Search Results (10)

The aim of our study was to predict the occurrence of distant metastases in non-small-cell lung cancer (NSCLC) patients using machine learning methods and texture analysis of ¹⁸F-labeled 2-deoxy-d-glucose Positron Emission Tomography/Computed Tomography {[¹⁸F]FDG PET/CT} images. In this retrospective and single-center study, we evaluated 79 patients with advanced NSCLC who had undergone [¹⁸F]FDG PET/CT scan at diagnosis before any therapy. Patients were divided into two independent training (n = 44) and final testing (n = 35) cohorts. Texture features of primary tumors and lymph node metastases were extracted from [¹⁸F]FDG PET/CT images using the LIFEx program. Six machine learning methods were applied to the training dataset using the entire panel of features. Dedicated selection methods were used to generate different combinations of five features. The performance of selected machine learning methods applied to the different combinations of features was determined using accuracy, the confusion matrix, receiver operating characteristic (ROC) curves, and area under the curve (AUC). A total of 104 and 78 lesions were analyzed in the training and final testing cohorts, respectively. The support vector machine (SVM) and decision tree methods showed the highest accuracy in the training cohort. Seven combinations of five features were obtained and introduced in the models and subsequently applied to the training and final testing cohorts using the SVM and decision tree. The accuracy and the AUC of the decision tree method were higher than those obtained with the SVM in the final testing cohort. The best combination of features included shape sphericity, gray level run length matrix_run length non-uniformity (GLRLM_RLNU), Total Lesion Glycolysis (TLG), Metabolic Tumor Volume (MTV), and shape compacity. The combination of these features with the decision tree method could predict the occurrence of distant metastases with an accuracy of 74.4% and an AUC of 0.63 in NSCLC patients. Full article

The growing worldwide problem of wastewater management needs sustainable methods for conserving water supplies while addressing environmental and economic considerations. With the depletion of freshwater supplies, wastewater treatment has become critical. An effective solution is needed to efficiently treat the organic contaminants departing from wastewater treatment plants (WWTPs). Photocatalysis appears to be a viable method for eliminating these recalcitrant micropollutants. This study is focused on the degradation of Reactive Black 5 (RB5), a typical contaminant from textile waste, using a photocatalytic method. Titanium dioxide (TiO₂) was deposited on a novel luminous fabric and illuminated using a light-emitting diode (LED). The pollutant degrading efficiency was evaluated for two different light sources: (i) a UV lamp as an external light source and (ii) a cold LED. Interestingly, the LED UV source design showed more promising results after thorough testing at various light levels. In fact, we note a 50% increase in mineralization rate when we triple the number of luminous tissues in the same volume of reactor, which showed a clear improvement with an increase in compactness. Full article

Energy efficiency in high-density urban areas is increasingly gaining more attention as the energy crisis and environmental issues worsen. Urban morphology is an essential factor affecting the energy consumption and solar energy development potential of buildings. In response to the research gap of previous studies that only analyzed building energy consumption or solar energy potential from a single objective, this paper aims to combine the two objectives of block-scale building energy consumption and solar development potential to explore the joint influence of urban residential morphological elements on correlations between the two. By investigating and summarizing 100 sample cases of Wuhan city blocks, 30 urban residential block prototypes were constructed. The correlations between the leading morphological indicators of the blocks with the building energy consumption and solar energy potential of the residential prototypes were quantified, respectively. The study results show that at certain floor area ratios, the highest solar power generation can be achieved with a mixture of high-rise slabs and high-rise towers, but the building energy intensity level is relatively high; combining building energy consumption and solar power generation, the residential block form of high-rise towers and low-rise villas has incredible energy-saving potential. In addition, the regression analysis results show that three block form indicators, namely the roof-to-envelope area ratio, compacity, and site coverage, have the most prominent influence on building energy intensity and solar power generation, and they all show positive correlations. This study can provide suggestions for urban residential planners and managers to promote urban energy conservation at the design stage. Full article

