Macro Images Research Articles

Introduction Teledermatology, which utilizes communication technologies to remotely assess skin lesions, has become a vital tool in healthcare. This study aimed to compare the diagnostic accuracy of teledermatology versus face-to-face examination and explore factors influencing accuracy, such as teledermatoscopy use, dermatoscopy type, and clinical experience. Methods Fifty-seven cutaneous tumors were evaluated using handheld or digital dermatoscopy in face-to-face examinations, and preliminary diagnoses were recorded. A definitive diagnosis was established through histopathological examination, which served as the reference standard. Macro and dermatoscopic images were then sent to six teledermatologists for remote diagnosis, and findings were analyzed statistically. Results The preliminary diagnosis matched the histopathological diagnosis in 84.2% of face-to-face cases. Teledermatologists achieved 63.7% accuracy with macro images alone, increasing to 70.8% with dermatoscopic images. Teledermatology showed lower accuracy than face-to-face examination, regardless of whether teledermatoscopy was used (p < 0.05), but accuracy significantly improved with dermatoscopic images (p = 0.004). The teledermatology’s accuracy for malignancy prediction was comparable to face-to-face examination (p > 0.05). Dermatoscopy type did not significantly impact accuracy (p > 0.05), while longer clinical experience correlated with higher accuracy (p < 0.05). Interrater reliability was poor for specific diagnoses but improved when categorizing lesions as malignant or benign (κ = 0.192, κ = 0.683). Conclusion Although teledermatology performed below face-to-face examination in terms of specific diagnoses, it remained effective in distinguishing between benign and malignant cutaneous tumors. The inclusion of teledermatoscopy and longer clinical experience enhanced diagnostic accuracy.

BackgroundThis in vitro study assessed the influence of using two types of fiber-reinforced composite with different placement methods on the flexural strength of two resin materials.MethodsSpecimens were fabricated using two FRC products (QUARTZ SPLINT® UD(UD) / WOVEN (WO)) with two resin composites (BEAUTIFIL II (BT II) and BEAUTIFIL Flow Plus (BF+)). Seven placements were employed to prepare specimens for each composite, including one control group without FRCs, two using UD, and the other four using WO. Specimens were prepared for flexural strength testing to evaluate the mechanical properties. Fracture mode was examined by dividing it into three categories. Three-way ANOVA and Tucky’ HSD test was performed (α = 0.05), with macro images and scanning electron microscope (SEM) micrographs analyzed.ResultsIn comparison to the control group, experimental groups utilizing BEAUTIFIL II (BT II) and BEAUTIFIL Flow Plus (BF+) with FRCs showed higher flexural strength (116.80 ± 11.45 MPa/107.02 ± 13.68 MPa and 302.06 ± 89.00 MPa/358.16 ± 96.10 MPa, respectively) (p < 0.05). Three-way ANOVA revealed that the flexural strength values were significantly affected by different resin composites, placing methods and fiber orientation respectively (p < 0.001).ConclusionsFRCs can be used as a reinforcing material for resin composites in a simulation of direct restoration. In some situations, the use of FRCs avoided complete fracture. The placement of FRCs and the composite used could be considered when applied clinically.Clinical trial numberNot applicable.

The order Pezizales (Ascomycota) consists of cup and truffle fungi growing in a wide range of habitats and geographical zones worldwide, exhibiting diverse nutritional behaviors. In Israel, morphological studies have designated most Pezizales as saprotrophs. We re-screened Pezizales mushrooms collected in northern Israel between 2020–2022 using molecular tools based on DNA sequences of partial large subunit rRNA (28S), internal transcribed spacer (ITS), and partial heat shock protein (Hsp90) regions, along with macro images of each freshly collected samples. Trophic mode was determined through available literature and δ13C and δ15N stable isotope analysis along with a quadratic discriminator analysis (QDA) model to predict trophic modes: 112 collections were positively identified with identification of 23 genera; 23 taxa were resolved to the species level, 11 to approximate species, and 15 to the genus level. Helvella was the most species-rich genus; 25 species and species approximations were newly reported for Israel. Further molecular phylogenetic studies are needed to resolve species identity of the Israeli Pezizales. Most Pezizales collections were determined by trophic mode studies to be ectomycorrhizal, with a few saprotrophs. The QDA model yielded several samples with undefined nutritional behavior or a different trophic mode than previously inferred, suggesting that more in-depth study is needed to understand their trophic ecology. This study improves knowledge regarding species diversity, ecology, and evolution of Israeli Pezizales.

