Texture Analysis Research Articles

Tomato Pedicel Physical Characterization for Fruit-Pedicel Separation Tomato Harvesting Robot

To solve the problem of the lack of physical properties of pedicels and the changing pattern for designing the end-effector of tomato harvesting robot and different harvesting modes, research was conducted on the physical properties of tomato pedicels and their change patterns. Using a Universal TA texture analyzer, tensile, three-point bending, and shearing tests were performed on tomato pedicels in the early firm-ripening stage. The tomato variety used was Syngenta Spectrum, cultivated seasonally with two crops per year. Spring crop tomatoes were used in this study. The experimental results provide a theoretical basis for designing tomato harvesting robots across three harvesting modes. Tensile tests measured the pull-off force and tensile strength of the abscission zone with varying diameters. These results are crucial for designing robots using a tensile harvesting mode. The location of the tomato pedicel significantly affects the shearing force. A one-way test was conducted on the shearing part. The results showed that the shearing force and energy required for the proximal pedicel are significantly greater than for the distal pedicel. To reduce the shearing force and energy needed by the end-effector’s shearing mechanism on distal pedicels, a response surface test was conducted. Three factors were examined: shearing speed, angle, and distal pedicel diameter. Design–Expert software optimized these factors to minimize shearing energy and force, leading to the best shearing parameters for different distal pedicel diameters. From the three-point bending tests, the average maximum bending breaking force, bending modulus, and bending strength of the tomato abscission zone were determined. These findings offer a theoretical basis for designing tomato harvesting robots with a bending-type harvesting mode.

Operator-independent assessment of bread spoilage profiles caused by Bacillaceae reveals a high degree of inter- and intraspecies heterogeneity

Ropy bread spoilage caused by aerobic spore-forming bacteria (ASF) is characterized by discoloration, sticky and stringy crumb degradation, and a fruity odor due to the release of volatile organic compounds (VOCs). Previous studies employing model experiments have demonstrated strain-specific spoilage potential. However, to gain a deeper understanding, it is essential to study rope spoilage within baked bread. This study aimed to objectively evaluate the effect of different ASF strains on bread quality. 82 strains were subjected to a comprehensive evaluation, including proteotypic and genotypic fingerprinting, and 13 were selected for further analysis, where ASF endospore-spiked dough samples were baked and incubated. Physical changes in crumb texture, discoloration, and VOC production were quantified using texture analysis, color measurements, and headspace solid-phase microextraction gas chromatography-mass spectrometry. The high intraspecies diversity was reflected in strain-specific variations in rope spoilage profiles. A significant reduction in crumb firmness and increased discoloration, as well as the development of high levels of relative acetoin, were associated with rope spoilage. While color measurements could not detect early-stage spoilage, changes in crumb texture and VOC development were detectable after 24 h of baking. Even low levels of contamination (10^1 spores/g) could cause potential spoilage detectable by texture analysis, although not visible to the naked eye. This study provides an unbiased framework for future research and may help develop early detection tools for improved bread spoilage management.

Studying Impact of Moisture, Node Position and Loading Rate of Paddy Straw on its Mechanical Properties

In this study, mechanical properties of paddy straw such as bending strength, shear strength and Young's modulus were determined through force-deformation curve using textural analyzer with 50 kg load cell. The mechanical properties were determined at three moisture contents, i.e., 18.4% (M1), 13.5% (M2) and 10.8% (M3), at three node positions, i.e., N1, N2 and N3 and three loading rates, i.e., 25, 30 and 35 mm min-1, respectively. The results revealed that moisture content and loading rate at different node positions significantly (p<0.01) affected the bending strength, shear strength, and Young's modulus of straw, whose values varied from 5.35 to 17.34 MPa, 4.99 to 7.35 MPa, 0.43 to 1.39 GPa, respectively, through N1 to N3 with decrease in moisture content; likewise, other findings also indicated increase in output values on increasing loads through N1 to N3. Cutting force was also significantly affected (p<0.01) by shear angle and moisture content, which varied from 6.39 to 22.9 N, and cutting energy ranged from 142 to 511 J by Straw Management System serrated blade and was found to be minimum at 20° shear angle. The mechanical property of the straw for residue management in the context of cutting force for node position N3 at the initial moisture content was found optimum.

