Fire damage, mortality, and suckering in aspen

1987 ◽  
Vol 17 (9) ◽  
pp. 1100-1109 ◽  
Author(s):  
James K. Brown ◽  
Norbert V. DeByle
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Tree Mortality ◽  
Fire Severity ◽  
Fire Damage ◽  
Bark Thickness ◽  
Breast Height ◽  
High Severity ◽  
Tree Number ◽  
Fire Characteristics

Relationships among fire characteristics, fire damage, tree mortality, and sucker response in Populustremuloides Michx. are described. Circumference charred averaged more than 75% on trees killed and less than 50% on live trees. Average char heights ranged from 0.5 m in low severity fire to 1.5 m in high severity fire. Logistic regression analysis showed that probability of mortality was strongly related to diameter at breast height (dbh), char height, and circumference charred. Char heights of 30 cm had a 90% probability of killing aspen less than 25 cm dbh. Bark thickness at breast height and 10 cm aboveground, which relates to fire resistance, related strongly to tree dbh. Bark thickness was the same at sidehill, downhill, and uphill positions. Minimal flame heights required to kill aspen with 90% probability ranged from 10 cm for a 10-cm dbh tree to 60 cm for a 25-cm dbh tree. Number of suckers per hectare on three burns varied from 9 880 to 57 570 the 1st year following fire and from 7 060 to 21 240 4 years after the fire. Depth of sucker origin ranged from 0.2 to 18 cm and was related to fire severity. Sucker density varied greatly between plots and was not significantly related to fire severity.

Wachstum und Wertleistung der Douglasie in Abhängigkeit von der Standraumgestaltung

2012 ◽  
Vol 163 (3) ◽  
pp. 96-104 ◽  
Author(s):  
Joachim Klädtke ◽  
Ulrich Kohnle ◽  
Edgar Kublin ◽  
Andreas Ehring ◽  
Hans Pretzsch ◽  
...  
Keyword(s):  
Wood Quality ◽  
Volume Growth ◽  
Static Stability ◽  
Douglas Fir ◽  
Breast Height ◽  
Monetary Analysis ◽  
Starting Conditions ◽  
Tree Number ◽  
Clear Differentiation ◽  
Further Development

Growth and value production of Douglas-fir under varying stand densities The investigation is focused on the effects of initial tree number and thinning on growth and value performance of Douglas-fir stands. Data base is a coordinated Douglas-fir spacing experiment in South Germany, started 40 years ago and comprising variants of tree numbers with 500, 1,000, 2,000 and 4,000 Douglas-firs per hectare. The treatment was performed according to a standardized experiment program. The results show that at low initial tree numbers, the diameter on breast height (DBH) of (pre)dominant trees at the beginning of the observations (with 12 m top height) is bigger than at higher initial plant numbers. Accordingly, the quotient of height (H) to DBH (as an indicator for tree's static stability) is lower. The further development of DBH and H/DBH quotient is decisively determined by stand treatment, which superimposes the effect of the initial tree number. The total volume growth shows a clear differentiation, too, the variants with initially high tree numbers appearing on top. In the monetary analysis, this ranking is reversed: despite a supposed inferior wood quality, the variants with lower initial tree numbers clearly outperform the ones with higher numbers in terms of value. From these results, the following silvicultural recommendations for Douglas-fir can be derived: the initial tree numbers should be in the range from 1,000 to 2,000 plants per hectare. On technically not accessible sites, even lower tree numbers may come into question. The strong influence of stand treatment on DBH and H/DBH development highlights the problem of postponed thinnings, for this causes growth and stability losses even under favorable starting conditions in terms of competition.

