The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

NASA Astrophysics Data System (ADS)

Oh, Yun-Yeong; Yun, Seong-Taek; Yu, Soonyoung; Hamm, Se-Yeong

2017-12-01

To identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3 years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors (DFs) were then extracted using DFA for each group; thus, six major factors were extracted. Next, the time-frequency variability of the extracted DFs was examined using multiresolution cross-correlation analysis (MRCCA) with the following steps: 1) major driving forces and their scales in GWL fluctuations were identified by comparing maximum correlation coefficients (rmax) between DFs and the GWL time series and 2) the results were supplemented using the wavelet transformed coherence (WTC) analysis between DFs and the hydrological time series. Finally, relative contributions of six major DFs to the GWL fluctuations could be quantitatively assessed by calculating the effective dynamic efficiency (Def). The characteristics and relevant process of the identified six DFs are: 1) WCG1DF4,1 as an indicative of seasonal agricultural pumping (scales = 64-128 days; rmax = 0.68-0.89; Def ≤ 23.1%); 2) WCG1DF4,4 representing the cycle of regional groundwater recharge (scales = 64-128 days; rmax = 0.98-1.00; Def ≤ 11.1%); 3) WCG2DF4,1 indicating the complex interaction between the episodes of precipitation and direct runoff (scales = 2-8 days; rmax = 0.82-0.91; Def ≤ 35.3%) and seasonal GW-RW interaction (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 14.2%); 4) WCG2DF4,4 reflecting the complex effects of seasonal pervasive pumping and the local recharge

Establishing a direct connection between detrended fluctuation analysis and Fourier analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken

2015-10-01

To understand methodological features of the detrended fluctuation analysis (DFA) using a higher-order polynomial fitting, we establish the direct connection between DFA and Fourier analysis. Based on an exact calculation of the single-frequency response of the DFA, the following facts are shown analytically: (1) in the analysis of stochastic processes exhibiting a power-law scaling of the power spectral density (PSD), S (f ) ˜f-β , a higher-order detrending in the DFA has no adverse effect in the estimation of the DFA scaling exponent α , which satisfies the scaling relation α =(β +1 )/2 ; (2) the upper limit of the scaling exponents detectable by the DFA depends on the order of polynomial fit used in the DFA, and is bounded by m +1 , where m is the order of the polynomial fit; (3) the relation between the time scale in the DFA and the corresponding frequency in the PSD are distorted depending on both the order of the DFA and the frequency dependence of the PSD. We can improve the scale distortion by introducing the corrected time scale in the DFA corresponding to the inverse of the frequency scale in the PSD. In addition, our analytical approach makes it possible to characterize variants of the DFA using different types of detrending. As an application, properties of the detrending moving average algorithm are discussed.

76 FR 60094 - DFA Investment Dimensions Group Inc., et al.; Notice of Application

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-28

... SECURITIES AND EXCHANGE COMMISSION [Investment Company Act Release No. 29820; File No. 812-13943] DFA Investment Dimensions Group Inc., et al.; Notice of Application September 22, 2011. AGENCY... the Investment Company Act of 1940 (``Act'') for an exemption from rule 12d1-2(a) under the Act...

Identification of mongoose (genus: Herpestes) species from hair through band pattern studies using discriminate functional analysis (DFA) and microscopic examination.

PubMed

Sahajpal, Vivek; Goyal, S P; Raza, R; Jayapal, R

2009-09-01

India is home to seven species of mongoose (Herpestes sp). Mongooses are being poached primarily for their hair, which is used in the production of painting and shaving brushes. Prior to September 2002, mongooses were listed under Schedule-IV of the Wildlife (Protection) Act 1972 (India). Indiscriminate poaching of the mongoose created an immediate threat to their survival and hence mongooses have now been placed under Schedule-II of the Wildlife (Protection) Act-1972 (India). In order to convict a person under this legislation, species identification of case related samples is necessary. Four species of mongoose i.e. H. edwardsii, H. smithii, H. palustris and H. urva were characterised by performing discriminate functional analysis (DFA) on measurements of their dorsal guard hair banding pattern and by microscopic hair characteristics (Cuticular, medullar and cross section). It was possible to distinguish between the four species studied, based on both these methods.

Backward assembly planning with DFA analysis

NASA Technical Reports Server (NTRS)

Lee, Sukhan (Inventor)

1995-01-01

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies, and analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans is presented. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc. that must occur during the assembly, and handles nonreversible as well as reversible assembly tasks through backward assembly planning. In order to increase the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Backward assembly planning with DFA analysis

NASA Technical Reports Server (NTRS)

Lee, Sukhan (Inventor)

1992-01-01

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies is presented. The planning system analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc., that must occur during the assembly. Additionally, the planning handles nonreversible, as well as reversible, assembly tasks through backward assembly planning. In order to decrease the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Difructose Dianhydrides (DFAs) and DFA-Enriched Products as Functional Foods

NASA Astrophysics Data System (ADS)

Mellet, Carmen Ortiz; Fernández, José M. García

This review provides an overview of the current status of the chemistry and biology of di-d-fructose dianhydrides (DFAs) with a focus on their potential as functional foods. The history of this family of cyclic ketodisaccharides has expanded for almost 100 years and offers a paradigmatic example of artificial synthetic molecules that were identified as natural products later on and finally encountered in our own table. Issued from fundamental investigations on the reactivity of carbohydrates in strongly acidic media, DFAs remained laboratory curiosities for decades. Early reports on their isolation from plants raised doubts, until the formation of some DFA representatives by the action of microorganisms on fructans was reported in the middle 1980s. Since then, research on DFAs has run in parallel in the areas of microbiology and carbohydrate chemistry. Evidence of the potential of these compounds as functional food was accumulated from both sides, with the development of biotechnological processes for mass production of selected candidates and of chemical methodologies to prepare DFA-enriched products from sucrose or inulin. In 1994 a decisive discovery in the field took place in the laboratory of Jacques Defaye in Grenoble, France: the presence of DFAs in a commercial sucrose caramel was evidenced in a quite significant 18% mass proportion! The development of an efficient analytical protocol for DFAs and the stereoselective synthesis of individual standards allowed one to demonstrate that DFAs and their glycosylated derivatives (glycosyl-DFAs) are universally formed during caramelization reactions. They are not potential food products; they have actually always been in our daily food. Most important, they seem to exert beneficial effects: they are acariogenic, low-caloric, and promote the growth of beneficial microflora in the gut.

A Framework for the Development of Automatic DFA Method to Minimize the Number of Components and Assembly Reorientations

NASA Astrophysics Data System (ADS)

Alfadhlani; Samadhi, T. M. A. Ari; Ma’ruf, Anas; Setiasyah Toha, Isa

2018-03-01

Assembly is a part of manufacturing processes that must be considered at the product design stage. Design for Assembly (DFA) is a method to evaluate product design in order to make it simpler, easier and quicker to assemble, so that assembly cost is reduced. This article discusses a framework for developing a computer-based DFA method. The method is expected to aid product designer to extract data, evaluate assembly process, and provide recommendation for the product design improvement. These three things are desirable to be performed without interactive process or user intervention, so product design evaluation process could be done automatically. Input for the proposed framework is a 3D solid engineering drawing. Product design evaluation is performed by: minimizing the number of components; generating assembly sequence alternatives; selecting the best assembly sequence based on the minimum number of assembly reorientations; and providing suggestion for design improvement.

Multifractal property of Chinese stock market in the CSI 800 index based on MF-DFA approach

NASA Astrophysics Data System (ADS)

Zhu, Huijian; Zhang, Weiguo

2018-01-01

CSI 800 index consists of CSI 500 index and CSI 300 index, aiming to reflect the performance of stocks with large, mid and small size of China A share market. In this paper we analyze the multifractal structure of Chinese stock market in the CSI 800 index based on the multifractal detrended fluctuation analysis (MF-DFA) method. We find that the fluctuation of the closing logarithmic returns have multifractal properties, the shape and width of multifractal spectrum are depended on the weighing order q. More interestingly, we observe a bigger market crash in June-August 2015 than the one in 2008 based on the local Hurst exponents. The result provides important information for further study on dynamic mechanism of return fluctuation and whether it would trigger a new financial crisis.

Discriminant function analysis as tool for subsurface geologist

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chesser, K.

1987-05-01

Sedimentary structures such as cross-bedding control porosity, permeability, and other petrophysical properties in sandstone reservoirs. Understanding the distribution of such structures in the subsurface not only aids in the prediction of reservoir properties but also provides information about depositional environments. Discriminant function analysis (DFA) is a simple yet powerful method incorporating petrophysical data from wireline logs, core analyses, or other sources into groups that have been previously defined through direct observation of sedimentary structures in cores. Once data have been classified into meaningful groups, the geologist can predict the distribution of specific sedimentary structures or important reservoir properties in areasmore » where cores are unavailable. DFA is efficient. Given several variables, DFA will choose the best combination to discriminate among groups. The initial classification function can be computed from relatively few observations, and additional data may be included as necessary. Furthermore, DFA provides quantitative goodness-of-fit estimates for each observation. Such estimates can be used as mapping parameters or to assess risk in petroleum ventures. Petrophysical data from the Skinner sandstone of Strauss field in southeastern Kansas tested the ability of DFA to discriminate between cross-bedded and ripple-bedded sandstones. Petroleum production in Strauss field is largely restricted to the more permeable cross-bedded sandstones. DFA based on permeability correctly placed 80% of samples into cross-bedded or ripple-bedded groups. Addition of formation factor to the discriminant function increased correct classifications to 83% - a small but statistically significant gain.« less

Detrended Fluctuation Analysis of Heart Rate Dynamics Is an Important Prognostic Factor in Patients with End-Stage Renal Disease Receiving Peritoneal Dialysis

PubMed Central

Lin, Lian-Yu; Chang, Chin-Hao; Chu, Fang-Ying; Lin, Yen-Hung; Wu, Cho-Kai; Lee, Jen-Kuang; Hwang, Juei-Jen; Lin, Jiunn-Lee; Chiang, Fu-Tien

2016-01-01

Background and Objectives Patients with severe kidney function impairment often have autonomic dysfunction, which could be evaluated noninvasively by heart rate variability (HRV) analysis. Nonlinear HRV parameters such as detrended fluctuation analysis (DFA) has been demonstrated to be an important outcome predictor in patients with cardiovascular diseases. Whether cardiac autonomic dysfunction measured by DFA is also a useful prognostic factor in patients with end-stage renal disease (ESRD) receiving peritoneal dialysis (PD) remains unclear. The purpose of the present study was designed to test the hypothesis. Materials and Methods Patients with ESRD receiving PD were included for the study. Twenty-four hour Holter monitor was obtained from each patient together with other important traditional prognostic makers such as underlying diseases, left ventricular ejection fraction (LVEF) and serum biochemistry profiles. Short-term (DFAα1) and long-term (DFAα2) DFA as well as other linear HRV parameters were calculated. Results A total of 132 patients (62 men, 72 women) with a mean age of 53.7±12.5 years were recruited from July 2007 to March 2009. During a median follow-up period of around 34 months, eight cardiac and six non-cardiac deaths were observed. Competing risk analysis demonstrated that decreased DFAα1 was a strong prognostic predictor for increased cardiac and total mortality. ROC analysis showed that the AUC of DFAα1 (<0.95) to predict mortality was 0.761 (95% confidence interval (CI). = 0.617–0.905). DFAα1≧ 0.95 was associated with lower cardiac mortality (Hazard ratio (HR) 0.062, 95% CI = 0.007–0.571, P = 0.014) and total mortality (HR = 0.109, 95% CI = 0.033–0.362, P = 0.0003). Conclusion Cardiac autonomic dysfunction evaluated by DFAα1 is an independent predictor for cardiac and total mortality in patients with ESRD receiving PD. PMID:26828209

Factors influencing food choices of food-allergic consumers: findings from focus groups.

PubMed

Sommer, I; Mackenzie, H; Venter, C; Dean, T

2012-10-01

Up to 35% of the population modify their diet for adverse reactions to food. This study described the food choice behaviour of diagnosed food-allergic (DFA), self-reported food-allergic or intolerant (SFA) and nonfood-allergic (NFA) consumers, and explored differences between them. Six focus groups with adults (n = 44) were conducted. Data analysis was performed using thematic content analysis. Compared to NFA participants, DFA consumers were deprived of satisfaction and pleasure from foods, experienced difficulties finding safe foods and had to be organized with eating. SFA participants faced similar problems, but to a lesser degree; their food choices were strongly influenced by emotional factors or health awareness. Food-allergic consumers' food choices are influenced by a number of factors that differ to those of NFA consumers. It is therefore important to offer people with food allergies or intolerances advice that goes beyond how to avoid allergens. © 2012 John Wiley & Sons A/S.

AR(p) -based detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, J.; Rodriguez, E.

2018-07-01

Autoregressive models are commonly used for modeling time-series from nature, economics and finance. This work explored simple autoregressive AR(p) models to remove long-term trends in detrended fluctuation analysis (DFA). Crude oil prices and bitcoin exchange rate were considered, with the former corresponding to a mature market and the latter to an emergent market. Results showed that AR(p) -based DFA performs similar to traditional DFA. However, the former DFA provides information on stability of long-term trends, which is valuable for understanding and quantifying the dynamics of complex time series from financial systems.

Nonlinear filtering properties of detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken; Tsujimoto, Yutaka

2016-11-01

Detrended fluctuation analysis (DFA) has been widely used for quantifying long-range correlation and fractal scaling behavior. In DFA, to avoid spurious detection of scaling behavior caused by a nonstationary trend embedded in the analyzed time series, a detrending procedure using piecewise least-squares fitting has been applied. However, it has been pointed out that the nonlinear filtering properties involved with detrending may induce instabilities in the scaling exponent estimation. To understand this issue, we investigate the adverse effects of the DFA detrending procedure on the statistical estimation. We show that the detrending procedure using piecewise least-squares fitting results in the nonuniformly weighted estimation of the root-mean-square deviation and that this property could induce an increase in the estimation error. In addition, for comparison purposes, we investigate the performance of a centered detrending moving average analysis with a linear detrending filter and sliding window DFA and show that these methods have better performance than the standard DFA.

Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Chen, Shu-Peng

2010-08-01

In this article, we investigated the multifractality and its underlying formation mechanisms in international crude oil markets, namely, Brent and WTI, which are the most important oil pricing benchmarks globally. We attempt to find the answers to the following questions: (1) Are those different markets multifractal? (2) What are the dynamical causes for multifractality in those markets (if any)? To answer these questions, we applied both multifractal detrended fluctuation analysis (MF-DFA) and multifractal singular spectrum analysis (MF-SSA) based on the partition function, two widely used multifractality detecting methods. We found that both markets exhibit multifractal properties by means of these methods. Furthermore, in order to identify the underlying formation mechanisms of multifractal features, we destroyed the underlying nonlinear temporal correlation by shuffling the original time series; thus, we identified that the causes of the multifractality are influenced mainly by a nonlinear temporal correlation mechanism instead of a non-Gaussian distribution. At last, by tracking the evolution of left- and right-half multifractal spectra, we found that the dynamics of the large price fluctuations is significantly different from that of the small ones. Our main contribution is that we not only provided empirical evidence of the existence of multifractality in the markets, but also the sources of multifractality and plausible explanations to current literature; furthermore, we investigated the different dynamical price behaviors influenced by large and small price fluctuations.

Dynamic factor analysis of long-term growth trends of the intertidal seagrass Thalassia hemprichii in southern Taiwan

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Lin, Hsing-Juh

2010-01-01

We examined environmental factors which are most responsible for the 8-year temporal dynamics of the intertidal seagrass Thalassia hemprichii in southern Taiwan. A dynamic factor analysis (DFA), a dimension-reduction technique, was applied to identify common trends in a multivariate time series and the relationships between this series and interacting environmental variables. The results of dynamic factor models (DFMs) showed that the leaf growth rate of the seagrass was mainly influenced by salinity (Sal), tidal range (TR), turbidity ( K), and a common trend representing an unexplained variability in the observed time series. Sal was the primary variable that explained the temporal dynamics of the leaf growth rate compared to TR and K. K and TR had larger influences on the leaf growth rate in low- than in high-elevation beds. In addition to K, TR, and Sal, UV-B radiation (UV-B), sediment depth (SD), and a common trend accounted for long-term temporal variations of the above-ground biomass. Thus, K, TR, Sal, UV-B, and SD are the predominant environmental variables that described temporal growth variations of the intertidal seagrass T. hemprichii in southern Taiwan. In addition to environmental variables, human activities may be contributing to negative impacts on the seagrass beds; this human interference may have been responsible for the unexplained common trend in the DFMs. Due to successfully applying the DFA to analyze complicated ecological and environmental data in this study, important environmental variables and impacts of human activities along the coast should be taken into account when managing a coastal environment for the conservation of intertidal seagrass beds.

Detrended Fluctuation Analysis: A Scale-Free View on Neuronal Oscillations

PubMed Central

Hardstone, Richard; Poil, Simon-Shlomo; Schiavone, Giuseppina; Jansen, Rick; Nikulin, Vadim V.; Mansvelder, Huibert D.; Linkenkaer-Hansen, Klaus

2012-01-01

Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT) and links to the NBT tutorial website http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations. PMID:23226132

Prognostic factors of Pneumocystis jirovecii pneumonia in patients without HIV infection.

PubMed

Kim, Soo Jung; Lee, Jinwoo; Cho, Young-Jae; Park, Young Sik; Lee, Chang-Hoon; Yoon, Ho Il; Lee, Sang-Min; Yim, Jae-Joon; Lee, Jae Ho; Yoo, Chul-Gyu; Lee, Choon-Taek; Kim, Young Whan; Han, Sung Koo; Kim, Hong Bin; Park, Jong Sun

2014-07-01

The incidence of Pneumocystis jirovecii pneumonia (PCP) in patients without HIV infection (non-HIV PCP) has been increasing along with the increased use of chemotherapeutic agents and immunosuppressants, but the prognostic factors of non-HIV PCP remain unclear. This study aimed to identify the prognostic factors of non-HIV PCP. Immunocompromised patients without HIV infection who were diagnosed and treated for PCP were included. The PCP diagnosis was based on positive direct fluorescent antibody (DFA) or polymerase chain reaction (PCR) results and compatible clinical symptoms and radiological findings. In total, 372 non-HIV patients with positive PCP DFA or PCR findings were screened and 173 were included. Univariate analysis indicated that age, smoking, chronic lung disease or hematologic malignancy, chemotherapeutic agents, high alveolar-arterial oxygen gradient (D[A-a]O2), C-reactive protein, albumin, blood urea nitrogen (BUN), CMV antigenemia, combined bacteremia, high percentage of neutrophils and rate of co-infection in BAL fluid, and mechanical ventilator care were related to the prognosis of non-HIV PCP. Multivariate analysis revealed that high D(A-a)O2, combined bacteremia, increased BUN and preexisting lung disease were indicators of a poor prognosis. High D(A-a)O2, combined bacteremia, increased BUN and preexisting lung disease were independent factors of poor prognosis in non-HIV PCP patients. Copyright © 2014 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Microhabitat analysis using radiotelemetry locations and polytomous logistic regression

Treesearch

Malcolm P. North; Joel H. Reynolds

1996-01-01

Microhabitat analyses often use discriminant function analysis (DFA) to compare vegetation structures or environmental conditions between sites classified by a study animal's presence or absence. These presence/absence studies make questionable assumptions about the habitat value of the comparison sites and the microhabitat data often violate the DFA's...

Time Correlations of Lightning Flash Sequences in Thunderstorms Revealed by Fractal Analysis

NASA Astrophysics Data System (ADS)

Gou, Xueqiang; Chen, Mingli; Zhang, Guangshu

2018-01-01

By using the data of lightning detection and ranging system at the Kennedy Space Center, the temporal fractal and correlation of interevent time series of lightning flash sequences in thunderstorms have been investigated with Allan factor (AF), Fano factor (FF), and detrended fluctuation analysis (DFA) methods. AF, FF, and DFA methods are powerful tools to detect the time-scaling structures and correlations in point processes. Totally 40 thunderstorms with distinguishing features of a single-cell storm and apparent increase and decrease in the total flash rate were selected for the analysis. It is found that the time-scaling exponents for AF (αAF) and FF (αFF) analyses are 1.62 and 0.95 in average, respectively, indicating a strong time correlation of the lightning flash sequences. DFA analysis shows that there is a crossover phenomenon—a crossover timescale (τc) ranging from 54 to 195 s with an average of 114 s. The occurrence of a lightning flash in a thunderstorm behaves randomly at timescales <τc but shows strong time correlation at scales >τc. Physically, these may imply that the establishment of an extensive strong electric field necessary for the occurrence of a lightning flash needs a timescale >τc, which behaves strongly time correlated. But the initiation of a lightning flash within a well-established extensive strong electric field may involve the heterogeneities of the electric field at a timescale <τc, which behave randomly.

Language time series analysis

NASA Astrophysics Data System (ADS)

Kosmidis, Kosmas; Kalampokis, Alkiviadis; Argyrakis, Panos

2006-10-01

We use the detrended fluctuation analysis (DFA) and the Grassberger-Proccacia analysis (GP) methods in order to study language characteristics. Despite that we construct our signals using only word lengths or word frequencies, excluding in this way huge amount of information from language, the application of GP analysis indicates that linguistic signals may be considered as the manifestation of a complex system of high dimensionality, different from random signals or systems of low dimensionality such as the Earth climate. The DFA method is additionally able to distinguish a natural language signal from a computer code signal. This last result may be useful in the field of cryptography.