Improving the Accuracy of Building Damage Estimation Model Due to Earthquake Using 10 Explanatory Variables

Aiming to support disaster recovery, we have developed a new method to extract damaged buildings by using machine learning that combines 10 explanatory variables obtained from analysis of aerial photographs and observation data. We used site amplification factors, seismic intensities of foreshock and mainshock, distance from faults, estimated building structures and ages, coverage by blue tarps, texture analysis, and digital surface model differences before and after the earthquake as explanatory variables, in addition to convolutional neural network prediction results based on post-earthquake aerial photographs. The random forest method resulted in an overall accuracy of about 81% and an average F-measure of three classes was about 70%, indicating that it can classify possible damage to buildings more accurately than our previous studies.

Conduit armouring preceding explosive activity at an andesitic stratovolcano, an example from Taranaki Mounga, New Zealand

The strength and permeability of volcanic conduits can directly influence eruption dynamics via moderating the outgassing of ascending magma and the density of eruption plumes. Lithic clasts in pyroclastic ejecta can be used to understand the dynamic evolution of conduit walls because they are incorporated into the ascending melt-gas-particle mixture during volcanic eruptions. We examine the 1655 CE Burrell eruption of Taranaki Mounga, which transitioned from effusive activity to an explosive sub-Plinian phase and ended in unsteady columns. This episode was followed by a series of effusive eruptions of lower explosivity. Using textural analysis and physical properties, we distinguish five dominant lithic clast types within Burrell deposits that represent different regions of the shallow conduit and vent. Lithic types 1–3 represent juvenile (‘intrusive cognate’) and older (‘intrusive accessory’) conduit-filling plug materials. Lithic type 4 represents juvenile (‘extrusive cognate’) vent-filling lava dome extruded at the eruption onset, while Type 5 lithics (‘extrusive cognate’) represent sintered/compacted cognate material from the shallow vent accumulated during transitions in eruptive style. Crystalline andesite lithics (type 1) show a microlite-dominated groundmass. Hydrothermally altered andesite lithics (type 2) show breakdown of phenocrysts and increased seismic velocity relative to type 1 lithics. Brecciated andesite lithics (type 3) comprise fractured and sintered clasts of crystalline andesite. Glassy andesite lithics (type 4) show sub-rounded vesicles and glass-hosted microlites. Banded vitrophyre lithics (type 5) show bands of varying vesicularity, crystallinity and clast load. Physical property data reveals porosity, fracturing, sintering and alteration extent dictate dynamic changes in conduit permeability and potentially strength. Our results show how, during the explosive phase of the Burrell eruption, the conduit was lined with juvenile and remnant shallow plug material that was variably fractured, sintered and altered before being eroded and ejected. Comparison with previous work on Taranaki and dome-plug material from around the world shows how fracturing and sintering of conduit walls, combined with lining with dense juvenile material, cause overall permeability reduction and strengthening of the conduit. This inhibits outgassing and preserves conduit structure, facilitating the transition to explosive activity and the establishment of a stable eruption column.

Quantification of Muscle Wasting in CKD by Texture Analysis on 1H-Magnetic Resonance Images

Quantification of Muscle Wasting in CKD by Texture Analysis on 1H-Magnetic Resonance Images

A comprehensive study of the effect of scanning strategy on IN939 fabricated by powder bed fusion-laser beam

This study provides a comprehensive investigation into the effects of different scanning strategies on the material properties of IN939 fabricated using the PBF-LB process. The scanning strategies examined included alternating bi-directional scanning with rotation angles of 0°, 45°, 67°, and 90° between adjacent layers (named as shown), as well as alternating chessboard scanning with rotation angles of 67° and 90° (named as Q67° and Q90°). The results revealed that the 45° and 67° samples had the highest relative density, while the 0° and Q67° samples showed the highest average porosity. Moreover, various types of cracks, including solidification, solid-state, and oxide-induced cracks, were observed. Among the bi-directional scan samples, the 0° sample displayed the most extensive cracking and the highest σmax residual stress values in both XZ and XY planes. Conversely, the 45° and 67° samples exhibited fewer cracks. Notably, the lowest σmax residual stress in the XZ planes among the bi-directional scan samples was observed in the 67° sample. Additionally, microstructural analyses indicated differences in grain size and morphology, among the samples. Texture analysis indicated that the 0° and 90° samples exhibited strong cube textures, whereas the texture intensity weakened for the 45° and 67° samples. Moreover, the alternating chessboard scanning strategy led to rougher surfaces (higher Sa and Sz values) compared to the alternating bi-directional scanning strategy, regardless of the rotation angles. Furthermore, the microhardness values among the samples showed minimal variance, ranging between 321 ± 14 HV and 356± 7 HV.

