Appl. Sci., Volume 14, Issue 6 (March-2 2024) – 447 articles

Electrophotography is a digital, on-demand, dry, and page printing technique that operates based on toner particles of electronic materials using an electrostatic force and generates an electrical circuit via distribution of the toner particles. We developed a 10 $\mathsf{\mu }$m linewidth resolution with various electronic materials, including conductors, semiconductors, and insulators, without any chemical pretreatments on the substrate films, while a 5 $\mathsf{\mu }$m resolution was also possible for limited materials. The electrical resistivity of the printed Ag–Ni after an intense pulse light sintering was comparable to that of commercial indium tin oxide transparent films. Full article

The development of hydrogen-blended natural gas (HBNG) increases the risk of gas transportation and presents challenges for pipeline security in utility tunnels. The objective of this study is to investigate the diffusion properties of HBNG in utility tunnels and evaluate the effectiveness of various ventilation mechanisms. The numerical simulation software Fluent 2023 R1 is applied to simulate and analyze the leakage of small holes in a HBNG pipeline in the natural gas compartment. By examining the leaking behavior of HBNG through small holes in different circumstances, we aimed to identify the most unfavorable operational situation for leakage. Subsequently, we analyzed the ventilation strategy for sub-high-pressure pipes at various pressure levels in this unfavorable condition. This study’s findings demonstrate that blending hydrogen improves the gas diffusion capacity and increases the likelihood of explosion. The primary factors that influence the pattern of leakage are the size of the leaking holes and the pressure of the pipeline. The gas compartment experiences the most unfavorable working conditions for natural gas pipeline leaks when there are higher pressures, wider leak openings, higher hydrogen blending ratios (HBRs), and leaks in close proximity to an air inlet. When the HBR is 20%, the minimum accident ventilation rates for pressures of 0.4 MPa and 0.8 MPa are 15 air changes per hour and 21 air changes per hour, respectively. The maximum allowable wind speed for accident ventilation is 5 m/s, as regulated by China’s national standard, GB 50838-2015. This regulation makes it difficult to minimize the risk of leakage in a 1.6 MPa gas pipeline. It is recommended to install a safety interlock device to quickly shut off the pipeline in the event of a leak in order to facilitate the dispersion of the substance. Full article

Background and Objectives: Trichomonas tenax is a protozoan which participates in the human oral microflora. It is considered as a potential paradontopathogen. This microorganism is also reported in the respiratory tract. We aimed to analyze the available literature about the prevalence of Trichomonas tenax in the population affected by periodontal disease. Materials and Methods: Searching the Scopus, PubMed, and ScienceDirect databases with the keywords: “Trichomonas tenax” and “periodontal diseases” was able to identify several systematic reviews and original articles up until July 2023. All studies with patients suffering from periodontal disease, which mentioned the year of publication, the country, specified the detection methods, and included the total number of tested samples as well as the percentage of those infected with Trichomonas tenax were included. Irrelevant articles were excluded. Results: We found 137 studies, but only 64 studies about the distribution of Trichomonas tenax in patients with gum disease underwent qualitative analysis. The highest number of studies have been conducted in Iran, Poland and Iraq. Different methods have been used to detect the unicellular organism, each with a different specificity and sensitivity. Conclusions: Interest in Trichomonas tenax has grown considerably since 2000. Because of its association with periodontal disease, Trichomonas tenax’s role in the inflammatory process should not be overlooked. Full article

Wireless localization and target sensing both rely on precise extraction of parameters such as signal amplitude, propagation delay, and Doppler shift from the received signals. Due to the high multi-path resolution and strong penetration, both localization and sensing can be achieved through identical UWB waveforms. In this paper, we try to properly allocate resources for localization and sensing to fully exploit the potential of UWB systems. Considering the complexity of the multi-slot networks, we derive the Fisher Information Matrix (FIM) expressions for single-slot and dual-slot integrated sensing and localization (ISAL) networks, respectively, and propose two resource optimization schemes, namely the step-by-stepscheme and the integrated scheme, respectively. The numerical results show that: (i) for the sensing-resource-limited networks with relatively uniform node distribution, the energy allocated to each step in the step-by-step scheme satisfies the relationship energy for clock offset < energy for radar localization < energy for target sensing; (ii) in the multi-slot ISAL networks, more energy will be allocated to the time slots where the networks are relatively sensing-resource-limited; (iii) the step-by-step scheme is more suitable for the sensing-resource-abundant networks, while the integrated scheme is more suitable for the sensing-resource-limited networks. Full article