Multichannel Detrended Fluctuation Analysis Reveals Synchronized Patterns of Spontaneous Spinal Activity in Anesthetized Cats

PubMed Central

Rodríguez, Erika E.; Hernández-Lemus, Enrique; Itzá-Ortiz, Benjamín A.; Jiménez, Ismael; Rudomín, Pablo

2011-01-01

The analysis of the interaction and synchronization of relatively large ensembles of neurons is fundamental for the understanding of complex functions of the nervous system. It is known that the temporal synchronization of neural ensembles is involved in the generation of specific motor, sensory or cognitive processes. Also, the intersegmental coherence of spinal spontaneous activity may indicate the existence of synaptic neural pathways between different pairs of lumbar segments. In this study we present a multichannel version of the detrended fluctuation analysis method (mDFA) to analyze the correlation dynamics of spontaneous spinal activity (SSA) from time series analysis. This method together with the classical detrended fluctuation analysis (DFA) were used to find out whether the SSA recorded in one or several segments in the spinal cord of the anesthetized cat occurs either in a random or in an organized manner. Our results are consistent with a non-random organization of the sets of neurons involved in the generation of spontaneous cord dorsum potentials (CDPs) recorded either from one lumbar segment (DFA- mean = 1.040.09) or simultaneously from several lumbar segments (mDFA- mean = 1.010.06), where  = 0.5 indicates randomness while 0.5 indicates long-term correlations. To test the sensitivity of the mDFA method we also examined the effects of small spinal lesions aimed to partially interrupt connectivity between neighboring lumbosacral segments. We found that the synchronization and correlation between the CDPs recorded from the L5 and L6 segments in both sides of the spinal cord were reduced when a lesion comprising the left dorsal quadrant was performed between the segments L5 and L6 (mDFA- = 0.992 as compared to initial conditions mDFA- = 1.186). The synchronization and correlation were reduced even further after a similar additional right spinal lesion (mDFA- = 0.924). In contrast to the classical methods, such as correlation

Detrended fluctuation analysis based on higher-order moments of financial time series

NASA Astrophysics Data System (ADS)

Teng, Yue; Shang, Pengjian

2018-01-01

In this paper, a generalized method of detrended fluctuation analysis (DFA) is proposed as a new measure to assess the complexity of a complex dynamical system such as stock market. We extend DFA and local scaling DFA to higher moments such as skewness and kurtosis (labeled SMDFA and KMDFA), so as to investigate the volatility scaling property of financial time series. Simulations are conducted over synthetic and financial data for providing the comparative study. We further report the results of volatility behaviors in three American countries, three Chinese and three European stock markets by using DFA and LSDFA method based on higher moments. They demonstrate the dynamics behaviors of time series in different aspects, which can quantify the changes of complexity for stock market data and provide us with more meaningful information than single exponent. And the results reveal some higher moments volatility and higher moments multiscale volatility details that cannot be obtained using the traditional DFA method.

Scaling analysis of stock markets

NASA Astrophysics Data System (ADS)

Bu, Luping; Shang, Pengjian

2014-06-01

In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis.

Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition

PubMed Central

Thomas, Felicity; Signal, Matthew; Chase, J. Geoffrey

2015-01-01

Patients admitted to critical care often experience dysglycemia and high levels of insulin resistance, various intensive insulin therapy protocols and methods have attempted to safely normalize blood glucose (BG) levels. Continuous glucose monitoring (CGM) devices allow glycemic dynamics to be captured much more frequently (every 2-5 minutes) than traditional measures of blood glucose and have begun to be used in critical care patients and neonates to help monitor dysglycemia. In an attempt to obtain a better insight relating biomedical signals and patient status, some researchers have turned toward advanced time series analysis methods. In particular, Detrended Fluctuation Analysis (DFA) has been a topic of many recent studies in to glycemic dynamics. DFA investigates the “complexity” of a signal, how one point in time changes relative to its neighboring points, and DFA has been applied to signals like the inter-beat-interval of human heartbeat to differentiate healthy and pathological conditions. Analyzing the glucose metabolic system with such signal processing tools as DFA has been enabled by the emergence of high quality CGM devices. However, there are several inconsistencies within the published work applying DFA to CGM signals. Therefore, this article presents a review and a “how-to” tutorial of DFA, and in particular its application to CGM signals to ensure the methods used to determine complexity are used correctly and so that any relationship between complexity and patient outcome is robust. PMID:26134835

Analyzing psychotherapy process as intersubjective sensemaking: an approach based on discourse analysis and neural networks.

PubMed

Nitti, Mariangela; Ciavolino, Enrico; Salvatore, Sergio; Gennaro, Alessandro

2010-09-01

The authors propose a method for analyzing the psychotherapy process: discourse flow analysis (DFA). DFA is a technique representing the verbal interaction between therapist and patient as a discourse network, aimed at measuring the therapist-patient discourse ability to generate new meanings through time. DFA assumes that the main function of psychotherapy is to produce semiotic novelty. DFA is applied to the verbatim transcript of the psychotherapy. It defines the main meanings active within the therapeutic discourse by means of the combined use of text analysis and statistical techniques. Subsequently, it represents the dynamic interconnections among these meanings in terms of a "discursive network." The dynamic and structural indexes of the discursive network have been shown to provide a valid representation of the patient-therapist communicative flow as well as an estimation of its clinical quality. Finally, a neural network is designed specifically to identify patterns of functioning of the discursive network and to verify the clinical validity of these patterns in terms of their association with specific phases of the psychotherapy process. An application of the DFA to a case of psychotherapy is provided to illustrate the method and the kinds of results it produces.

A dynamic factor model of the evaluation of the financial crisis in Turkey.

PubMed

Sezgin, F; Kinay, B

2010-01-01

Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

Characterizing Detrended Fluctuation Analysis of multifractional Brownian motion

NASA Astrophysics Data System (ADS)

Setty, V. A.; Sharma, A. S.

2015-02-01

The Hurst exponent (H) is widely used to quantify long range dependence in time series data and is estimated using several well known techniques. Recognizing its ability to remove trends the Detrended Fluctuation Analysis (DFA) is used extensively to estimate a Hurst exponent in non-stationary data. Multifractional Brownian motion (mBm) broadly encompasses a set of models of non-stationary data exhibiting time varying Hurst exponents, H(t) as against a constant H. Recently, there has been a growing interest in time dependence of H(t) and sliding window techniques have been used to estimate a local time average of the exponent. This brought to fore the ability of DFA to estimate scaling exponents in systems with time varying H(t) , such as mBm. This paper characterizes the performance of DFA on mBm data with linearly varying H(t) and further test the robustness of estimated time average with respect to data and technique related parameters. Our results serve as a bench-mark for using DFA as a sliding window estimator to obtain H(t) from time series data.

Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

PubMed Central

Signal, Matthew; Thomas, Felicity; Shaw, Geoffrey M.; Chase, J. Geoffrey

2013-01-01

Background Critically ill patients often experience high levels of insulin resistance and stress-induced hyperglycemia, which may negatively impact outcomes. However, evidence surrounding the causes of negative outcomes remains inconclusive. Continuous glucose monitoring (CGM) devices allow researchers to investigate glucose complexity, using detrended fluctuation analysis (DFA), to determine whether it is associated with negative outcomes. The aim of this study was to investigate the effects of CGM device type/calibration and CGM sensor location on results from DFA. Methods This study uses CGM data from critically ill patients who were each monitored concurrently using Medtronic iPro2s on the thigh and abdomen and a Medtronic Guardian REAL-Time on the abdomen. This allowed interdevice/calibration type and intersensor site variation to be assessed. Detrended fluctuation analysis is a technique that has previously been used to determine the complexity of CGM data in critically ill patients. Two variants of DFA, monofractal and multifractal, were used to assess the complexity of sensor glucose data as well as the precalibration raw sensor current. Monofractal DFA produces a scaling exponent (H), where H is inversely related to complexity. The results of multifractal DFA are presented graphically by the multifractal spectrum. Results From the 10 patients recruited, 26 CGM devices produced data suitable for analysis. The values of H from abdominal iPro2 data were 0.10 (0.03–0.20) higher than those from Guardian REAL-Time data, indicating consistently lower complexities in iPro2 data. However, repeating the analysis on the raw sensor current showed little or no difference in complexity. Sensor site had little effect on the scaling exponents in this data set. Finally, multifractal DFA revealed no significant associations between the multifractal spectrums and CGM device type/calibration or sensor location. Conclusions Monofractal DFA results are dependent on the device

Evenly spaced Detrended Fluctuation Analysis: Selecting the number of points for the diffusion plot

NASA Astrophysics Data System (ADS)

Liddy, Joshua J.; Haddad, Jeffrey M.

2018-02-01

Detrended Fluctuation Analysis (DFA) has become a widely-used tool to examine the correlation structure of a time series and provided insights into neuromuscular health and disease states. As the popularity of utilizing DFA in the human behavioral sciences has grown, understanding its limitations and how to properly determine parameters is becoming increasingly important. DFA examines the correlation structure of variability in a time series by computing α, the slope of the log SD- log n diffusion plot. When using the traditional DFA algorithm, the timescales, n, are often selected as a set of integers between a minimum and maximum length based on the number of data points in the time series. This produces non-uniformly distributed values of n in logarithmic scale, which influences the estimation of α due to a disproportionate weighting of the long-timescale regions of the diffusion plot. Recently, the evenly spaced DFA and evenly spaced average DFA algorithms were introduced. Both algorithms compute α by selecting k points for the diffusion plot based on the minimum and maximum timescales of interest and improve the consistency of α estimates for simulated fractional Gaussian noise and fractional Brownian motion time series. Two issues that remain unaddressed are (1) how to select k and (2) whether the evenly-spaced DFA algorithms show similar benefits when assessing human behavioral data. We manipulated k and examined its effects on the accuracy, consistency, and confidence limits of α in simulated and experimental time series. We demonstrate that the accuracy and consistency of α are relatively unaffected by the selection of k. However, the confidence limits of α narrow as k increases, dramatically reducing measurement uncertainty for single trials. We provide guidelines for selecting k and discuss potential uses of the evenly spaced DFA algorithms when assessing human behavioral data.

Analysis of launch site processing effectiveness for the Space Shuttle 26R payload

NASA Technical Reports Server (NTRS)

Flores, Carlos A.; Heuser, Robert E.; Pepper, Richard E., Jr.; Smith, Anthony M.

1991-01-01

A trend analysis study has been performed on problem reports recorded during the Space Shuttle 26R payload's processing cycle at NASA-Kennedy, using the defect-flow analysis (DFA) methodology; DFA gives attention to the characteristics of the problem-report 'population' as a whole. It is established that the problem reports contain data which distract from pressing problems, and that fully 60 percent of such reports were caused during processing at NASA-Kennedy. The second major cause of problem reports was design defects.

Detrended fluctuation analysis for major depressive disorder.

PubMed

Mumtaz, Wajid; Malik, Aamir Saeed; Ali, Syed Saad Azhar; Yasin, Mohd Azhar Mohd; Amin, Hafeezullah

2015-01-01

Clinical utility of Electroencephalography (EEG) based diagnostic studies is less clear for major depressive disorder (MDD). In this paper, a novel machine learning (ML) scheme was presented to discriminate the MDD patients and healthy controls. The proposed method inherently involved feature extraction, selection, classification and validation. The EEG data acquisition involved eyes closed (EC) and eyes open (EO) conditions. At feature extraction stage, the de-trended fluctuation analysis (DFA) was performed, based on the EEG data, to achieve scaling exponents. The DFA was performed to analyzes the presence or absence of long-range temporal correlations (LRTC) in the recorded EEG data. The scaling exponents were used as input features to our proposed system. At feature selection stage, 3 different techniques were used for comparison purposes. Logistic regression (LR) classifier was employed. The method was validated by a 10-fold cross-validation. As results, we have observed that the effect of 3 different reference montages on the computed features. The proposed method employed 3 different types of feature selection techniques for comparison purposes as well. The results show that the DFA analysis performed better in LE data compared with the IR and AR data. In addition, during Wilcoxon ranking, the AR performed better than LE and IR. Based on the results, it was concluded that the DFA provided useful information to discriminate the MDD patients and with further validation can be employed in clinics for diagnosis of MDD.

Detrended fluctuation analysis of non-stationary cardiac beat-to-beat interval of sick infants

NASA Astrophysics Data System (ADS)

Govindan, Rathinaswamy B.; Massaro, An N.; Al-Shargabi, Tareq; Niforatos Andescavage, Nickie; Chang, Taeun; Glass, Penny; du Plessis, Adre J.

2014-11-01

We performed detrended fluctuation analysis (DFA) of cardiac beat-to-beat intervals (RRis) collected from sick newborn infants over 1-4 day periods. We calculated four different metrics from the DFA fluctuation function: the DFA exponents αL (>40 beats up to one-fourth of the record length), αs (15-30 beats), root-mean-square (RMS) fluctuation on a short-time scale (20-50 beats), and RMS fluctuation on a long-time scale (110-150 beats). Except αL , all metrics clearly distinguished two groups of newborn infants (favourable vs. adverse) with well-characterized outcomes. However, the RMS fluctuations distinguished the two groups more consistently over time compared to αS . Furthermore, RMS distinguished the RRi of the two groups earlier compared to the DFA exponent. In all the three measures, the favourable outcome group displayed higher values, indicating a higher magnitude of (auto-)correlation and variability, thus normal physiology, compared to the adverse outcome group.

Influence of Sub-Daily Variation on Multi-Fractal Detrended Fluctuation Analysis of Wind Speed Time Series

PubMed Central

Li, Weinan; Kong, Yanjun; Cong, Xiangyu

2016-01-01

Using multi-fractal detrended fluctuation analysis (MF-DFA), the scaling features of wind speed time series (WSTS) could be explored. In this paper, we discuss the influence of sub-daily variation, which is a natural feature of wind, in MF-DFA of WSTS. First, the choice of the lower bound of the segment length, a significant parameter of MF-DFA, was studied. The results of expanding the lower bound into sub-daily scope shows that an abrupt declination and discrepancy of scaling exponents is caused by the inability to keep the whole diel process of wind in one single segment. Additionally, the specific value, which is effected by the sub-daily feature of local meteo-climatic, might be different. Second, the intra-day temporal order of wind was shuffled to determine the impact of diel variation on scaling exponents of MF-DFA. The results illustrate that disregarding diel variation leads to errors in scaling. We propose that during the MF-DFA of WSTS, the segment length should be longer than 1 day and the diel variation of wind should be maintained to avoid abnormal phenomena and discrepancy in scaling exponents. PMID:26741491

Fractal scaling analysis of groundwater dynamics in confined aquifers

NASA Astrophysics Data System (ADS)

Tu, Tongbi; Ercan, Ali; Kavvas, M. Levent

2017-10-01

Groundwater closely interacts with surface water and even climate systems in most hydroclimatic settings. Fractal scaling analysis of groundwater dynamics is of significance in modeling hydrological processes by considering potential temporal long-range dependence and scaling crossovers in the groundwater level fluctuations. In this study, it is demonstrated that the groundwater level fluctuations in confined aquifer wells with long observations exhibit site-specific fractal scaling behavior. Detrended fluctuation analysis (DFA) was utilized to quantify the monofractality, and multifractal detrended fluctuation analysis (MF-DFA) and multiscale multifractal analysis (MMA) were employed to examine the multifractal behavior. The DFA results indicated that fractals exist in groundwater level time series, and it was shown that the estimated Hurst exponent is closely dependent on the length and specific time interval of the time series. The MF-DFA and MMA analyses showed that different levels of multifractality exist, which may be partially due to a broad probability density distribution with infinite moments. Furthermore, it is demonstrated that the underlying distribution of groundwater level fluctuations exhibits either non-Gaussian characteristics, which may be fitted by the Lévy stable distribution, or Gaussian characteristics depending on the site characteristics. However, fractional Brownian motion (fBm), which has been identified as an appropriate model to characterize groundwater level fluctuation, is Gaussian with finite moments. Therefore, fBm may be inadequate for the description of physical processes with infinite moments, such as the groundwater level fluctuations in this study. It is concluded that there is a need for generalized governing equations of groundwater flow processes that can model both the long-memory behavior and the Brownian finite-memory behavior.

Glucose time series complexity as a predictor of type 2 diabetes

PubMed Central

Rodríguez de Castro, Carmen; Vargas, Borja; García Delgado, Emilio; García Carretero, Rafael; Ruiz‐Galiana, Julián; Varela, Manuel

2016-01-01

Abstract Background Complexity analysis of glucose profile may provide valuable information about the gluco‐regulatory system. We hypothesized that a complexity metric (detrended fluctuation analysis, DFA) may have a prognostic value for the development of type 2 diabetes in patients at risk. Methods A total of 206 patients with any of the following risk factors (1) essential hypertension, (2) obesity or (3) a first‐degree relative with a diagnosis of diabetes were included in a survival analysis study for a diagnosis of new onset type 2 diabetes. At inclusion, a glucometry by means of a Continuous Glucose Monitoring System was performed, and DFA was calculated for a 24‐h glucose time series. Patients were then followed up every 6 months, controlling for the development of diabetes. Results In a median follow‐up of 18 months, there were 18 new cases of diabetes (58.5 cases/1000 patient‐years). DFA was a significant predictor for the development of diabetes, with ten events in the highest quartile versus one in the lowest (log‐rank test chi2 = 9, df = 1, p = 0.003), even after adjusting for other relevant clinical and biochemical variables. In a Cox model, the risk of diabetes development increased 2.8 times for every 0.1 DFA units. In a multivariate analysis, only fasting glucose, HbA1c and DFA emerged as significant factors. Conclusions Detrended fluctuation analysis significantly performed as a harbinger of type 2 diabetes development in a high‐risk population. Complexity analysis may help in targeting patients who could be candidates for intensified treatment. Copyright © 2016 The Authors. Diabetes/Metabolism Research and Reviews Published by John Wiley & Sons Ltd. PMID:27253149

Scaling analysis of the effects of load on hand tremor movements in essential tremor

NASA Astrophysics Data System (ADS)

Blesić, S.; Stratimirović, Dj.; Milošević, S.; Marić, J.; Kostić, V.; Ljubisavljević, M.

2011-05-01

In this paper we have used the Wavelet Transform (WT) and the Detrended Fluctuation Analysis (DFA) methods to analyze hand tremor movements in essential tremor (ET), in two different recording conditions (before and after the addition of wrist-cuff load). We have analyzed the time series comprised of peak-to-peak (PtP) intervals, extracted from regions around the first three main frequency components of the power spectra (PwS) of the recorded tremors, in order to substantiate results related to the effects of load on ET, to distinguish between multiple sources of ET, and to separate the influence of peripheral factors on ET. Our results show that, in ET, the dynamical characteristics, that is, values of respective scaling exponents, of the main frequency component of recorded tremors change after the addition of load. Our results also show that in all the observed cases the scaling behavior of the calculated functions changes as well-the calculated WT scalegrams and DFA functions display a shift in the position of the crossover when the load is added. We conclude that the difference in behavior of the WT and DFA functions between different conditions in ET could be associated with the expected pathology in ET, or with some additional mechanism that controls movements in ET patients, and causes the observed changes in scaling behavior.

Phylogenetic comparative methods complement discriminant function analysis in ecomorphology.

PubMed

Barr, W Andrew; Scott, Robert S

2014-04-01

In ecomorphology, Discriminant Function Analysis (DFA) has been used as evidence for the presence of functional links between morphometric variables and ecological categories. Here we conduct simulations of characters containing phylogenetic signal to explore the performance of DFA under a variety of conditions. Characters were simulated using a phylogeny of extant antelope species from known habitats. Characters were modeled with no biomechanical relationship to the habitat category; the only sources of variation were body mass, phylogenetic signal, or random "noise." DFA on the discriminability of habitat categories was performed using subsets of the simulated characters, and Phylogenetic Generalized Least Squares (PGLS) was performed for each character. Analyses were repeated with randomized habitat assignments. When simulated characters lacked phylogenetic signal and/or habitat assignments were random, <5.6% of DFAs and <8.26% of PGLS analyses were significant. When characters contained phylogenetic signal and actual habitats were used, 33.27 to 45.07% of DFAs and <13.09% of PGLS analyses were significant. False Discovery Rate (FDR) corrections for multiple PGLS analyses reduced the rate of significance to <4.64%. In all cases using actual habitats and characters with phylogenetic signal, correct classification rates of DFAs exceeded random chance. In simulations involving phylogenetic signal in both predictor variables and predicted categories, PGLS with FDR was rarely significant, while DFA often was. In short, DFA offered no indication that differences between categories might be explained by phylogenetic signal, while PGLS did. As such, PGLS provides a valuable tool for testing the functional hypotheses at the heart of ecomorphology. Copyright © 2013 Wiley Periodicals, Inc.

Dynamic factor analysis of groundwater quality trends in an agricultural area adjacent to Everglades National Park.

PubMed

Muñoz-Carpena, R; Ritter, A; Li, Y C

2005-11-01

The extensive eastern boundary of Everglades National Park (ENP) in south Florida (USA) is subject to one of the most expensive and ambitious environmental restoration projects in history. Understanding and predicting the water quality interactions between the shallow aquifer and surface water is a key component in meeting current environmental regulations and fine-tuning ENP wetland restoration while still maintaining flood protection for the adjacent developed areas. Dynamic factor analysis (DFA), a recent technique for the study of multivariate non-stationary time-series, was applied to study fluctuations in groundwater quality in the area. More than two years of hydrological and water quality time series (rainfall; water table depth; and soil, ground and surface water concentrations of N-NO3-, N-NH4+, P-PO4(3-), Total P, F-and Cl-) from a small agricultural watershed adjacent to the ENP were selected for the study. The unexplained variability required for determining the concentration of each chemical in the 16 wells was greatly reduced by including in the analysis some of the observed time series as explanatory variables (rainfall, water table depth, and soil and canal water chemical concentration). DFA results showed that groundwater concentration of three of the agrochemical species studied (N-NO3-, P-PO4(3-)and Total P) were affected by the same explanatory variables (water table depth, enriched topsoil, and occurrence of a leaching rainfall event, in order of decreasing relative importance). This indicates that leaching by rainfall is the main mechanism explaining concentration peaks in groundwater. In the case of N-NH4+, in addition to leaching, groundwater concentration is governed by lateral exchange with canals. F-and Cl- are mainly affected by periods of dilution by rainfall recharge, and by exchange with the canals. The unstructured nature of the common trends found suggests that these are related to the complex spatially and temporally varying land

Dynamic factor analysis of groundwater quality trends in an agricultural area adjacent to Everglades National Park

NASA Astrophysics Data System (ADS)

Muñoz-Carpena, R.; Ritter, A.; Li, Y. C.

2005-11-01

The extensive eastern boundary of Everglades National Park (ENP) in south Florida (USA) is subject to one of the most expensive and ambitious environmental restoration projects in history. Understanding and predicting the water quality interactions between the shallow aquifer and surface water is a key component in meeting current environmental regulations and fine-tuning ENP wetland restoration while still maintaining flood protection for the adjacent developed areas. Dynamic factor analysis (DFA), a recent technique for the study of multivariate non-stationary time-series, was applied to study fluctuations in groundwater quality in the area. More than two years of hydrological and water quality time series (rainfall; water table depth; and soil, ground and surface water concentrations of N-NO 3-, N-NH 4+, P-PO 43-, Total P, F -and Cl -) from a small agricultural watershed adjacent to the ENP were selected for the study. The unexplained variability required for determining the concentration of each chemical in the 16 wells was greatly reduced by including in the analysis some of the observed time series as explanatory variables (rainfall, water table depth, and soil and canal water chemical concentration). DFA results showed that groundwater concentration of three of the agrochemical species studied (N-NO 3-, P-PO 43-and Total P) were affected by the same explanatory variables (water table depth, enriched topsoil, and occurrence of a leaching rainfall event, in order of decreasing relative importance). This indicates that leaching by rainfall is the main mechanism explaining concentration peaks in groundwater. In the case of N-NH 4+, in addition to leaching, groundwater concentration is governed by lateral exchange with canals. F -and Cl - are mainly affected by periods of dilution by rainfall recharge, and by exchange with the canals. The unstructured nature of the common trends found suggests that these are related to the complex spatially and temporally varying

Detrended fluctuation analysis of short datasets: An application to fetal cardiac data

NASA Astrophysics Data System (ADS)

Govindan, R. B.; Wilson, J. D.; Preißl, H.; Eswaran, H.; Campbell, J. Q.; Lowery, C. L.

