The technical difficulty of separating extracellular vesicles (EVs) from plasma proteins in human blood presents a significant hurdle in EV research, particularly during nano ultra-high-performance liquid chromatography–tandem mass spectrometric (UHPLC-MS/MS) analysis, where detecting “vesicular” proteins among abundant plasma proteins is challenging. Standardisation is a pressing issue in EV research, prompting collaborative global efforts to address it. While the MISEV guidelines offer valuable recommendations, unanswered questions remain, particularly regarding sample storage. We compared size exclusion chromatography (SEC) columns with pore sizes of 35 nm and 70 nm to identify fractions with minimal contaminating proteins and the highest concentration of small EVs (sEVs). Following column selection, we explored potential differences in the quality and quantity of sEVs isolated from platelet-free plasma (PFP) after long-term storage at −80 °C (>2.5 years) compared to freshly drawn blood. Our methodologically rigorous study indicates that prolonged storage, under correct storage and processing conditions, does not compromise sEV quality. Both columns effectively isolated vesicles, with the 70 nm column exhibiting a higher abundance of “vesicular” proteins. We propose a relatively rapid and moderately efficient protocol for obtaining a comparatively pure sEV fraction from plasma, facilitating sEV processing in clinical trials. Full article

V-set domain-containing T-cell activation inhibitor 1 (aliases VTCN1, B7H4) participates in tumour immune escape by delivering inhibitory signals to T cells. The purpose of this article was to assess the B7H4 prognostic value in solid cancers. Three databases were searched for relevant articles. The main endpoints were overall survival (OS), disease-specific survival (DSS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-free survival (DFS). Appropriate hazard ratios (HRs) were pooled. The R studio software (version 4.0.3) was used for data analysis. Thirty-one studies met the inclusion criteria. High expression of B7H4 was associated with worse OS (HR = 1.52, 95% CI: 1.37–1.68) but not with DSS (HR = 1.14, 95% CI: 0.49–2.63), RFS (HR = 1.77, 95% CI: 0.75–4.18), DFS (HR = 1.29, 95% CI: 0.8–2.09), or PFS (HR = 1.71, 95% CI: 0.91–3.2) in patients with solid cancers. High expression of B7H4 is associated with a poorer prognosis in patients with solid cancers. B7H4 is a promising prognostic biomarker and immunotherapeutic target for various solid cancers because of its activity in cancer immunity and tumourigenesis. Full article

Alkali-activated materials are gaining much interest due to their outstanding performance, including their great resistance to chemical corrosion, good thermal characteristics, and ability to valorise industrial waste materials. Reusing waste glasses in creating alkali-activated materials appears to be a viable option for more effective solid waste utilisation and lower-cost products. However, very little research has been conducted on the suitability of waste glass as a prime precursor for alkali activation. This study examines the reuse of seven different types of waste glasses in the creation of geopolymeric and cementitious concretes as sustainable building materials, focusing in particular on how using waste glasses as the raw material in alkali-activated materials affects the durability, microstructures, hydration products, and fresh and hardened properties in comparison with using traditional raw materials. The impacts of several vital parameters, including the employment of a chemical activator, gel formation, post-fabrication curing procedures, and the distribution of source materials, are carefully considered. This review will offer insight into an in-depth understanding of the manufacturing and performance in promising applications of alkali-activated waste glass in light of future uses. The current study aims to provide a contemporary review of the chemical and structural properties of glasses and the state of research on the utilisation of waste glasses in the creation of alkali-activated materials. Full article

