Leaf nitrogen concentration (LNC) is a primary indicator of crop nitrogen status, closely related to the growth and development dynamics of crops. Accurate and efficient monitoring of LNC is significant for precision field crop management and enhancing crop productivity. However, the biochemical properties and canopy structure of wheat change across different growth stages, leading to variations in spectral responses that significantly impact the estimation of wheat LNC. This study aims to investigate the construction of feature combination indices (FCIs) sensitive to LNC across multiple wheat growth stages, using remote sensing data to develop an LNC estimation model that is suitable for multiple growth stages. The research employs UAV multispectral remote sensing technology to acquire canopy imagery of wheat during the early (Jointing stage and Booting stage) and late (Early filling and Late filling stages) in 2021 and 2022, extracting spectral band reflectance and texture metrics. Initially, twelve sensitive spectral feature combination indices (SFCIs) were constructed using spectral band information. Subsequently, sensitive texture feature combination indices (TFCIs) were created using texture metrics as an alternative to spectral bands. Machine learning algorithms, including partial least squares regression (PLSR), random forest regression (RFR), support vector regression (SVR), and Gaussian process regression (GPR), were used to integrate spectral and texture information, enhancing the estimation performance of wheat LNC across growth stages. Results show that the combination of Red, Red edge, and Near-infrared bands, along with texture metrics such as Mean, Correlation, Contrast, and Dissimilarity, has significant potential for LNC estimation. The constructed SFCIs and TFCIs both enhanced the responsiveness to LNC across multiple growth stages. Additionally, a sensitive index, the Modified Vegetation Index (MVI), demonstrated significant improvement over NDVI, correcting the over-saturation concerns of NDVI in time-series analysis and displaying outstanding potential for LNC estimation. Spectral information outperforms texture information in estimation capability, and their integration, particularly with SVR, achieves the highest precision (coefficient of determination (R²) = 0.786, root mean square error (RMSE) = 0.589%, and relative prediction deviation (RPD) = 2.162). In conclusion, the sensitive FCIs developed in this study improve LNC estimation performance across multiple growth stages, enabling precise monitoring of wheat LNC. This research provides insights and technical support for the construction of sensitive indices and the precise management of nitrogen nutrition status in field crops. Full article

Cordycepin is the primary active compound of Cordyceps militaris. However, the definitive genetic mechanism governing cordycepin synthesis in fruiting body growth and development remains elusive, necessitating further investigation. This study consists of 64 C. militaris strains collected from northeast China. The high-yielding cordycepin strain CMS19 was selected for the analysis of cordycepin production and the genetic basis of cordycepin anabolism. First, the whole-genome sequencing of CMS19 yielded a final size of 30.96 Mb with 8 contigs and 9781 protein-coding genes. The genome component revealed the presence of four additional secondary metabolite gene clusters compared with other published genomes, suggesting the potential for the production of new natural products. The analyses of evolutionary and genetic differentiation revealed a close relationship between C. militaris and Beauveria bassiana. The population of strains distributed in northeast China exhibited the significant genetic variation. Finally, functional genes associated with cordycepin synthesis were identified using a combination of genomic and transcriptomic analyses. A large number of functional genes associated with energy and purine metabolism were significantly enriched, facilitating the reconstruction of a hypothetical cordycepin metabolic pathway. Therefore, our speculation of the cordycepin metabolism pathway involved 24 genes initiating from the glycolysis and pentose phosphate pathways, progressing through purine metabolism, and culminating in the core region of cordycepin synthesis. These findings could offer fundamental support for scientific utilizations of C. militaris germplasm resources and standardized cultivation for cordycepin production. Full article

Essential oils (EOs) are vital secondary metabolites in plants. They have garnered substantial attention owing to their distinct flavors and desirable attributes, including potent antioxidant, antibacterial, and antitumor properties. Nevertheless, the active constituents of EOs exhibit intricate chemical structures, and conventional separation techniques are inadequate for purifying the individual chemical components from EOs. High-speed countercurrent chromatography, based on the principles of a hydrodynamic equilibrium system, has emerged as a liquid–liquid chromatographic separation method renowned for its ability to handle substantial single injection volumes and the absence of irreversible adsorption. Consequently, in recent years, this technique has been widely employed in the isolation and refinement of natural products. In this review, a comprehensive analysis is conducted, contrasting the merits and demerits of high-speed countercurrent chromatography with conventional separation methods. The solvent systems, elution modes, commonly employed detectors, and practical applications are reviewed in the context of high-speed countercurrent chromatography for essential oil separation and purification. Furthermore, this review offers a glimpse into the potential prospects of applying this technique, with the intention of serving as a valuable reference for the use of high-speed countercurrent chromatography in the purification of EOs. Full article

