Appl. Sci., Volume 13, Issue 19 (October-1 2023) – 562 articles

Vegetation slope protection plays an important role in improving the slope stability and protecting the environment. In this study, the mechanical properties of root–soil composites in different growth periods and their effects on slope stability were investigated. First, the shear strength of undisturbed root–soil composites associated with Cynodon dactylon (C.d), Magnolia multiflora (M.m) and grass and shrub mixture (G.s) were measured by large direct shear tests. Then, the effects of plant reinforcement in different growth periods on slope stability were analyzed using ABAQUS. The results show that the shear strength of the root–soil composites were significantly higher than that of the unreinforced soil. The root–soil composites met the Mohr–Coulomb criterion. The shear strength of the three root–soil composites increased first and then decreased during the vegetation growth period. The calculation results show that the factor of safety (FS) of the bare slope was 1.482. The FS values of the C.d, M.m, and G.s slopes were 1.601, 1.658 and 1.715, which increased by 8%, 11.9% and 15.7% compared to the bare soil slopes. Therefore, vegetation could significantly improve slope stability, especially the grass–shrub mixture model. This could provide a rational basis for designing and constructing plant slope protection. Full article

This work presents a remote control device designed to drive the arm gestures of an assistant humanoid mobile robot. The remote control is a master device with two passive arms configured to replicate the four degrees of freedom of each arm of the original assistant humanoid robot and send this information to the robot. This configuration allows the mobile robot to directly replicate the position of the arms on the remote controller. The objective of this proposal is to provide the robot with enhanced non-verbal and pointing communication capabilities during human interaction or assistance. The master device registers the angular position of each joint of its passive arms and transmits this information to the mobile robot, which replicates it. The experimental evaluation of the system has shown that the humanoid robot is able to successfully replicate any gesture on the remote controller. The positions of the arms have been sampled at a frame rate of 20 ms, and the average telecontrol delay obtained in the gesture experiments has been 549 ms, without appreciable jumps or irregularities in the gestures. The conclusion is that the direct manipulation of the passive arms of the remote control device provides the APR-02 humanoid robot with enhanced non-verbal and pointing communication capabilities during human interaction or assistance. Full article

Object detection methods are commonly employed in power safety monitoring systems to detect violations in surveillance scenes. However, traditional object detection methods are ineffective for small objects that are similar to the background information in the power monitoring scene, which consequently affects the performance of violation behavior detection. This paper proposed a small object detection algorithm named HS-YOLO, based on High-Resolution Network (HRNet) and sub-pixel convolution. First, to fully extract the microfeature information of the object, a small object feature extraction backbone network is proposed based on the HRNet structure. The feature maps of different scales are processed by multiple parallel branches and fused with each other in the network. Then, to fully retain the effective features of small objects, the sub-pixel convolution module is incorporated as the upsampling operator in the feature fusion network. The low-resolution feature map is upsampled to a higher resolution by reorganizing pixel values and performing padding operations in this module. On our self-constructed power operation dataset, the HS-YOLO algorithm achieved a mAP of 87.2%, which is a 3.5% improvement compared to YOLOv5. Particularly, the dataset’s AP for detecting small objects such as cuffs, necklines, and safety belts is improved by 10.7%, 5.8%, and 4.4%, respectively. These results demonstrate the effectiveness of our proposed method in detecting small objects in power operation scenarios. Full article

