Estimating fire Duration using regression methods

Wildfire forecasting problems usually rely on complex grid-based mathematical models, mostly involving Computational fluid dynamics(CFD) and Celluar Automata, but these methods have always been computationally expensive and difficult to deliver a fast decision pattern. In this paper, we provide machine learning based approaches that solve the problem of high computational effort and time consumption. This paper predicts the burning duration of a known wildfire by RF(random forest), KNN, and XGBoost regression models and also image-based, like CNN and Encoder. Model inputs are based on the map of landscape features provided by satellites and the corresponding historical fire data in this area. This model is trained by happened fire data and landform feature maps and tested with the most recent real value in the same area. By processing the input differently to obtain the optimal outcome, the system is able to make fast and relatively accurate future predictions based on landscape images of known fires.Comment: 15pages, 5 figure

Novel Common Genetic Susceptibility Loci for Colorectal Cancer

BACKGROUND: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. METHODS: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. RESULTS: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. CONCLUSIONS: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screenin

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Effect of preoperatively continued aspirin use on early and mid-term outcomes in off-pump coronary bypass surgery: a propensity score-matched study of 1418 patients.

To date, effect of preoperatively continued aspirin administration in off-pump coronary artery bypass grafting (CABG) is less known. We aimed to assess the effect of preoperatively continued aspirin use on early and mid-term outcomes in patients receiving off-pump CABG.From October 2009 to September 2013 at the Fuwai Hospital, 709 preoperative aspirin users were matched with unique 709 nonaspirin users using propensity score matching to obtain risk-adjusted outcome comparisons between the two groups. Early outcomes were in-hospital death, stroke, intra- and post-operative blood loss, reoperation for bleeding and blood product transfusion. Major adverse cardiac events (death, myocardial infarction or repeat revascularization), angina recurrence and cardiogenic readmission were considered as mid-term endpoints.There were no significant differences among the groups in baseline characteristics after propensity score matching. The median intraoperative blood loss (600 ml versus 450 ml, P = 0.56), median postoperative blood loss (800 ml versus 790 ml, P = 0.60), blood transfusion requirements (25.1% versus 24.4%, P = 0.76) and composite outcome of in-hospital death, stroke and reoperation for bleeding (2.8% versus 1.6%, P = 0.10) were similar in aspirin and nonaspirin use group. At about 4 years follow-up, no significant difference was observed among the aspirin and nonaspirin use group in major adverse cardiac events free survival estimates (95.7% versus 91.5%, P = 0.23) and freedom from cardiogenic readmission (88.5% versus 85.3%, P = 0.77) whereas the angina recurrence free survival rates was 83.7% and 73.9% in the aspirin and nonaspirin use group respectively (P = 0.02), with odd ratio for preoperative aspirin estimated at 0.71 (95% confidence interval, 0.49-1.04, P = 0.08).Preoperatively continued aspirin use was not associated with increased risk of intra- and post-operative blood loss, blood transfusion requirements and composite outcome of in-hospital death, stroke and reoperation for bleeding in off-pump CABG. Preoperative aspirin use tended to decrease the hazard of mid-term angina recurrence

Bioactive Substances and Biological Functions in <i>Malus hupehensis</i>: A Review

Malus hupehensis (MH), as a natural resource, contains various active ingredients such as polyphenols, polysaccharides, proteins, amino acids, volatile substances, and other components. Increasingly, studies have indicated that MH showed a variety of biological activities, including antioxidant, hypoglycemic, hypolipidemic, anti-cancer, anti-inflammatory activities, and other activities. Hence, MH has attracted wide interest because of its high medical and nutritional value. It is necessary to review the active components and biological activities of MH. This paper systematically reviewed the chemical substances, biological activities, and potential problems of MH to further promote the related research of MH and provide an important reference for its application and development in medicine and food

Ultrasonic-Assisted Aqueous Two-Phase Extraction and Properties of Water-Soluble Polysaccharides from Malus hupehensis

Malus hupehensis (M. hupehensis), an edible and medicinal plant with significant antioxidant and hypoglycemic activity, has been applied to new resource foods. However, the structural characterization and biological effects of its polysaccharides (MHP) are less known. The optimum extraction parameters to achieve the highest extraction efficiency (47.63%), the yield (1.68%) and purity of MHP (89.6%) by ultrasonic-assisted aqueous two-phase system (ATPS) were obtained under the liquid-to-solid ratio of 23 g/mL, ultrasonic power of 65 W, and ultrasonic time of 33 min. According to the analysis results, MHP was composed of Man, GlcA, Rha, GalA, Glc, Gal, Xyl, Ara, and Fuc, in which Ara and Gal were the main components, and the content of GlcA was the lowest. In in vitro activity analysis, MHP showed a significant antioxidant capacity, and an inhibition activity of α-glucosidase and the advanced glycation end products (AGEs) formation in the BSA/Glc reaction model. MHP interacted with α-glucosidase and changed the internal microenvironment of the enzyme, and inhibited the AGEs formation, which provides more evidence for the antihyperglycemic mechanism of MHP. The results suggest that ATPS is an efficient and environmentally friendly solvent system, and M. hupehensis has broad application prospects in functional foods, healthcare products, and pharmaceuticals

Blood product requirements of propensity-matched patients based on preoperative aspirin use.

<p>Blood product requirements of propensity-matched patients based on preoperative aspirin use.</p

Kaplan-Meier Survival Estimates for Preoperative Aspirin and Nonaspirin Use Group.

<p>Kaplan-Meier Survival Estimates for Preoperative Aspirin and Nonaspirin Use Group.</p

DataSheet_1_Establishment of predictive nomogram and web-based survival risk calculator for malignant pleural mesothelioma: A SEER database analysis.docx

BackgroundMalignant pleural mesothelioma (MPM) is an uncommon condition with limited available therapies and dismal prognoses. The purpose of this work was to create a multivariate clinical prognostic nomogram and a web-based survival risk calculator to forecast patients’ prognoses.MethodsUsing a randomization process, training and validation groups were created for a retrospective cohort study that examined the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 for individuals diagnosed with MPM (7:3 ratio). Overall survival (OS) and cancer-specific survival (CSS) were the primary endpoints. Clinical traits linked to OS and CSS were identified using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, which was also utilized to develop nomogram survival models and online survival risk calculators. By charting the receiver operating characteristic (ROC), consistency index (C-index), calibration curve, and decision curve analysis (DCA), the model’s performance was assessed. The nomogram was used to classify patients into various risk categories, and the Kaplan-Meier method was used to examine each risk group’s survival rate.ResultsThe prognostic model comprised a total of 1978 patients. For the total group, the median OS and CSS were 10 (9.4-10.5) and 11 (9.4-12.6) months, respectively. As independent factors for OS and CSS, age, gender, insurance, histology, T stage, M stage, surgery, and chemotherapy were chosen. The calibration graphs demonstrated good concordance. In the training and validation groups, the C-indices for OS and CSS were 0.729, 0.717, 0.711, and 0.721, respectively. Our nomogram produced a greater clinical net benefit than the AJCC 7th edition, according to DCA and ROC analysis. According to the cut-off values of 171 for OS and 189 for CSS of the total scores from our nomogram, patients were classified into two risk groups. The P-value ConclusionsPatient survival in MPM was correctly predicted by the risk evaluation model. This will support clinicians in the practice of individualized medicine.</p