ANALISIS HUBUNGAN SARANA, PENGETAHUAN, DAN SIKAP BIDAN PRAKTIK MANDIRI DENGAN KEPATUHAN MENJALANKAN STANDAR PELAYANAN ANTENATAL CARE DI KOTA PADANGSIDIMPUAN

2019 ◽  
Vol 2 (1) ◽  
pp. 27-33
Author(s):  
Megawati Sinambela ◽  
Evi Erianty Hasibuan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Antenatal Care ◽  
Pregnant Women ◽  
Logistic Regression Analysis ◽  
Care Service ◽  
Multivariate Logistic Regression Analysis ◽  
Bivariate Analysis ◽  
Cross Sectional ◽  
The North

Antenatal care is a service provided to pregnant women to monitor, support maternal health and detect mothers whether normal or problematic pregnant women. According to the WHO, globally more than 70% of maternal deaths are caused by complications of pregnancy and childbirth such as hemorrhage, hypertension, sepsis, and abortion. Based on data obtained from the profile of the North Sumatra provincial health office in 2017, in the city of Padangsidimpuan in 2017 the coverage of ANC visits reached (76.58%) and had not reached the target in accordance with the 2017 Provincial Health Office strategy plan (95%). This type of research was an observational analytic study with a cross sectional design. The population in this study were independent practice midwives who were in the Padangsidimpuan, the sample in this study amounted to 102 respondents. The technique of collecting data used questionnaires and data analysis used univariate, bivariate and multivariate analysis with logistic regression analysis. Based on bivariate analysis showed that there was a relationship between facilities, knowledge and attitudes of independent midwives with compliance with the standards of antenatal care services with a value of p <0.05. The results of the study with multivariate logistic regression analysis showed that the factors associated with the compliance of independent midwives in carrying out antenatal care service standards were attitudes with values (p = 0.026).

Risk Factors of Recurrent Ischemic Events after Acute Noncardiogenic Ischemic Stroke

2020 ◽  
Vol 25 (45) ◽  
pp. 4827-4834 ◽  
Author(s):  
Limin Zhang ◽  
Xingang Li ◽  
Dongzhi Wang ◽  
Hong Lv ◽  
Xuezhong Si ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Operating Characteristic ◽  
Control Group ◽  
Case Group ◽  
Stroke Patients ◽  
Clopidogrel Therapy ◽  
Ischemic Events

Background: A considerable proportion of acute noncardiogenic ischemic stroke patients continue to experience recurrent ischemic events after standard therapy. Aim: We aimed to identify risk factors for recurrent ischemic event prediction at an early stage. Methods : 286 non-cardioembolic ischemic stroke patients with the onset of symptoms within 24 hours were enrolled. Vascular risk factors, routine laboratory data on admission, thromboelastography test seven days after clopidogrel therapy and any recurrent events within one year were assessed. Patients were divided into case group (patients with clinical adverse events, including ischemic stokes, transient ischemic attack, myocardial infarction and vascular related mortality) and control group (events-free patients). The risk of the recurrent ischemic events was determined by the receiver operating characteristic curve and multivariable logistic regression analysis. Results: Clinical adverse events were observed in 43 patients (case group). The mean levels of Mean Platelet Volume (MPV), Platelet/Lymphocyte Ratio (PLR), Lymphocyte Count (LY) and Fibrinogen (Fib) on admission were significantly higher in the case group as compared to the control group (P<0.001). Seven days after clopidogrel therapy, the ADP-induced platelet inhibition rate (ADP%) level was lower in the case group, while the Maximum Amplitude (MA) level was higher in the case group as compared to the control group (P<0.01). The Area Under the Curve (AUC) of receiver operating characteristic(ROC) curve of LY, PLR, , Fib, MA, ADP% and MPV were 0.602, 0.614, 0.629, 0.770, 0.800 and 0.808, respectively. The logistic regression analysis showed that MPV, ADP% and MA were indeed predictive factors. Conclusion: MPV, ADP% and MA were risk factors of recurrent ischemic events after acute noncardiogenic ischemic stroke. Urgent assessment and individual drug therapy should be offered to these patients as soon as possible.