Computer vision solutions have become widely used in various industries and as part of daily solutions. One task of computer vision is object detection. With the development of object detection algorithms and the growing number of various kinds of image data, different problems arise in relation to the building of models suitable for various solutions. This paper investigates the influence of parameters used in the training process involved in detecting similar kinds of objects, i.e., the hyperparameters of the algorithm and the training parameters. This experimental investigation focuses on the widely used YOLOv5 algorithm and analyses the performance of different models of YOLOv5 (n, s, m, l, x). In the research, the newly collected construction details (22 categories) dataset is used. Experiments are performed using pre-trained models of the YOLOv5. A total of 185 YOLOv5 models are trained and evaluated. All models are tested on 3300 images photographed on three different backgrounds: mixed, neutral, and white. Additionally, the best-obtained models are evaluated using 150 new images, each of which has several dozen construction details and is photographed against different backgrounds. The deep analysis of different YOLOv5 models and the hyperparameters shows the influence of various parameters when analysing the object detection of similar objects. The best model was obtained when the YOLOv5l was used and the parameters are as follows: coloured images, image size—320; batch size—32; epoch number—300; layers freeze option—10; data augmentation—on; learning rate—0.001; momentum—0.95; and weight decay—0.0007. These results may be useful for various tasks in which small and similar objects are analysed. Full article

We proposed and verified a scheme of chaos synchronization for integrated five-section semiconductor lasers with matching parameters. The simulation results demonstrated that the integrated five-section semiconductor laser could generate a chaotic signal within a large parameter range of the driving currents of five sections. Subsequently, chaos synchronization between two integrated five-section semiconductor lasers with matched parameters was realized by using a common noise signal as a driver. Moreover, it was found that the synchronization was sensitive to the current mismatch in all five sections, indicating that the driving currents of the five sections could be used as keys of chaotic optical communication. Therefore, this synchronization scheme provides a candidate to increase the dimension of key space and enhances the security of the system. Full article

Background and Objectives: Treatment of chronic plantar fasciitis is challenging given that there are various of available treatment options with no clear gold standard. The aim of the study was to examine the dose-escalation effect of rESWT on the biomechanical parameters of the plantar fascia and pain ailments. Materials and Methods: In the experimental group (n = 30), the intensity of the shock wave was increased every two subsequent treatment sessions. In the control group (n = 32), the treatment parameters were not changed. In both groups, six treatments were performed, with two treatment sessions a week. In order to assess the biomechanical parameters of the plantar fascia, myotonometric measurements were performed. The pain intensity was assessed using the Visual Analog Scale (VAS). Results: The tension of the plantar fascia attachment in the experimental group decreased from 27.69 ± 2.06 [Hz] before treatment to 26.29 ± 1.69 [Hz] after treatment (p = 0.009) and to 26.03 ± 2.15 [Hz] 1 month after the beginning of treatment (p = 0.003). In the control group, the frequency results did not change significantly (p > 0.05). Flexibility increased in both groups. The test results before treatment and 1 month after the beginning of the treatment showed statistical significance in the experimental group (p = 0.001) vs. (p = 0.002) in the control group. The differences were not statistically significant between groups (p > 0.05). The assessment of pain intensity carried out 1 month after the end of treatment in the experimental group amounted to 3.14 ± 2.28 points, which was statistically significantly lower compared to that in the control group, where it amounted to 5.14 ± 1.92 points. (p < 0.001). Conclusions: The use of rESWT performed with an increasing intensity of impact during subsequent treatment procedures demonstrated greater effectiveness in improving the biomechanical parameters of the plantar fascia and was also more effective in reducing the pain ailments. Our results are encouraging. The dose escalation in the treatment cycle is worth considering. To prove that this method of treatment is more effective, a randomized controlled trial should be carried out on a representative sample. Full article

Diet is integral to the healthy ageing process and certain diets can mitigate prolonged and deleterious inflammation. This review aims to assess the impact of diets high in sustainably sourced proteins on nutrient intake, gut, and age-related health in older adults. A systematic search of the literature was conducted on 5 September 2023 across multiple databases and sources. Studies assessing sustainably sourced protein consumption in community dwelling older adults (≥65 years) were included. Risk of bias (RoB) was assessed using ‘RoB 2.0′ and ‘ROBINS-E’. Narrative synthesis was performed due to heterogeneity of studies. Twelve studies involving 12,166 older adults were included. Nine studies (n = 10,391) assessed habitual dietary intake and had some RoB concerns, whilst three studies (n = 1812), two with low and one with high RoB, conducted plant-based dietary interventions. Increased adherence to sustainably sourced diets was associated with improved gut microbial factors (n = 4640), healthier food group intake (n = 2142), and increased fibre and vegetable protein intake (n = 1078). Sustainably sourced diets positively impacted on gut microbiota and healthier intake of food groups, although effects on inflammatory outcomes and health status were inconclusive. Future research should focus on dietary interventions combining sustainable proteins and fibre to evaluate gut barrier function and consider inflammatory and body composition outcomes in older adults. Full article

