Implementation of artificial intelligence based ensemble models for gully erosion susceptibility assessment

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The Rarh Bengal region in West Bengal, particularly the eastern fringe area of the Chotanagpur plateau, is highly prone to water-induced gully erosion. In this study, we analyzed the spatial patterns of a potential gully erosion in the Gandheswari watershed. This area is highly affected by monsoon rainfall and ongoing land-use changes. This combination causes intensive gully erosion and land degradation. Therefore, we developed gully erosion susceptibility maps (GESMs) using the machine learning (ML) algorithms boosted regression tree (BRT), Bayesian additive regression tree (BART), support vector regression (SVR), and the ensemble of the SVR-Bee algorithm. The gully erosion inventory maps are based on a total of 178 gully head-cutting points, taken as the dependent factor, and gully erosion conditioning factors, which serve as the independent factors. We validated the ML model results using the area under the curve (AUC), accuracy (ACC), true skill statistic (TSS), and Kappa coefficient index. The AUC result of the BRT, BART, SVR, and SVR-Bee models are 0.895, 0.902, 0.927, and 0.960, respectively, which show very good GESM accuracies. The ensemble model provides more accurate prediction results than any single ML model used in this study

Novel machine learning approaches for modelling the gully erosion susceptibility

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The extreme form of land degradation caused by the formation of gullies is a major challenge for the sustainability of land resources. This problem is more vulnerable in the arid and semi-arid environment and associated damage to agriculture and allied economic activities. Appropriate modeling of such erosion is therefore needed with optimum accuracy for estimating vulnerable regions and taking appropriate initiatives. The Golestan Dam has faced an acute problem of gully erosion over the last decade and has adversely affected society. Here, the artificial neural network (ANN), general linear model (GLM), maximum entropy (MaxEnt), and support vector machine (SVM) machine learning algorithm with 90/10, 80/20, 70/30, 60/40, and 50/50 random partitioning of training and validation samples was selected purposively for estimating the gully erosion susceptibility. The main objective of this work was to predict the susceptible zone with the maximum possible accuracy. For this purpose, random partitioning approaches were implemented. For this purpose, 20 gully erosion conditioning factors were considered for predicting the susceptible areas by considering the multi-collinearity test. The variance inflation factor (VIF) and tolerance (TOL) limit were considered for multi-collinearity assessment for reducing the error of the models and increase the efficiency of the outcome. The ANN with 50/50 random partitioning of the sample is the most optimal model in this analysis. The area under curve (AUC) values of receiver operating characteristics (ROC) in ANN (50/50) for the training and validation data are 0.918 and 0.868, respectively. The importance of the causative factors was estimated with the help of the Jackknife test, which reveals that the most important factor is the topography position index (TPI). Apart from this, the prioritization of all predicted models was estimated taking into account the training and validation data set, which should help future researchers to select models from this perspective. This type of outcome should help planners and local stakeholders to implement appropriate land and water conservation measures

PHYTOCHEMICAL STANDARDIZATION AND ANTIOXIDANT POTENTIAL OF AYURVEDA FORMULATION DARVYADI RASKRIYA

The study represents phytochemical standardization and antioxidant potential of ayurveda formulation Darvyadi Raskriya. The study involves development of high-performance thin-layer chromatographic (HPTLC) method for analysis of formulation. The study utilizes analysis of glycyrrhizin in formulation which is the phytoconstituent of Glycyrrhiza glabra one of the component of formulation. The sample in ethanol was applied on aluminium TLC plates using Linomat 5 spray (CAMAG). Linear ascending development was performed in twin trough glass chamber saturated with mobile phase. The mobile phase consisted of ethyl acetate-methanol-formic acid (10:5:1 v/v/v). The spectrodensitometric detection was performed at the wavelength of 254 nm. The regression analysis was found to be linear with r2=0.997 in the concentration range 5-25 ppm. The antioxidant activity of formulation was also found to be significant as compared to control. Keywords: Standardization, Glycyrrhiza glabra, Glycyrrhizin, HPTLC, Antioxidant

Acute cholecystitis with massive upper gastrointestinal bleed: A case report and review of the literature

BACKGROUND: Cystic artery pseudoaneurysm is a rare complication following cholecystitis. Its presentation with upper gastrointestinal hemorrhage (UGIH) is even rarer. Thirteen patients with cystic artery pseudoaneurysm have been reported in the literature but only 2 of them presented with UGIH alone. CASE PRESENTATION: We report a 43-year-old woman who developed a cystic artery pseudoaneurysm following an episode of acute cholecystitis. She presented with haematemesis and melaena associated with postural symptoms. Upper gastrointestinal endoscopy revealed a duodenal ulcer with adherent clots in the first part of the duodenum. Ultrasonography detected gallstones and a pseudoaneurysm at the porta hepatis. Selective hepatic angiography showed two small pseudoaneurysms in relation to the cystic artery, which were selectively embolized. However, the patient developed abdominal signs suggestive of gangrene of the gall bladder and underwent an emergency laparotomy. Cholecystectomy with common bile duct exploration along with repair of the duodenal rent, and pyloric exclusion and gastrojejunostomy was done. CONCLUSION: This case illustrates the occurrence of a rare complication (pseudoaneurysm) following cholecystitis with an unusual presentation (UGIH). Cholecystectomy, ligation of the pseudoaneurysm and repair of the intestinal communication is an effective modality of treatment