Application of validated size-exclusion chromatography method for physicochemical characterization of topical gel formulation of deferoxamine conjugated with PEGylated carbon nanoparticles

The focus of current research work was to develop and validate size-exclusion chromatography method and develop and evaluate gel formulation of deferoxamine conjugated with PEGylated carbon nanoparticles (DEF-PEG-CNP) for topical delivery. Size-exclusion chromatography-based method was validated as per ICH guidelines. Effect of Carbopol® 974P and Transcutol® on the nanoparticles’ permeation was studied by 3-level full factorial design of experiment. Gel formulations were characterized for viscosity, cohesive and adhesive force by texture analyzer, and drug permeation through pig ear and human skin. The analytical method was specific as no interference from solvent or excipients were observed and met preset criteria of validation with limit of quantification of 0.24 ± 0.00 μg/mL. The nanoparticles permeation, steady state flux, and retained drug were statistically (p < 0.05) affected by Carbopol® 974P and Transcutol® percentage in the gel formulations. The permeation, steady state flux, and retained nanoparticles from the gel formulations varied from 23.2 ± 2.5 % to 70.9 ± 113.3 %, 0.8 ± 0.3 to 6.6 ± 2.1 μg/cm2.h, and 5.6 ± 0.3 to 38.8 ± 8.8 µg/g, respectively. Permeation of the nanoparticles was 1.9 folds higher in pig skin compared to human skin. Immunofluorescence detected successful permeation of DEF-PEG-CNP particles into skin. In conclusion, the analytical method can quantify the nanoparticles from the gel formulation without interference, and gel formulation of the nanoparticles can permeate across the skin.

Systematic screening of particle engineered polymers for the preparation of multiparticulates embedded orally disintegrating tablets

This paper evaluated polymers' physical and mechanical properties to formulate modified-release multiparticulates to be embedded in orally disintegrating tablets (ODTs). The targeted polymer should have adequate elastic-plastic properties in a multiparticulate system during the manufacturing process, which is affected by its physical properties. The good mechanical properties of the multiparticulate system can effectively aid in retaining the shape of the particles from being affected under applied compression pressure during the formulation process and tablets preparations. Therefore, the formulation should have good mechanical attains. Five polymers (three natural and two synthetic), namely: sodium alginate, polyvinyl alcohol (PVA), methylcellulose (MC), polyacrylic acid (PAA) and Eudragit L100, were evaluated. Polymers in raw form or particle engineered using spray drying were characterised using different analysis techniques: differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), compacts tensile strength, texture analysis, particle size analysis and surface area analysis. The unprocessed PAA exhibited the lowest Young's modulus, measuring at 5.38 MPa, whereas MC displayed the highest value of 14.74 MPa. The polymers were subjected to spray drying at a concentration of 5% w/v. Data of the texture analysis revealed that Young's modulus increased for the spray-dried PAA powder, reaching 13.69 MPa. This suggests an enhanced polymer compressibility subsequent to the spray drying process. Eudragit L100 demonstrated an enhanced tabletability prolife after spray drying. SEM and surface area results showed a correlation with the mechanical findings. Plasticity and elasticity together provide strong, durable tablets with structural integrity. Achieving a balance between these properties is crucial for effective tabletability. The results of this study provide an insight into physical and mechanical properties and changes encountered upon spray drying. A balance between elastic- plastic properties is required for optimal multiparticulate development.