This paper proposes a conceptual analysis of the limitations related to the development (and integration) of hybrid–electric propulsion on regional transport aircraft, with the aim to identify a feasibility space for this innovative aircraft concept. Hybrid–electric aircraft have attracted the interest of aeronautical research as these have the potential to reduce fuel consumption and, thus, the related greenhouse gas emissions. Nevertheless, considering the development of such an aircraft configuration while keeping the constraints deriving from technological and/or operating aspects loose could lead to the analysis of concepts that are unlikely to be realised. In this paper, specifically to outline the boundaries constraining the actual development of such aircraft, the influence on overall aircraft design and performance of the main technological, operating, and design factors characterising the development of such a configuration is analysed and discussed at a conceptual level. Specifically, the current achievable gravimetric battery energy density (BED) is identified as the main limiting factor for the development of regional hybrid–electric aircraft, and a sensitivity analysis shows the correlation of this important technological parameter with aircraft performance in terms of both fuel consumption and energy efficiency. In this context, minimum technological development thresholds are therefore identified to enable the effective development of this type of aircraft; namely, a minimum of BED = 500 Wh/kg at battery pack level is identified as necessary to provide tangible benefits. From an operating point of view, flight distance is the most limiting design requirement, and a proper assessment of the design range is necessary if a hybrid–electric aircraft is to be designed to achieve lower emissions than the state of the art; flight ranges equal to or lower than 600 nm are to be considered for this type of aircraft. As a bridging of both of the previous constraints, a change in the design paradigm with respect to established practices for state-of-the-art aircraft is necessary. More specifically, penalisations in maximum take-off weight and overall aircraft energy efficiency may be necessary if the aim is to reduce direct in-flight consumption by means of integration of hybrid–electric powertrains. Full article

In the realm of retail supply chain management, accurate forecasting is paramount for informed decision making, as it directly impacts business operations and profitability. This study delves into the application of tree-based ensemble forecasting, specifically using extra tree Regressors (ETRs) and long short-term memory (LSTM) networks. Utilizing over six years of historical demand data from a prominent retail entity, the dataset encompasses daily demand metrics for more than 330 products, totaling 5.2 million records. Additionally, external variables, such as meteorological and COVID-19-related data, are integrated into the analysis. Our evaluation, spanning three perishable product categories, reveals that the ETR model outperforms LSTM in metrics including MAPE, MAE, RMSE, and R². This disparity in performance is particularly pronounced for fresh meat products, whereas it is marginal for fruit products. These ETR results were evaluated alongside three other tree-based ensemble methods, namely XGBoost, Random Forest Regression (RFR), and Gradient Boosting Regression (GBR). The comparable performance across these four tree-based ensemble techniques serves to reinforce their comparative analysis with LSTM-based deep learning models. Our findings pave the way for future studies to assess the comparative efficacy of tree-based ensembles and deep learning techniques across varying forecasting horizons, such as short-, medium-, and long-term predictions. Full article

In the southeastern coastal regions of China, thick layers of marine soft soil are widely distributed, exhibiting characteristics such as high compressibility, high porosity, low strength, high sensitivity, and easy thixotropy, and these viscoelastic behaviors of foundation soil have significant implications for elastic compression bending bar, as evidenced by issues such as post-construction settlement of roadbeds and long-term operation deviation of bridge pile foundations. In this study, a mechanical model of an elastic bar embedded in an elastic and viscoelastic medium, fixed at the base and free at the top, is established based on the Winkler foundation assumption. The deflection function of a bar subjected to both axial force and locally distributed horizontal load is derived using the Rayleigh-Ritz method. Utilizing the elastic-viscoelastic correspondence principle, the viscoelastic medium surrounding the bar is modeled as an elastic medium in which the ground reaction coefficient varies within phase space formulation. This study provides a robust theoretical foundation for soft soil foundation engineering projects and fills a significant gap in the literature by offering a comprehensive framework for understanding displacement in elastic bars within viscoelastic media. Drawing upon the derivation of the deformation function for elastic rods within a viscoelastic medium, the findings of this research hold significant applicability across a range of domains. These include, but are not limited to, the expansion of roadways in regions characterized by coastal soft soil, as well as the monitoring of deformation and lifespan in bridge pile foundations. Full article