Comparative effects of whey and casein proteins on satiety in overweight and obese individuals: A randomized controlled trial

Background/Objective: Dairy protein seems to reduce appetite by increasing satiety and delaying the return of hunger and subsequently lowering energy intake compared with fat or carbohydrate. The aim of this study was to compare the effect of whey with that of casein proteins on satiety in overweight/obese individuals. Methods/Subjects: This was a randomized, parallel-design 12-week-long study. Seventy subjects with a body mass index between 25 and 40 kg/m2 and aged 18–65 years were randomized into one of three supplement groups: glucose control (n=25), casein (n=20) or whey (n=25) protein. Before commencing the study, at weeks 6 and 12 of the treatment, a Visual Analogue Scale (VAS) was used to measure subjective sensations of appetite before lunch and before dinner. Results: Rating for VAS (mm) at 6 and 12 weeks showed significantly higher satiety in the whey group compared with the casein (P=0.017 and P=0.025, respectively) or control (P=0.024 and P=0.032, respectively) groups when measured before lunch. Similarly, at 6 and 12 weeks, the score for fullness was also significantly higher in the whey group compared with both casein (P=0.038 and P=0.022, respectively) and control (P=0.020 and P=0.030, respectively) groups. However, these short-term effects on satiety from dairy whey proteins did not have any long-term effects on energy intake or body weight over 12 weeks compared with casein. Conclusions: Collectively, whey protein supplementation appears to have a positive and acute postprandial effect on satiety and fullness compared with casein and carbohydrate supplementation in overweight and obese individuals

Studies on an alkali-thermostable xylanase from Aspergillus fumigatus MA28

An alkalitolerant fungus, Aspergillus fumigatus strain MA28 produced significant amounts of cellulase-free xylanase when grown on a variety of agro-wastes. Wheat bran as the sole carbon source supported higher xylanase production (8,450 U/L) than xylan (7,500 U/L). Soybean meal was observed to be the best nitrogen source for xylanase production (9,000 U/L). Optimum medium pH for xylanase production was 8 (9,800 U/L), though, significant quantities of the enzyme was also produced at pH 7 (8,500 U/L), 9 (8,200 U/L) and 10 (4,600 U/L). The xylanase was purified by ammonium sulphate precipitation and carboxymethyl cellulose chromatography, and was found to have a molecular weight of 14.4 kDa with a Vmax of 980 μmol/min/mg of protein and a Km of approximately 4.9 mg/mL. The optimum temperature and pH for enzyme activity was 50 °C and pH 8, respectively. However, the enzyme also showed substantial residual activity at 60–70 °C (53–75%) and at alkaline pH 8–9 (56–88%)

Spectral-based mesh segmentation

In design and manufacturing, mesh segmentation is required for FACE construction in boundary representation (BRep), which in turn is central for featurebased design, machining, parametric CAD and reverse engineering, among others -- Although mesh segmentation is dictated by geometry and topology, this article focuses on the topological aspect (graph spectrum), as we consider that this tool has not been fully exploited -- We preprocess the mesh to obtain a edgelength homogeneous triangle set and its Graph Laplacian is calculated -- We then produce a monotonically increasing permutation of the Fiedler vector (2nd eigenvector of Graph Laplacian) for encoding the connectivity among part feature submeshes -- Within the mutated vector, discontinuities larger than a threshold (interactively set by a human) determine the partition of the original mesh -- We present tests of our method on large complex meshes, which show results which mostly adjust to BRep FACE partition -- The achieved segmentations properly locate most manufacturing features, although it requires human interaction to avoid over segmentation -- Future work includes an iterative application of this algorithm to progressively sever features of the mesh left from previous submesh removal

Rapid Pathway Evolution Facilitated by Horizontal Gene Transfers across Prokaryotic Lineages

The evolutionary history of biological pathways is of general interest, especially in this post-genomic era, because it may provide clues for understanding how complex systems encoded on genomes have been organized. To explain how pathways can evolve de novo, some noteworthy models have been proposed. However, direct reconstruction of pathway evolutionary history both on a genomic scale and at the depth of the tree of life has suffered from artificial effects in estimating the gene content of ancestral species. Recently, we developed an algorithm that effectively reconstructs gene-content evolution without these artificial effects, and we applied it to this problem. The carefully reconstructed history, which was based on the metabolic pathways of 160 prokaryotic species, confirmed that pathways have grown beyond the random acquisition of individual genes. Pathway acquisition took place quickly, probably eliminating the difficulty in holding genes during the course of the pathway evolution. This rapid evolution was due to massive horizontal gene transfers as gene groups, some of which were possibly operon transfers, which would convey existing pathways but not be able to generate novel pathways. To this end, we analyzed how these pathways originally appeared and found that the original acquisition of pathways occurred more contemporaneously than expected across different phylogenetic clades. As a possible model to explain this observation, we propose that novel pathway evolution may be facilitated by bidirectional horizontal gene transfers in prokaryotic communities. Such a model would complement existing pathway evolution models

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution