This work focused on the nutritional and technological evaluation of pancakes fortified with increasing Acheta domesticus powder (AP) levels. Scientific literature underscores AP's potential as an ...ingredient in bakery formulations due to its notable fiber and protein content. Thus, we formulated different pancake samples by replacing wheat flour (WF) with 10, 20, and 30% of AP, denoted as AP10, AF 20, and AP30, respectively, alongside a control sample (CP). We evaluated Water Absorption Capacity (WAC) and Water Solubility Index (WSI) on WF, AP, different WF and AP mixes, and batters' rheology. Lastly, we assessed the pancakes' physical, technological, and compositional parameters. The consistency index, flow index, and density increased from CP to AP30. A similar trend was observed for the textural parameter of hardness and chewiness, while cohesiveness slightly decreased. The pancake diameter and height were higher in fortified samples than in CP. A noticeable shift from brighter to darker color was observed from CP to AP30, with an increase in the a* (toward red) and b* parameters (toward blue). AP can represent a valuable ingredient for baked good fortification.
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•A. Domesticus is a promising protein source in food fortification.•Pancake fortification with A. Domesticus powder was developed.•Rheological and textural parameters of fortified pancakes were evaluated.•Nutritional properties of fortified pancakes were evaluated.•The attribution of nutritional claims in fortified pancakes was assessed.
The aim of this study was to evaluate the prognostic value of PET-derived metabolic features and textural parameters of primary tumors in pediatric sarcoma patients.
The imaging findings of 43 ...patients (14 girls and 29 boys; age 11.4 ± 4.4 years) who underwent 18-fluorodeoxyglucose positron emission tomography (PET)/computed tomography for primary staging prior to therapy between 2005 and 2020 were retrospectively evaluated. The diagnoses were osteosarcoma in 10, rhabdomyosarcoma in 10, and Ewing sarcoma in 23 patients. PET metabolic data and textural features of primary tumors were obtained. Cox proportional hazards regression models were used to identify predictors for progression-free survival and overall survival. Survival curves were estimated by using the Kaplan-Meier method.
Distant metastases were detected in primary staging in 13 patients (30.2%). The median follow-up duration after diagnosis was 28 months (range: 10-171 months). In multivariate Cox regression analysis, the presence of distant metastasis and neighborhood grey-level difference matrix_Contrast (ngldm_Contrast) were found as independent predictors for both progression-free survival and overall survival. Grey-level zone length matrix_Zone-length nonuniformity (glzlm_ZLNU) was also found as an independent predictor for overall survival. The Kaplan-Meier survival analysis showed that higher ngldm_Contrast and glzlm_ZLNU values of primary tumors were significantly associated with shorter progression-free survival and overall survival.
In addition to the presence of distant metastasis at initial diagnosis, textural features of primary tumors may be used as prognostic biomarkers to identify patients with worse prognosis in pediatric sarcoma. Higher tumor heterogeneity is significantly associated with shorter progression-free survival and OS.
The current study is focused on the successful fabrication and characterization of microstructure and properties gradient composite made of 3 mm thick sheets of AA5083-O, AA6061-T6, and AA7075-T6 ...alloys using friction stir additive manufacturing (FSAM) technique. Two combinations of four layered FSAM builds (6756 and 7567) were fabricated successfully without any major defects at the optimized process parameters of 850 rpm (tool rotational speed) and 55 mm/min (tool transverse speed). The material mixing, interfacial bonding features, microstructure evolution, and mechanical performance within the stir zones (SZ) were thoroughly examined using advanced characterization techniques. Electron backscatter diffraction (EBSD) analysis confirmed a gradient microstructure along the build depth in both FSAM builds, with average grain sizes decreasing from 52 μm (AA5083), 46 μm (AA6061), and 40 μm (AA7075) in base metals to ∼ 4–7 μm within the SZ. The remarkable grain refinement within the SZ was mainly attributed to the dominant presence of the continuous dynamic recrystallization (CDRX) mechanism. Texture analysis corresponding to pole figures (PFs) and orientation distribution function (ODF) plots reveals the crystallographic texture evolution along the build depth. The prevalent existence of B/ B‾ and C textures throughout all regions of the FSAM builds affirms the presence of ample shear strain during the FSAM procedure. Through thickness miniature tensile and microhardness tests depict the gradient in mechanical performance for both the FSAM builds along the build depth. Microhardness gradients in the range from ∼ 80 HV0.1 to ∼ 145 HV0.1 were observed along the build depth. The axial sample in the build direction shows appreciable strength (265 MPa and 224 MPa) and uniform elongation (28 % and 24 %) for 6756 and 7567 FSAM build, respectively. Furthermore, remarkable strain hardening behaviour corresponding to hardening capacity (Hc) and hardening exponent (n) was noticed for both the axial build samples compared to AA6061-T6 and AA7075-T6 base metals. These findings underscore the potential of FSAM in fabricating functionally gradient composite materials tailored to specific functional requirements.
