Biomarkers for evaluating tumor response to therapy and estimating the risk of disease relapse represent tremendous areas of clinical need. To evaluate treatment efficacy, tumor response is routinely assessed using different imaging modalities like positron emission tomography/computed tomography or magnetic resonance imaging. More recently, the development of circulating tumor DNA detection assays has provided a minimally invasive approach to evaluate tumor response and prognosis through a blood test (liquid biopsy). Integrating imaging- and circulating tumor DNA-based biomarkers may lead to improvements in the prediction of patient outcomes. For this mini-review, we searched the scientific literature to find original articles that combined quantitative imaging and circulating tumor DNA biomarkers to build prediction models. Seven studies reported building prognostic models to predict distant recurrence-free, progression-free, or overall survival. Three discussed building models to predict treatment response using tumor volume, pathologic complete response, or objective response as endpoints. The limited number of articles and the modest cohort sizes reported in these studies attest to the infancy of this field of study. Nonetheless, these studies demonstrate the feasibility of developing multivariable response-predictive and prognostic models using regression and machine learning approaches. Larger studies are warranted to facilitate the building of highly accurate response-predictive and prognostic models that are generalizable to other datasets and clinical settings. Full article

The overexpression of somatostatin receptor type 2 (SSTR2) is a property of various tumor types. Hybrid imaging utilizing [⁶⁸Ga]1,4,7,10-tetraazacyclododecane-1,4,7,10-tetra-acetic acid (DOTA) may improve the differentiation between tumor and healthy tissue. We conducted an experimental study on 47 anonymized patient cases including 30 meningiomas, 12 PitNET and 5 SBPGL. Four independent observers were instructed to contour the macroscopic tumor volume on planning MRI and then reassess their volumes with the additional information from DOTA-PET/CT. The conformity between observers and reference volumes was assessed. In total, 46 cases (97.9%) were DOTA-avid and included in the final analysis. In eight cases, PET/CT additional tumor volume was identified that was not detected by MRI; these PET/CT findings were potentially critical for the treatment plan in four cases. For meningiomas, the interobserver and observer to reference volume conformity indices were higher with PET/CT. For PitNET, the volumes had higher conformity between observers with MRI. With regard to SBGDL, no significant trend towards conformity with the addition of PET/CT information was observed. DOTA PET/CT supports accurate tumor recognition in meningioma and PitNET and is recommended in SSTR2-expressing tumors planned for treatment with highly conformal radiation. Full article

In this paper, an irregular octagonal two-port MIMO patch antenna is designed specifically for New Radio (NR) 5G applications in the mid-band sub-6 GHz. The proposed antenna comprises an irregularly shaped patch antenna equipped with a regular 50-ohm feed line and a parasitic strip line antenna, and is partially grounded. Jeans material serves as a substrate with an effective dielectric constant of 1.6 and a thickness of 1 mm. This material is studied experimentally. The proposed antenna design undergoes analysis and optimization using the ANSYS HFSS tool. Furthermore, the design incorporates the influence of the slot on both the ground plane and the parasitic strip line to optimize performance, enhance isolation, and improve impedance matching among antenna elements. The dimensions of the jeans substrate are 40 mm × 50 mm. The simulated impedance bandwidth ranged from 3.6 GHz to 7 GHz and the measured bandwidth was slightly narrower, from 4.35 GHz to 7 GHz. The simulation results demonstrated an isolation level greater than 12 dB between antenna elements, while the measured results reached 28.5 dB, and the peak gain for this proposed antenna stood at 6.74 dB. These qualities made this proposed antenna suitable for various New Radio mid-band 5G wireless applications within the sub-6 GHz band, such as N79, Wi-Fi-5/6, V2X, and DSRC applications. Full article

