scholarly journals Modeling the Wintering Habitat Distribution of Oriental Honey Buzzards in West Java Indonesia with Satellite Tracking Data Using Logistic Regression

2021 ◽  
Vol 29 (1) ◽  
pp. 9-21
Author(s):  
Syartinilia Syartinilia ◽  
Yeni Aryati Mulyani ◽  
Afra Donatha Nimia Makalew ◽  
Hiroyoshi Higuchi
Keyword(s):  
Logistic Regression ◽  
Probability Model ◽  
Satellite Tracking ◽  
Probability Models ◽  
Habitat Distribution ◽  
West Java ◽  
Predicted Probability ◽  
Presence Data ◽  
Wintering Habitat ◽  
Surrounding Areas

Oriental honey buzzards (OHBs, Pernis ptilorhynchus) are one of migratory raptor from Japan to Indonesia which is widely recognized as indicator species reflecting the conditions of their habitat. Since 2003, OHBs have been satellite-tracked in their wintering grounds in Indonesia. Less information available on wintering areas in the west Java, which hampers the OHB conservation efforts. This paper proposes a new approach for predicting the probability models of the wintering habitat distribution of OHBs with the presence data derived from satellite tracking using logistic regression analysis coupled with RAMAS GIS. This spatial model was locally constructed from the data concerning Talaga Bodas and its surrounding areas and extrapolated for the entire West Java region. The best predicted probability model successfully characterized the distribution of the OHB wintering habitat using slope (25–40%), elevation (0–300 m and >1,000 m), and land cover (forest, paddy field, and water body). The extrapolation model generated potential areas of the wintering habitat distribution covering an area of 3013.13 km2 (8.11% of West Java). These areas were predominantly located outside the protected areas (94.04%). The modeling approach proposed herein may be used to study other migratory species that are tracked using satellite or other navigation technologies.

scholarly journals Identifying trauma patients with benefit from direct transportation to Level-1 trauma centers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Charlie A. Sewalt ◽  
Benjamin Y. Gravesteijn ◽  
Daan Nieboer ◽  
Ewout W. Steyerberg ◽  
Dennis Den Hartog ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Trauma Center ◽  
Trauma Patients ◽  
Trauma Centers ◽  
Absolute Benefit ◽  
Predicted Probability ◽  
Prehospital Triage ◽  
Level 1 ◽  
Level 1 Trauma Center ◽  
Level 2

Abstract Background Prehospital triage protocols typically try to select patients with Injury Severity Score (ISS) above 15 for direct transportation to a Level-1 trauma center. However, ISS does not necessarily discriminate between patients who benefit from immediate care at Level-1 trauma centers. The aim of this study was to assess which patients benefit from direct transportation to Level-1 trauma centers. Methods We used the American National Trauma Data Bank (NTDB), a retrospective observational cohort. All adult patients (ISS > 3) between 2015 and 2016 were included. Patients who were self-presenting or had isolated limb injury were excluded. We used logistic regression to assess the association of direct transportation to Level-1 trauma centers with in-hospital mortality adjusted for clinically relevant confounders. We used this model to define benefit as predicted probability of mortality associated with transportation to a non-Level-1 trauma center minus predicted probability associated with transportation to a Level-1 trauma center. We used a threshold of 1% as absolute benefit. Potential interaction terms with transportation to Level-1 trauma centers were included in a penalized logistic regression model to study which patients benefit. Results We included 388,845 trauma patients from 232 Level-1 centers and 429 Level-2/3 centers. A small beneficial effect was found for direct transportation to Level-1 trauma centers (adjusted Odds Ratio: 0.96, 95% Confidence Interval: 0.92–0.99) which disappeared when comparing Level-1 and 2 versus Level-3 trauma centers. In the risk approach, predicted benefit ranged between 0 and 1%. When allowing for interactions, 7% of the patients (n = 27,753) had more than 1% absolute benefit from direct transportation to Level-1 trauma centers. These patients had higher AIS Head and Thorax scores, lower GCS and lower SBP. A quarter of the patients with ISS > 15 were predicted to benefit from transportation to Level-1 centers (n = 26,522, 22%). Conclusions Benefit of transportation to a Level-1 trauma centers is quite heterogeneous across patients and the difference between Level-1 and Level-2 trauma centers is small. In particular, patients with head injury and signs of shock may benefit from care in a Level-1 trauma center. Future prehospital triage models should incorporate more complete risk profiles.

