity was recorded in the PFC with a fluorescent indicator (AChGRAB 3.0). AIE produced learning deficits on the SAT, which were spared with LM11A-31. In addition, PFC ACh activity was blunted by AIE, which LM11A-31 corrected. Investigation of NbM ChAT+ and TrkA+ neuronal expression found that AIE led to a reduction of ChAT+TrkA+ neurons, which again LM11A-31 protected. Taken together, these findings demonstrate the p75NTR activity during AIE treatment is a key regulator of cholinergic degeneration. Full article

Drought may considerably decrease the growth and yield of potatoes. Small tubers may have lower performance and be more sensitive to abiotic stresses than larger tubers. Since an increase in drought areas may be expected, the development of potato varieties with drought tolerance has become necessary. Two-year greenhouse experiments were conducted to test the drought tolerance of potato breeding lines (C103, C107, C20) with great osmotic stress tolerance. Minitubers with diameters of 25–35, 20–24, 15–19 and 10–14 mm were planted. Treatments were the optimal irrigated control (100%) and moderate and severe drought (60% and 20% of optimum water supply). To study the after-effects of drought, tubers from different treatments were planted separately the following year because seed tuber priming may increase drought tolerance. Seed tubers (25–35 mm), two irrigation treatments (control and severe drought), and two control cultivars were used in the second year. We observed the rate of emergence from day-after-planting (DAP) 20 to 30 and flowering from 48 to 54. NDVI measurements were performed on the DAP35-45-75. Plant height and fresh weight of aboveground biomass (AGB) were recorded on DAP76. Harvested tubers were counted, weighed, and size-categorized, and then the number and fresh tuber yield per plant (TN and TY) were calculated. Stress indices (SI) were calculated as percentages of the results of control plots to compare the responses of genotypes to drought stress. We found that each breeding line showed adequate drought tolerance, although only the C103 and C107 breeding lines were stable in in vivo conditions. SI values for tuber number/tuber yield were 103/57; 102/63; 83/52; 80/58 and 55/41 in C103, C107, C20, ‘Boglárka’ and ‘Desiree’ (the last two were control varieties), respectively. The size of the seed tuber significantly affected each character, and usually minitubers larger than 20 mm performed better than smaller ones. No significant after-effect of drought stress on the next generation was found. Although we found a positive correlation (r=0.83) between NDVI values and yield parameters, the correlations in our study were not consistent in all genotypes and water treatments. Full article

This study examined 430 Chinese college students’ engagement in arts activities and the psychological benefits derived from such activities. The research differentiated between various types of arts participation and ways of involvement and examined four potential positive psychological outcomes. The findings revealed correlations between (1) creative participation in the performing arts, ‘flow’, and aesthetic emotions; (2) consumptive participation in the visual arts and aesthetic emotions; and (3) creative participation in the literary arts and ego identity. Holistic arts participation demonstrated a significantly positive relationship with flourishing. A path analysis showed that flow experience and aesthetic emotions served as mediators in the mechanism through which holistic arts participation affected flourishing, with a chained mediation effect from flow experience to ego identity. This study confirms that arts participation is an effective pathway for individual flourishing and that more diverse and profound engagement in the arts can lead to sustained and widespread happiness. Full article

In order to cleanly and efficiently extract zirconium from zircon sand (the main component is ZrSiO₄), sodium hydroxide sub-molten salt was used to decompose ZrSiO₄ in this study. When ZrSiO₄ reacts with sodium hydroxide sub-molten salt, the formation of Na₂ZrSiO₅ (a water-insoluble product) considerably affects the separation efficiency of Zr and Si and increases production cost. Thus, it is necessary to control the formation of Na₂ZrSiO₅. The influence of NaOH content, reaction temperature, reaction time, and NaOH/ore mass ratio on the formation of Na₂ZrSiO₅ were systematically investigated. The optimum reaction parameters for the inhibition of Na₂ZrSiO₅ formation were as follows: 80% NaOH content, 245 °C reaction temperature, 4:1 NaOH/ore mass ratio, 10 h reaction time, and 400 r/min agitation speed. These results indicate that ZrSiO₄ is decomposed to Na₂ZrO₃ and Na₂SiO₃ by reacting with NaOH, realizing the separation of Zr and Si, and then the reactions between Na₂ZrO₃ and Na₂SiO₃ result in the formation of Na₂ZrSiO₅, during the decomposition of ZrSiO₄ using NaOH sub-molten salt. The sub-molten salt decomposition process can realize the clean extraction of zirconium, which is conducive to the sustainable development of zirconium resources. Full article

