Genetic justification of COVID-19 patient outcomes using DERGA, a novel data ensemble refinement greedy algorithm.

Complement inhibition has shown promise in various disorders, including COVID-19. A prediction tool including complement genetic variants is vital. This study aims to identify crucial complement-related variants and determine an optimal pattern for accurate disease outcome prediction. Genetic data from 204 COVID-19 patients hospitalized between April 2020 and April 2021 at three referral centres were analysed using an artificial intelligence-based algorithm to predict disease outcome (ICU vs. non-ICU admission). A recently introduced alpha-index identified the 30 most predictive genetic variants. DERGA algorithm, which employs multiple classification algorithms, determined the optimal pattern of these key variants, resulting in 97% accuracy for predicting disease outcome. Individual variations ranged from 40 to 161 variants per patient, with 977 total variants detected. This study demonstrates the utility of alpha-index in ranking a substantial number of genetic variants. This approach enables the implementation of well-established classification algorithms that effectively determine the relevance of genetic variants in predicting outcomes with high accuracy.

Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method.

Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazards, and the accurate estimation of induced stresses at different positions in the pillar is helpful for pillar design and guaranteeing pillar stability. There are many modeling methods to design pillars and evaluate their stability, including empirical and numerical method. However, empirical methods are difficult to be applied to places other than the original environmental characteristics, and numerical methods often simplify the boundary conditions and material properties, which cannot guarantee the stability of the design. Currently, machine learning (ML) algorithms have been successfully applied to pillar stability assessment with higher accuracy. Thus, the study adopted a back-propagation neural network (BPNN) and five elements including the sparrow search algorithm (SSA), gray wolf optimizer (GWO), butterfly optimization algorithm (BOA), tunicate swarm algorithm (TSA), and multi-verse optimizer (MVO). Combining metaheuristic algorithms, five hybrid models were developed to predict the induced stress within the pillar. The weight and threshold of the BPNN model are optimized by metaheuristic algorithms, in which the mean absolute error (MAE) is utilized as the fitness function. A database containing 149 data samples was established, where the input variables were the angle of goafline (A), depth of the working coal seam (H), specific gravity (G), distance of the point from the center of the pillar (C), and distance of the point from goafline (D), and the output variable was the induced stress. Furthermore, the predictive performance of the proposed model is evaluated by five metrics, namely coefficient of determination (R2), root mean squared error (RMSE), variance accounted for (VAF), mean absolute error (MAE), and mean absolute percentage error (MAPE). The results showed that the five hybrid models developed have good prediction performance, especially the GWO-BPNN model performed the best (Training set: R2 = 0.9991, RMSE = 0.1535, VAF = 99.91, MAE = 0.0884, MAPE = 0.6107; Test set: R2 = 0.9983, RMSE = 0.1783, VAF = 99.83, MAE = 0.1230, MAPE = 0.9253).

Knowledge mapping of research progress in blast-induced ground vibration from 1990 to 2022 using CiteSpace-based scientometric analysis.

Blasting constitutes an essential component of the mining and construction industries. However, the associated nuisances, particularly blast vibration, have emerged as significant concerns that pose threats to operational stability and the safety of the surrounding areas. Given the increasing emphasis on sustainability, ecological responsibility, safety, and geo-environmental practices, the impact of blast vibration has garnered heightened attention and scrutiny. Nevertheless, the field still lacks comprehensive phase analysis studies. Therefore, it is imperative to elucidate the research progress on blast vibration and discern its current frontiers of investigation. To address this need, this study employs bibliometric methods and the CiteSpace 6.1.R2 software to analyze 3093 papers from the Web of Science database. Through this comprehensive analysis, the study aims to chronicle the developmental trajectory, assess the present research status, and identify future trends in the field of blast vibration. The findings of this study reveal that research on "blasting vibration" is advancing rapidly, with the number of citations exhibiting a J-shaped growth curve over time. China emerges as the leading contributor to this research, followed by India, and the foremost institution in this field is Central South University in China. Cluster analysis identifies the effects of ground vibration, numerical simulation, blast load, blasting vibration and rockburst hazard as the most prominent research areas presently. The primary research directions in this domain revolve around the rock fragmentation, compressive strength, particle swarm optimization, and ann. The emergence of these keywords underscores a dynamic shift towards a more holistic and multidisciplinary approach in the field of blasting-induced ground vibration. Furthermore, this study provides a concise overview of blast vibration, discusses prediction techniques, and proposes measures for its control. Additionally, the discussion delves into the social significance of intelligent blasting systems within the context of artificial intelligence, aiming to address the hazards associated with blast-induced ground vibrations.