Background Postoperative infection and rejection of miniplates in maxillofacial surgery are linked to surface irregularities and bacterial adhesion. This study investigated the physical and microbiological characteristics of patient-rejected miniplates to elucidate factors contributing to implant failure. Methods Forty miniplates, including straight-type BSSO and L-shaped designs, were collected from patients. Macro photography documented surface deformities. Contact angle measurements assessed surface wettability. Bacterial adhesion for Staphylococcus aureus, Streptococcus mutans, Pseudomonas aeruginosa, and Enterococcus faecalis was quantified via the crystal violet assay. Scanning electron microscopy (SEM) was used to visualize microbial colonization. Results Macro images showed visible deformations, especially in the bridge areas of straight-type BSSO plates. Contact angle analysis revealed significantly greater hydrophobicity in rejected plates than controls (mean: 89.6° vs. 72.3°, p &lt; 0.01). Rejected plates demonstrated significantly increased adhesion of S. aureus and S. mutans (p &lt; 0.001), particularly on mandibular plates. P. aeruginosa adhered more to control plates (p &lt; 0.05), while E. faecalis showed no significant difference between groups. SEM confirmed dense bacterial clusters, with S. aureus forming cocci aggregates and S. mutans forming chains, particularly in regions of surface distortion. Conclusion Rejected miniplates exhibit increased surface roughness and hydrophobicity, correlating with elevated bacterial adhesion. These findings highlight the need for improved surface design or coating technologies to reduce biofilm formation and enhance clinical outcomes in maxillofacial surgery.

In this study, as the first welding process, GTAW (Gas Tungsten Arc Welding) welding process was carried out on 9.53 mm thick A 333 Gr.6 pipe and A350LF-2 flange steels using 2.4 mm ER70S-6 electrode and SMAW (Manual Arc Welding) welding process was carried out using 2.5 mm E 7018-1 electrode for filler and cover passes. As the second welding process, GTAW welding process was carried out on 5.49 mm thick A 333 Gr.6 pipe and A350LF-2 flange steels using 2.4 mm ER70S-6 electrode and SMAW welding process was carried out using 2.5 mm E 7018-1 electrode for filler and cover passes. Post-weld heat treatment was applied during the first welding process. No post-weld heat treatment was applied during the second welding process. The effect of heat treatment on some mechanical properties of the materials and the changes that occur after stress relief were investigated for the welds made with the same materials, the same electrodes, the same welding methods but with different thicknesses. Tensile test, bending test, hardness test, notch impact test was performed as mechanical tests of the welded parts, macro images were taken and comparisons were made. As a result, the effects on the weld quality were investigated and results indicate that welding processes were successfully carried out with given filler electrodes and steel pipes.

The study focussed on the explosive welding of DP1000 steel and Al sheets. Secondarily, the punching of these sheets with various tips was performed, analysed and the cut surfaces were visually inspected (using electron and stereo microscopy). Moreover, a three-dimensional finite element modeling (FEM) analysis was conducted to predict the punching process of the welded sheet metal specimen. Additionally, the metal plate was subjected to a tensile test with the objective of obtaining data on its strength and ductility. DP1000-Al sheets can be welded successfully. The strength values of the composite (668 MPa) are lower than those of DP1000 but significantly higher than the Al sheet, showing that the composite has the properties of both materials. The cutting forces were reduced by 54.5%, 57%, 62%, and 72%, respectively, when the V16, R1, R2, and 16 punches were employed instead of the flat tip punch (P0). Reduced cutting force supports the laminate stability. The study of macro and micro images proved useful in understanding the surfaces and areas created by the cutting process. The findings of this study have the potential to establish a foundation for subsequent research, particularly concerning the implementation of sophisticated FEM and machine learning methodologies.

