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Abstract Enhancements in the structural and operational aspects of transportation are important for achieving high-quality mobility. Toll plazas are commonly known as a potential bottleneck stretch, as they tend to interfere with the normality of the flow due to the charging points. Focusing on the automation of toll plazas, this research presents the development of an axle counter to compose a free-flow toll collection system. The axle counter is responsible for the interpretation of images through algorithms based on computer vision to determine the number of axles of vehicles crossing in front of a camera. The You Only Look Once (YOLO) model was employed in the first step to identify vehicle wheels. Considering that several versions of this model are available, to select the best model, YOLOv5, YOLOv6, YOLOv7, and YOLOv8 were compared. The YOLOv5m achieved the best result with precision and recall of 99.40% and 98.20%, respectively. A passage manager was developed thereafter to verify when a vehicle passes in front of the camera and store the corresponding frames. These frames are then used by the image reconstruction module which creates an image of the complete vehicle containing all axles. From the sequence of frames, the proposed method is able to identify when a vehicle was passing through the scene, count the number of axles, and automatically generate the appropriate charge to be applied to the vehicle.

Abstract To ensure the electrical power supply, inspections are frequently performed in the power grid. Nowadays, several inspections are conducted considering the use of aerial images since the grids might be in places that are difficult to access. The classification of the insulators' conditions recorded in inspections through computer vision is challenging, as object identification methods can have low performance because they are typically pre‐trained for a generalized task. Here, a hybrid method called YOLOu‐Quasi‐ProtoPNet is proposed for the detection and classification of failed insulators. This model is trained from scratch, using a personalized ultra‐large version of YOLOv5 for insulator detection and the optimized Quasi‐ProtoPNet model for classification. For the optimization of the Quasi‐ProtoPNet structure, the backbones VGG‐16, VGG‐19, ResNet‐34, ResNet‐152, DenseNet‐121, and DenseNet‐161 are evaluated. The F1‐score of 0.95165 was achieved using the proposed approach (based on DenseNet‐161) which outperforms models of the same class such as the Semi‐ProtoPNet, Ps‐ProtoPNet, Gen‐ProtoPNet, NP‐ProtoPNet, and the standard ProtoPNet for the classification task.

Genome-wide association studies (GWAS) and candidate pathway studies have identified low-penetrant genetic variants associated with cutaneous melanoma. We investigated the association of melanoma-risk variants with primary melanoma tumor prognostic characteristics and melanoma-specific survival. The Genes, Environment, and Melanoma Study enrolled 3285 European origin participants with incident invasive primary melanoma. For each of 47 melanoma-risk single nucleotide polymorphisms (SNPs), we used linear and logistic regression modeling to estimate, respectively, the per allele mean changes in log of Breslow thickness and odds ratios for presence of ulceration, mitoses, and tumor-infiltrating lymphocytes (TILs). We also used Cox proportional hazards regression modeling to estimate the per allele hazard ratios for melanoma-specific survival. Passing the false discovery threshold (p = 0.0026) were associations of IRF4 rs12203592 and CCND1 rs1485993 with log of Breslow thickness, and association of TERT rs2242652 with presence of mitoses. IRF4 rs12203592 also had nominal associations (p < 0.05) with presence of mitoses and melanoma-specific survival, as well as a borderline association (p = 0.07) with ulceration. CCND1 rs1485993 also had a borderline association with presence of mitoses (p = 0.06). MX2 rs45430 had nominal associations with log of Breslow thickness, presence of mitoses, and melanoma-specific survival. Our study indicates that further research investigating the associations of these genetic variants with underlying biologic pathways related to tumor progression is warranted.

In an effort to understand the difference between melanomas diagnosed in Australia (New South Wales) and Canada, where the incidence in New South Wales is almost three times greater than in Canada, and mortality is twice as high although survival is slightly more favorable, we had one pathologist review 1,271 melanomas from British Columbia and Ontario, Canada, to compare these to melanomas in New South Wales, Australia. We hypothesized that histopathologic characteristics might provide insight into divergent pathways to melanoma development. We found a number of differences in risk factors and tumor characteristics between the two geographic areas. There were higher mole counts and darker phenotypes in the Canadian patients, while the Australian patients had greater solar elastosis, more lentigo maligna melanomas, and more tumor infiltrating lymphocytes. We hypothesize that the differences observed may illustrate different etiologies – the cumulative exposure pathway among Australian patients and the nevus pathway among Canadian patients. This is one of the largest studies investigating the divergent pathway hypothesis and is particularly robust due to the evaluation of all lesions by one dermatopathologist.