Perceptions of geographical indication labels as quality indicators inside and outside the labels’ area of influence: the case of spring fruits

2021 ◽  
pp. 1-7
Author(s):  
Rabadán Adrián ◽  
Martínez-Carrasco Laura ◽  
Brugarolas Margarita ◽  
Bernabéu Rodolfo
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Quality Indicators ◽  
Added Value ◽  
Geographical Indications ◽  
Geographical Indication ◽  
Protected Designation Of Origin ◽  
Rural Environments ◽  
Production Area ◽  
Area Of Influence

Abstract Geographical indications (GIs) are valuable attributes that enhance the competitiveness of agri-food products, generate added value and revitalize rural environments. The aim of this work was to analyze the attributes spring fruit consumers associate with GIs when they decide to purchase these products. Moreover, the changes in these associations with the increasing distance between the region of production and the place of consumption were also evaluated. We specifically analyzed two GIs used for spring fruits: the protected geographical indication for Mountain Cherries from Alicante (Spain) and the protected designation of origin for Loquats from Callosa d'En Sarriá (Spain). Data were analyzed using logistic regression analysis. The results show the significant association in consumers' minds between the preference for GI fruit and the importance attributed to the place of production (origin). The association of different attributes with the GI fruit label is product dependent as the number of attributes associated in the case of cherries (origin, organic, color and variety) is higher than for loquats (origin and variety). Regarding the distance between the production area and the place of consumption, our findings suggest that the closer the consumer is to the GI area of influence, the more attributes they associate with these labels. In this regard, increasing the knowledge of the GI labels beyond their area of influence could boost the demand for these products as consumers would be aware of the different quality attributes concentrated in that label.

scholarly journals Efficacy of flurbiprofen axetil for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Atsushi Kotera
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Postoperative Pain ◽  
Logistic Regression Analysis ◽  
Pain Control ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Postoperative Pain Control ◽  
Flurbiprofen Axetil ◽  
Postanesthetic Shivering

Abstract Background Postanesthetic shivering is an unpleasant adverse event in surgical patients. A nonsteroidal anti-inflammatory drug has been reported to be useful in preventing postanesthetic shivering in several previous studies. The aim of this study was to evaluate the efficacy of flurbiprofen axetil being a prodrug of a nonsteroidal anti-inflammatory drug for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries. Method This study is a retrospective observational study. I collected data from patients undergoing gynecologic laparotomy surgeries performed between October 1, 2019, and September 30, 2020, at Kumamoto City Hospital. All the patients were managed with general anesthesia with or without epidural analgesia. The administration of intravenous 50 mg flurbiprofen axetil for postoperative pain control at the end of the surgery was left to the individual anesthesiologist. The patients were divided into two groups: those who had received intravenous flurbiprofen axetil (flurbiprofen group) and those who had not received intravenous flurbiprofen axetil (non-flurbiprofen group), and I compared the frequency of postanesthetic shivering between the two groups. Additionally, the factors presumably associated with postanesthetic shivering were collected from the medical charts. Intergroup differences were assessed with the χ2 test with Yates’ correlation for continuity category variables. The Student’s t test was used to test for differences in continuous variables. Furthermore, a multivariate logistic regression analysis was performed to elucidate the relationship between the administration of flurbiprofen axetil and the incidence of PAS. Results I retrospectively examined the cases of 141 patients aged 49 ± 13 (range 21-84) years old. The overall postanesthetic shivering rate was 21.3% (30 of the 141 patients). The frequency of postanesthetic shivering in the flurbiprofen group (n = 31) was 6.5%, which was significantly lower than that in the non-flurbiprofen group (n = 110), 25.5% (p value = 0.022). A multivariate logistic regression analysis showed that administration of flurbiprofen axetil was independently associated with a reduced incidence of postanesthetic shivering (odds ratio 0.12; 95% confidence interval, 0.02-0.66, p value = 0.015). Conclusions My result suggests that intraoperative 50 mg flurbiprofen axetil administration for postoperative pain control is useful to prevent postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries.

scholarly journals Prior Admissions as a Risk Factor for Readmission in Patients Surgically Treated for Femur Fractures: Implications for a Potential Hip Fracture Bundle

