Search Results (921)

As internal combustion engines (ICEs) develop towards higher explosion pressures and lower weights, their structures need to be more compact; thus, the wall thickness of their cylinder liners is reducing. However, intense vibrations in the cylinder liner can lead to coolant cavitation and, in severe cases, penetration of the liner, posing a significant reliability issue for ICEs. Therefore, research on cylinder liner cavitation has attracted increasing interest. Gray cast iron is widely used in cylinder liners for its hardness and wear resistance; however, additional surface plating is necessary to improve cavitation resistance. This study developed a novel surface-modification technology using electroless Ni-P plating combined with high-temperature heat treatment to create cylinder liners with refined grains, low weight loss rate, and high hardness. The heat-treatment temperature ranged from 100 to 600 °C. An ultrasonic cavitation tester was used to simulate severe cavitation conditions, and we analyzed and compared Ni-P-plated and heat-treated Ni-P-plated surfaces. The findings showed that the combination of Ni-P plating with high-temperature heat treatment led to smoother, more refined surface grains and the formation of cellular granular structures. After heat treatment, the plating structure converted from amorphous to crystalline. From 100 to 600 °C, the weight loss of specimens was within the range of 0.162% to 0.573%, and the weight loss (80.2% lower than the plated surface) and weight loss rate at 600 °C were the smallest. Additionally, cavitation resistance improved by 80.1%. The microhardness of the heat-treated plated surface reached 895 HV at 600 °C, constituting a 306 HV (65.8%) increase compared with that of the unplated surface, and a 560 HV increase compared with that of the maximum hardness of the plated surface without heat treatment of 335 HV, with an enhancement rate of 62.6%. Full article

Wound dehiscence is a rare complication after penetrating keratoplasty (PK) that may occur with or without prior trauma. Multiple factors may influence corneal wound healing, including patient factors, corneal wound characteristics, and other external factors. There is also the possibility that systemic medications could impact corneal wound healing. Possible factors that may predispose a cornea to experience wound dehiscence are discussed. We propose a hypothesis that oral angiotensin-inhibiting medications could play a role in reduced corneal wound healing. A literature review was conducted to investigate the effect of angiotensin inhibitors on corneal wound healing. Five patients on systemic oral angiotensin-inhibiting medications at the time of PK developed dehiscence of the graft–host wound junction following removal of sutures. The dehiscence required resuturing in all cases and resulted in an expulsive choroidal hemorrhage and complete loss of vision in one eye. Age, diabetes, lack of corneal neovascularization, early suture removal, underlying epithelial basement membrane dystrophy, corneal oedema, slower tapering of topical corticosteroid dosage, and glaucoma medication with preservatives were possible predisposing factors for some of these instances of wound dehiscence. However, oral angiotensin-inhibiting medications were taken by all patients in this series, and the literature suggests that ACE inhibitors and ARBs can reduce corneal fibrosis, resulting in inadequate healing. Oral angiotensin-inhibiting medications could have played an anti-fibrotic role in these corneae and predisposed them to wound dehiscence with minimal trauma. Despite limited evidence, these medications warrant further investigation as potential modulators of corneal wound healing. Full article

Bench-scale geological modeling is often uncertain due to limited exploration drilling and geophysical wireline measurements, reducing production efficiency. Measure-While-Drilling (MWD) systems collect drilling data to analyze mining blast hole drill rig performance. Early MWD studies focused on penetration rates to identify rock types. This paper investigates Artificial Intelligence (AI)-based regression models to predict geophysical signatures like density, gamma, magnetic susceptibility, resistivity, and hole diameter using MWD data. The machine learning (ML) models evaluated include Linear Regression (LR), Decision Trees (DTs), Support Vector Machines (SVMs), Random Forests (RFs), Gaussian Processes (GP), and Neural Networks (NNs). An analytical method was validated for accuracy, and a three-tier experimental method assessed the importance of MWD features, revealing no performance loss when excluding features with less than 2% importance. RF, DTs, and GPs outperformed other models, achieving R² values up to 0.98 with a low RMSE, while LR and SVMs showed lower accuracy. The NN’s performance improved with larger datasets. This study concludes that the DT, RF, and GP models excel in predicting geophysical signatures. While ML-based methods effectively model relationships in the data, their predictive performance remains inherently constrained by the underlying geological and physical mechanisms. Model selection depends on computational resources and application needs, offering valuable insights for real-time orebody analysis using AI. These findings could be invaluable to geologists who wish to utilize AI techniques for real-time orebody analysis and prediction. Full article

