Skid resistance of a road pavement surface is the force developed when tyre is prevented from rotating slides along the pavement sur-face. This property comes from the combination of the macro- and micro-texture of pavement. The skid resistance of an asphalt pave-ment is an important parameter influencing driving safety on a road, since there is a proven relationship between skid resistance and accident parameters. The paper deals with the measurement principle of pavement skid resistance (surface friction) including longitudinal and transverse friction. A high number of measuring devices of skid resist-ance are also introduced highlighting their advantages and limitations. Besides, the measurement policies in the European Union and in Hun-gary are outlined. Pavement surface texture is investigated dealing with the levels of surface tex-ture, the most common measuring tech-niques, the macro-texture features of asphalt types, as well as the Hungarian regulation in the field. As a related topic, the aggregate properties and their implication in the relevant Hungarian specification are introduced briefly, as well. Some outcomes of the EU’s COST Ac-tion 354 on the development of unified European macro-roughness and skid resistance performance indicators and indices are also presented.

In many image processing and computer vision applications, the main aim is to describe image contents. So, different visual properties such as color, texture and shape are extracted to make aim. In this respect, texture information play important role in image description and visual pattern classification. Texture is referred to a specific local distribution of intensities that is repeated throughout the image. Since now different operations or descriptors have been proposed to analysis texture characteristics. In the multi object images specific texture operators usually doesn’t provide accurate results. So, in many cases, combination of texture operators are used to achieve more discriminant features. In this paper, some combination methods are survived to analysis effect of combinational texture features in image content description. Also, in the result part, different related methods are compared in terms of accuracy and computational complexity.

Many (if not a very large number) of metals and alloys evince substantial softening with torsion deformation to strains not usually achievable in tension. Of course, softening has long been observed by discontinuous dynamic recrystallization (DDRX) but this paper will discuss cases where softening is associated by texture development with large-strain deformation that is not reliant on changes in the dislocation hardening. This paper reviews the work of the current authors on FCC metals and alloys in this area and extends to a new discussion of BCC and HCP cases.

This paper compares a series of traditional and deep learning methodologies for the segmentation of textures. Six well-known texture composites first published by Randen and Hus{\o}y were used to compare traditional segmentation techniques (co-occurrence, filtering, local binary patterns, watershed, multiresolution sub-band filtering) against a deep-learning approach based on the U-Net architecture. For the latter, the effects of depth of the network, number of epochs and different optimisation algorithms were investigated. Overall, the best results were provided by the deep-learning approach. However, the best results were distributed within the parameters, and many configurations provided results well below the traditional techniques.

Background: Objective quantitative texture characteristics may be helpful in salivary glandular tumor differential diagnosis. This study uses machine learning (ML) to explore and validate the performance of ultrasound (US) texture features in diagnosing salivary glandular tumors. Material and methods: 122 patients with salivary glandular tumors, including 71 benign and 51 malignant tumors, are enrolled. A representative brightness mode US pictures are selected for further Gray Level Co-occurrence Matrix (GLCM) texture analysis. We use t-test to test the significance and use receiver operating characteristic curve method to fund optimal cut-point for these significant features. After splitting 80% data into training set and 20% data into testing set, we use five machine learning models k-nearest Neighbors (kNN), Naïve Bayes, Logistic regression, Artificial Neural Networks (ANN) and supportive vector machine (SVM) to explore and validate the performance of US GLCM texture features in diagnosing salivary glandular tumors. Results: This study includes 49 female and 73 male patients, with a mean age of 53 years old, ranging from 21 to 93. We find that six GLCM texture features (contrast, inverse difference movement, entropy, dissimilarity, inverse difference and difference entropy) are significantly different between benign from malignant tumors (p<0.05). On ML, the overall accuracy rates are 74.3% (95%CI: 59.8-88.8%), 94.3% (86.6-100%), 72% (54-89%), 84% (69.5-97.3%) and 73.5% (58.7-88.4%) for kNN, Naïve Bayes, Logistic regression, one node ANN and SVM, respectively. Conclusion: US texture analysis with ML has potential as an objective and valuable tool for assessment of salivary gland tumors.

Soil structure is a sensitive and dynamic soil physical property which responds rapidly to different tillage systems, and thus it requires constant monitoring and evaluation. The visual evaluation of soil structure (VESS) and subsoil visual evaluation of soil structure (SubVESS) methods were used to assess the soil structure quality of clayey soils subjected to different tillage systems. The tillage systems were no-tillage (NT), conventional tillage (CT) and virgin land (VG). The study was conducted at Tshivhilwi and Dzingane in Thohoyandou, Vhembe District, Limpopo Province, South Africa. The NT system was practised for 8 and 40+ years at Tshivhilwi and Dzingahe, respectively. The results showed no impact of tillage system on both VESS and SubVESS at Tshivhilwi. The soil structure quality at Tshivhilwi as determined by VESS and SubVESS were found to be poor. However, at Dzingahe, both the VESS and SubVESS responded to the impact of tillage. At Dzingahe VESS showed a fair (Sq = 2.25) soil structural quality in the NT system, poor (Sq = 3.57) in the CT system and moderately poor (Sq = 3.05) in the VG. Similarly, at the same location the SubVESS scores were moderately good in the NT system, moderately poor for CT system and fair in the VG. The differences in the response of the VESS and SubVESS at the two locations were attributed to the differences in the duration at which the NT systems were practised. The VESS and SubVESS results were supported by selected measured soil physicochemical properties such as bulk density and porosity. In conclusion, the findings of this study showed that the VESS and SubVESS were able to effectively differentiate the impact of tillage systems on soil structural quality in clayey soils where NT was practised for a long period (40+ years) while it could not where NT was practised for a few years (8 years).

Texture has long been considered an important attribute for food acceptance. However, which specific textural characteristics contribute to overall acceptance of a food is not well understood. It has been suggested that texture contrasts and combinations are a universal feature in giving foods a desirable texture, yet this notion is largely based upon anecdotal data. This study uses multiple survey research methods to assess the importance of texture contrast and combinations across cultures (Poland, U.S.A., and Singapore). Participants (n = 288) completed a survey that included overt measures of food texture contrast importance as well as free response questions regarding texture. The overall importance of texture for food liking was not different across the populations. However, the participants from Singapore and Poland gave more importance to a desirable food having multiple textures than the U.S.A. cohort. When looking at free responses, participants were twice as likely to mention combinations (multiple textures) with a texture contrast when describing foods they liked, in comparison to foods they disliked. This was observed across all 3 cultures. However, the type and quantity of texture terms used within combinations were different among cultures. For instance, Asians enjoyed more texturally diverse food combinations than the other two cultures. These findings highlight the importance of texture contrasts and combinations in three distinct cultures.

This paper presented a feature vector using a different statistical texture analysis of brain tumor from MRI image. The statistical feature texture is computed using GLCM (Gray Level Co-occurrence Matrices) of Brain Nodule structure. For this paper, the brain nodule segmented using strips method to implemented marker watershed image segmentation based on PSO (Particle Swarm Optimization) and Fuzzy C-means clustering (FCM). Furthermore, the four angles 0^o, 45^o, 90^o and 135^o are calculated the segmented brain image in GLCM. The four angular directions are calculated using texture features are correlation, energy, contrast and homogeneity. The texture analysis is performed a different types of images using past years. So the algorithm proposed statistical texture features are calculated for iterative image segmentation. These results show that MRI image can be implemented in a system of brain cancer detection.

Margarine exhibits significant variations in composition, allowing it to cater to diverse consumer segments. This study aimed to characterize the physical and sensory attributes of margarine samples available in the Brazilian market. Twelve commercial samples from six different brands, encompassing 30% to 80% of lipid contents, were subjected to instrumental texture analysis, sensory profiling, and hedonic assessment. A total of 112 consumers participated in acceptance tests and Check-All-That-Apply (CATA) evaluations, while another group of 62 subjects performed Projective Mapping. Samples with lipid percentages exceeding 70% achieved the highest average acceptance scores for taste and overall impression. The brand with the lowest lipid content (30%) exhibited a stronger association with negative attributes, including rancid flavor and aroma, bitterness, and metallic flavor, resulting in lower average scores for aroma, flavor, texture, and overall impression. However, these scores were not statistically different from those of samples with 50% and 60% lipid content. Reducing lipid levels in fat-based products such as margarine poses a challenge to food manufacturers, as consumers generally perceive higher lipid percentages as indicative of superior flavor quality.

In this paper were analyzed the effects of double reduction and annealing during rolling process on texture evolution in an ultrathin sheet of low carbon steel. Experimental samples were obtained from each process stage. EBSD technique and correlated tools as orientation density functions and pole figures were used to analyze the microstructural changes and the texture. Results show that {111} recrystallized grains were formed during process, reducing dramatically gamma-fibre texture intensity and generating an adequate finished product for deep die stamping.

The intentional damages to local Cultural Heritage sites carried out in recent months by the Islamic State have received wide coverage from the media worldwide. Earth Observation data provide important information to assess these damages in such non-accessible areas, and automated image processing techniques would be needed to speed up the analysis if a fast response is desired. This paper shows the first results of applying fast and robust change detection techniques to sensitive areas, based on the extraction of textural information and robust differences of brightness values related to pre- and post-disaster satellite images. A map highlighting potentially damaged buildings is derived, which could help experts at timely assessing the damages to the Cultural Heritage sites of interest. Encouraging results are obtained for two archaeological sites in Syria and Iraq.

The as-received commercial Inconel 718 material was solid solution heat treated (ST), cold rolled (CR), and precipitation hardened (PH) to investigate the effects of deformation on tensile properties, hardness, and texture. Three sets of specimens (0%, 20% and 50% CR) were STed at 1100 C/1h, CR and aged (720 °C/8 h + 650 °C/8 h) for the analysis. Ultimate tensile strength (UTS), 0.2% yield strength (YS) and elongation of 50% deformed condition were 1645 MPa, 1512 MPa, and 3.8 %, respectively. The 20 % deformation resulted in a balanced UTS (1348 MPa), YS (1202 MPa) and elongation (11%). Contributions of precipitation hardening to the strength was decreasing, while contribution of CR increases with increasing percentage of deformation. Correspondingly, the size and quantities of  decreased with increasing deformation level. In CR specimens, a high density of nano/micro twins were generated with the twin planes oriented perpendicular to the RD-ND surface. The preferred rotation of the crystals generated the gradient of orientation and internal features of the large austenitic grains. The cross-slip of screw dislocations induced a complete β-fibre, consisting of {110}, {112}, and{123}, with doubled intensity at higher deformation. In addition, the specimens tended to be highly susceptible to the twinning-induced orientation emerged by a predominant ⫽ND. An incomplete but intense α-fibre clustered between {110} and {110} was characterized in the as-deformed condition. Besides achieving highest strength, the current work demonstrates the effects of CR on the material strength without the complex influences of  precipitate.

This study aimed to investigate the incorporation of micronized salt (MS) to reduce sodium content in fresh sausages while preserving technological, chemical, textural, and sensory characteristics. Four treatments were prepared: control (C) with 2.0% regular salt; M2.0% with 2.0% micronized salt; M1.5% with 1.5% micronized salt; and M1.0% with 1.0% micronized salt. Half of the micronized salt treatment was mixed with the fat during the processing of the fresh sausages. It was possible to achieve a 50% reduction in sodium (M1.0%) in the fresh sausages without negative effects on most technological, chemical, and textural parameters, which did not differ from the control treatment (C). Conversely, "chewiness" decreased in M2.0% compared to the control (C) due to mixing micronized salt with the fat. The sodium reduction did not impact the temporal sensory profile and overall liking. Therefore, using micronized salt in fresh sausages reduces sodium content without affecting sensory traits and product stability.

Watermelon fruits of different ploidy exhibit significant variations in texture. In order to investigate the primary factors influencing texture differences, this study was conducted to investigate the differences in fruit texture development using homozygous autogamous diploid (2X)lines and their autotriploid (3X) and autotetraploid (4X) lines 'Yixuan'. The research encompassed fruit development, flesh texture profile analysis (TPA), flesh cell wall polysaccharide content, and flesh cell microstructure analysis, specifically in 2X, 3X, and 4X watermelon fruits.The results showed that as watermelon fruits matured, several characteristics exhibited an ascending trend, including fruit weight, TSS (total soluble solids) content, rind hardness, flesh cell size, and cell wall polysaccharide contents such as crude fiber, cellulose, hemicellulose, lignin, and protopectin. Conversely, the flesh texture parameters and soluble pectin content of the flesh cell wall gradually declined. Notably, significant differences in fruit flesh texture and flesh cell structure were observed among fruits of different ploidy at the 32d. Specifically, 2X fruits displayed considerably lower rind hardness, reduced flesh texture (Hardness, Fracturability, Chewiness, Gumminess), and cell density compared to 3X and 4X fruits. Additionally, 2X fruits exhibited larger cell sizes than 3X and 4X fruits. However, no significant differences were observed in the content of flesh cell wall polysaccharide contents across various ploidy levels.These findings suggested that the variation in texture among watermelon fruits of different ploidy can be attributed to the size and arrangement of flesh cells. Importantly, this research provided a foundation for further exploration of the intrinsic regulatory factors and molecular mechanisms contributing to texture variation in polyploid watermelon fruits.

Magnesium (Mg) alloy is a widely used lightweight metal structural material due to its high specific strength and stiffness, excellent damping performance, and recyclability. Wrought Mg alloys are widely favored in fields such as aerospace, transportation, and biomedical stents. However, most wrought Mg alloys with a hexagonal close-packed (HCP) crystal structure lack sufficient independent slip systems to meet the von Mises criterion for uniform plastic deformation at room temperature. This can result in the formation of strong basal texture during plastic deformation and poor room temperature plastic forming ability. Improving the room temperature forming performance is a crucial challenge that must be addressed to broaden the application of Mg alloy sheets. Our research group has comprehensively summarized significant work and latest research progress in improving the room temperature forming of Mg alloy sheets via extrusion technology in recent years. Specifically, we have developed a new type of asymmetric extrusion technology that combines material structure evolution, mechanical property, and forming behavior analysis. We have elucidated the extrusion process characteristics, texture control mechanism, and forming properties of Mg alloy sheets through plastic deformation mechanisms, mold design, and finite element numerical simulation. Our findings provide a novel extrusion technology for the fabrication of highly formable Mg alloy sheets, which can be utilized in various applications.

