Pythium amaminum sp. nov. was isolated from river and reservoir water on Amami island, Kagoshima Prefecture, Japan. The species can grow at temperatures between 10 °C and 35 °C. At the optimum ...temperature of 25 °C, the radial growth rate is 22.5 mm per day. Pythium amaminum produces filamentous sporangia consisting of branched, lobulate or digitate elements forming large complexes. Zoospores form inside the vesicle, which is discharged through a long tube at least 320 μm. Globose oogonia are ornamented with conical blunt spines. Oospores are aplerotic and globose. Antheridia twine around the oogonia or stick to them. These features having a both of the long discharge tube from sporangium and oogonia with spines are not observed in any other species of the genus Pythium, and thus we conclude that P. amaminum is a new Pythium species.
Residual shives have a major impact on the quality and performance of flax textile and composite preforms. Quantifying the content of shives in batches of scutched flax fibres is a time-consuming and ...operator-dependent process. Although the shive content can be estimated from the chemical composition, our aim here is to explore a series of effective, reliable and complementary approaches to quantifying shives. Various methods are presented: microscopic observations, analytical biochemistry (monosaccharides, lignins), indirect methods (infrared spectroscopy) and dynamic morphological analysis (QICPIC). A reference standard was first analysed and then compared with batches of flax tow fibre of unknown shive content from current industrial production. This approach shows that calibration curves can be established by applying each selected method to batches with known fibre and shive content. In addition, a database was generated to determine the shive content of industrial batches using partial least squares (PLS) regression. Finally, a detailed study of shives in industrial batches is presented, comparing the different analytical methods.
•Quantification of flax shives was studied on laboratory and industrial batches.•Biochemical and morphological analysis were tested for estimating the shive content.•A good correlation was demonstrated between shive and galactose or xylose content.•Lignin content determination seems to be the most promising method.•Multivariate analysis is essential to quantifying batches with low shives content.
Aggregated aerosol particles released from high temperature processes and combustion processes are often described as quasi-fractal aggregates, where the shape of these particles is represented by ...the scaling law. A detailed understanding of the morphology is quite important as various properties are strongly dependent on the particle shape. Electron microcopy based image analysis is the most commonly used technique to visualize and study the morphological features. In this study, we propose a machine learning (ML)-assisted retrieval method where ML techniques are combined with optimization algorithms to predict the morphological features and the corresponding 3-dimensional structures from microscopic images. The proposed algorithm is comprehensively tested with “synthetic” images as well as Transmission Electron Microcopy images. Various ML models, including Linear regression, Artificial Neural Network, K-nearest neighbours, Random Forest regression, and XGBoost are used for preliminary prediction of the morphological features (Number of monomers (N), fractal prefactor (kf) and fractal Dimension (Df)). These are used to narrow down the search space in the optimization algorithms. Random Forest and XGBoost methods achieved approximately 0.96 R2 score for N, 0.85 for Df and 0.73 for kf. Multiple optimization methods, including PSO, JAYA, and JAYA-SA, were tested in the study. The method was tested across a wide range of parameters, including N (up to 500), Df (1.1–2.7), and kf (0.6–2.1), and the results are quite promising while comparing various 3-dimensional properties of the retrieved structures. The retrieved fractal parameters, N and Df, exhibited errors under 10%, and the predicted kf values were found within approximately 15% using the proposed method. Results also show that the 3-dimensional properties of the predicted structure are quite close to the structures used for testing the algorithm. The algorithm was also parallelized to improve the computational time. The results show that the predicted fractal parameters and the retrieved 3-dimensional structures are quite similar to the structures used for testing across a wide range of particle morphologies. The incorporation of ML models has significantly improved the accuracy and computational speed, compared to the existing retrieval techniques.
•ML-assisted optimization to predict 3D fractal morphology from microscopic images.•Linear Regression, ANN, Random Forest Regressor, XGBoost, and kNN are tested.•FracVAL is employed for tuning, generating aggregate structures.•Particle Swarm Optimization, JAYA and self-adaptive JAYA are used for Optimization.•Accurate and fast prediction of 3-dimensional properties from microscopic images.