In urban road detection using Ground Penetrating Radar (GPR), challenges arise from complex and variable road structures and diversified detection environments. These unstable factors decrease GPR detection signal strength and cause signal shape distortion, negatively affecting detection accuracy. This reduces the interpretive accuracy of GPR images, impacting precise diagnosis of underground structures and hidden defects in urban roads. Therefore, understanding and overcoming these challenges is practically important for improving GPR performance and interpretive efficiency in urban road detection. To address these issues, this study proposes an innovative strategy using unsupervised learning for GPR image restoration. Specifically, it utilizes the Cycle-Consistent Adversarial Network (CycleGAN) with the Convolutional Block Attention Module (CBAM) generator and integrates the Multi-Scale Structural Similarity Index (MS-SSIM) loss function to enhance restoration quality. The method is trained and validated using field experimentally collected datasets with and without road surface interference, and the performance is evaluated through qualitative and quantitative analysis of restored GPR B-scan images. The experimental results show that the proposed method improves image restoration by 4.9% in SSIM, 39.15% in PSNR, and 76.88% in MAE, confirming its significant effect in GPR image restoration. Full article

The durability of marine structures in the northern coastal areas is significantly damaged due to the double deterioration of chloride salt and freeze–thaw, and adding fiber can effectively improve the durability of marine structures. This work investigated the influence of polypropylene fiber content and salt freezing cycles on the flexural strength and durability of high-performance concrete through salt freezing cycle tests. The main experimental methods used included four-point load bending tests, relative dynamic elastic modulus tests, mass loss rate tests, and chloride ion permeability tests, with the mechanisms analyzed using SEM. The results indicated that an appropriate amount of polypropylene fibers significantly enhanced the flexural strength and durability of high-performance concrete. At a fiber content of 0.9 kg/m³, the concrete achieved the highest flexural strength. However, when the fiber content exceeded 0.9 kg/m³, excessive fibers caused uneven distribution and formed clusters, which reduced the flexural strength. At a fiber content of 1.2 kg/m³, the high-performance concrete showed optimal resistance to salt freezing and chloride ion permeability. However, exceeding this fiber content increased the concrete’s porosity, allowing harmful substances like chloride ions to penetrate more easily, thereby accelerating degradation under freeze–thaw conditions. This study contributes to a broader understanding of the durability of marine structures in coastal northern regions and provides theoretical data support for such environments. Full article

To address the challenges of micro-fracture development in shale formations, frequent wellbore instability, and the limited plugging capability of water-based drilling fluids in unconventional reservoirs, a nano-plugging agent (NPA) was synthesized using emulsion polymerization. The synthesized NPA was characterized through thermogravimetric analysis (TGA) and transmission electron microscopy (TEM), revealing excellent high-temperature stability and a spherical or sub-spherical morphology, with particle diameters ranging from approximately 20 to 50 nm. The rheological, filtration, and plugging properties of NPA were systematically evaluated, and its sealing mechanism was analyzed. The results demonstrate that at a test temperature of 180 °C, the optimal NPA concentration in the drilling fluid base slurry is 1.5%, achieving a 60.5% reduction in HTHP (high-temperature high-pressure) sand disc filtration loss. Additionally, the API filtration loss and HTHP filtration loss reduction rates reached 58.1% and 50.3%, respectively, highlighting the remarkable filtration loss reduction and plugging efficiency of NPA under high-temperature conditions. After NPA treatment, the specific surface area and pore volume of shale cuttings decreased to 9.348 m²/g and 0.035 cm³/g, respectively, indicating effective surface plugging. The mechanism analysis suggests that due to its nanoscale size, NPA can penetrate deep into micro-pores and fractures within the shale, achieving deep-layer plugging. Furthermore, NPA forms a physical plugging barrier on the shale surface, effectively suppressing shale hydration and swelling. This study provides valuable insights and guidance for addressing wellbore instability and the insufficient plugging performance of drilling fluids in unconventional reservoir drilling operations. Full article