Thin-wall heat pipe is an efficient heat transfer component, which has been widely used in the field of heat dissipation of high-power electronic equipment in recent years. In this study, the orange peel morphology defect of thin-wall heat pipes after bending deformation was analyzed both for the macro 3D profile and for the micro-formation mechanism. The results show that after high temperature sintering treatment, the matrix grains of heat pipe are coarsened seriously and formed a strong Goss texture, while a certain annealing twins with the unique Copper orientation are retained. The distribution of Schmid factor value subjected to the uniaxial stress indicate the inhomogeneity of intergranular deformation exist among the annealing twins and matrix grains. The annealing twin exhibit a “hard-oriented” component during the deformation; thus, it plays a role as barrier and hinder the slipping of dislocation. As the strain accumulates, part of the annealing twins may protrude from the surface of heat pipe, forming a large-scale fluctuation of the surface as the so called the “orange peel” morphology. The 3D profile shows the bulged twins mostly perpendicular to the drawing direction, with about 200-300μm in width and 10-20μm in height.

Aloe Vera leaves have a great potential as an economic supplement with an adequate nutritional profile. In this study, Aloe Vera leaf gel (AVG) powder was used to fortify plain cakes. Freeze drying of AVG was performed for the production of Aloe Vera powder (ALP) and four plain cakes were prepared with different proportions of ALP for further investigation. Analysis suggested that ALP contained significantly (p<0.05) higher amount of protein (22.23 vs 12.24), ash (19.83 vs 0.64) and iron (175 vs 3.05) content than refined wheat flour (RWF). ALP also contained significant amount of total polyphenols and antioxidant. Moisture, protein, ash, weight, and minerals (Fe, Ca) content were higher (p<0.05) in ALP-cakes; whereas fat, volume, specific volume, height, baking loss, and total carbohydrate content were higher (p<0.05) in RWF-cakes. Incorporation of 6 and 8% ALP in the formulation increased the total polyphenols and anti-oxidant activity in plain cakes. Texture analysis revealed that hardness and chewiness increased in ALP-cakes but decreased in RWF-cakes, however, cohesiveness, springiness, and chewiness decreased in ALP-cakes. Sensory attributes suggested that 4% ALP incorporated cake was attributed as the best formulation. In conclusion, ALP can be supplemented in cakes up to 8% to improve the nutrient value.

Additive manufacturing (AM) technologies show potential for the development of functionally integrated lightweight designs, biomimetic structures and material savings. Typically, as-built surfaces show powder particle agglomerations and re-entrant features, leading to rough surfaces, which are associated with poor fatigue performance. To benefit from the full range of advantages with special focus on aerospace applications, critical features for crack initiation when subjected to fatigue loading need to be identified and mitigated. A first step toward achieving this goal is the surface texture characterisation based on the quantification of surface features. In this paper, selected areal height, functional and feature parameters from ISO 25178-2:2022 are generated and process-specific features are examined for as-built AlSi7Mg0.6 from laser powder bed fusion (PBF-LB). A connection with the particle size distribution of the used powder is demonstrated. It is shown that surface feature analysis opens up opportunities to use physically meaningful surface characteristics in future quality assurance and part qualification processes.

The commercial oxygen-free copper sheets were cold-rolled with reduction rates ranging from 20% to 87% reduction rate and annealed at 400, 500 and 600 °C. The microstructure and texture evolution during cold-rolling and annealing processes were studied using optical microscopy (OM), the scanning electron microscopy (SEM) and the electron back-scattered diffraction (EBSD). The results show that the deformation textures of {123} (S) , {112} (Copper) and {110} (Brass) were continuously enhanced with the increase of cold-rolling reduction. The orientations along the α-oriented fiber converged towards Brass and the orientation density of β fiber obviously increased when the rolling reduction exceeded 60%. The recrystallization texture was significantly affected by the cold-rolling reduction. After 60% cold-rolling reduction, Copper and S textures components gradually decreased and {011} recrystallization texture component formed with the increase of annealing temperature. After 87% cold-rolling reduction, a strong Cube texture formed and other textures were inhibited with the increase of annealing temperature. The strong Brass and S deformation texture was conducive to the formation of a strong Cube annealing texture. The density of annealing twin boundary decreased with the increase of annealing temperature, and more annealing twin boundaries formed in the oxygen-free copper sheets with the increase of cold rolling reduction.

Myofascial Pain Syndrome (MPS) is a prevalent chronic pain disorder characterized by myofascial trigger points (MTrPs). Current diagnosis relies on manual detection of MTrPs, which has low inter-rater reliability. This study aims to enhance diagnosis through machine learning (ML) and a combination of texture-features extracted from B-mode ultrasound (B-mode-US) images. Four texture-features were investigated: statistical-features, and their combination with Gabor, local binary (LBP), and SEGL, LBP + gray-level-co-occurrence-matrices + Edge for the classification of MTrPs on the B-mode-US images. B-mode-US images of trapezius muscles (n=90) were examined for MTrPs and healthy muscle. Three methods of LBP, SEGL, and Gabor were separately calculated for each B-mode-US image. Then, the statistical-features (e.g., entropy) were calculated over the B-mode-US images and those three methods. Seven Machine learning (ML) classifiers (e.g., neural network) with the calculated statistical-features were applied to discriminate MTrPs from healthy muscle. Additionally, traditional statistical analysis (i.e., ANOVA) was calculated between statistical-features within each method. The results indicated that the combination of statistical-features effectively discriminated between MTrPs and healthy muscles, based on traditional statistical analysis. However, ML classifiers struggled due to high variation and similar mean values among them. This discrepancy between them prompts further exploration of US texture-based automated ML for MTrPs diagnosis.

Texture is essential information for image representation, capturing patterns, and structures. Consequently, texture plays a crucial role in the manufacturing industry and has been extensively studied in the fields of computer vision and pattern recognition. However, real-world textures are susceptible to defects, which can degrade the image quality and cause various issues. Therefore, there is a need for accurate and effective methods to detect texture defects. In this study, a simple autoencoder and Fourier transform were employed for texture defect detection. The proposed method combines Fourier transform analysis with the reconstructed template obtained from the simple autoencoder. Fourier transform is a powerful tool for analyzing the frequency domain of images and signals. Moreover, analyzing the frequency domain enables effective defect detection because texture defects often exhibit characteristic changes in specific frequency ranges. The proposed method demonstrates effectiveness and accuracy in detecting texture defects. Experimental results are presented to evaluate its performance and compare it with those of existing approaches.

Kiwifruits are often exposed to various temperature fluctuation (TF) during postharvest storage. To evaluate the effect of TF on the qualities of kiwifruits, fruits were stored at 2 ºC, 2 ºC or 5 ºC (TF2ºC-5ºC), 2 ºC or 7 ºC (TF2ºC-7ºC), alternating every 12 h. Observations revealed that kiwifruits stored at constant 2 °C showed the lowest loss of weight and vitamin C due to the minimum ethylene production and respiratory rate compared to that of TF2ºC-5ºC and TF2ºC-7ºC. Moreover, the results of RT-qPCR verifed that the expression of genes encoding polygalacturonase, β-galacturonidase, and pectin methyl esterase was significantly increased by the treatment of TF. Hence, TF accelerated the degradation of the cell walls, softening, translucency and relative conductivity of the flesh of kiwifruits. Besides, the impact of TF2ºC-7ºC on kiwifruits was more significant relative to TF2ºC-5ºC. The present study provides a theoretical basis for kiwifruit during cold storage.

The texture properties of cooked rice are a dominant property which can indicate the eating quality. Evaluation of back extrusion (BE) test precision and sensitivity for cooked germinated brown rice (GBR) texture in production process was investigated in this study. BE test on texture properties of cooked GBR rice show high precision of measurement of hardness, toughness and stickiness tests which indicated by the repeatability and reproductivity test but the sensitivity indicated by coefficient of variation of the texture properties. The findings of the study of the effect of different soaking and aging duration in the production of Khao Dawk Mali 105 (KDML 105) GBR on cooked GBR texture measured by BE test confirmed the developed protocol for evaluation of high precision and sensitivity of the texture measurement method. Repeatability and reproducibility of reliable measurements have a low standard deviation of the farthest different between replicates, which is considered high precision. High coefficient of variation where the relative wide variation of the absolute value of the property can be detected indicate high sensitivity which even small resolution can be detected or vice versa. But the correlation coefficient among the texture properties by BE were not related to the precision or sensitivity of the test. By these results, the original protocol for determination of precision and sensitivity of food texture measurement was successfully verified as the usable evaluation protocol for GBR texture measurement.

Colorectal cancer (CRC) is one of the most common types of cancer worldwide. The KRAS mutation is present in 30-50% of CRC patients. This mutation confers resistance to treatment with anti-EGFR therapy. This article aims at proving that Computer Tomography (CT)-based Radiomics can predict the KRAS mutation in CRC patients. The piece is a retrospective study with 56 CRC patients from the Hospital of Santiago de Compostela, Spain. All patients had a confirmatory pathological analysis of the KRAS status. Radiomics features were obtained from the abdominal contrast enhancement CT (CECT), before applying any treatments. We used several classifiers, including adaboost, neural network, decision tree, support vector machine and random forest, to predict the presence or absence of KRAS mutation. The most reliable prediction was achieved using the adaboost ensemble on clinical patient data, with a kappa and accuracy of 53.7% and 76.8%, respectively. The sensitivity and specific were of 73.3% and 80.8%. Using texture descriptors, the best accuracy and kappa were 73.2% and 46%, respectively, with sensitivity and specificity of 76.7% and 69.2%, showing also a correlation between texture patterns on CT images and KRAS mutation. Radiomics could help manage CRC patients, and in the future, it could have a crucial role in diagnosing CRC patients ahead of invasive methods.

Obstructive sleep apnea (OSA) is multi-faceted world-wide distributed disorder exerting deep effects on the sleeping brain. In the latest years strong efforts have been dedicated to find novel measures assessing the real impact and severity of the pathology, traditionally trivialized by the simplistic apnea/hypopnea index. Due to the unavoidable connection between OSA and sleep we reviewed the key aspects linking the breathing disorder with sleep pathophysiology, focuings on the role of cyclic alternating pattern (CAP). Sleep structure, reflecting the degree of apnea-induced sleep instability, may provide topical informations to stratify OSA severity and foresee some of its dangerous consequences such as excessive daytime sleepiness and cognitive deterioration.

With recent developments in fusion engineering, interest has sparked in development of fusion devices for deterrent. Enormous amount of energy generated by combining two light nuclei could be contained and manipulated at will to trigger and accelerate micro explosions (from shock wave, x-rays or ion beam focusing) which finally result in full scale blast. Materials required to make such device are critical. They must possess high strength, high hardness, ductility, formability, drawability, and anisotropic properties. High entropy alloys (HEA) are new class of materials which nicely fulfils this requirement. Essentially, they are solid solutions of multi principal elements (usually > 5) eliminating the need of base metal as in conventional alloys. This gives them many unique properties which may be tailored at will (heat treatment, cold rolling, precipitation, irradiation). They also exhibit excellent directional properties with formation of distinct bands along certain preferred crystallographic planes even in hexagonal close packed structures. These anisotropic properties are strong function of rolling, working, or forging (swaging) direction and can be utilized to benefit. This study encompasses making outer shell of a typical fusion device selected on the basis of the weight, which is a function of area of pay load bay of carrier aircraft.

Based on the textured controllable interface effect, the dynamic performances of the textured and ordinary pilot valve are analyzed experimentally, and the influence of the textured controllable interface on the response of pilot valve is studied. Results show that when Pin is small, the textured surface shortens the reciprocating time of valve core, increasing the flow rate, and speeds up the piston stroke of oil cylinder. The valve core actions much more stable and sensitivity. Meanwhile, combined with the theoretical calculation, the operation mechanism of texturing the pilot valve is analyzed. It is concluded that the stress of textured valve core sealing surface is greater than that of ordinary one, and the pressure difference gradually decreases with the increase of Pin, and the flow difference is basically the same as the force on the sealing surface. This indicates that the textured surface improves lubrication characteristics, reduces the friction between components. The textured valve makes the velocity changes gently, and enhances the responsiveness and stability of the valve. Those related results provide a new idea for enhancing the response design of the pilot valve.

The popularity of functional gummies has increased, which is evident from the growing line of functional gummies from almost every nutraceutical companies. Sensory evaluation serves the purpose of determining which brand of functional gummy would capture the largest market share. Texture profile analysis was used to determine the mechanical properties of functional gummies. The brands of functional gummies that came under the scope of this study were denoted as Brand A, B, C, D, E, F and G. Fourier Transform Infrared Spectroscopy was utilised to detect organic material and functional groups in the functional gummies. Texture profile analysis gave valuable insights into the gummies’ mechanical properties which are cohesiveness, springiness, hardness, gumminess, and chewiness. Amongst the gummies that were studied, Brand F gummy has the highest value of cohesiveness of 0.92. Brand A gummy has a high springiness value of 1.0. Brand B gummy possesses the highest value of hardness, gumminess and chewiness of 12 532.2 g, 7617.6 N, and 6256.8 J, respectively. Qualitative sensory evaluation reveals that Brand G gummy has the best aesthetic qualities in terms of colour and appearance. Brand B gummy tastes the best while brand A gummy claims the top spot for gumminess and chewiness. Overall, the respondents in this study preferred brand A gummy over other brands.