2021 ◽  
Vol 12 ◽  
pp. 215145932199616
Author(s):  
Robert Erlichman ◽  
Nicholas Kolodychuk ◽  
Joseph N. Gabra ◽  
Harshitha Dudipala ◽  
Brook Maxhimer ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hip Fracture ◽  
Logistic Regression Analysis ◽  
Hip Fractures ◽  
Surgical Procedure ◽  
Hospital Admissions ◽  
Fracture Care ◽  
Increased Risk ◽  
Payment Models

Introduction: Hip fractures are a significant economic burden to our healthcare system. As there have been efforts made to create an alternative payment model for hip fracture care, it will be imperative to risk-stratify reimbursement for these medically comorbid patients. We hypothesized that patients readmitted to the hospital within 90 days would be more likely to have a recent previous hospital admission, prior to their injury. Patients with a recent prior admission could therefore be considered higher risk for readmission and increased cost. Methods: A retrospective chart review identified 598 patients who underwent surgical fixation of a hip or femur fracture. Data on readmissions within 90 days of surgical procedure and previous admissions in the year prior to injury resulting in surgical procedure were collected. Logistic regression analysis was used to determine if recent prior admission had increased risk of 90-day readmission. A subgroup analysis of geriatric hip fractures and of readmitted patients were also performed. Results: Having a prior admission within one year was significantly associated (p < 0.0001) for 90-day readmission. Specifically, logistic regression analysis revealed that a prior admission was significantly associated with 90-day readmission with an odds ratio of 7.2 (95% CI: 4.8-10.9). Discussion: This patient population has a high rate of prior hospital admissions, and these prior admissions were predictive of 90-day readmission. Alternative payment models that include penalties for readmissions or fail to apply robust risk stratification may unjustly penalize hospital systems which care for more medically complex patients. Conclusions: Hip fracture patients with a recent prior admission to the hospital are at an increased risk for 90-day readmission. This information should be considered as alternative payment models are developed for hip fracture care.

scholarly journals Online health information-seeking behaviors and skills of Chinese college students

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dangui Zhang ◽  
Weixin Zhan ◽  
Chunwen Zheng ◽  
Jinsheng Zhang ◽  
Anqi Huang ◽  
...  
Keyword(s):  
College Students ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Health Information ◽  
Information Seeking ◽  
Online Health Information ◽  
Chinese College Students ◽  
Link Type ◽  
Bivariate Logistic Regression ◽  
Information Seeking Behaviors

Abstract Background Seeking online health information (OHI) has become a common practice globally. The information seekers could face health risks if they are not proficient in OHI literacy. The OHI-seeking behaviors and skills of Chinese college students, the largest proportion of college students in the world, are understudied. This study was aimed to describe OHI-seeking behaviors and skills of college students in Guangdong, China. Methods College students in the Guangdong province with OHI-seeking experience were invited via WeChat, QQ, and Sina Weibo using QR code posters and flyers for participation in this online anonymized questionnaire-based study. Data on demographics, OHI literacy, information resources, search approaches, and behaviors were collected. The relationship between perceived OHI literacy and high-risk behaviors was investigated by bivariate logistic regression analysis. Results Respondents were 1203 college students with a mean age of 20.6 years, females (60.2%), and undergraduates (97.2%). They sought health information via websites (20.3%), WeChat (2.6%), or both (77.1%). Baidu was the main search engine, and baike.baidu.com (80.3%), Zhihu.com (48.4%), and Zhidao.baidu.com (35.8%) were top three among 20 searched websites for information about self-care (80.7%), general health (79.5%), disease prevention (77.7%), self-medication (61.2%), family treatment (40.9%), drugs (37.7%), western medications (26.6%), hospitals (22.7%), physicians (21.4%), and Traditional Chinese Medicine (15.6%). Despite most respondents (78%) lacked confidence in the evidence quality and satisfaction with the results, only 32.4% further consulted doctors. Many (> 50%) would recommend the retrieved information to others. About 20% experienced hacking/Internet fraud. Cronbach’s alpha for the internal consistency of OHI literacy was 0.786. Bivariate logistic regression analysis showed that students who believed they can judge the evidence level of OHI were more likely to self-diagnose (OR = 2.2, 95%CI, 1.6–3.1) and look for drug usage (OR = 3.1, 95%CI, 1.9–5.0). Conclusions This study reveals Chinese college students’ heavy reliance on OHI to manage their own and others’ health without sufficient knowledge/skills to identify misinformation and disinformation. The apparent risky information-seeking behaviors of Chinese college students warrant the provision of regulated, accurate, and actionable health information; assurance of cybersecurity; and health information literacy promotion in colleges by concerned authorities.