The isomeric mixture of alpha and beta amyrin (AMY), present in the resin of Protium heptaphyllum, is popularly used as anti-inflammatory and anti-ulcer. The literature has been demonstrating ...pharmacological activities of these triterpenes in the central and peripheral nervous systems, and in the gastrointestinal and immunological systems. This study traces a toxicological profile of amyrin, aiming to provide information that may clarify its safety. Nine female Wistar rats (170 to 200 g) were divided into three groups of three animals each (control, amyrin 300 and amyrin 2000 mg kg-1, p.o.), which were evaluated by protocols preconized by the Organization for Economic Co-operation and Development (OECD). Open field Test and Malone Hippocratic Screening Scale were performed. AMY, mostly at 2000 mg kg-1, reduced the number of crossings by 57% vs. saline (22.67 ± 2.40) and the number of rearing by 53% vs. saline (42.67 ± 2.96), but increased the number of grooming by 26% vs. saline (1.66 ± 0.33). AMY (2000 mg kg-1) increased the serum glucose by 77% vs. saline (126.70 ± 4.33 mg dL-1), triglycerides by 50% vs. saline (78.67 ± 2.18 mg dL-1) and uric acid by 65% vs. saline (0.73 ± 0.03 mg dL-1). AMY induced vascular congestion and hemorrhage in the liver, spleen and cerebral cortex. Renal changes (cellular damage, inflammatory infiltrate, tubular protein deposition and glomeruli atrophy) were also seen. In conclusion, AMY decreased rat locomotor activity, caused minor biochemical changes, and altered the morphology of the kidney. The present study may contribute to deepen the knowledge about the safety of AMY, aiming the development of a novel pharmacological product.
Intestinal protozoa, which can be asymptomatic or cause diarrhea, dysentery and even death, are among the main agents that affect nonhuman primates (NHPs) kept under human care. Nevertheless, ...information on the molecular and morphometric profiles of parabasilids in the Neotropics is still scarce. In this context, the objective of this study was to isolate the Parabasalia protozoa detected in the feces of NHPs and their keepers in Pavlova and TYSGM9 media and to characterize the isolates by molecular biology and morphometry. Fecal samples from NHPs from five Brazilian institutions were analyzed. Direct examination was performed immediately after obtaining the samples. A total of 511 fecal samples from NHPs were collected, and 10.6% contained parabasilids. Regarding the handlers, of the 74 samples analyzed, three were positive. In vitro-generated parabasilid isolates were successfully obtained from all positive samples, as identified via microscopy. Isolates of the parasite were obtained both from New World NHPs, including the genera Leontopithecus, Saguinus, Leontocebus, Aotus, Saimiri, Sapajus, and Alouatta, and from the Old World primate Pan troglodytes. Forty-nine NHP isolates were molecularly identified: Pentatrichomonas hominis (16), Trichomitus batrachorum (14), Tetratrichomonas brumpti (13) and Hypotrichomonas hampli (6). The human isolates were identified as Tetratrichomonas sp. (2) and T. batrachorum (1). Visualization and morphometric analysis revealed trophozoites with piriform or rounded shapes that presented variable measurements. The isolates previously characterized as P. hominis had up to five free flagella, while T. batrachorum and Tetratrichomonas sp. had up to four free flagella, and H. hampli had a maximum of three free flagella. These morphometric characteristics corroborated the molecular identification. In general, a variety of parabasilids were observed to infect NHPs, and T. batrachorum was isolated from biological samples from both NHPs and their keepers, a finding that reinforces the susceptibility of these hosts to infections by parabasilids in Brazil.