Acoustic imaging systems construct spatial maps of sound sources and have potential in various applications, but large, cumbersome form factors limit their adoption. This paper investigates methodologies to miniaturize acoustic camera systems for improved mobility. Our approach optimizes planar microphone array design to achieve directional sensing capabilities on significantly reduced footprints compared to benchmarks. The current prototype utilizes a 128−microphone, 50 × 50 cm² array with beamforming algorithms to visualize acoustic fields in real time but its stationary bulk hampers portability. We propose minimizing the physical aperture by carefully selecting microphone positions and quantities with tailored spatial filter synthesis. This irregular array geometry concentrates sensitivity toward target directions while avoiding aliasing artefacts. Simulations demonstrate a 32−element, ≈20 × 20 cm² array optimized this way can outperform the previous array in directivity and noise suppression in a sub-range of frequencies below 4 kHz, supporting a 4× surface factor reduction with acceptable trade-offs. Ongoing work involves building and testing miniature arrays to validate performance predictions and address hardware challenges. The improved mobility of compact acoustic cameras could expand applications in car monitoring, urban noise mapping and other industrial fields limited by current large systems. Full article

Digital music is one of the most important commodities on the market due to music royalty distribution in Korea. As the music market has been transformed into a digital music market by means such as downloading and streaming, the distribution of music royalties via online service providers (OSPs) has become a highly important issue for music rights holders. Currently, one of the most important issues in music royalty distribution in Korea is the unfair distribution of royalties due to the indiscriminate repeat streaming of digital music. To prevent this, music consumption log data from several OSPs were collected via a day-based system; however, there was a limit on the identification of detailed information on the use of music in its current state. This paper analyzes the structural problems and limitations related to the settlement of music royalties and provides a structure in which there can be transparent settlement and distribution between users and rights holders as an institutional measure. We also propose various AI (artificial intelligence)-based applications using music consumption log data. The proposed system will hopefully be used for public purposes. Full article

Background: According to statistics, worldwide, the number of young persons diagnosed with idiopathic scoliosis has tripled in the last 10 years. This tendency seems to be related to the development of technological devices that induce vicious postures. Specialized literature shows that the predicted evolution will lead to a tripling of the population affected by scoliosis by 2050. Associated complications can be most varied, with functional or respiratory and cardiac impairment being the most severe. The purpose of this study is to objectify the effect of associating Schroth therapy with general elements of global postural reeducation (GPR) therapy in the treatment of scoliosis using electromyography, scoliosis assessment scales, and sleep quality evaluation. The present study is addressed to scoliotic patients. Methods: In order to assess the muscle imbalance installed in scoliosis, we have used SEMG, while Epworth, Baecke, and SAQ scales assessed sleepiness, physical activity levels, and self-perception of the scoliotic patient. Results: After performing a therapeutic protocol that combines Schroth and global postural reeducation (GPR) exercises, an improvement of the functional status was observed for the scoliotic patients. The statistical analysis presents a favorable symmetry index during flexion (p = 0.042), a significant difference in the Epworth score (p = 0.002), as well as a significant difference in the SAQ2 score (p = 0.049). Conclusion: Early detection of scoliosis prevents functional degradation. On the other hand, developing an adequate therapeutic protocol leads to an improved functional status and increased life quality. Full article

The present study evaluated the application of Ground Penetrating Radar and Electromagnetic Induction geophysical tools combined with sedimentology for the description of the subsurface of sites destined for the installation of ponds for an extensive freshwater fish farming system. Two areas with similar topographic characteristics (flat land near bodies of water) were investigated in the Amazon region of northern Brazil: Area 1—the future site of an aquaculture research center, and Area 2—an established fish farming operation. These tools performed well in the evaluation of the suitability of the terrain for the installation of aquaculture ponds. The application of these tools can, thus, be recommended for aquaculture projects, given that it provides advanced knowledge on the characteristics of the local soils, which is extremely important to guarantee the sustainability of any aquaculture operation. These data can help minimize the environmental impacts of the process, while maximizing the economic returns to the installation of an aquaculture operation. Full article