Background Mild anemia is a frequent although often overlooked finding in old age. Nevertheless, in recent years anemia has been linked to several adverse outcomes in the elderly population. Objective of the study was to investigate the association of mild anemia (hemoglobin concentrations: 10.0–11.9/12.9 g/dL in women/men) with all-cause mortality over 11–15 years and the effect of change in anemia status on mortality in young-old (65–84 years) and old-old (80+ years). Methods The Health and Anemia and Monzino 80-plus are two door-to-door, prospective population-based studies that included residents aged 65-plus years in Biella municipality and 80-plus years in Varese province, Italy. No exclusion criteria were used. Results Among 4,494 young-old and 1,842 old-old, mortality risk over 15/11 years was significantly higher in individuals with mild anemia compared with those without (young-old: fully-adjusted HR: 1.35, 95%CI, 1.15–1.58; old-old: fully-adjusted HR: 1.28, 95%CI, 1.14–1.44). Results were similar in the disease-free subpopulation (age, sex, education, smoking history, and alcohol consumption adjusted HR: 1.54, 95%CI, 1.02–2.34). Both age groups showed a dose-response relationship between anemia severity and mortality (P for trend Conclusions Findings from these two large prospective population-based studies consistently suggest an independent, long-term impact of mild anemia on survival at older ages.

The present article aims at analyzing the social and ontological effects of listening music online, with particular attention to the artistic practice of improvisation. In the first paragraph, I will briefly explain the essential concepts which ontology of music has traditionally counted on, and I will suggest an alternative theoretical approach, that I define as ontology of musical act. Then I will investigate the relation between recording practices and improvisation. In the final paragraph I will compare some features of musical recordings (suggested by Andrew Kania) with those of technological devices that allow us to listen music online.

In control engineering education, the possibility of using a real control system in the learning process motivates professors to improve both students’ knowledge and skills, thus avoiding an approach only based on control theory. While considering that control engineering laboratories are expensive, mainly because educational plants should reproduce classical problems that are found in the industry, the use of virtual laboratories appears as an interesting strategy for reducing costs and improving the diversity of experiments. In this research, remote experimentation was assumed regarding the ball and beam process as an alternative didactic methodology. While assuming a nonlinear and unstable open-loop process, this study presents how students should proceed to control the plant focusing on the topic that is associated with multiobjective optimization. Proportional-Integral-Derivative (PID) controller was tuned considering the Non-dominated Sorting Genetic Algorithm (NSGA-II) to illustrate the WebLab learning procedures described in this research. The proposed strategy was compared to the Åström’s robust loop shaping method to emphasize the performance of the multiobjective optimization technique. Analyzing the feedback provided by the students, remote experimentation can be seen as an interesting approach for the future of engineering learning, once it can be directly associated with industry demand of connected machines and real-time information analysis.

The surface contamination of electrical insulators can increase the electrical conductivity of these components, which may lead to faults in the electrical power system. During inspections, ultrasound equipment is employed to detect defective insulators or those that may cause failures within a certain period. Assuming that the signal collected by the ultrasound device can be processed and used for both the detection of defective insulators and prediction of failures, this study starts by presenting an experimental procedure considering a contaminated insulator removed from the distribution line for data acquisition. Based on the obtained data set, an offline time series forecasting approach with an Adaptive Neuro-Fuzzy Inference System (ANFIS) was conducted. To improve the time series forecasting performance and to reduce the noise, Wavelet Packets Transform (WPT) was associated to the ANFIS model. Once the ANFIS model associated with WPT has distinct parameters to be adjusted, a complete evaluation concerning different model configurations was conducted. In this case, three inference system structures were evaluated: grid partition, fuzzy c-means clustering, and subtractive clustering. A performance analysis focusing on computational effort and the coefficient of determination provided additional parameter configurations for the model. Taking into account both parametrical and statistical analysis, the Wavelet Neuro-Fuzzy System with fuzzy c-means showed that it is possible to achieve impressive accuracy, even when compared to classical approaches, in the prediction of electrical insulators conditions.

