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Typical crack detection processes in digital images produce a binary-segmented image that constitutes the basis for all of the following analyses. Binary images are, however, an unsatisfactory data format for advanced crack analysis algorithms due to their sparse nature and lack of significant data structuring. Therefore, this work instead proposes a new approach based on Euclidean graphs as functional crack pattern descriptors for all post-detection analyses. Conveying both geometrical and topological information in an integrated representation, Euclidean graphs are an ideal structure for efficient crack path description, as they precisely locate the cracks on the original image and capture salient crack skeleton features. Several Euclidean graph-based algorithms for autonomous crack refining, correlation and analysis are described, with significant advantages in both their capabilities and implementation convenience over the traditional, binary image-based approach. Moreover, Euclidean graphs allow the autonomous selection of specific cracks or crack parts based on objective criteria. Well-known performance metrics, namely precision, recall, intersection over union and F1-score, have been adapted for use with Euclidean graphs. The automated generation of Euclidean graphs from binary-segmented images is also reported, enabling the application of this technique to most existing detection methods (e.g., threshold-based or neural network-based) for cracks and other curvilinear features in digital images.

This study presents an experimental overview for the development of photocatalytic materials based on geopolymer binders as catalyst support matrices. Particularly, geopolymer matrices obtained from different solid precursors (fly ash and metakaolin), composite systems (siloxane-hybrid, foamed hybrid), and curing temperatures (room temperature and 60 °C) were investigated for the same photocatalyst content (i.e., 3% TiO2 by weight of paste). The geopolymer matrices were previously designed for different applications, ranging from insulating (foam) to structural materials. The photocatalytic activity was evaluated as NO degradation in air, and the results were compared with an ordinary Portland cement reference. The studied matrices demonstrated highly variable photocatalytic performance depending on both matrix constituents and the curing temperature, with promising activity revealed by the geopolymers based on fly ash and metakaolin. Furthermore, microstructural features and titania dispersion in the matrices were assessed by scanning electron microscopy (SEM) and energy dispersive X-ray (EDS) analyses. Particularly, EDS analyses of sample sections indicated segregation effects of titania in the surface layer, with consequent enhancement or depletion of the catalyst concentration in the active sample region, suggesting non-negligible transport phenomena during the curing process. The described results demonstrated that geopolymer binders can be interesting catalyst support matrices for the development of photocatalytic materials and indicated a large potential for the exploitation of their peculiar features.

In the present work, rice husks (RHs), which, worldwide, represent one of the most abundant agricultural wastes in terms of their quantity, have been treated and fractionated in order to allow for their complete valorization. RHs coming from the raw and parboiled rice production have been submitted at first to a hydrothermal pretreatment followed by a deep eutectic solvent fractionation, allowing for the separation of the different components by means of an environmentally friendly process. The lignins obtained from raw and parboiled RHs have been thoroughly characterized and showed similar physico-chemical characteristics, indicating that the parboiling process does not introduce obvious lignin alterations. In addition, a preliminary evaluation of the potentiality of such lignin fractions as precursors of cement water reducers has provided encouraging results. A fermentation-based optional preprocess has also been investigated. However, both raw and parboiled RHs demonstrated a poor performance as a microbiological growth substrate, even in submerged fermentation using cellulose-degrading fungi. The described methodology appears to be a promising strategy for the valorization of these important waste biomasses coming from the rice industry towards a circular economy perspective.

In the present work, brewers’ spent grain (BSG), which represents the major by-product of the brewing industry, was recovered from a regional brewery and fractionated in order to obtain a complete valorization. In particular, the whole process was divided in two main parts. A first pretreatment with hot water in an autoclave allowed the separation of a solution containing the soluble proteins and sugars, which accounted for 25% of the total starting biomass. This first step allowed the preparation of a medium that was successfully employed as a valuable growing medium for different microbial fermentations, leading to valuable fungal biomass as well as triglycerides with a high content of linear or branched fatty acids, depending on the microorganism used. The solid water-insoluble residue was then submitted to a lignocellulose deep eutectic solvent-mediated fractionation, which allowed the recovery of two important main fractions: BSG cellulose and BSG lignin. The latter product was tested as potential precursor for the development of cement water reducers with encouraging results. This combination of treatments of the waste biomass appeared to be a promising sustainable strategy for the development of the full exploitation of BSG from a circular economy perspective.