Etalon is considered to be one of the most promising satellites for studying crustal motions, Earth rotation, and other scientific applications. Unfortunately, its outsized shape and signature result in a measurement range bias of several millimeters. On the basis of simulations of the echo signals, we analyze the center of mass corrections (CoM) for Etalon due to variations in satellite signature effect at different incidence angles. To minimize range bias caused by satellite signature effects, a center of mass corrections filter has been proposed for the processing of standard SLR data. According to the relationship between RMS of CoM and the upper limits of the rejection criteria, the measurements with the lowest variability of CoM are selected for normal points. Statistics indicate that the center of mass corrections filter can improve the stability of the collected data by 79%, and reduce the mean RMS of normal points from 163.7 × 41.8 ps to 118.2 × 8.94 ps. Additionally, the new algorithm is applicable to Etalon-2. In particular, this paper enriches and provides a useful reference for minimizing the effects of satellite signatures on the production of SLR data by providing a theoretical model that incorporates systematic errors in SLR. Full article

This study analyzes the impact of injection condition design factors of (3-glycidoxypropyl)trimethoxysilane (GPTMS)–SiO₂ nanofluid on improving wettability and oil recovery through flotation and core flooding tests, respectively. Flotation tests were conducted to assess improvements in wettability that resulted from varying nanoparticle concentration, reaction time, and treatment temperature. The test results demonstrated that the hydrophilic sample ratio increased by up to 97.75% based on the nanoparticle reaction, confirming significant wettability improvement in all samples. Additionally, time-dependent fluid-flow experiments were conducted to validate oil recovery and rock–fluid interactions. In these experiments, for a 24-h reaction time, nanofluid injection caused a decrease in the maximum contact angle (43.4° from 166.5°) and a remarkable enhancement in the oil recovery rate by over 25%. Moreover, variations in contact angle and sample permeability were observed as the reaction time increased. Subsequently, the core flooding test revealed a critical reaction time of 24 h, maximizing oil recovery while minimizing permeability. Below this point in time, wettability improvement did not significantly enhance oil recovery. Conversely, beyond this threshold, additional adsorption due to particle aggregation decreased permeability, causing reduced oil recovery. Therefore, GPTMS–SiO₂ nanofluid can be utilized as an injection fluid to enhance oil recovery in high-temperature and high-salinity carbonate reservoirs. Full article

Due to the increasing reliance on social network platforms in recent years, hate speech has risen significantly among online users. Government and social media platforms face the challenging responsibility of controlling, detecting, and removing massively growing hateful content as early as possible to prevent future criminal acts, such as cyberviolence and real-life hate crimes. Twitter is used globally by people from various backgrounds and nationalities; it contains tweets posted in different languages, including code-mixed language, such as Hindi–English. Due to the informal format of tweets with variations in spelling and grammar, hate speech detection is especially challenging in code-mixed text. In this paper, we tackle the critical issue of hate speech detection on social media, with a focus on a mix of English and Hindi–English (code-mixed) text messages on Twitter. More specifically, we aim to evaluate the impact of data pre-processing on hate speech detection. Our method first performs 10-step data cleansing; then, it builds a detection method based on two architectures, namely a convolutional neural network (CNN) and a combination of CNN and long short-term Memory (LSTM) algorithms. We tune the hyperparameters of the proposed model architectures and conduct extensive experimental analysis on real-life tweets to evaluate the performance of the models in terms of accuracy, efficiency, and scalability. Moreover, we compare our method with a closely related hate speech detection method from the literature. The experimental results suggest that our method results in an improved accuracy and a significantly improved runtime. Among our best-performing models, CNN-LSTM improved accuracy by nearly 2% and decreased the runtime by almost half. Full article

Visual understanding is a research area that bridges the gap between computer vision and natural language processing. Image captioning is a visual understanding task in which natural language descriptions of images are automatically generated using vision-language models. The transformer architecture was initially developed in the context of natural language processing and quickly found application in the domain of computer vision. Its recent application to the task of image captioning has resulted in markedly improved performance. In this paper, we briefly look at the transformer architecture and its genesis in attention mechanisms. We more extensively review a number of transformer-based image captioning models, including those employing vision-language pre-training, which has resulted in several state-of-the-art models. We give a brief presentation of the commonly used datasets for image captioning and also carry out an analysis and comparison of the transformer-based captioning models. We conclude by giving some insights into challenges as well as future directions for research in this area. Full article