In this work, PM_2.5 was sampled at Dunkerque, a medium-sized city located in northern France. The mean concentration of PM_2.5 during the sampling period was 12.6 ± 9.5 μg·m⁻³. Samples were analyzed for elemental and organic carbon (EC/OC), water-soluble organic carbon (WSOC), humic-like substances (HULIS-C), water-soluble inorganic ions, and major and trace elements. The origin and the variations of species concentrations were examined using elemental enrichment factors, bivariate polar plot representations, and diagnostic concentration ratios. Secondary inorganic ions were the most abundant species (36% of PM_2.5), followed by OC (12.5% of PM_2.5). Secondary organic carbon (SOC) concentrations were estimated to account for 52% of OC. A good correlation between SOC and WSOC indicated that secondary formation processes significantly contribute to the WSOC concentrations. HULIS-C also represents almost 50% of WSOC. The determination of diagnostic ratios revealed the influence of anthropogenic emission sources such as integrated steelworks and fuel oil combustion. The clustering of 72 h air masses backward trajectories data evidenced that higher concentrations of PM_2.5, OC, and secondary inorganic aerosols were recorded when air masses came from north-eastern Europe and the French continental sector, showing the considerable impact of long-range transport on the air quality in northern France. Full article

Water-based lubricating fluids (WBLFs), known for their significant environmental benefits, are the focus of this study. The properties of WBLFs directly influence lubricated mechanisms’ longevity and operating efficiency. WBLFs are enhanced using additives, which must improve their properties and, at the same time, remain environmentally friendly. This study combines bis(2-hydroxyethyl) ammonium erucate protic ionic liquid and titanium oxide nanoparticles to formulate the hybrid additive. The lubricity was investigated using Alumina/Bearing steel and WC/Bearing steel friction pairs in a reciprocating ball-on-plate tribo-tester. The results show that protic ionic liquid can significantly improve lubricity and the corrosion-preventing ability of the base fluid. Applying a hybrid additive further improved the wear reduction ability in the WC/Bearing steel friction pair. However, the wear reduction ability was diminished when a hybrid additive was used to lubricate the Alumina/Bearing steel friction pair. The proposed lubricity improvement mechanism is based on forming an adsorption layer of ionic liquid molecules and rolling and tribo-sintering titanium oxide nanoparticles. Full article

Herein, the starch nanocrystal/tannic acid (ST) complex particles, which were prepared based on the hydrogen bond between starch nanocrystal (SNC) and tannic acid (TA), were successfully used to stabilize the HIPPE gels. The optimal TA concentration of the ST complex particles resulted in better water dispersibility, surface wettability, and interfacial activity as compared to SNC. The hydrogen bond responsible for the formation of ST complex particles and subsequent stable emulsions was demonstrated by varying the pH and ionic strength of the aqueous phase. Notably, the HIPPE gels stabilized via the ST complex particles can maintain long-term stability for up to three months. The HIPPEs stabilized via the ST complex particles all displayed gel-like features and had smaller droplets and denser droplet networks than the SNC-stabilized HIPPEs. The rheological behavior of HIPPE gels stabilized via the ST complex particles can be readily changed by tuning the mass ratio of SNC and TA as well as pH. Finally, the prepared HIPPE gels used to effectively protect encapsulated β-carotene against high temperatures and ultraviolet radiation and its controllable release at room temperature were demonstrated. It is anticipated that the aforementioned findings will provide new perspectives on the preparation of Pickering emulsion for delivery systems. Full article

In this study, the constant temperature control system of a heating plate was established, ethanol–diesel fuel with different proportions was prepared, and a series of experiments were carried out. The experimental system was used to observe, summarize, and analyze four evaporation and crushing modes of mixed droplets, which were explosion, liquid filament stretching, exocytosis, and ejection mode. The evaporation process of four kinds of mixed droplets in their life cycle was analyzed by normalizing the diameter square. It was proposed that the evaporation process of droplets could be divided into the following three stages: a heating stage, a fluctuating evaporation stage, and an equilibrium evaporation stage. It was also pointed out that the expansion, ejection, and micro-explosion of droplets were the causes of fluctuating evaporation. The concept of expansion and crushing intensity was put forward and the expansion and crushing intensity of ethanol/diesel mixed droplets with different proportions were calculated. The reasons why expansion and crushing intensity first increased and decreased with the increase in ethanol blending ratio were analyzed. Finally, the time proportion of ethanol–diesel mixed droplets in each evaporation stage was calculated, which explained that the time proportion of the instantaneous heating stage showed a parabolic law with the increase in ethanol content. Full article