Heparin and insulin in the management of hypertriglyceridemia-associated pancreatitis: case series and literature review.

Severe hypertriglyceridemia accounts for up to 7% of all cases of acute pancreatitis. Heparin and insulin activate lipoprotein lipase (LPL), thereby reducing plasma triglyceride levels. However, the safety and efficacy of heparin and insulin in the treatment of hypertriglyceridemia-associated acute pancreatitis have not been well established yet. We successfully used heparin and insulin as first-line therapy in four consecutive patients with acute pancreatitis secondary to hypertriglyceridemia. In a literature search, we revised almost all reports published to date of patients managed successfully with this combination. Heparin and insulin appear to be a safe, effective, and inexpensive first-line therapy for hypertriglyceridemia-associated acute pancreatitis.

Identification of Novel SNP in Promoter Sequence of TaGW2-6A Associated with Grain Weight and Other Agronomic Traits in Wheat (Triticum aestivum L.).

TaGW2 is an orthologue of rice gene OsGW2, which encodes E3 RING ubiquitin ligase and controls the grain size in rice. In wheat, three copies of TaGW2 have been identified and mapped on wheat homoeologous group 6 viz. TaGW2-6A, TaGW2-6B and TaGW2-6D. In the present study, using as many as 207 Indian wheat genotypes, we identified four SNPs including two novel SNPs (SNP-988 and SNP-494) in the promoter sequence of TaGW2-6A. All the four SNPs were G/A or A/G substitutions (transitions). Out of the four SNPs, SNP-494 was causal, since it was found associated with grain weight. The mean TGW (41.1 g) of genotypes with the allele SNP-494_A was significantly higher than mean TGW (38.6 g) of genotypes with the allele SNP-494_G. SNP-494 also regulates the expression of TaGW2-6A so that the wheat genotypes with SNP-494_G have higher expression and lower TGW and the genotypes with SNP-494_A have lower expression but higher TGW. Besides, SNP-494 was also found associated with grain length-width ratio, awn length, spike length, grain protein content, peduncle length and plant height. This suggested that gene TaGW2-6A not only controls grain size, but also controls other agronomic traits. In the promoter region, SNP-494 was present in 'CGCG' motif that plays an important role in Ca2+/calmodulin mediated regulation of genes. A user-friendly CAPS marker was also developed to identify the desirable allele of causal SNP (SNP-494) for use in marker-assisted selection for improvement of grain weight in wheat. Using four SNPs, five haplotypes were identified; of these, Hap_5 (G_A_G_A) was found to be a desirable haplotype having significantly higher grain weight (41.13g) relative to other four haplotypes (36.33-39.16 g).

Prediction of sea water intrusion for mining activity in close precincts of sea shore.

The mining lease area of Surka [District Bhavnagar, Gujarat (India)] is located within 6-12 km horizontal distance of sea shore of Gulf of Cambay. Whenever, there will be onset of lignite extraction, there will be always a threat of sea water intrusion into the mining lease area due to its close proximity to seashore. This article describes the prediction of sea water intrusion into the lease area of whole mining block using Ghyben-Herzberg relation between fresh and saline water, Remote Sensing, Ground Truth verification, Electrical Resistivity Survey and groundwater table monitored during the year 2004. As per the Ghyben-Herzberg relation, results show that there will not be sea water intrusion. If there is excess pumping of water then also the basement rock below the lignite seam will put hindrance to any possible upconing of saline water interface.

Heparin and insulin in the management of hypertriglyceridemia-associated pancreatitis: case series and literature review

SUMMARY Severe hypertriglyceridemia accounts for up to 7% of all cases of acute pancreatitis. Heparin and insulin activate lipoprotein lipase (LPL), thereby reducing plasma triglyceride levels. However, the safety and efficacy of heparin and insulin in the treatment of hypertriglyceridemia-associated acute pancreatitis have not been well established yet. We successfully used heparin and insulin as first-line therapy in four consecutive patients with acute pancreatitis secondary to hypertriglyceridemia. In a literature search, we revised almost all reports published to date of patients managed successfully with this combination. Heparin and insulin appear to be a safe, effective, and inexpensive first-line therapy for hypertriglyceridemia-associated acute pancreatitis.