Previously, in regard to tunnel design and research, the focus was primarily on traffic capacity and safety requirements, with less consideration given to cave landscape design and its impacts on drivers. This study addressed this gap by proposing a comprehensive evaluation system for urban tunnel landscape driving based on the Analytic Hierarchy Process (AHP) theory. Considering the information and perception aspects of the driving process and the unique landscape characteristics of urban tunnels, we utilized the drivers’ perception of biomass as an index layer and performed a simulation using a machine learning algorithm. The proposed model was validated through vehicle field tests that were conducted in four urban tunnels along with a substantial amount of measured biomass data obtained during the experiments. The research demonstrated a strong correlation between the urban tunnel body landscape and the driving comprehensive index, particularly under relevant biomass conditions, which revealed the interactive relationship between urban tunnel body landscape design parameters and biomass. Furthermore, the study analyzed and proposed the impact degree of the urban tunnel body landscape on drivers’ biomass indicators, which offered valuable insights into designing tunnel body landscapes with consideration for biomass perception. Full article

Concrete that self-compacts is frequently utilized in engineering construction. Recycled coarse aggregate self-compacting concrete (RCASCC) is made by partially substituting recycled coarse aggregates (RCA) for natural coarse aggregates in order to conserve construction resources. This study examines the impact of linked sulfate erosion, dry and wet cycles, and RCA replacement rates of 0%, 25%, 50%, 75%, and 100% on the mechanical properties and durability of RCASCC. By using the mass loss rate, relative dynamic elastic modulus, corrosion resistance factor, X-ray diffraction (XRD), scanning electron microscope (SEM), and atomic force microscope (AFM) analyses, as well as other macroscopic and microscopic methods, it is possible to examine the deterioration patterns of RCASCC under dry and wet cycles. The results demonstrate that the addition of RCA has a notable impact on concrete’s resistance to sulfate attack during both dry and wet cycles. The erosion products steadily rise, the interfacial transition zone (ITZ) becomes rougher, and the sulfate resistance falls as the replacement rate of RCA rises. According to the findings of SiO₂, AFt, and CaCO₃, the examination of corrosion products from XRD and microstructure from SEM and EDS is carried out. The old mortar that has adhered to the surface of RCA, as shown by the AFM analysis of ITZ and the SEM analysis of RCA, can significantly affect the roughness of ITZ inside RCASCC. Full article

Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based on the curve increment strategy with adaptive particle swarm optimization (CIPSO). Firstly, the objective function is constructed based on the multi-objective optimization method. Here, a fuzzy comprehensive evaluation (FCE)-based vessel collision hazard model and vessel speed-varying energy-loss model integrating the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) are involved. Furthermore, in response to the limitations of the PSO algorithm, which is prone to falling into local optima in the later stages of iteration, a curve increment strategy is incorporated. To improve the performance of the global optimization, it is optimized using a local followed by global search method. The iterative evolution of CIPSO is used to obtain the optimal decision value in the set domain of feasible solutions. Finally, the effectiveness and feasibility of the proposed method are verified by the numerical simulation and large vessel maneuvering simulator, which can provide collision avoidance decision support for ship pilots. Full article

This study is primarily intended to present a damage constitutive equation under the combined action of confining pressures and freeze–thaw cycles by subjecting deep expansive clay to the consolidated undrained triaxial tests. We study the influence of the numbers of freeze–thaw cycles on various mechanical indexes of soil by using the TSZ-2 instrument (fully automatic triaxial instrument). As the number of freeze–thaw cycles increases, the ultimate peak stress of the soil decreases, and then, the effect of the freeze–thaw effect on the shear strength gradually weakened. By combining the expression method of the damage variable under the action of loading alone with the expression method under the action of freeze–thaw cycles alone, we brought in the damage evolution equation to obtain the damage constitutive equation under the combined action of confining pressures and freeze–thaw cycles. The stress values under three confining pressures (100 kPa, 200 kPa, and 300 kPa) can be determined by using the final damage constitutive model. The measured data with a water content of 17% and six freeze–thaw cycles were compared with the theoretical data. The actual strength values were 118.4 kPa, 152.3 kPa, and 184.1 kPa, and the theoretical strength values were 120 kPa, 150 kPa, and 186 kPa. The fitting degree of the strength value was as high as 99%, which verifies the feasibility of this model. This study can serve as an available reference for well wall construction and disaster prediction in deep coal mining. Full article