Alternative models and randomization techniques for Bayesian response-adaptive randomization with binary outcomes

2021 ◽  
pp. 174077452110101
Author(s):  
Jennifer Proper ◽  
John Connett ◽  
Thomas Murray
Keyword(s):  
Logistic Regression ◽  
Sample Size ◽  
Error Rate ◽  
Adaptive Design ◽  
Type I Error ◽  
Probability Model ◽  
Binary Outcomes ◽  
Type I ◽  
Operating Characteristics ◽  
Type I Error Rate

Background: Bayesian response-adaptive designs, which data adaptively alter the allocation ratio in favor of the better performing treatment, are often criticized for engendering a non-trivial probability of a subject imbalance in favor of the inferior treatment, inflating type I error rate, and increasing sample size requirements. The implementation of these designs using the Thompson sampling methods has generally assumed a simple beta-binomial probability model in the literature; however, the effect of these choices on the resulting design operating characteristics relative to other reasonable alternatives has not been fully examined. Motivated by the Advanced R2 Eperfusion STrategies for Refractory Cardiac Arrest trial, we posit that a logistic probability model coupled with an urn or permuted block randomization method will alleviate some of the practical limitations engendered by the conventional implementation of a two-arm Bayesian response-adaptive design with binary outcomes. In this article, we discuss up to what extent this solution works and when it does not. Methods: A computer simulation study was performed to evaluate the relative merits of a Bayesian response-adaptive design for the Advanced R2 Eperfusion STrategies for Refractory Cardiac Arrest trial using the Thompson sampling methods based on a logistic regression probability model coupled with either an urn or permuted block randomization method that limits deviations from the evolving target allocation ratio. The different implementations of the response-adaptive design were evaluated for type I error rate control across various null response rates and power, among other performance metrics. Results: The logistic regression probability model engenders smaller average sample sizes with similar power, better control over type I error rate, and more favorable treatment arm sample size distributions than the conventional beta-binomial probability model, and designs using the alternative randomization methods have a negligible chance of a sample size imbalance in the wrong direction. Conclusion: Pairing the logistic regression probability model with either of the alternative randomization methods results in a much improved response-adaptive design in regard to important operating characteristics, including type I error rate control and the risk of a sample size imbalance in favor of the inferior treatment.

Study on Hazard Analysis Method of Earthquake Secondary Fire Disaster in Urban Area Based on GIS

2012 ◽  
Vol 204-208 ◽  
pp. 3457-3461
Author(s):  
Tian Qi Li ◽  
Fei Geng
Keyword(s):  
Urban Areas ◽  
Hazard Analysis ◽  
Probability Model ◽  
Probability Models ◽  
Housing Density ◽  
Earthquake Excitation ◽  
Fire Disaster ◽  
High Hazard ◽  
The City ◽  
And Diffusion

In order to study the probability of occurrence of secondary fire after the earthquake in urban areas, the probability model of the hazard analysis that the fire occurred and the spread is established and applied. Probability models need to consider the destruction level of buildings under earthquake excitation as well as the probability of the leakage and diffusion of combustible material in the buildings in the corresponding destruction level, combination of weather, season, housing density and other factors to determine the probability of the single building earthquake secondary fire. On this basis , the natural administrative areas in the city as a unit , considering the factors of regional hazard analysis such as population density , property distribution and density within a region , to calculate the hazard indicator and determine the high hazard areas of secondary fire in the city. The Geographic Information System was used as the platform, to division of urban earthquake secondary fire high-hazard areas.

