Appl. Sci., Volume 14, Issue 4 (February-2 2024) – 358 articles

The primary objective of this investigation was to assess the potential applicability of hemp (Cannabis sativa L. var. sativa) lateral inflorescence extract in mitigating the growth of fungi, including phytopathogens, on agricultural plants. The extract, comprising a blend of biologically active compounds, holds promise for integration into contemporary plant protection methodologies. The research involved a comprehensive analysis of the extract’s chemical composition, encompassing the determination of total polyphenol and flavonoid content (utilizing spectrophotometric methods), antioxidant activity (evaluated through the DPPH method employing synthetic 2,2-diphenyl-1-picrylhydrazyl radical), and cannabinoid content (analyzed using HPLC techniques). Additionally, this study employed the poisoned substrate method to gauge the impact of 5, 10, and 20% extract concentrations on the growth of various microfungi, including Alternaria alternata, Botrytis cinerea, Colletotrichum coccodes, Fusarium avenaceum, F. culmorum, F. graminearum, F. oxysporum, F. sporotrichioides, and Trichoderma koningii. The hemp extract demonstrated a substantial presence of total polyphenolic compounds, with polyphenol and flavonoid concentrations measuring 149.65 mg/mL and 1.55 mg/mL, respectively. Furthermore, the extract contained cannabinoids at a concentration of 0.12%. The most pronounced antifungal activity was observed with the 20% extract, particularly against T. koningii (62.22–84.79%), C. coccodes (61.65–81.82%), and B. cinerea (45.00–75.42%). However, the efficacy of hemp extracts exhibited large differences against Fusarium spp. (3.10–72.95%), dependent on the specific extract and fungus strain. Introduction of hemp extracts to the substrate induced a reduction in substrate pigment and a discernible color alteration in the mycelium to a lighter shade compared to the control. These findings mark the initial phase in the exploration of practical applications for plant extracts, setting the groundwork for subsequent field trials to ascertain the extract’s impact on phytotoxicity and the health status of agricultural plants. Full article

Sensor technologies have sufficiently advanced to provide low-cost devices that can quantify carbon dioxide levels in honeybee hives with high temporal resolution and in a small enough package for hive deployment. Recent publications have shown that summer carbon dioxide levels vary throughout the day and night over ranges that typically exceed 5000 ppm. Such dramatic changes in a measurable parameter associated with bee physiology are likely to convey information about the colony health. In this work, we present data from four UK-based hives collected through the winter of 2022/2023, with a focus on seeing if carbon dioxide can indicate when colonies are at risk of failure. These hives have been fitted with two Sensirion SCD41 photoacoustic non-dispersive infrared (NDIR) carbon dioxide sensors, one in the queen excluder, at the top of the brood box, and one in the crown board, at the top of the hive. Hive scales have been used to monitor the hive mass, and internal and external temperature sensors have been included. Embedded accelerometers in the central frame of the brood box have been used to measure vibrations. Data showed that the high daily variation in carbon dioxide continued throughout the coldest days of winter, and the vibrational data suggested that daily fanning may be responsible for restoring lower carbon dioxide levels. The process of fanning will draw in colder air to the hive at a time when the bees should be using their energy to maintain the colony temperature. Monitoring carbon dioxide may provide feedback, prompting human intervention when the colony is close to collapse, and a better understanding may contribute to discussions on future hive design. Full article

The metallurgical sector is one of the important sectors of the Slovak economy. Its integral part is the storage of metallurgical waste, which is accompanied by noise that bothers the inhabitants of the surrounding urban areas. This paper focuses on the analysis of the problem of noise propagation into protected areas located in the vicinity of the metallurgical plant. The paper describes a number of measurements that have been carried out at the slag landfill. Based on these measurements, simulations were performed using a mathematical model, and predictions of noise propagation in the exterior were made. Subsequently, noise reduction measures were proposed. The results obtained by the authors form a methodological basis for addressing such situations, since, during the solution, it was often necessary to deal with non-standard situations that were specific to the area of the technology addressed. This solution was then applied in real practice. Full article