Automated monitoring of cutting tool wear is of paramount importance in the manufacturing industry, as it directly impacts production efficiency and product quality. Traditional manual inspection methods are time-consuming and prone to human error, necessitating the adoption of more advanced techniques. This study explores the application of ViDiDetect, a deep learning-based defect detection solution, in the context of machine vision for assessing cutting tool wear. By capturing high-resolution images of machining tools and analyzing wear patterns, machine vision systems offer a non-contact and non-destructive approach to tool wear assessment, enabling continuous monitoring without disrupting the machining process. In this research, a smart camera and an illuminator were utilized to capture images of a car suspension knuckle’s machined surface, with a focus on detecting burrs, chips, and tool wear. The study also employed a mask to narrow the region of interest and enhance classification accuracy. This investigation demonstrates the potential of machine vision and ViDiDetect in automating cutting tool wear assessment, ultimately enhancing manufacturing processes’ efficiency and product quality. The project is at the implementation stage in one of the automotive production plants located in southern Poland. Full article

Three-dimensional radiological evaluation through cone beam computer tomography is essential in diagnosing and establishing proper surgical management in impacted teeth. Through Augmented Reality (AR), clinicians have the opportunity to use three-dimensional computer-generated radiologic information to visualise the patient and simultaneously the superimposition of his internal structures. Here, we describe a digital workflow to assist the oral surgeon in pre-orthodontic exposure of a vestibular impacted canine using AR. The AR hardware consists of a camera and a traditional stand-up monitor. The registration and tracking are video-based and marker-free, with an automatic pose estimation obtained through VisLab 20.10.1AR software algorithm’s object recognition and tracking approach. A 3D model is created by combining the anterior teeth taken from the intraoral scan with the same teeth plus the included tooth taken from the CBCT segmentation. The 3D file is uploaded into the AR software. Model tracking is straightforward to set up without prior registration of targets or surroundings. The AR information is used successfully to define the surgical access to perform flap and osteotomy. The accuracy of model tracking matching was calculated constantly by the software. During the tracking, the process recorded an inlier ratio of 0.39:0.48. Further studies and clinical trials will evaluate the value of this novel technology in the management of impacted teeth. Full article

Off-axis parabolic mirrors have extensive applications in X-ray optics, with the precision of their curvature directly impacting grazing-incidence focusing performance. Notably, the off-axis parabolic surface has non-rotating and non-symmetrical characteristics. Ultra-precision raster grinding utilizing a diamond wheel is a common method. Crucially, establishing an optimal wheel path stands as the key to ensuring surface accuracy during off-axis paraboloid grinding. In this study, according to the double curvature property of an off-axis parabolic surface, two different wheel paths were compared: one tracing the meridian direction (parabolic generatrix) and the other following the arc vector direction (arc). The results showed that the wheel path in raster grinding stepping along the arc vector direction can obtain a smaller scallop height and higher surface accuracy. The surface accuracy of one step along the arc vector direction is 9.6 μm, and that of the other step along the meridian direction is 32.6 μm. A model of the scallop height was established based on the relative relationship between adjacent wheel paths, and the error is within 5%. According to the correlation between scallop height and shape error, we conducted an analysis of the spatial distribution of shape errors under varying wheel paths. The wheel path that steps along the arc vector is more suitable for raster grinding of the off-axis paraboloid. The above study can provide theoretical guidance for the wheel path planning of off-axis parabolic mirrors with high surface accuracy. Full article

