scholarly journals Prey’s traits mediate a neotropical toad diet

2018 ◽  
Author(s):  
Matthew T. McElroy ◽  
David A. Donoso
Keyword(s):  
Regression Models ◽  
Morphological Characteristics ◽  
Handling Time ◽  
Species Level ◽  
Barro Colorado Island ◽  
List Type ◽  
Nutritional Content ◽  
Widespread Occurrence ◽  
Multiple Regression Models ◽  
Predator Preference

B.ABSTRACTDespite the widespread occurrence of myrmecophagy in anurans it is generally unclear whether ant-specialists feed on ants opportunistically or whether they preferentially select for certain species, potentially favoring specific morphological, ecological, or nutritional traits.We flushed 105 stomachs of a lowland neotropical toad, Rhinella alata, and identified each consumed ant to species level. We used linear selectivity to calculate predator preference by comparing the abundances of consumed species to their abundances in the leaf litter community on Barro Colorado Island, Panama. We conducted multiple regression models to test whether linear selectivity or general predator preference related to seven morphological characteristics and two measurements of nutritional content.Rhinella alata preferentially harvested 24 ant species. Other species were either avoided (n=34) or were eaten opportunistically (n=26). We found that R. alata predominantly preys upon large ants that are textured with hair and/or rugosity and preference for prey did not relate to nutrition content. Rhinella alata avoided small ants even if they were hyper abundant in the environment, and preferentially ate chemically-defended and aggressive ants if they were large enough.We propose that R. alata prefers large ants because they represent a more efficient prey item in terms of predator handling time and because they are easier to see than are smaller ants. Furthermore, we hypothesize that R. alata predation attempts are more successful when prey are textured because microstructures on the tongue and prey surface may increase prey adhesion.The ant specialist R. alata is not specializing on any particular ant species but rather maximizing prey quantity over quality by only eating the largest ants, despite their scarcity in the environment.

scholarly journals 242 Effect of trucking distance on sale price of beef calf and feeder cattle lots sold through video auctions from 2010 through 2018

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 10-11
Author(s):  
Esther D McCabe ◽  
Mike E King ◽  
Karol E Fike ◽  
Maggie J Smith ◽  
Glenn M Rogers ◽  
...  
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Average Weight ◽  
Sale Price ◽  
Feeder Cattle ◽  
A Value ◽  
Multiple Regression Models ◽  
Determine Effect

Abstract The objective was to determine effect of trucking distance on sale price of beef calf and feeder cattle lots sold through Superior Livestock Video Auctions from 2010 through 2018. Data analyzed were collected from 211 livestock video auctions. There were 42,043 beef calf lots and 19,680 feeder cattle lots used in these analyses. Six states (Colorado, Iowa, Kansas, Nebraska, Oklahoma, and Texas) of delivery comprised 70% of calf lots and 83% of feeder cattle lots and were used in these analyses. All lot characteristics that could be accurately quantified or categorized were used to develop multiple regression models that evaluated effects of independent factors using backwards selection. A value of P < 0.05 was used to maintain a factor in the final models. Based upon reported state of origin and state of delivery, lots were categorized into one of the following trucking distance categories: 1) Within-State, 2) Short-Haul, 3) Medium-Haul, and 4) Long-Haul. Average weight and number of calves in lots analyzed was 259.2 ± 38.4 kg BW and 100.6 ± 74.3 head, respectively. Average weight and number of feeder cattle in lots analyzed was 358.4 ± 34.3 kg BW and 110.6 ± 104.1 head, respectively. Beef calf lots hauled Within-State sold for more ($169.24/45.36 kg; P < 0.0001) than other trucking distance categories (Table 1). Long-Haul calf lots sold for the lowest (P < 0.0001) price ($166.70/45.36 kg). Within-State and Short-Haul feeder cattle lots sold for the greatest (P < 0.0001) price ($149.96 and $149.81/45.36 kg, respectively; Table 2). Long-Haul feeder cattle lots sold for the lowest (P < 0.0001) price, $148.43/45.36 kg. These results indicate there is a price advantage for lots expected to be hauled shorter distances, likely because of cost and risk associated with transportation.