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•The FSAM technique has been used to fabricate two combination of defect-free FGCM using AA5083-O/AA6061-T6/AA7075-T6 alloys.•Fine-grained microstructure with appreciable material mixing at the interfacial region is noticed within the stir zones.•Tensile properties in the build direction shows remarkable strength and ductility with appreciable strain-hardening behavior.•The dominant presence of recrystallization textures within the SZ confirms the prominent presence of the CDRX mechanism.•The findings underscore the potential of FSAM in fabricating functionally gradient composite materials for specific functional requirements.
•We proposed a fruit-classification system that can recognize 18 types of fruits.•We used a hybrid feature set with color, texture, and shape information.•We used FNN as the classifier that is ...trained by FSCABC algorithm.•FSCABC–FNN obtained better classification accuracy than existing algorithms.
Fruit classification is a difficult challenge due to the numerous types of fruits. In order to recognize fruits more accurately, we proposed a hybrid classification method based on fitness-scaled chaotic artificial bee colony (FSCABC) algorithm and feedforward neural network (FNN). First, fruits images were acquired by a digital camera, and then the background of each image were removed by split-and-merge algorithm. We used a square window to capture the fruits, and download the square images to 256×256. Second, the color histogram, texture and shape features of each fruit image were extracted to compose a feature space. Third, principal component analysis was used to reduce the dimensions of the feature space. Finally, the reduced features were sent to the FNN, the weights/biases of which were trained by the FSCABC algorithm. We also used a stratified K-fold cross validation technique to enhance the generation ability of FNN. The experimental results of the 1653 color fruit images from the 18 categories demonstrated that the FSCABC–FNN achieved a classification accuracy of 89.1%. The classification accuracy was higher than Genetic Algorithm–FNN (GA–FNN) with 84.8%, Particle Swarm Optimization–FNN (PSO–FNN) with 87.9%, ABC–FNN with 85.4%, and kernel support vector machine with 88.2%. Therefore, the FSCABC–FNN was seen to be effective in classifying fruits.
Characteristic attributes of pea-protein fortified, extruded rice snacks were evaluated by mechanical, acoustic and descriptive sensory analysis. The addition of pea protein isolate (0 to 45% (w/w)) ...to rice flour and extruder screw speed strongly affected the expansion behaviour and therefore, textural attributes of extruded snack products. The sensory panel described the texture of highly expanded extrudates as crisp, while low expanded extrudates were perceived as hard, crunchy and non-crisp. Results of the instrumental and sensory analysis were compared and showed a high correlation between mechanical and sensory hardness (r=0.98), as well as acoustic and sensory crispness (r=0.88). However, poor and/or negative correlations between acoustic and sensory hardness and crunchiness were observed (r=−0.35 and −0.84, respectively).
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•Pea protein content affected hardness, crunchiness and crispness of extruded snacks•Maximum expansion and crispness was observed at a pea protein content of 13%.•Pea protein content of 45% resulted in hard, crunchy and non-crisp extrudates.•Mechanical and sensory hardness were positively correlated.•Acoustic hardness did not correlate well with sensory perceived hardness.
Retina is an important body organ responsible for human vision. There are many important retinal diseases which may damage the vision and even cause blindness. Optical Coherence Tomography (OCT) is ...an important tool for verifying and evaluating retina. Moreover, retina is a window to brain and since the imaging from retina is simpler than brain, valuable information from brain can be obtained through retinal imaging. In fact, many neuro-degenerative diseases can be followed through retinal OCT images. Texture refers to the way of locating pixels with different intensity values in an image neighborhood. In this paper, the purpose is to provide a review on the methods which focus on the anomaly detection in OCT images. Also, the role of texture in the identification of retinal diseases is discussed in detail. Different texture descriptors in image processing applications are introduced and the methods which utilized them for the mentioned purpose are explained. In addition, different retinal diseases are classified in several classes and the texture-based methods suggested for each class of diseases are separately described.