Hydrogen combustion engine vehicles have the potential to rapidly enter the market and reduce greenhouse gas emissions (GHG) compared to conventional engines. The ability to provide a rapid market deployment is linked to the fact that the industry would take advantage of the existing internal combustion engine production chain. The aim of this paper is twofold. First, it aims to develop a methodology for applying life-cycle assessment (LCA) to internal combustion engines to estimate their life-cycle GHG emissions. Also, it aims to investigate the decarbonization potential of hydrogen engines produced by exploiting existing diesel engine technology and assuming diverse hydrogen production routes. The boundary of the LCA is cradle-to-grave, and the assessment is entirely based on primary data. The products under study are two monofuel engines: a hydrogen engine and a diesel engine. The hydrogen engine has been redesigned using the diesel engine as a base. The engines being studied are versatile and can be used for a wide range of uses such as automotive, cogeneration, maritime, off-road, and railway; however, this study focuses on their application in pickup trucks. As part of the redesign process, certain subsystems (e.g., combustion, injection, ignition, exhaust gas recirculation, and exhaust gas aftertreatment) have been modified to make the engine run on hydrogen. Results revealed that employing a hydrogen engine using green hydrogen (i.e., generated from water electrolysis using wind-based electricity) might reduce GHG emission by over 90% compared to the diesel engine This study showed that the benefits of the new hydrogen engine solution outweigh the increase of emissions related to the redesign process, making it a potentially beneficial solution also for reconditioning current and used internal combustion engines. Full article

Carbon-fiber-reinforced polyimide (PI) resin composites have gained significant attention in the field of continuous-fiber-reinforced polymers, in which the interfacial bonding between carbon fiber and matrix resin has been an important research direction. This study designed and prepared a water-soluble thermoplastic polyamide acid sizing agent to improve the wettability of carbon fiber, enhance the van der Waals forces between carbon fiber and resin and strengthen the chemical bonding between the sizing agent and the alkyne-capped polyimide resin by introducing alkyne-containing functional groups into the sizing agent. This study found that the addition of a sizing layer effectively bridged the large modulus difference between the fiber and resin regions, resulting in the formation of an interfacial layer approximately 85 nm thick. This layer facilitated the transfer of stress from the matrix to the reinforced carbon fiber, leading to a significant improvement in the interfacial properties of the composites. Adjusting the concentration of the sizing agent showed that composites treated with 3% had the best interfacial properties. The interfacial shear strength increased from 82.08 MPa to 108.62 MPa (32.33%) compared to unsized carbon fiber. This research is significant for developing sizing agents suitable for carbon-fiber-reinforced polyimide composites. Full article

Bacteria, fungi, and protists occupy a pivotal position in maintaining soil ecology. Despite limited knowledge on their responses to managed vegetation restoration strategies in karst regions, we aimed to study the essential microbial communities involved in the process of vegetation restoration. We compared microbial characteristics in four land use types: planted forests (PF), forage grass (FG), a mixture of plantation forest and forage grass (FF), and cropland (CR) as a reference. Our findings revealed that the richness of bacteria and protists was higher in FF compared to PF, while fungal richness was lower in both PF and FF than in CR. Additionally, the bacterial Shannon index in FF was higher than that in CR and PF, while the fungal and protist Shannon indices were similar across all four land use types. Significant differences were observed in the compositions of bacterial, fungal, and protist communities between FF and the other three land use types, whereas bacterial, fungal, and protist communities were relatively similar in PF and FG. In FF, the relative abundance of bacterial taxa Acidobacteria, Firmicutes, and Gemmatimonadetes was significantly higher than in PF and CR. Fungal communities were dominated by Ascomycota and Basidiomycota, with the relative abundance of Ascomycota significantly higher in FF compared to other land use types. Regarding protistan taxa, the relative abundance of Chlorophyta was higher in FF compared to CR, PF, and FG, while the relative abundance of Apicomplexa was higher in CR compared to FF. Importantly, ammonium nitrogen, total phosphorus, and microbial biomass nitrogen were identified as key soil properties predicting changes in the diversity of bacteria, fungi, and protists. Our results suggest that the microbial community under FF exhibits greater sensitivity to vegetation restoration compared to PF and FG. This sensitivity may stem from differences in soil properties, the formation of biological crusts and root systems, and management activities, resulting in variations in bacterial, fungal, and protist diversity and taxa in PF. As a result, employing a combination restoration strategy involving plantation forest and forage grass proves to be an effective approach to enhance the microbial community and thereby improve ecosystem functionality in ecologically fragile areas. Full article