Phalaenopsis orchids are a popular ornamental plant in the flower market. During some festivals, demand increases significantly. These mature orchids must be placed in cooling rooms for inflorescence formation at specific times to increase the financial return from their sale. The purpose of this study is to evaluate the effect of day and night temperatures on the inflorescence formation percentage using the proposed sigmoid model. Four varieties that are cultured in different vegetative temperature regimes are placed in a cooling room. An empirical inflorescence formation model is proposed as a management tool to predict the inflorescence formation percentage for Phalaenopsis. Some data sets from previous studies are used for comparison. The accumulation temperature is calculated using the day and night temperatures and is an index to predict the inflorescence formation percentage. The results show that there is a similar distribution of the inflorescence formation percentage and accumulation temperature for the four varieties. The proposed sigmoid model has a good fitting ability for the inflorescence formation percentage. This inflorescence formation model from the pooled data sets allows quantitative microclimate management of the vegetative and cooling room. Full article

The increasingly adverse impacts of climate change (e.g., rainfall patterns, droughts, and floods), coupled with the ever-increasing water demands, are often translated into a contingent liability for water users’ communities. Additional complexities arise due to competing priorities, water rights, and transboundary water sources. Therefore, conventional water management practices should shift toward more comprehensive and responsive integrative approaches, even for systems with limited data. Furthermore, water managers must prioritize dynamic and interactive management techniques for existing systems. One such management technique is water banking, which is the focus of this study. Herein, a dynamic interactive water allocation model, which encompasses the water managers and heterogeneous parties with competing demands, is developed. The voluntary sales of water shares between parties are illustrated through the specific case of the Medjerda River in Tunisia, an excellent example of a transboundary basin with limited hydrologic data and conflicting water use requirements between its upstream and downstream sectors. A set of scenarios is developed for the first analysis with this model: two management scenarios that include the no-water trade and the water banking option; three demand scenarios that include a combination of steady-, low-, and high-water demand conditions; and two hydrologic scenarios that include dry and wet conditions. Based on an economic model, the economic impacts of water banking are calculated using estimates of the costs of water shortages brought to users that illustrate the magnitude. The results show that the water banking technique can improve water resource availability by optimizing the management, operation, and conservation of natural and artificial water storage systems and water distribution infrastructure. Specifically, water banking can offset users’ profit losses during severe conditions (i.e., drought), even with limited hydrologic data. This water management technique would allow the Tunisian government to minimize the economic impacts on farmers from drought and to plan for future uncertainties by optimizing the water storage potential in years of abundant rainfall. Full article

SLAM (Simultaneous Localization and Mapping), primarily relying on camera or LiDAR (Light Detection and Ranging) sensors, plays a crucial role in robotics for localization and environmental reconstruction. This paper assesses the performance of two leading methods, namely ORB-SLAM3 and SC-LeGO-LOAM, focusing on localization and mapping in both indoor and outdoor environments. The evaluation employs artificial and cost-effective datasets incorporating data from a 3D LiDAR and an RGB-D (color and depth) camera. A practical approach is introduced for calculating ground-truth trajectories and during benchmarking, reconstruction maps based on ground truth are established. To assess the performance, ATE and RPE are utilized to evaluate the accuracy of localization; standard deviation is employed to compare the stability during the localization process for different methods. While both algorithms exhibit satisfactory positioning accuracy, their performance is suboptimal in scenarios with inadequate textures. Furthermore, 3D reconstruction maps established by the two approaches are also provided for direct observation of their differences and the limitations encountered during map construction. Moreover, the research includes a comprehensive comparison of computational performance metrics, encompassing Central Processing Unit (CPU) utilization, memory usage, and an in-depth analysis. This evaluation revealed that Visual SLAM requires more CPU resources than LiDAR SLAM, primarily due to additional data storage requirements, emphasizing the impact of environmental factors on resource requirements. In conclusion, LiDAR SLAM is more suitable for the outdoors due to its comprehensive nature, while Visual SLAM excels indoors, compensating for sparse aspects in LiDAR SLAM. To facilitate further research, a technical guide was also provided for the researchers in related fields. Full article