This paper presents a novel data-driven multiagent reinforcement learning (MARL) controller for enhancing the running stability of independently rotating wheels (IRW) and reducing wheel–rail wear. We base our active guidance controller on the multiagent deep deterministic policy gradient (MADDPG) algorithm. In this framework, each IRW controller is treated as an independent agent, facilitating localized control of individual wheelsets and reducing the complexity of the required observations. Furthermore, we enhance the MADDPG algorithm with prioritized experience replay (PER), resulting in the PER-MADDPG algorithm, which optimizes training convergence and stability by prioritizing informative experience samples. In this paper, we compare the PER-MADDPG algorithm against existing controllers, demonstrating the superior simulation performance of the proposed algorithm, particularly in terms of self-centering capability and curve-negotiation behavior, effectively reducing the wear number. We also develop a scaled IRW vehicle for active guidance experiments. The experimental results validate the enhanced running performance of IRW vehicles using our proposed controller. Full article

Livestock blood, a major organic waste generated by the livestock industry, poses a risk of pollution due to its rapid decomposition. However, it is a potential protein source for agricultural purposes due to its protein-rich organic matter. In this study, we conducted studies on an eco-friendly, scalable, and effective protein degradation process using livestock blood to reduce waste and produce an amino acid liquid fertilizer that can be recycled for agricultural use. Ultrasonic technology was applied as a pretreatment method to improve the enzymatic hydrolysis efficiency of proteins in livestock blood, and the optimal conditions that led to 95.91% solubilization rate of hemoglobin were ultrasound duration for 30 min at an ultrasound density of 0.5 W/mL. As a result of hydrolyzing ultrasonically pretreated blood by mixing exo- and endo-type proteolytic enzymes, the optimal combination was a mixture of Savinase^® 1% and Flavourzyme^® 1%. After 4 h of reaction, the protein concentration was 27.8 mg/mL and the amino acid concentration was confirmed to be 54.6 mg/mL. This is about 4.2 times higher than the amino acid concentration of blood without ultrasound pretreatment, 13.1 mg/mL, and it was confirmed that sonication has a significant effect on improving protein degradation efficiency. As protein degradation increased, the viscosity of blood gradually decreased, suggesting that the physical force applied to the agitator torque diminished during the enzyme reaction; a significant correlation between protein and amino acid concentrations (biological factors) and torque (mechanical factor) was observed. Measuring torque during an enzyme reaction can confirm the extent of the enzyme reaction, so it can be used as an indicator of reaction progress when scaling up the process in the future. Full article

This study investigates the pH values and optical characteristics of Dual Rinse HEDP, either independently or combined with sodium hypochlorite (NaOCl), and compares them to other irrigants used in endodontics. The solutions used in this study were commercially acquired and prepared, followed by pH measurements using a pH meter and spectral analysis using UV/Vis spectrophotometry in specified wavelengths of the ultraviolet (UV) C (190–280 nm), UVB (281–315 nm), UVA (316–400 nm), visible light (VL) (401–780 nm), and near-infrared (NIR) spectra (781–1100 nm). The pH analysis revealed alkaline values for NaOCl, EDTA, Dual Rinse HEDP, and the HEDP + NaOCl combination, an acidic value for citric acid, and nearly neutral values for chlorhexidine and distilled water. Spectral analysis revealed the notable absorption characteristics of endodontic irrigants. In the UV range, all solutions exhibited higher absorption values to water (p < 0.05), with Dual Rinse HEDP resembling EDTA and citric acid, and HEDP + NaOCl resembling NaOCl. The NIR region highlights absorption peaks around 975 nm for all solutions, including NaOCl and Dual Rinse HEDP + NaOCl, suggesting potential applications in laser-activated irrigation. This study provides comprehensive insights into the pH and optical features of endodontic irrigants, emphasizing their potential roles in enhancing disinfection strategies and optimizing laser-activated irrigation protocols. Full article

The use of cricket protein in emulsions is in line with the growing interest in sustainable food sources, as crickets require minimal resources and produce lower greenhouse gas emissions than traditional livestock. Research in this area suggests that incorporating cricket protein into emulsions not only improves their nutritional value but also contributes to the development of environmentally friendly and functional food products. This study proposes the use of cricket protein for the stabilization of emulsions formulated with avocado oil as a dispersed phase. This oil is rich in monounsaturated fats, particularly oleic acid, and a variety of bioactive compounds. In the first part of this study, we assessed the influence of the emulsifier concentration and found that 2 wt.% is the optimum because a depletion flocculation effect was produced. Subsequently, processing was optimized using ultrasonication so that the higher energy input produced emulsions with a droplet diameter of less than 700 nm. Finally, rhamsan gum was added to the formulation, producing emulgels with improved pseudoplastic behavior and physical stability. This study demonstrates that cricket protein in combination with rhamsan gum is capable of forming stable, low-droplet-size emulgels with potential applications in encapsulation systems. Full article