To protect the security of medical images and to improve the embedding ability of data in encrypted medical images, this paper proposes a permutation ordered binary (POB) number system-based hiding and authentication scheme for medical images, which includes three parts: image preprocessing, double hiding, and information extraction and lossless recovery. In the image preprocessing and double hiding phase, firstly, the region of significance (ROS) of the original medical image is segmented into a region of interest (ROI) and a region of non-interest (RONI). Then, the bit plane of the ROI and RONI are separated and cross-reorganization to obtain two new Share images. After the two new Share images are compressed, the images are encrypted to generate two encrypted shares. Finally, the embedding of secret data and attaching of authentication bits in each of these two encrypted shares was performed using the POB algorithm. In the information extraction and lossless recovery phase, the POBN algorithm is first used to extract the authentication bits to realize image tamper detection; then, the embedded secret message is extracted, and the original medical image is recovered. The method proposed in this research performs better in data embedding and lossless recovery, as demonstrated by experiments. Full article

Ceramics based on zirconium dioxide are very important compounds for dental, implant, and structural material applications. Despite the fact that tetragonally stabilized YSZ has been well studied, the search for new compositions of zirconia-based ceramics is still in progress. The ZrO₂-CeO₂ system is one of the alternatives for YSZ materials, but there is conflicting experimental data on its phase composition and mechanical properties depending on the ratio of components. In this study, we investigated the phase composition, and microstructural, mechanical, and physical properties of (1 − x)∙ZrO₂-x∙CeO₂ (step of x = 0.05) ceramics obtained by the solid-state sintering process from micron-sized powders. For the characterization of samples, XRD, Raman spectroscopy, SEM, the Vickers Microhardness Test, and dielectric spectroscopy were implemented. The results showed that by varying the CeO₂ concentration, it is possible to synthesize stable tetragonal ZrO₂ at room temperature with a high microhardness HV0.05 value of ~1500, low porosity (~2.5%), and a high dielectric constant of 36. The pronounced combined effect of tetragonal phase formation, densification, and grain size reduction on the mechanical and dielectric properties of the experimental samples was investigated. Refined experimental data make it possible to synthesize high-quality zirconia–ceria ceramics for use as refractories, dispersed nuclear fuel, or solid oxide fuel cells. Full article

Understanding the reliability of jump testing is essential to determine the neuromuscular progress of athletes and make informed decisions. This study aimed to assess the reliability of several countermovement jump (CMJ) and drop jump (DJ) test metrics in female volleyball players. Sixteen (n = 16) semi-professional female volleyball players participated in this test-retest study. Intrasession and intersession reliability of CMJ and DJ metrics were evaluated using a randomized cross-over design. A dual force platform was used to collect CMJ and DJ data, and several dependent variables were calculated using forward dynamics. Intraclass correlation coefficients (ICC), coefficients of variation (CV), and minimum difference (MD) were calculated to assess intra- and interday reliability. During the same testing, the third attempt consistently yielded the highest values for both tests in jump height but presented excellent reliability (CMJ: ICC [95%CI] = 0.97 [0.93–0.99]; CV [95%CI] = 4.1% [1.2–7.0]; MD95 = 3.5 cm; MD90 = 2.9 cm; DJ: ICC [95%CI] = 0.91 [0.77–0.97]; CV [95%CI] = 6.7% [1.9–11.5]; MD95 = 6.0 cm; MD90 = 5.0 cm). CMJ height exhibited excellent reliability between sessions (ICC [95%CI] = 0.93 [0.81–0.97]; CV [95%CI] = 3.8% [1.1–6.4]; MD95 = 3.5 cm; MD90 = 3.0 cm), whereas DJ height demonstrated slightly lower but still acceptable intersession reliability (ICC [95%CI] = 0.81 [0.55–0.93]; CV [95%CI] = 6.1% [1.7–10.4]; MD95 = 5.2 cm; MD90 = 4.4 cm). Intersession reliability for CMJ kinetics and kinematics was excellent for 13 of the 24 metrics assessed. For DJ, only concentric (ICC [95%CI] = 0.91 [0.76–0.97]; CV [95%CI] = 3.0% [0.9–5.2]; MD95 = 15 Ns; MD90 = 12.6 Ns) and eccentric impulses (ICC [95%CI] = 0.99 [0.96–0.99]; CV [95%CI] = 1.7% [0.5–2.9]; MD95 = 9.2 Ns; MD90 = 7.7 Ns) demonstrated excellent intersession reliability. Most CMJ variables showed excellent reliability within sessions, while DJ had lower reliability in most metrics. These findings provide valuable information to physical trainers to select the metrics to assess athletes’ performance as well as to identify a minimum cut-off value that serves as a reference for each of the metrics reported in both tests. Full article