Type 2 diabetes mellitus (T2DM) management and glycemic control in underserved non-Hispanic Black adults presents with multifaceted challenges: balancing the optimal complexity of antihyperglycemic medications prescribed, limited medication access due to socioeconomic status, medication nonadherence, and high prevalence of cardiometabolic comorbidities. This single-center, cross-sectional, retrospective chart analysis evaluated the association of Medication Regimen Complexity (MRC) with cardiometabolic outcomes (glycemic, atherogenic cholesterol, and blood pressure control) among non-Hispanic Black adults with type 2 diabetes. Utilizing 470 independent patient electronic health records, MRC and other covariates were examined to determine their associations with cardiometabolic outcomes. Chi-square tests of independence and multiple logistic regression were performed to identify associations between MRC and cardiometabolic outcomes. Our findings indicate significant negative and positive associations between MRC and glycemic control and atherogenic cholesterol control, respectively. However, there were no associations between MRC and blood pressure control. As diabetes MRC was shown to be associated with poor glycemic control and improved atherogenic cholesterol control, there is a critical need to standardize interdisciplinary diabetes care to include pharmacists and to develop more insurance policy interventions that increase access to newer, efficacious diabetes medications for historically marginalized populations. Full article

The increase in Cervical Spondylosis cases and the expansion of the affected demographic to younger patients have escalated the demand for X-ray screening. Challenges include variability in imaging technology, differences in equipment specifications, and the diverse experience levels of clinicians, which collectively hinder diagnostic accuracy. In response, a deep learning approach utilizing a ResNet-34 convolutional neural network has been developed. This model, trained on a comprehensive dataset of 1235 cervical spine X-ray images representing a wide range of projection angles, aims to mitigate these issues by providing a robust tool for diagnosis. Validation of the model was performed on an independent set of 136 X-ray images, also varied in projection angles, to ensure its efficacy across diverse clinical scenarios. The model achieved a classification accuracy of 89.7%, significantly outperforming the traditional manual diagnostic approach, which has an accuracy of 68.3%. This advancement demonstrates the viability of deep learning models to not only complement but enhance the diagnostic capabilities of clinicians in identifying Cervical Spondylosis, offering a promising avenue for improving diagnostic accuracy and efficiency in clinical settings. Full article

Class IIa bacteriocins produced in lactic acid bacteria are short cationic peptides with antimicrobial activity. In the search for new biopreservation agents, class IIa bacteriocins are considered to be the best potential candidates, not only due to their large abundance but also because of their high biological activity and excellent thermal stability. However, regulated by the biosynthetic regulatory system, the natural class IIa bacteriocin yield is low, and the extraction process is complicated. The biotechnological production of class IIa bacteriocins in various cell factories has been attempted to improve this situation. In this review, we focus on the application of biotechnological routes for class IIa bacteriocin production. The drawbacks and improvements in the production of class IIa bacteriocins in various cell factories are discussed. Furthermore, we present the main challenge of class IIa bacteriocins, focusing on increasing their production by constructing suitable cell factories. Recombinant bacteriocins have made considerable progress from inclusion body formation, dissolved form and low antibacterial activity to yield recovery. The development of prospective cell factories for the biotechnological production of bacteriocins is still required, which may facilitate the application of bacteriocins in the food industry. Full article