In the field of behavioral detection, deep learning has been extensively utilized. For example, deep learning models have been utilized to detect and classify malware. Deep learning, however, has vulnerabilities that can be exploited with crafted inputs, resulting in malicious files being misclassified. Cyber-Physical Systems (CPS) may be compromised by malicious files, which can have catastrophic consequences. This paper presents a method for classifying Windows portable executables (PEs) using Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). To generate malware executable adversarial examples of PE, we conduct two white-box attacks, Jacobian-based Saliency Map Attack (JSMA) and Carlini and Wagner attack (C&W). An adversarial payload was injected into the DOS header, and a section was added to the file to preserve the PE functionality. The attacks successfully evaded the CNN model with a 91% evasion rate, whereas the RNN model evaded attacks at an 84.6% rate. Two defense mechanisms based on distillation and training techniques are examined in this study for overcoming adversarial example challenges. Distillation and training against JSMA resulted in the highest reductions in the evasion rates of 48.1% and 41.49%, respectively. Distillation and training against C&W resulted in the highest decrease in evasion rates, at 48.1% and 49.9%, respectively. Full article

Low-disturbance mining in surface mining (LDM) can transform traditional surface mine production systems into a more sustainable model by reducing the disturbance of surface mining, minimizing pollutant emissions, and reducing ecological impacts. The purpose of this paper is to explore the LDM evaluation method by applying multi-criteria decision-making to provide technical support for LDM implementation. Therefore, an evaluation method based on the combination of the fuzzy analytical hierarchy process (F-AHP) and grey clustering was proposed. Analyzed in terms of the current status of the evaluation indicators (reality) and the significance of the development of the LDM (desirability). Determined the weights and low-disturbance (LD) levels of the evaluation indicators. Combined with the fuzzy technique for order preference by similarity to an ideal solution (F-TOPSIS), the low-disturbance open pit mining paths are ranked, and finally, the decision support system for low-disturbance mining in surface mining is constructed. This study not only enriches the existing literature on related technologies but also lays the foundation for further research on LDM and provides exploratory insights for deeper improvement of LD level in surface mining. Full article

Research on the electrical properties of rocks and ores plays a crucial role in the development of geophysical electromagnetism methods. However, currently available instruments suffer from high power consumption, a limited number of electrodes, inaccurate measurements, poor portability, and a limited ability to measure the electrical parameters of rocks and ores. To address these issues, this paper presents a three-dimensional electrical impedance tomography system for rock samples with high-density microelectrodes based on an Android system and STM32 microcontroller. The system features high observation accuracy, dense electrode arrays (with 384 current and potential electrodes), flexible electrode selection, user-friendly human–computer interaction, good stability, and real-time performance. Powered by a single power bank, the entire instrument can be controlled and monitored wirelessly via Bluetooth and Wi-Fi technology using an Android smartphone. Additionally, the system not only enables accurate measurement of electrical parameters, but also facilitates the generation of three-dimensional impedance imaging of specimens via inversion algorithms after data export, allowing for a comprehensive understanding of the electrical properties of rocks and ores. This system holds great potential for future research in this field. Full article

Today, the IoT has become a vital part of our lives because it has entered into the precise details of human life, like smart homes, healthcare, eldercare, vehicles, augmented reality, and industrial robotics. Cloud computing and fog computing give us services to process IoT tasks, and we are seeing a growth in the number of IoT devices every day. This massive increase needs huge amounts of resources to process it, and these vast resources need a lot of power to work because the fog and cloud are based on the term pay-per-use. We make to improve the performance and cost (PC) algorithm to give priority to the high-profit cost and to reduce energy consumption and Makespan; in this paper, we propose the performance and cost–gray wolf optimization (PC-GWO) algorithm, which is the combination of the PCA and GWO algorithms. The results of the trial reveal that the PC-GWO algorithm reduces the average overall energy usage by 12.17%, 11.57%, and 7.19%, and reduces the Makespan by 16.72%, 16.38%, and 14.107%, with the best average resource utilization enhanced by 13.2%, 12.05%, and 10.9% compared with the gray wolf optimization (GWO) algorithm, performance and cost algorithm (PCA), and Particle Swarm Optimization (PSO) algorithm. Full article