Tribological Analysis of Surface Textures in Porcelain Tiles for Enhancing Pedestrian Walkway Safety

Due to their durability and aesthetic appeal, porcelain tiles have become a staple in modern construction and interior design. However, the persistent challenge of mitigating slip hazards, particularly in moist conditions, remains a critical concern for pedestrian safety. This study investigates the slip resistance performance of porcelain tiles, focusing on the influence of varying surface textures. The study clarifies the intricate relationship between surface texture and slip resistance through comprehensive dynamic friction tests involving four distinct porcelain tile samples and three different shoe samples conducted under arid, damp, and lathered conditions. While dry conditions showcase robust traction, moist environments underscore the significance of surface textures in enhancing grip. Moreover, the study introduces an operational scale of surface roughness, delineating optimal texture boundaries for maximal slip resistance. The implications of these findings extend beyond mere material characterisation, offering actionable insights for architects, designers, and safety professionals to enhance pedestrian safety in diverse settings. By bridging the gap between material science and real-world safety concerns, this research paves the way for innovative porcelain tile designs that prioritise safety without compromising aesthetic appeal.

Enhanced Artificial Intelligence Methods for Liver Steatosis Assessment Using Machine Learning and Color Image Processing: Liver Color Project.

The use of livers with significant steatosis is associated with worse transplantation outcomes. Brain death donor liver acceptance is mostly based on subjective surgeon assessment of liver appearance, since steatotic livers acquire a yellowish tone. The aim of this study was to develop a rapid, robust, accurate, and cost-effective method to assess liver steatosis. From June 1, 2018, to November 30, 2023, photographs and tru-cut needle biopsies were taken from adult brain death donor livers at a single university hospital for the study. All the liver photographs were taken by smartphones then color calibrated, segmented, and divided into patches. Color and texture features were then extracted and used as input, and the machine learning method was applied. This is a collaborative project between Vall d'Hebron University Hospital and Barcelona MedTech, Pompeu Fabra University, and is referred to as LiverColor. A total of 192 livers (362 photographs and 7240 patches) were included. When setting a macrosteatosis threshold of 30%, the best results were obtained using the random forest classifier, achieving an AUROC = 0.74, with 85% accuracy. Machine learning coupled with liver texture and color analysis of photographs taken with smartphones provides excellent accuracy for determining liver steatosis.

Kidney medicine meets computer vision: a bibliometric analysis.

Rapid advances in computer vision (CV) have the potential to facilitate the examination, diagnosis, and treatment of diseases of the kidney. The bibliometric study aims to explore the research landscape and evolving research focus of the application of CV in kidney medicine research. The Web of Science Core Collection was utilized to identify publications related to the research or applications of CV technology in the field of kidney medicine from January 1, 1900, to December 31, 2022. We analyzed emerging research trends, highly influential publications and journals, prolific researchers, countries/regions, research institutions, co-authorship networks, and co-occurrence networks. Bibliographic information was analyzed and visualized using Python, Matplotlib, Seaborn, HistCite, and Vosviewer. There was an increasing trend in the number of publications on CV-based kidney medicine research. These publications mainly focused on medical image processing, surgical procedures, medical image analysis/diagnosis, as well as the application and innovation of CV technology in medical imaging. The United States is currently the leading country in terms of the quantities of published articles and international collaborations, followed by China. Deep learning-based segmentation and machine learning-based texture analysis are the most commonly used techniques in this field. Regarding research hotspot trends, CV algorithms are shifting toward artificial intelligence, and research objects are expanding to encompass a wider range of kidney-related objects, with data dimensions used in research transitioning from 2D to 3D while simultaneously incorporating more diverse data modalities. The present study provides a scientometric overview of the current progress in the research and application of CV technology in kidney medicine research. Through the use of bibliometric analysis and network visualization, we elucidate emerging trends, key sources, leading institutions, and popular topics. Our findings and analysis are expected to provide valuable insights for future research on the use of CV in kidney medicine research.

Sequential extraction of hawthorn pectin: An attempt to reveal their original mode of being in plants and functional properties

Hawthorn is rich in pectin, which is much higher than most cultivated fruits, but conventional extraction methods do not meet the requirements of low energy consumption and green production. Pectin in hawthorn is divided into soluble and insoluble parts, and with the ripening of hawthorn, the original pectin is converted into soluble pectin and pectic acid under the action of enzymes. Therefore, based on the characteristics of hawthorn pectin, this study sequentially extracted hawthorn pectin using water-soluble pectin (WSP) and hot acid-soluble pectin (HAP) method, verifying the feasibility of extracting hawthorn pectin with pure water at room temperature, and systematically analyzing and comparing the physicochemical properties and functional characteristics of the two methods. The combination of texture analysis and gel rheology revealed that WSP formed a more uniform and dense network structure during the gelation process. Additionally, microscopic observations and emulsification index results indicated that the emulsion prepared with WSP (WSE) had a smaller particle size and better stability. This indicates that hawthorn pectin is suitable for extraction with pure water at room temperature, which can maintain its good physical properties while reducing energy consumption, providing a new approach for the large-scale extraction of pectin in the food industry.