Polymethoxyflavonoids, such as nobiletin (abundant in Citrus depressa), have been reported to have antioxidant, anti-inflammatory, anticancer, and anti-dementia effects, and are also a circadian clock modulator through retinoic acid receptor-related orphan receptor (ROR) α/γ. However, the optimal timing of nobiletin intake has not yet been determined. Here, we explored the time-dependent treatment effects of nobiletin and a possible novel mechanistic idea for nobiletin-induced circadian clock regulation in mice. In vivo imaging showed that the PER2::LUC rhythm in the peripheral organs was altered in accordance with the timing of nobiletin administration (100 mg/kg). Administration at ZT4 (middle of the light period) caused an advance in the peripheral clock, whereas administration at ZT16 (middle of the dark period) caused an increase in amplitude. In addition, the intraperitoneal injection of nobiletin significantly and potently stimulated corticosterone and adrenaline secretion and caused an increase in Per1 expression in the peripheral tissues. Nobiletin inhibited phosphodiesterase (PDE) 4A1A, 4B1, and 10A2. Nobiletin or rolipram (PDE4 inhibitor) injection, but not SR1078 (RORα/γ agonist), caused acute Per1 expression in the peripheral tissues. Thus, the present study demonstrated a novel function of nobiletin and the regulation of the peripheral circadian clock. Full article

Age-related hearing loss (HL), or presbycusis, is a complex and heterogeneous condition, affecting a significant portion of older adults and involving various interacting mechanisms. Metabolic presbycusis, a type of age-related HL, is characterized by the dysfunction of the stria vascularis, which is crucial for maintaining the endocochlear potential necessary for hearing. Although attention on metabolic presbycusis has waned in recent years, research continues to identify strial pathology as a key factor in age-related HL. This narrative review integrates past and recent research, bridging findings from animal models and human studies, to examine the contributions of the stria vascularis to age-related HL. It provides a brief overview of the structure and function of the stria vascularis and then examines mechanisms contributing to age-related strial dysfunction, including altered ion transport, changes in pigmentation, inflammatory responses, and vascular atrophy. Importantly, this review outlines the contribution of metabolic mechanisms to age-related HL, highlighting areas for future research. It emphasizes the complex interdependence of metabolic and sensorineural mechanisms in the pathology of age-related HL and highlights the importance of animal models in understanding the underlying mechanisms. The comprehensive and mechanistic investigation of all factors contributing to age-related HL, including cochlear metabolic dysfunction, remains crucial to identifying the underlying mechanisms and developing personalized, protective, and restorative treatments. Full article

An hourglass-shaped magnetic field pattern arises naturally from the gravitational collapse of a star-forming gas cloud. Most studies have focused on the prestellar collapse phase, when the structure has a smooth and monotonic radial profile. However, most observations target dense clouds that already contain a central protostar, and possibly a circumstellar disk. We utilize an analytic treatment of the magnetic field along with insights gained from simulations to develop a more realistic magnetic field model for the protostellar phase. Key elements of the model are a strong radial magnetic field in the region of rapid collapse, an off-center peak in the magnetic field strength (a consequence of magnetic field dissipation in the circumstellar disk), and a strong toroidal field that is generated in the region of rapid collapse and outflow generation. A model with a highly pinched and twisted magnetic field pattern in the inner collapse zone facilitates the interpretation of magnetic field patterns observed in protostellar clouds. Full article