Background: Scarce evidence is available regarding the occurrence and prevalence of hard/soft tissue deficiencies among patients undergoing surgically assisted rapid maxillary expansion (SARME) as compared to non-surgical rapid maxillary expansion (NSRME) approaches. The purpose of this study is to evaluate the effect of NSRME and SARME upon the periodontal structures. Methods: A literature search was performed to identify studies that fulfilled pre-established eligibility criteria, evaluating changes in the periodontium (e.g., probing depths) and hard/soft tissue deficiencies (e.g., bone levels, gingival recession) within patients undergoing NSRME and SARME procedures. Results: A total of 21 articles were included in the present review. Four of them evaluated the outcomes of both NSRME and SARME procedures, while six and eleven studies analyzed NSRME alone and SARME alone, respectively. The incidence of hard (e.g., changes in buccal bone width/height) and soft tissue deficiencies (e.g., gingival recession, keratinized tissue, and clinical attachment level) is slightly increased among patients undergoing maxillary expansion with worsened outcomes during NSRME procedures. Conclusions: The impact of NSRME and SARME upon the periodontium remains inconclusive. Full article

Efficient document recognition and sharing remain challenges in the healthcare, insurance, and finance sectors. One solution to this problem has been the use of deep learning techniques to automatically extract structured information from paper documents. Specifically, the structured extraction of a medical examination report (MER) can enhance medical efficiency, data analysis, and scientific research. While current methods focus on reconstructing table bodies, they often overlook table headers, leading to incomplete information extraction. This paper proposes MSIE-Net (multi-stage-structured information extraction network), a novel structured information extraction method, leveraging refined attention transformers and associated entity detection to enhance comprehensive MER information retrieval. MSIE-Net includes three stages. First, the RVI-LayoutXLM (refined visual-feature independent LayoutXLM) targets key information extraction. In this stage, the refined attention accentuates the interaction between different modalities by adjusting the attention score at the current position using previous position information. This design enables the RVI-LayoutXLM to learn more specific contextual information to improve extraction performance. Next, the associated entity detection module, RIFD-Net (relevant intra-layer fine-tuned detection network), identifies each test item’s location within the MER table body. Significantly, the backbone of RIFD-Net incorporates the intra-layer feature adjustment module (IFAM) to extract global features while homing in on local areas, proving especially sensitive for inspection tasks with dense and long bins. Finally, structured post-processing based on coordinate aggregation links the outputs from the prior stages. For the evaluation, we constructed the Chinese medical examination report dataset (CMERD), based on real medical scenarios. MSIE-Net demonstrated competitive performance in tasks involving key information extraction and associated entity detection. Experimental results validate MSIE-Net’s capability to successfully detect key entities in MER and table images with various complex layouts, perform entity relation extraction, and generate structured labels, laying the groundwork for intelligent medical documentation. Full article

In this study, full-scale laboratory tests were conducted on a 315 mm diameter HDPE pipe under shallow buried and localised surface loading conditions to investigate the effects of pipe deflection and arching on stress distribution and the lateral earth pressure coefficient. The tests were validated using 2D finite element software, and further analyses were carried out through parametric studies. These studies considered variations in pipe stiffness, burial depth, backfill properties and pavement stiffness to increase the reliability of the test results. For a shallowly buried HDPE pipe, a comprehensive explanation is provided regarding the evolution of the lateral earth pressure coefficient within the central soil prism. Initially set at Ko conditions, this coefficient tends to shift towards Kp with increasing arching and transitions to Ka with weakening arching. The findings suggest that stress predictions in the crown region of shallow buried flexible pipes are achievable through the application of Terzaghi’s arching theory, contingent upon an accurate estimation of the lateral earth pressure coefficient for the central soil prism. Furthermore, the horizontal deflection of the pipe at the springline results in compressive behaviour and passive effects in the surrounding backfill in this specific region. This situation demonstrates that the horizontal stresses at the springline and the lateral earth pressure coefficient can be reliably estimated by considering them as functions of the horizontal deflection of the pipe. Full article