Despite being an effective chemotherapeutic agent, the clinical use of doxorubicin (DOX) is limited by several organ toxicities including hepatic injury. Pentoxifylline (PTX) is a methylxanthine derivative with marked anti-inflammatory and anti-apoptotic features. It is unknown, however, whether PTX can mitigate DOX-evoked hepatotoxicity. This study aims to explore the potential hepatoprotective impact of PTX in DOX-induced hepatic injury and the underlying molecular mechanisms. Histopathology, immunohistochemistry, and ELISA were used to examine liver tissues. The current findings revealed that PTX administration to DOX-intoxicated rats mitigated the pathological manifestations of hepatic injury, reduced microscopical damage scores, and improved serum ALT and AST markers, revealing restored hepatic cellular integrity. These favorable effects were attributed to PTX’s ability to mitigate inflammation by reducing hepatic IL-1β and TNF-α levels and suppressing the pro-inflammatory HMGB1/TLR4/NF-κB axis. Moreover, PTX curtailed the hepatic apoptotic abnormalities by suppressing caspase 3 activity and lowering the Bax/Bcl-2 ratio. In tandem, PTX improved the defective autophagy events by lowering hepatic SQSTM-1/p62 accumulation and enhancing the AMPK/mTOR pathway, favoring autophagy and hepatic cell preservation. Together, for the first time, our findings demonstrate the ameliorative effect of PTX against DOX-evoked hepatotoxicity by dampening the hepatic HMGB1/TLR4/NF-κB pro-inflammatory axis and augmenting hepatic AMPK/mTOR-driven autophagy. Thus, PTX could be utilized as an adjunct agent with DOX regimens to mitigate DOX-induced hepatic injury. Full article

In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies. This article focuses on exploring the integration of AR in Industry 4.0, with a particular emphasis on its role in improving technical assistance and training. The research addresses the ways in which AR not only facilitates more efficient processes but also acts as an essential bridge for training and skills development in constantly changing technological environments. It investigates the significant impact of AR on both optimising work processes and training workers to meet the emerging challenges of Industry 4.0. Through a qualitative analysis, the studies are categorised according to their application domains, grouping them into specific thematic areas. Subsequently, a meta-analysis is conducted to determine the actual impact of AR in the sector. The findings reveal a positive and significant correlation between the implementation of AR and its effectiveness in assistance and training in the framework of Industry 4.0. Finally, the article delves into an analysis of current limitations and challenges, providing insights into possible developments and trends in the use of AR for assistance and training in Industry 4.0. Full article

In recent years, the awareness that pesticides can have other effects apart from generic toxicity is growing. In particular, several pieces of evidence highlight their influence on human fertility. In this study, we investigated, by a virtual screening approach, the binding between pesticides and proteins present in human gametes or associated with reproduction, in order to identify new interactions that could affect human fertility. To this aim, we prepared ligand (pesticides) and receptor (proteins) 3D structure datasets from online structural databases (such as PubChem and RCSB), and performed a virtual screening analysis using Autodock Vina. In the comparison of the predicted interactions, we found that famoxadone was predicted to bind Cellular Retinol Binding Protein-III in the retinol-binding site with a better minimum energy value of −10.4 Kcal/mol and an RMSD of 3.77 with respect to retinol (−7.1 Kcal/mol). In addition to a similar network of interactions, famoxadone binding is more stabilized by additional hydrophobic patches including L20, V29, A33, F57, L117, and L118 amino acid residues and hydrogen bonds with Y19 and K40. These results support a possible competitive effect of famoxadone on retinol binding with impacts on the ability of developing the cardiac tissue, in accordance with the literature data on zebrafish embryos. Moreover, famoxadone binds, with a minimum energy value between −8.3 and −8.0 Kcal/mol, to the IZUMO Sperm–Egg Fusion Protein, interacting with a network of polar and hydrophobic amino acid residues in the cavity between the 4HB and Ig-like domains. This binding is more stabilized by a predicted hydrogen bond with the N185 residue of the protein. A hindrance in this position can probably affect the conformational change for JUNO binding, avoiding the gamete membrane fusion to form the zygote. This work opens new interesting perspectives of study on the effects of pesticides on fertility, extending the knowledge to other typologies of interaction which can affect different steps of the reproductive process. Full article

Non-impregnated small-pore graphite (NSPG), which has a compact microstructure and is used in molten salt reactors (MSRs), was prepared by a novel process. The pore diameter of NSPG was reduced to ~800 nm. The irradiation evaluation of NSPG was carried out by 7 MeV Xe²⁶⁺ ion irradiation. The microstructural changes of NSPG were investigated with IG-110 as a comparison. The graphitization degree of NSPG was higher than that of IG-110, though it was not subjected to an impregnation process. Under low-dose ion irradiation (<2.5 dpa), the microscopic morphology of the NSPG changes in a small magnitude, and the lamellar structure of graphite remains within the scale of more than a dozen nanometers, which exhibits a better resistance to irradiation. With the increase in irradiation dose, the accumulation of defects leads the graphite toward amorphization, which shows consistency with IG-110. This study provides an efficient and low-cost method for the preparation of graphite for MSR, and investigates the damage behavior of graphite, which is of great significance in accumulating data for the development of MSR nuclear graphite and the optimal design of graphite materials. Full article