This paper describes the development of an Advanced Driver Assistance System (ADAS) which will allow drivers to avoid collisions with an oncoming vehicle from an occluded area when turning right at intersections in left-hand traffic. Connected vehicles, in coordination with infrastructure, represent one of the commercialized ADAS technologies for collision avoidance. However, the coverage of the ADAS will be limited to designated intersections only, as communication equipment needs to be installed in both the vehicle and infrastructure to enable the assistance. This paper proposes an ADAS using on-board sensors, independent of infrastructure facilities, to control the vehicle velocity to avoid collisions. Most current intersection assistance, by using an Autonomous Emergency Braking System (AEBS), allows the driver to avoid a collision with oncoming vehicles when there is clear vision without occlusion. However, many accidents occur when the vehicle detects the oncoming vehicle too late because of occlusion in the intersection, such as a vehicle in the opposite lane. This system calculates the hazardous speed criteria of the ego vehicle, which might result in a high risk of collision when darting out occurs, and provides speed control assistance to allow the driver to escape from the hazardous speed region. The simulation results reveal that the proposed system effectively reduces the possibility of collisions compared to conventional AEBS. Full article

FLASH proton therapy is widely considered in many labs. However, achieving a dose rate sufficient for FLASH is challenging, especially when using the scanning method. A beam uniformization process using a nonlinear magnet is employed to reduce the scanning time, supplemented by multi-energy extraction to enhance the dose rate. The impact of octupole fields, multipole field components, and step field on the transport line are tested. The nonlinear effect of the magnetic fields on the transverse motion of the particle beam is used to establish a uniform dose distribution at the target. Different schemes are investigated and the octupole approach was finally selected. Full article

This paper presents an energy management strategy using a Stateflow controller related to DC microgrids with the important penetration of renewable energy. The increase in world electricity demand is one of the principal drivers of the exhaustion of fossil fuels and increased greenhouse gas emissions. To solve these problems, several countries have adopted actions for widespread renewable energy deployment, which includes wind energy, solar power, biomass power, tidal, and hydropower. These sources are considered as significant in delivering clean energy and reducing greenhouse gas emissions for sustainable improvement. As these sources play an increasingly vital role in the global energy landscape, the efficient management of these intermittent sources is essential for grid stability and sustainability. This paper aimed to develop an energy management strategy for DC microgrids to supply power to a DC microgrid system. The main objective of this paper was to implement an energy management system to ensure the proper operation of DC microgrid systems utilizing Simulink blocks available in MATLAB/Simulink 2020b software. The simulation results demonstrated that the developed energy management algorithm was unconditionally reliable, ensuring the proper operation of the microgrid systems. Additionally, the results demonstrated that the energy management strategy exhibited robust performance across different scenarios, effectively balancing energy generation and consumption while ensuring the reliable operation of the microgrid system. Moreover, the developed algorithm model presents another advantage, as it enables users to access and to change any control parameters within the DC microgrid. By comparing these results with the literature, the developed energy management algorithm provides safety and the automatic control of the microgrid. Full article

This paper investigates innovative methods for enhancing heat transfer efficiency in high-power permanent magnet electrical machines. The objectives are to quantify the effects of increasing the air speed, increasing the turbulence intensity, and introducing the spacing between windings on cooling performance. The cooling of stator windings is studied through experimental wind tunnel testing and Computational Fluid Dynamics (CFD) modelling. The CFD model is validated against wind tunnel measurements to within 4 Kelvin (K). The results demonstrate that each enhancement method significantly improves the cooling capability. Increasing the air speed from 10 m/s to 40 m/s reduces the winding hotspot temperature by 34%. Introducing a high turbulence intensity of 40% leads to a 21% lower hotspot temperature compared to 0.5% turbulence intensity. Creating a 1.5 mm spacing between coils also substantially improves convection and conduction heat transfer. Overall, combining these optimised design parameters yields over a 40% reduction in hotspot temperature compared to the original design. This research provides practical guidance for maximising heat transfer efficiency in high-power permanent magnet machines, without increasing complexity. The findings will lead to higher machine efficiency, reliability, and longevity for aerospace and other applications. Full article