The cellulose present in the cell wall of vegetables prevents the greater release of nutrients to the animal. Therefore, the use of the cellulase enzyme is a viable strategy as it is capable of breaking cellulose bonds, releasing nutrients such as glucose, increasing dietary energy, and thus improving the productive performance of birds. Trichoderma reesei is efficient in the production of cellulase, which is produced via submerged fermentation followed by purification, formulation, and drying. Therefore, an experiment was carried out using 240 male broilers of the Cobb-500^® lineage to verify the effects resulting from the addition of powdered (500 g/t and 1000 g/t) and liquid (500 mL/t) cellulase over a period of 1 to 21 days. A completely randomized experimental design was used, consisting of four treatments with six replications and ten birds per replication that were housed in an experimental cage. It was observed that performance and digestibility results were significantly different with cellulase supplementation. Also, the relative weight of the large intestine in the period between one and seven days increased when cellulase was added at 1000 g/t. In the period of between eight and 14 days of life, the birds that consumed only the basal diet obtained higher levels of liver protein than those that received the treatments with the addition of the enzyme. However, 15 and 21 days, the consumed feed effect did not occur between thus, it is not conclusive whether hepatotoxicity occurs with the addition of cellulase. For the blood parameters, at 21 days, the diets with added cellulase were not significantly different regarding electrolytes. It was concluded that this cellulase produced by Trichoderma reesei can be included in the animals’ diet. Full article

This study is an in-depth exploration of the nascent field of Natural Language Processing (NLP) and generative Artificial Intelligence (AI), and it concentrates on the vital task of distinguishing between human-generated text and content that has been produced by AI models. Particularly, this research pioneers the identification of financial text derived from AI models such as ChatGPT and paraphrasing tools like QuillBot. While our primary focus is on financial content, we have also pinpointed texts generated by paragraph rewriting tools and utilized ChatGPT for various contexts this multiclass identification was missing in previous studies. In this paper, we use a comprehensive feature extraction methodology that combines TF–IDF with Word2Vec, along with individual feature extraction methods. Importantly, combining a Random Forest model with Word2Vec results in impressive outcomes. Moreover, this study investigates the significance of the window size parameters in the Word2Vec approach, revealing that a window size of one produces outstanding scores across various metrics, including accuracy, precision, recall and the F1 measure, all reaching a notable value of 0.74. In addition to this, our developed model performs well in classification, attaining AUC values of 0.94 for the ‘GPT’ class; 0.77 for the ‘Quil’ class; and 0.89 for the ‘Real’ class. We also achieved an accuracy of 0.72, precision of 0.71, recall of 0.72, and F1 of 0.71 for our extended prepared dataset. This study contributes significantly to the evolving landscape of AI text identification, providing valuable insights and promising directions for future research. Full article

The co-administration of curcumin and hesperetin might be beneficial in terms of neuroprotective activity; therefore, in this study, we attempted to develop a fixed-dose formulation comprising these two compounds in an amorphous state. The aim of obtaining an amorphous state was to overcome the limitations of the low solubility of the active compounds. First, we assessed the possibility of using popular sweeteners (erythritol, xylitol, and sorbitol) as plasticizers to reduce the glass transition temperature of PVP K30 to prepare the polymer–excipient blends, which allowed the preparation of amorphous solid dispersions via hot-melt extrusion at a temperature below the original glass transition of PVP K30. Erythritol proved to be the superior plasticizer. Then, we focused on the development of fixed-dose amorphous solid dispersions of curcumin and hesperetin. Powder X-ray diffraction and thermal analysis confirmed the amorphous character of dispersions, whereas infrared spectroscopy helped to assess the presence of intermolecular interactions. The amorphous state of the produced dispersions was maintained for 6 months, as shown in a stability study. Pharmaceutical parameters such as dissolution rate, solubility, and in vitro permeability through artificial membranes were evaluated. The best improvement in these features was noted for the dispersion, which contained 15% of the total content of the active compounds with erythritol used as the plasticizer. Full article

Alnus riparian communities are important for ecological stability. Data on Alnus species were gathered from herbaria and literature, revealing that 54.39% of the information refers to Alnus glutinosa, 39.42% to Alnus incana, and 6.18% to Alnus pubescens. This information highlights the widespread occurrence of A. glutinosa and A. incana, as described in distribution maps, contrasting with the more limited range of the hybrid A. pubescens. Principal component analysis (PCA), utilizing standardized factors, was carried out on 217 relevés of the communities of the studied species. In these relevés, we identified a total of 169 plant species, categorized as herbaceous (83%), trees (11%), and shrubs (6%). Three distinct forest communities, Stellario nemorum-Alnetum glutinosae, Alnetum incanae, and Telekio speciosae-Alnetum incanae, emerged from relevé groups. The distribution maps of the three taxa were overlaid on maps of the region’s protected areas, revealing a substantial presence of these taxa within the protected zones. The research aims to highlight the sustainability and conservation importance of Alnus communities in the Romanian Carpathians, to contribute to ongoing conservation efforts and promote the viability and resilience of these ecologically important wetland habitats. Full article