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Generic cosmetic creams (oil-in-water emulsions) were prepared using dry Bacterial Cellulose and Carboxymethyl Cellulose (BC:CMC) to study the possibility of partially or completely ...replacing surfactants, while ensuring a long-term stability and the required organoleptic characteristics. BC:CMC was benchmarked against two hydrocolloidal Avicel products (PC-591 and PC-611), commonly used as thickeners and stabilizing aids in cosmetics production. The emulsions were then characterized regarding storage stability, rheology, texture and microscopic features.
The full replacement of 5.5 % surfactants with only 0.75 % BC:CMC consistently showed similar results to those obtained with surfactants, namely concerning viscosity and texture. Although producing emulsions with larger oil droplets, BC:CMC provided for a very effective stabilization through a Pickering effect and by structuring the continuous phase. The more effective Avicel tested (PC-591) required a higher concentration (1.5 %) to achieve similar rheological profile but was ineffective in stabilizing the oil phase in a surfactant-free formulation with the adopted protocol. By replacing surfactants, dry BC:CMC matches a strong market need since both end users and manufacturers increasingly seek natural ingredients for cosmetic formulations.
Automatic classification of fruits via computer vision is still a complicated task due to the various properties of numerous types of fruits. We propose a novel classification method based on a ...multi-class kernel support vector machine (kSVM) with the desirable goal of accurate and fast classification of fruits. First, fruit images were acquired by a digital camera, and then the background of each image was removed by a split-and-merge algorithm; Second, the color histogram, texture and shape features of each fruit image were extracted to compose a feature space; Third, principal component analysis (PCA) was used to reduce the dimensions of feature space; Finally, three kinds of multi-class SVMs were constructed, i.e., Winner-Takes-All SVM, Max-Wins-Voting SVM, and Directed Acyclic Graph SVM. Meanwhile, three kinds of kernels were chosen, i.e., linear kernel, Homogeneous Polynomial kernel, and Gaussian Radial Basis kernel; finally, the SVMs were trained using 5-fold stratified cross validation with the reduced feature vectors as input. The experimental results demonstrated that the Max-Wins-Voting SVM with Gaussian Radial Basis kernel achieves the best classification accuracy of 88.2%. For computation time, the Directed Acyclic Graph SVMs performs swiftest.
Background and objective
Prediction of disease course in patients with progressive pulmonary fibrosis remains challenging. The purpose of this study was to assess the prognostic value of lung ...fibrosis extent quantified at computed tomography (CT) using data‐driven texture analysis (DTA) in a large cohort of well‐characterized patients with idiopathic pulmonary fibrosis (IPF) enrolled in a national registry.
Methods
This retrospective analysis included participants in the Australian IPF Registry with available CT between 2007 and 2016. CT scans were analysed using the DTA method to quantify the extent of lung fibrosis. Demographics, longitudinal pulmonary function and quantitative CT metrics were compared using descriptive statistics. Linear mixed models, and Cox analyses adjusted for age, gender, BMI, smoking history and treatment with anti‐fibrotics were performed to assess the relationships between baseline DTA, pulmonary function metrics and outcomes.
Results
CT scans of 393 participants were analysed, 221 of which had available pulmonary function testing obtained within 90 days of CT. Linear mixed‐effect modelling showed that baseline DTA score was significantly associated with annual rate of decline in forced vital capacity and diffusing capacity of carbon monoxide. In multivariable Cox proportional hazard models, greater extent of lung fibrosis was associated with poorer transplant‐free survival (hazard ratio HR 1.20, p < 0.0001) and progression‐free survival (HR 1.14, p < 0.0001).
Conclusion
In a multi‐centre observational registry of patients with IPF, the extent of fibrotic abnormality on baseline CT quantified using DTA is associated with outcomes independent of pulmonary function.
The extent of pulmonary fibrosis, measured objectively at baseline computed tomography using a deep learning algorithm, is associated with disease progression and mortality, independent of pulmonary function.
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