2007-02-01

Using detrended fluctuation analysis (DFA) we perform scaling analysis of short datasets of length 500-1500 data points. We quantify the long range correlation (exponent α) by computing the mean value of the local exponents αL (in the asymptotic regime). The local exponents are obtained as the (numerical) derivative of the logarithm of the fluctuation function F(s) with respect to the logarithm of the scale factor s:αL=dlog10F(s)/dlog10s. These local exponents display huge variations and complicate the correct quantification of the underlying correlations. We propose the use of the phase randomized surrogate (PRS), which preserves the long range correlations of the original data, to minimize the variations in the local exponents. Using the numerically generated uncorrelated and long range correlated data, we show that performing DFA on several realizations of PRS and estimating αL from the averaged fluctuation functions (of all realizations) can minimize the variations in αL. The application of this approach to the fetal cardiac data (RR intervals) is discussed and we show that there is a statistically significant correlation between α and the gestation age.

Two-Dimensional Matrix Algorithm Using Detrended Fluctuation Analysis to Distinguish Burkitt and Diffuse Large B-Cell Lymphoma

PubMed Central

Yeh, Rong-Guan; Lin, Chung-Wu; Abbod, Maysam F.; Shieh, Jiann-Shing

2012-01-01

A detrended fluctuation analysis (DFA) method is applied to image analysis. The 2-dimensional (2D) DFA algorithms is proposed for recharacterizing images of lymph sections. Due to Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL), there is a significant different 5-year survival rates after multiagent chemotherapy. Therefore, distinguishing the difference between BL and DLBCL is very important. In this study, eighteen BL images were classified as group A, which have one to five cytogenetic changes. Ten BL images were classified as group B, which have more than five cytogenetic changes. Both groups A and B BLs are aggressive lymphomas, which grow very fast and require more intensive chemotherapy. Finally, ten DLBCL images were classified as group C. The short-term correlation exponent α1 values of DFA of groups A, B, and C were 0.370 ± 0.033, 0.382 ± 0.022, and 0.435 ± 0.053, respectively. It was found that α1 value of BL image was significantly lower (P < 0.05) than DLBCL. However, there is no difference between the groups A and B BLs. Hence, it can be concluded that α1 value based on DFA statistics concept can clearly distinguish BL and DLBCL image. PMID:23365623

Wavelets and Multifractal Analysis

DTIC Science & Technology

2004-07-01

distribution unlimited 13. SUPPLEMENTARY NOTES See also ADM001750, Wavelets and Multifractal Analysis (WAMA) Workshop held on 19-31 July 2004., The original...f)] . . . 16 2.5.4 Detrended Fluctuation Analysis [DFA(m)] . . . . . . . . . . . . . . . 17 2.6 Scale-Independent Measures...18 2.6.1 Detrended -Fluctuation- Analysis Power-Law Exponent (αD) . . . . . . 18 2.6.2 Wavelet-Transform Power-Law Exponent

Fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis and Mahalanobis distance criterion

NASA Astrophysics Data System (ADS)

Lin, Jinshan; Chen, Qian

2013-07-01

Vibration data of faulty rolling bearings are usually nonstationary and nonlinear, and contain fairly weak fault features. As a result, feature extraction of rolling bearing fault data is always an intractable problem and has attracted considerable attention for a long time. This paper introduces multifractal detrended fluctuation analysis (MF-DFA) to analyze bearing vibration data and proposes a novel method for fault diagnosis of rolling bearings based on MF-DFA and Mahalanobis distance criterion (MDC). MF-DFA, an extension of monofractal DFA, is a powerful tool for uncovering the nonlinear dynamical characteristics buried in nonstationary time series and can capture minor changes of complex system conditions. To begin with, by MF-DFA, multifractality of bearing fault data was quantified with the generalized Hurst exponent, the scaling exponent and the multifractal spectrum. Consequently, controlled by essentially different dynamical mechanisms, the multifractality of four heterogeneous bearing fault data is significantly different; by contrast, controlled by slightly different dynamical mechanisms, the multifractality of homogeneous bearing fault data with different fault diameters is significantly or slightly different depending on different types of bearing faults. Therefore, the multifractal spectrum, as a set of parameters describing multifractality of time series, can be employed to characterize different types and severity of bearing faults. Subsequently, five characteristic parameters sensitive to changes of bearing fault conditions were extracted from the multifractal spectrum and utilized to construct fault features of bearing fault data. Moreover, Hilbert transform based envelope analysis, empirical mode decomposition (EMD) and wavelet transform (WT) were utilized to study the same bearing fault data. Also, the kurtosis and the peak levels of the EMD or the WT component corresponding to the bearing tones in the frequency domain were carefully checked

Scaling range of power laws that originate from fluctuation analysis

NASA Astrophysics Data System (ADS)

Grech, Dariusz; Mazur, Zygmunt

2013-05-01

We extend our previous study of scaling range properties performed for detrended fluctuation analysis (DFA) [Physica A0378-437110.1016/j.physa.2013.01.049 392, 2384 (2013)] to other techniques of fluctuation analysis (FA). The new technique, called modified detrended moving average analysis (MDMA), is introduced, and its scaling range properties are examined and compared with those of detrended moving average analysis (DMA) and DFA. It is shown that contrary to DFA, DMA and MDMA techniques exhibit power law dependence of the scaling range with respect to the length of the searched signal and with respect to the accuracy R2 of the fit to the considered scaling law imposed by DMA or MDMA methods. This power law dependence is satisfied for both uncorrelated and autocorrelated data. We find also a simple generalization of this power law relation for series with a different level of autocorrelations measured in terms of the Hurst exponent. Basic relations between scaling ranges for different techniques are also discussed. Our findings should be particularly useful for local FA in, e.g., econophysics, finances, or physiology, where the huge number of short time series has to be examined at once and wherever the preliminary check of the scaling range regime for each of the series separately is neither effective nor possible.

A time series analysis of multiple ambient pollutants to investigate the underlying air pollution dynamics and interactions.

PubMed

Yu, Hwa-Lung; Lin, Yuan-Chien; Kuo, Yi-Ming

2015-09-01

Understanding the temporal dynamics and interactions of particulate matter (PM) concentration and composition is important for air quality control. This paper applied a dynamic factor analysis method (DFA) to reveal the underlying mechanisms of nonstationary variations in twelve ambient concentrations of aerosols and gaseous pollutants, and the associations with meteorological factors. This approach can consider the uncertainties and temporal dependences of time series data. The common trends of the yearlong and three selected diurnal variations were obtained to characterize the dominant processes occurring in general and specific scenarios in Taipei during 2009 (i.e., during Asian dust storm (ADS) events, rainfall, and under normal conditions). The results revealed the two distinct yearlong NOx transformation processes, and demonstrated that traffic emissions and photochemical reactions both critically influence diurnal variation, depending upon meteorological conditions. During an ADS event, transboundary transport and distinct weather conditions both influenced the temporal pattern of identified common trends. This study shows the DFA method can effectively extract meaningful latent processes of time series data and provide insights of the dominant associations and interactions in the complex air pollution processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ecomorphological analysis of bovid mandibles from Laetoli Tanzania using 3D geometric morphometrics: Implications for hominin paleoenvironmental reconstruction.

PubMed

Forrest, Frances L; Plummer, Thomas W; Raaum, Ryan L

2018-01-01

The current study describes a new method of mandibular ecological morphology (ecomorphology). Three-dimensional geometric morphometrics (3D GM) was used to quantify mandibular shape variation between extant bovids with different feeding preferences. Landmark data were subjected to generalized Procrustes analysis (GPA), principal components analysis (PCA), and discriminant function analysis (DFA). The PCA resulted in a continuum from grazers to browsers along PC1 and DFA classified 88% or more of the modern specimens to the correct feeding category. The protocol was reduced to a subset of landmarks on the mandibular corpus in order to make it applicable to incomplete fossils. The reduced landmark set resulted in greater overlap between feeding categories but maintained the same continuum as the complete landmark model. The DFA resubstitution and jackknife analyses resulted in classification success rates of 85% and 80%, respectively. The reduced landmark model was applied to fossil mandibles from the Upper Laetolil Beds (∼4.3-3.5 Ma) and Upper Ndolanya Beds (∼2.7-2.6 Ma) at Laetoli, Tanzania in order to assess antelope diet, and indirectly evaluate paleo-vegetation structure. The majority of the fossils were classified by the DFA as browsers or mixed feeders preferring browse. Our results indicate a continuous presence of wooded habitats and are congruent with recent environmental studies at Laetoli indicating a mosaic woodland-bushland-grassland savanna ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Concurrent sympathetic activation and vagal withdrawal in hyperthyroidism: Evidence from detrended fluctuation analysis of heart rate variability

NASA Astrophysics Data System (ADS)

Chen, Jin-Long; Shiau, Yuo-Hsien; Tseng, Yin-Jiun; Chiu, Hung-Wen; Hsiao, Tzu-Chien; Wessel, Niels; Kurths, Jürgen; Chu, Woei-Chyn

2010-05-01

Despite many previous studies on the association between hyperthyroidism and the hyperadrenergic state, controversies still exist. Detrended fluctuation analysis (DFA) is a well recognized method in the nonlinear analysis of heart rate variability (HRV), and it has physiological significance related to the autonomic nervous system. In particular, an increased short-term scaling exponent α1 calculated from DFA is associated with both increased sympathetic activity and decreased vagal activity. No study has investigated the DFA of HRV in hyperthyroidism. This study was designed to assess the sympathovagal balance in hyperthyroidism. We performed the DFA along with the linear analysis of HRV in 36 hyperthyroid Graves’ disease patients (32 females and 4 males; age 30 ± 1 years, means ± SE) and 36 normal controls matched by sex, age and body mass index. Compared with the normal controls, the hyperthyroid patients revealed a significant increase ( P<0.001) in α1 (hyperthyroid 1.28±0.04 versus control 0.91±0.02), long-term scaling exponent α2 (1.05±0.02 versus 0.90±0.01), overall scaling exponent α (1.11±0.02 versus 0.89±0.01), low frequency power in normalized units (LF%) and the ratio of low frequency power to high frequency power (LF/HF); and a significant decrease ( P<0.001) in the standard deviation of the R-R intervals (SDNN) and high frequency power (HF). In conclusion, hyperthyroidism is characterized by concurrent sympathetic activation and vagal withdrawal. This sympathovagal imbalance state in hyperthyroidism helps to explain the higher prevalence of atrial fibrillation and exercise intolerance among hyperthyroid patients.

Evaluation of Sleep by Detrended Fluctuation Analysis of the Heartbeat

NASA Astrophysics Data System (ADS)

Yazawa, Toru; Shimoda, Yukio; Hutapea, Albert M.

2011-08-01

There are already-established methods for investigating biological signals such as rhythmic heartbeats. We used detrended fluctuation analysis (DFA), originally developed by Peng et al. (1995) to check power-law characteristics, because the method can quantify the heart condition numerically. In this article, we studied the heartbeat of sleeping subjects. Our purpose was to test whether DFA is useful to evaluate the subject's wellness of both during being awake and sleeping. This is a challenge to measure sleep without complex/expensive machine, an electro encephalography (EEG). We conducted electrophysiological recording to measure heartbeats during sleep using electrocardiograph with three-leads, one ground electrode and two active electrodes attached to chest. For good recording, a stable baseline must be maintained even when subjects move their body. We needed a tool to ensure long-term steady recording. We thus invented a new electric-circuit designed to produce this desired result. This gadget allowed us to perform heartbeat recording without any drifting baseline. We then were able to detect 100% of heartbeat peaks over the entire period of sleep. Here, we show a case study as empirical evidence that DFA is useful numerical method for quantifying sleep by using the scaling exponents.

Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

PubMed Central

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6–7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and

Examining the effectiveness of discriminant function analysis and cluster analysis in species identification of male field crickets based on their calling songs.

PubMed

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and

Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhang, Minjia

2015-10-01

This paper focuses on the comparative analysis of extreme values in the Chinese and American stock markets based on the detrended fluctuation analysis (DFA) algorithm using the daily data of Shanghai composite index and Dow Jones Industrial Average. The empirical results indicate that the multifractal detrended fluctuation analysis (MF-DFA) method is more objective than the traditional percentile method. The range of extreme value of Dow Jones Industrial Average is smaller than that of Shanghai composite index, and the extreme value of Dow Jones Industrial Average is more time clustering. The extreme value of the Chinese or American stock markets is concentrated in 2008, which is consistent with the financial crisis in 2008. Moreover, we investigate whether extreme events affect the cross-correlation between the Chinese and American stock markets using multifractal detrended cross-correlation analysis algorithm. The results show that extreme events have nothing to do with the cross-correlation between the Chinese and American stock markets.

Autocorrelation and cross-correlation in time series of homicide and attempted homicide

NASA Astrophysics Data System (ADS)

Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

2014-04-01

We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

Financial liberalization and stock market cross-correlation: MF-DCCA analysis based on Shanghai-Hong Kong Stock Connect

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Zhang, Shuhua; Lv, Dayong; Lu, Xinsheng

2018-02-01

Based on the implementation of Shanghai-Hong Kong Stock Connect in China, this paper examines the effects of financial liberalization on stock market comovement using both multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods. Results based on MF-DFA confirm the multifractality of Shanghai and Hong Kong stock markets, and the market efficiency of Shanghai stock market increased after the implementation of this connect program. Besides, analysis based on MF-DCCA has verified the existence of persistent cross-correlation between Shanghai and Hong Kong stock markets, and the cross-correlation gets stronger after the launch of this liberalization program. Finally, we find that fat-tail distribution is the main source of multifractality in the cross-correlations before the stock connect program, while long-range correlation contributes to the multifractality after this program.

The relationship of Asperger's syndrome to autism: a preliminary EEG coherence study.

PubMed

Duffy, Frank H; Shankardass, Aditi; McAnulty, Gloria B; Als, Heidelise

2013-07-31

It has long been debated whether Asperger's Syndrome (ASP) should be considered part of the Autism Spectrum Disorders (ASD) or whether it constitutes a unique entity. The Diagnostic and Statistical Manual, fourth edition (DSM-IV) differentiated ASP from high functioning autism. However, the new DSM-5 umbrellas ASP within ASD, thus eliminating the ASP diagnosis. To date, no clear biomarkers have reliably distinguished ASP and ASD populations. This study uses EEG coherence, a measure of brain connectivity, to explore possible neurophysiological differences between ASP and ASD. Voluminous coherence data derived from all possible electrode pairs and frequencies were previously reduced by principal components analysis (PCA) to produce a smaller number of unbiased, data-driven coherence factors. In a previous study, these factors significantly and reliably differentiated neurotypical controls from ASD subjects by discriminant function analysis (DFA). These previous DFA rules are now applied to an ASP population to determine if ASP subjects classify as control or ASD subjects. Additionally, a new set of coherence based DFA rules are used to determine whether ASP and ASD subjects can be differentiated from each other. Using prior EEG coherence based DFA rules that successfully classified subjects as either controls or ASD, 96.2% of ASP subjects are classified as ASD. However, when ASP subjects are directly compared to ASD subjects using new DFA rules, 92.3% ASP subjects are identified as separate from the ASD population. By contrast, five randomly selected subsamples of ASD subjects fail to reach significance when compared to the remaining ASD populations. When represented by the discriminant variable, both the ASD and ASD populations are normally distributed. Within a control-ASD dichotomy, an ASP population falls closer to ASD than controls. However, when compared directly with ASD, an ASP population is distinctly separate. The ASP population appears to constitute a

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

PubMed

Duffy, Frank H; D'Angelo, Eugene; Rotenberg, Alexander; Gonzalez-Heydrich, Joseph

2015-11-02

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri. Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON

Unique volatolomic signatures of TP53 and KRAS in lung cells

PubMed Central

Davies, M P A; Barash, O; Jeries, R; Peled, N; Ilouze, M; Hyde, R; Marcus, M W; Field, J K; Haick, H

2014-01-01

Background: Volatile organic compounds (VOCs) are potential biomarkers for cancer detection in breath, but it is unclear if they reflect specific mutations. To test this, we have compared human bronchial epithelial cell (HBEC) cell lines carrying the KRASV12 mutation, knockdown of TP53 or both with parental HBEC cells. Methods: VOC from headspace above cultured cells were collected by passive sampling and analysed by thermal desorption gas chromatography mass spectrometry (TD-GC–MS) or sensor array with discriminant factor analysis (DFA). Results: In TD-GC–MS analysis, individual compounds had limited ability to discriminate between cell lines, but by applying DFA analysis combinations of 20 VOCs successfully discriminated between all cell types (accuracies 80–100%, with leave-one-out cross validation). Sensor array detection DFA demonstrated the ability to discriminate samples based on their cell type for all comparisons with accuracies varying between 77% and 93%. Conclusions: Our results demonstrate that minimal genetic changes in bronchial airway cells lead to detectable differences in levels of specific VOCs identified by TD-GC–MS or of patterns of VOCs identified by sensor array output. From the clinical aspect, these results suggest the possibility of breath analysis for detection of minimal genetic changes for earlier diagnosis or for genetic typing of lung cancers. PMID:25051409

A Cycling Movement Based System for Real-Time Muscle Fatigue and Cardiac Stress Monitoring and Analysis

PubMed Central

Chen, Szi-Wen; Liaw, Jiunn-Woei; Chang, Ya-Ju; Chan, Hsiao-Lung; Chiu, Li-Yu

2015-01-01

In this study, we defined a new parameter, referred to as the cardiac stress index (CSI), using a nonlinear detrended fluctuation analysis (DFA) of heart rate (HR). Our study aimed to incorporate the CSI into a cycling based fatigue monitoring system developed in our previous work so the muscle fatigue and cardiac stress can be both continuously and quantitatively assessed for subjects undergoing the cycling exercise. By collecting electrocardiogram (ECG) signals, the DFA scaling exponent α was evaluated on the RR time series extracted from a windowed ECG segment. We then obtained the running estimate of α by shifting a one-minute window by a step of 20 seconds so the CSI, defined as the percentage of all the less-than-one α values, can be synchronously updated every 20 seconds. Since the rating of perceived exertion (RPE) scale is considered as a convenient index which is commonly used to monitor subjective perceived exercise intensity, we then related the Borg RPE scale value to the CSI in order to investigate and quantitatively characterize the relationship between exercise-induced fatigue and cardiac stress. Twenty-two young healthy participants were recruited in our study. Each participant was asked to maintain a fixed pedaling speed at a constant load during the cycling exercise. Experimental results showed that a decrease in DFA scaling exponent α or an increase in CSI was observed during the exercise. In addition, the Borg RPE scale and CSI were positively correlated, suggesting that the factors due to cardiac stress might also contribute to fatigue state during physical exercise. Since the CSI can effectively quantify the cardiac stress status during physical exercise, our system may be used in sports medicine, or used by cardiologists who carried out stress tests for monitoring heart condition in patients with heart diseases. PMID:26115515

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae)

PubMed Central

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Abstract Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks’s λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant (p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species. PMID:29134012

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae).

PubMed

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks's λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant ( p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species.

A new method for fingerprinting sediments source contributions using distances from discriminant function analysis

USDA-ARS?s Scientific Manuscript database

Mixing models have been used to predict sediment source contributions. The inherent problem of the mixing models limited the number of sediment sources. The objective of this study is to develop and evaluate a new method using Discriminant Function Analysis (DFA) to fingerprint sediment source contr...

Groundwater salinity in a floodplain forest impacted by saltwater intrusion

NASA Astrophysics Data System (ADS)

Kaplan, David A.; Muñoz-Carpena, Rafael

2014-11-01

Coastal wetlands occupy a delicate position at the intersection of fresh and saline waters. Changing climate and watershed hydrology can lead to saltwater intrusion into historically freshwater systems, causing plant mortality and loss of freshwater habitat. Understanding the hydrological functioning of tidally influenced floodplain forests is essential for advancing ecosystem protection and restoration goals, however finding direct relationships between hydrological inputs and floodplain hydrology is complicated by interactions between surface water, groundwater, and atmospheric fluxes in variably saturated soils with heterogeneous vegetation and topography. Thus, an alternative method for identifying common trends and causal factors is required. Dynamic factor analysis (DFA), a time series dimension reduction technique, models temporal variation in observed data as linear combinations of common trends, which represent unexplained common variability, and explanatory variables. DFA was applied to model shallow groundwater salinity in the forested floodplain wetlands of the Loxahatchee River (Florida, USA), where altered watershed hydrology has led to changing hydroperiod and salinity regimes and undesired vegetative changes. Long-term, high-resolution groundwater salinity datasets revealed dynamics over seasonal and yearly time periods as well as over tidal cycles and storm events. DFA identified shared trends among salinity time series and a full dynamic factor model simulated observed series well (overall coefficient of efficiency, Ceff = 0.85; 0.52 ≤ Ceff ≤ 0.99). A reduced multilinear model based solely on explanatory variables identified in the DFA had fair to good results (Ceff = 0.58; 0.38 ≤ Ceff ≤ 0.75) and may be used to assess the effects of restoration and management scenarios on shallow groundwater salinity in the Loxahatchee River floodplain.

Groundwater salinity in a floodplain forest impacted by saltwater intrusion.

PubMed

Kaplan, David A; Muñoz-Carpena, Rafael

2014-11-15

Coastal wetlands occupy a delicate position at the intersection of fresh and saline waters. Changing climate and watershed hydrology can lead to saltwater intrusion into historically freshwater systems, causing plant mortality and loss of freshwater habitat. Understanding the hydrological functioning of tidally influenced floodplain forests is essential for advancing ecosystem protection and restoration goals, however finding direct relationships between hydrological inputs and floodplain hydrology is complicated by interactions between surface water, groundwater, and atmospheric fluxes in variably saturated soils with heterogeneous vegetation and topography. Thus, an alternative method for identifying common trends and causal factors is required. Dynamic factor analysis (DFA), a time series dimension reduction technique, models temporal variation in observed data as linear combinations of common trends, which represent unexplained common variability, and explanatory variables. DFA was applied to model shallow groundwater salinity in the forested floodplain wetlands of the Loxahatchee River (Florida, USA), where altered watershed hydrology has led to changing hydroperiod and salinity regimes and undesired vegetative changes. Long-term, high-resolution groundwater salinity datasets revealed dynamics over seasonal and yearly time periods as well as over tidal cycles and storm events. DFA identified shared trends among salinity time series and a full dynamic factor model simulated observed series well (overall coefficient of efficiency, Ceff=0.85; 0.52≤Ceff≤0.99). A reduced multilinear model based solely on explanatory variables identified in the DFA had fair to good results (Ceff=0.58; 0.38≤Ceff≤0.75) and may be used to assess the effects of restoration and management scenarios on shallow groundwater salinity in the Loxahatchee River floodplain. Copyright © 2014 Elsevier B.V. All rights reserved.