Image captioning, also recognized as the challenge of transforming visual data into coherent natural language descriptions, has persisted as a complex problem. Traditional approaches often suffer from semantic gaps, wherein the generated textual descriptions lack depth, context, or the nuanced relationships contained within the images. In an effort to overcome these limitations, we introduce a novel encoder–decoder framework called A Unified Visual and Linguistic Semantics Method. Our method comprises three key components: an encoder, a mapping network, and a decoder. The encoder employs a fusion of CLIP (Contrastive Language–Image Pre-training) and SegmentCLIP to process and extract salient image features. SegmentCLIP builds upon CLIP’s foundational architecture by employing a clustering mechanism, thereby enhancing the semantic relationships between textual and visual elements in the image. The extracted features are then transformed by a mapping network into a fixed-length prefix. A GPT-2-based decoder subsequently generates a corresponding Chinese language description for the image. This framework aims to harmonize feature extraction and semantic enrichment, thereby producing more contextually accurate and comprehensive image descriptions. Our quantitative assessment reveals that our model exhibits notable enhancements across the intricate AIC-ICC, Flickr8k-CN, and COCO-CN datasets, evidenced by a 2% improvement in BLEU@4 and a 10% uplift in CIDEr scores. Additionally, it demonstrates acceptable efficiency in terms of simplicity, speed, and reduction in computational burden. Full article

The computer numerically controlled (CNC) system is the key functional component of CNC machine tool control systems, and the servo drive system is an important part of CNC systems. The complex working environment will lead to frequent failure of servo drive systems. Taking effective health management measures is the key to ensure the normal operation of CNC machine tools. In this paper, the comprehensive effect of fault prediction and fault diagnosis is considered for the first time, and a health management system for machine tool servo drive systems is proposed and applied to operation and maintenance management. According to the data collected by the system and related indicators, the technology can predict the state trend of equipment operation, identify the hidden fault characteristics in the data, and further diagnose the fault types. A health management system mainly includes fault prediction and fault diagnosis. The core of fault prediction is the gated recurrent unit (GRU). The attention mechanism is introduced into a GRU neural network, which can solve the long-term dependence problem and improve the model performance. At the same time, the Nadam optimizer is used to update the model parameters, which improves the convergence speed and generalization ability of the model and makes it suitable for solving the prediction problem of large-scale data. The core of fault diagnosis is the self-organizing mapping (SOM) neural network, which performs cluster analysis on data with different characteristics, to realize fault diagnosis. In addition, feature standardization and principal component analysis (PCA) are introduced to balance the influence of different feature scales, enhance the feature of fault data, and achieve data dimensionality reduction. Compared with the other two algorithms and their improved versions, the superiority of the health management system with high-dimensional data and the enhancement effect of fault identification are verified. The relative relationship between fault prediction and diagnosis is further revealed, and the adjustment idea of the production plan is provided for decision makers. The rationality and effectiveness of the system in practical application are verified by a series of tests of fault data sets. Full article

High-intensity interval exercise (HIIE) is a type of structured physical training characterized by repeated bouts of high-intensity exercise interspersed with recovery periods. Although HIIE was found to improve physical performance in a relatively short period of time, there is emerging evidence suggesting that acute HIIE may induce oxidative stress. The purpose, therefore, of the present study was to examine the effect of intermittency and/or acceleration during HIIE on oxidative stress in male participants. Nine healthy males [(age: 21.0 ± 3.0 years; height: 180.0 ± 4.0 cm; body mass: 79.4 ± 7.9 kg; maximal oxygen uptake ($\dot{V}$O_2max) 52.0 ± 6.0 mL·kg⁻¹·min⁻¹)] were recruited to perform six distinct exercise protocols of various intermittency (high, medium, and low) and acceleration (high, medium, and low) while a control session was also included. Blood samples were obtained to determine oxidative stress indices (lipid hydroperoxides, superoxide dismutase, and total glutathione) at rest, 1 h, 2 h, and 24 h following exercise on a non-motorized treadmill. The intra-individual variability of participants was observed in lipid hydroperoxides at baseline, ranging from 1.80 to 20.69 μmol·L⁻¹. No significant differences among the six different exercise protocols in any of the oxidative stress indices evaluated were observed (p > 0.05). These results suggest that the influence of various intermittency levels and acceleration patterns upon exercise-induced oxidative stress is negligible. Full article