The study analysed the absorption and void content of CTCS mixtures with two cement types (CP II-F 32 and CP IV 32 RS) and binder levels (3% and 5%) to evaluate the impact of cement type on porosity. The results indicated that replacing CP II-F 32 cement with CP IV 32 RS cement leads to mixtures that are less porous, more compact, and with stronger bonds between mortar and aggregate. The macro and microstructure images corroborated the results obtained. Complementary analyses of the mechanical behavior of the mixtures showed that mixtures with CP IV had higher strengths and stiffnesses compared to mixtures with the same CP II cement content, indicating a better performance of mixtures with cement containing a high content of pozzolanic material. Factorial models highlighted a strong correlation between porosity and mechanical properties, demonstrating that reduced absorption and void indices result in higher performance.

In this study, two different pipe welding processes were carried out. In the first welding process, root and hot passes were made using A 312 TP 316L stainless steel and A106 Gr.B carbon steel materials with GTAW (Gas Tungsten Arc Welding) welding method and 2.4 mm ER309L electrode, and 2.5 mm with SMAW (Manual Arc Welding) welding method. Filling and cover passes were performed using the E309L-15 electrode. In the second welding process, A 312 TP 316L stainless steel and A106 Gr.B carbon steel materials were welded with GTAW method using 2.4 mm INCONEL 82 (ER NiCr-3) electrode for root and hot passes, welded with SMAW method with 2.5 mm INCONEL 182 (E NiCrFe-3) electrode for filling and cover passes. As mechanical tests of the obtained welded parts, tensile test, bending test, hardness test and PMI (Positive Material Identification) test were performed, macro images were taken and comparisons were made. As a result, the weldability of stainless and carbon steels with different filler metals and their effects on mechanical properties were examined.

Aluminum alloys are known for their wide application in the automotive, river and marine boat constructions, but also in hydraulic systems (radiators/oil coolers). Their use is made by manufacturing parts directly from the semi-finished state, with or without certain volumetric heat treatments and surface hardening, depending on the functional role and the physical-mechanical characteristics pursued. Some of these parts work in hydrodynamic conditions, where cavitation manifests itself through erosion, such as: propellers of boats and barges, pump rotors in water cooling systems of automobiles. Visual analyzes performed on sailboat and powerboat propellers, after identical durations and operating conditions, showed cavitation erosion damage, different depending on the type of aluminum alloy. As a result, the paper presents and analyzes the behavior and resistance to erosion by vibratory cavitation of 4 types of aluminum alloys in the state of rolled semi-finished products. To highlight the differences in the destruction of structures under the cyclic stresses of cavitational microjets, macro and microscopic images of the eroded structure are used, as well as the curves with the values of the parameters specific to cavitation, recommended by the ASTM G32 -2016 norms and used in the research laboratory's custom. The analysis of the results shows that the resistance of the structure to cavitation erosion is dependent on the type of alloy, the degree of brittle intermetallic compounds and the mechanical properties specific to toughness.

Over the years, research in the field of cultural heritage preservation and document analysis has exponentially grown. In this study, we propose an advanced approach for non-destructive estimation of paper fibers using macro images. Expanding on studies that implemented EfficientNet-B0, we explore the effectiveness of six other deep learning networks, including DenseNet-201, DarkNet-53, Inception-v3, Xception, Inception-ResNet-v2, and NASNet-Large, in conjunction with enlarged patch sizes. We experimentally classified three types of paper fibers, namely, kozo, mitsumata, and gampi. During the experiments, patch sizes of 500, 750, and 1000 pixels were evaluated and their impact on classification accuracy was analyzed. The experiments demonstrated that Inception-ResNet-v2 with 1000-pixel patches achieved the highest patch classification accuracy of 82.7%, whereas Xception with 750-pixel patches exhibited the best macro-image-based fiber estimation performance at 84.9%. Additionally, we assessed the efficacy of the method for images containing text, observing consistent improvements in the case of larger patch sizes. However, limitations exist in background patch availability for text-heavy images. This comprehensive evaluation of network architectures and patch sizes can significantly advance the field of non-destructive paper analysis, offering valuable insights into future developments in historical document examination and conservation science.