Axial postural abnormalities (APAs), characterized by their frequency, disabling nature, and resistance to pharmacological treatments, significantly impact Parkinson’s disease and atypical Parkinsonism patients. Despite advancements in diagnosing, assessing, and understanding their pathophysiology, managing these complications remains a significant challenge. Often underestimated by healthcare professionals, these disturbances can exacerbate disability. This systematic review assesses botulinum toxin treatments’ effectiveness, alone and with rehabilitation, in addressing APAs in Parkinson’s disease, utilizing MEDLINE (PubMed), Web of Science, and SCOPUS databases for source material. Of the 1087 records retrieved, 16 met the selection criteria. Most research has focused on botulinum toxin (BoNT) as the primary treatment for camptocormia and Pisa syndrome, utilizing mostly observational methods. Despite dose and injection site variations, a common strategy was using electromyography-guided injections, occasionally enhanced with ultrasound. Patients with Pisa syndrome notably saw consistent improvements in APAs and pain. However, studies on the combined effects of botulinum toxin and rehabilitation are limited, and antecollis is significantly under-researched. These findings recommend precise BoNT injections into hyperactive muscles in well-selected patients by skilled clinicians, avoiding compensatory muscles, and underscore the necessity of early rehabilitation. Rehabilitation is crucial in a multidisciplinary approach to managing APAs, highlighting the importance of a multidisciplinary team of experts. 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

Sensing and cognition by homeowners and technicians for home maintenance are prime examples of human–building interaction. Damage, decay, and pest infestation present signals that humans interpret and then act upon to remedy and mitigate. The maintenance cognition process has direct effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern technologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recommend courses of remedial action. The demonstrated technologies include robotic sensing in confined areas, LiDAR scans of structural shape and deformation, moisture and gas sensing, water leak detection, network embedded ML, and augmented reality interfaces with multi-user teaming capabilities. The sensor information passes through a private local dynamic network to processors with neural network pattern recognition capabilities to abstract the information, which then feeds to humans through augmented reality and conventional smart device interfaces. This networked sensor system serves as a testbed and demonstrator for home maintenance technologies, for what can be termed Home Maintenance 4.0. Full article

Even slight structural differences between phytocannabinoid isomers are usually enough to cause a change in their biological properties. In this study, we used in vitro CB1 agonism/antagonism assays to compare the receptor binding functionality of THCV (tetrahydrocannabivarin) and HHC (hexahydrocannabinol) isomers and applied molecular docking to provide an explanation for the difference in the activities. No CB1 agonism was observed for ∆9- and ∆8-THCV. Instead, both isomers antagonized CP 55940, with ∆9-THCV being approximately two times more potent than the ∆8 counterpart (IC₅₀ = 52.4 nM and 119.6 nM for ∆9- and ∆8-THCV, respectively). Docking simulations found two binding poses for THCV isomers, one very similar to ∆9-THC and one newly discovered pose involving the occupation of side pocket 1 of the CB1 receptor by the alkyl chain of the ligand. We suggested the latter as a potential antagonist pose. In addition, our results established 9R-HHC and 9S-HHC among partial agonists of the CB1 receptor. The 9R-HHC (EC₅₀ = 53.4 nM) isomer was a significantly more potent agonist than 9S (EC₅₀ = 624.3 nM). ∆9-THC and 9R-HHC showed comparable binding poses inside the receptor pocket, whereas 9S-HHC adopted a new and different binding posture that can explain its weak agonist activity. Full article

Artisanal small-scale mines (ASMs) in the Amazon Rainforest are an important cause of deforestation, forest degradation, biodiversity loss, sedimentation in rivers, and mercury emissions. Satellite image data are widely used in environmental decision-making to monitor changes in the land surface, but ASMs are difficult to map from space. ASMs are small, irregularly shaped, unevenly distributed, and confused (spectrally) with other land clearance types. To address this issue, we developed a reliable and efficient ASM detection method for the Tapajós River Basin of Brazil—an important gold mining region of the Amazon Rainforest. We enhanced detection in three key ways. First, we used the time-series segmentation (LandTrendr) Google Earth Engine (GEE) Application Programming Interface to map the pixel-wise trajectory of natural vegetation disturbance and recovery on an annual basis with a 2000 to 2019 Landsat image time series. Second, we segmented 26 textural features in addition to 5 spectral features to account for the high spatial heterogeneity in ASM pixels. Third, we trained and tested a Random Forest model to detect ASMs after eliminating irrelevant and redundant features with the Variable Selection Using Random Forests “ensemble of ensembles” technique. The out-of-bag error and overall accuracy of the final Random Forest was 3.73 and 92.6%, which are comparable to studies mapping large industrial mines with the normalized difference vegetation index (NDVI) and LandTrendr. The most important feature in our study was NDVI, followed by textural features in the near and shortwave infrared. Our work paves the way for future ASM regulation through large area monitoring from space with free and open-source GEE and operational satellites. Studies with sufficient computational resources can improve ASM monitoring with advanced sensors consisting of spectral narrow bands (Sentinel-2, Environmental Mapping and Analysis Program, PRecursore IperSpettrale della Missione Applicativa) and deep learning. Full article