scholarly journals Characterization of Ultra-Thin Diamond-Like Carbon Films by SEM/EDX

Coatings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 729
Author(s):  
Chanida Puttichaem ◽  
Guilherme P. Souza ◽  
Kurt C. Ruthe ◽  
Kittipong Chainok
Keyword(s):  
Regression Models ◽  
Hard Disk Drives ◽  
Carbon Films ◽  
Diamond Like Carbon ◽  
Disk Drives ◽  
Cross Sectional ◽  
Protective Films ◽  
High Throughput Method ◽  
Multiple Regression Models

A novel, high throughput method to characterize the chemistry of ultra-thin diamond-like carbon films is discussed. The method uses surface sensitive SEM/EDX to provide substrate-specific, semi-quantitative silicon nitride/DLC stack composition of protective films extensively used in the hard disk drives industry and at Angstrom-level. SEM/EDX output is correlated to TEM to provide direct, gauge-capable film thickness information using multiple regression models that make predictions based on film constituents. The best model uses the N/Si ratio in the films, instead of separate Si and N contributions. Topography of substrate/film after undergoing wear is correlatively and compositionally described based on chemical changes detected via the SEM/EDX method without the need for tedious cross-sectional workflows. Wear track regions of the substrate have a film depleted of carbon, as well as Si and N in the most severe cases, also revealing iron oxide formation. Analysis of film composition variations around industry-level thicknesses reveals a complex interplay between oxygen, silicon and nitrogen, which has been reflected mathematically in the regression models, as well as used to provide valuable insights into the as-deposited physics of the film.

Multiple regression models for predicting total daily pollen concentration in Cartagena

Grana ◽  
2005 ◽  
Vol 44 (2) ◽  
pp. 108-114 ◽  
Author(s):  
José Manuel Angosto ◽  
Stella Moreno‐Grau ◽  
Javier Bayo ◽  
Belén Elvira‐Rendueles
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Pollen Concentration ◽  
Multiple Regression Models ◽  
Daily Pollen Concentration

The Effects of Prepaid Metering Systems on Customer Satisfaction in Niger State, Nigeria

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Ayooluwa Femi Aribisala ◽  
Musa Mohammed
Keyword(s):  
Customer Satisfaction ◽  
Regression Models ◽  
Response Rate ◽  
Spearman Correlation ◽  
Electricity Use ◽  
Customer Care ◽  
Level Of Satisfaction ◽  
Multiple Regression Models ◽  
The Relationship ◽  
Structured Questionnaire

Energy consumers in Nigeria have long complained about Distribution Companies' unfair billing practices, exorbitant monthly electricity bills resulting from meter estimation rather than accurate meter reading and calculation based on uninterrupted electricity use. The objectives of the study were to establish the relationship between the prepaid metering system and customer satisfaction; and to evaluate the level of satisfaction with respect to the usage of the prepaid metering system in Niger State, Nigeria. In carrying out the study, the structured questionnaire was administered to 393 randomly chosen respondents drawn from prepaid meter users, out of which 344 responded generating a response rate of 87.5%. The data derived were subjected to spearman correlation and multiple regression models. The major findings from the study showed a significant, moderate and positive relationship between the prepaid metering system and customer satisfaction. Additionally, three significant predictors, Affordability, Availability and Flexibility with p < .01 are statistically significant. Further findings from descriptive statistics revealed that users had the highest level of satisfaction with the privacy they had as a result of no meter readers and no accumulated. The study concluded that there exist a positive and beneficial link between the prepaid metering system and customer satisfaction. The study therefore recommends the provision of a smart metering system, good customer care units and a marketing campaign for better knowledge of the prepaid metering system.

scholarly journals New Algorithms for L1 Norm Regression

2019 ◽  
Vol 1 (1) ◽  
pp. 1-18
Author(s):  
Bijan Bidabad
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Simple Linear Regression ◽  
L1 Norm ◽  
Median Problem ◽  
Regression Parameters ◽  
Multiple Regression Models ◽  
Weighted Median ◽  
Weighted Median Problem ◽  
New Algorithms

In this paper, we propose four algorithms for L1 norm computation of regression parameters, where two of them are more efficient for simple and multiple regression models.  However, we start with restricted simple linear regression and corresponding derivation and computation of the weighted median problem. In this respect, a computing function is coded.  With discussion on the m parameters model, we continue to expand the algorithm to include unrestricted simple linear regression, and two crude and efficient algorithms are proposed. The procedures are then generalized to the m parameters model by presenting two new algorithms, where the algorithm 4 is selected as more efficient. Various properties of these algorithms are discussed.