Building envelopes are constantly subjected to temperature and moisture gradients. This loading induces a complex response, particularly for highly hygroscopic insulating materials. Latent effects can no longer be neglected for these materials in which heat and moisture transfers are strongly coupled. The purpose of this article is to analyze the behavior of a wood fiber insulation subjected to non-isothermal loading under a vapor concentration gradient. An experimental setup and a mathematical model of hygrothermal transfer were developed to analyze the behavior of the wall. The mathematical model describes the main physical phenomena involved, notably water vapor adsorption and the dependence of thermophysical properties in state variables. The experimental setup developed allows studying a wall under controlled conditions. The temperature and relative humidity profiles within the wall were measured. The evolution of the profiles with time suggests that the adsorption of the water vapor occurs together with the redistribution of liquid water within the envelope. The comparison of the experimental results with the numerical model shows good agreement although the prediction can be improved during the transient phase. The comparisons of these results with a purely diffusive thermal transfer model show the limits of the latter and permit quantifying the latent effects on the total heat transfer.

Semiparametric hazard function regression models are among the well studied risk models in survival analysis. The Cox proportional hazards model has been a popular choice in modelling data from epidemiological settings. The Cox-Aalen model is one of the tools for handling the problem of non-proportional effects in the Cox model. We show an application on Piedmont cancer registry data. We initially fit standard Cox model and with the help of the score process we detect the violation of the proportionality assumption. Covariates and risk factors that, on the basis of clinical reasoning, best model baseline hazard are then moved into the additive part of the Cox-Aalen model. Multiplicative effects results are consistent with those of the Cox model whereas only the Cox-Aalen model fully represents the timevarying effect of tumour size.

This essay aims at clarifying the relation between the notions of formativity and improvisation, with particular attention to musical practices. Firstly, I will focus on originality and exemplarity, then I will briefly deepen three themes of particular interest faced by Pareyson’s philosophy of art: 1) the unforeseen; 2) the interpretation; 3) the cue or sketch. My purpose is to suggest some adjustments to the notion of formativity, in order to outline the essential features of a logic of musical improvisation.

Variation in the melanocortin-1receptor (MC1R) gene is associated with pigmentary phenotypes and risk of malignant melanoma. Few studies have reported on MC1R variation with respect to tumor characteristics, especially clinically important prognostic features. We examined associations between MC1R variants and histopathological melanoma characteristics. Study participants were enrolled from nine geographic regions in Australia, Canada, Italy and the United States and were genotyped for MC1R variants classified as high-risk [R] (D84E, R142H, R151C, R160W, and D294H, all nonsense and insertion/deletion) or low-risk [r] (all other nonsynonymous) variants. Tissue was available for 2,160 white participants of the Genes, Environment and Melanoma (GEM) Study with a first incident primary melanoma diagnosis, and underwent centralized pathologic review. No statistically significant associations were observed between MC1R variants and AJCC established prognostic tumor characteristics: Breslow thickness, presence of mitoses or presence of ulceration. However, MC1R was significantly associated with anatomic site of melanoma (p = 0.002) and a positive association was observed between carriage of more than one [R] variant and melanomas arising on the arms (OR = 2.39; 95% CI: 1.40, 4.09). We also observed statistically significant differences between sun-sensitive and sun-resistant individuals with respect to associations between MC1R genotype and AJCC prognostic tumor characteristics. Our results suggest inherited variation in MC1R may play an influential role in anatomic site presentation of melanomas and may differ with respect to skin pigmentation phenotype.

The hygrothermal analysis of roofs is relevant due to the large areas exposed to a wide range of weather conditions, these directly affecting the energy performance and thermal comfort of buildings. However, after a long life service, the solar absorptivity coatings of roofs can be altered by mould accumulation. Based on two well established mathematical models, one that adopts driving potentials to calculate temperature, moist air pressure and water vapor pressure gradients, and the other to estimate the mould growth risk on surfaces, this research introduces an approach to predict mould growth considering a reduced computational effort and simulation time. By adopting multiple MISO (Multiple-Input, Single-Output) Nonlinear AutoRegressive with eXogenous inputs (NARX) models, a machine learning technique known as Least Squares Support Vector Machines (LS-SVM), a maximum margin model based on structural risk minimization, was used to predict vapor flux, sensible heat flux, latent heat flux, and mould growth risk on roof surfaces. The proposed model was validated in terms of the Multiple Correlation Coefficient (R2R2R2), Mean Square Error (MSE) and Mean Absolute Error (MAE) performance indices considering as input the weather file from Curitiba city—Brazil, showing consistent precision when compared to the results of a validated numerical model.