Hyperspectral images (HSIs) provide valuable spatial–spectral information for ground analysis. However, in few-shot (FS) scenarios, the limited availability of training samples poses significant challenges in capturing the sample distribution under diverse environmental conditions. Semi-supervised learning has shown promise in exploring the distribution of unlabeled samples through pseudo-labels. Nonetheless, FS HSI classification encounters the issue of high intra-class spectral variability and inter-class spectral similarity, which often lead to the diffusion of unreliable pseudo-labels during the iterative process. In this paper, we propose a simple yet effective progressive pseudo-label selection strategy that leverages the spatial–spectral consistency of HSI pixel samples. By leveraging spatially aligned ground materials as connected regions with the same semantic and similar spectrum, pseudo-labeled samples were selected based on round-wise confidence scores. Samples within both spatially and semantically connected regions of FS samples were assigned pseudo-labels and joined subsequent training rounds. Moreover, considering the spatial positions of FS samples that may appear in diverse patterns, to fully utilize unlabeled samples that fall outside the neighborhood of FS samples but still belong to certain connected regions, we designed a matching active learning approach for expert annotation based on the temporal confidence difference. We identified samples with the highest training value in specific regions, utilizing the consistency between predictive labels and expert labels to decide whether to include the region or the sample itself in the subsequent semi-supervised iteration. Experiments on both classic and more recent HSI datasets demonstrated that the proposed base model achieved SOTA performance even with extremely rare labeled samples. Moreover, the extended version with active learning further enhances performance by involving limited additional annotation. Full article

Characterizing the coseismic slip behaviors of earthquakes could offer a better understanding of regional crustal deformation and future seismic potential assessments. On 18 December 2023, an Mw 6.0 earthquake occurred on the Lajishan–Jishishan fault system (LJFS) in the northeastern Tibetan Plateau, causing serious damage and casualties. The seismogenic fault hosting this earthquake is not well constrained, as no surface rupture was identified in the field. To address this issue, in this study, we use Interferometric Synthetic Aperture Radar (InSAR) data to investigate the coseismic surface deformation of this earthquake and invert both ascending and descending line-of-sight observations to probe the seismogenic fault and its slip characteristics. The InSAR observations show up to ~6 cm surface uplift caused by the Jishishan earthquake, which is consistent with the thrust-dominated focal mechanism. A Bayesian-based dislocation modeling indicates that two fault models, with eastern and western dip orientations, could reasonably fit the InSAR observations. By calculating the coseismic Coulomb failure stress changes (∆CFS) induced by both fault models, we find that the east-dipping fault scenario could reasonably explain the aftershock distributions under the framework of stress triggering, while the west-dipping fault scenario produced a negative ∆CFS in the region of dense aftershocks. Integrating regional geological structures, we suggest that the seismogenic fault of the Jishishan earthquake, which strikes NNE with a dip of 56° to the east, may be either the Jishishan western margin fault or a secondary buried branch. The optimal finite-fault slip modeling shows that the coseismic slip was dominated by reverse slip and confined to a depth range between ~5 and 15 km. The released seismic moment is 1.61 × 10¹⁸ N·m, which is equivalent to an Mw 6.07 earthquake. While the Jishishan earthquake ruptured a fault segment of approximately 20 km, it only released a small part of the seismic moment that was accumulated along the 220 km long Lajishan–Jishishan fault system. The remaining segments of the Lajishan–Jishishan fault system still have the capability to generate moderate-to-large earthquakes in the future. Full article