Pounded yam eaten with any type of soup is a delicacy eaten by Nigerians. It is manually prepared by pounding yam, cocoyam or combination with mortar and pestle. Preparation takes 30-45 mins. Researches on the improvements have taken place to reduce the heavy burden on the pounded yam preparation. One of the efforts made is the fabrication of pounding machine from the Department of Engineering, Federal College of Agriculture, Akure, Nigeria. The aim of this study is to carry out the organoleptic analysis of pounded yam produced from the fabricated machine. A ten-man panelist was used to determine the organoleptic analysis of the pounded yam in terms of the appearance, taste, colour, odour and texture. The panelists were scored with a class of quality grading: 22.6-25.0 (excellent), 20.2-22.5 (good), 18.2-20.1 (satisfactory), 16.2-18.1 (less satisfactory), and <15.2 (unsatisfactory). Also, sensory attributes were scored as 1= unsatisfactory, 2= less satisfactory, 3= satisfactory, 4=good, and 5= excellent. The results were statistically analysed. From the results it was found that the mean results of appearance, colour, odour, taste, and texture were 4.55, 4.43, 4.15, 4.32, and 4.08 respectively. Coefficients of variation (%) were 16.89, 17.80, 21.65, 15.67, and 24.40. The Skewness of the parameters was in negative, while only odour has its Kurtosis in negative form (-0.37). All the panelists rated the appearance (19-24%) of all the samples high above all other parameters. The Pearson Coefficient of Correlation and Principal Component Analysis showed elements of relationships between the parameters. In conclusion, the machine pounded yam was scored above satisfactory, which means the fabricated machine was efficient.

Label-free confocal photothermal (CPT) microscopy was utilized for the first time to investigate malignancy in mouse skin cells. A laser diode (LD) with 405nm or 488nm was used as a pump and 638nm LD as a probe for the CPT microscope. The Grey Level Cooccurrence Matrix (GLCM) for texture analysis was applied to the CPT images. Nine parameters of GLCM were calculated for the intracellular super-resolved CPT images, and the parameters Entropy and Prominence were found to be most suited among the nine parameters to discriminate between healthy cells and MM cells in case pump wavelength of 488nm is used.

Accumulative roll bonding (ARB) is one of methods of severe plastic deformation which is relevant for industrial production of sheets. While mechanical properties of several magnesium alloys subjected to ARB process have been studied, the physical properties have been reported only for some magnesium alloys. These properties are influenced by the texture developed during the ARB process and the temperature load. In the presented contribution, we studied thermal diffusivity and thermal conductivity of an AZ31 magnesium alloy after 1 and 2 passes through the rolling mill. Thermal diffusivity was measured with the laser-flash method in the temperature range between 20 and 350 °C. Thermal conductivity depends on the number of rolling passes. The microstructure and texture of sheets are significant factors influencing the thermal properties.

While texturing of workpiece surfaces to promote lubrication in metal forming has been applied for several decades tool surface texturing is rather new. In the present paper tool texturing is studied as a method to prevent galling. Adopting a strip reduction test longitudinal pocket geometries oriented perpendicular to the sliding direction, with shallow pocket depth, small pocket angle to the workpiece surface and varying distance between pockets are investigated. The experiments reveal that the distance between pockets should be larger than the pocket width thereby creating a topography similar to flat table mountains to avoid mechanical interlocking in the valleys; otherwise an increase in drawing load and pick-up on the tools is observed. The textured tool surface lowers friction and improves lubrication performance provided that the distance between pockets is 2-4 times larger than the pocket width. Larger drawing speed facilitates escape of the entrapped lubricant in the pockets. Testing with low to medium viscosity oils leads to a low sheet roughness on the plateaus but also local workpiece material pick-up on the tool plateaus. Large lubricant viscosity results in higher sheet plateau roughness but also prevents pick-up and galling.

Chromium (Cr) metal has garnered significant attention in alloy systems owing to its exceptional properties, such as high melting point, low density, and superior oxidation and corrosion resistance. However, its processing capabilities are hindered by the high Ductile-Brittle Transition Temperature (DBTT). Recently, powder bed fusion-laser beam for metals (PBF-LB/M) has emerged as a promising technique, offering the fabrication of net shapes and precise control over crystallographic texture. Nevertheless, research investigating the mechanism underlying crystallographic texture development in pure Cr via PBF-LB/M still needs to be conducted. This study explores the impact of scan speed on relative density and crystallographic texture. At the optimal scan speed, an increase in grain size attributed to epitaxial growth was observed, resulting in the formation of cubic texture. Consequently, a reduction in High Angle Grain Boundaries (HAGB) was achieved, suppressing defects such as cracks and enhancing relative density up to 98.1%. Furthermore, with increasing densification, Vickers hardness also exhibited a corresponding increase. These findings underscore the efficacy of PBF-LB/M for processing metals with high DBTT properties.

Negative temperature coefficient (NTC) materials are usually based on ceramic semiconductors and electrons are involved in their transport mechanism. A new type of NTC material, adequate for alternating current (AC) applications, is represented by zeolites. Indeed, zeolites are single-charge carrier ionic conductors with a temperature-dependent electrical conductivity. In particular, electrical transport in zeolites is due to the monovalent charge-balancing cations, like K⁺, capable of hopping between negatively charged sites in the aluminosilicate framework. Owing to the highly non-linear electrical behavior of the traditional electronic NTC materials, the possibility to have alternative types of materials, showing linearity in the electrical behavior, is very desirable. Among different zeolites, the natural clinoptilolite has been selected for investigating the NTC behavior since it is characterized by high zeolite content, convenient Si/Al atomic ratio, good mechanical strength, due to its compact microstructure, and low toxicity. Clinoptilolite has shown a rapid and quite reversible impedance change under heating, characterized by a linear dependence on temperature. X-ray diffraction (XRD) has been used to identify the natural zeolite, to establish all types of crystalline phases present in the mineral, and to investigate the thermal stability of these phases up to 150°C. X-ray photoelectron spectroscopy (XPS) analysis has been used for the chemical characterization of the natural clinoptilolite sample, providing important information on the cationic content and framework composition. In addition, since electrical transport takes place in the zeolite free-volume, a Brunauer–Emmett–Teller (BET) analysis of the mineral has been also performed.

In this study, we successfully obtained a 2Mg-Fe mixture through mechanical alloying (MA) and processed it via accumulative roll bonding (ARB) (MA+ARB). Our primary focus was to analyze the impact of ambient air exposure while also evaluating the processing route. Some powder samples were exposed to air for 12 months before undergoing ARB processing. The Mg samples obtained after ARB processing exhibited a (002)-type texture. Our results demonstrate that all samples, including those processed via ARB, could rapidly absorb hydrogen within a matter of minutes, despite considerable differences in surface area between powders and rolled samples. ARB-processed samples reached approximately 60% of their maximum acquired capacity within just 24 minutes, compared to powders stored for a year which took 36 minutes. Also, the desorption temperatures were lower than those of MgH2. The absorption and desorption kinetics remained fast even after prolonged exposure to air. Although there were minor variations in capacities, our overall findings are promising since scalable techniques such as ARB have the potential to produce hydrogen storage materials that are both safe and cost-effective in a highly competitive market.

The aim of this study was to determine the effect of sous-vide and pressure-cooker heating of pork muscles (Longissimus lumborum) on the physicochemical and technological characteristics of pork. The study included an analysis of the basic composition, colour, texture, nutritional value (vitamin B1 content), and rheological properties of meat heated at 60°C for 6-18h and, for comparison, in an autoclave at 121.1°C. The heating conditions affected the weight loss, colour, thiamine content, texture, and rheological properties of the meat. As the heating time increased, the texture determinants of firmness and chewiness decreased, which resulted in softer meat. The differences in the rheological properties of the sous-vide- and autoclave-heated meat resulted from different organ-isation of the spatial matrix of proteins and changes in the structure of muscle fibres caused by the high temperature.

This paper presents a robust method based on graph topology to find the topologically correct and consistent subset of inter-robot relative pose measurements for multi-robot map fusion. However, the absence of good prior gives a severe challenge to distinguish the inliers and outliers, and wrong loop closures can seriously corrupt the fused global map. Existing works mainly rely on the consistency of spatial dimension to select inter-robot measurements, which does not always hold. In this paper, we propose a fast inter-robot loop closure selection method that integrates the consistency and topology relationship of measurements, which both conform to the continuity characteristics of similar scenes and spatiotemporal consistency. The traditional high-dimensional consistency matrix is decomposed into the sub-matrix blocks corresponding to the overlapping trajectory area. Building on this logic, a clustering method involving topology correctness of inter-robot loop closures is introduced to split the entire measurement set into multiple clusters. We define the weight function to find the maximum cardinality subset with topologically correct and consistent, then convert the weight function to a maximum clique problem in the graph and solve it. We evaluate the performance of our method in a simulation and in a real-world experiment. Compared to state-of-the-art methods, the results show that our method can achieve competitive performance in accuracy while reducing computation time by 75%.

In order to realize rapid and nondestructive monitoring of wheat biomass in field, field experiments based on different densities, nitrogen fertilizer and variety treatments were studied. RGB images of wheat in the main growth stage were obtained by UAV, and wheat color and texture feature indices were obtained by image processing, and wheat biomass was obtained by field sampling in the same period. Then the relationship between different color and texture feature indices and wheat biomass was analyzed to select the color and texture feature index suitable for wheat biomass estimation. The results showed that there was a high correlation between image color index and wheat biomass in different stages, and most of them reached a very significant correlation level. However, the correlation between image texture feature index and wheat biomass was poor, only a few indexes reached significant or extremely significant correlation level. Based on the above results, the color indices with the highest correlation to wheat biomass or the combining indices of color and texture feature in different growth stage were used to construct estimation model of wheat biomass. The models were validated using independently measured biomass data, and the correlation between simulated and measured values reached the significant level, RMSE were smaller. This indicated that the estimated results by the models were reliable and accurate. It also showed that the estimation models of wheat biomass combined with color and texture feature indices of UAV image were better than the single color index models. The results would provide a new method for real-time monitoring of wheat field growth and biomass estimation.

Mexican yuca (Yucca decipiens Trel.) is native to the semidesert region across north-central Mexico. Based on its empirical medicinal uses, the flour produced from leaves and stems of yuca was evaluated to determine its agro-industrial and medicinal uses (food, beer, and mezcal). The flour was characterized based on the granulometry, rheology, texture, and functional properties, which were analyzed with the RStudio software. The results indicate that the water absorption capacity of yuca flour (data here) is similar to wheat flour; however, it absorbs half the volume of oil than wheat flour. Therefore, it has a hydrophilic behavior similar to that of wheat and a lower oil requirement for formulas. The expansion capacity of yuca flour is like that of wheat flour, showing an ideal gluten content for agro-industrial purposes (food) that require this structural component. The flour had a remarkable foam formation, high stability, and low-fat content. These results are particularly important for foods that require foaming properties. Fermentation matched the parameters of the 56-60 Physicochemical Test Methods of the Cereal &amp; Grains Association; consequently, their flours are classified as equal to flours produced from soft and weak wheat, supporting their use for fermentation processes. The internal friction values (0.85-0.92) suggest a limited flow; however, its high density shows a fine granulometry that facilitates the sacking, handling, and storing of the flour, complying with the Mexican standards, and allowing it to be added to combinations aimed to enrich food.

This study investigated the mechanical properties and fatigue behavior of FH36 steel plate rolled in different directions. By adopting a sequential rolling process in the rolling direction (RD) and transverse direction (TD), the differences in properties between RD and TD were eliminated, resulting in nearly identical tensile properties. The steel plate exhibited a yield strength of approximately 420 MPa, a tensile strength of approximately 506 MPa, and an elongation of approximately 25%. Fatigue tests conducted at room temperature and -60℃ showed a fatigue limit of the maximum stress of 488 MPa at room temperature and 500 MPa at -60℃, indicating improved low-temperature fatigue performance. The fracture surfaces displayed distinct characteristics, such as oblique shearing fractures for high-cycle fatigue and cup-cone shape fractures for low-cycle fatigue. The fatigue source zone were both on the surface of the specimens. As the maximum stress increased, the area of the crack propagation zone for high-cycle fatigue decreased, while the area of the final fracture zone, the number of dimples and the proportion of the LAGBs increased.

Historical city textures are living history embodying public open spaces of former civilizations, their landscapes and traditional life cultures, carrying them to the present and giving them life. The squares, which form the public open spaces, have been important meeting centers in the social lives of people. City furniture are the important elements in these public open spaces, reflecting the identity of the city and improving quality of life. City furniture improve the reflection of cultural value in historical city textures and their usability. The walled city center, where the historical city texture of Nicosia lies, has a very rich historical texture with the cultural heritage of various civilizations in the history of Cyprus. Public open spaces within the texture, which have acquired the quality of squares with their functions throughout the social history of Nicosia, are still important social spaces for the people of the city. This study analyzed Asmaaltı and Selimiye Squares, two important spaces of the walled city, through examining the city furniture in terms of their material, shape, and functionality, and their conformity with the historical texture. Their deficiencies and nonconformities with the historical texture were identified accordingly. In consideration with such examples, city furniture in historical city textures were assessed for their conformity with the texture characteristics, architectural styles, social, cultural, and economical characteristics, and relevant recommendations are presented respectively.