Renewable energy sources (RES) will play a key role in the transition to clean energy. Financial and socio-economic benefits determine the investment management in these energy sources. This article aims to indicate current energy policy goals, present socio-economic benefits resulting from renewable energy investments, and review further development directions in Poland. The research was carried out using desk research, case studies, and literature review methods to provide a broader economic context for RES investments. The scope of the research included both the Polish and the European Union contexts. The authors examined the Polish objectives of investment in renewable energy contained in strategic, planning, and other legal documents compared to EU targets, reviewed possible investments in renewable energy, and indicated wind farms and photovoltaic investments as the most effective ones from the point of view of further development which aims to meet the EU’s goals by 2030. The authors also demonstrated a wide range of socio-economic benefits based on literature reviews, analysis of policy documents, and regulations regarding the energy sector, and examined a specific example of investment implementation and identified the ecosystem of beneficiaries and their benefits. Full article

Forest-dwelling residents frequently collect non-timber forest products (NTFPs) for various reasons, such as food, medicine, firewood, religious reasons, or handicrafts. This study examines the multiple benefits derived from NTFPs and how they contribute to the livelihoods of Ghanaian communities to alleviate poverty. Resources and services provided by NTFPs have an essential role in providing economic, nutritional, medicinal, cultural, and environmental benefits. This study examines the diverse range of NTFPs locals collect, such as chewing sticks, games, herbs, honey, leaves, mushrooms, pestles, raffia and palms, snails, and straws. In addition to serving different purposes, these NTFPs contribute to income generation, food security, health care, cultural practices, and the protection of the environment. A qualitative research approach was used in this study to collect data through semi-structured interviews and focus groups with members on multiple collections of NTFPs and their multiple benefits. We interviewed 732 residents regarding their multiple NTFPs and their potential to improve the livelihood of the locals. The data for the study were analysed using descriptive statistics. As a result of the survey, the frequency and percentages of responses were analysed for each indicator related to multiple values of NTFPs. Both males and females collected a list of NTFPs during the survey. Regarding NTFPs used for sale, 275 were reported, representing 37.57% of the total. In addition to emphasising the importance of sustainable management practices and equitable distribution of benefits, the study explores the multiple benefits of NTFPs for poverty alleviation in Ghanaian communities. It is essential to ensure the conservation of forest ecosystems and promote inclusive policies to harness the potential of NTFPs and maximise their positive impact on livelihoods. NTFPs provide multiple benefits for Ghanaian communities, including income, nutrition, healthcare, cultural preservation, and environmental sustainability. To promote sustainable development, it is imperative to understand the role of NTFPs and implement appropriate strategies. Full article

To meet the increased demand for home workouts owing to the COVID-19 pandemic, this study proposes a new approach to real-time exercise posture classification based on the convolutional neural network (CNN) in an ensemble learning system. By utilizing MediaPipe, the proposed system extracts the joint coordinates and angles of the human body, which the CNN uses to learn the complex patterns of various exercises. Additionally, this new approach enhances classification performance by combining predictions from multiple image frames using an ensemble learning method. Infinity AI’s Fitness Basic Dataset is employed for validation, and the experiments demonstrate high accuracy in classifying exercises such as arm raises, squats, and overhead presses. The proposed model demonstrated its ability to effectively classify exercise postures in real time, achieving high rates in accuracy (92.12%), precision (91.62%), recall (91.64%), and F1 score (91.58%). This indicates its potential application in personalized fitness recommendations and physical therapy services, showcasing the possibility for beneficial use in these fields. Full article