Dongba characters are ancient ideographic scripts with abstract expressions that differ greatly from modern Chinese characters; directly applying existing methods cannot achieve the font style transfer of Dongba characters. This paper proposes an Attention-based Font style transfer Generative Adversarial Network (AFGAN) method. Based on the characteristics of Dongba character images, two core modules are set up in the proposed AFGAN, namely void constraint and font stroke constraint. In addition, in order to enhance the feature learning ability of the network and improve the style transfer effect, the Convolutional Block Attention Module (CBAM) mechanism is added in the down-sampling stage to help the network better adapt to input font images with different styles. The quantitative and qualitative analyses of the generated font and the real font were conducted by consulting with professional artists based on the newly built small seal script, slender gold script, and Dongba character dataset, and the styles of the small seal script and slender gold script were transferred to Dongba characters. The results indicate that the proposed AFGAN method has advantages in evaluation indexes and visual quality compared to existing networks. At the same time, this method can effectively learn the style features of small seal script and slender gold script, and transfer them to Dongba characters, indicating the effectiveness of this method. Full article

Aspergillus cristatus is a crucial edible fungus used in tea fermentation. In the industrial fermentation process, the fungus experiences a low to high osmotic pressure environment. To explore the law of material metabolism changes during osmotic pressure changes, NaCl was used here to construct different osmotic pressure environments. Liquid chromatography–mass spectrometry (LC–MS) combined with multivariate analysis was performed to analyze the distribution and composition of A. cristatus under different salt concentrations. At the same time, the in vitro antioxidant activity was evaluated. The LC–MS metabolomics analysis revealed significant differences between three A. cristatus mycelium samples grown on media with and without NaCl concentrations of 8% and 18%. The contents of gibberellin A3, A124, and prostaglandin A2 related to mycelial growth and those of arabitol and fructose-1,6-diphosphate related to osmotic pressure regulation were significantly reduced at high NaCl concentrations. The biosynthesis of energy-related pantothenol and pantothenic acid and antagonism-related fluvastatin, aflatoxin, and alternariol significantly increased at high NaCl concentrations. Several antioxidant capacities of A. cristatus mycelia were directly related to osmotic pressure and exhibited a significant downward trend with an increase in environmental osmotic pressure. The aforementioned results indicate that A. cristatus adapts to changes in salt concentration by adjusting their metabolite synthesis. At the same time, a unique set of strategies was developed to cope with high salt stress, including growth restriction, osmotic pressure balance, oxidative stress response, antioxidant defense, and survival competition. Full article

Subgrid scale models for unresolved turbulent fluxes are investigated, with a focus on combustion for space propulsion applications. An extension to the gradient model is proposed, introducing a dependency on the local burning regimen. The dynamic behaviors of the model’s coefficients are investigated, and scaling laws are studied. The discussed models are validated using a DNS database of a high-pressure, turbulent, fuel-rich methane–oxygen diffusion flame. The operating point and turbulence characteristics are selected to resemble those of modern combustors for space propulsion applications to support the future usage of the devised model in this context. Full article

This is a summary of the main results within the Scale-Invariant Vacuum (SIV) paradigm based on Weyl integrable geometry. We also review the mathematical framework and utilize alternative derivations of the key equations based on the reparametrization invariance as well. The main results discussed are related to the early universe; that is, applications to inflation, Big Bang Nucleosynthesis, and the growth of the density fluctuations within the SIV. Some of the key SIV results for the early universe are a natural exit from inflation within the SIV in a later time $t_{\mathrm{exit}}$ with value related to the parameters of the inflationary potential along with the possibility for the density fluctuations to grow sufficiently fast within the SIV without the need for dark matter to seed the growth of structure in the universe. In the late-time universe, the applications of the SIV paradigm are related to scale-invariant dynamics of galaxies, MOND, dark matter, and dwarf spheroidals, where one can find MOND to be a peculiar case of the SIV theory. Finally, within the recent time epoch, we highlight that some of the change in the length-of-the-day (LOD), about 0.92 cm/yr, can be accounted for by SIV effects in the Earth–Moon system. Full article