Tarihi kent dokuları, eski uygarlıkların kamusal açık alanlarını, peyzajlarını ve geleneksel yaşam kültürlerini bünyesinde barındıran, günümüze taşıyan ve yaşatan yaşayan bir tarihtir. Kamusal açık alanları oluşturan meydanlar, insanların sosyal yaşamlarında önemli buluşma merkezleri olmuştur. Kent mobilyaları bu kamusal açık alanlarda kentin kimliğini yansıtan ve yaşam kalitesini artıran önemli unsurlardır. Kent mobilyaları, kültürel değerlerin tarihi kent dokularına yansımasını ve kullanılabilirliğini artırır. Lefkoşa'nın tarihi kent dokusunun yattığı Suriçi kent merkezi, Kıbrıs tarihindeki çeşitli uygarlıkların kültürel mirası ile oldukça zengin bir tarihi dokuya sahiptir. Doku içinde kamusal açık alanlar, Lefkoşa'nın sosyal tarihi boyunca işlevleriyle meydan niteliği kazanan meydanlar, kent insanı için halen önemli sosyal mekanlardır. Bu çalışmada, Suriçi kentin iki önemli mekanı olan Asmaaltı ve Selimiye Meydanları, kent mobilyaları malzeme, biçim, işlevsellik ve tarihi dokuya uygunluk açısından incelenerek incelenmiştir. Buna göre eksiklikleri ve tarihi dokuya uymayanları tespit edilmiştir. Bu örnekler ışığında tarihi kent dokularındaki kent mobilyalarının doku özellikleri, mimari üsluplar, sosyal, kültürel ve ekonomik özelliklerle uygunluğu değerlendirilmiş ve öneriler sunulmuştur. kentliler için hala önemli sosyal mekanlardır. Bu çalışmada, Suriçi kentin iki önemli mekanı olan Asmaaltı ve Selimiye Meydanları, kent mobilyaları malzeme, biçim, işlevsellik ve tarihi dokuya uygunluk açısından incelenerek incelenmiştir. Buna göre eksiklikleri ve tarihi dokuya uymayanları tespit edilmiştir. Bu örnekler ışığında tarihi kent dokularındaki kent mobilyalarının doku özellikleri, mimari üsluplar, sosyal, kültürel ve ekonomik özelliklerle uygunluğu değerlendirilmiş ve öneriler sunulmuştur. kentliler için hala önemli sosyal mekanlardır. Bu çalışmada, Suriçi kentin iki önemli mekanı olan Asmaaltı ve Selimiye Meydanları, kent mobilyaları malzeme, biçim, işlevsellik ve tarihi dokuya uygunluk açısından incelenerek incelenmiştir. Buna göre eksiklikleri ve tarihi dokuya uymayanları tespit edilmiştir. Bu örnekler ışığında tarihi kent dokularındaki kent mobilyalarının doku özellikleri, mimari üsluplar, sosyal, kültürel ve ekonomik özelliklerle uygunluğu değerlendirilmiş ve öneriler sunulmuştur. ve tarihi dokuya uygunluğu. Buna göre eksiklikleri ve tarihi dokuya uymayanları tespit edilmiştir. Bu örnekler ışığında tarihi kent dokularındaki kent mobilyalarının doku özellikleri, mimari üsluplar, sosyal, kültürel ve ekonomik özelliklerle uygunluğu değerlendirilmiş ve öneriler sunulmuştur. ve tarihi dokuya uygunluğu. Buna göre eksiklikleri ve tarihi dokuya uymayanları tespit edilmiştir. Bu örnekler ışığında tarihi kent dokularındaki kent mobilyalarının doku özellikleri, mimari üsluplar, sosyal, kültürel ve ekonomik özelliklerle uygunluğu değerlendirilmiş ve öneriler sunulmuştur.

3D reconstruction from a single 2D input is a classic problem in the field of computer vision. With the advancements in deep learning, the performance of 3D reconstruction has also significantly improved. The reconstruction task is more difficult for objects with no textures or complex deformations. This paper serves as a review of recent literature on 3D reconstruction from a single view, with a focus on deep learning methods from 2018 to 2021. Due to lack of standard datasets or 3D shape representation methods, it is hard make direct comparisons between all reviewed methods. However, this paper reviews different approaches for reconstructing 3d shape as depth maps, surface normals, point clouds and meshes; along with various loss functions and evaluation metrics used to train and evaluate these methods.

The manufacturing parameters influence the properties of thermo-mechanically processed met-als such as Mg alloys. This paper presents how the mechanical properties, the microstructure and the degradation rate of extruded Mn-containing Mg-Gd-alloys can be modified. Gd as repre-sented REE-element is particularly interesting due to the influence on the texture development in Mg and therefore studied as a base alloy system. The contents of Gd were investigated be-tween 2 to 9 wt.% with Mn-addition of 0.5 and 1.0 wt.%. The grain sizes and the corresponding textures were modified by the extrusion parameters and the alloy content. It was shown that modification by Mn can decrease the grain size, but increase the degree of recrystallization and decrease the degradation rate in the biological medium compared to the binary Mg-Gd system from previous studies. The results suggest that the binary Mg-Gd system can be produced more efficiently by adding Mn and that the resulting properties are more robust.

Abstract: A lower bed single row for pineapple cultivation could protect pineapple from soil erosion in rainy season and during drought, however, disease problem could arise due to water logging. Two experiments using a lower bed single row was done to understand the ability of gypsum providing soil calcium (Ca) available to pineapple plant, resistance to heart rot disease, and give better effect on crop growth and fruit quality of the pineapple in Ultisol soil. In the first trial, four level dosis of gypsum (0, 1.0, 1.5, 2.0 Mg ha-1) and dolomite 2 Mg ha-1 were applied by spreading and incorporated into the soil which have saturated with inoculums of Phytophthora nicotianae. In the second trial, gypsum treatments (0, 1.0, 1.5, 2.0, 2.5 Mg ha-1) were applied in the row between the single row beds as a basic fertilizer. The result showed that P. nicotianae attacked the pineapple plants in all treatments at 6 weeks after planting (WAP), and at 10 WAP, the mortality of dolomite treatment reached 63.8%, significantly different than that for gypsum treatments (3.3-14.3%). In the second experiment, gypsum increased plant weight significantly at 3 until 9 months after planting especially when it was applied 1.5-2.5 Mg ha-1. Fruit texture, total soluble solid (TSS), titratable acidity (TA) were not significant different among the treatment but all meet the standards for grades of canned pineapple. Result showed that soil applied gypsum before planting provides soil calcium and met the plant Ca requirement during a period of early and fast growth step and safe for heart rot disease.

700 MPa grade Ti and Nb-Ti microalloyed steels produced by thermo-mechanical control rolled processes (TMCP) were studied to elucidate texture that contributes to delamination and consequent impact toughness. The microstructure of Ti and Nb-Ti steels consisted of ferrite and bainite. Compared with Ti steel, Nb-Ti steel was characterized by a microstructure with finer ferrite and more bainite. The results from tensile and impact tests indicated that there is insignificant change in tensile properties, but toughness was greater in Nb-Ti steel compared with Ti steel. More severe delamination in Nb-Ti steel is attributed to stronger α-fiber (RD ||<110>) texture than Ti steel, especially {100}<110>, {113}<110> and {112}<110> texture. Typical cleavage river patterns were not observed on delaminated fracture surface, instead the cleavage fracture surface indicated some dimples. Interestingly, the impact energy of samples with delamination was greater than samples without delamination in the ductile–brittle transition region. The study suggests that delamination in the ductile–brittle transition zone may also be representative of high toughness.

Single-level Principal Components Analysis (PCA) and multi-level PCA (mPCA) methods are applied here to a set of (2D frontal) facial images from a group of 80 Finnish subjects (34 male; 46 female) with two different facial expressions (smiling and neutral) per subject. Inspection of eigenvalues gives insight into the importance of different factors affecting shapes, including: biological sex, facial expression (neutral versus smiling), and all other variations. Biological sex and facial expression are shown to be reflected in those components at appropriate levels of the mPCA model. Dynamic 3D shape data for all phases of a smile made up a second dataset sampled from 60 adult British subjects (31 male; 29 female). Modes of variation reflected the act of smiling at the correct level of the mPCA model. Seven phases of the dynamic smiles are identified: rest pre-smile, onset 1 (acceleration), onset 2 (deceleration), apex, offset 1 (acceleration), offset 2 (deceleration), and rest post-smile. A clear cycle is observed in standardized scores at an appropriate level for mPCA and in single-level PCA. mPCA can be used to study static shapes and images, as well as dynamic changes in shape. It gave us much insight into the question “what’s in a smile?”

The information of seismic damage of buildings in SAR images of different time phase, especially in SAR images after earthquake, is easily disturbed by other factors, which affects the accuracy of information discrimination. In order to identify and evaluate the distribution information of the seismic damage accurately and make full use of the abundant texture features in the SAR image. The conventional method of change detection based on texture features usually takes the pixel as the calculating unit. In this paper, a method of texture feature change detection of SAR images based on watershed segmentation algorithm is proposed. Based on the optimization of texture feature parameters, the feature parameters are segmented by the watershed segmentation algorithm, and the feature object image is obtained. This method introduces the idea of object oriented, and carries out the calculation of the difference map at the object level, Finally, the classification threshold value of different types of seismic damage types is selected, and the recognition of building damage is achieved. Taking the ALOS data before and after the earthquake in Yushu as an example to verify the effectiveness of the method, the overall accuracy of the building extraction is 88.9%, Compared with pixel-based methods, it is proved that the proposed method is effective.

For advancing manufacturing, arising AM, with an inverse philosophical approach compared to conventional procedures, has benefits that include intricate fabrication, reduced material waste, flexible design, and more. Regardless of its potential, AM must overcome several challenges due to multi-physical processes with miscellaneous physical stimuli in diverse materials systems and situations, such as anisotropic microstructure and mechanical properties, a restricted choice of materials, defects, and high cost. Unlike conventional experimental work that requires extensive trial and error resources and FEM, which generally consumes substantial computational power, the analytical approach based on physics is an exceptional choice. Understanding the relationship between the microstructure and material properties of the fabricated parts is a crucial focus in AM research. Texture is a vital factor in almost every modern industry. This study first proposed a physics-based model to foreshadow the multi-phase crystallographic orientation distribution in Ti-6Al-4V LPBF while considering the part boundary conditions due to the importance of part geometry in real industry. The thermal distribution obtained from this function operates as the information for the single-phase crystallographic texture model. In this model, we forerun and validate the orientations of single-phase materials utilizing three Euler Angles with the principles of CET and thermodynamics, as well as the intensity of the texture by approximating them with published results. Then, we transform the single-phase texture into a dual-phase texture in Bunge calculation, illustrating visualized by pole figures of both BCC and HCP phases. This texture evolution model provides a new paradigm for future researchers to model the texture or microstructure evolution semi-analytically and save many computational resources in a real-world perspective. Others have not yet done this work about simulating the multi-phase texture in an analytical approach, so this work bridges the gap in this field. Furthermore, this paper establishes the foundation for future research on materials properties affected by microstructure or texture in academic and industrial environments. The precision and dependability of the results obtained through this method make it a valuable tool for ongoing research and advancement.

The agricultural soil maps (ASMs) showing the agricultural land of Poland were prepared in 1:5000 scale in 1960s’ and 1970s’. These maps show land suitability group, soil type and soil texture (ST) to a depth of about 150cm. Nowadays, these maps are being digitalized and might be a basis for the preparation of modern soil maps at local, regional, national and international level. The agreement between the ST of topsoil derived from ASMs and recently evaluated for eleven fields located in three voivodeships (regions) of Poland was studied. The study of soil considered the examination of soil profiles or augerings and laboratory analysis of the ST. The agreement between soil status in the field and according to maps was field-specific. Complete agreement (purity) within the field was assessed for 5-79% of ST classes and for 23-100% of agronomic categories (ACs) – a groupings of similar ST classes. However, the averaged agreement, which treated adjacent ST classes as having partial agreement, varied from 37 to 88% for ST classes and from 61 to 100% for the ACs among studied fields. These results indicate on the variable quality of the information shown on the ASMs and on the necessity of improvement of these maps.

A 2-month incubation study was carried out using two soil types to determine nitrogen mineralization of different inorganic-organic amendments. The following seven treatments (T) were established; T1 = control, T2 = 5 g of dry algae per kg of soil (100%DA), T3 = 136g of agri-mat per kg of soil (100%GA), T4 = 61 g of ground grass per kg of soil (100%GG), T5 = 2.5 g of dry algae + 2.5 g of nitrogen fertilizer (NF) per kg of soil (50%DA50NF), T6 = 50%GA50NF, T7 = 50%GG50NF. Three samples per treatment were drawn at 0, 3, 7, 15, 30, 45, and 60 days for mineral-N determination. A 2-month glasshouse experiment was established afterwards with the following five treatments: T1 = Control, T2 = 50%DA, T3 = 50%GA, T4 = 50%GG, and T5 = 100NF. The results indicated that nitrogen mineralization was significantly higher in organic-inorganic amendments compared to sole organic amendments. The percentage differences ranged from 157% to 195%. The 50%DA treatment increased spinach yield by 20.6% in sandy loam and 36.5% in loam soil. It is difficult to fully recommend the 50%DA treatment without field-scale evaluation, but it is a promising option to be considered.

The aims of this research were to know the physicochemical parameters, texture properties and sensory profile of vegetarian sausages through the flash profile, overall liking and purchase intention. Additionally, protein, fat and carbohydrate contents, pH, water activity, color, instrumental texture and descriptive profile were quantified with the overall liking and purchase intention of four sausages: ovo-vegetarian (SO), classic vegan (SC), fine herb vegan (SH) and vegan quinoa (SQ). Regarding the physicochemical properties, significant differences (p &lt; 0.05) were obtained. Using the flash profile, consumers described SO with attributes of elasticity, tamale smell, strange smell, characteristic flavor, pastiness, softness, pastel color. SC described as soft, pale color, characteristic odor, characteristic flavor, porous and flexible; SH and SQ characterized by the presence of ingredients, stew flavor, spices, pale and soft color. The SO sample presented greater overall liking and purchase intention compared to the other samples, and had a better texture and higher protein content. Through the HMFA analysis, a positive correlation was obtained between the texture and descriptive sensory of the flash profile, and on the other hand, a correlation between the physicochemical characteristics pH, aw, color, overall liking and purchase intention.