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•Parabasilids were detected in feces of nonhuman primates raised ex-situ and keepers.•All the isolates of parabasilids were successfully cultiveted in Pavlova medium.•Molecular analysis of 18S was made to identify the isolates of group Parabasalia.•T. batrachorum was isolated from both human and nonhuman primates.•Pentatrichomonas hominis was the most frequent taxa, mainly found in S. collinsi.
The Internet-of-Things (IoT) empowers remote monitoring and management of the performance of machines, vehicles, processes, etc., which facilitate service business models. However, companies in ...emerging and transitional economies, in particular, face challenges when applying IoT, not only related to the use of technology, but especially regarding the need for a new business model. The main goal of this paper is to better understand emerging IoT business models in Vietnam through identifying and interpreting business model design options and choices. The case studies and their commonalities are used to perform a morphological analysis and create a generic IoT business model providing business model alternatives for each of the four business model dimensions. The research provides insights into the commonalities and discrepancies of IoT-based business models. Also, it provides a novel application of morphological analysis to business model innovation to create a generic business model for IoT applications in emerging markets.
This review aims to provide a description of the recent advances in the preparation of polymer nanocomposites via mechanical milling. An assessment of possible future scenarios that could be created ...by the utilization of improved experimental methodologies and a deeper understanding of structure-property relationship is also provided. It is then reported, in a logical sequence, crucial information on five subjects: (i) the motivation of fundamental and applied research in the field of thermoplastic and thermosetting polymer nanocomposites, (ii) the mechanochemical response of polymeric substances to mechanical activation, (iii) the broad spectrum of experimental behaviours exhibited by the most studied classes of polymers, (iv) the methodology for the mindful utilization of mechanical processing to mix polymers and disperse heterophases, and (v) the physico-chemical approach to describing the kinetics of mechanically activated transformations. In addition, critical questions regarding the advantages and disadvantages of mechanical processing compared to more conventional dispersion methods are highlighted. Finally, the general trends in the current research are discussed, and possible future perspectives in this field are briefly described.
Chatbots have become common in marketing-related applications, providing 24/7 service, engaging customers in humanlike conversation, and reducing employee workload in handling customer calls. ...However, the academic literature on the use of chatbots in marketing remains sparse and scattered across disciplines. The present study combines morphological analysis and co-occurrence analysis to bring structure to this area and to identify relevant research gaps. Morphological analysis divides a problem into pertinent and clearly distinguishable components, namely dimensions (at an abstract level) and variants (at a concrete level). A Zwicky box (a cross-variant matrix of dimensions) is then constructed to identify future research opportunities. Here, the authors obtain 11 dimensions and 264 variants. To eliminate inconsistent configurations (i.e., combinations of variants across dimensions), they perform a cross-consistency assessment and identify potential research gaps. To increase objectivity in the selection of relevant gaps, the authors use VOSviewer software to conduct a co-occurrence analysis of the variants.
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•Arguments for the importance of diversity within scenario sets are developed.•The diversity of six global scenario sets is assessed.•Results show relatively good performance with ...regards to scenario set diversity.•There is a trade-off between covering the scenario space and redundancy.
Scenario development and analysis is an important methodological approach in the assessment of global environmental change. Scenarios are used to assess climate change and its impacts on societies, economies, and ecosystems, and identify, test, and improve policy responses to manage the negative consequences of a changing environment. Evaluation of scenarios, especially global scenarios widely used in the climate research and policy community, is therefore urgently needed. While the quality and usefulness of individual scenarios have been extensively examined through a wide array of criteria, standards for systematic evaluation of scenario sets are only emerging. Scenario diversity (i.e., diversity between individual scenarios in a set) has been advanced as a measure to assess the quality of global scenario sets. In this paper, we use scenario diversity analysis, a systematic and transparent quantitative method, to examine six major global scenario sets with regards to scenario set diversity. Results show that the assessed scenario sets show relatively good performance with regards to scenario set diversity. However, the use of classic methods for building scenario architectures and the number of scenarios included in a set raise important questions about the potential trade-offs between covering a bigger space of futures possibilities and adding redundancy to the scenario set.