The accurate prediction of soil contamination in abandoned mining areas is necessary to address their environmental risks. This study employed a combined model of machine learning and geostatistics to predict the spatial distribution of soil contamination using heavy metal data collected in an abandoned metal mine. An exploratory data analysis was used to identify patterns in the collected data, the root mean squared error (RMSE) and coefficient of determination (R²) were used to verify the predicted values, and the model was validated using K-fold cross-validation. The prediction results were produced as a map by applying hyperparameter tuning to Random Forest (RF) and Ordinary Kriging (OK) through GridSearchCV using optimal parameter selections. Furthermore, the prediction residuals of the RF model were calculated, and the RF prediction map and OK interpolation results of the RF prediction residuals were summarized to construct an RF–OK prediction map. The RMSE and R² values for the RF, OK, and RF–OK interpolation models were 66.214, 65.101, and 52.884 mg/kg and 0.867, 0.871, and 0.915, respectively. In addition, the optimization results with the minimum RMSE and maximum R² were obtained through hyperparameter tuning. The proposed RF–OK hybrid model demonstrated superior prediction performance compared to the individual models. Full article

Floor mats are commonly used to improve the impact sound performance of existing homes, but actual impact sound reductions do not consistently appear, as they depend on the test-bed conditions used to determine impact sound performance. Therefore, this study evaluated the effects of the environmental conditions of the test bed on the impact sound reduction performances of different floor mats. The Korean industrial standard KS F 2865 specifies the measurement method in the test room and sets the thickness range of the available target floor structure to bare slabs with thicknesses ranging from 120 mm to 210 mm. The evaluation method is ∆L, which is the difference in standardized impact sound levels before and after the installation of the floor finishing material. In this study, a total of eight types of floor mats were tested in four different test beds according to KS F 2865. The impact sources used were tapping, bang machines, and a rubber ball, and we used these sources to consider both light-weight and heavy-weight impact sounds. The results were derived as the impact sound reduction performance for each frequency band and a single-number quantity. The results showed that light impact sound had a similar minimum reduction characteristic of at least 38 dB, regardless of the floor structure on which the mat was installed. However, the heavy-weight impact sound showed different tendencies depending on the floor mat and the characteristics of the floor structure of the test bed when a bang machine and a rubber ball were used. In particular, the reduction achieved by the bang machine showed less than half the tendency of the reduction by the rubber ball, and the tendency of the heavy-weight impact sound was shown to be reducible depending on how the floor mat was maintained, but the reductions differed depending on the test bed. The reductions were larger in the box-type test room than in the real-life-type test room, and among the box-type test rooms, the one with a thicker bare slab showed a relatively larger reduction. In addition, the reliability of the measurement results was evaluated through a correlation analysis between the single-number quantities depending on the thicknesses of the bare slabs of the test beds. Full article

Object detection in unmanned aerial vehicle (UAV) images has become a popular research topic in recent years. However, UAV images are captured from high altitudes with a large proportion of small objects and dense object regions, posing a significant challenge to small object detection. To solve this issue, we propose an efficient YOLOv7-UAV algorithm in which a low-level prediction head (P2) is added to detect small objects from the shallow feature map, and a deep-level prediction head (P5) is removed to reduce the effect of excessive down-sampling. Furthermore, we modify the bidirectional feature pyramid network (BiFPN) structure with a weighted cross-level connection to enhance the fusion effectiveness of multi-scale feature maps in UAV images. To mitigate the mismatch between the prediction box and ground-truth box, the SCYLLA-IoU (SIoU) function is employed in the regression loss to accelerate the training convergence process. Moreover, the proposed YOLOv7-UAV algorithm has been quantified and compiled in the Vitis-AI development environment and validated in terms of power consumption and hardware resources on the FPGA platform. The experiments show that the resource consumption of YOLOv7-UAV is reduced by 28%, the mAP is improved by 3.9% compared to YOLOv7, and the FPGA implementation improves the energy efficiency by 12 times compared to the GPU. Full article

Four-level pulse amplitude modulation (PAM4) can transmit more information in the same symbol interval, effectively improving the information transmission rate and frequency band utilization of visible light communication (VLC). This paper proposes a method for encoding and decoding the PAM4 signal based on FPGA. The PAM4 signal is studied and analyzed under different channel noise models. The research results show that the bit error rate (BER) performance of the PAM4 signal is the best under the additive noise model. The influence of the multiplicative noise on the BER of the PAM4 signal is much greater than that of the additive noise. The BER performance of the PAM4 signal depends on the variance of the noise data. The greater the variance, the worse the BER performance. At the same time, an indoor VLC system based on PAM4 is designed. The simulation results verify that the system scheme is feasible and provides a way to further realize high-speed signal transmission. Full article