The noise control of flank array sonar is a primary approach to enhance the sonar detection range. During submarine navigation, hydrodynamic noise is the main noise source in the platform region of the flank array sonar, which includes flow noise and flow-induced noise. Therefore, an in-depth investigation of hydrodynamic noise is necessary. In this paper, we firstly take the teardrop submarine as a computational model to validate the computational method. Afterwards, we numerically simulate the flow and flow-induced noise characteristics for the cylindrical shell model, and investigate differences in noise at different detection points along the X, Y, and Z axes. Finally, experiments are conducted to confirm the accuracy of the simulation results. The research findings reveal that, at the same frequency, flow-induced noise exceeds flow noise, and the noise decreases as the distance between the walls of the cylindrical shell increases. The experimental and simulation results are consistent, suggesting that the selected computational method can precisely simulate the submarine’s noise. Full article

For the development of reinforced concrete structures and infrastructure construction, traditional rebar checking and acceptance methods have shortcomings in terms of efficiency. The use of digital image processing technology cannot easily identify a rebar configuration with complex and diverse backgrounds. To solve this problem, an inspection method combining deep learning and digital image processing techniques is proposed using an improved DeeplabV3+ model to identify reinforcing bars, with the identification results subjected to digital image processing operations to obtain the size information of the reinforcing bar. The proposed method was validated through a field test. The results of the experiment indicated that the proposed model is more accurate than other models, with a mean Intersection over Union (mIoU), precision, recall, and F1 score reaching 94.62%, 97.42%, 96.95%, and 97.18%, respectively. Moreover, the accuracy of the dimension estimations for the test reinforcements met the engineering acceptance standards. Full article

This study investigated the impact of incorporating Cissus quadrangularis (CQ) powder into Yanggaeng, a traditional Korean food, focusing on its functional properties. This study examined the proximate composition, physicochemical characteristics, antioxidant capabilities, sensory attributes, and consumer preferences of Yanggaeng when treated with different levels (CON [0%], CQ2 [2%], CQ4 [4%], and CQ6 [6%]) of CQ powder. Yanggaeng with CQ powder exhibited a significantly reduced pH, and among the CQ additive groups the highest °Brix value was observed in CQ2. The water holding capacity (WHC) decreased after adding CQ powder. The color properties of Yanggaeng with CQ powder, including L*, a*, and b*, were measured. L* values dose-dependently decreased as the amount of CQ powder increased. Conversely, a* values increased significantly with CQ powder addition compared with CON, and b* values were highest in CQ2. Similarly, the browning index (BI) increased in the CQ powder treatment groups compared with CON. The antioxidative properties of Yanggaeng with CQ powder were evaluated by measuring the total phenolic content (TPC), total flavonoid content (TFC), 1,1-diphenyl-1-picrylhydrazyl (DPPH) and 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (ABTS) radical scavenging activities, and ferric reducing antioxidant power (FRAP). The antioxidant capacity dose-dependently increased with higher levels of CQ powder added. Regarding the texture profile of Yanggaeng, compared with the control group, adding CQ powder caused decreased hardness, gumminess, and chewiness. In consumer preference evaluations, CQ2 showed similarities to CON in all aspects (color, scent, flavor, sweetness, taste, chewiness, overall acceptance, and purchase intention). Therefore, incorporating CQ powder, a natural and edible antioxidative ingredient, into Yanggaeng may be acceptable to consumers despite significant changes in its physicochemical properties. Full article

This study aimed to investigate the practical applications of a ground source heat pump (GSHP) system for heating applications in embankment engineering. A special direct-expansion GSHP (DE-GSHP) was designed and manufactured, and its performance was experimentally assessed. Subsequently, the newly developed DE-GSHP structure demonstrated an excellent heating performance with respect to positive heat-supplying temperatures in cold regions. The temperature could be automatically controlled at 30, 45, 60, and 75; additionally, the heat-absorbing temperatures were maintained below 0 °C, which was extremely lower than that of the deep frost-free stratum. Further, the experimental data were used to evaluate the coefficient of performance of the DE-GSHP, which was more than 3.5. The findings indicated that the GSHP has potential applications for embankment heating in cold regions. Full article