Simulation analysis and quantitative approaches have become very important in the foundry industry to improve product quality and minimize defects. This study aims to analyze macro defects, particularly porosity, in ashtray patterns produced through sand casting. A quantitative approach was used to identify and evaluate macro defects in the castings by utilizing 3D simulation techniques. This process involves taking macro images of the molded samples and then processing them to determine the porosity level. The porosity evaluation was carried out by comparing the simulation results with experimental data, thus enabling a more in-depth understanding of the factors affecting casting quality. The results of this study show the porosity formed by 3-dimensional simulation and the porosity percentage derived from statistical interpretation of macro photographs of sand casting materials. The findings are expected to make a meaningful contribution to the foundry industry, particularly in the effort to improve product quality through process optimization. This study also highlights the importance of quantitative and simulation approaches in analyzing and predicting casting defects, which can ultimately reduce production costs and improve product yield.

Abstract In the UK the incidence of skin cancer has increased by 26.1% since 2013, with 225 000 cases diagnosed in 2019. In response to the rising demand we must adapt our service pathways to ensure patients have a reliable, responsive service that meets the National Health Service Faster Diagnosis Standard. Prior to adapting our service, we had 600–900 referrals per month, with an increasing backlog of patients who were waiting to be seen, missing the 14-day target. For several years, an effective collaborative partnership with our plastic surgery colleagues has greatly improved our skin cancer service; patients were seen face to face, with dermatology and plastic surgery consultants working side by side in a polyclinic format. Despite this, the pressure on services still resulted in a backlog, with only 0.7% of referrals seen within 14 days in July 2023. In July, we introduced a teledermatology service to run in tandem to our face-to-face service; this allowed for increased capacity and also improved our referral response times. There are several exclusion criteria for our new pathway. If a general practitioner refers a lesion with a high level of concern for malignancy, if the patient is over 85 years old, or if there are multiple lesions, patients are assessed face to face; the remainder are reviewed via teledermatology. Within 7 days of referral, the patient is assessed face to face by an experienced dermatology healthcare assistant. They complete a skin cancer assessment and take macro and dermoscopic images of the lesion. This information is uploaded onto our electronic medical record and reviewed by a consultant within 5 days. If the lesion is concerning for malignancy or the diagnosis is unclear, patients are booked for face-to-face review within 14 days. The patient can also be directly listed for surgery; for those directly listed, they are sent a letter with our minor surgery patient leaflet and offered a face-to-face appointment prior to their procedure only if they desire. For benign lesions, the patient is discharged directly following teledermatology review. Our system has been designed to be flexible; if it is felt there are other lesions of concern by the healthcare authority, or if there is insufficient information or subquality images, the patient can be easily and quickly transferred to a face-to-face review. Within 6 months, we are now seeing over 95% of our referrals within 14 days. Our data demonstrate that by adapting our service and introducing a teledermatology pathway, we have significantly improved time from referral to assessment and improved the experience for patients. We aim to continually improve and adapt the service, adjusting it as needed with service demand.