Displacement mapping is a computer graphics technique that enables the design of components with regularly or randomly textured surfaces that can be quickly materialized on a three-dimensional (3D) printer when needed. This approach is in principle more flexible, faster and more economical compared to conventional texturing methods, but the accuracy of the texture depends heavily on the parameters used. The purpose of this study is to demonstrate how to produce a surface-textured part using polygonal (mesh) modeling software and a photopolymerizable resin, and to develop a universal methodology to predict the dimensional accuracy of the model file log combined with a resin 3D printer. The printed components were characterized on a scanning confocal microscope. In the setup used in this study, the mesh size had to be reduced to 10% of the smallest feature size and the textured layer had to be heavily (x4) overexposed to achieve the desired accuracy. As a practical application, two functional stamps with a regular (honeycomb) and a random texture, respectively, were successfully manufactured. The insights gained will be of great benefit in quickly and cost-effectively producing components with innovative patterns and textures for a variety of hobby, industrial and biomedical applications.

Salting influences microbial growth, enzymatic activity and biochemical reactions during ripening, thus contributing to the final quality of cheese. The aim of this study was to evaluate the influence of different salting methods (dry salting at 12, 24 and 48 h; in brine; and curd salting) on the chemical (moisture and salt content), physico-chemical (pH, titratable acidity and water activity) and sensory (texture profile analysis, colour and sensory attributes) characteristics of an industrial blue vein cheese. Dry salted cheeses had lower moisture content and water activity, and higher salt/moisture content and acidity than those salted in brine and curd. Dry-salted cheeses were also characterised by higher values for hardness, fracturability and instrumental gumminess. Dry-salted cheeses showed differences only in the red/green colour component (a*), with the curd-salted cheeses being less greenish. All cheeses scored high (around 7) in the tasters' overall impression, with the dry-salted cheeses at 12 and 24 h showing optimal growth and even distribution of mould, as well as better flavour and texture.

The introduction on Zinc oxide nanoparticles (ZnOn) in sunscreens solved the issue of poor spreadability of these formulations, which often left a white film on the skin. However, safety concerns have arisen regarding the topical application of ZnOn. Some studies employed commercial sunscreens to address the safety issues of the topical application of ZnOn; however, commercial formulations are often complex and contain a wide range of ingredients that could attenuate the potential damage caused by the ZnOn. Therefore, in this study we aimed to develop a simple stable formulation containing 20% of coated and uncoated ZnOn, characterize the formulations and the nanoparticles, and assess the skin penetration in Franz diffusion cell. The Feret's diameter for the uncoated and coated ZnOn was 137 nm and 134 nm, respectively. For the uncoated ZnOn the hydrodynamic size in water was 368 nm and for the coated ZnOn, the average hydrodynamic size in ethyl acetate was 135 nm. The incorporation of ZnOn led to formulations more consistent and easier to spread, as suggested by the lower work of shear and higher values of firmness, cohesiveness, consistency and index of viscosity compared with the vehicle. The stability assessment at 45ºC suggested that the formulations containing the ZnOn were stable for 30 days and the vehicle was stable for 90 days. The assessment off the skin penetration by reflectance confocal laser microscopy indicated that the formulations did not permeate into the deepest layers of the skin, but accumulated on the skin furrows, hair and hair follicle.

High surface area carbon was obtained from -carrageenan – urea cryogels doped with 1.25 – 5 wt% graphene oxide (GO). Incorporation of GO resulted in multifaceted modification in the textural and chemical properties of the carbon cryogel. The thermal decomposition of GO facilitated the formation of micropores resulted in a substantial increase in the apparent surface area (up to 1780 m2/g). The annealing at 1000 °C removed part of the heteroatoms but left behind a high number of defects. While the volatile thermal degradation products of GO affected the porous texture and the surface chemistry in a complex way, its reduced residue resulted in a gradually increasing electrical conductivity. The influence of GO was studied in oxygen reduction reaction (ORR) and in Li-ion storage application. GO affected the electron transfer mechanism in the ORR tests and challenged the stability of the electrodes. Even if the electrode has been stabilized under oxygen-free conditions, later may undergo destabilization processes during the ORR. The 5 wt% GO doped sample was the most sensitive under oxidative conditions, but finally it exhibited the highest capacitance. In the Li-ion battery tests the coulombic efficiency of all the samples was consistently above 98 %, indicating the great potential of such carbons for efficient Li-ion insertion and reinsertion during the charge – discharge process, thereby providing a promising alternative for graphite-based anodes. The cell from the 1.25% sample showed an initial discharge capacity of 313 mAh/g, 95.1 % capacity retention and 99.3 % coulombic efficiency after 50 charge – discharge cycles.

Karst wetlands are being seriously damaged, and protecting it has become an important matter. Karst vegetation is the essential component of wetland and plays an important role in in the ecological functions of wetland ecosystems. Classifying karst vegetation is important for karst wetlands protection and management. This paper addressed to classify karst vegetation in Huixian National Wetland Park, located in China using the improved SegNet Deep-Learning Algorithm and UAV images. This study proposed a method to fuse single-class SegNet models using the maximum probability algorithm for karst vegetation classification, and compared with object-based RF classification and multi-class SegNet classification, respectively. This paper evaluated the performance of multi-class SegNet model and fusion of single-class SegNet model with different EPOCH values for mapping karst vegetation. A new optimized post-classification algorithm was proposed to eliminate the stitching traces caused by SegNet model prediction. The specific conclusions of this paper include the followings:(1) fusion of four single-class SegNet models produced better classification for karst wetland vegetation than multi-class SegNet model, and achieved the highest overall classification accuracy (87.34%); (2) The optimized post-classification algorithm was able to improve prediction accuracy of SegNet model, and it could eliminate splicing traces; (3) The karst wetland vegetation classifications produced by single-class SegNet model outperformed multi-class SegNet model, and improved classification accuracy(F1-Score) between 10%~25%;(4)The EPCOH values and textural feature important impact on karst wetland vegetation classifications. The SegNet model with EPCOH 15 achieved greater classification accuracy(F1-Score) than the model with EPOCH 5 or 10. The textural feature improved improves the capability of the SegNet model for mapping karst vegetation;(5) Fusion of single-class SegNet models and object-based RF model could provide high classifications results for karst wetland vegetation, and both achieved greater 87% overall accuracy.

Eight samples of limestones and marbles were studied by neutron diffraction to collect 2 Quantitative Texture (i.e., Crystallographic Preferred Orientations or CPO) of calcite deforming at 3 different depths in the crust. We studied the different Texture patterns developed in shear zones at 4 different depth and their influence on seismic anisotropies. Samples were collected in the French and 5 Italian Alps, Apennines, and Paleozoic Sardinian basement. They are characterized by isotropic to 6 highly anisotropic (e.g., mylonite shear zone) fabrics. Mylonite limestones occur as shear zone horizons 7 within the Cenozoic Southern Domain in Alpine thrust-and-fold belts (Italy), the Briançonnais domain 8 of the Western Alps (Italy-France border), the Sardinian Paleozoic back-thrusts or in the Austroalpine 9 intermediate units. The analyzed marbles were collected in the Carrara Marble, in the Austroalpine Units 10 in the Central (Mortirolo) and Western Alps (Valpelline). The temperature and depth of development of fabrics vary from < 100◦C, to 800◦C and depth from <10 km to about 30 km, corresponding from upper 12 to lower crust conditions. Quantitative Texture Analysis shows different types of patterns for calcite: 13 random to strongly textured. Textured types may be further separated in orthorhombic and monoclinic 14 (Types A and B), based on the angle defined with the mesoscopic fabrics. Seismic anisotropies were 15 calculated by homogenizing the single crystal elastic tensor, using the Orientation Distribution Function 16 calculated by the Quantitative Texture Analysis. The resulting P- and S-waves anisotropies show a wide 17 variability due to the textural types, temperature and pressure conditions, and dip of the shear planes.

In this study, the effect of heat treatment was investigated to influence the occurrence of fracture during manufacturing process of Alloy B steel with boron contents as high as 130 ppm. As the content of boron increases, it affects the phase transformation temperature and texture. The development of {111}<uvw> components in the γ-fiber is affected depending on the austenite fraction after phase transformation. The Alloy B steel indicated that the increase in the boron content increased the α to γ phase transformation temperature such that sufficient transformation did not occur in the normalizing condition. The cracks occurred at the point of the transition from elastic to plastic deformation in the ND direction during the rolling process, thereby resulting in failure. Therefore, it is necessary to avoid the intermediate heat treatment condition in which γ-fiber does not fully develop, i.e., an imperfect normalization.

The present work shows a novel physical-mathematical model to estimate the average corrosion resistance index from the crystallographic texture in API 5L steels. The crystallographic texture of the studied steels was measured by means of the X-ray diffraction technique. The model, based on the symmetric spherical surface harmonics for a BCC structure, is capable of describing the anisotropy surface of anodic dissolution resistance of the crystal and establishing a straightforward relationship between crystallographic texture, surface roughness, and metal corrosion behavior. The predictions of the average corrosion resistance index made from the crystallographic texture were in good agreement with those obtained from potentiodynamic polarization curves for the investigated steels. This agreement validates the capacity of this model and opens the possibility of applying it as a novel criterion for the material selection and design stages in order to combat metal corrosion problems.

Cylindrical Fe-6.5wt.% Si bars with 7.5 mm in diameter were successfully fabricated from as cast ingot through three rolling stages within 10 passes: rough rolling at 850–900 °C and 8–10 m/min, medium rolling at 800–850 °C and 10–15 m/min, and finish rolling at 800–850 °C and 12–18 m/min. The evolution of microstructure, texture and ordered structure, and the mechanical property are investigated. The results showed that the grains were refined by the hot bar rolling. Area fractions of the {100}<011> oriented grains and the {011}<100> oriented grains decreased to 0 during the hot bar rolling. Whereas, the {100}<001> component, the {011}<211> component and the {112}<110> component increased, and γ fiber with {111}<110> component was dominant. DO₃ ordered phase were suppressed, and B2 ordered domains were refined after the hot bar rolling. Ductility of the as rolled bar was higher than that of the rotary swaged bar, due to the absence of the DO₃ ordered phase and the fine grains in the rolled bar. Hence, the hot bar rolling technology is an excellent process to fabricate the Fe-6.5wt.% Si bars.

Isolation of new plant-derived lactic acid bacteria (LAB) is highly prioritized in developing novel starter cultures for plant-based fermentation. This study explores the diversity of LAB in Danish flowers and their potential use for plant-based food fermentation. 46 flower samples under 34 genera were collected for LAB isolation. By introducing an enrichment step, in total of 61 LAB strains were isolated and identified by using MALDI-TOF and 16S rRNA sequencing. These strains represent 24 species across 9 genera, predominantly Leuconostoc mesenteroides, Fructobacillus fructosus, Apilactobacillus ozensis, and Apilactobacillus kunkeei. Phenotypic screening for exo-cellular polysaccharide production revealed that 40 strains exhibited sliminess or ropiness on sucrose containing agar plate. HPLC analysis confirmed that all isolates produced exo-cellular polysaccharides containing glucose, fructose or galactose as sugar monomer. Therefore, the strains were glucan, fructan and galactan producers. The suitability of these strains for plant-based fermentations was characterized by using almond, oat and soy milk. The results showed successful acidification in all three types of plant-based matrices but only observed texture development in soy by Leuconostoc, Weissella, Lactococcus, Apilactobacillus, and Fructobacillus. The findings highlight the potential of flower-derived LAB strains for texture development in soy-based dairy alternatives.

A superior variant of dried jujube in China is ‘Huizao’ (HZ) jujube. Nonetheless, detailed evaluations of the texture quality of HZ fruits have been the subject of few studies. Texture is a significant indicator of the sensory and processed quality of a fruit. Here, we differentiate and characterize the texture quality of HZ fruits from the four primary producing regions in southern Xinjiang, as well as develop a system for assessing the texture quality of HZ fruits. Furthermore, five texture indices of HZ fruits from 109 plantations were exhaustively evaluated utilizing principal component analysis, Pearson correlation analysis, and hierarchical clustering analysis. Consequently, by the 10th, 30th, 70th, and 90th percentiles, each index was classified into five grades—lower, medium, high, and higher. Correlation investigation indicated strong relationships between the springiness, chewiness, cohesiveness, gumminess, and hardness of HZ fruits. Springiness, hardness, and adhesiveness are essential indicators that influence the texture of HZ fruits. We used clustering analysis to separate the six texture indices into three major categories (hard factor, stick-elastic factor, and adhesive factor), with indices representing hardness, springiness, and adhesiveness, respectively. Furthermore, according to the factor molecules, the texture quality of HZ fruits in the four production areas was evaluated as Bazhou (1.24) > Hotan (0.773) > Kashi (-0.577) > Aksu (-0.852). RDA analysis of six texture quality parameters and 24 climate conditions identified higher mean temperature (TEM) and lower relative humidity (RHU) as the primary factors contributing to the improved texture quality of HZ fruits in Xinjiang. This study identified the texture quality characteristics of HZ fruits in four major producing areas of Southern Xinjiang, and it offered a theoretical foundation for optimizing the dominant producing areas and regional production of HZ varieties in Xinjiang.

As most of the videos are destined for human perception, many techniques have been designed to improve video coding based on how the human visual system perceives video quality. In this paper, we propose the use of two perceptual coding techniques, namely contrast masking and texture masking, jointly operating under the High Efficiency Video Coding (HEVC) standard. These techniques aim to improve the subjective quality of the reconstructed video at the same bit rate. For contrast masking, we propose the use of a specific weighting matrix for each block size (from 4×4 up to 32×32). We achieve average Bjøntegaard Delta-Rate (BD-rate) gains of between 2.5% and 4.48%, depending on the perceptual metric and coding mode used. The texture masking scheme is based on the classification of each coding unit, using its mean directional variance features as input to a support vector machine model. According to this classification, the block’s energy, the type of coding unit, and its size, an over-quantization is computed to provide a QP offset (DQP) for this coding unit. By applying both techniques in the HEVC Reference Software, an overall average of 5.79% BD-rate gain is achieved.