The risk level of the NIMBY (Not In My Back Yard) phenomenon is crucial for the safety and economy of transmission and transformation projects which is rarely studied, especially for site selection and the construction of transmission lines and substations. In order to effectively evaluate the risk level to solve the dilemma caused by the NIMBY phenomenon, an evaluation method for quantifying the level of the NIMBY phenomenon is proposed. In this paper, thirty-one evaluation criteria and a risk model are put forward according to relevant laws and regulations that should be followed in the transmission and transformation project in China, then the scores corresponding to these criteria are obtained by a questionnaire survey. The radar chart method and minimum area method are applied to determine the weights of the element and unit layers. Furthermore, the overall risk level is evaluated by the fuzzy comprehensive evaluation method. In addition, a transmission and transformation project in Xi’an City, China, is used as an example to verify the correction of the risk model and its evaluation method. The results show that the weaknesses in the transmission and transformation project are analyzed, and suggestions for decreasing the risk level are put forward to minimize losses due to the NIMBY phenomenon. Full article

To solve the problem that noise seriously affects the online monitoring of parts signals of outdoor machinery, this paper proposes a signal reconstruction method integrating deep neural network and compression sensing, called ADMM-1DNet, and gives a detailed online vibration signal monitoring scheme. The basic approach of the ADMM-1DNet network is to map the update steps of the classical Alternating Direction Method of Multipliers (ADMM) into the deep network architecture with a fixed number of layers, and each phase corresponds to an iteration in the traditional ADMM. At the same time, what differs from other unfolded networks is that ADMM-1DNet learns a redundant analysis operator, which can reduce the impact of outdoor high noise on reconstruction error by improving the signal sparse level. The implementation scheme includes the field operation of mechanical equipment and the operation of the data center. The empirical network trained by the local data center conducts an online reconstruction of the received outdoor vibration signal data. Experiments are conducted on two open-source bearing datasets, which verify that the proposed method outperforms the baseline method in terms of reconstruction accuracy and feature preservation, and the proposed implementation scheme can be adapted to the needs of different types of vibration signal reconstruction tasks. Full article

The local independence assumption is crucial for the consistent estimation of item parameters in item response theory models. This article explores a pairwise likelihood estimation approach for the two-parameter logistic (2PL) model that treats the local dependence structure as a nuisance in the optimization function. Hence, item parameters can be consistently estimated without explicit modeling assumptions of the dependence structure. Two simulation studies demonstrate that the proposed pairwise likelihood estimation approach allows nearly unbiased and consistent item parameter estimation. Our proposed method performs similarly to the marginal maximum likelihood and pairwise likelihood estimation approaches, which also estimate the parameters for the local dependence structure. Full article

The goaf treatment of underground metal mines is an important link in mining, and it is particularly important to master the laws of overlying rock strata and surface movement of goaf. In this paper, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology is used to monitor the surface subsidence of the Taibao lead-zinc mine, and the surface subsidence laws of goaf-closure, partial-filling, and full-filling treatments are analyzed by the time-series method. The findings indicate that the surface subsidence of the closed goaf is solely governed by the pillars, with the quality of these pillars playing a pivotal role in controlling such subsidence. Factors like stope span also influence the surface subsidence of partially filled goaf. Prior to compaction, it is primarily the pillars that control surface subsidence; however, after compaction, filling and pillars jointly regulate this phenomenon. Notably, in filled goaf, the quality of both roof and pillars significantly impacts surface subsidence. Before compaction occurs, control over surface subsidence is not evident, yet post-compaction, the filling is effective and tends to stabilize this process. The research findings are significant in enhancing goaf’s treatment efficacy, mitigating surface damage and minimizing ecological environmental impact. Full article

This article aims to conduct an in-depth investigation into the environmental impact of Hall thruster plumes on spacecraft surface charging. The non-uniform plasma plume generated by Hall thrusters may trigger charging and discharging effects, making the assessment of surface charging risks crucial. Through numerical simulations using SPIS system, this study evaluates the surface charging characteristics of a complex spacecraft in orbit, simulating the effects of turning on and off the thrusters, as well as varying distances between the thrusters and the spacecraft. The simulation demonstrates that turning on the thrusters significantly affects spacecraft charging, reducing the potential difference between spacecraft surfaces from 3740 V to 19.2 V, effectively alleviating electrostatic discharge on the spacecraft surface. The closer the thruster is to the spacecraft, the more CEX ions are collected on the surface, influenced by the beam ions, resulting in a surface potential change of 1.3 V, with minor effects on surface potential but contributing to increased deposition contamination on the spacecraft surface. Full article