Mycotoxins often contaminate rice, which are the secondary metabolites of fungi. Ustiloxins, a type of mycotoxin that has often been overlooked, pose a significant risk to human health. Therefore, identifying and controlling the pollution of ustiloxins in rice is required. In this study, we examined the natural contamination of rice with ustiloxins and their link to climate conditions. A total of 300 paddy samples were collected from six regions in southern China, and concentrations of ustiloxins A, B, C, D, and F were analyzed by liquid chromatography–tandem mass spectrometry (LC-MS/MS). Results showed that the occurrence of ustiloxins A, B, C, D, and F in paddies was found to be 55.7%, 41.3%, 29.0%, 93.7%, and 96.7%, respectively. Ustiloxin A had the highest mean (177.8 µg/kg) and maximum (3620.9 µg/kg) concentration, followed, in order, by ustiloxins C, B, D, and F. Furthermore, ustiloxin levels were significantly different depending on their origin, with the highest concentration in rice from Changde and Yueyang. And the regional difference in ustiloxins was related to the diversity of climate. A positive correlation between ustiloxin occurrence and mean humidity and precipitation was found in July and August of different regions, while mean temperature indicated a negative dependence. This is an essential survey of the contamination of rice with ustiloxins throughout southern China. The influence of climatic conditions on ustiloxins contamination was evaluated for the first time in our study. Overall, the rice samples examined in this study exhibited a high distribution of ustiloxins, suggesting that regulatory limits and the establishment of maximum allowable levels of ustiloxins in rice are necessary. This study provides a basis and guidance for the pollution situation and control strategy of ustiloxins in China. Full article

The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential during conduction, reflecting the developmental status of the fetus in utero and its physiological cardiac activity. Morphological alterations in the FECG can indicate intrauterine hypoxia, fetal distress, and neonatal asphyxia early on, enhancing maternal and fetal safety through prompt clinical intervention, thereby reducing neonatal morbidity and mortality. To reconstruct FECG signals with clear morphological information, this paper proposes a novel deep learning model, CBLS-CycleGAN. The model’s generator combines spatial features extracted by the CNN with temporal features extracted by the BiLSTM network, thus ensuring that the reconstructed signals possess combined features with spatial and temporal dependencies. The model’s discriminator utilizes PatchGAN, employing small segments of the signal as discriminative inputs to concentrate the training process on capturing signal details. Evaluating the model using two real FECG signal databases, namely “Abdominal and Direct Fetal ECG Database” and “Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeat Annotations”, resulted in a mean MSE and MAE of 0.019 and 0.006, respectively. It detects the FQRS compound wave with a sensitivity, positive predictive value, and F₁ of 99.51%, 99.57%, and 99.54%, respectively. This paper’s model effectively preserves the morphological information of FECG signals, capturing not only the FQRS compound wave but also the fetal P-wave, T-wave, P-R interval, and ST segment information, providing clinicians with crucial diagnostic insights and a scientific foundation for developing rational treatment protocols. Full article