scholarly journals Ultraviolet Exposure and Photokeratitis Complaints among Informal Welding Workers in Depok, West Java, Indonesia

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Maria K I J Yustheresani ◽  
Fajaria Nurcandra ◽  
Azizah Musliha Fitri ◽  
Annisa Ika Putri ◽  
Dyah Utari
Keyword(s):  
Logistic Regression ◽  
Uv Radiation ◽  
Education Level ◽  
Epithelial Tissue ◽  
West Java ◽  
Eye Protection ◽  
Regression Test ◽  
Safety Knowledge ◽  
Logistic Regression Test ◽  
Uv Rays

One of the photokeratitis risk factors is acute reversible radiation of ultraviolet (UV) rays, which injure the cornea's epithelial tissue. Informal welding workers are susceptible populations to UV rays exposure. This study aimed to confirm the influence of UV radiation exposure on photokeratitis complaints in welding workers in Cimanggis, Depok, West Java. A cross-sectional study was conducted from February to June 2019 and used to select 100 welding workers purposively. A semi-structured questionnaire was used to determine photokeratitis complaints, age, education level, eye protection, safety knowledge, and work period; the UV radiation measured by A UV meter. Data were analyzed using a logistic regression test. We found the proportion of photokeratitis to be 84.0%, with 76.0% of UV radiation exceeding the Threshold Limit Values (TLV). The logistic regression test showed a significant effect of UV radiation on photokeratitis after controlling confounding variables (education level, eye protection, safety knowledge, and welding distance) (p-value = 0.006; AdjOR = 7.236; 95% CI: 1.74–30.07). It can be concluded that UV radiation, more than TLV, constitutes the primary risk factor for photokeratitis complaints. Risks for photokeratitis were influenced by low education level, poor eye protection, limited safety knowledge, and welding distance ≤ 45 cm.

scholarly journals DAMPAK PEMINDAHAN IBU KOTA NEGARA TERHADAP PENDUDUK DAN KETENAGAKERJAAN DI PROVINSI JAWA BARAT

2021 ◽  
Vol 15 (2) ◽  
pp. 133
Author(s):  
Janiar Ningrum ◽  
Jamalludin Jamalludin ◽  
Izzun Nafiah ◽  
Ferry Maurist Sitorus ◽  
Ferlistya Pratita Rari ◽  
...  
Keyword(s):  
Secondary Data ◽  
Civil Servants ◽  
Capital City ◽  
Medium Term ◽  
The West ◽  
West Java ◽  
East Kalimantan ◽  
Secondary Data Sources ◽  
The Government ◽  
Surrounding Areas

The plan to relocate the Indonesian capital as set out in the 2020-2024 National Medium-Term Development Plan (RPJMN) to East Kalimantan Province will start in 2024. During the process, the government also plans to move central civil servants to the new capital. The planned relocation of the capital city impacts all central civil servants located in DKI Jakarta and surrounding areas. This research used secondary data sources as a basis for population and employment projections. From the results obtained, West Java's population will continue to grow during the growth rate decline. The relocation plan will directly impact the West Java population, but the effect tends to be less significant given the small number of central civil servants located in west java compared to West Java's population as a whole. The relocation plan will impact social environment conditions, economic activity, and the environment in surrounding areas.

scholarly journals On the S-instability and degeneracy of discrete deep learning models

2019 ◽  
Vol 9 (3) ◽  
pp. 627-655 ◽  
Author(s):  
Andee Kaplan ◽  
Daniel J Nordman ◽  
Stephen B Vardeman
Keyword(s):  
Probability Model ◽  
Correlated Data ◽  
Data Sequence ◽  
Probability Models ◽  
Large Classes ◽  
Learning Contexts ◽  
Probability Structure ◽  
Model Probability ◽  
Parameter Sequence ◽  
Outcome Result