Sourdough bread is a traditional product made using lactic acid bacteria (LAB) and yeast. The influence of rye arabinoxylans (AXs) of different molar masses on sourdough wheat bread has not been studied to date. The aim of this study was to research the influence of arabinoxylans of different molar masses on the properties of sourdough wheat bread. The breads were baked using the sourdough method with wheat flour without and with 1% or 2% rye AX with different molar masses, which were unmodified, partially enzymatically hydrolyzed and cross-linked. The addition of all the AX preparations significantly increased the water absorption of the wheat flour. In particular, the addition of the preparation of cross-linked arabinoxylans at an amount of 2% caused the highest increase (by 9.8%) in the addition of water to the wheat flour dough. It was shown that a 2% addition of partially hydrolyzed AXs, with a low molar mass (190,440 g/mol), had the highest influence on increasing (by 23.7%) the volume of the bread and decreasing (by 41%) the crumb hardness of the sourdough bread, determined on the day of baking. The addition of the cross-linked AXs at an amount of 2% had the strongest influence on increasing the moisture content of the crumbs on the day of baking, both in the central (by 2.6%) and peripheral (by 5.1%) parts of the bread compared to the bread without the addition of AXs. The breads with all the AX preparations after the first and third days of storage had a higher crumb moisture content compared to the bread without the AXs. Full article

Deep neural networks are powerful image classifiers but do they attend to similar image areas as humans? While previous studies have investigated how this similarity is shaped by technological factors, little is known about the role of factors that affect human attention. Therefore, we investigated the interactive effects of task and image characteristics. We varied the intentionality of the tasks used to elicit human attention maps (i.e., spontaneous gaze, gaze-pointing, manual area selection). Moreover, we varied the type of image to be categorized (i.e., singular objects, indoor scenes consisting of object arrangements, landscapes without distinct objects). The human attention maps generated in this way were compared to the attention maps of a convolutional neural network (CNN) as revealed by a method of explainable artificial intelligence (Grad-CAM). The influence of human tasks strongly depended on image type: for objects, human manual selection produced attention maps that were most similar to CNN, while the specific eye movement task had little impact. For indoor scenes, spontaneous gaze produced the least similarity, while for landscapes, similarity was equally low across all human tasks. Our results highlight the importance of taking human factors into account when comparing the attention of humans and CNN. Full article

The Maillard reaction (MR) is one of the main reactions that occurs during the thermal processing of food. It contributes positively to the flavor, aroma, and color of food but also produces harmful by-products, including acrylamide and advanced glycation end products (AGEs). Bakery products are major staples consumed daily by people from all walks of life and of all ages; the identification of strategies to hamper acrylamide formation in bread and bread-like products is thus crucial for public health. Several strategies have been proposed to inhibit the MR in food processing, including biochemical approaches such as the use of enzymes; innovative technologies such as ohmic heating, pulsed electric field, high pressure processing, or encapsulation of metal ions; and the chemical modification of reactants, intermediates, or products of MR. Recently, phenolic compounds have been reported to have an inhibitory effect on the formation of harmful by-products resulting from the MR. The aim of this paper is, therefore, to provide a state-of-the-art overview of the use of phenolic compounds in the formulation of bakery products to inhibit the MR. A systematic review of the most up-to-date scientific literature was thus performed. It emerged that the inhibitory action was mainly investigated in bread. Phenolic extracts and powders obtained from plant-based foods have been included in the formulation of bakery products. The effect of pure phenolic standards was also considered. Full article

The aim of this study was to examine the effects of sandstone ring specimens with different inner diameters on dynamic compression mechanical characteristics after dry and wet circulation. To carry out our study, we subjected a sandstone ring specimen with a 50 mm outer diameter and a 0~25 mm inner diameter to 10 cycles of dry and wet circulation. Afterward, we recorded the specimen’s basic physical parameters and used a split-Hopkinson pressure bar (SHPB) test device to perform an impact compression test. Following dry and wet circulation, our results showed that the mass loss rate increased and the volume expansion rates and density decreased with the increase in the inner diameter of the sandstone ring sample. Simultaneously, with the increase in the inner diameter of the specimen ring, the dynamic compressive strength of the specimen presented an exponential negative correlation, the dynamic elastic modulus presented a quadratic negative correlation, and the dynamic peak strain presented a quadratic positive correlation. Concurrently, the average particle size of the specimen decreased, and the degree of breakage increased with the increase in the sandstone sample’s inner diameter. Regarding the energy analysis performed in this study, the sandstone ring sample’s energy dissipation increased, and its kinetic performance evidently weakened with the increase in the ring sample’s inner diameter. The results of this study have certain reference values for the construction and maintenance of natural cavity rock and underground hard rock roadways. Full article