Fourier ptychographic microscopy (FPM) is a computational imaging technology that has endless vitality and application potential in digital pathology. Colored pathological image analysis is the foundation of clinical diagnosis, basic research, and most biomedical problems. However, the current colorful FPM reconstruction methods are time-inefficient, resulting in poor image quality due to optical interference and reconstruction errors. This paper combines coloring and FPM to propose a self-supervised generative adversarial network (GAN) for FPM color reconstruction. We design a generator based on the efficient channel residual (ECR) block to adaptively obtain efficient cross-channel interaction information in a lightweight manner, and we introduce content-consistency loss to learn the high-frequency information of the image and improve the image quality of the staining. Furthermore, the effectiveness of our proposed method is demonstrated through objective indicators and visual evaluations. Full article

Paperboard boxes represent a sought-after class of packaging products, where the use of recycled fibers offers a cost-effective and environmentally friendly alternative to virgin fibers. The presence of a significant proportion of recycled fibers in the paperboard leads to a number of limitations associated with the deterioration of its characteristics. In this study, the properties of coated and uncoated paperboards containing recycled fibers, wood pulp, and virgin cellulose fibers were investigated using a laboratory sample of paperboard produced from 100% recycled fibers without any chemical additives for comparison. Properties such as smoothness, bulk density, absorbency, and tensile strength, as well as colorimetric characteristics, were determined for the recycled paperboards; for the latter test, charts were printed using inkjet printing and UV-curable inks. Whiteness was calculated by three formulae (CIE, Berger, and Stensby), and all the paperboards had a relatively low whiteness (not exceeding 90 CIE), with a yellowish tint due to recycled fibers and mechanical pulp in the composition. The absence of optical brightening agents in the paperboards was experimentally confirmed. The color gamuts of the paperboards were in direct ratio to their whiteness, with the highest ones demonstrated by the coated paperboards. Color reproduction, according to the tone value increase curves, also depended on the whiteness. Uncoated paperboards demonstrated smaller color shifts than the coated ones, with the greatest increase in tone for yellow color. Coated recycled paperboards are suitable for packaging printing under the same conditions as virgin fiber boards, while uncoated boards are the recommended choice for digital printing with UV inks. Full article

The objective of this study is an investigation of the influence of six different plastic packages (polyethylene terephthalate, high-density polyethylene, biodegradable high-density polyethylene, low-density polyethylene, polypropylene and polyamide polyethylene) on the migration of phthalate residues in smoked carp, trout and salmon stored at −18 °C for three and six months. Six phthalate residues concentrations were determined using the gas chromatography-mass spectrometry method. Diisobutyl phthalate (DIBP) and dibutyl phthalate (DBP) migrated the most into salmon meat from PAPE packaging after six months of storage, reaching 73.77 μg/kg and 78.45 μg/kg, respectively. The highest concentrations of bis(2-ethylhexyl) phthalate (DEHP) after six months of storage were present in salmon meat packed in polyamide polyethylene (253.56 μg/kg) and the lowest in carp meat packages in polypropylene (157.72 μg/kg). Phthalate residues in all the samples showed higher levels after three and six months of storage compared to the control sample. Among the investigated phthalates, polypropylene was the material with the lowest migration into fish meat. A further amount of DEHP migration in the fish was detected with a higher fat content. We acknowledge that levels of phthalates should be monitored, and research in this field should be continued, especially since there are no legal restrictions regarding the maximum level of phthalates in food. Full article

Faced with the challenges of global climate change, zero-carbon buildings (ZCB) serve as a crucial means to achieve carbon peak and carbon neutrality goals, particularly in the development of tropical island regions. This study aims to establish a ZCB technology system suitable for the unique climatic conditions of tropical islands. By employing methods such as energy flow boundaries, parametric design, and data-driven optimization algorithms, the research systematically analyzes the integrated mechanisms and optimization solutions for energy utilization, energy conservation, energy production, and intelligent systems. The study identifies and addresses key technical challenges faced by ZCB in tropical island regions, including the accurate identification of system design parameters, the precise quantification of the relationship between design parameters and building performance, and the comprehensive optimization of technical and economic goals for zero-carbon operational design solutions. The research results not only provide a comprehensive theoretical framework, promoting the development of architectural design theory, but also establish a practical framework for technology and methods, advancing the integration and application of ZCB technology. The study holds significant practical implications for the green transformation of the tropical island construction industry and the realization of national dual-carbon strategic goals. Future research should further explore the applicability of the technology system and the economic feasibility of optimized design solutions, promoting continuous innovation and development in ZCB technology. Full article