Liquid metal-embedded magnetic hydrogel beads as novel adsorbents for malachite green removal

Malachite green (MG) is widely used in aquaculture as a parasiticide. It has generated much concern due to its carcinogenesis, mutagenesis, chromosomal fractures, teratogenicity, and respiratory toxicity. Effective methods for removing MG from water or other media are highly needed. Here, liquid metal (LM) is embedded into the magnetic hydrogel to create magnetic LM hydrogel beads with high adsorption capacity. The morphology and physical properties of the LM-embedded magnetic hydrogel beads are characterized using scanning electron microscopy, optical microscopy, and texture analysis methods. The adsorption efficiency of malachite green was assessed using spectrophotometric analysis at a wavelength of 623 nm. The hardness of these hydrogel beads reached a maximum of 4610 g, and its adsorption capacity reached 10 mg/g. Under the optimal condition, 0.05 %wt LM embedded magnetic hydrogel could remove 100 % of MG. This highly efficient magnetic adsorbent for dye removal has considerable potential for rapidly separating toxic contaminants from aquatic animal tissues, providing a cost-effective and straightforward solution to reduce dye pollution in aquatic environments and food products.

Testosterone hormone levels and breast muscle performance of Pelung chickens after zinc sulfate and synthetic testosterone supplementation

Background and Aim: Pelung chicken Gallus gallus gallus (Linnaeus, 1758) is a chicken endemic to Cianjur, West Java, Indonesia. This study aimed to determine the effects of zinc sulfate (ZnSO4) and synthetic testosterone supplementations for 56 days on testosterone hormone levels and breast muscle performance in Pelung chickens. Materials and Methods: This study used 12 Pelung chickens with three treatment groups (G) and four replications, namely, control (G0), ZnSO4 0.9 mg/kg (G1), and synthetic testosterone 3 mg/day (G2). Chickens were acclimatized for 7 days and then supplemented for 56 days. Drinking water and commercial standard feed were provided ad libitum. Blood was collected through the brachial vein for the analysis of testosterone levels using the enzyme-linked immunosorbent assay. The samples were collected every 14 days; on days 0, 14, 28, 42, and 56. Breast muscles were collected for texture analysis, and breast muscle preparations were made with hematoxylin-eosin staining to measure the fascicle area (FA), number of myofibers in one fascicle (NMOF), and myofiber area (MA). The collected data were analyzed using analysis of variance at a 95% confidence level with the help of Statistical Package for the Social Sciences v.29.0. Furthermore, principal component analysis (PCA) was performed with the help of Minitab v. 19. Results: Statistical analysis results on 56 days of testosterone level parameters showed that G2 was significantly different from all treatments (p &lt; 0.05). The results of statistical analysis on Pelung chicken breast muscle performance, especially hardness, chewiness, FA, NMOF, and MA, were significantly different (p &lt; 0.05) compared with the other treatments. The results of PCA showed that the testosterone level parameters were positively correlated with FA, NMOF, MA, hardness, and chewiness, whereas the fracture parameters were negatively correlated with all parameters except the springiness index and were significantly different between the G2 group and the other groups (p &lt; 0.05). Conclusion: It can be concluded that supplementing synthetic testosterone 3 mg/day body weight for 56 days can improve testosterone levels and breast muscle performance, especially hardness, chewiness, FA, NMOF, and MA in Pelung chickens. Keywords: muscle, Pelung chicken, performance, testosterone, texture.