Forecasting of magnitude and duration of currency crises based on the analysis of distortions of fractal scaling in exchange rate fluctuations

NASA Astrophysics Data System (ADS)

Uritskaya, Olga Y.

2005-05-01

Results of fractal stability analysis of daily exchange rate fluctuations of more than 30 floating currencies for a 10-year period are presented. It is shown for the first time that small- and large-scale dynamical instabilities of national monetary systems correlate with deviations of the detrended fluctuation analysis (DFA) exponent from the value 1.5 predicted by the efficient market hypothesis. The observed dependence is used for classification of long-term stability of floating exchange rates as well as for revealing various forms of distortion of stable currency dynamics prior to large-scale crises. A normal range of DFA exponents consistent with crisis-free long-term exchange rate fluctuations is determined, and several typical scenarios of unstable currency dynamics with DFA exponents fluctuating beyond the normal range are identified. It is shown that monetary crashes are usually preceded by prolonged periods of abnormal (decreased or increased) DFA exponent, with the after-crash exponent tending to the value 1.5 indicating a more reliable exchange rate dynamics. Statistically significant regression relations (R=0.99, p<0.01) between duration and magnitude of currency crises and the degree of distortion of monofractal patterns of exchange rate dynamics are found. It is demonstrated that the parameters of these relations characterizing small- and large-scale crises are nearly equal, which implies a common instability mechanism underlying these events. The obtained dependences have been used as a basic ingredient of a forecasting technique which provided correct in-sample predictions of monetary crisis magnitude and duration over various time scales. The developed technique can be recommended for real-time monitoring of dynamical stability of floating exchange rate systems and creating advanced early-warning-system models for currency crisis prevention.

Utility of drain fluid amylase measurement on the first postoperative day after distal pancreatectomy.

PubMed

Vass, David G; Hodson, James; Isaac, John; Marudanayagam, Ravi; Mirza, Darius F; Muiesan, Paolo; Roberts, Keith; Sutcliffe, Robert P

2018-05-22

Early exclusion of a postoperative pancreatic fistula (POPF) may facilitate earlier drain removal in selected patients after distal pancreatectomy. The purpose of this study was to evaluate the role of first postoperative day drain fluid amylase (DFA1) measurement to predict POPF. Patients in whom DFA1 was measured after distal pancreatectomy were identified from a prospectively maintained database over a five-year period. A cut-off value of DFA1 was derived using ROC analysis, which yielded sensitivity and negative predictive value of 100% for excluding POPF. DFA1 was available in 53 of 138 (38%) patients who underwent distal pancreatectomy. 19 of 53 patients (36%) developed a pancreatic fistula (Grade A - 15, Grade B - 3, Grade C - 1). Median DFA1 was significantly higher in those who developed a pancreatic fistula (5473; range 613-28,450) compared those without (802; range 57-2350). p < 0.0001. Using ROC analysis, a DFA1 less than 600 excluded pancreatic fistula with a sensitivity of 100% (AUROC of 0.91; SE = 0.04, p < 0.001). First postoperative day drain fluid amylase measurement may have a role in excluding pancreatic fistula after distal pancreatectomy. Such patients may be suitable for earlier drain removal. Copyright © 2017. Published by Elsevier Ltd.

Phytoplankton dynamics of a subtropical reservoir controlled by the complex interplay among hydrological, abiotic, and biotic variables.

PubMed

Kuo, Yi-Ming; Wu, Jiunn-Tzong

2016-12-01

This study was conducted to identify the key factors related to the spatiotemporal variations in phytoplankton abundance in a subtropical reservoir from 2006 to 2010 and to assist in developing strategies for water quality management. Dynamic factor analysis (DFA), a dimension-reduction technique, was used to identify interactions between explanatory variables (i.e., environmental variables) and abundance (biovolume) of predominant phytoplankton classes. The optimal DFA model significantly described the dynamic changes in abundances of predominant phytoplankton groups (including dinoflagellates, diatoms, and green algae) at five monitoring sites. Water temperature, electrical conductivity, water level, nutrients (total phosphorus, NO 3 -N, and NH 3 -N), macro-zooplankton, and zooplankton were the key factors affecting the dynamics of aforementioned phytoplankton. Therefore, transformations of nutrients and reactions between water quality variables and aforementioned processes altered by hydrological conditions may also control the abundance dynamics of phytoplankton, which may represent common trends in the DFA model. The meandering shape of Shihmen Reservoir and its surrounding rivers caused a complex interplay between hydrological conditions and abiotic and biotic variables, resulting in phytoplankton abundance that could not be estimated using certain variables. Additional water quality and hydrological variables at surrounding rivers and monitoring plans should be executed a few days before and after reservoir operations and heavy storm, which would assist in developing site-specific preventive strategies to control phytoplankton abundance.

A Comparative Analysis of Polymerase Chain Reaction and Direct Fluorescent Antibody Test for Diagnosis of Genital Herpes.

PubMed

Patwardhan, Vrushali; Bhalla, Preena; Rawat, Deepti; Garg, Vijay Kumar; Sardana, Kabir; Sethi, Sumit

2017-01-01

To compare laboratory tests that can simultaneously detect and type herpes simplex virus (HSV) directly from the genital ulcer specimens in clinically suspected cases of genital herpes. A study was conducted over 10 months and 44 adult male and female patients clinically suspected with genital herpes were recruited. Genital ulcer swab specimens were subjected to glycoprotein-G gene-based conventional polymerase chain reaction (PCR) and commercially available direct fluorescent antibody (DFA) test and the results were compared. PCR for HSV was positive in 82% (36/44) cases. DFA was positive in 68.2% (30/44) cases. There was 100% agreement between HSV types detected by DFA and PCR. The strength of agreement between the results was better in primary genital herpes than recurrent cases. PCR was found to be better in the detection of HSV in recurrent genital herpes patients. It is a better modality, especially when genital herpes clinically presents with ulcerative or crusted lesions, and is also a cheaper alternative as compared to DFA.

The relationship of Asperger’s syndrome to autism: a preliminary EEG coherence study

PubMed Central

2013-01-01

Background It has long been debated whether Asperger’s Syndrome (ASP) should be considered part of the Autism Spectrum Disorders (ASD) or whether it constitutes a unique entity. The Diagnostic and Statistical Manual, fourth edition (DSM-IV) differentiated ASP from high functioning autism. However, the new DSM-5 umbrellas ASP within ASD, thus eliminating the ASP diagnosis. To date, no clear biomarkers have reliably distinguished ASP and ASD populations. This study uses EEG coherence, a measure of brain connectivity, to explore possible neurophysiological differences between ASP and ASD. Methods Voluminous coherence data derived from all possible electrode pairs and frequencies were previously reduced by principal components analysis (PCA) to produce a smaller number of unbiased, data-driven coherence factors. In a previous study, these factors significantly and reliably differentiated neurotypical controls from ASD subjects by discriminant function analysis (DFA). These previous DFA rules are now applied to an ASP population to determine if ASP subjects classify as control or ASD subjects. Additionally, a new set of coherence based DFA rules are used to determine whether ASP and ASD subjects can be differentiated from each other. Results Using prior EEG coherence based DFA rules that successfully classified subjects as either controls or ASD, 96.2% of ASP subjects are classified as ASD. However, when ASP subjects are directly compared to ASD subjects using new DFA rules, 92.3% ASP subjects are identified as separate from the ASD population. By contrast, five randomly selected subsamples of ASD subjects fail to reach significance when compared to the remaining ASD populations. When represented by the discriminant variable, both the ASD and ASD populations are normally distributed. Conclusions Within a control-ASD dichotomy, an ASP population falls closer to ASD than controls. However, when compared directly with ASD, an ASP population is distinctly separate. The

Factor Analysis via Components Analysis

ERIC Educational Resources Information Center

Bentler, Peter M.; de Leeuw, Jan

2011-01-01

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…

Detection of crossover time scales in multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Ge, Erjia; Leung, Yee

2013-04-01

Fractal is employed in this paper as a scale-based method for the identification of the scaling behavior of time series. Many spatial and temporal processes exhibiting complex multi(mono)-scaling behaviors are fractals. One of the important concepts in fractals is crossover time scale(s) that separates distinct regimes having different fractal scaling behaviors. A common method is multifractal detrended fluctuation analysis (MF-DFA). The detection of crossover time scale(s) is, however, relatively subjective since it has been made without rigorous statistical procedures and has generally been determined by eye balling or subjective observation. Crossover time scales such determined may be spurious and problematic. It may not reflect the genuine underlying scaling behavior of a time series. The purpose of this paper is to propose a statistical procedure to model complex fractal scaling behaviors and reliably identify the crossover time scales under MF-DFA. The scaling-identification regression model, grounded on a solid statistical foundation, is first proposed to describe multi-scaling behaviors of fractals. Through the regression analysis and statistical inference, we can (1) identify the crossover time scales that cannot be detected by eye-balling observation, (2) determine the number and locations of the genuine crossover time scales, (3) give confidence intervals for the crossover time scales, and (4) establish the statistically significant regression model depicting the underlying scaling behavior of a time series. To substantive our argument, the regression model is applied to analyze the multi-scaling behaviors of avian-influenza outbreaks, water consumption, daily mean temperature, and rainfall of Hong Kong. Through the proposed model, we can have a deeper understanding of fractals in general and a statistical approach to identify multi-scaling behavior under MF-DFA in particular.

Study of Glycemic Variability Through Time Series Analyses (Detrended Fluctuation Analysis and Poincaré Plot) in Children and Adolescents with Type 1 Diabetes.

PubMed

García Maset, Leonor; González, Lidia Blasco; Furquet, Gonzalo Llop; Suay, Francisco Montes; Marco, Roberto Hernández

2016-11-01

Time series analysis provides information on blood glucose dynamics that is unattainable with conventional glycemic variability (GV) indices. To date, no studies have been published on these parameters in pediatric patients with type 1 diabetes. Our aim is to evaluate the relationship between time series analysis and conventional GV indices, and glycosylated hemoglobin (HbA1c) levels. This is a transversal study of 41 children and adolescents with type 1 diabetes. Glucose monitoring was carried out continuously for 72 h to study the following GV indices: standard deviation (SD) of glucose levels (mg/dL), coefficient of variation (%), interquartile range (IQR; mg/dL), mean amplitude of the largest glycemic excursions (MAGE), and continuous overlapping net glycemic action (CONGA). The time series analysis was conducted by means of detrended fluctuation analysis (DFA) and Poincaré plot. Time series parameters (DFA alpha coefficient and elements of the ellipse of the Poincaré plot) correlated well with the more conventional GV indices. Patients were grouped according to the terciles of these indices, to the terciles of eccentricity (1: 12.56-16.98, 2: 16.99-21.91, 3: 21.92-41.03), and to the value of the DFA alpha coefficient (> or ≤1.5). No differences were observed in the HbA1c of patients grouped by GV index criteria; however, significant differences were found in patients grouped by alpha coefficient and eccentricity, not only in terms of HbA1c, but also in SD glucose, IQR, and CONGA index. The loss of complexity in glycemic homeostasis is accompanied by an increase in variability.

Comparison of detrending methods for fluctuation analysis in hydrology

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Chen, Yongqin David

2011-03-01

SummaryTrends within a hydrologic time series can significantly influence the scaling results of fluctuation analysis, such as rescaled range (RS) analysis and (multifractal) detrended fluctuation analysis (MF-DFA). Therefore, removal of trends is important in the study of scaling properties of the time series. In this study, three detrending methods, including adaptive detrending algorithm (ADA), Fourier-based method, and average removing technique, were evaluated by analyzing numerically generated series and observed streamflow series with obvious relative regular periodic trend. Results indicated that: (1) the Fourier-based detrending method and ADA were similar in detrending practices, and given proper parameters, these two methods can produce similarly satisfactory results; (2) detrended series by Fourier-based detrending method and ADA lose the fluctuation information at larger time scales, and the location of crossover points is heavily impacted by the chosen parameters of these two methods; and (3) the average removing method has an advantage over the other two methods, i.e., the fluctuation information at larger time scales is kept well-an indication of relatively reliable performance in detrending. In addition, the average removing method performed reasonably well in detrending a time series with regular periods or trends. In this sense, the average removing method should be preferred in the study of scaling properties of the hydrometeorolgical series with relative regular periodic trend using MF-DFA.

Sexing California gulls using morphometrics and discriminant function analysis

USGS Publications Warehouse

Herring, Garth; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Takekawa, John Y.

2010-01-01

A discriminant function analysis (DFA) model was developed with DNA sex verification so that external morphology could be used to sex 203 adult California Gulls (Larus californicus) in San Francisco Bay (SFB). The best model was 97% accurate and included head-to-bill length, culmen depth at the gonys, and wing length. Using an iterative process, the model was simplified to a single measurement (head-to-bill length) that still assigned sex correctly 94% of the time. A previous California Gull sex determination model developed for a population in Wyoming was then assessed by fitting SFB California Gull measurement data to the Wyoming model; this new model failed to converge on the same measurements as those originally used by the Wyoming model. Results from the SFB discriminant function model were compared to the Wyoming model results (by using SFB data with the Wyoming model); the SFB model was 7% more accurate for SFB California gulls. The simplified DFA model (head-to-bill length only) provided highly accurate results (94%) and minimized the measurements and time required to accurately sex California Gulls.

Factor Analysis and Counseling Research

ERIC Educational Resources Information Center

Weiss, David J.

1970-01-01

Topics discussed include factor analysis versus cluster analysis, analysis of Q correlation matrices, ipsativity and factor analysis, and tests for the significance of a correlation matrix prior to application of factor analytic techniques. Techniques for factor extraction discussed include principal components, canonical factor analysis, alpha…

Vegetation characteristics important to common songbirds in east Texas

USGS Publications Warehouse

Conner, Richard N.; Dickson, James G.; Locke, Brian A.; Segelquist, Charles A.

1983-01-01

Multivariate studies of breeding bird communities have used principal component analysis (PCA) or several-group (three or more groups) discriminant function analysis (DFA) to ordinate bird species on vegetational continua (Cody 1968, James 1971, Whitmore 1975). In community studies, high resolution of habitat requirements for individual species is not always possible with either PCA or several-group DFA. When habitat characteristics of several species are examined with a DFA the resultant axes optimally discriminate among all species simultaneously. Hence, the characteristics assigned to a particular species reflect in part the presence of other species in the analyses. A better resolution of each species' habitat requirements may be obtained from a two-group DFA, wherein habitats selected by a species are discriminated from all other available habitats. Analyses using two-group DFAs to compare habitat used by a species with habitat unused by the same species have the potential to provide an optimal frame of reference from which to examine habitat variables (Martinka 1972, Conner and Adkisson 1976, Whitmore 1981). Mathematically (DFA) it is possible to maximally separate two groups of multivariate observations with a single axis (Harner and whitmore 1977). A line drawn in three or n-dimensional space can easily be positioned to intersect two multivariate means (centroids). If three or more centroids for species are analyzed simultaneously, a single line can no longer intersect all centroids unless a perfectly linear relationship exists for the species being examined. The probability of such an occurrence is extremely low. Thus, a high degree of resolution can be realized when a two-group DFA is used to determine habitat parameters important to individual species. We have used two-group DFA to identify vegetation variable important to 12 common species of songbirds in East Texas.

Rapid discrimination of the causal agents of urinary tract infection using ToF-SIMS with chemometric cluster analysis

NASA Astrophysics Data System (ADS)

Fletcher, John S.; Henderson, Alexander; Jarvis, Roger M.; Lockyer, Nicholas P.; Vickerman, John C.; Goodacre, Royston

2006-07-01

Advances in time of flight secondary ion mass spectrometry (ToF-SIMS) have enabled this technique to become a powerful tool for the analysis of biological samples. Such samples are often very complex and as a result full interpretation of the acquired data can be extremely difficult. To simplify the interpretation of these information rich data, the use of chemometric techniques is becoming widespread in the ToF-SIMS community. Here we discuss the application of principal components-discriminant function analysis (PC-DFA) to the separation and classification of a number of bacterial samples that are known to be major causal agents of urinary tract infection. A large data set has been generated using three biological replicates of each isolate and three machine replicates were acquired from each biological replicate. Ordination plots generated using the PC-DFA are presented demonstrating strain level discrimination of the bacteria. The results are discussed in terms of biological differences between certain species and with reference to FT-IR, Raman spectroscopy and pyrolysis mass spectrometric studies of similar samples.

Design local exhaust ventilation on sieve machine at PT.Perkebunan Nusantara VIII Ciater using design for assembly (DFA) approach with Boothroyd and Dewhurst method

NASA Astrophysics Data System (ADS)

Khalqihi, K. I.; Rahayu, M.; Rendra, M.

2017-12-01

PT Perkebunan Nusantara VIII Ciater is a company produced black tea orthodox more or less 4 tons every day. At the production section, PT Perkebunan Nusantara VIII will use local exhaust ventilation specially at sortation area on sieve machine. To maintain the quality of the black tea orthodox, all machine must be scheduled for maintenance every once a month and takes time 2 hours in workhours, with additional local exhaust ventilation, it will increase time for maintenance process, if maintenance takes time more than 2 hours it will caused production process delayed. To support maintenance process in PT Perkebunan Nusantara VIII Ciater, designing local exhaust ventilation using design for assembly approach with Boothroyd and Dewhurst method, design for assembly approach is choosen to simplify maintenance process which required assembly process. There are 2 LEV designs for this research. Design 1 with 94 components, assembly time 647.88 seconds and assembly efficiency level 23.62%. Design 2 with 82 components, assembly time 567.84 seconds and assembly efficiency level 24.83%. Design 2 is choosen for this research based on DFA goals, minimum total part that use, optimization assembly time, and assembly efficiency level.

Sexual dimorphism of the mandible in a contemporary Chinese Han population.

PubMed

Dong, Hongmei; Deng, Mohong; Wang, WenPeng; Zhang, Ji; Mu, Jiao; Zhu, Guanghui

2015-10-01

A present limitation of forensic anthropology practice in China is the lack of population-specific criteria on contemporary human skeletons. In this study, a sample of 203 maxillofacial Cone beam computed tomography (CBCT) images, including 96 male and 107 female cases (20-65 years old), was analyzed to explore mandible sexual dimorphism in a population of contemporary adult Han Chinese to investigate the potential use of the mandible as sex indicator. A three-dimensional image from mandible CBCT scans was reconstructed using the SimPlant Pro 11.40 software. Nine linear and two angular parameters were measured. Discriminant function analysis (DFA) and logistic regression analysis (LRA) were used to develop the mathematics models for sex determination. All of the linear measurements studied and one angular measurement were found to be sexually dimorphic, with the maximum mandibular length and bi-condylar breadth being the most dimorphic by univariate DFA and LRA respectively. The cross-validated sex allocation accuracies on multivariate were ranged from 84.2% (direct DFA), 83.5% (direct LRA), 83.3% (stepwise DFA) to 80.5% (stepwise LRA). In general, multivariate DFA yielded a higher accuracy and LRA obtained a lower sex bias, and therefore both DFA and LRA had their own advantages for sex determination by the mandible in this sample. These results suggest that the mandible expresses sexual dimorphism in the contemporary adult Han Chinese population, indicating an excellent sexual discriminatory ability. Cone beam computed tomography scanning can be used as alternative source for contemporary osteometric techniques. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Heart rhythm complexity impairment in patients undergoing peritoneal dialysis

NASA Astrophysics Data System (ADS)

Lin, Yen-Hung; Lin, Chen; Ho, Yi-Heng; Wu, Vin-Cent; Lo, Men-Tzung; Hung, Kuan-Yu; Liu, Li-Yu Daisy; Lin, Lian-Yu; Huang, Jenq-Wen; Peng, Chung-Kang

2016-06-01

Cardiovascular disease is one of the leading causes of death in patients with advanced renal disease. The objective of this study was to investigate impairments in heart rhythm complexity in patients with end-stage renal disease. We prospectively analyzed 65 patients undergoing peritoneal dialysis (PD) without prior cardiovascular disease and 72 individuals with normal renal function as the control group. Heart rhythm analysis including complexity analysis by including detrended fractal analysis (DFA) and multiscale entropy (MSE) were performed. In linear analysis, the PD patients had a significantly lower standard deviation of normal RR intervals (SDRR) and percentage of absolute differences in normal RR intervals greater than 20 ms (pNN20). Of the nonlinear analysis indicators, scale 5, area under the MSE curve for scale 1 to 5 (area 1-5) and 6 to 20 (area 6-20) were significantly lower than those in the control group. In DFA anaylsis, both DFA α1 and DFA α2 were comparable in both groups. In receiver operating characteristic curve analysis, scale 5 had the greatest discriminatory power for two groups. In both net reclassification improvement model and integrated discrimination improvement models, MSE parameters significantly improved the discriminatory power of SDRR, pNN20, and pNN50. In conclusion, PD patients had worse cardiac complexity parameters. MSE parameters are useful to discriminate PD patients from patients with normal renal function.

The effect of respiratory oscillations in heart rate on detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Govindan, Rathinaswamy B.; Kota, Srinivas; Al-Shargabi, Tareq; Swisher, Christopher B.; du Plessis, Adre

2017-10-01

Characterization of heart rate using detrended fluctuation analysis (DFA) is impeded by respiratory oscillations. In particular, the short-term exponent measured from 15 to 30 beats is compromised in the DFA. We reconstruct respiratory signal from electrocardiograms and attenuate the respiratory oscillation in the heart rate using a frequency-dependent subtraction approach. We validate this method by applying it to an electrocardiogram signal simulated using a coupled differential equation with the respiratory oscillation modelled using a sine function. The exponent estimated using the proposed approach agreed with the exponent incorporated in the model within a narrow range. In contrast, the exponent obtained from the raw data deviated from the expected value. Furthermore, the exponents obtained for the raw heart rate are smaller than the exponents obtained for the respiration oscillation attenuated heart rate. We apply this approach to heart rate measured from 12 preterm infants that were being treated for prematurity related complications. As observed in the simulated data, we show that compared to the raw heart rate, the respiratory oscillation attenuated heart rate shows higher short-term exponent (p < 0.001).

