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.

The Role of Road Infrastructure and Air Pollution in the Recent Suburbanization of India’s Cities

2017 ◽  
Vol 8 (2) ◽  
pp. 151-169 ◽  
Author(s):  
Matthew J. Holian ◽  
Kala Seetharam Sridhar
Keyword(s):  
Air Pollution ◽  
Population Density ◽  
Urban Areas ◽  
Regression Models ◽  
Central City ◽  
Road Transport ◽  
Transport Infrastructure ◽  
Multiple Regression Models ◽  
Indian Cities

This article re-examines the suburbanization of Indian cities by calculating population density gradients, for a large number of urban agglomerations, using recent data and Mills’ two-point method. In the next step, we estimate multiple regression models to explore the determinants of suburbanization. This study presents several methodological advances over previous research, by incorporating new measures of transport infrastructure, air pollution and city–suburb income ratios as determinants of suburbanization of Indian cities. Our results clearly show that suburbanization is higher in urban areas with higher population and lower central city–suburban literacy ratios. We find some evidence that suburbanization is higher in urban areas with more road transport infrastructure, consistent with our expectations, though results concerning air pollution run counter to expectations. However, these could relate to caveats regarding the data and methods.

Self-concept clarity as a predictor of self-disclosure in romantic relationships

2020 ◽  
Vol 37 (6) ◽  
pp. 1873-1891
Author(s):  
Maryam Tajmirriyahi ◽  
William Ickes
Keyword(s):  
Romantic Relationships ◽  
Multiple Regression ◽  
Regression Models ◽  
Experimental Studies ◽  
Self Esteem ◽  
Self Concept ◽  
Future Research ◽  
Self Disclosure ◽  
Multiple Regression Models

Several studies have examined the role of self-esteem in self-disclosure while overlooking a potentially important confounding variable: self-concept clarity. Across three studies, we found an association between self-concept clarity and self-disclosure to one’s romantic partner. This incremental effect held even when the variance attributable to self-esteem was statistically controlled in a multiple regression analysis. Moreover, in two of the three studies, self-esteem was no longer a significant predictor of self-disclosure after controlling for the variance in self-concept clarity. These data suggest that self-concept clarity is an important predictor of self-disclosure—one that is conceptually and empirically distinct from self-esteem. That self-concept clarity tended to supplant self-esteem in the multiple regression models suggests that disclosing the specific aspects of the self that one clearly perceives (one’s attributes, goals, motives, values, etc.) might be more essential to everyday self-disclosure than disclosing only whether one has a globally positive or negative self-view. Future research should explore the causal relationships involved with the aid of experimental studies.

scholarly journals Alliance Portfolio Effects on New Venture’s Performance

2021 ◽  
Vol 17 ◽  
pp. 1-17
Author(s):  
Smriti Prabhakar-Sood
Keyword(s):  
Regression Models ◽  
New Ventures ◽  
Equity Market ◽  
New Venture ◽  
Strategy Research ◽  
Alliance Portfolio ◽  
Multiple Regression Models ◽  
Alliance Partners ◽  
Different Characteristics

This study investigates the effects of an alliance portfolio on a new venture’s performance. Specifically, this paper draws on the legitimacy perspective. It presents a model that aims to understand the influence of an alliance portfolio’s different characteristics on a new venture’s performance. The paper also considers the contingent role of the equity market environment. These relationships are investigated in a cross-industry sample of 123 new ventures with pre-IPO alliances. The data has been compiled from various databases selected for their comprehensiveness and extensive use in Strategy research. Hierarchical Multiple Regression models are run to analyze the data. This study suggests that new ventures can potentially send important signals regarding their quality by virtue of their partnership formations. The most important characteristic of the alliance portfolio that affects the value of the new venture is size. Consistent with prior research, this study finds that new ventures with prestigious underwriters have higher valuations at IPO across all industries. The results also extend this line of inquiry by showing that relationships with prominent underwriters, VCs and alliance partners are not prestigious.

scholarly journals The Effect of Innovational Performance on Determining Firm Value: Evidence from Indonesia

2020 ◽  
Vol 11 (2) ◽  
pp. 228-241
Author(s):  
Eka Handriani
Keyword(s):  
Firm Value ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Manufacturing Companies ◽  
Significant Determinant ◽  
Performance Variables ◽  
Multiple Regression Models ◽  
Total Investment

This study explores the most significant determinant of capital structure towards the value of manufacturing companies in Indonesia. Multiple regression models were used as statistical tools to investigate the most significant determinants of the firm value of manufacturing companies in Indonesia for a sample of 300 manufacturing firms listed on the Indonesia Stock Exchange. The results showed that profitability, company size, dividend, investment, and innovational performance were positively related to firm value. Debt was negatively related to firm value and dividend was an insignificant firm value determinant. Meanwhile, the influence of innovational performance variables mediating the effect of investment on firm value showed that the role of mediation innovational performance was able to increase the influence of total investment on firm value. Furthermore, empirical findings will help company managers to make decisions about the attempts to increase the firm value.