Abstract A probability model exhibits instability if small changes in a data outcome result in large and, often unanticipated, changes in probability. This instability is a property of the probability model, given by a distributional form and a given configuration of parameters. For correlated data structures found in several application areas, there is increasing interest in identifying such sensitivity in model probability structure. We consider the problem of quantifying instability for general probability models defined on sequences of observations, where each sequence of length $N$ has a finite number of possible values that can be taken at each point. A sequence of probability models, indexed by $N$, and an associated parameter sequence result to accommodate data of expanding dimension. Model instability is formally shown to occur when a certain log probability ratio under such models grows faster than $N$. In this case, a one component change in the data sequence can shift probability by orders of magnitude. Also, as instability becomes more extreme, the resulting probability models are shown to tend to degeneracy, placing all their probability on potentially small portions of the sample space. These results on instability apply to large classes of models commonly used in random graphs, network analysis and machine learning contexts.

scholarly journals The Association between Earlobe Crease (Frank’s Sign) and Abnormal Ankle-Brachial Index Determination Is Related to Age: A Population-Based Study

2018 ◽  
Vol 2018 ◽  
pp. 1-4 ◽  
Author(s):  
Oscar H. Del Brutto ◽  
Robertino M. Mera ◽  
Aldo F. Costa ◽  
Mauricio Zambrano ◽  
Mark J. Sedler
Keyword(s):  
Logistic Regression ◽  
Peripheral Artery Disease ◽  
Ankle Brachial Index ◽  
Heart Association ◽  
Population Based ◽  
Community Dwelling ◽  
Peripheral Artery ◽  
Probability Models ◽  
High Prevalence ◽  
Artery Disease

Background. Information on the association between earlobe crease (ELC) and peripheral artery disease is limited. We assessed this association in community-dwelling older adults. Study Design. A total of 294 Atahualpa residents aged ≥60 years were enrolled. ELC were visually identified by two raters. The ankle-brachial index (ABI), used as a surrogate of peripheral artery disease, was categorized using American Heart Association criteria. Using logistic regression and probability models, adjusted for demographics and cardiovascular risk factors, we assessed the relationship between ELC and abnormal ABI determinations, as well as the influence of age on this association. Results. ELC was identified in 141 (48%) individuals, and abnormal ABI determination was carried out in 56 (19%). The association between ELC and abnormal ABI was nonsignificant in logistic regression and probability models with individuals stratified according to their median age. Conclusions. The association between ELC and abnormal ABI determinations is probably attenuated by the high prevalence of both conditions in older persons. ELC might not be useful for identifying candidates for ABI determination.

scholarly journals Sex-related Differences in Habitat Use in Wintering American Kestrels

The Auk ◽  
2001 ◽  
Vol 118 (3) ◽  
pp. 746-750 ◽  
Author(s):  
Daniel R. Ardia ◽  
Keith L. Bildstein
Keyword(s):  
Logistic Regression ◽  
Habitat Use ◽  
Regression Models ◽  
Woody Vegetation ◽  
High Quality ◽  
Male And Female ◽  
Logistic Regression Models ◽  
American Kestrels ◽  
Wintering Habitat ◽  
Work Supports

AbstractWe investigated sex-related differences in habitat use in wintering American Kestrels (Falco sparverius) at two scales: within a 10 m radius and within a 100 m radius of perch sites. Female kestrels used areas containing a higher percentage of short vegetation (<0.25 m high) suitable for foraging than did males at both scales (100 m radius females 80%, males 69%; 10 m radius females 80%, males 73%). At both scales, females had more pasture (a high-quality foraging substrate) available than did males; areas within a 100 m radius of male perch sites contained more woodlot than did female perch sites. Logistic regression models indicated greater overlap between male and female habitat use on a 10 m radius scale than on a 100 m radius scale, suggesting that males may preferentially select smaller areas devoid of woody vegetation relative to what is available within 100 m radius of perch sites. Our results suggest that males may be constrained to winter in areas with lower overall foraging opportunities and possibly higher predation risk than areas used by females. Our work supports the hypothesis that males and female kestrels prefer open areas as wintering habitat.

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