Abstract Mole mapping is an effective way to facilitate the early detection of melanoma in high-risk patients with multiple and/or atypical naevi. Current UK guidance recommends baseline photography (preferably dermoscopic) and clinical review for monitoring [National Institute for Health and Care Excellence. Assessing melanoma. Available at: https://www.nice.org.uk/guidance/ng14/chapter/Recommendations#assessingmelanoma (last accessed 20 March 2024)]. Our aim was to evaluate the use of a mole-mapping device with artificial intelligence (AI) in our National Health Service specialist pigmented lesion clinic and to compare this to standard medical photography. We carried out a pilot in January 2023 comparing our current photography software, Medical Image Manager (MIM), to the Canfield IntelliStudio Gen3 with DermaGraphix® (Canfield Imaging Systems, Fairfield, NJ, USA). The IntelliStudio combines a semiautomated photoacquisition system with mole-tracking software, allowing linked comparison of two-dimensional macro and dermoscopic images. The software flags new or changed lesions, and AI known as DExI version 1.0 (Dermatology Explained Intelligence) risk stratifies lesions as low or high risk for malignancy. The technology was assessed on its efficiency of use, its ability to identify new or changed naevi, and the accuracy of DExI. Twelve patients with multiple and/or atypical naevi were recruited: seven had multiple visits and eight had images captured with both the IntelliStudio and standard photography by the clinical photography team. On average DermaGraphix® was 5.4 times faster (P = 0.03) and needed 54% fewer clicks per lesion (P = 0.02) compared with MIM to assess all marked naevi, macro and dermoscopically. Consultants identified lesions for dermoscopy ranging from 2 to 32 per patient (mean 11.9). The number of lesions per patient identified by DermaGraphix® ranged from 152 to 2721 (mean 700) and naevi counts ranged from 45 to 749 (mean 255). The software flagged a few new and changed lesions in most patients with follow-up images. The toggle function allowed these to be rapidly identified as either benign inflammatory lesions or false positives, mainly attributable to variable body positioning and artefacts such as clothing. DExI identified 13 lesions as high risk for malignancy, 5 of which scored as low risk on another visit. These lesions were reviewed by dermatologists; all were clinically stable and benign. In conclusion, the IntelliStudio was considered a time-efficient and user-friendly system. A key benefit is the linking of dermoscopic images to the body map using automated markerless tracking, viewed on a single-page dashboard. Specialists can rapidly compare sequential images using the toggle function. Although this pilot suggests that DExI is not yet clinically reliable, a newer version is now available. We conclude that the IntelliStudio is a superior mole-mapping system compared with MIM for monitoring high-risk patients in a tertiary pigmented lesion clinic.

Abstract There is increasing demand for artificial intelligence (AI) tools to manage skin cancer; however, there is minimal diversity in images used for AI training and validation (Wen D, Khan SM, Xu AJ et al. Characteristics of publicly available skin cancer image datasets: a systematic review. Lancet Digit Health 2022; 4: e64–74). Limited validation in ethnically diverse skin, in tandem with no human ‘sense check’ on photographic input and analysis by AI, increases the risk of misdiagnosis of skin cancers. We assessed AI bias and developed a cost-effective protocol to increase diagnostic accuracy in patients with ethnically diverse skin. A dermatology nurse collected clinical history and used videodermoscopy to capture optimized macro and dermoscopic images of lesions. Data were from consented patients with self-identified ethnically diverse skin, being assessed via the 2-week-wait skin cancer teledermatology pathway over 7 months. This was combined with clinical history. Histological diagnosis (where available) and consultant diagnosis were recorded for each lesion, used as gold standard to compare Moleanalyzer pro AI assessments of lesions. This ‘real-time AI’ is run at the bedside and clearly demarcates the lesion being analysed. We analysed 69 lesions from 64 patients (45 female, 19 male) with an age range of 18–81 years (mean 49.9). The AI malignancy threshold (MT) is 0–1 (1 being highest risk of malignancy). With MT on the Moleanalyzer pro AI at &amp;gt; 0.2, clinical–AI concordance was 75.4%, while AI sensitivity and specificity were 83.3% and 74.6%, respectively. Published results for Moleanalyzer pro AI in people with Fitzpatrick type II and III skin at MT 0.5 and above show sensitivity 81.6% and specificity 88.9%. In some cases in our study, AI picked out the incorrect darker area and not the index lesion in ethnically diverse skin. In addition, only rare subtypes of skin cancers were found in our patient population. We found that when using dermatological AI diagnostic tools, a nurse-led photography protocol is optimal. Incorporating clinical history alongside ‘real-time AI’ at the bedside, and a human ‘sense check’ on AI diagnosis, reduces risk. When using AI in an ethnically diverse population, a reduced MT must be considered to achieve a level of accuracy comparable with published data. With an effective protocol, AI can provide extensive savings and reduced waiting times. Each diagnostic AI tool developed for skin cancer should be validated with ethnically diverse skin images to reduce health inequality and potential harm to patients. We propose this is introduced into formal quality standards for AI used in skin cancer diagnosis.