The Role of Department Supports on Doctoral Completion and Time-to-Degree

2016 ◽  
Vol 20 (4) ◽  
pp. 511-529 ◽  
Author(s):  
Enyu Zhou ◽  
Hironao Okahana
Keyword(s):  
Financial Support ◽  
Regression Models ◽  
Doctoral Programs ◽  
Academic Support ◽  
The United States ◽  
Future Research ◽  
Doctoral Completion ◽  
Time To Degree ◽  
Multiple Regression Models

This study examined department supports that influence doctoral completion and time-to-degree among 5,001 doctoral programs at 212 universities in the United States. Multiple regression models were used to determine the relationships between financial support and academic support and doctoral retention and how these relationships vary across STEM and non-STEM fields. Analyzing the American National Research Council’s data, we found that a department’s financial support significantly predict doctoral completion and time-to-degree. However, no overarching relationship was found between department academic support and doctoral completion and time-to-degree. These findings provide a better understanding of how department supports are associated with doctoral student success. The article concludes with implications for theory, practice, and future research.

scholarly journals Influence of Structural Age Shifts of Population on Sectoral Structure of Employment

2021 ◽  
Vol 39 (5) ◽  
Author(s):  
Liubov Vodianka ◽  
Andrii Antokhov ◽  
Natalіia Podluzhna ◽  
Iryna Antokhova ◽  
Viktor Saichuk ◽  
...  
Keyword(s):  
Regression Models ◽  
Quantitative Methods ◽  
Age Groups ◽  
Individual Characteristics ◽  
Economic Science ◽  
Essential Information ◽  
Sectoral Structure ◽  
Multiple Regression Models ◽  
Economic Reality

This article examines the correlation between the increase in age groups of population and branch structure of employment in the Ukrainian economy. Today, the study of human capital's impact on economic processes is an essential economic science component. The application of quantitative methods in this relationship's study provides essential information about the nature of the interconnection of individual characteristics of human capital and critical socio-economic processes in the current domestic economic reality. Applying correlation-regression analysis, modelling these interdependencies with multiple regression models, and estimating correlation and deterministic relationships, in particular, are essential means in the practical study of this macroeconomic resource impact. Economic and mathematical analysis of the interdependencies between employment in agricultural, industrial, and financial sectors and the growth of the Ukrainian population's age groups were carried out. Based on these data, conclusions were drawn about critical macroeconomic processes, which are quantitatively confirmed by the built models. The role of the age structure of the population in structural transformations of the Ukrainian economy was evaluated.

Soil Chemical Pollution and Aggressive Pathologies

2018 ◽  
Vol 69 (8) ◽  
pp. 2278-2282
Author(s):  
Stelian Ioan Morariu ◽  
Letitia Doina Duceac ◽  
Alina Costina Luca ◽  
Florina Popescu ◽  
Liliana Pavel ◽  
...  
Keyword(s):  
Health Care Professionals ◽  
Scientific Progress ◽  
Volcanic Eruptions ◽  
Chemical Pollution ◽  
Optimal Parameters ◽  
Chemical Pollutants ◽  
Wide Range ◽  
Health Physician ◽  
Solid Liquid

Maintaining the soil in optimal parameters is vital for mankind, given its essential role in providing the alimentary base, as well as its extremely slow formation and regeneration (hundreds or thousands of years). The direct and indirect pollution of the soil and especially its chemical pollution represent a corollary of other types of pollution, given that it is produced by solid, liquid and gaseous residues. It may be involved in a wide range of diseases (respiratory, cardiovascular, digestive, renal, haematological, osteoarticular, neurological) of allergic, infectious, degenerative or neoplastic nature, from infancy to the old age. Although there are natural causes of soil pollution (e.g. volcanic eruptions), most pollutants come from human activities, which are the most incriminated in its pollution, degradation and erosion at an accelerated pace. The growing concern of all nations for the adoption of measures to limit the chemical pollution of the soil is partially found so far in viable and effective solutions intended to combat soil contamination and degradation and ensure its restoration. Chemical industrialization leads to technical and scientific progress, but at the same time it can develop related pathologies, which means that the role of the occupational health physician is essential in ensuring prophylaxis and the early detection of occupational diseases. Besides that, the role of the pediatrician is equally precious for the detection of specific diseases caused by chemical pollutants to children, because they will develop into adults with pathological stigma.The chemical pollution of the soil is a major challenge for ecologists, given that it is an important risk factor for many types of afflictions. It requires maximum attention from civil society, health care professionals and government institutions. The specialist in occupational medicine, as well as the pediatrician bear an essential responsibility in both, prevention and treatment.

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.

scholarly journals What Is Orientation in Dignitarian Thinking? Self, Other, Time and Space

2020 ◽  
pp. 174387212098228
Author(s):  
Stephen Riley
Keyword(s):  
The Self ◽  
The Other ◽  
Core Area ◽  
Methodological Challenge ◽  
Time And Space ◽  
Normative Discourse ◽  
The Government

Drawing upon Kant’s analysis of the role of intuitions in our orientation towards knowledge, this paper analyses four points of departure in thinking about dignity: self, other, time and space. Each reveals a core area of normative discourse – authenticity in the self, respect for the other, progress through time and authority as the government of space – along with related grounds of resistance to dignity. The paper concludes with a discussion of the methodological challenge presented by our different dignitarian intuitions, in particular the role of universality in testing and cohering our intuitions.

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