The influence of implant surface roughness on implant treatment outcome is still under debate. A rougher implant surface improves osseointegration but yields greater plaque accumulation and biofilm formation. Hybrid implants have a minimally rough component coronally and a moderately rough implant body. The aim of this split-mouth study is to evaluate the long-term outcome of treatment with hybrid and moderately rough implants after 6 years. As a secondary aim, Oral Health Quality of Life (OHQoL) was assessed after one and six years. Fully edentulous patients received an overdenture supported by two implants. One implant had a hybrid surface (MSC) and one implant had a moderately rough surface (DCC). Radiographic crestal bone loss (CBL), plaque score, bleeding on probing (BoP) and periodontal probing depth (PPD) were determined at one and six years. OHQoL was evaluated using the Oral Health Impact Profile-14 (OHIP-14) questionnaire and a Visual Analogue Scale (VAS). Twenty-one patients with 42 implants were evaluated after 6 years. No implants failed and a mean CBL of 0.26 mm (SD: 0.42) for the MSC group and 0.17 mm (SD: 0.29) for the DCC group was observed, which was not statistically significant. Periodontal parameters were comparable after 6 years and a significant improvement in OHQoL was observed. This randomized controlled trial concludes that hybrid implants are a predictable treatment alternative for moderately rough implants in patients with an overdenture supported by two implants. Full article

The dynagraph card plays a crucial role in evaluating oilfield pumping systems’ performance. Nevertheless, classifying dynagraph cards can be quite difficult because certain operating conditions may exhibit similar patterns. Conventional classification approaches mainly involve labor-intensive manual analysis of these cards, leading to subjectivity, prolonged processing times, and vulnerability to human prejudices. In response to this challenge, our study introduces a novel approach that leverages transfer learning and the Swin Transformer model for classifying dynagraph cards across various operating conditions in rod pumping systems. Initially, the Swin Transformer model undergoes pre-training using the ImageNet-22k dataset. Subsequently, we fine-tune the model’s weights using actual dynagraph card datasets, facilitating direct classification analysis with dynagraph cards as input variables. The adoption of transfer learning significantly reduces the training time while enhancing the accuracy of condition diagnosis. To assess the effectiveness of our proposed method, we conducted a comparative evaluation against conventional models like ResNet50, DenseNet121, LeNet, and ViT. The findings demonstrate that our approach outperforms other methods, achieving an accuracy of 96%, thereby improving classification accuracy by 3–4%. Therefore, our approach, based on transfer learning and the Swin Transformer model, provides a better solution for practical problems involving similar dynagraph cards. It meets the requirements of oil field operations, enhancing economic benefits and work efficiency. Full article

This study focuses on the surface modification of Ti₆Al₄V scaffolds produced through additive manufacturing using the Powder-Bed Fusion Electron-Beam Melting (PBF-EB) technique. From our perspective, this technique has the potential to enhance implant osseointegration, involving the growth of a layer of titanium dioxide nanotubes (TiO₂) on surfaces through anodic oxidation. Scaffolds with anodized surfaces were characterized, and the formation of a nanoporous and crystalline TiO₂ layer was confirmed. The analysis of cell morphology revealed that cells adhered to the anodized surfaces through their filopodia, which led to proliferation during the initial hours. However, it was observed that the adhesion of Saos-2 cells was lower on anodized scaffolds compared to both built and chemically polished scaffolds throughout the cell culture period. The results obtained here suggest that while anodic oxidation is effective in achieving a nanoporous surface, cell adhesion and interaction were affected by the weak adhesion of cell filopodia to the surface. Thus, combining surface treatment techniques to create micro- and nanopores may be an effective alternative for achieving a favorable cellular response when the objective is to enhance the performance of porous titanium scaffolds in the short term. Full article

The paper presents a model that aims to support the construction contractor in the process of construction workforce planning by verifying initial assumptions about the planned number of man-hours, determined using a widely available and widely used method. The construction of the mathematical labour planning model of was based on the fuzzy sets theory. As a result of the operation of the model, four detailed coefficients are obtained, which, after applying the weights of normalized groups of factors, allow to determine the overall result of the model. The model, by verifying the planned number of man-hours, directly influences the employment planning process at a construction site and also supports the scheduling of the overall progress of the works, making it assumedly closer to reality in terms of the involvement of employees as well as the execution time of the construction works. Full article