Eight lesions were analyzed using some algorithms of Intelligence Artificial: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), melanoma (MEL), actinic keratosis (AK), benign keratosis (BKL), dermatofibromas (DF), melanocytic nevi (NV), and vascular lesions (VASC). This manuscript presents the possibility of using concatenated signatures (instead of images) obtained from different integral transforms, such as Fourier, Mellin, and Hilbert, to classify skin lesions. Eleven other Artificial Intelligence models were applied so that eight skin lesions could be classified by analyzing the particular signatures of each lesion. The database was randomly divided into 80%–20% for the training and test datasets images, respectively. The metrics that are being reported are accuracy, sensitivity, specificity, and precision. Each case was repeated 30 times to avoid bias, according to the central limit theorem in this work, and the average and ±standard deviation were reported. Although all the results were very satisfactory, the best average mark for the eight lesions analyzed was obtained using the Subspace KNN model, where the metrics for the test were 99.98% accuracy, 99.96% sensitivity, 99.99% specificity, and 99.95% precision.

"Hidden hunger", the deficiency of important mineral micronutrients, affects more than 2 billion people globally. Adolescence is unquestionably a period of nutritional risk, given the high nutritional requirements for growth and development, erratic or capricious diets and the increased consumption of snacks. This study applied the rational food design approach to obtain micronutrient-dense biscuits by combining chickpea and rice flours to achieve an optimal nutritional profile, crunchy texture and appealing flavour. The perception of 33 adolescents of the suitability of such biscuits as a mid-morning snack was examined. Four biscuits were formulated, with different ratios of chickpea and rice flours (CF:RF): G100:0, G75:25, G50:50 and G25:75. Nutritional content, baking loss, acoustic-texture and sensory analyses were carried out. On average, the mineral content of biscuits with the CF:RF ratio of 100:0 doubled compared with the 25:75 formula. The dietary reference values for iron, potassium and zinc reached 100% in the biscuits with CF:RF ratios of 50:50, 75:25 and 100:0, respectively. The analysis of mechanical properties revealed that samples G100:0 and G75:25 were harder than the others. Sample G100:0 showed the highest sound pressure level (Smax). Sensory analysis showed that increasing the proportion of CF in the formulation augments the grittiness, hardness, chewiness and crunchiness. Most of the adolescents (72.7%) were habitual snack consumers; 52% awarded scores ≥ 6 to biscuit G50:50 for its overall quality, 24% described its flavour as "biscuit" and 12% as "nutty". However, 55% of the participants could not pinpoint any dominant flavour. In conclusion, it is possible to design nutrient-dense snacks that meet the micronutrient requirements and sensory expectations of adolescents by combining flours naturally rich in micronutrients.

Surimi-based products occupy an important position in the aquatic product processing industry. To enhance the quality and flavor of surimi-based products, the effects of pre-emulsified safflower seed oil on the texture, water-holding capacity (WHC), microstructure, and flavor of Nemipterus virgatus surimi gel was evaluated. The texture and whiteness of gel were improved, and the WHC increased (P &lt; 0.05) as the content of safflower seed oil increased up to 2 mL per 100 g surimi. Furthermore, the drops of pre-emulsified safflower seed oils with an average diameter of less than 0.10 μm were evenly distributed in gel matrix. Microstructure and infrared spectroscopy analyses indicated that low-content pre-emulsified safflower seed oil acted as filler particles to occupy void spaces, resulting in gel exhibiting a dense network structure. Volatile analysis showed the gel containing pre-emulsified oil enriched volatile compounds, mainly resulting from oxidation and decomposition of oils by the activation of lipoxygenase, which synergistically contributes to unique flavors of gel. Consequently, low-content pre-emulsified safflower seed oil can used to enhance the quality and flavor of N. virgatus surimi-based products. These findings are especially relevant to the current growing interest in low-fat and high-protein diets.

To date, most people prefer softer and stickier rice with high glycaemic index, which has led to the study of the association between the dietary fibre profile and the textural properties to balance between the eating quality, and health benefits. A slight variation was observed in the dietary fibre composition among rice varieties with different amylose content. The percentage of insoluble dietary fibre (IDF) in whole grain rice varied from 1.65–4.32 while the percentage of soluble dietary fibre (SDF) ranged from 0.26–1.37. We demonstrated that the SDF/IDF ratio was higher in soft texture rice with low amylose and it shared a negative correlation with hardness and chewiness of cooked whole grain rice determined by a texture analyser, which suggested that the distribution of SDF throughout the rice endosperm influences the reduction of the hardness of cooked rice. According to the importance of dietary fibre, we proposed a simple linear regression method to estimate the amount of IDF and total dietary fibre with r = 0.97 and 0.92, respectively, of whole grain rice based on its bran layer, determined by the alternative alkaline method. Furthermore, low amylose rice has higher content of -glucan and pectin, which are classified as soluble dietary fibre, than high amylose rice. The percentage of -glucan and pectin in whole grain rice ranged from 0.03 and 0.07 respectively, for high amylose rice to 0.14 and 0.27 respectively for low amylose rice,

This paper reports the effect of silicon substrate orientation and aluminum nitride buffer layer deposited by molecular beam epitaxy on the growth of aluminum nitride thin films deposited by DC magnetron sputtering technique at low temperature. The structural analysis has revealed a strong (0001) fiber texture for both substrates Si (100) and (111) and a hetero-epitaxial growth on few nanometers AlN buffer layer grown by MBE on Si (111) substrate. SEM images and XRD characterization have shown an enhancement in AlN crystallinity thanks to AlN (MBE) buffer layer. Raman spectroscopy indicated that the AlN film was relaxed when it deposited on Si (111), in compression on Si (100) and under tension on AlN buffer layer grown by MBE/Si (111) substrates, respectively. The interface between Si (111) and AlN grown by MBE is abrupt and well defined; contrary to the interface between AlN deposited using PVD and AlN grown by MBE. Nevertheless, AlN hetero-epitaxial growth was obtained at low temperature (<250°C).

We report on space-selective crystallization of congruent and polar Sr2TiSi2O8 crystals in a stoichiometric SrO-TiO2-SiO2 glass induced by (1030 nm, 300 fs) femtosecond laser irradiation. This allows us to compare with non-congruent laser induced crystallization of polar LiNbO3, in non stoichiometric Li2O-Nb2O5-SiO2 glass and gain information on the mechanism of nanocrystals orientation with the laser polarization that we pointed out previously. Using scanning electron microscopy (SEM), Second-harmonic generation (SHG) and electron backscattered diffraction (EBSD), we studied the laser induced crystallization according to the laser processing parameters (pulse energy, pulse repetition rate, scanning speed). We found 1) a domain where the laser track is filled with crystals not perfectly textured (low energy), 2) a domain where an amorphous volume remain surrounded by a crystallized shell (high energy). This arises from Sr out-diffusion and may gives rise to crystallization of both SrTiO3 and Sr2TiSi2O8 phases at low speed. In the one-phase domain (at higher speed), it is found the possibility to elaborate a tube with a perfect fresnoite texture. Significant difference in size and morphology whereas crystallization threshold remains similar are discussed based on glases thermal propeties. Contrarily to Li2O-Nb2O5-SiO2 (LNS) glass, no domain of oriented nanocrystallization controlled by the laser polarization has been found in SrO-TiO2-SiO2 (STS) glass, which is attributed to the larger crystallization speed in STS glass. No nanogratings have also been found that is likely due to the congruency of the glass.

Targets detection in synthetic aperture radar (SAR) remote sensing images, which is a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Besides, the ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of SAR image scene still remains a challenge. This paper analyzes the defects and shortcomings of traditional visual models applied to SAR images. Then a visual attention model designed for SAR images is proposed. The model draws the basic framework of classical ITTI model; selects and extracts the texture features and other features that can describe the SAR image better. We proposes a new algorithm for computing the local texture saliency of the input image, then the model constructs the corresponding saliency maps of features; Next, a new mechanism of feature fusion is adopted to replace the linear additive mechanism of classical models to obtain the overall saliency map; Finally, the gray-scale characteristics of focus of attention (FOA) in saliency map of all features are taken into account, our model choose the best saliency representation, Through the multi-scale competition strategy, the filter and threshold segmentation of the saliency maps can be used to select the salient regions accurately, thereby completing this operation for the visual saliency detection in SAR images. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X), Radarsat-2, are used to evaluate the performance of visual models. The results show that our model provides superior performance compared with classical visual models. By further contrasting with the classical visual models, Our model reduce the false alarm caused by speckle noise, and its detection speed is greatly improved, and it is increased by 25% to 45%.

Researchers are exploring solutions to meet the growing demand for protein due to the expected increase in global population by 2050. Interest in alternative protein sources like insects has risen, driven by concerns about environmental impact and the need for sustainable food production. This study aimed to develop and evaluate the physicochemical properties of soy protein-based burger enriched with insect protein from Alphitobius diaperinus. Three formulations were developed: a control (B0), and burgers with 5% (B5) and 10% (B10) insect protein - Whole Buffalo Powder (WBP). Results showed that adding insect protein decreased the burger analogue's pH. There was observed a clear trend of increasing total lipids and SFA, and decreasing MUFA and PUFA, as the WBP concentration increases from 0% to 10%. No significant differences with increasing WBP concentration in the protein content of the burger analogue, as well as the cooking yield, were noted. The WBP addition had a notable effect on the color change, especially decrease in brightness (L*). It was shown that as the WBP concentration increased, there were no significant differences in the texture profile of the burger analogues. The formulation with 5% WBP concentration was the most acceptable in sensory analysis.

High-methoxyl apple pectin (AP) derived from apple was employed as the main ingredient facilitating rheological modification features for developing dysphagia-friendly fluidized alimentary matrices. Xanthan gum (XG) was also included as a composite counterpart to modify the viscoelastic properties of the thickened system under different thermal processes. The results indicate that AP is extremely sensitive to thermal processing, and the viscosity is greatly depleted under a neutral pH level. Moreover, the inclusion of calcium ions echoed a modification effect on the rheological properties of AP, and both the elastic property and viscosity value are promoted after thermal processing. The modification effect of viscoelastic properties (Gʹ and Gʹʹ) is observed while XG is incorporated into the composite formula. By promoting the XG ratio from 7: 3 to 6: 4 (AP: XG), it triggers the rheological transformation from a liquid-like form to a solid-like state, and the viscosity value shows that the AP-XG composite system exhibits better thermal stability after thermal processing. The ambient modifiers of pH (pH &lt; 4) and calcium chloride concentration (7.5%) with an optimal AP-XG ratio of 7:3 lead to weak-gel-like behavior (Gʹʹ &lt; Gʹ), helping to maintain the texture properties of dysphagia-friendly features similar to those prior to the thermal processing.

The mechanical behavior, microstructures as well as the crystallographic textures of the Ti57-Nb43 alloy were investigated on cylindrical specimens compressed at high temperatures, in the range of 700-1000 °C, and strain rates between 0.001 and 1.0 s-1. Hardening, followed by softening behaviours were observed as a function of strain, due to the occurrence of dynamic recrystallization/recovery in hot deformation. The modified five-parameter Voce type equation described well the stress-strain curves, but for the present alloy, it was also possible with only four parameters. A new two-variables polynomial function was employed on the four parameters that described well the flow curves as a direct function of temperature and strain rate. It permitted to reduce the number of parameters and had the predictive capacity for the flow stress at any temperature, strain, and strain rate in the investigated range. The crystallographic textures were similar at all temperatures with an increase of intensity from 900 °C. The textures could be characterized by a double &lt;100&gt; and &lt;111&gt; fiber and a unique component of (001)&lt;110&gt;, the latter inherited from the initial hot rolling texture. Viscoplastic polycrystal self-consistent deformation modeling reproduced the measured textures showing that dynamic recrystallization did not alter the development of the deformation texture, only increased it intensity.

The changes in storage loss, water distribution status, gel characteristics, TBARS, total volatile basic nitrogen, and total plate count of cooked reduced-phosphate silver carp surimi batter during cold storage at 4 °C were investigated. The storage loss, content of free water, pH, hardness, TBARS, total volatile basic nitrogen value and total plate count of all cooked reduced-phosphate silver carp surimi batters significantly increased (P < 0.05) with increasing the cold storage time. Meanwhile, the content of immobilized water, whiteness, springiness, and cohesiveness decreased significantly (P < 0.05). At the same cold storage time, the sample of cooked reduced-phosphate silver carp surimi batter has lower water mobility, darker colour and better texture characteristics, but the values of TBARS, total volatile basic nitrogen and total plate count were not significantly different (P > 0.05). To sum up, the use of potassium bicarbonate instead of sodium tripolyphosphate could produce the cooked reduced-phosphate silver carp surimi batter with better water holding capacity and gel characteristics during cold storage.

In winter sports, the equipment often comes into contact with snow or ice, and this contact generates a force that resists motion. In some sports, such as cross-country skiing, this resistive force can significantly affect the outcome of a race, as a small reduction in this force can give an athlete an advantage. Researchers have examined the contact between skis and snow in detail, and to fully understand this friction, the entire ski must be studied at various scales. At the macro scale, the entire geometry of the ski is considered and the apparent contact between the ski and the snow is considered and at the micro scale the contact between the snow and the ski base ski-base textures. In the present work, a method for characterising contact between the ski-base texture and virtual snow will be presented. Six different ski-base textures will be considered. Five of them are stone-ground ski bases, and three of them have linear longitudinal textures with a varying number of lines and peak-to-valley height, and the other two are factory-ground “universal” ski bases. The sixth ski base has been fabricated by a steel-scraping procedure. In general, the results show that a ski base texture with a higher Spk-value has less real contact area, and that the mutual differences can be large for surfaces with similar Sa-values. The average interfacial separation is, in general, correlated with the Sa-value, where a “rougher” surface exhibits a larger average interfacial separation. The results for the reciprocal average interfacial separation, which is related to the Couette type of viscous friction, were in line with the general consensus that a “rougher” texture performs better at high speed than a “smoother” one, and it was found that a texture with high Sa and Spk values resulted in a low reciprocal average interfacial separation and consequently low viscous friction. The reciprocal average interfacial separation was found to increase with increasing real contact area, indicating a correlation between the real area of contact and the Couette part of viscous friction.