This systematic review investigates the potential of bergamot, a polyphenol-rich citrus fruit, in improving osteosarcopenic obesity, a condition characterized by the simultaneous presence of osteoporosis, obesity, and sarcopenia. Bergamot extracts have been suggested to possess several pharmacological properties, including anti-inflammatory and antioxidant effects, which could be useful in the management of age-related diseases and neuromuscular health. The review highlights the promising effects of bergamot extracts on skeletal muscle mass and function, particularly in the context of obesity, metabolic syndrome, osteosarcopenic obesity, and osteoporosis. Furthermore, some studies have shown that bergamot extracts can improve the metabolic balance, endothelial function, and maximal oxygen uptake in athletes, highlighting their potential benefits for skeletal muscle health. Taken together, these results suggest that bergamot extracts, especially those rich in polyphenols, may be a valuable adjunct in the management of osteosarcopenic obesity and other associated clinical conditions involving pro-inflammatory effects on organs and tissues.

The availability of immobilized nanostructured photocatalysts is of great importance in the purification of both polluted air and liquids (e.g., industrial wastewaters). Metal-supported titanium dioxide films with nanotubular morphology and good photocatalytic efficiency in both environments can be produced by anodic oxidation, which avoids release of nanoscale materials in the environment. Here we evaluate the effect of different anodizing procedures on the photocatalytic activity of TiO2 nanostructures in gas and liquid phases, in order to identify the most efficient and robust technique for the production of TiO2 layers with different morphologies and high photocatalytic activity in both phases. Rhodamine B and toluene were used as model pollutants in the two media, respectively. It was found that the role of the anodizing electrolyte is particularly crucial, as it provides substantial differences in the oxide specific surface area: nanotubular structures show remarkably different activities, especially in gas phase degradation reactions, and within nanotubular structures, those produced by organic electrolytes lead to better photocatalytic activity in both conditions tested.

In compliance with the national legal framework, the regional offices (CFDs) of the Italian Civil Protection Department have the daily duty to issue warnings to the local population on the account of the weather and hydrology‐related impacts, predicted by forecast models and refined through their expertise and experience: this composite of objective (model) and subjective (analyst) assessments are both contributing to the actual colour‐coded warning system. Given its hybrid nature, it is of paramount importance to evaluate the predictive ability of the warning decision‐making process as a whole. To this end, this study compares the return period T of the occurred flood (estimated through an hydrological model fed with observations) to the warning level that was issued. The novelty of this approach is that, by applying this methodology extensively in space and time, the probability curves of the variable T for each warning level are computed, allowing to evaluate the consistency between the warnings and the actual (estimated) severity of the event. As results suggest, the national early warning system is proven to be overall reliable for most cases, though very fine scale events (e.g., severe, localised, short‐lived thunderstorms) are still an open challenge.

Background Neuroglial cells that provide homeostatic support and form defence of the nervous system contribute to all neurological disorders. We analyzed three major types of neuroglia, astrocytes, oligodendrocytes, and microglia in the brains of an animal model of autism spectrum disorder, in which rats were exposed prenatally to antiepileptic and mood stabilizer drug valproic acid; this model being of acknowledged clinical relevance. Methods We tested the autistic-like behaviors of valproic acid-prenatally exposed male rats by performing isolation-induced ultrasonic vocalizations, the three-chamber test, and the hole board test. To account for human infancy, adolescence, and adulthood, such tasks were performed at postnatal day 13, postnatal day 35, and postnatal day 90, respectively. After sacrifice, we examined gene and protein expression of specific markers of neuroglia in hippocampus, prefrontal cortex, and cerebellum, these brain regions being associated with autism spectrum disorder pathogenesis. Results Infant offspring of VPA-exposed dams emitted less ultrasonic vocalizations when isolated from their mothers and siblings and, in adolescence and adulthood, they showed altered sociability in the three chamber test and increased stereotypic behavior in the hole board test. Molecular analyses indicate that prenatal valproic acid exposure affects all types of neuroglia, mainly causing transcriptional modifications. The most prominent changes occur in prefrontal cortex and in the hippocampus of autistic-like animals; these changes are particularly evident during infancy and adolescence, while they appear to be mitigated in adulthood. Conclusions Neuroglial pathological phenotype in autism spectrum disorder rat model appears to be rather mild with little signs of widespread and chronic neuroinflammation.

Systemic lupus erythematosus (SLE) patients have an increased risk of cardiovascular disease and thrombotic events, and the presence of antiphospholipid antibodies further raises the risk of these complications. Here we report a case of a patient with SLE and triple positivity for antiphospholipid antibodies who developed a popliteal artery thrombosis in the context of a severe hyperhomocysteinemia after the introduction of methotrexate (MTX) treatment. MTX is one of the most prescribed medications for a wide spectrum of autoimmune diseases, including SLE. On the other hand, by interfering with folate metabolism, it may induce hyperhomocysteinemia, which, in turn, may increase the risk of vascular complications. Current recommendations suggest screening and, when possible, treating classical and disease-related cardiovascular risk factors in all lupus patients. Based on what observed in our case, we suggest a follow-up of homocysteine levels after the introduction of drugs capable of inducing hyperhomocysteinemia, such as MTX, in SLE patients at high cardiovascular risk.

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.