Battery energy storage systems (BESSs) can play a significant role in overcoming the challenges in Distribution Systems (DSs) with a high level of penetration from renewable energy sources (RESs). In this paper, the goal is to determine the optimal location, size, and charging/discharging dispatches of BESSs in DSs with a high level of photovoltaic (PV) installations. The problem of the location and size of BESSs is solved with multi-criteria optimization using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The criteria of the multi-criteria optimization are minimal investment costs for BESS and improvement of the network performance index. The network performance index includes the reduction in annual losses of active energy in DSs and the minimization of voltage deviations. The dispatch of a BESS is determined using auxiliary optimization. Linear Programming (LP) is used for auxiliary optimization, with the aim of dispatching the BESS to smooth the load profile in DS. The proposed optimization method differs from previous studies because it takes in its calculations all days of the year. This was performed using the K-means clustering technique. The days of one year are classified by the level of consumption and PV production. The optimization was performed for five different levels of PV penetration (60%, 70%, 80%, 90%, and 100%) and for two scenarios: the first with one BESS and the second with two BESSs. The proposed methodology is applied to the IEEE 33 bus balanced radial distribution system. The results demonstrate that with an optimal choice of location and parameters of the BESS, significant improvement in network performance is achieved. This refers to a reduction in losses of active power, improvement of voltage profile, smoothing the load diagram, and reducing the peak load. For the scenario with one BESS and PV penetration of 100%, the reduction in daily energy losses reaches a value of up to 10% compared to the base case (case without a BESS). The reduction in peak load goes to 20%. Further, the highest voltage during the day is significantly lower in all buses compared to the base case. Similarly, the lowest voltage during the day is considerably higher. The methodology from this paper can be applied to any radial distribution network with a variable number of BESSs. The testing results confirm the effectiveness of the proposed method. Full article

The pylon has been identified as a highly promising method for enhancing mixing efficiency in scramjet combustors. This work systematically assessed the impact of spanwise, streamwise, and oblique multi-pylon combinations in a supersonic cold flow through numerical simulations, employing pylon-aided ethylene fuel injection under low dynamic pressure conditions. The Reynolds-averaged Navier–Stokes (RANS) equations with the SST k-ω turbulence model are applied during the simulation. Numerical results reveal that, in comparison to the streamwise combination, the spanwise combination exhibits superior flow field characteristics in terms of mixing efficiency, penetration depth, and total pressure loss. For a given injection condition, an optimal distance between pylons exists in the spanwise combination, with the angle between two pylons having minimal influence on mixing efficiency. The oblique multi-pylon combination yields poorer mixing enhancement efficiency and fuel penetration but incurs less total pressure loss in the near field when compared to the spanwise combination. Additionally, the oblique multi-pylon combination demonstrates enhanced mixing efficiency further downstream of the injector than the spanwise combination. This investigation into fuel injection schemes based on multi-pylon combinations offers valuable insights for the structural design of scramjet engines. Full article

Nanoemulsions are significant for cosmetic products intended for skin care and for health products due to the reduced size (range 20 to 500 nm) of the globules, which avoids processes of instability. They present transparency, fluidity, wettability, and spreadability; increase skin penetration; and have good sensation. The main instability mechanism of nanoemulsions is called Ostwald ripening, responsible for increasing the average diameter of emulsion globules. Sesame Seed Oil (SO) and Raspberry Seed Oil (RO) are indicated as moisturizing agents recently used in the cosmetic industry and for reducing transepidermal water loss, preventing damage to the skin barrier. They contain specific compounds with common properties such as antioxidant, moisturizing, emollient, and photoprotective actions, making them attractive alternative and complementary treatments to soften the process of skin aging. Below, we present the results of this research on the development of nanoemulsions containing Sesame Seed Oil added with Raspberry Seed Oil by the low-energy method. SO nanoemulsions at HLB = 8.0 were obtained with PEG 15 castor oil (A) and PEG 30 castor oil (F.80) and had globule sizes of 50 nm and 200 nm, respectively, along with pH values considered suitable for skin care products and lower viscosity values allowing for the easy application of nanoemulsions to the skin. Nanoemulsions A and F.80 showed antioxidant activities of 68.71% and 67.75%, respectively. SO nanoemulsions with PEG 15 and PEG 30 castor oil were obtained at 85 °C and 75 °C, respectively, and have the lowest Ostwald ripening index (1.33 × 10²² m³ s⁻¹). The in vitro evaluation conducted using the HET-CAM method for nanoemulsions and PEG 15 and PEG 30 castor oils showed that they were slightly irritating and could be used in cosmetic products. Full article