The rapid urbanization that takes place in developing regions such as Sub-Saharan Africa is associated with a large range of environmental and social issues. In this context, remote sensing is essential to provide accurate and up-to-date spatial information to support risk assessment and decision making. However, mapping urban areas remains a challenge because of their heterogeneity, especially in developing regions where the highest rates of misclassification are observed. Nevertheless, urban areas located in arid climates --- which are among the most vulnerables to anthropogenic impacts, suffer from the spectral confusion occurring between built-up and bare soil areas when using optical imagery. Today, the increasing availability of satellite imagery from multiple sensors allow to tackle the aforementioned issues by combining optical data with Synthetic Aperture Radar (SAR). In this paper, we assess the complementarity of the Landsat 8 and Sentinel-1 sensors to map built-up areas in twelve Sub-Saharan African urban areas, using a pixel-level supervised classification based on the Random Forest classifier. We make use of textural information extracted from SAR backscattering data in order to reduce the speckle noise and to introduce contextual information at the pixel level. Results suggest that combining both optical and SAR features consistently improves classification performances, mainly by enhancing the differentiation between built-up and bare lands. However, the fusion was less beneficial in mountainous case studies, suggesting that including features derived from a Digital Elevation Model (DEM) could improve the reliability of the proposed approach. As suggested by previous studies, combining features computed from both VV and VH polarizations consistently led to better classification performances. On the contrary, introducing textures computed from different spatial scales did not improve the classification performances.

This study investigated the optimal treatment conditions to improve the quality of white pan bread by applying high-voltage pulsed electric fields (PEF) technology with varying electric field treatment times to bread dough. The treatment was conducted at an electric field strength of 2 kV/cm, frequency of 10 Hz, and a pulse width of 100 µs, with varying treatment time of 10, 20, and 30 min. When PEF was applied for 10 min, the treatment dough’s fermentation expansion rate was significantly higher. Bread made with the 10 min treated dough also exhibited higher weight, volume, specific volume, and moisture content, along with lower oven spring and baking loss rate. During storage, the 10 min treated samples maintained higher moisture content, while the 20 and 30 min treated samples showed no significant difference. In terms of texture profile analysis, the treated samples had lower hardness and chewiness compared to the control, while springiness, cohesiveness, and resilience tended to be slightly higher. In terms of texture, the treated samples had lower hardness and chewiness, but higher springiness, cohesiveness, and resilience compared to the control group.

Oleogels are of high interest as promising substitutes for trans fats in foods. An emulsion-templated method was used to trap olive oil in the chitosan crosslinked with vanillin matrix. Oil in water emulsions (50:50 w/w) with different chitosan content (0.7 and 0.8% w/w) with constant vanillin/chitosan ratio (1.3) were air-dried at different temperatures (50, 60, 70 and 80ºC) and freeze-dried (-26ºC and 0.1 mbar) to produce oleogels. Only falling-rate periods were determined during air-drying kinetics and were successfully modelled with empirical and diffusional models. At drying temperature of 70ºC the drying kinetics were the fastest. Viscoelasticity of oleogels showed that elastic modulus significantly increased after drying at 60 and 70ºC, and those dried at 50ºC and freeze-dried were weaker. All oleogels showed high oil binding capacity (&gt; 91%), but the highest values (&gt; 97%) were obtained in oleogels with a threshold elastic modulus (50,000 Pa). Oleogels color depended on drying temperature and chitosan content (independent of the drying method). Significant differences were observed between air-dried and freeze-dried oleogels with respect to oxidative stability. Oxidation increased with air drying time regardless of chitosan content. Found results indicated that drying conditions must be carefully selected to produce oleogels with specific features.

ORB (Oriented FAST and Rotated Brief) features are the most commonly used features in visual SLAM and visual odometry that have high computational speed, and rotation scale invariance. However, due to the homogenization of ORB features, the corner properties of specific features are poor in some artificial environments, and it can lead to poor matching performance when the environmental texture is not rich. The underlying reason is that the pixel grayscale changes in the less-richly textured regions on the image are not obvious, leading to a certain degree of mis-matching in the matching process. At the same time, when the camera motion speed is low, there is much overlap between adjacent frames. This results in minimal or almost no changes in the projection of feature points, and the system is highly sensitive to errors, In this case, even small errors can cause significant fluctuations in the calculation results. In response to the above issues, an improved feature point method for stereo vision mileage calculation is proposed to solve the problem of system stability deterioration when cameras move at low speeds in artificial envi-ronments. Firstly, weight calculation based on different texture regions is used to solve the problem of low corner properties of feature points caused by environmental texture differences. Then, keyframes are used for motion model estimation to improve the system's stability under low-speed motion. The experimental results of the dataset showed that the key frame rate was optimal between 10% and 12%, and the positioning accuracy was higher than these open-source systems compared with three common open-source VO systems.

Efficient management of basal cell carcinoma (BCC) requires reliable assessments of both tumors and post-treatment scars. We aimed to estimate image similarity metrics that account for BCC's perceptual color and texture deviation from perilesional skin. 176 clinical photographs of BCC were assessed by six physicians using a visual deviation scale. Internal consistency and inter-rater agreement were estimated using Cronbach's α, weighted Gwet's AC2, and quadratic Cohen's Kappa. The mean visual scores were used to validate a range of similarity metrics employing different color spaces, distances, and image embeddings from pre-trained VGG16 neural network. The calculated similarities were transformed into discrete values using ordinal logistic regression models. The Bray-Curtis distance in the YIQ color model and rectified embeddings from the 'fc6' layer minimized the mean squared error and demonstrated strong performance in representing perceptual similarities. Box plot analysis and Wilcoxon rank-sum test were used to visualize and compare the levels of agreement, conducted on a random validation round between the two groups: ‘Human-System’ and ‘Human-Human’. The proposed metrics were comparable in terms of internal consistency and agreement with human raters. The findings suggest that the proposed metrics offer a robust, and cost-effective approach to monitoring BCC treatment outcomes in clinical settings.

The optical reflection characteristics of asphalt pavement are an important influencing factor in road lighting design, and the macro and micro textures of asphalt pavement significantly affect its reflection characteristics. To investigate the impact of texture parameters on the retroreflection coefficient of asphalt pavement, this study obtained the macroscopic and microscopic texture properties of rutting board specimens and on-site asphalt pavement using a pavement texture tester. The macro- and microtexture parameters, such as macroscopic texture distribution density (D1), microscopic texture distribution density (D2), profile height root-mean-square (Rq), profile slope root-mean-square (Δq), skewness Rsk and kurtosis Rku, were measured, and the corresponding retroreflection coefficient RL was measured using a retro-reflectometer. In the laboratory ex-periments, rutting specimens of AC-13, SMA-13, and OGFC-13 asphalt mixtures were formed. The changes in texture parameters and retroreflection coefficient of different rutting specimens before and after crushing were studied, and a factor influence model between macro- and microtexture parameters and RL was established. And the correlation models of texture index and RL of asphalt pavement are further established. The results showed that in the single factor model, the param-eters can be used to characterize RL with high prediction accuracy, whereas for the on-site meas-urements, the three parameters of Δq, Rsk, and Rku can characterize the RL well. The nonlinear model established on the basis of the B-P neural network algorithm improves its prediction ac-curacy. This research can provide ideas for optimizing the reflection characteristics of asphalt pavement and further provide a decision-making basis for road lighting design.

At the highest level of endurance sports, the differences in finishing times are small, so equipment is constantly being constantly improved to enhance the athletes' performance. For instance, one dominant resistive force in connection with cross-country skiing is the friction between the skis and snow and since the 1930s, research designed to understand and reduce this friction has been ongoing. The mechanisms involved in ski-snow friction include compaction, micro-ploughing, adhesion, viscosity, and water-bridging. Of these, adhesive and viscous friction have been most studied, while much less is presently known about compaction, micro-ploughing, and water-bridging. At the macro-scale, the ski-camber profile plays a key role in determining whether, with respect to friction, a particular cross-country ski is suitable for use under a given set of conditions. Through its influence on where ski-snow contact occurs, this ski-camber profile has a profound impact on adhesive and viscous friction, micro-ploughing, the formation of water bridges, and the rate of compaction. Different contact zones with different apparent areas of contact and pressure have been found to be most suitable for different conditions. In addition, the micro-scale texture of the ski base is also an important determinant of ski-snow friction. Topographical measurements of this texture can be achieved with white-light interferometer and recent characterisation has focused on the mechanical properties of contact. In numerous tribological studies the interactions between features at different scales are modelled. In most tribological systems, features on several scales influence friction and ski-snow contact is certainly no exception. Accordingly, the current investigation was designed to evaluate the multi-scale properties of different combinations of two skis with two different base textures. The real area of contact and the average interfacial separation and total average reciprocal interfacial separation between the ski and snow were taken into consideration. We found that different macro- and micro-scale properties of the ski favour different mechanisms of friction. Both the profile of the ski camber and texture of the base play decisive roles in determining viscous friction. At the same time, the texture of the ski base exerts a greater impact on the average real contact pressure, real contact area and minimal average interfacial separation between the ski and snow than does the ski-camber profile.

Surfaces of additively manufactured metal parts from powder-based processes typically show powder particle agglomerations and other features, resulting in high surface roughness. Proper characterization of those surfaces is necessary in order to assess part quality with respect to coatability, mechanical performance or corrosion resistance for use in aerospace, automotive, medical and more industrial applications. Optical surface texture measurement allows for collection of areal surface data, while the established contact stylus method only captures line profile data. When applying optical methods for surface topography measurements, proper data acquisition and post-processing in order to assess surface texture may be complex. A number of variables can be adjusted, such as different measurement settings, approaches to outlier removal, evaluated area size or form removal. This work shows the influence of selected z-range prior to measurement and the influence of choosing pre-defined outlier removal settings in MountainsMap 9.2 on selected ISO 25178-2:2022 parameters calculated from data obtained from confocal microscopy for as-built Ti6Al4V from laser powder bed fusion. The aim is to show the influence of variation in measurement and post-processing on calculated surface texture parameters and stress the importance of proper documentation in order to achieve reproducibility of data for quality management.

For a wide industrial application of magnesium alloys, a method for imparting high damping properties while maintaining mechanical properties is required. Controlling the crystallographic texture seems to be useful, because dislocations are known to have a significant influence on the damping characteristics of magnesium alloys. Therefore, the effect of twinning and annealing, which can affect to the recrystallization were investigated in this study. An AZ31 alloy was hot rolled at 673K with a reduction ratio of 10 % and 50 %, and then annealed at 673K and 723K for 0.5, 1, 2, and 3H respectively. SEM-EBSD was used to examine the microstructure and texture. In addition, each specimen’s hardness and internal friction were contemporarily measured. As a result, hot rolling produced tensile twins and their fraction increased with internal friction when the reduction ratio increased. Due to annealing, a discontinuous type of static recrystallization occurred within the twinning grains, and was highly activated along with the increasing annealing temperature and the fraction of twinning. In the samples annealed at 723K, the internal friction continuously increased over the annealing time, whereas in the samples annealed at 673K, the decrease in dislocation density was delayed while, the internal friction showed a relatively low value.

Introduction: In Traditional Chinese Medicine (TCM), tongue diagnosis plays an important role. Besides shape, colour and textural attributes of tongue regions have significance due to their association with different organs (viz. heart, lung, kidney-bladder, liver-gallbladder and stomach-spleen) in health and disease. Although numerous quantitative methods have been proposed to reduce inter and intra observer variability in tongue diagnosis, almost all of them considered only global colour/ textural features i.e. from entire body of tongue. In this work, regional colour and texture information of tongue have been analysed for healthy subjects (NOM) and patients suffering from chronic acidity-indigestion (ACD). Methods: Tongue boundaries are marked manually in each image and then tongue bodies are automatically partitioned into five regions linked with said internal organs. Rough assessments of regions’ boundaries are obtained from literature and then they are fine-tuned according to experts’ advice. As boundaries are not well defined, regions near the common boundary of two or more organs, are not assigned to any organ. Several first and second order statistical features based on grey scale intensities and a* values of LAB colour space (indicative of redness) have been extracted from five different regions of tongue images. Intragroup analysis using Wilcoxon signed rank test compared different regions within individual study group. Additionally, intergroup analysis using Wilcoxon rank sum test compared tongues of NOM with ACD for each region separately. Results: Intragroup analysis reveals a* values are statistically different (p&lt;0.01) between stomach-spleen and liver-gallbladder regions for ACD while no significant change of a* are noted between these regions of normal tongue. It was found from intergroup analysis that correlation (one of the second order texture features extracted from grey scale images) of heart region has significantly decreased while correlation of kidney, liver-gallbladder and stomach-spleen regions significantly increased from NOM to ACD. Conclusion: This study sheds light on importance of inclusion of regional textural analysis of tongue in quantitative studies and can be applied to automated tongue diagnosis for other diseases.

The models of partial least squares (PLS) regression and artificial neural network (ANN) for evaluation of texture properties of cooked germinated brown rice (GBR) using the Fourier transform near infrared (NIR) spectra of uncooked whole grain combined with data separation methods, spectral pretreatment methods were investigated in this study. The ANN was outperformed in evaluation of hardness by back extrusion test of cooked GBR using the smoothing combined with standard normal variate pretreated NIR spectra in the range of 12,500-4,000 cm−1 of 188 whole grain samples where the calibration sample set was separated from prediction set by Kennard-Stone method where the best ANN model for hardness from hidden layers of 25 and 8 iteration time provided R2, r2, RMSEC, RMSEP, Bias and RPD of 0.9987, 0.9447, 0.1021 N, 0.7699 N, 0.0216 N and 4.3 respectively. The PLS regression of 64 sample KDML GBR group and 64 sample various variety GBR group, provided models for the hardness of the former and the toughness of the latter which developed by using 7506−5446.3, 4605.4−4242.9 cm−1 which included the amylose vibration band of 6834 cm−1 while toughness model was from 9403.8-6094.3 cm−1 where included 6834 and 8316 cm−1 vibration bands of amylose which influenced the texture of cooked rice. The PLS regression models for hardness and toughness were with the r2 of 0.85 and 0.82, and the RPD of 2.9 and 2.4, respectively. The ANN model for hardness of cooked GBR should be implemented to the practical use in GBR production factories for the quality assurance and further updating using more samples and several brands to obtain the robust models.