İzmit Bay, a 50 km long inlet at the eastern end of the Marmara Sea, is crucial for the region’s economy, culture, and marine ecosystem. The bay’s water circulation regulates nutrient distribution, stratification, sedimentation, oxygen levels, heat, and pollution levels. It is also influenced by meteorological events, such as short-term moderate to strong wind conditions. This study investigated the sensitivity of İzmit Bay Water Circulation to wind speed, direction, and duration using the MITgcm model with Orlanski boundary conditions and process-oriented modeling. The simulations showed that under weak forcing conditions, seawater temperature, salinity, and stratification do not significantly vary. However, strong forcing and wind speeds (statistically defined by percentiles of observation data) of 4.9 m/s (75%), 6.7 m/s (90%), and 10.1 m/s (99%) generate significant mesoscale and sub-mesoscale processes, depending on the direction. Westerly component winds cause downwelling at the eastern coastline, while easterly component winds bring sub-surface water to the surface. Strong winds from N, NE, and E sectors lead to the rise in lower-layer waters in the western basin, forcing them to overflow through the Hersek Delta sill into the central basin. Overall, severe wind events greater than 4.9 m/s (75%) significantly affect the bay’s hydrography by transforming the upper layer, with a decrease in temperature up to 5 °C and an increase in salinity up to 10 ppt. Full article

This study describes the conception, development, and growth of the Triage Cancer Conference hosted by Triage Cancer, a national nonprofit organization providing free legal and financial education to the cancer community. We conducted a retrospective analysis of post-conference participant surveys. Descriptive statistics were calculated for participant demographics, and acceptability, feasibility, and appropriateness were evaluated. From 2016–2021, 1239 participants attended the conference and completed post-conference surveys. Participants included social workers (33%), nurses (30%), and cancer patients/survivors (21%), with representation from over 48 states. Among those who reported race, 16% were Black, and 7% were Hispanic. For acceptability, more than 90% of participants felt that the conference content, instructors, and format were suitable and useful. For feasibility, more than 90% of participants felt that the material was useful, with 93–96% reporting that they were likely to share the information and 98% reporting that they would attend another triage cancer event. Appropriateness was also high, with >80–90% reporting that the sessions met the pre-defined objectives. Triage Cancer fills an important gap in mitigating financial toxicity, and formal evaluation of these programs allows us to build evidence of the role and impact of these existing resources. Future research should focus on adding validated patient-reported outcomes, longer-term follow-up, and ensuring inclusion and evaluation of outcome metrics among vulnerable populations. Full article

Global urbanization and increasing traffic volume have intensified traffic congestion throughout transportation infrastructure, particularly at toll plazas, highlighting the critical need to implement proactive transportation infrastructure solutions. Traditional toll plaza management approaches, often relying on manual interventions, suffer from inefficiencies that fail to adapt to dynamic traffic flow and are unable to produce preemptive control strategies, resulting in prolonged queues, extended travel times, and adverse environmental effects. This study proposes a proactive traffic control strategy using advanced technologies to combat toll plaza congestion and optimize traffic management. The approach involves deep learning convolutional neural network models (YOLOv7–Deep SORT) for vehicle counting and an extended short-term memory model for short-term arrival rate prediction. When projected arrival rates exceed a threshold, the strategy proactively activates variable speed limits (VSLs) and ramp metering (RM) strategies during peak hours. The novelty of this study lies in its predictive and adaptive capabilities, ensuring efficient traffic flow management. Validated through a case study at Ravi Toll Plaza Lahore using PTV VISSIMv7, the proposed method reduces queue length by 57% and vehicle delays by 47% while cutting fuel consumption and pollutant emissions by 28.4% and 34%, respectively. Additionally, by identifying the limitations of conventional approaches, this study presents a novel framework alongside the proposed strategy to bridge the gap between theory and practice, making it easier for toll plaza operators and transportation authorities to adopt and benefit from advanced traffic management techniques. Ultimately, this study underscores the importance of integrated and proactive traffic control strategies in enhancing traffic management, minimizing congestion, and fostering a more sustainable transportation system. Full article

Laser powder bed fusion (LPBF) is a prospective and promising technique of additive manufacturing of which there is a growing interest for the development and production of Fe-based bulk metallic glasses and amorphous–nanocrystalline composites. Many factors affect the quality and properties of the resulting material, and these factors are being actively investigated by many researchers, however, the factor of the inert gas atmosphere used in the process remains virtually unexplored for Fe-based metallic glasses and composites at this time. Here, we present the results of producing amorphous–nanocrystalline composites from amorphous Fe-based powder via LPBF using argon and helium atmospheres. The analysis of the microstructures and phase compositions demonstrated that using helium as an inert gas in the LPBF resulted in a nearly three-fold increase in the amorphization degree of the material. Additionally, it had a beneficial impact on phase composition and structure in a heat-affected zone. The received results may help to develop approaches to control and improve the structural-phase state of amorphous–nanocrystalline compositional materials obtained via LPBF. Full article