The aquatic plant species Eichhornia crassipes, commonly known as water hyacinth, is indigenous to South America and is considered an invasive species. The invasive water hyacinth has caused significant economic and ecological damage by preventing sunlight from penetrating the surface of the water, resulting in the loss of aquatic life. To quantify the invasiveness and address the issue of accurately identifying plant species, water hyacinths have prompted numerous researchers to propose approaches to detect regions occupied by water hyacinths. One such solution involves the utilization of multispectral imaging which obtain detailed information about plant species based on the surface reflectance index. This is achieved by analyzing the intensity of light spectra at different wavelengths emitted by each plant. However, the use of multispectral imagery presents a potential challenge since there are various spectral indices that can be used to capture different information. Despite the high accuracy of these multispectral images, there remains a possibility that plants similar to water hyacinths may be misclassified if the right spectral index is not chosen. Considering this challenge, the objective of this research is to develop a low-cost multispectral camera capable of capturing multispectral images. The camera will be equipped with two infrared light spectrum filters with wavelengths of 720 and 850 nanometers, respectively, as well as red, blue, and green light spectrum filters. Additionally, the implementation of the U-Net architecture is proposed for semantic segmentation to accurately identify water hyacinths, as well as other classes such as lakes and land. An accuracy rate of 96% was obtained for the identification of water hyacinths using data captured by an autonomous drone constructed in the laboratory flying at an altitude of 10 m. We also analyzed the contribution each of the infrared layers to the camera’s spectrum setup. Full article

Background/Objectives: Hair loss (alopecia or effluvium) can significantly affect the self-esteem and psychosocial well-being of patients, resulting in a reduced quality of life. It may herald a systemic disease, nutritional deficiency, or side effects of pharmacotherapy. Current therapeutic options for hair loss are not always satisfactory and may be associated with considerable side effects; therefore, new solutions are still sought. Caffeine seems to be an effective agent against hair loss thanks to its stimulating effects on cell growth and good penetration into the hair follicle. The aim of this study was to systematically review published clinical trials of topical caffeine preparations against hair loss. Methods: We searched PubMed, Scopus, and Web of Science for clinical trials investigating the efficacy of topical caffeine products in hair loss, published until 29 November 2024. The quality of evidence was assessed using the GRADE classification. Results: The query returned 1121 articles, of which 9 ultimately met the inclusion criteria. In total, 684 people with androgenetic alopecia, excessive hair loss, or hair thinning were included in these trials. In all studies, conclusions were in favor of topical caffeine treatment; however, the level of scientific evidence was medium in 3 studies, low in 1, and very low in the remaining 5. Their major flaws included the lack of randomization and placebo and control groups, as well as the lack of information on the caffeine concentration in the topical products. Conclusions: Results from studies published to date suggest that topical caffeine preparations are safe and effective against hair loss. Nevertheless, better-designed clinical trials of well-defined caffeine products are required for an ultimate statement. Commercial hair products with caffeine offered on the market nowadays may be worth a try, but due to incomplete scientific data and product information, satisfactory outcomes are not guaranteed. Full article

The demand for electricity in Albania has risen significantly in recent years, accompanied by a growing emphasis on sustainable and environmentally friendly development. As a result, the focus of electricity generation is increasingly shifting towards renewable sources, particularly solar energy. In recent years, several large-scale solar plants have been installed across the country. This research examines four different scenarios and evaluates various technical parameters related to electrical power quality to assess the effects of integrating solar plants into the power system. Specifically, the analysis focuses on the active power losses and voltage fluctuations in the electrical distribution network following the connection of solar plants through the main distribution grid. Simulations were conducted using the Electrical Transient Analyzer Program (ETAP) software platform. The results suggest that a substantial penetration of solar energy into the grid may lead to increased losses in both active and reactive power. Full article