Using Horn's Parallel Analysis Method in Exploratory Factor Analysis for Determining the Number of Factors

ERIC Educational Resources Information Center

Çokluk, Ömay; Koçak, Duygu

2016-01-01

In this study, the number of factors obtained from parallel analysis, a method used for determining the number of factors in exploratory factor analysis, was compared to that of the factors obtained from eigenvalue and scree plot--two traditional methods for determining the number of factors--in terms of consistency. Parallel analysis is based on…

Analysis of physiological signals for recognition of boredom, pain, and surprise emotions.

PubMed

Jang, Eun-Hye; Park, Byoung-Jun; Park, Mi-Sook; Kim, Sang-Hyeob; Sohn, Jin-Hun

2015-06-18

The aim of the study was to examine the differences of boredom, pain, and surprise. In addition to that, it was conducted to propose approaches for emotion recognition based on physiological signals. Three emotions, boredom, pain, and surprise, are induced through the presentation of emotional stimuli and electrocardiography (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmography (PPG) as physiological signals are measured to collect a dataset from 217 participants when experiencing the emotions. Twenty-seven physiological features are extracted from the signals to classify the three emotions. The discriminant function analysis (DFA) as a statistical method, and five machine learning algorithms (linear discriminant analysis (LDA), classification and regression trees (CART), self-organizing map (SOM), Naïve Bayes algorithm, and support vector machine (SVM)) are used for classifying the emotions. The result shows that the difference of physiological responses among emotions is significant in heart rate (HR), skin conductance level (SCL), skin conductance response (SCR), mean skin temperature (meanSKT), blood volume pulse (BVP), and pulse transit time (PTT), and the highest recognition accuracy of 84.7% is obtained by using DFA. This study demonstrates the differences of boredom, pain, and surprise and the best emotion recognizer for the classification of the three emotions by using physiological signals.

Distribution of Anaerobic Hydrocarbon-Degrading Bacteria in Soils from King George Island, Maritime Antarctica.

PubMed

Sampaio, Dayanna Souza; Almeida, Juliana Rodrigues Barboza; de Jesus, Hugo E; Rosado, Alexandre S; Seldin, Lucy; Jurelevicius, Diogo

2017-11-01

Anaerobic diesel fuel Arctic (DFA) degradation has already been demonstrated in Antarctic soils. However, studies comparing the distribution of anaerobic bacterial groups and of anaerobic hydrocarbon-degrading bacteria in Antarctic soils containing different concentrations of DFA are scarce. In this study, functional genes were used to study the diversity and distribution of anaerobic hydrocarbon-degrading bacteria (bamA, assA, and bssA) and of sulfate-reducing bacteria (SRB-apsR) in highly, intermediate, and non-DFA-contaminated soils collected during the summers of 2009, 2010, and 2011 from King George Island, Antarctica. Signatures of bamA genes were detected in all soils analyzed, whereas bssA and assA were found in only 4 of 10 soils. The concentration of DFA was the main factor influencing the distribution of bamA-containing bacteria and of SRB in the analyzed soils, as shown by PCR-DGGE results. bamA sequences related to genes previously described in Desulfuromonas, Lautropia, Magnetospirillum, Sulfuritalea, Rhodovolum, Rhodomicrobium, Azoarcus, Geobacter, Ramlibacter, and Gemmatimonas genera were dominant in King George Island soils. Although DFA modulated the distribution of bamA-hosting bacteria, DFA concentration was not related to bamA abundance in the soils studied here. This result suggests that King George Island soils show functional redundancy for aromatic hydrocarbon degradation. The results obtained in this study support the hypothesis that specialized anaerobic hydrocarbon-degrading bacteria have been selected by hydrocarbon concentrations present in King George Island soils.

An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA

NASA Astrophysics Data System (ADS)

Rizvi, Syed Aun R.; Dewandaru, Ginanjar; Bacha, Obiyathulla I.; Masih, Mansur

An efficient market has been theoretically proven to be a key component for effective and efficient resource allocation in an economy. This paper incorporates econophysics with Efficient Market Hypothesis to undertake a comparative analysis of Islamic and developed countries’ markets by extending the understanding of their multifractal nature. By applying the Multifractal Detrended Fluctuation Analysis (MFDFA) we calculated the generalized Hurst exponents, multifractal scaling exponents and generalized multifractal dimensions for 22 broad market indices. The findings provide a deeper understanding of the markets in Islamic countries, where they have traces of highly efficient performance particularly in crisis periods. A key finding is the empirical evidence of the impact of the ‘stage of market development’ on the efficiency of the market. If Islamic countries aim to improve the efficiency of resource allocation, an important area to address is to focus, among others, on enhancing the stage of market development.

The cross-correlation analysis of multi property of stock markets based on MM-DFA

NASA Astrophysics Data System (ADS)

Yang, Yujun; Li, Jianping; Yang, Yimei

2017-09-01

In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal.

PubMed

Nayak, Suraj K; Bit, Arindam; Dey, Anilesh; Mohapatra, Biswajit; Pal, Kunal

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.

Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

NASA Astrophysics Data System (ADS)

Majumder, Himadri; Maity, Kalipada

2018-03-01

Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

Determining the Number of Factors in P-Technique Factor Analysis

ERIC Educational Resources Information Center

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

Extending Differential Fault Analysis to Dynamic S-Box Advanced Encryption Standard Implementations

DTIC Science & Technology

2014-09-18

entropy . At the same time, researchers strive to enhance AES and mitigate these growing threats. This paper researches the extension of existing...the algorithm or use side channels to reduce entropy , such as Differential Fault Analysis (DFA). At the same time, continuing research strives to...the state matrix. The S-box is an 8-bit 16x16 table built from an affine transformation on multiplicative inverses which guarantees full permutation (S

Multifractal characterization of energy stocks in China: A multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Yang, Liansheng; Zhu, Yingming; Wang, Yudong

2016-06-01

In this paper, we investigate the impacts of oil price changes on energy stocks in Chinese stock market from the multifractal perspective. The well-known multifractal detrended fluctuation analysis (MF-DFA) is applied to detect the multifractality. We find that both returns and volatilities of energy industry index display apparent multifractal behavior. Oil market activity is an important source of multifractality in energy stocks index in addition to long-range correlations and fat-tail distributions.

Changes of Serum Calcium Concentration, Frequency of Ruminal Contraction and Feed Intake Soon after Parturition of Dairy Cows Fed Difructose Anhydride III.

PubMed

Wynn, S; Teramura, M; Sato, T; Hanada, M

2015-01-01

Requirements to control the large decrease in serum calcium (Ca) due to parturition and to increase the feed intake soon after parturition have been well accepted in dairy cows. This study was aimed to investigate the feed intake affected by serum Ca concentration with difructose anhydride (DFA) III supplement in dairy cows soon after parturition. Fourteen transition Holstein cows were divided into DFA and control (CONT) groups within 1 to 5 parity variations in each group. Measurement schedule for an individual cow was from 14 d before parturition to 7 d following parturition. The cows in DFA group were supplied 0.2 kg/head/d of DFA III feed containing 40 g of pure DFA III while the cows in CONT group received no DFA III. Other feeding procedures were the same for all cows in both groups. At parturition (d 0), serum Ca concentration sharply declined in both groups (p<0.05). Time interval for recovery from decreased serum Ca to its normal range (>9.0 mg/dL) tended to be faster in DFA group (12 h) than in the CONT group (48 h), but the differences were not significant. Active ruminal contraction was observed in DFA group at following parturition of d 1 (p<0.05), d 3 (p<0.05), and d 5 (p<0.01). Dry matter (DM) intake did not differ between the groups. However, positive correlations were observed between serum Ca concentration and ruminal contraction (p<0.001), and between ruminal contraction and DM intake (p<0.001) during following parturition. According to multiple regression analysis (R(2) = 0.824, p<0.001), the DM intake was positively affected by serum Ca concentration and ruminal contraction. These results suggest that feed intake soon after parturition in dairy cows can be increased by improvement of serum Ca concentration and active ruminal contraction, but DFA III supplementation in this study did not improve the lower serum Ca concentration due to parturition.

Changes of Serum Calcium Concentration, Frequency of Ruminal Contraction and Feed Intake Soon after Parturition of Dairy Cows Fed Difructose Anhydride III

PubMed Central

Wynn, S.; Teramura, M.; Sato, T.; Hanada, M.

2015-01-01

Requirements to control the large decrease in serum calcium (Ca) due to parturition and to increase the feed intake soon after parturition have been well accepted in dairy cows. This study was aimed to investigate the feed intake affected by serum Ca concentration with difructose anhydride (DFA) III supplement in dairy cows soon after parturition. Fourteen transition Holstein cows were divided into DFA and control (CONT) groups within 1 to 5 parity variations in each group. Measurement schedule for an individual cow was from 14 d before parturition to 7 d following parturition. The cows in DFA group were supplied 0.2 kg/head/d of DFA III feed containing 40 g of pure DFA III while the cows in CONT group received no DFA III. Other feeding procedures were the same for all cows in both groups. At parturition (d 0), serum Ca concentration sharply declined in both groups (p<0.05). Time interval for recovery from decreased serum Ca to its normal range (>9.0 mg/dL) tended to be faster in DFA group (12 h) than in the CONT group (48 h), but the differences were not significant. Active ruminal contraction was observed in DFA group at following parturition of d 1 (p<0.05), d 3 (p<0.05), and d 5 (p<0.01). Dry matter (DM) intake did not differ between the groups. However, positive correlations were observed between serum Ca concentration and ruminal contraction (p<0.001), and between ruminal contraction and DM intake (p<0.001) during following parturition. According to multiple regression analysis (R2 = 0.824, p<0.001), the DM intake was positively affected by serum Ca concentration and ruminal contraction. These results suggest that feed intake soon after parturition in dairy cows can be increased by improvement of serum Ca concentration and active ruminal contraction, but DFA III supplementation in this study did not improve the lower serum Ca concentration due to parturition. PMID:25557676

Fractal analysis of GPS time series for early detection of disastrous seismic events

NASA Astrophysics Data System (ADS)

Filatov, Denis M.; Lyubushin, Alexey A.

2017-03-01

A new method of fractal analysis of time series for estimating the chaoticity of behaviour of open stochastic dynamical systems is developed. The method is a modification of the conventional detrended fluctuation analysis (DFA) technique. We start from analysing both methods from the physical point of view and demonstrate the difference between them which results in a higher accuracy of the new method compared to the conventional DFA. Then, applying the developed method to estimate the measure of chaoticity of a real dynamical system - the Earth's crust, we reveal that the latter exhibits two distinct mechanisms of transition to a critical state: while the first mechanism has already been known due to numerous studies of other dynamical systems, the second one is new and has not previously been described. Using GPS time series, we demonstrate efficiency of the developed method in identification of critical states of the Earth's crust. Finally we employ the method to solve a practically important task: we show how the developed measure of chaoticity can be used for early detection of disastrous seismic events and provide a detailed discussion of the numerical results, which are shown to be consistent with outcomes of other researches on the topic.

Non-linear Heart Rate Variability as a Discriminator of Internalizing Psychopathology and Negative Affect in Children With Internalizing Problems and Healthy Controls

PubMed Central

Fiskum, Charlotte; Andersen, Tonje G.; Bornas, Xavier; Aslaksen, Per M.; Flaten, Magne A.; Jacobsen, Karl

2018-01-01

Background: Internalizing psychopathology and dysregulated negative affect are characterized by dysregulation in the autonomic nervous system and reduced heart rate variability (HRV) due to increases in sympathetic activity alongside reduced vagal tone. The neurovisceral system is however, a complex nonlinear system, and nonlinear indices related to psychopathology are so far less studied in children. Essential nonlinear properties of a system can be found in two main domains: the informational domain and the invariant domain. sample entropy (SampEn) is a much-used method from the informational domain, while detrended fluctuation analysis (DFA) represents a widely-used method from the invariant domain. To see if nonlinear HRV can provide information beyond linear indices of autonomic activation, this study investigated SampEn and DFA as discriminators of internalizing psychopathology and negative affect alongside measures of vagally-mediated HRV and sympathetic activation. Material and Methods: Thirty-Two children with internalizing difficulties and 25 healthy controls (aged 9–13) were assessed with the Child Behavior Checklist and the Early Adolescent Temperament Questionnaire, Revised, giving an estimate of internalizing psychopathology, negative affect and effortful control, a protective factor against psychopathology. Five minute electrocardiogram and impedance cardiography recordings were collected during a resting baseline, giving estimates of SampEn, DFA short-term scaling exponent α1, root mean square of successive differences (RMSSD), and pre-ejection period (PEP). Between-group differences and correlations were assessed with parametric and non-parametric tests, and the relationships between cardiac variables, psychopathology and negative affect were assessed using generalized linear modeling. Results: SampEn and DFA were not significantly different between the groups. SampEn was weakly negatively related to heart rate (HR) in the controls, while DFA

Non-linear Heart Rate Variability as a Discriminator of Internalizing Psychopathology and Negative Affect in Children With Internalizing Problems and Healthy Controls.

PubMed

Fiskum, Charlotte; Andersen, Tonje G; Bornas, Xavier; Aslaksen, Per M; Flaten, Magne A; Jacobsen, Karl

2018-01-01

Background: Internalizing psychopathology and dysregulated negative affect are characterized by dysregulation in the autonomic nervous system and reduced heart rate variability (HRV) due to increases in sympathetic activity alongside reduced vagal tone. The neurovisceral system is however, a complex nonlinear system, and nonlinear indices related to psychopathology are so far less studied in children. Essential nonlinear properties of a system can be found in two main domains: the informational domain and the invariant domain. sample entropy (SampEn) is a much-used method from the informational domain, while detrended fluctuation analysis (DFA) represents a widely-used method from the invariant domain. To see if nonlinear HRV can provide information beyond linear indices of autonomic activation, this study investigated SampEn and DFA as discriminators of internalizing psychopathology and negative affect alongside measures of vagally-mediated HRV and sympathetic activation. Material and Methods: Thirty-Two children with internalizing difficulties and 25 healthy controls (aged 9-13) were assessed with the Child Behavior Checklist and the Early Adolescent Temperament Questionnaire, Revised, giving an estimate of internalizing psychopathology, negative affect and effortful control, a protective factor against psychopathology. Five minute electrocardiogram and impedance cardiography recordings were collected during a resting baseline, giving estimates of SampEn, DFA short-term scaling exponent α 1 , root mean square of successive differences (RMSSD), and pre-ejection period (PEP). Between-group differences and correlations were assessed with parametric and non-parametric tests, and the relationships between cardiac variables, psychopathology and negative affect were assessed using generalized linear modeling. Results: SampEn and DFA were not significantly different between the groups. SampEn was weakly negatively related to heart rate (HR) in the controls, while DFA

Assessment of long-range correlation in animal behavior time series: The temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus)

NASA Astrophysics Data System (ADS)

Kembro, Jackelyn M.; Flesia, Ana Georgina; Gleiser, Raquel M.; Perillo, María A.; Marin, Raul H.

2013-12-01

Detrended Fluctuation Analysis (DFA) is a method that has been frequently used to determine the presence of long-range correlations in human and animal behaviors. However, according to previous authors using statistical model systems, in order to correctly use DFA different aspects should be taken into account such as: (1) the establishment by hypothesis testing of the absence of short term correlation, (2) an accurate estimation of a straight line in the log-log plot of the fluctuation function, (3) the elimination of artificial crossovers in the fluctuation function, and (4) the length of the time series. Taking into consideration these factors, herein we evaluated the presence of long-range correlation in the temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus). In our study, modeling the data with the general autoregressive integrated moving average (ARFIMA) model, we rejected the hypothesis of short-range correlations (d=0) in all cases. We also observed that DFA was able to distinguish between the artificial crossover observed in the temporal pattern of locomotion of Japanese quail and the crossovers in the correlation behavior observed in mosquito larvae locomotion. Although the test duration can slightly influence the parameter estimation, no qualitative differences were observed between different test durations.

Model selection for identifying power-law scaling.

PubMed

Ton, Robert; Daffertshofer, Andreas

2016-08-01

Long-range temporal and spatial correlations have been reported in a remarkable number of studies. In particular power-law scaling in neural activity raised considerable interest. We here provide a straightforward algorithm not only to quantify power-law scaling but to test it against alternatives using (Bayesian) model comparison. Our algorithm builds on the well-established detrended fluctuation analysis (DFA). After removing trends of a signal, we determine its mean squared fluctuations in consecutive intervals. In contrast to DFA we use the values per interval to approximate the distribution of these mean squared fluctuations. This allows for estimating the corresponding log-likelihood as a function of interval size without presuming the fluctuations to be normally distributed, as is the case in conventional DFA. We demonstrate the validity and robustness of our algorithm using a variety of simulated signals, ranging from scale-free fluctuations with known Hurst exponents, via more conventional dynamical systems resembling exponentially correlated fluctuations, to a toy model of neural mass activity. We also illustrate its use for encephalographic signals. We further discuss confounding factors like the finite signal size. Our model comparison provides a proper means to identify power-law scaling including the range over which it is present. Copyright © 2016 Elsevier Inc. All rights reserved.

Drive for activity in patients with anorexia nervosa.

PubMed

Sternheim, Lot; Danner, Unna; Adan, Roger; van Elburg, Annemarie

2015-01-01

Hyperactivity and elevated physical activity are both considered symptom characteristics of anorexia nervosa (AN). It has been suggested that a drive for activity (DFA) may underlie these expressions, yet research into DFA in AN remains scant. This study investigated DFA levels in patients with AN and its relation to AN severity. Furthermore, as physical exercise may be a way to reduce negative affect, the influence of negative affect (anxiety) on the role of DFA in AN was tested. Two hundred and forty female patients with AN completed measures for DFA, eating disorder (ED) pathology, anxiety, and clinical parameters. A strong relation between DFA levels and ED pathology was found, which remained significant even after controlling for negative affect (anxiety). After much theorizing about DFA in AN this study provides empirical evidence for DFA as a hallmark feature of AN, independent of anxiety levels. Future research should shed light on the relationships between DFA, actual physical activity, and the course of AN. © 2014 Wiley Periodicals, Inc.

Detrended Fluctuation Analysis and Adaptive Fractal Analysis of Stride Time Data in Parkinson's Disease: Stitching Together Short Gait Trials

PubMed Central

Liebherr, Magnus; Haas, Christian T.

2014-01-01

Variability indicates motor control disturbances and is suitable to identify gait pathologies. It can be quantified by linear parameters (amplitude estimators) and more sophisticated nonlinear methods (structural information). Detrended Fluctuation Analysis (DFA) is one method to measure structural information, e.g., from stride time series. Recently, an improved method, Adaptive Fractal Analysis (AFA), has been proposed. This method has not been applied to gait data before. Fractal scaling methods (FS) require long stride-to-stride data to obtain valid results. However, in clinical studies, it is not usual to measure a large number of strides (e.g., strides). Amongst others, clinical gait analysis is limited due to short walkways, thus, FS seem to be inapplicable. The purpose of the present study was to evaluate FS under clinical conditions. Stride time data of five self-paced walking trials ( strides each) of subjects with PD and a healthy control group (CG) was measured. To generate longer time series, stride time sequences were stitched together. The coefficient of variation (CV), fractal scaling exponents (DFA) and (AFA) were calculated. Two surrogate tests were performed: A) the whole time series was randomly shuffled; B) the single trials were randomly shuffled separately and afterwards stitched together. CV did not discriminate between PD and CG. However, significant differences between PD and CG were found concerning and . Surrogate version B yielded a higher mean squared error and empirical quantiles than version A. Hence, we conclude that the stitching procedure creates an artificial structure resulting in an overestimation of true . The method of stitching together sections of gait seems to be appropriate in order to distinguish between PD and CG with FS. It provides an approach to integrate FS as standard in clinical gait analysis and to overcome limitations such as short walkways. PMID:24465708

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

PubMed Central

Mohapatra, Biswajit

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis. PMID:29854361

Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides.

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2012-03-20

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.

The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index

NASA Astrophysics Data System (ADS)

Domino, Krzysztof

2012-01-01

The WIG20 index-the index of the 20 biggest companies traded on the Warsaw Stock Exchange-reached the global maximum on 29th October 2007. I have used the local DFA (Detrended Functional Analysis) to obtain the Hurst exponent (diffusion exponent) and investigate the signature of anti-correlation of share price evolution around the maximum. The analysis was applied to the share price evolution for variable DFA parameters. For many values of parameters, the evidence of anti-correlation near the WIG20 maximum was pointed out.

Empirical mode decomposition and long-range correlation analysis of sunspot time series

NASA Astrophysics Data System (ADS)

Zhou, Yu; Leung, Yee

2010-12-01

Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the

Multifractal analysis of the Korean agricultural market

NASA Astrophysics Data System (ADS)

Kim, Hongseok; Oh, Gabjin; Kim, Seunghwan

2011-11-01

We have studied the long-term memory effects of the Korean agricultural market using the detrended fluctuation analysis (DFA) method. In general, the return time series of various financial data, including stock indices, foreign exchange rates, and commodity prices, are uncorrelated in time, while the volatility time series are strongly correlated. However, we found that the return time series of Korean agricultural commodity prices are anti-correlated in time, while the volatility time series are correlated. The n-point correlations of time series were also examined, and it was found that a multifractal structure exists in Korean agricultural market prices.

Potential use of ionic species for identifying source land-uses of stormwater runoff.

PubMed

Lee, Dong Hoon; Kim, Jin Hwi; Mendoza, Joseph A; Lee, Chang-Hee; Kang, Joo-Hyon

2017-02-01

Identifying critical land-uses or source areas is important to prioritize resources for cost-effective stormwater management. This study investigated the use of information on ionic composition as a fingerprint to identify the source land-use of stormwater runoff. We used 12 ionic species in stormwater runoff monitored for a total of 20 storm events at five sites with different land-use compositions during the 2012-2014 wet seasons. A stepwise forward discriminant function analysis (DFA) with the jack-knifed cross validation approach was used to select ionic species that better discriminate the land-use of its source. Of the 12 ionic species, 9 species (K + , Mg 2+ , Na + , NH 4 + , Br - , Cl - , F - , NO 2 - , and SO 4 2- ) were selected for better performance of the DFA. The DFA successfully differentiated stormwater samples from urban, rural, and construction sites using concentrations of the ionic species (70%, 95%, and 91% of correct classification, respectively). Over 80% of the new data cases were correctly classified by the trained DFA model. When applied to data cases from a mixed land-use catchment and downstream, the DFA model showed the greater impact of urban areas and rural areas respectively in the earlier and later parts of a storm event.

Managing dental fear and anxiety in pediatric patients: A qualitative study from the public's perspective.