Areas excluded from agricultural production are susceptible to the presence of beaver families. The most significant changes occur during the initial period, when agricultural utilization is abandoned and beavers establish their presence on the land. During this period, some parcels remain uncultivated, while agricultural activities persist in neighboring areas. This situation is accompanied by the destruction of beaver dams, especially during periods of abundant water resources, and notably during intensive fieldwork. The article presents field studies aimed at determining the extent to which constructed and operational beaver dams contribute to changes in groundwater levels in drained peatland areas. In order to protect and sustainably use peat soils, it is necessary to maintain their high moisture content by ensuring a high groundwater level elevation. This can be achieved through the use of existing damming structures in the area (levees, weirs). Beaver dams can also serve a similar function, blocking the outflow of water from peat lands by raising the water level and consequently retaining it naturally. The specific objective was to develop principles for verifying factors influencing the effects of beaver dam construction on groundwater levels in fields within their range of influence. The water table levels within the study area during rainless periods were influenced by water levels in ditches, dependent on beaver activity in the nearby river. Beaver activities, manifested through dam construction, were influenced by periodic water resources in the river, defined by the cumulative monthly precipitation. Factors affecting groundwater levels in rainless periods on the plots also included the distance from the river cross-section and the permeability of soils expressed by the filtration coefficient of the active layer. Beaver dams had the greatest impact on stabilizing the water table in the soil profile closest to the river. Full article

The sustainability of the food production achieved with the help of irrigation systems and the sustainability of their energy consumption are major challenges of the current century. Pumping systems currently account for approximately 30% of global electrical energy consumption. As electricity prices rise, there is a growing need for technological advancements to enhance energy efficiency and reduce consumption costs effectively. This study focuses on operating centrifugal pumps at variable frequency as an effective means of achieving this goal. Most centrifugal pump manufacturers/providers traditionally assume that pump efficiency remains constant across various operating frequencies, often equating the efficiency at various frequencies to that at the standard frequency (50/60 Hz). In contrast, this paper introduces a new formula for estimating pump efficiency, crucial to precise power consumption determination, particularly in variable-frequency scenarios. The formula parameters are identified by using experimental data acquired from an existing pumping system. The tests and results presented in this paper demonstrate that the proposed formula outperforms the formulas of the current industry standards in accuracy. Practically, the new relation assures enhanced accuracy in estimating pump efficiency and absorbed power, allowing for the design of a more precise model used for control systems synthesis required for operating centrifugal pumps at variable frequency. This research offers a new way of calculating pump efficiency, which could be very useful for industry practitioners seeking to optimize energy consumption in pumping systems. Full article

The rapid and accurate estimation of forest carbon stock is important for analyzing the carbon cycle. In order to obtain forest carbon stock efficiently, this paper utilizes airborne LiDAR data to research the applicability of different feature screening methods in combination with machine learning in the carbon stock estimation model. First, Spearman’s Correlation Coefficient (SCC) and Extreme Gradient Boosting tree (XGBoost) were used to screen out the variables that were extracted via Airborne LiDAR with a higher correlation with carbon stock. Then, Bagging, K-nearest neighbor (KNN), and Random Forest (RF) were used to construct the carbon stock estimation model. The results show that the height statistical variable is more strongly correlated with carbon stocks than the density statistical variables are. RF is more suitable for the construction of the carbon stock estimation model compared to the instance-based KNN algorithm. Furthermore, the combination of the XGBoost algorithm and the RF algorithm performs best, with an R² of 0.85 and an MSE of 10.74 on the training set and an R² of 0.53 and an MSE of 21.81 on the testing set. This study demonstrates the effectiveness of statistical feature screening methods and Random Forest for carbon stock estimation model construction. The XGBoost algorithm has a wider applicability for feature screening. Full article