scholarly journals A large database supports the use of simple models of post-fire tree mortality for thick-barked conifers, with less support for other species

Fire Ecology ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
C. Alina Cansler ◽  
Sharon M. Hood ◽  
Phillip J. van Mantgem ◽  
J. Morgan Varner
Keyword(s):  
Tree Mortality ◽  
Characteristic Curve ◽  
Small Diameter ◽  
Fire Effects ◽  
Tree Level ◽  
Clear Understanding ◽  
Bark Thickness ◽  
Mortality Models ◽  
Species Specific ◽  
Stem Mortality

Abstract Background Predictive models of post-fire tree and stem mortality are vital for management planning and understanding fire effects. Post-fire tree and stem mortality have been traditionally modeled as a simple empirical function of tree defenses (e.g., bark thickness) and fire injury (e.g., crown scorch). We used the Fire and Tree Mortality database (FTM)—which includes observations of tree mortality in obligate seeders and stem mortality in basal resprouting species from across the USA—to evaluate the accuracy of post-fire mortality models used in the First Order Fire Effects Model (FOFEM) software system. The basic model in FOFEM, the Ryan and Amman (R-A) model, uses bark thickness and percentage of crown volume scorched to predict post-fire mortality and can be applied to any species for which bark thickness can be calculated (184 species-level coefficients are included in the program). FOFEM (v6.7) also includes 38 species-specific tree mortality models (26 for gymnosperms, 12 for angiosperms), with unique predictors and coefficients. We assessed accuracy of the R-A model for 44 tree species and accuracy of 24 species-specific models for 13 species, using data from 93 438 tree-level observations and 351 fires that occurred from 1981 to 2016. Results For each model, we calculated performance statistics and provided an assessment of the representativeness of the evaluation data. We identified probability thresholds for which the model performed best, and the best thresholds with either ≥80% sensitivity or specificity. Of the 68 models evaluated, 43 had Area Under the Receiver Operating Characteristic Curve (AUC) values ≥0.80, indicating excellent performance, and 14 had AUCs <0.7, indicating poor performance. The R-A model often over-predicted mortality for angiosperms; 5 of 11 angiosperms had AUCs <0.7. For conifers, R-A over-predicted mortality for thin-barked species and for small diameter trees. The species-specific models had significantly higher AUCs than the R-A models for 10 of the 22 models, and five additional species-specific models had more balanced errors than R-A models, even though their AUCs were not significantly different or were significantly lower. Conclusions Approximately 75% of models tested had acceptable, excellent, or outstanding predictive ability. The models that performed poorly were primarily models predicting stem mortality of angiosperms or tree mortality of thin-barked conifers. This suggests that different approaches—such as different model forms, better estimates of bark thickness, and additional predictors—may be warranted for these taxa. Future data collection and research should target the geographical and taxonomic data gaps and poorly performing models identified in this study. Our evaluation of post-fire tree mortality models is the most comprehensive effort to date and allows users to have a clear understanding of the expected accuracy in predicting tree death from fire for 44 species.

scholarly journals The association between hypoglycemia and glycemic variability in elderly patients with type 2 diabetes: a prospective observational study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Takahisa Handa ◽  
Akinobu Nakamura ◽  
Aika Miya ◽  
Hiroshi Nomoto ◽  
Hiraku Kameda ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Observational Study ◽  
Elderly Patients ◽  
Prospective Observational Study ◽  
Multivariate Logistic Regression Analysis ◽  
Glycemic Variability ◽  
Multivariate Logistic Regression

Abstract Background This study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes. Methods We conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%. Results In the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses. Conclusions Among elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined. Trial registration UMIN-CTR: UMIN000029993. Registered 16 November 2017

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