PubMed

Hamzah, Hajar S; Gao, Xiaoli; Yung Yiu, Cynthia K; McGrath, Colman; King, Nigel M

2014-01-01

Internet social media offers a rich source for soliciting the public's views on health issues. This qualitative research, using You-Tube as a platform, aimed to explore the public's perspectives on management of dental fear and anxiety (DFA) in pediatric patients. Using three keywords ("dental fear," "dental phobia," and "dental anxiety"), YouTube videos were searched. Twenty-seven videos related to DFA in children and adolescents were reviewed by three investigators, including a nondental layperson. Inductive thematic analysis was adopted for interpreting the data. Several strategies were considered useful for controlling DFA in pediatric patients, including: verbal and nonverbal communication to establish closeness and effective guidance (explanation, permission-seeking, reassurance, and negotiation); desensitization to dental settings and procedures; tell-show-do; positive reinforcement; distraction by imagination and thoughtful designs of clinic; and parental presence and support. Some self-coping strategies adopted by patients alleviated their DFA, such as self-reasoning and trust-building through long-term connection. Dentists' clinical competence, favorable treatment outcomes, and state-of-the-art devices and technologies (dental lasers, intraoral camera, and adapted anaesthesia method) contributed to reducing DFA. Authentic testimonials in YouTube videos endorsed and interpreted a variety of strategies adoptable by patients, parents, and dental professionals for managing children's and adolescents' dental fears and anxieties.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Mean wind speed persistence over China

NASA Astrophysics Data System (ADS)

Jiang, Lei

2018-07-01

The wind speed persistence is an important factor in the assessment of wind energy potential. In this paper, we explore the persistence of Mean Wind Speed (MWS) with many years of record using Detrended Fluctuation Analysis (DFA) over China. The results illustrate that there exist irregular high-frequency fluctuations for daily MWS anomaly records. Long-term persistence of MWS is found for all meteorological observed sites. We also make some numerical tests in order to verify the significance of long-term persistence by shuffling the data records many times. These facts prove that the MWS anomaly records have long-term persistence over all the stations in China. The mean value 0.64 in DFA-exponents for all stations over China is also obviously higher than the value 0.53 according to interval threshold of 95% confidence level after shuffling the MWS records many times. In addition, the values of scaling exponent vary from station to station over China. Long-term persistence of MWS in spatial distributions seems to be downward trends from east to west China. Many factors may affect long-term persistence of MWS such as southwest monsoon, Tibetan Plateau landform and atmosphere-ocean-land interaction and so on. Possible physical mechanism need further analysis in the future.

Factors affecting construction performance: exploratory factor analysis

NASA Astrophysics Data System (ADS)

Soewin, E.; Chinda, T.

2018-04-01

The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

Multifractal detrended fluctuation analysis of sheep livestock prices in origin

NASA Astrophysics Data System (ADS)

Pavón-Domínguez, P.; Serrano, S.; Jiménez-Hornero, F. J.; Jiménez-Hornero, J. E.; Gutiérrez de Ravé, E.; Ariza-Villaverde, A. B.

2013-10-01

The multifractal detrended fluctuation analysis (MF-DFA) is used to verify whether or not the returns of time series of prices paid to farmers in original markets can be described by the multifractal approach. By way of example, 5 weekly time series of prices of different breeds, slaughter weight and market differentiation from 2000 to 2012 are analyzed. Results obtained from the multifractal parameters and multifractal spectra show that the price series of livestock products are of a multifractal nature. The Hurst exponent shows that these time series are stationary signals, some of which exhibit long memory (Merino milk-fed in Seville and Segureña paschal in Jaen), short memory (Merino paschal in Cordoba and Segureña milk-fed in Jaen) or even are close to an uncorrelated signals (Merino paschal in Seville). MF-DFA is able to discern the different underlying dynamics that play an important role in different types of sheep livestock markets, such as degree and source of multifractality. In addition, the main source of multifractality of these time series is due to the broadness of the probability function, instead of the long-range correlation properties between small and large fluctuations, which play a clearly secondary role.

Discrimination of chicken seasonings and beef seasonings using electronic nose and sensory evaluation.

PubMed

Tian, Huaixiang; Li, Fenghua; Qin, Lan; Yu, Haiyan; Ma, Xia

2014-11-01

This study examines the feasibility of electronic nose as a method to discriminate chicken and beef seasonings and to predict sensory attributes. Sensory evaluation showed that 8 chicken seasonings and 4 beef seasonings could be well discriminated and classified based on 8 sensory attributes. The sensory attributes including chicken/beef, gamey, garlic, spicy, onion, soy sauce, retention, and overall aroma intensity were generated by a trained evaluation panel. Principal component analysis (PCA), discriminant factor analysis (DFA), and cluster analysis (CA) combined with electronic nose were used to discriminate seasoning samples based on the difference of the sensor response signals of chicken and beef seasonings. The correlation between sensory attributes and electronic nose sensors signal was established using partial least squares regression (PLSR) method. The results showed that the seasoning samples were all correctly classified by the electronic nose combined with PCA, DFA, and CA. The electronic nose gave good prediction results for all the sensory attributes with correlation coefficient (r) higher than 0.8. The work indicated that electronic nose is an effective method for discriminating different seasonings and predicting sensory attributes. © 2014 Institute of Food Technologists®

Extension Procedures for Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Nagy, Gabriel; Brunner, Martin; Lüdtke, Oliver; Greiff, Samuel

2017-01-01

We present factor extension procedures for confirmatory factor analysis that provide estimates of the relations of common and unique factors with external variables that do not undergo factor analysis. We present identification strategies that build upon restrictions of the pattern of correlations between unique factors and external variables. The…

Farm factors associated with reducing Cryptosporidium loading in storm runoff from dairies.

PubMed

Miller, W A; Lewis, D J; Pereira, M D G; Lennox, M; Conrad, P A; Tate, K W; Atwill, E R

2008-01-01

A systems approach was used to evaluate environmental loading of Cryptosporidium oocysts on five coastal dairies in California. One aspect of the study was to determine Cryptosporidium oocyst concentrations and loads for 350 storm runoff samples from dairy high use areas collected over two storm seasons. Selected farm factors and beneficial management practices (BMPs) associated with reducing the Cryptosporidium load in storm runoff were assessed. Using immunomagnetic separation (IMS) with direct fluorescent antibody (DFA) analysis, Cryptosporidium oocysts were detected on four of the five farms and in 21% of storm runoff samples overall. Oocysts were detected in 59% of runoff samples collected near cattle less than 2 mo old, while 10% of runoff samples collected near cattle over 6 mo old were positive. Factors associated with environmental loading of Cryptosporidium oocysts included cattle age class, 24 h precipitation, and cumulative seasonal precipitation, but not percent slope, lot acreage, cattle stocking number, or cattle density. Vegetated buffer strips and straw mulch application significantly reduced the protozoal concentrations and loads in storm runoff, while cattle exclusion and removal of manure did not. The study findings suggest that BMPs such as vegetated buffer strips and straw mulch application, especially when placed near calf areas, will reduce environmental loading of fecal protozoa and improve stormwater quality. These findings are assisting working dairies in their efforts to improve farm and ecosystem health along the California coast.

Reversible heart rhythm complexity impairment in patients with primary aldosteronism

NASA Astrophysics Data System (ADS)

Lin, Yen-Hung; Wu, Vin-Cent; Lo, Men-Tzung; Wu, Xue-Ming; Hung, Chi-Sheng; Wu, Kwan-Dun; Lin, Chen; Ho, Yi-Lwun; Stowasser, Michael; Peng, Chung-Kang

2015-08-01

Excess aldosterone secretion in patients with primary aldosteronism (PA) impairs their cardiovascular system. Heart rhythm complexity analysis, derived from heart rate variability (HRV), is a powerful tool to quantify the complex regulatory dynamics of human physiology. We prospectively analyzed 20 patients with aldosterone producing adenoma (APA) that underwent adrenalectomy and 25 patients with essential hypertension (EH). The heart rate data were analyzed by conventional HRV and heart rhythm complexity analysis including detrended fluctuation analysis (DFA) and multiscale entropy (MSE). We found APA patients had significantly decreased DFAα2 on DFA analysis and decreased area 1-5, area 6-15, and area 6-20 on MSE analysis (all p < 0.05). Area 1-5, area 6-15, area 6-20 in the MSE study correlated significantly with log-transformed renin activity and log-transformed aldosterone-renin ratio (all p < = 0.01). The conventional HRV parameters were comparable between PA and EH patients. After adrenalectomy, all the altered DFA and MSE parameters improved significantly (all p < 0.05). The conventional HRV parameters did not change. Our result suggested that heart rhythm complexity is impaired in APA patients and this is at least partially reversed by adrenalectomy.

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

PubMed

Zhou, Jing; Wu, Xiao-ming; Zeng, Wei-jie

2015-12-01

Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of the electroencephalogram (EEG) signals. The purpose of this study is to find a novel and simpler method for detecting apnea patients and to quantify nonlinear characteristics of the sleep apnea. 30 min EEG scaling exponents that quantify power-law correlations were computed using detrended fluctuation analysis (DFA) and compared between six SAS and six healthy subjects during sleep. The mean scaling exponents were calculated every 30 s and 360 control values and 360 apnea values were obtained. These values were compared between the two groups and support vector machine (SVM) was used to classify apnea patients. Significant difference was found between EEG scaling exponents of the two groups (p < 0.001). SVM was used and obtained high and consistent recognition rate: average classification accuracy reached 95.1% corresponding to the sensitivity 93.2% and specificity 98.6%. DFA of EEG is an efficient and practicable method and is helpful clinically in diagnosis of sleep apnea.

Direct immunofluorescence assay compared to cell culture for the diagnosis of mucocutaneous herpes simplex virus infections in children.

PubMed

Caviness, A Chantal; Oelze, Lindsay L; Saz, Ulas E; Greer, Jewel M; Demmler-Harrison, Gail J

2010-09-01

Direct immunofluorescence assay (DFA) is commonly used for the rapid identification of herpes simplex virus (HSV) infection in mucocutaneous lesions, yet little is known about its diagnostic accuracy. To determine the diagnostic yield and accuracy of HSV DFA for the diagnosis of mucocutaneous HSV infection in pediatric patients. Retrospective cross-sectional study of all patients who underwent HSV DFA testing by the Texas Children's Hospital Diagnostic Virology between January 1, 1995 and December 31, 2005. HSV DFA sensitivity, specificity, positive likelihood ratio (LRs), and negative LRs were estimated using viral culture as the reference standard. 659 specimens were submitted for HSV DFA with concurrent viral cultures. Viral cultures were positive for HSV type 1 in 158 (24%) and HSV type 2 in 2 (0.3%). There were 433 different patients with a median age of 8.6 years. Types of lesions were as follows: 50% ulcerative, 26% vesicular, 8% erythema or purpura, 5% pustular, and 11% missing. Of the 659 specimens submitted for HSV DFA, 160 (24%) were inconclusive due to inadequate cells. Of the 499 adequate specimens, overall HSV DFA test accuracy was: sensitivity 61%, specificity 99%, LR positive 40, and LR negative 0.39. A quarter of specimens submitted for HSV DFA testing are not adequate for DFA testing. When HSV DFA can be performed, it is specific, but not sensitive, for the identification of mucocutaneous HSV infection in children. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Power-law statistics of neurophysiological processes analyzed using short signals

NASA Astrophysics Data System (ADS)

Pavlova, Olga N.; Runnova, Anastasiya E.; Pavlov, Alexey N.

2018-04-01

We discuss the problem of quantifying power-law statistics of complex processes from short signals. Based on the analysis of electroencephalograms (EEG) we compare three interrelated approaches which enable characterization of the power spectral density (PSD) and show that an application of the detrended fluctuation analysis (DFA) or the wavelet-transform modulus maxima (WTMM) method represents a useful way of indirect characterization of the PSD features from short data sets. We conclude that despite DFA- and WTMM-based measures can be obtained from the estimated PSD, these tools outperform the standard spectral analysis when characterization of the analyzed regime should be provided based on a very limited amount of data.

The role of sympathetic and vagal cardiac control on complexity of heart rate dynamics.

PubMed

Silva, Luiz Eduardo Virgilio; Silva, Carlos Alberto Aguiar; Salgado, Helio Cesar; Fazan, Rubens

2017-03-01

Analysis of heart rate variability (HRV) by nonlinear approaches has been gaining interest due to their ability to extract additional information from heart rate (HR) dynamics that are not detectable by traditional approaches. Nevertheless, the physiological interpretation of nonlinear approaches remains unclear. Therefore, we propose long-term (60 min) protocols involving selective blockade of cardiac autonomic receptors to investigate the contribution of sympathetic and parasympathetic function upon nonlinear dynamics of HRV. Conscious male Wistar rats had their electrocardiogram (ECG) recorded under three distinct conditions: basal, selective (atenolol or atropine), or combined (atenolol plus atropine) pharmacological blockade of autonomic muscarinic or β 1 -adrenergic receptors. Time series of RR interval were assessed by multiscale entropy (MSE) and detrended fluctuation analysis (DFA). Entropy over short (1 to 5, MSE 1-5 ) and long (6 to 30, MSE 6-30 ) time scales was computed, as well as DFA scaling exponents at short (α short , 5 ≤ n ≤ 15), mid (α mid , 30 ≤ n ≤ 200), and long (α long , 200 ≤ n ≤ 1,700) window sizes. The results show that MSE 1-5 is reduced under atropine blockade and MSE 6-30 is reduced under atropine, atenolol, or combined blockade. In addition, while atropine expressed its maximal effect at scale six, the effect of atenolol on MSE increased with scale. For DFA, α short decreased during atenolol blockade, while the α mid increased under atropine blockade. Double blockade decreased α short and increased α long Results with surrogate data show that the dynamics during combined blockade is not random. In summary, sympathetic and vagal control differently affect entropy (MSE) and fractal properties (DFA) of HRV. These findings are important to guide future studies. NEW & NOTEWORTHY Although multiscale entropy (MSE) and detrended fluctuation analysis (DFA) are recognizably useful prognostic/diagnostic methods, their

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis.

PubMed

Buldyrev, S V; Goldberger, A L; Havlin, S; Mantegna, R N; Matsa, M E; Peng, C K; Simons, M; Stanley, H E

1995-05-01

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

NASA Technical Reports Server (NTRS)

Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Matsa, M. E.; Peng, C. K.; Simons, M.; Stanley, H. E.

1995-01-01

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Exploratory Bi-factor Analysis: The Oblique Case.

PubMed

Jennrich, Robert I; Bentler, Peter M

2012-07-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

A better understanding of long-range temporal dependence of traffic flow time series

NASA Astrophysics Data System (ADS)

Feng, Shuo; Wang, Xingmin; Sun, Haowei; Zhang, Yi; Li, Li

2018-02-01

Long-range temporal dependence is an important research perspective for modelling of traffic flow time series. Various methods have been proposed to depict the long-range temporal dependence, including autocorrelation function analysis, spectral analysis and fractal analysis. However, few researches have studied the daily temporal dependence (i.e. the similarity between different daily traffic flow time series), which can help us better understand the long-range temporal dependence, such as the origin of crossover phenomenon. Moreover, considering both types of dependence contributes to establishing more accurate model and depicting the properties of traffic flow time series. In this paper, we study the properties of daily temporal dependence by simple average method and Principal Component Analysis (PCA) based method. Meanwhile, we also study the long-range temporal dependence by Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA). The results show that both the daily and long-range temporal dependence exert considerable influence on the traffic flow series. The DFA results reveal that the daily temporal dependence creates crossover phenomenon when estimating the Hurst exponent which depicts the long-range temporal dependence. Furthermore, through the comparison of the DFA test, PCA-based method turns out to be a better method to extract the daily temporal dependence especially when the difference between days is significant.

Preparation and characterization of acorn starch/poly(lactic acid) composites modified with functionalized vegetable oil derivates.

PubMed

Li, Shouhai; Xia, Jianling; Xu, Yuzhi; Yang, Xuejuan; Mao, Wei; Huang, Kun

2016-05-20

Composites of acorn starch (AS) and poly(1actic acid) (PLA) modified with dimer fatty acid (DFA) or dimer fatty acid polyamide (DFAPA) were produced by a hot-melt extrusion method. The effects of DFA and DFAPA contents on the mechanical, hydrophobic, thermal properties and melt fluidity of the composites were studied under an invariable AS-to-PLA mass ratio of 40/60. SEM and DMA research results show that the compatibility of AS/PLA composites are determined by the dosage of DFA or DFAPA. The hydrophobicity and melt fluidity of composites are improved with the addition of DFA and DFAPA. The glass transition temperatures of the composites are all reduced remarkably by additives DFA and DFAPA. However, DFA and DFAPA exert different effects on the mechanical properties of AS/PLA composites. In the DFAPA-modified system, the tensile and flexural strength first increase and then decrease with the increase of DFAPA dosage; the mechanical strength is maximized when the dosage of DFAPA is 2 wt% of total weight. In the DFA-modified system, the tensile and flexural strength decrease with the increase of DFA dosage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Three-dimensional fractal analysis of 99mTc-MAA SPECT images in chronic thromboembolic pulmonary hypertension for evaluation of response to balloon pulmonary angioplasty: association with pulmonary arterial pressure.

PubMed

Maruoka, Yasuhiro; Nagao, Michinobu; Baba, Shingo; Isoda, Takuro; Kitamura, Yoshiyuki; Yamazaki, Yuzo; Abe, Koichiro; Sasaki, Masayuki; Abe, Kohtaro; Honda, Hiroshi

2017-06-01

Balloon pulmonary angioplasty (BPA) is used for inoperable chronic thromboembolic pulmonary hypertension (CTEPH), but its effect cannot be evaluated noninvasively. We devised a noninvasive quantitative index of response to BPA using three-dimensional fractal analysis (3D-FA) of technetium-99m-macroaggregated albumin (Tc-MAA) single-photon emission computed tomography (SPECT). Forty CTEPH patients who underwent pulmonary perfusion scintigraphy and mean pulmonary arterial pressure (mPAP) measurement by right heart catheterization before and after BPA were studied. The total uptake volume (TUV) in bilateral lungs was determined from maximum intensity projection Tc-MAA SPECT images. Fractal dimension was assessed by 3D-FA. Parameters were compared before and after BPA, and between patients with post-BPA mPAP more than 30 mmHg and less than or equal to 30 mmHg. Receiver operating characteristic analysis was carried out. BPA significantly improved TUV (595±204-885±214 ml, P<0.001) and reduced the laterality of uptake (238±147-135±131 ml, P<0.001). Patients with poor therapeutic response (post-BPA mPAP≥30 mmHg, n=16) showed a significantly smaller TUV increase (P=0.044) and a significantly greater post-BPA fractal dimension (P<0.001) than the low-mPAP group. Fractal dimension correlated with mPAP values before and after BPA (P=0.013 and 0.001, respectively). A post-BPA fractal dimension threshold of 2.4 distinguished between BPA success and failure with 75% sensitivity, 79% specificity, 78% accuracy, and area under the curve of 0.85. 3D-FA using Tc-MAA SPECT pulmonary perfusion scintigraphy enables a noninvasive evaluation of the response of CTEPH patients to BPA.

Exploratory Bi-Factor Analysis: The Oblique Case

ERIC Educational Resources Information Center

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

Age-related change and sex difference over 60s in disc-fovea angle in Japanese population: the Nagahama Study.

PubMed

Miyata, Manabu; Yoshikawa, Munemitsu; Ohtsuki, Hiroshi; Muraoka, Yuki; Hata, Masayuki; Yokota, Satoshi; Fujimoto, Masahiro; Miyake, Masahiro; Tabara, Yasuharu; Matsuda, Fumihiko; Yoshimura, Nagahisa

2018-01-25

To analyse the disc-fovea angle (DFA) by age group and to compare sex differences in each age group in a large cohort population. This community-based cross-sectional cohort study included 9682 eyes of 9682 volunteers (aged 30-75 years). We measured the DFA, which is the angle between a horizontal line and a line connecting the fovea with the centroid of an optic disc on fundus photographs of the right eye. We manually marked the fovea and surrounded the optic disc. The centroid of an optic disc and the DFA was automatically calculated using originally developed software. We compared the DFA between age groups in 10-year increments and investigated sex differences of DFA in each age group. Overall mean DFA was 6.32 ± 3.53°. The DFA of older subjects was significantly larger than that of younger subjects (p < 0.001). The DFA of women was larger than that of men in their 60s and 70s (p < 0.001 for both), but not in subjects in their 30s, 40s and 50s. Larger DFA in women than in men in their 60s and 70s suggests the possibility that age-related excyclo-shift occurs more easily in postmenopausal women compared to men of the same age. © 2018 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Dietary fatty acid metabolism in prediabetes.

PubMed

Noll, Christophe; Carpentier, André C

2017-02-01

Experimental evidences are strong for a role of long-chain saturated fatty acids in the development of insulin resistance and type 2 diabetes. Ectopic accretion of triglycerides in lean organs is a characteristic of prediabetes and type 2 diabetes and has been linked to end-organ complications. The contribution of disordered dietary fatty acid (DFA) metabolism to lean organ overexposure and lipotoxicity is still unclear, however. DFA metabolism is very complex and very difficult to study in vivo in humans. We have recently developed a novel imaging method using PET with oral administration of 14-R,S-F-fluoro-6-thia-heptadecanoic acid (FTHA) to quantify organ-specific DFA partitioning. Our studies thus far confirmed impaired storage of DFA per volume of fat mass in abdominal adipose tissues of individuals with prediabetes. They also highlighted the increased channeling of DFA toward the heart, associated with subclinical reduction in cardiac systolic and diastolic function in individuals with prediabetes. In the present review, we summarize previous work on DFA metabolism in healthy and prediabetic states and discuss these in the light of our novel findings using PET imaging of DFA metabolism. We herein provide an integrated view of abnormal organ-specific DFA partitioning in prediabetes in humans.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Site characterization at Groningen gas field area through joint surface-borehole H/V analysis

NASA Astrophysics Data System (ADS)

Spica, Zack J.; Perton, Mathieu; Nakata, Nori; Liu, Xin; Beroza, Gregory C.

2018-01-01

A new interpretation of the horizontal to vertical (H/V) spectral ratio in terms of the Diffuse Field Assumption (DFA) has fuelled a resurgence of interest in that approach. The DFA links H/V measurements to Green's function retrieval through autocorrelation of the ambient seismic field. This naturally allows for estimation of layered velocity structure. In this contribution, we further explore the potential of H/V analysis. Our study is facilitated by a distributed array of surface and co-located borehole stations deployed at multiple depths, and by detailed prior information on velocity structure that is available due to development of the Groningen gas field. We use the vertical distribution of H/V spectra recorded at discrete depths inside boreholes to obtain shear wave velocity models of the shallow subsurface. We combine both joint H/V inversion and borehole interferometry to reduce the non-uniqueness of the problem and to allow faster convergence towards a reliable velocity model. The good agreement between our results and velocity models from an independent study validates the methodology, demonstrates the power of the method, but more importantly provides further constraints on the shallow velocity structure, which is an essential component of integrated hazard assessment in the area.