Recurrent infections after root canal treatments often involve Enterococcus faecalis, a microorganism closely associated with therapy failures due to its biofilm production, survival in nutrient-deprived conditions, and antibiotic tolerance. Essential oils (EOs), which display antimicrobial and antibacterial properties, exhibit inhibitory effects on the growth of many microorganisms including E. faecalis. This study assessed the in vitro efficacy of combining 5% antibiotics (kanamycin 2.5 mg/mL, streptomycin 2.5 mg/mL, gentamicin 1.5 mg/mL, and ampicillin 5 mg/mL) with cinnamon (1.25% to 5%) or clove (25% and 50%) EOs in inhibiting the growth of E. faecalis, using disk diffusion tests. Disks were treated with EOs-only, antibiotics-only, or EO–antibiotic combinations, placed on BEA agar plates, and incubated for 24 h, and the zones of inhibition were measured. Results showed that EOs (cinnamon and clove) and 5% antibiotics, by themselves, had robust growth inhibition of E. faecalis across all tested concentrations. Moreover, combining 5% aminoglycosides (kanamycin 2.5 mg/mL, streptomycin 2.5 mg/mL, and gentamicin 1.5 mg/mL) with 5% cinnamon EO produced significantly enhanced antimicrobial effect than the corresponding 10% antibiotic solution alone. These findings suggest that combining cinnamon EO with aminoglycoside antibiotics can achieve significant inhibition of E. faecalis at a lower concentration of antibiotics compared to using a higher dose of antibiotics alone. Further in vivo studies should determine the safety, efficacy, and treatment duration, with the potential to reduce antibiotic dosages and associated toxicity while preventing recurrent infections. Full article

The accurate analysis of multi-scale flame development plays a crucial role in improving firefighting decisions and facilitating smart city establishment. However, flames’ non-rigid nature and blurred edges present challenges in achieving accurate segmentation. Consequently, little attention is paid to extracting further flame situation information through fire segmentation. To address this issue, we propose Flame-SeaFormer, a multi-scale flame situation detection model based on the pixel-level segmentation of visual images. Flame-SeaFormer comprises three key steps. Firstly, in the context branch, squeeze-enhanced axial attention (SEA attention) is applied to squeeze fire feature maps, capturing dependencies among flame pixels while reducing the computational complexity. Secondly, the fusion block in the spatial branch integrates high-level semantic information from the contextual branch with low-level spatial details, ensuring a global representation of flame features. Lastly, the light segmentation head conducts pixel-level segmentation on the flame features. Based on the flame segmentation results, static flame parameters (flame height, width, and area) and dynamic flame parameters (change rates of flame height, width, and area) are gained, thereby enabling the real-time perception of flame evolution behavior. Experimental results on two datasets demonstrate that Flame-SeaFormer achieves the best trade-off between segmentation accuracy and speed, surpassing existing fire segmentation methods. Flame-SeaFormer enables precise flame state acquisition and evolution exploration, supporting intelligent fire protection systems in urban environments. Full article

The present study investigated the impact of cane girdling on the ‘Hayward’ kiwifruit cultivar, both in terms of leaf physiological functions and fruit quality attributes, at harvest and post-storage. Four treatments were conducted: the control cane girdling conducted separately in August (GA), in September (GS), and both in August and September (double girdling) (GAS), using different canes. The results indicated that the carbon assimilation rate was reduced in girdled canes. Nevertheless, girdling resulted in increased fruit dry matter (by 1.7%), weight (by 6.4%), and dimensions without altering fruit shape. Additionally, fruits produced on girdled canes exhibited higher total soluble solids content (by almost 13%) and TSS-to-TA ratio post-storage. There were no significant differences in chlorophyll and carotenoid concentrations, organic acids, and most sugars assessed, both at harvest and post-storage. There were no significant differences among the treatments at harvest regarding total phenolic compounds, except for total flavonoids, which were lowest in the GA treatment. Post-storage, girdling (especially GAS and GS) was found to enhance the fruits’ total phenols and total flavanols, as well as its antioxidant capacity (1.88 μmol equiv. Trolox g⁻¹ FW based on DPPH assay under GS versus (0.53 μmol equiv. Trolox g⁻¹ FW under control). Overall, cane girdling can improve the quality of kiwifruit in terms of both fruit size and functional fruit properties. Full article