Search Results (14)

Peach palm (Bactris gasipaes Kunth) is a long-lived tropical palm valued for its edible, nutritious fruits. The cultivation area of peach palm, which was introduced to Thailand for fruit production, has been steadily expanding. Small brown spots that expanded into irregular lesions with dark margins were first observed on B. gasipaes seedlings in commercial nurseries in Phetchaburi Province, southern Thailand. To identify the causal pathogens, ten fungal isolates were obtained from symptomatic leaves and subjected to pathogenicity tests, confirming their ability to cause the disease. Morphological and molecular analyses identified five isolates as Colletotrichum fructicola (BGC02.2, BGC03) and C. theobromicola (BGC01, BGC02.1, BGC04) and five isolates as Fusarium pernambucanum (BGF01, BGF02, BGF03, BGF04.1, BGF04.2). Phylogenetic analysis was based on act, cal, gapdh, ITS, and tub2 regions for Colletotrichum spp. and cal, rpb2, and tef1-α for Fusarium spp. In vitro fungicide assays revealed that C. fructicola and C. theobromicola were the most sensitive to carbendazim, mancozeb, and prochloraz, while F. pernambucanum was effectively inhibited by mancozeb and prochloraz. This study represents the first report of C. fructicola, C. theobromicola, and F. pernambucanum causing leaf spot disease on B. gasipaes in Thailand, providing essential insights for disease management strategies in the region. Full article

Unveiling the heat transfer behavior of solar collectors in concentrating solar thermochemical energy storage is crucial for harnessing full-spectrum solar light. In this study, a glass Flat Tube-Shaped Heat Pipe (FT-SHP) was developed, and a visualization experimental platform was established to investigate its internal operation mechanisms and heat transfer characteristics. The results revealed that the liquid filling ratio (FR) significantly affects the heat transfer performance, with an optimal value identified as 25%. As the heat flow temperature in the evaporation section increased, both the Bubble Growing Frequency (BGF) and Droplet Condensation Reflux Period (DCRP) decreased, leading to a reduction in thermal resistance. Conversely, an increase in the cooling flow rate resulted in opposite trends in BGF and DCRP within the tube, while both the Reynolds (Re) number and thermal resistance decreased. As such, an empirical correlation between thermal resistance and Re number was derived, demonstrating a nonlinear relationship between thermal resistance, BGF, and DCRP. These findings provide important insights for the design of heat pipes, with the potential to enhance the efficiency and reliability of solar collectors. Full article

With the rapid development of deep learning, unmanned aerial vehicles (UAVs) have acquired intelligent perception capabilities, demonstrating efficient data collection across various fields. In UAV perspective scenarios, captured images often contain small and unevenly distributed objects, and are typically high-resolution. This makes object detection in UAV imagery more challenging compared to conventional detection tasks. To address this issue, we propose a lightweight object detection algorithm, BGF-YOLOv10, specifically designed for small object detection, based on an improved version of YOLOv10n. First, we introduce a novel YOLOv10 architecture tailored for small objects, incorporating BoTNet, variants of C2f and C3 in the backbone, along with an additional small object detection head, to enhance detection performance for small objects. Second, we embed GhostConv into both the backbone and head, effectively reducing the number of parameters by nearly half. Finally, we insert a Patch Expanding Layer module in the neck to restore the feature spatial resolution. Experimental results on the VisDrone-DET2019 and UAVDT datasets demonstrate that our method significantly improves detection accuracy compared to YOLO series networks. Moreover, when compared to other state-of-the-art networks, our approach achieves a substantial reduction in the number of parameters. Full article

The magnetic properties of Aurivillius-phase Bi₇Fe₃Ti3O₂₁ (BFT) and Bi_7−xGd_xFe3Ti3O₂₁, where x = 0.2, 0.4, and 0.6 (BGFT), were investigated. Ceramic material undoped (BGF) and doped with Gd³⁺ ions were prepared by conventional solid-state reaction. In order to confirm that the obtained materials belong to Aurivillius structures, XRD tests were performed. The XRD results confirmed that both the undoped and the gadolinium-doped materials belong to the Aurivillius phases. The qualitative chemical composition of the obtained materials was confirmed based on EDS tests. The temperature dependences of magnetization and magnetic susceptibility were examined for the ceramic material both undoped and doped with Gd³⁺ ions. The measurements were taken in the temperature range from T = 10 K to T = 300 K. Using Curie’s law, the value of the Curie constant was determined, and on its basis, the number of iron ions that take part in magnetic processes was calculated. The value of Curie constant C = 0.266 K, while the concentration of iron ions Fe³⁺, which influence the magnetic properties of the material, is equal 3.7 mol% (for BFT). Hysteresis loop measurements were also performed at temperatures of T = 10 K, T = 77 K, and T = 300 K. The dependence of magnetization on the magnetic field was described by the Brillouin function, and on its basis, the concentration of Fe³⁺ ions, which are involved in magnetic properties, was also calculated (3.4 mol% for BFT). Tests showed that the material is characterized by magnetic properties at low temperatures. At room temperature (RT), it has paramagnetic properties. It was also found that Gd³⁺ ions improve the magnetic properties of tested material. Full article