In OLED production, the glass fabrication process is prone to frequent occurrences of persistent mura defects, leading to significant damage in the event of defects, as the subsequent final inspection, AVI (Auto Visual Inspection), is time‐consuming. Therefore, there is a need for a consistent inspection. Currently, manual inspection by operators introduces variations in inspection criteria among individuals, resulting in ongoing challenges related to false judgments and post‐process leakage issues The invested automated inspection system for quantitative determination is utilized as a reference only, as the distinction between pseudo‐defects deemed acceptable in AVI and true defects identified as faulty in AVI poses limitations with the traditional logic‐based inspection methods. We enhanced the mura visibility of automatic inspection system (Auto Macro) images through pre‐processing, followed by translation into an image environment similar to AVI images using Pix2pix GAN. Subsequently, we compared the mura index extracted from the processed images with the AVI mura index for evaluation. The Auto Macro images transformed by Pix2pix GAN exhibited similarities with AVI images in terms of overall luminance, gray distribution, and mura visibility intensity. Consequently, the R‐Squared correlation between the mura index of Auto Macro and AVI improved from 0.00 to 0.68. Additionally, defects unrecognized in AVI during Auto Macro inspection were automatically eliminated. False defects in the Auto Macro test that were not recognized in AVI were automatically removed. In this study, we applied the AI model to the Auto Macro inspection system to overcome the limitations of logic‐based inspections. We proposed a method to proactively detect defect‐induced muras before cell‐level processing, aiming to improve yield and reduce incidents of customer leakage accidents.

Smartphone-based machine learning model for real-time assessment of medical kidney biopsy

BackgroundMosquito-borne diseases exert a huge impact on both animal and human populations, posing substantial health risks. The behavioural and fitness traits of mosquitoes, such as locomotion and fecundity, are crucial factors that influence the spread of diseases. In existing egg-counting tools, each image requires separate processing with adjustments to various parameters such as intensity threshold and egg area size. Furthermore, accuracy decreases significantly when dealing with clustered or overlapping eggs. To overcome these issues, we have developed EggCountAI, a Mask Region-based Convolutional Neural Network (RCNN)-based free automatic egg-counting tool for Aedes aegypti mosquitoes.MethodsThe study design involves developing EggCountAI for counting mosquito eggs and comparing its performance with two commonly employed tools—ICount and MECVision—using 10 microscopic and 10 macroscopic images of eggs laid by females on a paper strip. The results were validated through manual egg counting on the strips using ImageJ software. Two different models were trained on macroscopic and microscopic images to enhance egg detection accuracy, achieving mean average precision, mean average recall, and F1-scores of 0.92, 0.90, and 0.91 for the microscopic model, and 0.91, 0.90, and 0.90 for the macroscopic model, respectively. EggCountAI automatically counts eggs in a folder containing egg strip images, offering adaptable filtration for handling impurities of varying sizes.ResultsThe results obtained from EggCountAI highlight its remarkable performance, achieving overall accuracy of 98.88% for micro images and 96.06% for macro images. EggCountAI significantly outperformed ICount and MECVision, with ICount achieving 81.71% accuracy for micro images and 82.22% for macro images, while MECVision achieved 68.01% accuracy for micro images and 51.71% for macro images. EggCountAI also excelled in other statistical parameters, with mean absolute error of 1.90 eggs for micro, 74.30 eggs for macro, and a strong correlation and R-squared value (0.99) for both micro and macro. The superior performance of EggCountAI was most evident when handling overlapping or clustered eggs.ConclusionAccurate detection and counting of mosquito eggs enables the identification of preferred egg-laying sites and facilitates optimal placement of oviposition traps, enhancing targeted vector control efforts and disease transmission prevention. In future research, the tool holds the potential to extend its application to monitor mosquito feeding preferences.Graphical