To clarify the effect of proteins on the charging and aggregation–dispersion characteristics of oxidized carbon nanohorn (CNHox), we measured the electrophoretic mobility and stability ratios as a function of concentrations of a model protein, lysozyme (LSZ), and KCl. The zeta potential from the electrophoretic mobility of CNHox was neutralized and reversed by the addition of oppositely charged LSZ. Electrical and hydrophobic interactions between CNHox and LSZ can be attributed to the adsorption and charge reversal of CNHox. The stability ratio of CNHox in the presence or absence of LSZ showed Derjaguin–Landau and Verwey–Overbeek (DLVO) theory-like behavior. That is, the slow aggregation regime, fast aggregation regime, and critical coagulation concentration (CCC) were identified. At the isoelectric point, only the fast aggregation regime was shown. The existence of patch-charge attraction due to the charge heterogeneity on the surface was inferred to have happened due to the enhanced aggregation of CNHox at high LSZ dosage and low electrolyte concentration. The relationship between critical coagulation ionic strength and surface charge density at low LSZ dosage showed that the aggregation of CNHox is in line with the DLVO theory. An obvious decrement in the Hamaker constant at high LSZ dosage can probably be found due to an increased interaction of LSZ-covered parts. Full article

In this paper, we propose a learning model for tracking the isolines of fluid based on the physical properties of particles in particle-based fluid simulations. Our method involves analyzing which weights, closely related to surface tracking among the various physical properties of fluid particles, are significant. These weights are used as input values for the learning algorithm, enabling relatively accurate isoline tracking. In addition, compared to existing learning models such as linear regression, LSTM (long short-term memory), and learning representation (1-layer) models, our method obtained superior surface tracking results without accumulating errors. By using our proposed network structure to track the fluid surface, it learns and predicts values derived from existing fluid simulation algorithms, eliminating the need for computational processes for level-set values and enabling real-time surface tracking. As the scale of the simulation increases, our method significantly reduces the time and resources consumed compared to traditional methods and can track the fluid surface without additional resource consumption. Furthermore, due to our method’s simple network structure, the time consumed in the initial process of loading the model into memory is faster than models such as CNN and LSTM. Our proposed model occupies less than 30 kb of storage space, making it suitable for use in middleware. Lastly, to verify the generality of our method, we conducted tests in a total of five scenes, and in all test scenes, visually natural fluid isolines were represented. Full article

On a global scale, traffic incidents are a leading cause of mortality and material damage. Romania exhibits the highest rate of road traffic fatalities both in the European Union and worldwide, requiring a comprehensive examination of its overall influence on a national level. The current study uses an extensive approach centering on a spatial analysis model based on the Analytic Hierarchy Process (AHP). Employing a series of spatial databases, this model delineates the geographical distribution and characteristics of road accidents to establish both their cumulative national impact and the identification of high-risk areas. The spatial database, containing traffic incident data, is constructed using geolocation techniques and integrated through network analysis to evaluate the impact in relation to distance. The AHP framework is applied in analyzing the impact across five key dimensions: accident severity, occurrence mode, prevailing weather conditions, traffic restrictions, and road markings. This multi-level AHP analysis not only identifies high-risk hotspots but also confirms the effectiveness of the proposed spatial model. Full article