The delayed healing of chronic wounds, such as diabetic foot ulcers (DFUs), is a clinical problem. Few dressings can promote wound healing by satisfying the demands of chronic wound exudate management and tissue granulation. Therefore, the aim of this study was to prepare a high-absorption polyurethane (PU) foam dressing modified by polyethylene glycol (PEG) and triethoxysilane (APTES) to promote wound healing. PEG-modified (PUE) and PEG/APTES-modified (PUESi) dressings were prepared by self-foaming reactions. Gauze and PolyMem were used as controls. Next, Fourier transform-infrared spectroscopy, thermomechanical analyses, scanning electron microscopy and tensile strength, water absorption, anti-protein absorption, surface dryness and biocompatibility tests were performed for in vitro characterization. Wound healing effects were further investigated in nondiabetic (non-DM) and diabetes mellitus (DM) rat models. The PUE and PUESi groups exhibited better physicochemical properties than the gauze and PolyMem groups. Moreover, PUESi dressing showed better anti-adhesion properties and absorption capacity with deformation. Furthermore, the PUESi dressing shortened the inflammatory phase and enhanced collagen deposition in both the non-DM and DM animal models. To conclude, the PUESi dressing not only was fabricated with a simple and effective strategy but also enhanced wound healing via micronegative-pressure generation by its high absorption compacity with deformation. Full article

Introduction: We assessed the performance of F-18 fluorodeoxyglucose positron emission tomography (FDG PET)-based radiomics for the prediction of tumor mutational burden (TMB) and prognosis using a machine learning (ML) approach in patients with stage IV colorectal cancer (CRC). Methods: Ninety-one CRC patients who underwent pretreatment FDG PET/computed tomography (CT) and palliative chemotherapy were retrospectively included. PET-based radiomics were extracted from the primary tumor on PET imaging using the software LIFEx. For feature selection, PET-based radiomics associated with TMB were selected by logistic regression analysis. The performances of seven ML algorithms to predict high TMB were compared by the area under the receiver’s operating characteristic curves (AUCs) and validated by five-fold cross-validation. A PET radiomic score was calculated by averaging the z-score of each radiomic feature. The prognostic power of the PET radiomic score was assessed using Cox proportional hazards regression analysis. Results: Ten significant radiomic features associated with TMB were selected: surface-to-volume ratio, total lesion glycolysis, tumor volume, area, compacity, complexity, entropy, correlation, coarseness, and zone size non-uniformity. The k-nearest neighbors model obtained the good performance for prediction of high TMB (AUC: 0.791, accuracy: 0.814, sensitivity: 0.619, specificity: 0.871). On multivariable Cox regression analysis, the PET radiomic score (Hazard ratio = 4.498, 95% confidential interval = 1.024–19.759; p = 0.046) was a significant independent prognostic factor for OS. Conclusions: This study demonstrates that PET-based radiomics are useful image biomarkers for the prediction of TMB status in stage IV CRC. PET radiomic score, which integrates significant radiomic features, has the potential to predict survival in stage IV CRC patients. Full article

Through theoretical analysis, this paper preliminarily puts forward the optimization design method of a mix proportion large stone permeable mixture based on target voidage. The optimized large stone permeable mixture is abbreviated as OLSPM (optimization large stone permeable mixture). On this basis, the asphalt content was verified by leakage analysis experiment, and the molding method was determined by comparing the volume parameter changes and the appearance of the specimen in the molding process of both a Marshall compaction test and rotary compaction test. The final experimental analysis results show that the asphalt content calculated by this method can meet the technical requirements of leakage loss. The rotary compaction method is the suitable molding method for indoor cylindrical specimens of OLSPM, and the voidage is used as the index to control the compac-tion times of OLSPM. Under the same voidage, OLSPM-25 has more fine aggregates and thus leads to a relatively large amount of asphalt. In addition, the content of 4.75–19 mm coarse aggregate in its coarse aggregate is also higher than that of LSPM-25. Full article

Objective: To compare the radiomic features of F-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and intratumoral heterogeneity according to tumor budding (TB) status and to develop a prediction model for the TB status using the radiomic feature of ¹⁸F-FDG PET/CT in patients with cervical cancer. Materials and Methods: Seventy-six patients with cervical cancer who underwent radical hysterectomy and preoperative ¹⁸F-FDG PET/CT were included. We assessed the status of intratumoral budding (ITP) and peritumoral budding (PTB) in all available hematoxylin and eosin-stained specimens. Three conventional metabolic parameters and fifty-nine features were extracted and analyzed. Univariate analysis was used to identify significant metabolic parameters and radiomic findings for TB status. The prediction model for TB status was built using 3 machine learning classifiers (random forest, support vector machine, and neural network). Results: Univariate analysis led to the identification of 2 significant metabolic parameters and 12 significant radiomic features according to intratumoral budding (ITB) status. Among these parameters, following multivariate analysis for the ITB status, only compacity remained significant (odds ratio, 5.0047; 95% confidence interval, 1.1636–21.5253; p = 0.0305). Two conventional metabolic parameters and 25 radiomic features were selected by the Lasso regularization, and the prediction model for the ITB status had a mean area under the curve of 0.762 in the test dataset. Conclusion: Radiomic features of ¹⁸F-FDG PET/CT were associated with the ITB status. The prediction model using radiomic features successfully predicted the TB status in patients with cervical cancer. The prediction models for the ITB status may contribute to personalized medicine in the management of patients with cervical cancer. Full article