Fruit juices (FJ) have gained widespread global consumption, driven by their perceived health benefits. The accuracy of nutrition information is essential for consumers assessing FJ quality, especially with increasing concerns about added sugars and obesity risk. Conversely, ascorbic acid (Vitamin C), found in nature in many fruits and vegetables, is often lost due to its susceptibility to light, air, and heat, and it undergoes fortification during FJ production. Current analytical methods for determining FJ components are time-consuming and labor-intensive, prompting the need for rapid analytical tools. This study employed a field-deployable portable FT-IR device, requiring no sample preparation, to simultaneously predict multiple quality traits in 68 FJ samples from US markets. Using partial least square regression (PLSR) models, a strong correlation (R_CV ≥ 0.93) between FT-IR predictions and reference values was obtained, with a low standard error of prediction. Remarkably, 21% and 37% of FJs deviated from nutrition label values for sugars and ascorbic acid, respectively. Portable FT-IR devices offer non-destructive, simultaneous, simple, and high-throughput approaches for chemical profiling and real-time prediction of sugars and acid levels in FJs. Their handiness and ruggedness can provide food processors with a valuable “out-of-the-laboratory” analytical tool. Full article

Lossless coding is a compression method in the Versatile Video Coding (VVC) standard, which can compress video without distortion. Lossless coding has great application prospects in fields with high requirements for video quality. Since the current VVC standard is mainly designed for lossy coding, the compression efficiency of VVC lossless coding makes it hard to meet people’s needs. In order to improve the performance of VVC lossless coding, this paper proposes a sample-based intra-gradient edge detection and angular prediction (SGAP) method. SGAP utilizes the characteristics of lossless intra-coding to employ samples adjacent to the current sample as reference samples and performs prediction through sample iteration. SGAP aims to improve the prediction accuracy for edge regions, smooth regions and directional texture regions in images. Experimental results on the VVC Test Model (VTM) 12.3 reveal that SGAP achieves 7.31% bit-rate savings on average in VVC lossless intra-coding, while the encoding time is only increased by 5.4%. Compared with existing advanced sample-based intra-prediction methods, SGAP can provide significantly higher coding performance gain. Full article

Korean forests are highly vulnerable to forest fires, which can severely damage property and human life. This necessitates the establishment of a rapid response system and the construction of firebreaks to prevent the spread of fires and protect key facilities. The existing firebreak construction methods can be classified into prevention- and response-stage methods. In the prevention stage, the progression and spread of fire are delayed, while in the response stage, primitive manual methods involving tools such as hooks are used, in addition to aerial deployment of water and fire retardants through helicopters. Herein, we propose the use of “fire-extinguishing drones” for firebreak construction during the initial, low-intensity stage of a fire before the deployment of firefighting personnel. We implement a continuous fire-extinguishing module capable of carrying six fire-extinguishing balls to verify its deployment accuracy and stable hovering capabilities. Through the operation of multiple drones using a ground control system and real-time kinematics to precisely generate designated automatic flight paths, we conducted experiments to assess the feasibility of firebreak construction by using fire-extinguishing drones to prevent the spread of wildfires. A firebreak construction field test was conducted to evaluate the accuracy of continuous fire extinguisher deployment, hovering performance during deployment, accuracy of the RTK-designated paths, and GCS performance. The proposed system achieved 100% performance on all indicators, except the accuracy of the RTK-designated paths. Full article

Background: The main objective of this study was to compare the clinical efficacy of two different devices, the Eptamed elastodontic device and a common bite sold in pharmacies, by assessing a computer aid evaluation of patients’ surface electromyography (sEMG) and kinesiography activity of four pairs of masticatory and postural muscles (anterior temporalis, digastricus, masseters and sternocleidomastoids muscles) before and after 6 months of treatment. Materials and Methods: Twelve adult patients with temporomandibular disorders and in need of orthodontic treatment were enrolled in the study and divided into cases and controls. Cases underwent orthodontic treatment with the Eptamed elastodontic device, while controls were treated with a bite sold in pharmacies. Both groups underwent electromyographic and kinesiographic examinations before and after 6 months from the start of treatment. Results: The Eptamed device was found to guarantee an improvement in the electrical activity of the muscles examined. The subjects in the control group, on the other hand, had a general worsening of electrical activity after wearing a splint purchased in a pharmacy. As for the kinesiographic examination, there was no significant improvement in both groups. Conclusions: the use of the Eptamed device in subjects with TMD ensured a greater relaxation of the chewing muscles than a standard bite, effectively reducing the risk of worsening the symptomatology of temporomandibular disorders. Full article