This paper proposes an enhanced BertGCN-Fusion (BGF) model aimed at addressing the limitations of Graph Convolutional Networks (GCN) in processing global text features for text categorization tasks. While traditional GCN effectively capture local structural features, they face challenges when integrating global semantic features. Issues such as the potential loss of global semantic information due to local feature fusion and limited depth of information propagation are prevalent. To overcome these challenges, the BGF model introduces improvements based on the BertGCN framework: (1) Feature fusion mechanism: Introducing a linear layer to fuse BERT outputs with traditional features facilitates the integration of fine-grained local semantic features from BERT with traditional global features. (2) Multilayer fusion approach: Employing a multilayer fusion technique enhances the integration of textual semantic features, thereby comprehensively and accurately capturing text semantic information. Experimental results demonstrate that the BGF model achieves notable performance improvements across multiple datasets. On the R8 and R52 datasets, the BGF model achieves accuracies of 98.45% and 93.77%, respectively, marking improvements of 0.28% to 0.90% compared to the BertGCN model. These findings highlight the BGF model’s efficacy in overcoming the deficiencies of traditional GCN in processing global semantic features, presenting an efficient approach for handling text data. Full article

On account of the external disturbances and difficult maneuverability of a hovercraft, this paper devises a safety-guaranteed, robust, nonlinear, path-following control strategy of a hovercraft targeted for unknown dynamics, unavailable velocity, and unknown external ocean disturbances. Firstly, for the sake of accurately observing unavailable lumped disturbances and unavailable velocity measurements, a finite-time extended state observer (FTESO) is proposed. Secondly, a line-of-sight (LOS) guidance law constructed with a bounded-gain-forgetting (BGF) adaptive estimator is devised to follow the desired path while considering external environmental disturbances accurately, in which the tracking errors and the parameter estimation are both proven to be bounded. In addition, for the sake of safety, a safety-guaranteed auxiliary system that can constrain the drift angle during the hovercraft’s navigation is proposed. Thirdly, the robust, nonlinear, path-following controllers achieved high tracking performance with the constructed safety-guaranteed compensation backstepping method. Finally, according to the Lyapunov and homogeneous theories, the observation error can be guaranteed to zero and the tracking error can converge to an arbitrarily small region near zero in finite time. Numerical simulations illustrate the effectiveness for the proposed robust, nonlinear, path-following scheme. Full article

Biomimetic technologies for the remineralisation of enamel subsurface lesions (ESLs) have been developed and include: fluorocalcium phosphosilicate bioglass (BG/F); casein phosphopeptide-amorphous calcium phosphate (CPP–ACP) and with fluoride (CPP–ACFP); and self-assembling oligopeptide P11-4 (SAP). The aim of this study was to compare the remineralisation of ESLs in vitro using these technologies. Human enamel slabs with ESLs were cut into two half-slabs; one half-slab was untreated (control), and the other half was treated by exposure to one of the four technologies with artificial saliva (AS) or AS alone for 14 days at 37 °C. The technologies were applied to the ESL surface according to the manufacturer’s instructions. At the completion of each treatment, the treated half-slabs and their paired control half-slabs were embedded, sectioned and the mineral content was determined using transverse microradiography. The change in mineral content (remineralisation) between treatments was statistically analysed using one-way ANOVA. The order from highest to lowest remineralisation was CPP–ACFP (52.6 ± 2.6%) > CPP–ACP (43.0 ± 4.9%) > BG/F (13.2 ± 2.5%) > SAP (5.8 ± 1.6%) > AS (2.1 ± 0.5%). Only CPP–ACFP and CPP–ACP produced remineralisation throughout the body of the lesions. All four biomimetic technologies had some effect on the remineralisation of ESLs; however, CPP–ACFP with calcium, phosphate and fluoride ions stabilised by CPP was superior in the level and pattern of remineralisation obtained. Full article