Understanding the potential effects of climate change on forest fire behavior and the resulting release of combustion products is critical for effective mitigation strategies in Greece. This study utilizes data from the MAGICC 2.4 (Model for the Assessment of Greenhouse Gas-Induced Climate Change) climate model and the SCENGEN 2.4 (SCENarioGENerator) database to assess these impacts. By manipulating various model parameters such as climate sensitivity, scenario, time period, and global climate models (GCMs) within the SCENGEN 2.4 database, we analyzed climatic trends affecting forest fire generation and evolution. The results reveal complex and nuanced findings, indicating a need for further investigation. Case studies are conducted using the FARSITE 4 (Fire Area Simulator) model, incorporating meteorological changes derived from climate trends. Simulations of two fires in East Attica, accounting for different fuel and meteorological conditions, demonstrate an increase in the rate of combustion product release. This underscores the influence of changing meteorological parameters on forest fire dynamics and highlights the importance of proactive measures to mitigate future risks. Our findings emphasize the urgency of addressing climate change impacts on wildfire behavior to safeguard environmental and public health in Greece. Full article

The combination of water electrolysis and renewable energy to produce hydrogen is a promising way to solve the climate and energy crisis. However, the fluctuating characteristics of renewable energy not only present a significant challenge to the use of water electrolysis electrodes, but also limit the development of the hydrogen production industry. In this study, the effects of three different types of waveforms (square, step, and triangle, which were used to simulate the power input of renewable energy) on the electrochemical catalysis behavior of Ni plate cathodes for HER was investigated. During the test, the HER performance of the Ni cathode increased at first and then slightly decreased. The fluctuating power led to the degradation of the Ni cathode surface, which enhanced the catalysis effect by increasing the catalytic area and the active sites. However, prolonged operation under power fluctuations could have damaged the morphology of the electrode surface and the substances comprising this surface, potentially resulting in a decline in catalytic efficiency. In addition, the electrochemical catalysis behavior of the prepared FeNiMo-LDH@NiMo/SS cathode when subjected to square-wave potential with different fluctuation amplitudes was also extensively studied. A larger amplitude of fluctuating power led to a change in the overpotential and stability of the LDH electrode, which accelerated the degradation of the cathode. This research provides a technological basis for the coupling of water electrolysis and fluctuating renewable energy and thus offers assistance to the development of the “green hydrogen” industry. Full article

This research investigates the sustainable marketing effectiveness of Poland’s fruit and vegetable industry using a seminal approach to analyze the interconnected dynamics among all factors and highlight pivotal elements through a structural model. Methodologically, the research used a sample of 216 companies utilizing a comprehensive survey to gauge various dimensions of sustainable marketing, including the environmental and social aspects of production, pricing, distribution and promotional activities. The findings reveal a nuanced landscape of sustainability practices within the industry. While there is a commendable level of awareness and some positive strides in certain areas such as employee-focused social aspects, other domains lag significantly, particularly consumer-focused social aspects and sustainable promotional activities. The study highlights the need for a more concerted and integrated approach towards sustainability, emphasizing the necessity of balancing economic goals with environmental stewardship and social responsibility. These insights bear significant implications for both research and practice. Practically, the study offers industry stakeholders a detailed understanding of the current state of sustainable practices pinpointing areas of strength and opportunities for improvement. It underlines the originality and value of employing a sophisticated analytical approach in assessing and enhancing the sustainability of marketing practices in the industry. Full article

Anxiety disorders are prevalent mental health conditions often accompanied by various comorbidities. The association between anxiety and liver disease, as well as fluctuations in blood sugar levels, highlights the importance of carefully evaluating patients with anxiety undergoing antidepressant therapy. The aim of this study was to conduct a comparative assessment of liver function and blood glucose levels in patients diagnosed with anxiety disorders while considering potential gender-specific differences. Methods: An analysis was conducted over a 24-month period. This study included 88 patients diagnosed with anxiety disorders, with symptoms severe enough to require hospitalization, aged 18 or older, undergoing antidepressant monotherapy, without any additional pathologies. Liver enzymes (AST, ALT, GGT), AST/ALT ratio, and blood glucose levels were measured and compared. Results: While no significant differences were found between antidepressant classes, increased GGT levels were observed in men older than 40 years compared to women of the same age, suggesting that alcohol consumption may be a coping mechanism for anxiety. This gender difference was not observed among young patients. Conclusions: Early detection of alcohol consumption is essential in patients with anxiety disorders in order to prevent alcohol-related liver damage and to adjust the management of both conditions accordingly. Full article