Local multifractal detrended fluctuation analysis for non-stationary image's texture segmentation

NASA Astrophysics Data System (ADS)

Wang, Fang; Li, Zong-shou; Li, Jin-wei

2014-12-01

Feature extraction plays a great important role in image processing and pattern recognition. As a power tool, multifractal theory is recently employed for this job. However, traditional multifractal methods are proposed to analyze the objects with stationary measure and cannot for non-stationary measure. The works of this paper is twofold. First, the definition of stationary image and 2D image feature detection methods are proposed. Second, a novel feature extraction scheme for non-stationary image is proposed by local multifractal detrended fluctuation analysis (Local MF-DFA), which is based on 2D MF-DFA. A set of new multifractal descriptors, called local generalized Hurst exponent (Lhq) is defined to characterize the local scaling properties of textures. To test the proposed method, both the novel texture descriptor and other two multifractal indicators, namely, local Hölder coefficients based on capacity measure and multifractal dimension Dq based on multifractal differential box-counting (MDBC) method, are compared in segmentation experiments. The first experiment indicates that the segmentation results obtained by the proposed Lhq are better than the MDBC-based Dq slightly and superior to the local Hölder coefficients significantly. The results in the second experiment demonstrate that the Lhq can distinguish the texture images more effectively and provide more robust segmentations than the MDBC-based Dq significantly.

Environmental controls on the 2H/1H values of terrestrial leaf waxes in the eastern Canadian Arctic

NASA Astrophysics Data System (ADS)

Shanahan, Timothy M.; Hughen, Konrad A.; Ampel, Linda; Sauer, Peter E.; Fornace, Kyrstin

2013-10-01

The hydrogen isotope composition of plant waxes preserved in lacustrine sediments is a potentially valuable tool for reconstructing paleoenvironmental changes in the Arctic. However, in contrast to the mid- and low-latitudes, significantly less effort has been directed towards understanding the factors controlling D/H fractionation in high latitude plant waxes and the impact of these processes on the interpretation of sedimentary leaf wax δD records. To better understand these processes, we examined the D/H ratios of long chain fatty acids in lake surface sediments spanning a temperature and precipitation gradient on Baffin Island in the eastern Canadian Arctic. D/H ratios of plant waxes increase with increasing temperature and aridity, with values ranging from -240‰ to -160‰ over the study area. Apparent fractionation factors between n-alkanoic acids in Arctic lake sediments and precipitation(εFA-ppt) are less negative than those of mid-latitude lakes and modern plants by 25‰ to 65‰, consistent with n-alkane data from modern Arctic plants (Yang et al., 2011). Furthermore, εFA-ppt values from Arctic lakes become systematically more positive with increasing evaporation, in contrast to mid-latitude sites, which show little to no change in fractionation with aridity. These data are consistent with enhanced water loss and isotope fractionation at higher latitude in the Arctic summer, when continuous sunlight supports increased daily photosynthesis. The dominant control on δDFA variations on Baffin Island is temperature. However, changing εFA-ppt result in steeper δDFA-temperature relationships than observed for modern precipitation. The application of this δDFA-based paleotemperature calibration to existing δDFA records from Baffin Island produces much more realistic changes in late Holocene temperature and highlights the importance of these effects in influencing the interpretation of Arctic δDFA records. A better understanding of the controls on

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

Womack, Sid T.; Hannah, Shellie Louise; Bell, Columbus David

2012-01-01

Four factors in teaching intern effectiveness, as measured by a Praxis III-similar instrument, were found among observational data of teaching interns during the 2010 spring semester. Those factors were lesson planning, teacher/student reflection, fairness & safe environment, and professionalism/efficacy. This factor analysis was as much of a…

Relative effectiveness of kinetic analysis vs single point readings for classifying environmental samples based on community-level physiological profiles (CLPP)

NASA Technical Reports Server (NTRS)

Garland, J. L.; Mills, A. L.; Young, J. S.

2001-01-01

The relative effectiveness of average-well-color-development-normalized single-point absorbance readings (AWCD) vs the kinetic parameters mu(m), lambda, A, and integral (AREA) of the modified Gompertz equation fit to the color development curve resulting from reduction of a redox sensitive dye from microbial respiration of 95 separate sole carbon sources in microplate wells was compared for a dilution series of rhizosphere samples from hydroponically grown wheat and potato ranging in inoculum densities of 1 x 10(4)-4 x 10(6) cells ml-1. Patterns generated with each parameter were analyzed using principal component analysis (PCA) and discriminant function analysis (DFA) to test relative resolving power. Samples of equivalent cell density (undiluted samples) were correctly classified by rhizosphere type for all parameters based on DFA analysis of the first five PC scores. Analysis of undiluted and 1:4 diluted samples resulted in misclassification of at least two of the wheat samples for all parameters except the AWCD normalized (0.50 abs. units) data, and analysis of undiluted, 1:4, and 1:16 diluted samples resulted in misclassification for all parameter types. Ordination of samples along the first principal component (PC) was correlated to inoculum density in analyses performed on all of the kinetic parameters, but no such influence was seen for AWCD-derived results. The carbon sources responsible for classification differed among the variable types with the exception of AREA and A, which were strongly correlated. These results indicate that the use of kinetic parameters for pattern analysis in CLPP may provide some additional information, but only if the influence of inoculum density is carefully considered. c2001 Elsevier Science Ltd. All rights reserved.

Robust Bayesian Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Yuan, Ke-Hai

2003-01-01

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

Differential Fault Analysis on CLEFIA with 128, 192, and 256-Bit Keys

NASA Astrophysics Data System (ADS)

Takahashi, Junko; Fukunaga, Toshinori

This paper describes a differential fault analysis (DFA) attack against CLEFIA. The proposed attack can be applied to CLEFIA with all supported keys: 128, 192, and 256-bit keys. DFA is a type of side-channel attack. This attack enables the recovery of secret keys by injecting faults into a secure device during its computation of the cryptographic algorithm and comparing the correct ciphertext with the faulty one. CLEFIA is a 128-bit blockcipher with 128, 192, and 256-bit keys developed by the Sony Corporation in 2007. CLEFIA employs a generalized Feistel structure with four data lines. We developed a new attack method that uses this characteristic structure of the CLEFIA algorithm. On the basis of the proposed attack, only 2 pairs of correct and faulty ciphertexts are needed to retrieve the 128-bit key, and 10.78 pairs on average are needed to retrieve the 192 and 256-bit keys. The proposed attack is more efficient than any previously reported. In order to verify the proposed attack and estimate the calculation time to recover the secret key, we conducted an attack simulation using a PC. The simulation results show that we can obtain each secret key within three minutes on average. This result shows that we can obtain the entire key within a feasible computational time.

Recent advances on biological production of difructose dianhydride III.

PubMed

Zhu, Yingying; Yu, Shuhuai; Zhang, Wenli; Zhang, Tao; Guang, Cuie; Mu, Wanmeng

2018-04-01

Difructose dianhydride III (DFA III) is a cyclic difructose containing two reciprocal glycosidic linkages. It is easily generated with a small amount by sucrose caramelization and thus occurs in a wide range of food-stuffs during food processing. DFA III has half sweetness but only 1/15 energy of sucrose, showing potential industrial application as low-calorie sucrose substitute. In addition, it displays many benefits including prebiotic effect, low cariogenicity property, and hypocholesterolemic effect, and improves absorption of minerals, flavonoids, and immunoglobulin G. DFA III is biologically produced from inulin by inulin fructotransferase (IFTase, EC 4.2.2.18). Plenty of DFA III-producing enzymes have been identified. The crystal structure of inulin fructotransferase has been determined, and its molecular modification has been performed to improve the catalytic activity and structural stability. Large-scale production of DFA III has been studied by various IFTases, especially using an ultrafiltration membrane bioreactor. In this article, the recent findings on physiological effects of DFA III are briefly summarized; the research progresses on identification, expression, and molecular modification of IFTase and large-scale biological production of DFA III by IFTase are reviewed in detail.

13 CFR 120.812 - Probationary period for newly certified CDCs.

Code of Federal Regulations, 2010 CFR

2010-01-01

... its recommendation to the D/FA, who will make the final decision. SBA will determine permanent CDC... discretion. The CDC's Risk Rating, among other factors, will be considered in determining satisfactory SBA performance. Other factors may include, but are not limited to, on-site review/examination assessments...

The Infinitesimal Jackknife with Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Factor Retention in Exploratory Factor Analysis: A Comparison of Alternative Methods.

ERIC Educational Resources Information Center

Mumford, Karen R.; Ferron, John M.; Hines, Constance V.; Hogarty, Kristine Y.; Kromrey, Jeffery D.

This study compared the effectiveness of 10 methods of determining the number of factors to retain in exploratory common factor analysis. The 10 methods included the Kaiser rule and a modified Kaiser criterion, 3 variations of parallel analysis, 4 regression-based variations of the scree procedure, and the minimum average partial procedure. The…

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

Identifying the performance characteristics of a winning outcome in elite mixed martial arts competition.

PubMed

James, Lachlan P; Robertson, Sam; Haff, G Gregory; Beckman, Emma M; Kelly, Vincent G

2017-03-01

To determine those performance indicators that have the greatest influence on classifying outcome at the elite level of mixed martial arts (MMA). A secondary objective was to establish the efficacy of decision tree analysis in explaining the characteristics of victory when compared to alternate statistical methods. Cross-sectional observational. Eleven raw performance indicators from male Ultimate Fighting Championship bouts (n=234) from July 2014 to December 2014 were screened for analysis. Each raw performance indicator was also converted to a rate-dependent measure to be scaled to fight duration. Further, three additional performance indicators were calculated from the dataset and included in the analysis. Cohen's d effect sizes were employed to determine the magnitude of the differences between Wins and Losses, while decision tree (chi-square automatic interaction detector (CHAID)) and discriminant function analyses (DFA) were used to classify outcome (Win and Loss). Effect size comparisons revealed differences between Wins and Losses across a number of performance indicators. Decision tree (raw: 71.8%; rate-scaled: 76.3%) and DFA (raw: 71.4%; rate-scaled 71.2%) achieved similar classification accuracies. Grappling and accuracy performance indicators were the most influential in explaining outcome. The decision tree models also revealed multiple combinations of performance indicators leading to victory. The decision tree analyses suggest that grappling activity and technique accuracy are of particular importance in achieving victory in elite-level MMA competition. The DFA results supported the importance of these performance indicators. Decision tree induction represents an intuitive and slightly more accurate approach to explaining bout outcome in this sport when compared to DFA. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Computational Analysis of Pharyngeal Swallowing Mechanics in Patients with Motor Neuron Disease: A Pilot Investigation.

PubMed

Garand, K L; Schwertner, Ryan; Chen, Amy; Pearson, William G

2018-04-01

Swallowing impairment (dysphagia) is a common sequela in patients with motor neuron disease (MND). The purpose of this retrospective, observational pilot investigation was to characterize how pharyngeal swallowing mechanics are impacted in patients with MND using a comparison with healthy, non-dysphagic control group. Computational analysis of swallowing mechanics (CASM) was used to determine covariate biomechanics of pharyngeal swallowing from videofluoroscopic assessment in 15 patients with MND and 15 age- and sex-matched healthy controls. Canonical variant analysis with post hoc discriminate function analysis (DFA) was performed on coordinate data mapping functional muscle groups underlying pharyngeal swallowing. Differences in swallowing mechanics associated with group (MND; control), motor neuron predominance (upper; lower), onset (bulbar; spinal), and swallow task (thin, pudding) were evaluated and visualized. Pharyngeal swallowing mechanics differed significantly in patients with MND compared with healthy controls (D = 2.01, p < 0.0001). Post hoc DFA pairwise comparisons suggest differences in pharyngeal swallow mechanics by motor neuron predominance (D = 5.03, p < 0.0001), onset (D = 2.03, p < 0.0001), and swallow task (D = 1.04, p < 0.0001). Pharyngeal swallowing mechanics of patients with MND differ from and are more heterogeneous than healthy controls. These findings suggest patients with MND may compensate reductions in pharyngeal shortening and tongue base retraction by extending the head and neck and increasing hyolaryngeal excursion. This work and further CASM investigations will lead to further insights into development and evaluation of targeted clinical treatments designed to prolong safe and efficient swallowing function in patients with MND.

Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

USGS Publications Warehouse

Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

2003-01-01

We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

The scale-dependent market trend: Empirical evidences using the lagged DFA method

NASA Astrophysics Data System (ADS)

Li, Daye; Kou, Zhun; Sun, Qiankun

2015-09-01

In this paper we make an empirical research and test the efficiency of 44 important market indexes in multiple scales. A modified method based on the lagged detrended fluctuation analysis is utilized to maximize the information of long-term correlations from the non-zero lags and keep the margin of errors small when measuring the local Hurst exponent. Our empirical result illustrates that a common pattern can be found in the majority of the measured market indexes which tend to be persistent (with the local Hurst exponent > 0.5) in the small time scale, whereas it displays significant anti-persistent characteristics in large time scales. Moreover, not only the stock markets but also the foreign exchange markets share this pattern. Considering that the exchange markets are only weakly synchronized with the economic cycles, it can be concluded that the economic cycles can cause anti-persistence in the large time scale but there are also other factors at work. The empirical result supports the view that financial markets are multi-fractal and it indicates that deviations from efficiency and the type of model to describe the trend of market price are dependent on the forecasting horizon.

Multiple scaling behaviour and nonlinear traits in music scores

PubMed Central

Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

2017-01-01

We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece. PMID:29308256

Multiple scaling behaviour and nonlinear traits in music scores

NASA Astrophysics Data System (ADS)

González-Espinoza, Alfredo; Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

2017-12-01

We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece.

Damage detection of structures with detrended fluctuation and detrended cross-correlation analyses

NASA Astrophysics Data System (ADS)

Lin, Tzu-Kang; Fajri, Haikal

2017-03-01

Recently, fractal analysis has shown its potential for damage detection and assessment in fields such as biomedical and mechanical engineering. For its practicability in interpreting irregular, complex, and disordered phenomena, a structural health monitoring (SHM) system based on detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA) is proposed. First, damage conditions can be swiftly detected by evaluating ambient vibration signals measured from a structure through DFA. Damage locations can then be determined by analyzing the cross correlation of signals of different floors by applying DCCA. A damage index is also proposed based on multi-scale DCCA curves to improve the damage location accuracy. To verify the performance of the proposed SHM system, a four-story numerical model was used to simulate various damage conditions with different noise levels. Furthermore, an experimental verification was conducted on a seven-story benchmark structure to assess the potential damage. The results revealed that the DFA method could detect the damage conditions satisfactorily, and damage locations can be identified through the DCCA method with an accuracy of 75%. Moreover, damage locations can be correctly assessed by the damage index method with an improved accuracy of 87.5%. The proposed SHM system has promising application in practical implementations.

Scale and time dependence of serial correlations in word-length time series of written texts

NASA Astrophysics Data System (ADS)

Rodriguez, E.; Aguilar-Cornejo, M.; Femat, R.; Alvarez-Ramirez, J.

2014-11-01

This work considered the quantitative analysis of large written texts. To this end, the text was converted into a time series by taking the sequence of word lengths. The detrended fluctuation analysis (DFA) was used for characterizing long-range serial correlations of the time series. To this end, the DFA was implemented within a rolling window framework for estimating the variations of correlations, quantified in terms of the scaling exponent, strength along the text. Also, a filtering derivative was used to compute the dependence of the scaling exponent relative to the scale. The analysis was applied to three famous English-written literary narrations; namely, Alice in Wonderland (by Lewis Carrol), Dracula (by Bram Stoker) and Sense and Sensibility (by Jane Austen). The results showed that high correlations appear for scales of about 50-200 words, suggesting that at these scales the text contains the stronger coherence. The scaling exponent was not constant along the text, showing important variations with apparent cyclical behavior. An interesting coincidence between the scaling exponent variations and changes in narrative units (e.g., chapters) was found. This suggests that the scaling exponent obtained from the DFA is able to detect changes in narration structure as expressed by the usage of words of different lengths.

Fatigue reduces the complexity of knee extensor torque fluctuations during maximal and submaximal intermittent isometric contractions in man

PubMed Central

Pethick, Jamie; Winter, Samantha L; Burnley, Mark

2015-01-01

Neuromuscular fatigue increases the amplitude of fluctuations in torque output during isometric contractions, but the effect of fatigue on the temporal structure, or complexity, of these fluctuations is not known. We hypothesised that fatigue would result in a loss of temporal complexity and a change in fractal scaling of the torque signal during isometric knee extensor exercise. Eleven healthy participants performed a maximal test (5 min of intermittent maximal voluntary contractions, MVCs), and a submaximal test (contractions at a target of 40% MVC performed until task failure), each with a 60% duty factor (6 s contraction, 4 s rest). Torque and surface EMG signals were sampled continuously. Complexity and fractal scaling of torque were quantified by calculating approximate entropy (ApEn), sample entropy (SampEn) and the detrended fluctuation analysis (DFA) scaling exponent α. Fresh submaximal contractions were more complex than maximal contractions (mean ± SEM, submaximal vs. maximal: ApEn 0.65 ± 0.09 vs. 0.15 ± 0.02; SampEn 0.62 ± 0.09 vs. 0.14 ± 0.02; DFA α 1.35 ± 0.04 vs. 1.55 ± 0.03; all P < 0.005). Fatigue reduced the complexity of submaximal contractions (ApEn to 0.24 ± 0.05; SampEn to 0.22 ± 0.04; DFA α to 1.55 ± 0.03; all P < 0.005) and maximal contractions (ApEn to 0.10 ± 0.02; SampEn to 0.10 ± 0.02; DFA α to 1.63 ± 0.02; all P < 0.01). This loss of complexity and shift towards Brownian-like noise suggests that as well as reducing the capacity to produce torque, fatigue reduces the neuromuscular system's adaptability to external perturbations. PMID:25664928

13 CFR 120.631 - Suspension or termination of Pool Assembler.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Suspension or termination. The D/FA may suspend a Pool Assembler from operating in the Secondary Market for... its fitness to participate in the Secondary Market. (b) Suspension procedures. The D/FA shall notify a... chapter. The action of the D/FA shall remain in effect pending resolution of the appeal. (c) Notice of...

13 CFR 120.631 - Suspension or termination of Pool Assembler.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Suspension or termination. The D/FA may suspend a Pool Assembler from operating in the Secondary Market for... its fitness to participate in the Secondary Market. (b) Suspension procedures. The D/FA shall notify a... chapter. The action of the D/FA shall remain in effect pending resolution of the appeal. (c) Notice of...

[Determination of the healing effect of Piper aduncum (spiked pepper or matico) on human fibroblasts].

PubMed

Paco, Karen; Ponce-Soto, Luis Alberto; Lopez-Ilasaca, Marco; Aguilar, José L

2016-01-01

To evaluate the healing effect of a Piper aduncum ethanol-water extract on an adult human dermal fibroblast cell line (hDFa). After obtaining the extract via solid-liquid extraction, concentration, and lyophilization, extract proteins were purified using reverse phase high-performance liquid chromatography, identified using tandem mass spectrometry of tryptic peptides, and analyzed using MALDI-TOF-TOF on an ABSciex4800 mass spectrometer. Half maximum effective concentration values (EC50), half maximum inhibiting concentration (IC50), and percentages of cell proliferation were determined using tetrazolium salt assays. Cell migration was evaluated using a "scratch assay". Growth factor expression in cells was analyzed via quantitative real-time reverse transcription polymerase chain reaction. Against the hDFa cell line, the extract had an IC50 of 200 μg/mL and EC50 of 103.5 µg/mL. In the proliferation assay, protein K2 (obtained from the extract) exhibited increased proliferative activity relative to other treatments (1 µg/mL); this agent also exhibited increased activity (50 µg/mL) in the fibroblast migration assay.Furthermore, the relative expression of platelet-derived growth factor increased by 8.6-fold in the presence of K2 protein relative to the control. The hydroethanolic extract of Piper aduncum and its component proteins increased the proliferation and migration of hDFa and increased the expression of growth factors involved in the healing process.

Volatilities, Traded Volumes, and Price Increments in Derivative Securities

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Lim, Gyuchang; Kim, Soo Yong; Scalas, Enrico

2007-03-01

We apply the detrended fluctuation analysis (DFA) to the statistics of the Korean treasury bond (KTB) futures from which the logarithmic increments, volatilities, and traded volumes are estimated over a specific time lag. For our case, the logarithmic increment of futures prices has no long-memory property, while the volatility and the traded volume exhibit the existence of long-memory property. To analyze and calculate whether the volatility clustering is due to the inherent higher-order correlation not detected by applying directly the DFA to logarithmic increments of the KTB futures, it is of importance to shuffle the original tick data of futures prices and to generate the geometric Brownian random walk with the same mean and standard deviation. It is really shown from comparing the three tick data that the higher-order correlation inherent in logarithmic increments makes the volatility clustering. Particularly, the result of the DFA on volatilities and traded volumes may be supported the hypothesis of price changes.

Volatilities, traded volumes, and the hypothesis of price increments in derivative securities

NASA Astrophysics Data System (ADS)

Lim, Gyuchang; Kim, SooYong; Scalas, Enrico; Kim, Kyungsik

2007-08-01

A detrended fluctuation analysis (DFA) is applied to the statistics of Korean treasury bond (KTB) futures from which the logarithmic increments, volatilities, and traded volumes are estimated over a specific time lag. In this study, the logarithmic increment of futures prices has no long-memory property, while the volatility and the traded volume exhibit the existence of the long-memory property. To analyze and calculate whether the volatility clustering is due to a inherent higher-order correlation not detected by with the direct application of the DFA to logarithmic increments of KTB futures, it is of importance to shuffle the original tick data of future prices and to generate a geometric Brownian random walk with the same mean and standard deviation. It was found from a comparison of the three tick data that the higher-order correlation inherent in logarithmic increments leads to volatility clustering. Particularly, the result of the DFA on volatilities and traded volumes can be supported by the hypothesis of price changes.

Serum chemistry reference ranges for Steller sea lion (Eumetopias jubatus) pups from Alaska: stock differentiation and comparisons within a North Pacific sentinel species.

PubMed

Lander, Michelle E; Fadely, Brian S; Gelatt, Thomas S; Rea, Lorrie D; Loughlin, Thomas R

2013-12-01

Blood chemistry and hematologic reference ranges are useful for population health assessment and establishing a baseline for future comparisons in the event of ecosystem changes due to natural or anthropogenic factors. The objectives of this study were to determine if there was any population spatial structure for blood variables of Steller sea lion (Eumetopias jubatus), an established sentinel species, and to report reference ranges for appropriate populations using standardized analyses. In addition to comparing reference ranges between populations with contrasting abundance trends, data were examined for evidence of disease or nutritional stress. From 1998 to 2011, blood samples were collected from 1,231 pups captured on 37 rookeries across their Alaskan range. Reference ranges are reported separately for the western and eastern distinct population segments (DPS) of Steller sea lion after cluster analysis and discriminant function analysis (DFA) supported underlying stock structure. Variables with greater loading scores for the DFA (creatinine, total protein, calcium, albumin, cholesterol, and alkaline phosphatase) also were greater for sea lions from the endangered western DPS, supporting previous studies that indicated pup condition in the west was not compromised during the first month postpartum. Differences between population segments were likely a result of ecological, physiological, or age related differences.