With the growing demand for smart, secure, and intelligent solutions, Industry 4.0 has emerged as the future of various applications. One of the primary sectors that are becoming more vulnerable to security assaults like ransomware is the healthcare sector. Researchers have proposed various mechanisms in smart and secure health care systems with this vision in mind. Existing systems are vulnerable to security attacks on medical data. It is required to build a real-time diagnosis device using a cyber-physical system with blockchain technology in a considerable manner. The proposed work’s main purpose is to build secure, real-time preservation and tamper-proof control of medical data. In this work, the Bayesian grey filter-based convolution neural network (BGF-CNN) approach is used to enhance accuracy and reduce time complexity and overhead. Additionally, PSO and GWO optimization techniques are used to improve network performance. As an outcome of the proposed work, the privacy preservation of medical data is improved with a high accuracy rate by a blockchain-based cyber-physical system using a deep neural network (BGF Blockchain). To summarize, the proposed system helps in the privacy preservation of medical data along with a reduction in communication overhead using the Bayesian Grey Filter–CNN. Full article

Polyvinyl alcohol (PVA) hydrogels are promising implants due to the similarity of their low-friction behavior to that of cartilage tissue, and also due to their non-cytotoxicity. However, their poor mechanical resistance and insufficient durability restricts their application in this area. With the development of biodegradable glass fibers (BGF), which show desirable mechanical performance and bioactivity for orthopedic engineering, we designed a novel PVA hydrogel composite reinforced with biodegradable glass fibers, intended for use in artificial cartilage repair with its excellent cytocompatibility and long-term mechanical stability. Using structure characterization and thermal properties analysis, we found hydrogen bonding occurred among PVA molecular networks as well as in the PVA–BGF interface, which explained the increase in crystallinity and glass transition temperature, and was the reason for the improved mechanical performance and better anti-fatigue behavior of the composites in comparison with PVA. The compressive strength and modulus for the PBGF-15 composite reached 3.05 and 3.97 MPa, respectively, equaling the mechanical properties of human articular cartilage. Moreover, the increase in BGF content was found to support the proliferation of chondrocytes in vitro, whilst the PVA hydrogel matrix was able to control the ion concentration by adjusting the ions released from the BGF. Therefore, this novel biodegradable-glass-fiber-reinforced hydrogel composite possesses excellent properties for cartilage repair with potential in medical application. Full article

This paper presents temperature-dependent properties and fire resistance of geopolymer foams made of ground basalt fibers, aluminum foaming agents, and potassium-activated metakaolin-based geopolymers. Temperature-dependent properties of basalt-reinforced geopolymer foams (BGFs) were investigated by a series of measurements, including apparent density, water absorption, mass loss, drying shrinkage, compressive and flexural strengths, XRD, and SEM. Results showed that the apparent density and drying shrinkage of the BGFs increase with increasing the treated temperature from 400 to 1200 °C. Below 600 °C the mass loss is enhanced while the water absorption is reduced and they both vary slightly between 600 and 1000 °C. Above 1000 °C the mass loss is decreased rapidly, whereas the water absorption is increased. The compressive and flexural strengths of the BGFs with high fiber content are improved significantly at temperatures over 600 °C and achieved the maximum at 1200 °C. The BGF with high fiber loading at 1200 °C exhibited a substantial increase in compressive strength by 108% and flexural strength by 116% compared to that at room temperature. The enhancement in the BGF strengths at high temperatures is attributed to the development of crystalline phases and structural densification. Therefore, the BGFs with high fiber loading have extraordinary mechanical stability at high temperatures. The fire resistance of wood and steel plates has been considerably improved after coating a BGF layer on their surface. The coated BGF remained its structural integrity without any considerable macroscopic damage after fire resistance test. The longest fire-resistant times for the wood and steel plates were 99 and 134 min, respectively. In general, the BGFs with excellent fire resistance have great potential for fire protection applications. Full article

Bioactive glass F18 (BGF18), a glass containing SiO₂–Na₂O–K₂O–MgO–CaO–P₂O₅, is highly effective as an osseointegration buster agent when applied as a coating in titanium implants. Biocompatibility tests using this biomaterial exhibited positive results; however, its antimicrobial activity is still under investigation. In this study we evaluated biofilm formation and expression of virulence-factor-related genes in Candida albicans, Staphylococcus epidermidis, and Pseudomonas aeruginosa grown on surfaces of titanium and titanium coated with BGF18. C. albicans, S. epidermidis, and P. aeruginosa biofilms were grown on specimens for 8, 24, and 48 h. After each interval, the pH was measured and the colony-forming units were counted for the biofilm recovery rates. In parallel, quantitative real-time polymerase chain reactions were carried out to verify the expression of virulence-factor-related genes. Our results showed that pH changes of the culture in contact with the bioactive glass were merely observed. Reduction in biofilm formation was not observed at any of the studied time. However, changes in the expression level of genes related to virulence factors were observed after 8 and 48 h of culture in BGF18. BGF18 coating did not have a clear inhibitory effect on biofilm growth but promoted the modulation of virulence factors. Full article