In addressing the challenges of high energy consumption and low efficiency in fertilization borehole drilling for clayey soils in southern orchards, this study utilizes the Discrete Element Method to establish a simulation model for clayey soils. Through this approach, we identify an optimal set of operational parameters that significantly reduces energy consumption. By utilizing simulation technology to model the drilling process, we analyzed the impact of rotation speed and feed rate on the torque and resistance of the drilling apparatus. Initially, this paper describes field measurements of particle parameters in soils from southern orchards. Subsequently, utilizing the Discrete Element Method and particle contact theory, we established a simulation model to represent the interactions between soil and soil, as well as soil and auger in the soil environment of the southern region. For the Southern orchard clay with a moisture content of 16.8% and a measured angle of repose of 35.55°, parameter calibration was performed. The contact model “Hertz-Mindlin with Johnson-Kendall-Roberts” was selected in EDEM. Using Design Expert, a regression model variance analysis was applied to the discrete element model parameters, leading to the determination of the optimal values for significant soil model parameters. The soil JKR surface energy is 5.85 J·m⁻², with a soil–soil restitution coefficient of 0.65 and a soil–steel static friction coefficient of 0.5. Subsequently, discrete element simulation experiments on the drilling apparatus were conducted in EDEM, considering various rotation speeds and feed rates. The simulation analysis indicates that the torque consistently increases with higher rotation speeds, with a maximum relative error of 7%. The torque initially rises from zero to a maximum value, then gradually decreases to a low value, followed by a rapid increase to a higher value, and finally drops back down. This cycle repeats in the observed pattern. The total force experienced reaches its minimum average value of 200 N at a feed rate of 0.05 m/s. Simulation test results indicate that, among the three forces acting on the auger (vertical resistance, horizontal resistance, and lateral resistance), vertical resistance is the primary factor contributing to power consumption. As the rotation speed increases, the maximum value of vertical resistance continues to rise, while horizontal resistance and lateral resistance exhibit a declining trend. As the feed rate increases, the maximum values of resistance in all three directions also increase. When the feed rate exceeds 0.05 m/s, the maximum lateral resistance experiences a sharp increase. Through comprehensive analysis, the optimal operational parameters for borehole fertilization are determined to be a rotation speed of 100 r·min⁻¹ and a feed rate of 0.05 m/s. The aim of this study is to reduce the energy consumption of borehole fertilization operations, minimize carbon emissions, and promote the sustainable development of orchard production. Full article

The analysis of environmental DNA (eDNA) is a powerful and non-invasive method for monitoring the presence of species in ecosystems. However, ecologists and laboratory staff can find it challenging to use eDNA analysis software effectively due to the unfamiliar command-line interfaces used by many of these packages. Therefore, we developed the eDNA-container app, a free and open-source software package that provides a simple user-friendly interface for eDNA analysis. The application is based on the popular QIIME2 library and is distributed as a Docker image. The use of Docker makes it compatible with a wide range of operating systems and facilitates the reproducible analysis of data across different laboratories. The application includes a point-and-click user interface for selecting sequencing files, configuring parameters, and accessing the results. Key pipeline outputs, such as sequence quality plots, denoising, and ASV generation statistics, are automatically included in a PDF report. This open-source and freely available analysis package should be a valuable tool for scientists using eDNA in biodiversity and biosecurity applications. Full article

The early detection of cognitive impairment is essential in order to initiate interventions and guarantee access to healthcare services. Digital solutions are emerging in the literature as an alternative approach to cognitive screening. Our primary goal is to synthesize the evidence on digital solutions’ diagnostic ability to screen for cognitive impairment and their accuracy. A secondary goal is to distinguish whether the ability to screen for cognitive impairment varies as a function of the type of digital solution: paper-based or innovative digital solutions. A systematic review and meta-analysis of digital solutions’ diagnostic accuracy were conducted, including 25 studies. Digital solutions presented a variable diagnostic accuracy range. Innovative digital solutions offered at least 0.78 of sensitivity but showed lower specificity levels than the other subgroup. Paper-based digital solutions revealed at least 0.72 of specificity, but sensitivity started at 0.49. Most digital solutions do not demand the presence of a trained professional and include an automatic digital screening system and scoring, which can enhance cognitive screening and monitoring. Digital solutions can potentially be used for cognitive screening in the community and clinical practice, but more investigation is needed for an evidence-based decision. A careful assessment of the accuracy levels and quality of evidence of each digital solution is recommended. Full article

Recognizing aircraft automatically by using satellite images has different applications in both the civil and military sectors. However, due to the complexity and variety of the foreground and background of the analyzed images, it remains challenging to obtain a suitable representation of aircraft for identification. Many studies and solutions have been presented in the literature, but only a few studies have suggested handling the issue using semantic image segmentation techniques due to the lack of publicly labeled datasets. With the advancement of CNNs, researchers have presented some CNN architectures, such as U-Net, which has the ability to obtain very good performance using a small training dataset. The U-Net architecture has received much attention for segmenting 2D and 3D biomedical images and has been recognized to be highly successful for pixel-wise satellite image classification. In this paper, we propose a binary image segmentation model to recognize aircraft by exploiting and adopting the U-Net architecture for remote sensing satellite images. The proposed model does not require a significant amount of labeled data and alleviates the need for manual aircraft feature extraction. The public dense labeling remote sensing dataset is used to perform the experiments and measure the robustness and performance of the proposed model. The mean IoU and pixel accuracy are adopted as metrics to assess the obtained results. The results in the testing dataset indicate that the proposed model can achieve a 95.08% mean IoU and a pixel accuracy of 98.24%. Full article