Motion capture technology plays a crucial role in optimizing athletes’ skills, techniques, and strategies by providing detailed feedback on motion data. This article presents a comprehensive survey aimed at guiding researchers in selecting the most suitable motion capture technology for sports science investigations. By comparing and analyzing the characters and applications of different motion capture technologies in sports scenarios, it is observed that cinematography motion capture technology remains the gold standard in biomechanical analysis and continues to dominate sports research applications. Wearable sensor-based motion capture technology has gained significant traction in specialized areas such as winter sports, owing to its reliable system performance. Computer vision-based motion capture technology has made significant advancements in recognition accuracy and system reliability, enabling its application in various sports scenarios, from single-person technique analysis to multi-person tactical analysis. Moreover, the emerging field of multimodal motion capture technology, which harmonizes data from various sources with the integration of artificial intelligence, has proven to be a robust research method for complex scenarios. A comprehensive review of the literature from the past 10 years underscores the increasing significance of motion capture technology in sports, with a notable shift from laboratory research to practical training applications on sports fields. Future developments in this field should prioritize research and technological advancements that cater to practical sports scenarios, addressing challenges such as occlusion, outdoor capture, and real-time feedback. Full article

The incorporation of building information modeling (BIM) has brought about significant advancements in civil engineering, enhancing efficiency and sustainability across project life cycles. The utilization of advanced 3D point cloud technologies such as laser scanning extends the application of BIM, particularly in operations and maintenance, prompting the exploration of automated solutions for labor-intensive point cloud modeling. This paper presents a demonstration of supervised machine learning—specifically, a support vector machine—for the analysis and segmentation of 3D point clouds, which is a pivotal step in 3D modeling. The point cloud semantic segmentation workflow is extensively reviewed to encompass critical elements such as neighborhood selection, feature extraction, and feature selection, leading to the development of an optimized methodology for this process. Diverse strategies are implemented at each phase to enhance the overall workflow and ensure resilient results. The methodology is then evaluated using diverse datasets from infrastructure scenes of bridges and compared with state-of-the-art deep learning models. The findings highlight the effectiveness of supervised machine learning techniques at accurately segmenting 3D point clouds, outperforming deep learning models such as PointNet and PointNet++ with smaller training datasets. Through the implementation of advanced segmentation techniques, there is a partial reduction in the time required for 3D modeling of point clouds, thereby further enhancing the efficiency and effectiveness of the BIM process. Full article

This review article gathers the most recent recycling technologies for thermoset and thermoplastic polymers. Results about existing experimental procedures and their effectiveness are presented. For thermoset polymers, the review focuses mainly on fibre-reinforced polymer composites, with an emphasis on epoxy-based systems and carbon/glass fibres as reinforcement, due to the environmental concerns of their end-of-life management. Thermal processes (fluidised bed, pyrolysis) and chemical processes (different types of solvolysis) are discussed. The most recent combined processes (microwave, steam, and ultrasonic assisted techniques) and extraordinary recycling attempts (electrochemical, biological, and with ionic liquids) are analysed. Mechanical recycling that leads to the downgrading of materials is excluded. Insights are also given for the upcycling methodologies that have been implemented until now for the reuse of fibres. As for thermoplastic polymers, the most state-of-the-art recycling approach for the most common polymer matrices is presented, together with the appropriate additivation for matrix upcycling. Mechanical, chemical, and enzymatic recycling processes are described, among others. The use of fibre-reinforced thermoplastic composites is quite new, and thus, the most recent achievements are presented. With all of the above information, this extensive review can serve as a guide for educational purposes, targeting students and technicians in polymers recycling. Full article