Texture Analysis and Classification using Local Binary Patterns and Statistical Features

Texture analysis and classification are crucial in many applications such as medical applications, satellite imagery analysis, and so on. This paper presents a new technique that incorporates the LBP with the HOG to improve the texture analysis and classification. LBP is famous for finding out the local texture descriptors by comparing the pixel intensities it deals with and can challenge light variations and image transformations. On the other hand, there is HOG which emphasizes edge and gradient information to detect the orientation and shape of a texture in a given image. While LBP describes the local micro-patterns HOG gives the perspective of the global gradient orientation. The combined use of local and global texture information is helpful in the presented problem when prioritizing the recognition of complex texture patterns that cannot be deciphered by a single algorithm. To demonstrate the efficiency of the proposed hybrid method, several experiments are performed on several texture databases. According to the findings, the proposed LBP-HOG strategy proves more beneficial than basic LBP and HOG techniques concerning the classification rate and computing time. The combination method shows improved performance in terms of agreement with the reference of fine and coarse level of texture descriptions along with providing large-scale description of the texture which results in the improved discriminatory power of the texture classes.

Avocado peel by-product in cattle diets and supplementation with oregano oil and effects on production, carcass, and meat quality

Abstract The objective of this work was to evaluate the effects of including a commercial avocado peel meal (Avomel) by-product as a feed source supplemented with Lippia berlandieri Schauer oregano essential oil (OEO) in cattle diets. Eighteen 22-month-old male Charolais x Angus crossbred cattle (334.96 ± 27.48 kg) were randomly distributed in three experimental groups (n = 6): Control, cattle fed with the control diet without Avomel and without OEO; Avomel, cattle fed 10% of Avomel in the diet; and Avomel + OEO, cattle fed 10% Avomel and 600 mg/kg of OEO in the diet. The evaluated variables were bulls’ weight (BW), feed intake (FI), slaughter variables, carcass quality and the pH, water holding capacity (WHC), color and chemical composition of raw rib eye meat, as well as cooking loss (CL), shear force (SF), texture analysis and sensory evaluation of cooked meat. After 120 days of feeding, BW was highest (P &lt; 0.10) for Avomel and lowest (P &lt; 0.10) for Avomel + OEO. The Avomel + OEO group FI was low. Cattle slaughter variables, carcass quality variables, pH, and WHC did not show differences (P &gt; 0.05). Lightness was highest (P &lt; 0.05) for Avomel meat. Meat chemical composition was not affected (P &gt; 0.05). SF of meat was different (P &lt; 0.05) being highest for Avomel + OEO. On meat texture, springiness was different (P &lt; 0.05), i.e., meat treated with Avomel was highest, but no differences (P &gt; 0.05) were detected for hardness, adhesiveness, cohesiveness, gumminess, chewiness, and resilience. Odor, taste, softness, juiciness, and overall acceptability of cooked meat were not different (P &gt; 0.05), data not shown. The commercial by-product avocado peel meal supplemented with OEO could be used in cattle diets without adversely affecting productive performance, carcass traits, and meat quality.

Capacities of sorbents prepared by impregnation of inorganic carriers with PEI using different methods

The study presented here focused on the research of adsorbents for the separation of carbon dioxide from flue gas or other waste gases. Specifically, it focused on the possibility of eliminating the permanent problem with the insufficient resistance of inorganic adsorbents to unwanted – parasitic – adsorption of moisture from the processed gas. Based on the promising data published in recent papers regarding the wet impregnation of adsorbents with branched polyethyleneimine (PEI), four methods for the preparation of PEI-impregnated zeolite were tested. Penetration of the agent into the porous structure of the zeolite was achieved by: applying ultrasound, applying vacuum, combining vacuum and overpressure and boiling off the solvent without further operation. The raw zeolite was characterized by X-ray fluorescence spectrometry and X-ray diffractometry and also subjected to textural analysis. The characterization of the impregnated products mainly included thermogravimetric analysis, textural analysis and organic elemental analysis. In addition to gravimetric screening, the adsorption capacities of raw zeolite and impregnated products were primarily determined using a pressure flow-through apparatus with a fixed bed adsorber. The experimental conditions were determined to be close to real industrial installations: temperature during adsorption 20 and 40 °C, pressure during adsorption 600 kPa and 15% volume fraction of CO2 in the gas. Desorption was carried out by a combination of thermal desorption at 80 °C and vacuum. By reproducing the impregnation procedures from the literature, a PEI loading in the range of 4.1–23.7% was achieved, which is significantly lower than the literature sources state for the same preparation procedures. The measurement of textural properties verified that, depending on the value of PEI loading, there is a gradual reduction of the specific surface area, the total pore volume and the virtual disappearance of micropores and small mesopores. Specifically, at a PEI loading of 4%, the BET surface area decreased compared to the pristine zeolite from 29.4 to 2.9 m2 g–1 and at the same time the total pore volume decreased from 0.13 to 0.02 cm3 g–1, etc. The measurement of capacities did not confirm almost any of the results published in the literature. Without exception, the adsorption capacity decreased with the amount of PEI introduced into the zeolite particles. E.g. if a gas with 80% relative humidity and a content of 15% CO2 was used at a pressure of 600 kPa and a temperature of 40 °C, the capacity (by mass) decreased due to impregnation from 2.4% (for raw zeolite) to 0.8% for the sample with PEI mass fraction of 19%. Tests using dry gas resulted in even more marked deterioration. Thus, one can only partially agree with the literature data in the sense that humidity slightly compensates the negative effect of PEI on capacity. The effect, where the capacity increases with increasing temperature due to the replacement of physical CO2 adsorption by its chemisorption in the PEI layer, was also not confirmed. For example, for the above sample, humidity and pressure, the capacity was 0.9% at 20 °C. The impregnation procedure based on boiling off the solvent turned out to be completely unusable and, despite repeated rigorous attempts to reproduce it, did not lead to a product with a measurable capacity. The results of the study can be summarized in the following sentence. The problem is not that the experiments did not lead to a positive result, but above all the fundamental discrepancy between the published data and the attempts to reproduce them.