Oil continues to be a major source of world energy, but oil prices and funds have experienced high volatility over the last decade. This study applies the generalized autoregressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model on data spanning 1 July 2014 to 30 April 2020 to examine volatility transmission from the equity, bulk shipping, commodity, currency, and crude oil markets to the United States Oil Fund (USO) and BlackRock World Energy Fund A2 (BGF). By dividing the sample into two subsamples, we find a significant volatility transmission from the equity market to the oil ETF and energy fund both before and after the 2018 U.S.–China trade war. The volatility transmission from the bulk shipping, commodity, and crude oil markets turns significant for the oil ETF and energy fund after the 2018 U.S.–China trade war, extending into the COVID-19 pandemic in early 2020. The results suggest that investors can use the equity market to predict the movement of oil and energy funds during both tranquil and turmoil periods. Moreover, investors can use bulk shipping, commodity, and crude oil markets in addition to the equity market to forecast oil and energy funds’ volatility during the turmoil periods. This paper benefits investors against the high volatility of the energy funds. Full article

The aim of this article is to show geomorphological mapping of remote Antarctic locations using images taken by a fixed-wing unmanned aerial vehicle (UAV) during the Beyond Visual Line of Sight (BVLOS) operations. We mapped landform assemblages developed in forelands of Ecology Glacier (EGF), Sphinx Glacier (SGF) and Baranowski Glacier (BGF) in Antarctic Specially Protected Area No. 128 (ASPA 128) on King George Island (South Shetland Islands) and inferred about glacial dynamics. The orthophoto and digital elevation model allowed for geomorphological mapping of glacial forelands, including (i) glacial depositional landforms, (ii) fluvial and fluvioglacial landforms, (iii) littoral and lacustrine landforms, (iv) bodies of water, and (v) other. The largest area is occupied by ground moraine and glacial lagoons on EGF and BGF. The most profound features of EGF are the large latero-frontal moraine ridges from Little Ice Age and the first half of the 20th century. Large areas of ground moraine, frequently fluted and marked with large recessional moraine ridges, dominate on SGF. A significant percentage of bedrock outcrops and end moraine complexes characterize BGF. The landform assemblages are typical for discontinuous fast ice flow of tidewater glaciers over a deformable bed. It is inferred that ice flow velocity decreased as a result of recession from the sea coast, resulting in a significant decrease in the length of ice cliffs and decrease in calving rate. Image acquisition during the fixed-wing UAV BVLOS operation proved to be a very robust technique in harsh polar conditions of King George Island. Full article

This study addresses the problem of age determination of the southern king crab (Lithodes santolla). Given that recapture is difficult for this species and, thus, age cannot be directly determined with the help of the annual marks on the shell, the von Bertalanffy growth function (vBGF) cannot be used to directly model length-frequency data (LFD). To determine age classes, some researchers have proposed using the MIX algorithm that consists of sampling realization of a finite mixture of normal (FMN) distributions for each LFD. However, normality assumption in age-length data has been questioned in several works related to fish growth analysis. For this study, we considered the biological information of the southern king crab for the period 2007–2015 and localization between ${50}^{\circ }$ 06 ${}^{\prime }$ – ${53}^{\circ }$ 15 ${}^{\prime }$ S and ${76}^{\circ }$ 36 ${}^{\prime }$ – ${72}^{\circ }$ 18 ${}^{\prime }$ W. We assumed that LFD could be modelled by the novel class of finite mixture of skew-t (FMST). Assigned age classes were used to estimate the vBGF parameters. The estimated vBGF parameters were $L_{\infty }=176.756$ cm, $K=0.151$ ${\mathrm{year}}^{-1}$ , $t_0=-1.678$ year for males, and $L_{\infty }=134.799$ cm, $K=0.220$ ${\mathrm{year}}^{-1}$ , $t_0=-1.302$ year for females. This study concludes that (a) FMST modal decomposition can detect a group of younger individuals at age 2, given that those individuals have LFD with a left heavy-tail and asymmetry; (b) FMST produces a better representation of LFD than the FMN model; (c) males have bigger $L_{\infty }$ but grow slower than females; and (d) as expected, a high correlation exists among the vBGF estimates. Full article