Urban planning is often influenced by industrial and construction activities, leading to a lack of attention to the planning and construction of urban parks, which results in prominent spatial layout problems. Urban parks, as an important part of the urban green space system, play a significant role in improving the ecological environment, promoting urban economic development, and enhancing the daily living standards of the people. As a typical representative of China’s second and third-tier cities, Nanchang’s analysis of the evolution process of urban landscape patterns has reference significance for other similar cities in China. This paper is based on the theoretical foundations of landscape ecology, human geography, and urban planning, and analyzes the evolution of the park landscape pattern in the central urban area of Nanchang from 1999 to 2019 from the perspective of urban context, revealing the driving mechanisms. It provides important references and bases for the further optimization and construction development of the park landscape pattern in Nanchang. The results show that the park area and number in the central urban area of Nanchang have significantly increased, with the overall layout evolving from “central aggregation” to “core aggregation in each area”, and from “central scarcity, more on the periphery” to “inward concentration, outward diffusion”. However, the distribution of various types of parks is uneven, and there is a lack of green corridor links between parks. The park landscape pattern is driven by multiple factors such as natural factors of urban context, socio-economic factors, urban construction factors, historical policies, and related planning, which can have positive or negative effects. Incorporating relevant urban factors into the park planning system analysis can promote the benign development of urban context and park landscape layout, thereby achieving the “parkification” of the city. Full article

The Green School—An outline reflects on the author’s vision of a holistic approach to the education system as a leading arrow for human beings and social prosperity. It is a needed book, an education of choice, conviction, and passion by Thakur S. Powdyel, former Minister of Education, Royal Government of Bhutan a long with several studies in terms of reflections on Gross National Happiness in the education context and globalization, and context of development. Thus, Powdyel’s Green School conducts all the fundamentals as well as many other crucial aspects related to greenery concepts in the entire school as a whole-green school approach for future education. 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

Innovation is the primary driving force for development, and enterprises, as the main drivers of innovation, are an important part of implementing the national innovation strategy. This paper, combining the perspective of the enterprise lifecycle, thoroughly examines the differential impact of the CEO’s financial background on green innovation in enterprises at different stages of the lifecycle. This study finds that the CEO’s financial background has a significant inhibitory effect on green innovation in enterprises, and this conclusion holds true after multiple robustness tests. From the perspective of the lifecycle, it is found that when enterprises are in the mature stage, the CEO’s financial background has a strong inhibitory effect on innovation output. The impact of the CEO’s financial background on green innovation output in the growth stage is relatively weak, while there is no significant impact on green innovation in the declining period. Furthermore, based on the enterprise lifecycle, it is found that the CEO’s financial background has a stronger inhibitory effect on green innovation in non-state-owned enterprises and high-tech industries. The research findings of this paper have important theoretical value and practical significance for promoting green innovation in enterprises and implementing the national innovation strategy. Full article

Investigating the factors influencing the spatial-temporal disparities in China’s electricity consumption carbon emissions (ECCEs) will be of great help to advancing the reduction in carbon emissions on the consumption side of electricity. Based on the measurement of the ECCEs in 30 Chinese provinces between 2005 and 2021, we utilized the natural breakpoint method and the Dagum Gini coefficient to analyze the spatial-temporal disparities in ECCEs at the provincial and regional levels, and then we used Geodetector to explore the factors influencing the spatial-temporal disparities in ECCEs. The results revealed the following: (1) There were obvious inter-provincial spatial disparities in ECCEs, with coastal provinces such as Jiangsu and Guangdong consistently ranking at the top of the country and inland provinces such as Qinghai and Yunnan having relatively low carbon emission values. (2) The overall disparities in China’s ECCEs fluctuated and rose, with inter-regional disparities being the primary source of the overall disparities. (3) Economic development, industrialization level, population density, and foreign direct investment all had strong explanations for the spatial-temporal disparities in China’s ECCEs. When all these influencing factors were spatially superimposed, their effects were enhanced. Full article