Abstract WP238: Atrial Fibrillation is Associated With Severe Basal Ganglia Perivascular Spaces

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Alvin S Das ◽  
Elif Gokcal ◽  
Robert W Regenhardt ◽  
Andrew Warren ◽  
Kristin Schwab ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Basal Ganglia ◽  
Multiple Regression ◽  
Regression Models ◽  
Small Vessel Disease ◽  
Perivascular Spaces ◽  
Nonvalvular Atrial Fibrillation ◽  
Related Factors ◽  
Multiple Regression Models ◽  
Independent Effects

Introduction: High burdens of basal ganglia-perivascular spaces (BG-PVS) are often attributed to underlying hypertensive cerebral small vessel disease (HTN-CSVD). Although PVS are thought to arise from decreased perivascular drainage related to changes in arterial pulsatility, the contribution of pulsatility changes from nonvalvular atrial fibrillation (NVAF) has not been studied. Hypothesis: We hypothesized that NVAF patients have a higher burden of BG-PVS than HTN-CSVD patients, possibly through hemodynamic factors related to NVAF. Methods: Through an observational single-center study of consecutive stroke patients, we compared BG-EPVS severity between 136 patients with NVAF-related ischemic stroke (NVAF-IS) and 107 patients with HTN-CSVD-related intracerebral hemorrhage (HTN-ICH) without NVAF. Within the NVAF cohort, we also built multiple regression models to evaluate independent effects of NVAF-related factors on BG-PVS. All multiple regression models were adjusted for age, hypertension, sex, and neuroimaging markers of CSVD (extent of white matter hyperintensities (WMH), presence of lacunes, and cerebral microbleeds). Results: Patients with NVAF-IS were older than patients with HTN-ICH (75 + 12 vs. 64 + 13, p < 0.0001); however, there was no difference in sex between groups ( p = 0.6). Severe BG-PVS (defined as > 20 PVS in the BG) were found in 42.6% of NVAF-IS patients vs. 8.4% of HTN-ICH ( p < 0.0001). Even after multivariate adjustment, the presence of NVAF remained significantly related to BG-PVS ( p = 0.001). Within the NVAF cohort, CHA2DS2-VASc was associated with the presence of severe BG-PVS ( p = 0.003) despite controlling for other covariates. When CHA2DS2-VASc was replaced with its individual components in the same regression model, congestive heart failure (CHF, p = 0.017), WMH burden ( p = 0.009), and age ( p = 0.02) were found to be predictors of severe BG-PVS. Conclusions: Severe BG-PVS were significantly more common in NVAF patients compared to HTN-CSVD patients. NVAF-related features (CHA2DS2-VASc score) and CHF were associated with higher burdens of BG-PVS. These findings suggest that NVAF might play a role in the development of BG-PVS, conceivably through hemodynamic factors.

Optimal Spindle Detection Parameters for Predicting Cognitive Performance

SLEEP ◽  
2022 ◽  
Author(s):  
Noor Adra ◽  
Haoqi Sun ◽  
Wolfgang Ganglberger ◽  
Elissa M Ye ◽  
Lisa W Dümmer ◽  
...  
Keyword(s):  
Regression Models ◽  
Peak Frequency ◽  
Sleep Spindles ◽  
Methodological Challenge ◽  
Optimal Parameters ◽  
Mean Frequency ◽  
Multiple Regression Models ◽  
Parameter Interactions ◽  
Amplitude Density

Abstract Study Objectives Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition. Methods Adult patients (n=167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores. Results Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r=0.503) and age-adjusted fluid cognition scores (r=0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings. Conclusion Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

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