Flexible pavements stand out as the most commonly used worldwide, compared to rigid and composite pavements, owing to their versatility and widespread application. The use of hot mix asphalt (HMA) in flexible pavements causes significant environmental concerns due to high CO₂ emissions and energy consumption, whereas warm mix asphalt (WMA) technologies have gained popularity in recent decades, offering a more sustainable alternative by enabling asphalt production at lower temperatures. WMA technologies can be categorized into three main groups: foaming, organic additives, and chemical additives, with each offering distinct benefits for performance and environmental impact. One of the chemical additives used in WMA production is Cecabase RT BIO10. In this study, virgin bitumen with 50/70 penetration was modified by adding Cecabase RT BIO10 at four levels: 0%, 0.3%, 0.4%, and 0.5% by weight. The experimental design employed a Taguchi L16 orthogonal array to systematically evaluate the effects of various factors on modified bitumen performance. Binders were prepared at four temperatures (110 °C, 120 °C, 130 °C, and 140 °C), four mixing durations (15, 20, 25, and 30 min), and four mixing speeds (1000, 2000, 3000, and 4000 rpm), enabling an efficient analysis of each parameter’s impact. The prepared binders were subjected to a series of tests, including penetration, softening point, flash point, rotational thin film oven test (RTFOT), elastic recovery, Marshall stability, ultrasonic pulse velocity (UPV), and FTIR analysis. These tests were conducted to investigate the effects of various parameters and levels on the binder properties. Additionally, stiffness and seismic modules were evaluated to provide a more comprehensive understanding of the binder’s performance. The experiment results revealed that the penetration, elastic recovery percentage, and Marshall stability increased with increasing additive content while the softening point and RTFOT mass loss decreased. At a high service temperature of 40 °C, the stiffness modulus of the modified bitumen decreased slightly. At a low service temperature of −10 °C, it decreased further. Additionally, the incorporation of Cecabase RT BIO10 led to an increase in the seismic modulus. Through optimization using the Taguchi method, the optimal levels were determined to be a 0.4% Cecabase RT BIO10 ratio, 140 °C mixing temperature, 30 min mixing time, and 1000 RPM mixing speed. The optimal responses for each test were identified and integrated into a unified optimal response, resulting in a comprehensive design guide with 95% confidence level estimates for all possible level combinations. Full article

Currently, the electrical supply in stand-alone systems is usually composed of renewable sources with fossil-fuel generators and battery storage. This study shows a novel model for the metaheuristic–stochastic optimization (minimization of the net present cost, and NPC) of sizing and energy management for stand-alone photovoltaic (PV)–wind–diesel systems with hybrid pumped hydro storage (PHS)–battery storage systems. The model is implemented in C++ programming language. To optimize operations—thus reducing PHS losses and increasing battery lifetimes—optimal energy management can optimize the power limits of using the PHS or battery to supply or store energy. The probabilistic approach considers the variability of wind speed, irradiation, temperature, load, and diesel fuel price inflation. The variable efficiencies of the components and losses and advanced models for battery degradation are considered. This methodology was applied to Graciosa Island (Portugal), showing that, compared with the current system, the optimal system (with a much higher renewable power and a hybrid PHS–battery storage) can reduce the NPC by half, reduce life cycle emissions to 14%, expand renewable penetration to 96%, and reduce the reserve capacity shortage to zero. Full article

The grey mould fungus Botrytis cinerea is a dangerous plant pathogen responsible for substantial agricultural losses worldwide. The pathogenic mechanisms still have many unclear aspects, and numerous new pathogenic genes remain to be identified. Here, we show that the sterol regulatory element-binding protein Sre1 plays an important role in the development and pathogenicity of B. cinerea. We identified a homologue of gene SRE1 in the B. cinerea genome and utilized a reverse genetics approach to create the knockout mutant Δsre1. Our results demonstrate that SRE1 is essential for conidiation, as Δsre1 produced only 3% of the conidia compared to the wild-type strain. Conversely, Δsre1 exhibited increased sclerotium production, indicating a negative regulatory role of SRE1 in sclerotium formation. Furthermore, ergosterol biosynthesis was significantly reduced in the Δsre1 mutant, correlating with increased sensitivity to low-oxygen conditions. Pathogenicity assays revealed that Δsre1 had significantly reduced virulence, although it maintained normal infection cushion formation and penetration capabilities. Additionally, SRE1 was found to be crucial for hypoxia adaptation, as Δsre1 showed abnormal germination and reduced growth under low-oxygen conditions. These findings suggest that SRE1 mediates the development and pathogenicity of B. cinerea by regulating lipid homeostasis and facilitating adaptation to host tissue environments. Full article