This study investigates multiple extrusion regimens with twin screw extruder for valorising soy press cakes (by-products of soy drink & tofu manufacturing process) by varying physical conditions of extrusion (temperature and moisture content) for improving their morphological, physico-chemical, technological, and sensory parameters. Valorised soy press cakes were compared before and after extrusion. Four extrusion regimens (moisture content 30%-60% and temperature 110°C -120°C) were designed for producing different extruded samples. Small amounts (3%-6%) of untreated and extruded press cakes were utilised in the development of meat analogues. All samples showed comparable nutritional and trypsin inhibition activity with almost all samples possessing most essential amino acids above significant amounts. Press cakes with higher moisture indicated improved bulk density, water holding and oil holding capacity. Interestingly, the same samples also reportedly had texture more closely resembling native meat texture and scored the highest in overall sensory acceptance. Our results thus indicate that soy press cake samples from drink manufacturing process, when extruded with the regimen with 60% moisture and temperature of 120°C show the greatest potential in developing meat analogues.

As a result of the growing demand for foods with reduced animal protein content, many new alternative diets are now emerging. Nevertheless, recent studies have shown that the Western population is unprepared for drastic changes and is disinclined to accept foods based on alternative proteins. However, hybrid products might become a good transitional offer. This study used a desirability-based mixture design to model hybrid spreadable cheese analogues (SCAs). The design combined the dairy protein (MPC), Tenebrio molitor (IF) and faba bean (FBP) flours. Nine SCAs with different MPC/FBP/IF ratios were formulated, representing 0, 50 and 100% MPC replacement (7.1% of the formula). Incorporating the IF negatively impacted the desirable texture properties. The FBP flour improved the texture (achieving increased firmness and stickiness and decreased spreadability), but only when combined with MPC. Changing the MPC/FBP/IF ratio affected the colour of SCAs. Sensory analysis showed that hybrid SCAs (≤ 50% MPC) had a more characteristic cheesy flavour than the commercial plant-based reference, and sample C2 had a texture profile similar to the dairy reference. Samples containing IF showed a better flavour profile than the products without IF. The SCAs had higher protein and lower saturated fat, starch and sugar con-tent than commercial analogues.This study demonstrates that the inclusion of alternative proteins can be effective as a strategy to reduce dairy protein content in hybrid product formulations.

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 km² agricultural plain investigated through a dedicated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gamma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

Background: Upper tract urothelial carcinoma (UTUC) presents significant challenges in prognostication due to its rarity and complex anatomy. This study introduces a novel approach integrating perirenal fat (PRF) radiomics with clinical factors to enhance prognostic accuracy in UTUC. Methods: The study retrospectively analysed 103 UTUC patients who underwent radical nephroureterectomy. PRF radiomics features were extracted from preoperative CT scans using a semi-automated segmentation method. Three prognostic models were developed: clinical, ra-diomics, and combined. Model performance was assessed using concordance index (C-index), time-dependent Area Under the Curve (AUC), and integrated Brier score. Results: The combined model demonstrated superior performance (C-index: 0.784, 95% CI: 0.707-0.861) compared to the radiomics (0.759, 95% CI: 0.678-0.840) and clinical (0.653, 95% CI: 0.547-0.759) models. Time-dependent AUC analysis revealed the radiomics model's particular strength in short-term prognosis (12-month AUC: 0.9281), while the combined model excelled in long-term predictions (60-month AUC: 0.8403). Key PRF radiomics features showed stronger prognostic value than traditional clinical factors. Conclusions: Integration of PRF radiomics with clinical data significantly improves prognostic accuracy in UTUC. This approach offers a more nuanced analysis of the tumour microenvironment, potentially capturing early signs of tumour invasion not visible through conventional imaging. The semi-automated PRF segmentation method presents advantages in reproducibility and ease of use, facilitating potential clinical implementation.

Automatic garments design class identification for recommending the fashion trends is important nowadays because of the rapid growth of online shopping. By learning the properties of images efficiently, a machine can give better accuracy of classification. Several methods, based on Hand-Engineered feature coding exist for identifying garments design classes. But, most of the time, those methods do not help to achieve better results. Recently, Deep Convolutional Neural Networks (CNNs) have shown better performances for different object recognition. Deep CNN uses multiple levels of representation and abstraction that helps a machine to understand the types of data (images, sound, and text) more accurately. In this paper, we have applied deep CNN for identifying garments design classes. To evaluate the performances, we used two well-known CNN models AlexNet and VGGNet on two different datasets. We also propose a new CNN model based on AlexNet and found better results than existing state-of-the-art by a significant margin.

Biochar is a carbon-rich material that recently received attention due to its increasing agronomical potential. The agricultural utilization of biochar relates to its potential to act in the soil as a soil conditioner, nevertheless, the complex information on the direct dependence of biochar physical properties (texture, particle size) and corresponding leaching and availability of organic molecules (e.g. the polycyclic and heterocyclic organic compounds) and inorganic mineral salts (based on micro– and macroelements) are still not consistent. These aspects were addressed in our study. A multi-elemental analysis (ICP-OES) was used to access the information on the aqueous-extractable and total contents of inorganic macro- and macroelements in used commercial biochar samples (purchased from Sonnenerde GmbH, Novoterrra Sonnenerde GmbH, Biouhel.cz, s.r.o.). Potassium (K) was identified as the major macroelement, responsible for alkaline pH and the conductivity of biochar extract. Our results indicate an indirect relation between the size fraction of biochar and the content of extractable K, sodium (Na), and calcium (Ca) and a direct relation with the contents of phosphorus (P) and magnesium (Mg). As the total determined amounts of inorganic elements were significantly higher compared to aqueous-extractable amounts, we believe it could indicate the potential for repeated release to the surrounding soil. These findings were also confirmed by the analysis of biochar samples obtained after the cultivation (duration of 2 years) in selected representative soil samples from the Czech Republic (Cambisol, Fluvisol, Regosol, Chernozem). Moreover, gas chromatography (GC) coupled with mass spectroscopy (MS) was further used to reveal the concentrations of available polycyclic aromatic and heterocyclic compounds in biochar samples. The detected concentration of these types of organic compounds were far below the certified limits. We believe our in-depth analysis could provide the necessary insight into the description of biochar mineral content, its connection to biochar texture, corresponding physicochemical properties and potential availability to leach nutrients to the soil. These findings could help in further assessment of the potential applications of biochar in modern agriculture as a soil conditioner.

Abstract: Passive acoustic monitoring (PAM) is a non-invasive technique to supervise the wildlife. Acoustic surveillance is preferable in some situation such as in the case of marine mammals, when the animals spend most of their time underwater, making it hard to obtain their images. Machine learning is very useful for PAM, for example, to identify species based on audio recordings. But some care should be taken to evaluate the capability of a system. We define PAM-filters as the creation of the experimental protocols according to the dates and locations of the recordings, aiming to avoid the use of the same individuals, noise and recording devices in both training and test sets. A random division of a database present accuracies much higher than accuracies obtained with protocols generated with PAM-filter. Although we use the animal vocalizations, in our method we convert the audio into spectrogram images, after that, we describe the images using the texture. Those are well-known techniques for audio classification, and they have already been used for species classification. Also, we perform statistical tests to demonstrate the significant difference between accuracies generated with and without PAM-filters with several well-known classifiers. The configuration of our experimental protocols and the database were made available online.

In Indonesia, types of meat are still identified manually due to increasing prices for beef and buf-falo ahead of Idul Fitri. Traders mix beef with pork to thwart the beef scam. Haar wavelet and GLCM, GLCM with angles of 0°, 45°, 90°, and 135°, as well as matrices using contrast, correlation, energy, homogeneity, and entropy, are used in feature extraction. The following are the results of meat image classification testing using k-NN, Haar wavelet, and GLCM: The k-NN algorithm shows superiority in identifying fresh (99%), frozen (99%), and rotten (96%) meat texture images with the most fantastic accuracy results in every situation. Meanwhile, GLCM routinely provides good results, especially regarding the texture image of fresh meat (183.21) and rotten meat (115.79). However, despite delivering less throughput than k-NN and GLCM, Haar wavelets are still helpful, especially when dealing with fresh meat texture images (89,96).

This study investigated defect formation and strain distribution in high Mg content Al-Mg alloys during normal rolling and cross-rolling processes. The finite element analysis (FEA) revealed the presence of wave defects and strain localization-induced zipper cracks in normal cold rolling, which were confirmed by experimental results. The concentration of shear strain played a significant role in crack formation and propagation. However, the influence of wave defects was minimal in the cross-rolling process, which exhibited a relatively uniform strain distribution. Nonetheless, strain concentration at the edge and center regions led to the formation of zipper cracks and edge cracks, with more pronounced propagation observed in the experiments compared to FEA predictions. Furthermore, texture evolution was found to be a crucial factor affecting crack propagation, particularly with the development of the Goss texture component which is observed by electron backscattered diffraction analysis at bending points. The Goss texture hindered crack propagation, while the Brass texture allowed cracks to pass through. This phenomenon was consistent with both FEA and experimental observations. To mitigate edge crack formation and propagation, potential strategies involve promoting the formation of the Goss texture at the edge through alloy and process conditions, as well as implementing intermediate annealing to alleviate stress accumulation. These measures can enhance the overall quality and reliability of Al-Mg alloys during cross-rolling processes. In summary, understanding the mechanisms of defect formation and strain distribution in Al-Mg alloys during rolling processes is crucial for optimizing their mechanical properties. The findings of this study provide insights into the challenges associated with wave defects, strain localization, and crack propagation. Future research and optimization efforts should focus on implementing strategies to minimize defects and improve the overall quality of Al-Mg alloys in industrial applications.

Metal additive manufacturing technologies have large potential for future use in load bearing aerospace applications, requiring a deeper understanding of mechanical performance and influencing factors. The objective of this study is to manufacture fatigue specimens by laser powder bed fusion with comparable bulk and different as-built surface quality (without post-processing). This goal was pursued by using identical bulk/hatch scan parameters while varying contour scan parameters. The bulk quality was evaluated by density measurements according to Archimedes’ principle and tensile testing. The surfaces were investigated using the optical fringe projection method and surface quality was assessed by the areal surface texture parameters Sa (arithmetic mean height) and Sk (core height, derived from material ratio curve). The resulting mean values of max (ultimate tensile strength) were between 375 and 405 MPa, which is a variation of roughly 8%, for seven different surface conditions. It could be confirmed that the influence of contour scan variation on bulk quality is insignificant for the assessed samples.

Forest degradation is known to be widespread in the tropics, but is currently very poorly mapped, in part because there is little quantitative data on which satellite sensor characteristics and analysis methods are best at detecting it. To improve this, we used data from the Tropical Forest Degradation Experiment (FODEX) plots in the southern Peruvian Amazon, where different numbers of trees had been removed from four 1 ha forest plots, carefully inventoried by hand and Terrestrial Laser Scanning before and after the logging to give a range of biomass change (ΔAGB) values. We conducted a comparative study of six multispectral optical satellite sensors (WorldView-3, SkySat, SPOT-7, PlanetScope, Sentinel-2 and Landsat 8) at 0.3 – 30 m spatial resolution, to find the best combination of sensor and remote sensing indicator for change detection. Spectral reflectance, the Normalized Difference Vegetation Index (NDVI) and texture parameters were extracted after radiometric calibration and image preprocessing. The strength of the relationships between the change in these values and field-measured ΔAGB (computed in % ha−1) was analysed. The results demonstrate that: (a) texture measures correlates more with ΔAGB than simple spectral parameters; (b) the strongest correlations are achieved for those sensors with spatial resolutions in the intermediate range (1.5 - 10 m), with finer or coarser resolutions producing worse results, and (c) when texture is computed using a moving square window ranging between 9 - 14 m in length. Maps predicting ΔAGB showed very promising results using a NIR-derived texture parameter for 3 m resolution PlanetScope (R2 = 0.97 and RMSE = 1.80 % ha−1), followed by 1.5 m SPOT-7 (R2 = 0.74 and RMSE = 5.25 % ha−1) and 10 m Sentinel-2 (R2 = 0.71 and RMSE = 5.55 % ha−1). Texture models derived from 0.3 m WorldView-3 improved with increasing window size, with highest R2 of 0.62 and RMSE = 6.35 % ha−1 for a window of 14 m in length. The degradation in our field plots is invisible to the 30 m resolution Landsat data. Our findings imply that, at least for lowland Peru, low-medium intensity disturbance can be detected best in optical wavelengths using a texture measure derived from 3 m PlanetScope data. That such data are being collected daily, and currently released free as monthly mosaics over tropical forests as part of the Norway’s International Climate and Forest Initiative (NICFI), is excellent news for monitoring such degradation.

This research presents a novel approach for estimating soil organic carbon (SOC) content in agricultural soils using a photocatalytic Chemical Oxygen Demand (PeCOD) analyzer integrated with Geographic Information System (GIS) technology for spatial analysis. The PeCOD method, which relies on photochemical oxidation of organic carbon, demonstrated an uncanny correlation between its values and SOC content, making it a quick and accurate way to estimate SOC levels. Finer materials, such as clayey soils, demonstrated higher SOC content compared to coarser ones and decreased with increasing soil depth. GIS georeferencing enabled precise mapping of SOC distribution and identification of hotspot areas with high SOC content. This study highlights the significance of soil texture and depth on SOC distribution and emphasizes its significance within geological context when studying soil properties. Research results have practical ramifications for sustainable agriculture, climate change mitigation and soil health management - providing farmers and land managers with strategies that increase carbon sequestration while simultaneously improving soil health. Integrating PeCOD analyzer technology with GIS technology offers promising avenues for advanced soil carbon monitoring practices that promote climate-smart agricultural practices.