Various studies are carried out to increase the strength of the joints made with adhesives. One of these studies is to investigate the use of nanoparticles as reinforcement elements in adhesives. In this study, the tensile strength of the bonding joints made by adhesives DP410, DP460 and DP490 epoxy adhesives at the rates of 0.1, 0.2, 0.3 and 0.4% wt. of the graphene nanoparticles (GNP) were investigated. AA5754 aluminum alloys and glass fiber reinforced composites were used as adherent and patches, respectively. Tensile tests were carried out to determine the effect of reinforcement ratios on adhesive bonds. After the tensile tests, macro and scanning electron microscopy (SEM) images were taken to examine the adhesion damage between nanoparticle, adhesive and adherent surfaces. In the results of the tensile test experiments, the tensile strength of all the joints in which the reinforcement element is used was higher than the non-reinforced bonding. The highest tensile strength in GNP-reinforced joints using DP410 and DP490 adhesives was obtained as 5674.4 and 4837.4 MPa, respectively, at 0.2% wt. reinforcement rate. However, the highest tensile strength of all experiments was obtained as 6154.4 MPa in DP460 adhesive, where 0.3% wt. reinforcement ratio was used. In the damage analyses made after the tensile tests, it was observed that there were fiber breaks in the glass fiber composite used as the patch material in the bonding joints, where homogeneity was formed between the surfaces of the GNP and the epoxy adhesive. Especially, this situation occurred in the joints where 0.2% wt. in DP410 adhesive and 0.2% wt. and 0.3% wt. of reinforcement ratios of DP460 adhesive joints were used. Finally, in the fatigue tests, the GNP particle reinforcement increased the fatigue life of the adhesive joints.

Aluminium-based alloy type 7075 is known for its good ductility, high mechanical strength, toughness and high fatigue strength, which is why it is mainly used in the construction of dynamically stressed parts in the structure of airplanes, vehicles and ships. Although it has these qualities, at present its behavior has not been studied at the hydrodynamic stresses that allow it to be used in parts that work in cavitation conditions, such as pump rotors and boat propeller blades. Therefore, the research in this paper highlights the behavior of laminated semi-finished structures and obtained by heat treatment of artificial aging at 180°C, with a maintenance time of one hour. Of the 7075 alloy at the demands generated by the vibrating cavity, created by the standard vibrating device with piezoceramic crystals (frequency of 20 kHz, amplitude of 50 µm and electrical power of 500 W). Analysis based on the curves MDE (t) and MDER (t), of the specific parameters of cavitation erosion MDEmax and MDERs as well as of the macro and microscopic images of the eroded structures of cavitation show that, compared to the delivered state (semi-finished), by the heat treatment applied the microstructure does not change cavitation

Aluminum-based alloys have wide applicability in the construction of aircraft, vehicles, and ships. Some of their components, during operation, such as the radiators and the rotors of the cooling pumps in the vehicles, and the propellers of fishing and pleasure boats are affected by the abrasive, chemical and cavitational corrosive action of the water. At certain hydrodynamic flow regimes, the most dangerous becomes the corrosion through cavitation. Operation in such regimes inevitably leads to damaging the structure, due to cyclic stresses of the micro-jets and shock waves generated by the implosion of cavitation bubbles. Although the chemical constitution and alloying with other chemical elements increase the mechanical properties, the service life is still limited when operating in high-intensity cavitation flows. Therefore, researchers are looking for solutions to improve this resistance through various treatments, such as bulk heat. Research heading the same direction, but, made on 5083 alloy, is presented in this paper. The results highlight the behavior of a modified structure compared to the semi-fabricated state (obtained by rolling), through three durations regimes (one hours, 12 hours and 24 hours) of aging heat treatment to 180 °C temperature, after hardening treatment at 450 °C. The cavitation tests were performed in the Laboratory of the Polytechnic University of Timisoara, on the standard vibrating device with piezoceramic crystals. The results were expressed by curves and parameters specific to the evaluation of cavitation resistance, and by macro and microscopic images, showing the unique aspects of the connection between the structure and the mechanical properties obtained through heat treatment regimes. Thus, comparison of the results, including with the delivery state (laminated product), shows that the highest resistance is provided by the treatment at 24 hours. At the same time, the erosion, of pitting and caverns type, and differs from one structure to another.