To mitigate dust pollution generated during various stages of construction activities and reduce the environmental and health hazards posed by airborne dust, this study utilized hydroxyethyl cellulose, glycerol, and isomeric tridecyl alcohol polyoxyethylene ether as raw materials to formulate a composite chemical dust suppressant. The properties of the dust suppressant were characterized through analysis. Employing single-factor experiments, the optimal proportions of the binder, water-retaining agent, and surfactant for the composite dust suppressant were determined. Subsequently, a response surface model was established, and, after analysis and optimization, the optimal mass ratios of each component in the composite dust suppressant were obtained. Under optimal ratios, the physicochemical properties and wind erosion resistance of the composite dust suppressant were analyzed. Finally, the practical application of the suppressant was validated through on-site trials at a construction site. This study revealed that the optimal formulation for the dust suppressant was as follows: 0.2% hydroxyethyl cellulose, 2.097% glycerol, 0.693% isomeric tridecyl alcohol polyoxyethylene ether, and the remainder was pure water. The suppressant is non-toxic, non-corrosive, environmentally friendly, and exhibits excellent moisture retention and bonding properties compared to water. The research findings provide valuable insights for addressing dust pollution issues on construction sites. Full article

The resistance of nickel–titanium endodontic instruments against cyclic fatigue failure remains a significant concern in clinical settings. This study aimed to assess the cyclic fatigue strength of five nickel–titanium rotary systems, while correlating the results with the instruments’ geometric and metallurgical characteristics. A total of 250 new instruments (sizes S1/A1, S2/A2, F1/B1, F2/B2, F3/B3) from ProTaper Gold, ProTaper Universal, Premium Taper Gold, Go-Taper Flex, and U-Files systems underwent mechanical testing. Prior to experimental procedures, all instruments were meticulously inspected to identify irregularities that could affect the investigation. Using a stereomicroscope, design characteristics such as the number of spirals, length, spirals per millimeter, and average helical angle of the active blade were determined. The surface finishing characteristics of the instruments were examined using a scanning electron microscope. Differential scanning calorimetry was employed to establish the instruments’ phase transformation temperatures, while energy-dispersive X-ray spectroscopy was utilized to analyze the elemental composition of the alloy. The instruments were subjected to cyclic fatigue testing within a stainless steel non-tapered artificial canal featuring a 6 mm radius and 86 degrees of curvature. Appropriate statistical tests were applied to compare groups, considering a significance level of 0.05. The assessed design characteristics varied depending on the instrument type. The least irregular surface finishing was observed in U-Files and Premium Taper Gold files, while the most irregular surface was noted in Go-Taper Flex. All instruments exhibited near-equiatomic proportions of nickel and titanium elements, whereas ProTaper Universal and U-Files instruments demonstrated lower phase transformation temperatures compared to their counterparts. Larger-sized instruments, as well as ProTaper Universal and U-Files, tended to display lower cyclic fatigue strength results. Overall, the design, metallurgical, and cyclic fatigue outcomes varied among instruments and systems. Understanding these outcomes may assist clinicians in making more informed decisions regarding instrument selection. Full article

We studied a gradient anti-oxidation coating of C/C composite materials for aircraft brake discs with a simple process and low costs. The gradient coating consists of two layers, of which the inner layer is prepared with tetraethyl orthosilicate (Si (OC2H5)4), C₂H₅OH, H₃PO₄ and B₄C, and the outer layer is prepared with Na₂B₄O₇.10H₂O, B₂O₃, and SiO₂ powder. The experimental results show that after being oxidized at 700 °C for 15 h, the oxidation weight loss of the sample with the coating was only −0.17%. At the same time, after 50 thermal cycles in air at 900 °C, the sample’s oxidation weight loss was only −0.06%. We conducted the 1:1 dynamic simulation test for aircraft brake discs, and the brake disc did not oxidize, thus meeting the requirements for aircraft use. In addition, the anti-oxidation mechanism of the coating was analyzed via scanning electron microscopy (SEM), X-ray diffraction (XRD), differential thermal analysis (DSC-TGA), and high-temperature in situ SEM. 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