The Japanese city presents a certain number of peculiarities in the organization of its physical space (weak zoning regulations, fast piecemeal destruction/reconstruction of buildings and blocks, high compacity, incremental reorganization). Compared to countries where urban fabrics are more perennial and easily distinguishable (old centers, modern planned projects, residential areas, etc.), in Japanese metropolitan areas we often observe higher heterogeneity and more complex spatial patterns. Even within such a model, it should be possible to recognize the internal organization of the physical city. The aim of this paper is thus to study the spatial structure of the contemporary Japanese city, generalizing on the case study of Osaka and Kobe. In order to achieve this goal, we will need to identify urban forms at different local scales (building types, urban fabrics) and to analyze them at a wider scale to delineate morphological regions and their structuring of the overall layout of the contemporary Japanese city. Several analytical protocols are used together with field observations and literature. The results, and more particularly the building and urban fabric types and their location within the Osaka-Kobe metropolitan area, are interpreted in the light of Japanese history and model of urbanization. A synoptic graphical model of an urban morphological structure based upon Osaka is produced and proposed as an interpretative pattern for the Japanese metropolitan city in general. Full article

Using two GEOBIA (Geographical Object Based Image Analysis) algorithms on a set of segmented images compared to grid partitioning at different scales, we show that statistical metrics related to both objects and sets of pixels are (more or less) subject to the Modifiable Areal Unit Problem. Subsequently, even in a same spatial partition, there may be a bias in statistics describing the objects due to some size effect of the pixel samples. For instance, pixels homogeneity based on Grey Level Cooccurrence Matrices (GLCM), Landscape Shape Index, entropy, object compacity, perimeter/area ratio are studied according to scale. The approach consists in studying the behavior of a given statistical metrics through scales and to compare the results on several image segmentations, according to different partitioning processes, from GEOBIA (Baatz & Schäpe algorithm and Self Organizing Maps) or using reference grids. We finally discuss about the relationship between GEOBIA metrics and scale. By analysing object shape and pixels composition from different metrics points of views, we show that GEOBIA does not always mitigate the Modifiable Areal Unit Problem. Full article

The aim of this paper is to identify a parameterization method that considers existing connections and relationships between traditional indicators of environmental sustainability as a step in combating climate change via urban strategies. A typical Mediterranean city (Ancona, Italy) is investigated with a multi-objective optimization platform called modeFrontier, which uses Pareto optimality. This concept formalizes the trade-off between a given set of mutually contradicting objectives, such as high thermal comfort and low energy consumption, to identify a set of Pareto solutions. A solution is Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the others. The optimization process employs given constraints (for example, meteorological scenarios with high temperature and low winds or morphological building parameters), custom procedural algorithms (recursive algorithms to generate the set of all non-dominated objective parameters), and genetic algorithms (inspired by the natural selection process) to examine a wide urban space and identify interesting relationships among relevant variables for typical summer scenarios. Multi-objective optimizers involve many evaluations of two objectives (i.e., energy consumption and thermal comfort in this study) while considering many analytical constraints. This approach entails a considerably more exhaustive search of environmental variables that can help the urban planning process to mitigate the urban heat island (UHI) effect. Three quantitative metrics related to urban morphology and local climate conditions, as well as a thermal comfort indicator (the predicted mean vote), are defined and applied to Ancona to examine the potential for new sustainability in urban design. The results show that two parameters examined—compacity and a building-scale energy indicator—can offer insight when designing comfortable cities, while a citywide energy indicator shows that it is more difficult to find optimal solutions when dealing with the city as a whole. The research serves as a proof-of-concept and the possibility of identifying some local strategies in order to combat the UHI is verified. Full article