Mucositis is a pathological condition characterised by inflammation and ulceration of the mucous membranes lining the alimentary canal, particularly in the mouth (oral mucositis) and the gastrointestinal tract. It is a common side effect of cancer treatments, including chemotherapy and radiotherapy, and it is sometimes responsible for treatment interruptions. Preventing mucositis throughout the alimentary tract is therefore crucial. However, current interventions mainly target either oral or gastrointestinal side effects. This review aimed to investigate the use of systemically administered anti-inflammatory agents to prevent mucositis in cancer patients undergoing cancer treatment. PubMed, Ovid, Scopus, Web of Science, WHO ICTRP and ClinicalTrials.gov were screened to identify eligible randomised controlled trials (RCTs). The published literature on anti-inflammatory agents provides mixed evidence regarding the degree of efficacy in preventing/reducing the severity of mucositis in most anticancer treatments; however, sample size continued to be a significant limitation, alongside others discussed. Our review yielded a list of several anti-inflammatory agents that exhibit potential mucositis-preventive effects in cancer patients undergoing cancer treatment, which can be used to inform clinical practice. Full article

After the experience of the COVID-19 pandemic, it has become evident that efficient and secure interoperability of medical information is crucial for effective diagnoses and medical treatments. However, a significant challenge arises concerning the heterogeneity of the systems storing patient information in medical centers or hospitals. Memory management becomes a pivotal element for the effective operation of the proposed API, as it must seamlessly execute across various devices, ranging from healthcare units, such as mobile phones, to servers in cloud computing. This proposal addresses these issues through techniques designed to enhance the performance of the software architecture in creating a medical interoperability API. This API has the capacity to be cloned and distributed to facilitate the exchange of data related to a patient’s medical history. To tackle heterogeneity, efficient memory management was implemented by utilizing an object-oriented approach and leveraging design patterns like abstract factory and wrapper. Regarding the evaluation of the proposal, this study showed an estimated performance of 94.5 percent, which was indirectly demonstrated through the assessment of operation sequences. This result suggests a satisfactory level based on complexity and coupling. Full article

Background and Objectives: The modified Duke index derived from coronary computed tomography angiography (CCTA) was designed to predict cardiovascular outcomes based on the severity of coronary stenosis. However, it does not take into consideration the presence or severity of peri‑coronary inflammation. The peri-coronary fat attenuation index (FAI) is a novel imaging marker determined by CCTA which reflects the degree of inflammation in the coronary tree in patients with coronary artery disease. To assess the association between the modified Duke index assessed by CCTA, cardiovascular risk factors, and peri-coronary inflammation in the coronary arteries of patients with coronary artery disease. Materials and Methods: One hundred seventy-two patients who underwent CCTA for typical angina were assigned into two groups based on the modified Duke index: group 1—patients with low index, ≤3 (n = 107), and group 2—patients with high index, >3 (n = 65). Demographic, clinical, and CCTA data were collected for all patients, and FAI analysis of coronary inflammation was performed. Results: Patients with increased values of the modified Duke index were significantly older compared to those with a low index (61.83 ± 9.89 vs. 64.78 ± 8.9; p = 0.002). No differences were found between the two groups in terms of gender distribution, hypertension, hypercholesterolemia, or smoking history (all p > 0.5). The FAI score was significantly higher in patients from group 2, who presented a significantly higher score of inflammation compared to the patients in group 1, especially at the level of the right coronary artery (FAI score, 20.85 ± 15.80 vs. 14.61 ± 16.66; p = 0.01 for the right coronary artery, 13.85 ± 8.04 vs. 10.91 ± 6.5; p = 0.01 for the circumflex artery, 13.26 ± 10.18 vs. 11.37 ± 8.84; p = 0.2 for the left anterior descending artery). CaRi-Heart^® analysis identified a significantly higher risk of future events among patients with a high modified Duke index (34.84% ± 25.86% vs. 16.87% ± 15.80%; p < 0.0001). ROC analysis identified a cut-off value of 12.1% of the CaRi-Heart^® risk score for predicting a high severity of coronary lesions, with an AUC of 0.69. Conclusions: The CT-derived modified Duke index correlates well with local perilesional inflammation as assessed using the FAI score at different levels of the coronary circulation. Full article