Petrogenesis of Metamorphic Rock in the Mukito Formation at Sorawolio Region, Bau-Bau City, Buton Island, Southeast Sulawesi Province, Indonesia

The petrogenesis study of the metamorphic rocks of the Mukito Formation was carried out in the Sorawolio area, Bau-Bau City, Buton Island, Southeast Sulawesi Province, Indonesia. This research area is included in the southern part of the Buton sheet with coordinates S 5⁰23'40.8'' and E 122⁰43'44.9''. The aim of this research is to determine the petrogenesis of metamorphic rocks which includes determining the rock type, facies, type of metamorphism and protolith. The research methods used include megascopic and microscopic analysis of rocks in the form of petrographic analysis which includes identification of mineral content and rock texture and geochemical analysis in the form of XRF tests to determine the main oxide elements in metamorphic rock samples. Data obtained from the results of petrographic analysis show that the research area consists of several types of metamorphic rock, namely serpentinite, phyllite, chlorite schist, hornblende schist and amphibolite. The metamorphic rocks in the research area are included in the greenschist facies and amphibolite facies with regional metamorphism types as well as protoliths from igneous rocks in the form of basalt rock which were formed in the tholeiitic oceanic-island tectonic environment which is a convergent complex characterized by continental origin in the magma series in the form of the tholeiitic series and calc -alkaline series.

Prediction of Lesion-Based Treatment Response after Two Cycles of Lu-177 Prostate Specific Membrane Antigen Treatment in Metastatic Castration-Resistant Prostate Cancer Using Machine Learning

Introduction: Lutetium-177 (Lu-177) prostate-specific membrane antigen (PSMA) therapy is a radionuclide treatment that prolongs overall survival in metastatic castration-resistant prostate cancer (MCRPC). We aimed to predict lesion-based treatment response after Lu-177 PSMA treatment using machine learning with texture analysis data obtained from pretreatment Gallium-68 (Ga-68) PSMA positron emission tomography/computed tomography (PET/CT). Methods: Eighty-three progressed, and 91 nonprogressed malignant foci on pretreatment Ga-68 PSMA PET/CT of 9 patients were used for analysis. Malignant foci with at least a 30% increase in Ga-68 PSMA uptake after two cycles of treatment were considered progressed lesions. All other changes in Ga-68 PSMA uptake of the lesions were considered nonprogressed lesions. The classifiers tried to predict progressed lesions. Results: Logistic regression, Naive Bayes, and k-nearest neighbors’ area under the ROC curve (AUC) values in detecting progressed lesions in the training group were 0.956, 0.942, and 0.950, respectively, and their accuracy was 87%, 85%, and 89%, respectively. The AUC values of the classifiers in the testing group were 0.937, 0.954, and 0.867, respectively, and their accuracy was 85%, 88%, and 79%, respectively. Conclusion: Using machine learning with texture analysis data obtained from pretreatment Ga-68 PSMA PET/CT in MCRPC predicted lesion-based treatment response after two cycles of Lu-177 PSMA treatment.