New approach for rapid assessment of trophic status of Yellow Sea and East China Sea using easy-to-measure parameters

NASA Astrophysics Data System (ADS)

Kong, Xianyu; Liu, Yanfang; Jian, Huimin; Su, Rongguo; Yao, Qingzhen; Shi, Xiaoyong

2017-10-01

To realize potential cost savings in coastal monitoring programs and provide timely advice for marine management, there is an urgent need for efficient evaluation tools based on easily measured variables for the rapid and timely assessment of estuarine and offshore eutrophication. In this study, using parallel factor analysis (PARAFAC), principal component analysis (PCA), and discriminant function analysis (DFA) with the trophic index (TRIX) for reference, we developed an approach for rapidly assessing the eutrophication status of coastal waters using easy-to-measure parameters, including chromophoric dissolved organic matter (CDOM), fluorescence excitation-emission matrices, CDOM UV-Vis absorbance, and other water-quality parameters (turbidity, chlorophyll a, and dissolved oxygen). First, we decomposed CDOM excitation-emission matrices (EEMs) by PARAFAC to identify three components. Then, we applied PCA to simplify the complexity of the relationships between the water-quality parameters. Finally, we used the PCA score values as independent variables in DFA to develop a eutrophication assessment model. The developed model yielded classification accuracy rates of 97.1%, 80.5%, 90.3%, and 89.1% for good, moderate, and poor water qualities, and for the overall data sets, respectively. Our results suggest that these easy-to-measure parameters could be used to develop a simple approach for rapid in-situ assessment and monitoring of the eutrophication of estuarine and offshore areas.

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

Dental fear and anxiety in children and adolescents: qualitative study using YouTube.

PubMed

Gao, Xiaoli; Hamzah, S H; Yiu, Cynthia Kar Yung; McGrath, Colman; King, Nigel M

2013-02-22

Dental fear and anxiety (DFA) refers to the fear of and anxiety towards going to the dentist. It exists in a considerable proportion of children and adolescents and is a major dilemma in pediatric dental practice. As an Internet social medium with increasing popularity, the video-sharing website YouTube offers a useful data source for understanding health behaviors and perceptions of the public. Using YouTube as a platform, this qualitative study aimed to examine the manifestations, impacts, and origins of DFA in children and adolescents from the public's perspective. To retrieve relevant information, we searched YouTube using the keywords "dental fear", "dental anxiety", and "dental phobia". Videos in English expressing a layperson's views or experience on children's or adolescent's DFA were selected for this study. A video was excluded if it had poor audiovisual quality, was irrelevant, was pure advertisement or entertainment, or contained only the views of professionals. After the screen, we transcribed 27 videos involving 32 children and adolescents, which were reviewed by a panel of 3 investigators, including a layperson with no formal dental training. Inductive thematic analysis was applied for coding and interpreting the data. The videos revealed multiple manifestations and impacts of DFA, including immediate physical reactions (eg, crying, screaming, and shivering), psychological responses (eg, worry, upset, panic, helplessness, insecurity, resentment, and hatred), and uncooperativeness in dental treatment. Testimonials from children, adolescents, and their parents suggested diverse origins of DFA, namely personal experience (eg, irregular dental visits and influence of parents or peers), dentists and dental auxiliaries (eg, bad manner, lack of clinical skills, and improper work ethic), dental settings (eg, dental chair and sounds), and dental procedures (eg, injections, pain, discomfort, and aesthetic concerns). This qualitative study suggests that DFA in

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Should Varicella-Zoster Virus Culture Be Eliminated? A Comparison of Direct Immunofluorescence Antigen Detection, Culture, and PCR, with a Historical Review

PubMed Central

Wilson, D. A.; Yen-Lieberman, B.; Schindler, S.; Asamoto, K.; Schold, J. D.

2012-01-01

A comparison of direct fluorescent-antibody assay (DFA), culture, and two PCR assays disclosed sensitivities of 87.8%, 46.3%, and 97.6% and 100%, respectively. We reviewed 1,150 results for clinical specimens submitted for DFA and culture and found that only 17 were culture positive/DFA negative. The incremental cost to detect these 17 positives was $3,078/specimen. PMID:23035203

Should varicella-zoster virus culture be eliminated? A comparison of direct immunofluorescence antigen detection, culture, and PCR, with a historical review.

PubMed

Wilson, D A; Yen-Lieberman, B; Schindler, S; Asamoto, K; Schold, J D; Procop, G W

2012-12-01

A comparison of direct fluorescent-antibody assay (DFA), culture, and two PCR assays disclosed sensitivities of 87.8%, 46.3%, and 97.6% and 100%, respectively. We reviewed 1,150 results for clinical specimens submitted for DFA and culture and found that only 17 were culture positive/DFA negative. The incremental cost to detect these 17 positives was $3,078/specimen.

Anthropometric data reduction using confirmatory factor analysis.

PubMed

Rohani, Jafri Mohd; Olusegun, Akanbi Gabriel; Rani, Mat Rebi Abdul

2014-01-01

The unavailability of anthropometric data especially in developing countries has remained a limiting factor towards the design of learning facilities with sufficient ergonomic consideration. Attempts to use anthropometric data from developed countries have led to provision of school facilities unfit for the users. The purpose of this paper is to use factor analysis to investigate the suitability of the collected anthropometric data as a database for school design in Nigerian tertiary institutions. Anthropometric data were collected from 288 male students in a Federal Polytechnic in North-West of Nigeria. Their age is between 18-25 years. Nine vertical anthropometric dimensions related to heights were collected using the conventional traditional equipment. Exploratory factor analysis was used to categorize the variables into a model consisting of two factors. Thereafter, confirmatory factor analysis was used to investigate the fit of the data to the proposed model. A just identified model, made of two factors, each with three variables was developed. The variables within the model accounted for 81% of the total variation of the entire data. The model was found to demonstrate adequate validity and reliability. Various measuring indices were used to verify that the model fits the data properly. The final model reveals that stature height and eye height sitting were the most stable variables for designs that have to do with standing and sitting construct. The study has shown the application of factor analysis in anthropometric data analysis. The study highlighted the relevance of these statistical tools to investigate variability among anthropometric data involving diverse population, which has not been widely used for analyzing previous anthropometric data. The collected data is therefore suitable for use while designing for Nigerian students.

Comparisons of Exploratory and Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Daniel, Larry G.

Historically, most researchers conducting factor analysis have used exploratory methods. However, more recently, confirmatory factor analytic methods have been developed that can directly test theory either during factor rotation using "best fit" rotation methods or during factor extraction, as with the LISREL computer programs developed…

An electroglottographical analysis-based discriminant function model differentiating multiple sclerosis patients from healthy controls.

PubMed

Vavougios, George D; Doskas, Triantafyllos; Konstantopoulos, Kostas

2018-05-01

Dysarthrophonia is a predominant symptom in many neurological diseases, affecting the quality of life of the patients. In this study, we produced a discriminant function equation that can differentiate MS patients from healthy controls, using electroglottographic variables not analyzed in a previous study. We applied stepwise linear discriminant function analysis in order to produce a function and score derived from electroglottographic variables extracted from a previous study. The derived discriminant function's statistical significance was determined via Wilk's λ test (and the associated p value). Finally, a 2 × 2 confusion matrix was used to determine the function's predictive accuracy, whereas the cross-validated predictive accuracy is estimated via the "leave-one-out" classification process. Discriminant function analysis (DFA) was used to create a linear function of continuous predictors. DFA produced the following model (Wilk's λ = 0.043, χ2 = 388.588, p < 0.0001, Tables 3 and 4): D (MS vs controls) = 0.728*DQx1 mean monologue + 0.325*CQx monologue + 0.298*DFx1 90% range monologue + 0.443*DQx1 90% range reading - 1.490*DQx1 90% range monologue. The derived discriminant score (S1) was used subsequently in order to form the coordinates of a ROC curve. Thus, a cutoff score of - 0.788 for S1 corresponded to a perfect classification (100% sensitivity and 100% specificity, p = 1.67e -22 ). Consistent with previous findings, electroglottographic evaluation represents an easy to implement and potentially important assessment in MS patients, achieving adequate classification accuracy. Further evaluation is needed to determine its use as a biomarker.

Quantitative evaluation of dual-flip-angle T1 mapping on DCE-MRI kinetic parameter estimation in head and neck

PubMed Central

Chow, Steven Kwok Keung; Yeung, David Ka Wai; Ahuja, Anil T; King, Ann D

2012-01-01

Purpose To quantitatively evaluate the kinetic parameter estimation for head and neck (HN) dynamic contrast-enhanced (DCE) MRI with dual-flip-angle (DFA) T1 mapping. Materials and methods Clinical DCE-MRI datasets of 23 patients with HN tumors were included in this study. T1 maps were generated based on multiple-flip-angle (MFA) method and different DFA combinations. Tofts model parameter maps of kep, Ktrans and vp based on MFA and DFAs were calculated and compared. Fitted parameter by MFA and DFAs were quantitatively evaluated in primary tumor, salivary gland and muscle. Results T1 mapping deviations by DFAs produced remarkable kinetic parameter estimation deviations in head and neck tissues. In particular, the DFA of [2º, 7º] overestimated, while [7º, 12º] and [7º, 15º] underestimated Ktrans and vp, significantly (P<0.01). [2º, 15º] achieved the smallest but still statistically significant overestimation for Ktrans and vp in primary tumors, 32.1% and 16.2% respectively. kep fitting results by DFAs were relatively close to the MFA reference compared to Ktrans and vp. Conclusions T1 deviations induced by DFA could result in significant errors in kinetic parameter estimation, particularly Ktrans and vp, through Tofts model fitting. MFA method should be more reliable and robust for accurate quantitative pharmacokinetic analysis in head and neck. PMID:23289084

Bootstrap Standard Error Estimates in Dynamic Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Browne, Michael W.

2010-01-01

Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the…

Targeting L-Selectin to Improve Neurologic and Urologic Function After Spinal Cord Injury

DTIC Science & Technology

2015-10-01

demonstrated locomotor recovery in mice receiving 40mg/kg DFA up to 3 hours following spinal cord injury -We demonstrated improved locomotor recovery...health, as evaluated by body weight -We identified no added locomotor recovery due to multiple, successive doses of DFA. Moreover, additional doses...bladder function Significance: We have identified robust locomotor recovery in both mild and severe spinal cord injured mice that received DFA up

How Factor Analysis Can Be Used in Classification.

ERIC Educational Resources Information Center

Harman, Harry H.

This is a methodological study that suggests a taxometric technique for objective classification of yeasts. It makes use of the minres method of factor analysis and groups strains of yeast according to their factor profiles. The similarities are judged in the higher-dimensional space determined by the factor analysis, but otherwise rely on the…

Bridge effects on light harvesting of a DBfA type polymer system

NASA Astrophysics Data System (ADS)

Sun, Sam-Shajing; Hasib, Muhammad; Gavrilenko, Alexander V.; Devan, Joshua; Gavrilenko, Vladimir

2016-09-01

Plastic optoelectronic materials and thin film devices are very attractive in future optical sensor and solar energy applications due to their lightweight, flexible shape, high photon absorption coefficients, low cost, and environmental benefits. In this study, optoelectronic properties of D, D/fA blend, DfA, and a series of DBfA type of conjugated block copolymers has been investigated, where D is a donor type PPV conjugated block, B is a non-conjugated and flexible aliphatic hydrocarbon bridge chain containing different number of aliphatic methylene units, and fA is a fluorinated acceptor type PPV conjugated block. The optical absorptions of the D/fA blend, DfA, and DBfAs are typical overlaps of individual absorptions of D and fA blocks, while the solution steady state photoluminescence (PL) emission of D were quenched to different levels in blends and block copolymers, with DBfAs containing one methylene unit bridge (DB1fA) quenched most. This could be attributed to an intra-molecular photo induced electron transfer or charge separation in DBfA systems. Theoretical first principles study of the equilibrium atomic configuration of DfA reveals the existence of twisting angles between the D and fA blocks in DfA stable states which may account for a less PL quenching of DfA as compared to DB1fA. These results are important for designing and developing high efficiency polymer based optoelectronic systems.

Multifractal analysis of managed and independent float exchange rates

NASA Astrophysics Data System (ADS)

Stošić, Darko; Stošić, Dusan; Stošić, Tatijana; Stanley, H. Eugene

2015-06-01

We investigate multifractal properties of daily price changes in currency rates using the multifractal detrended fluctuation analysis (MF-DFA). We analyze managed and independent floating currency rates in eight countries, and determine the changes in multifractal spectrum when transitioning between the two regimes. We find that after the transition from managed to independent float regime the changes in multifractal spectrum (position of maximum and width) indicate an increase in market efficiency. The observed changes are more pronounced for developed countries that have a well established trading market. After shuffling the series, we find that the multifractality is due to both probability density function and long term correlations for managed float regime, while for independent float regime multifractality is in most cases caused by broad probability density function.

Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

PubMed

Zebende, Gilney Figueira; Oliveira Filho, Florêncio Mendes; Leyva Cruz, Juan Alberto

2017-01-01

In this paper we analyzed, by the FDFA root mean square fluctuation (rms) function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG). We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA) method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head) and P349, P654 (parietal region of the head). We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale) for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Fan, Qingju; Wu, Yonghong

2015-08-01

In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.

A Review of CEFA Software: Comprehensive Exploratory Factor Analysis Program

ERIC Educational Resources Information Center

Lee, Soon-Mook

2010-01-01

CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…

Fractal analysis of the ambulation pattern of Japanese quail.

PubMed

Kembro, J M; Perillo, M A; Pury, P A; Satterlee, D G; Marín, R H

2009-03-01

1. The study examined the practicality and usefulness of fractal analyses in evaluating the temporal organisation of avian ambulatory behaviour by using female Japanese quail in their home boxes as the model system. To induce two locomotion activity levels, we tested half of the birds without disturbance (Unstimulated) and the other half when food was scattered on the floor of the home box after 3 h of feeder withdrawal (Stimulated). 2. Ambulatory activity was recorded during 40 min at a resolution of 1 s and evaluated by: (1) detrended fluctuation analyses (DFA), (2) the frequency distribution of the duration of the walking or non-walking events (FDD-W or FDD-NW, respectively), and (3) the transition probabilities between walking/non-walking states. Conventional measures of total time spent walking and average duration of the walking/non-walking events were also employed. 3. DFA showed a decreased value of the self-similarity parameter (alpha; indicative of a more complex ambulatory pattern) in Stimulated birds compared to their Unstimulated counterparts. The FDD-NW showed a more negative scaling factor in Stimulated than in Unstimulated birds. Stimulated birds also had more transitions between non-walking and walking states, consistent with stimulated exploratory activity. No differences were found between groups in the FDD-W, in percentage of total time spent walking, or in average duration of the walking events. 4. The temporal walking pattern of female Japanese quail has a fractal structure and its organisation and complexity is altered when birds are stimulated to explore. The fractal analyses detected differences between the Unstimulated and Stimulated groups that went undetected by the traditional measurements of the percentage of total time spent walking and the duration of the walking events suggesting its usefulness as a tool for behavioural studies.

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics.

PubMed

Kumar, Deepak; Gupta, Ashish; Mandhani, Anil; Sankhwar, Satya Narain

2016-09-01

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH. The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort. DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH. (1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Patients' Reactions to Local Anaesthetic Application Devices in Paediatric Dentistry.

PubMed

Bajrić, Elmedin; Kobasglija, Sedin; Jurić, Hrvoje

2015-09-01

Local anaesthesia is the most common medium for pain control in most dental treatments. Physical appearance of syringe itself can be considered as a provoking factor for the emergence of dental fear and anxiety (DFA). In this research the patient reactions to local anaesthesia application devices, as one of the main causes for DFA emergence, were inquired. The sample comprised of 120 patients, divided in three age groups, formed of 40 patients aged 8, 12 and 15 years. DFA prevalence was quantified by Children Fear Survey Schedule-Dental Subscale (CFSS-DS). Three different syringes were offered to the patients. Reasons for choosing one of the syringes were detected. Patients assigned statistically highest rank to plastic syringe. Boys chose metal and intraligamental syringe statistically more often than girls. Patients with higher CFSS-DS scores chose metal syringe as last option. None of the reasons for selection was dominant, except pain that could be caused by usage of any of the three syringes. A large number of patients did not mention any of the reasons for choosing particular syringes. Plastic syringe represented the most acceptable device for local anaesthetic application to our patients. Patients often linked pain with dental syringes.

Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis

NASA Astrophysics Data System (ADS)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. The college students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. However, the results of the exploratory factor analysis indicated that the questionnaire could be revised to improve its construct validity. The goal of this study was to revise the questionnaire and establish its construct validity through a confirmatory factor analysis. In addition, a Rasch analysis was applied to the data to better understand the psychometric properties of the inventory and to further evaluate the construct validity. Results indicated that the final, revised inventory is a valid, reliable, and efficient tool for assessing student metacognition for physics problem solving.

A comparison study on detection of key geochemical variables and factors through three different types of factor analysis

NASA Astrophysics Data System (ADS)

Hoseinzade, Zohre; Mokhtari, Ahmad Reza

2017-10-01

Large numbers of variables have been measured to explain different phenomena. Factor analysis has widely been used in order to reduce the dimension of datasets. Additionally, the technique has been employed to highlight underlying factors hidden in a complex system. As geochemical studies benefit from multivariate assays, application of this method is widespread in geochemistry. However, the conventional protocols in implementing factor analysis have some drawbacks in spite of their advantages. In the present study, a geochemical dataset including 804 soil samples collected from a mining area in central Iran in order to search for MVT type Pb-Zn deposits was considered to outline geochemical analysis through various fractal methods. Routine factor analysis, sequential factor analysis, and staged factor analysis were applied to the dataset after opening the data with (additive logratio) alr-transformation to extract mineralization factor in the dataset. A comparison between these methods indicated that sequential factor analysis has more clearly revealed MVT paragenesis elements in surface samples with nearly 50% variation in F1. In addition, staged factor analysis has given acceptable results while it is easy to practice. It could detect mineralization related elements while larger factor loadings are given to these elements resulting in better pronunciation of mineralization.

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

Cross-correlations between RMB exchange rate and international commodity markets

NASA Astrophysics Data System (ADS)

Lu, Xinsheng; Li, Jianfeng; Zhou, Ying; Qian, Yubo

2017-11-01

This paper employs multifractal detrended analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) to study cross-correlation behaviors between China's RMB exchange rate market and four international commodity markets, using a comprehensive set of data covering the period from 22 July 2005 to 15 March 2016. Our empirical results from MF-DFA indicate that the RMB exchange rate is the most inefficient among the 4 selected markets. The results from quantitative analysis have testified the existence of cross-correlations and the result from MF-DCCA have further confirmed a strong multifractal behavior between RMB exchange rate and international commodity markets. We also demonstrate that the recent financial crisis has significant impact on the cross-correlated behavior. Through the rolling window analysis, we find that the RMB exchange rates and international commodity prices are anti-persistent cross-correlated. The main sources of multifractality in the cross-correlations are long-range correlations between RMB exchange rate and the aggregate commodity, energy and metals index.

Variations in task constraints shape emergent performance outcomes and complexity levels in balancing.

PubMed

Caballero Sánchez, Carla; Barbado Murillo, David; Davids, Keith; Moreno Hernández, Francisco J

2016-06-01

This study investigated the extent to which specific interacting constraints of performance might increase or decrease the emergent complexity in a movement system, and whether this could affect the relationship between observed movement variability and the central nervous system's capacity to adapt to perturbations during balancing. Fifty-two healthy volunteers performed eight trials where different performance constraints were manipulated: task difficulty (three levels) and visual biofeedback conditions (with and without the center of pressure (COP) displacement and a target displayed). Balance performance was assessed using COP-based measures: mean velocity magnitude (MVM) and bivariate variable error (BVE). To assess the complexity of COP, fuzzy entropy (FE) and detrended fluctuation analysis (DFA) were computed. ANOVAs showed that MVM and BVE increased when task difficulty increased. During biofeedback conditions, individuals showed higher MVM but lower BVE at the easiest level of task difficulty. Overall, higher FE and lower DFA values were observed when biofeedback was available. On the other hand, FE reduced and DFA increased as difficulty level increased, in the presence of biofeedback. However, when biofeedback was not available, the opposite trend in FE and DFA values was observed. Regardless of changes to task constraints and the variable investigated, balance performance was positively related to complexity in every condition. Data revealed how specificity of task constraints can result in an increase or decrease in complexity emerging in a neurobiological system during balance performance.

Dental Fear and Anxiety in Children and Adolescents: Qualitative Study Using YouTube

PubMed Central

Hamzah, SH; Yiu, Cynthia Kar Yung; McGrath, Colman; King, Nigel M

2013-01-01

Background Dental fear and anxiety (DFA) refers to the fear of and anxiety towards going to the dentist. It exists in a considerable proportion of children and adolescents and is a major dilemma in pediatric dental practice. As an Internet social medium with increasing popularity, the video-sharing website YouTube offers a useful data source for understanding health behaviors and perceptions of the public. Objective Using YouTube as a platform, this qualitative study aimed to examine the manifestations, impacts, and origins of DFA in children and adolescents from the public’s perspective. Methods To retrieve relevant information, we searched YouTube using the keywords “dental fear”, “dental anxiety”, and “dental phobia”. Videos in English expressing a layperson’s views or experience on children’s or adolescent’s DFA were selected for this study. A video was excluded if it had poor audiovisual quality, was irrelevant, was pure advertisement or entertainment, or contained only the views of professionals. After the screen, we transcribed 27 videos involving 32 children and adolescents, which were reviewed by a panel of 3 investigators, including a layperson with no formal dental training. Inductive thematic analysis was applied for coding and interpreting the data. Results The videos revealed multiple manifestations and impacts of DFA, including immediate physical reactions (eg, crying, screaming, and shivering), psychological responses (eg, worry, upset, panic, helplessness, insecurity, resentment, and hatred), and uncooperativeness in dental treatment. Testimonials from children, adolescents, and their parents suggested diverse origins of DFA, namely personal experience (eg, irregular dental visits and influence of parents or peers), dentists and dental auxiliaries (eg, bad manner, lack of clinical skills, and improper work ethic), dental settings (eg, dental chair and sounds), and dental procedures (eg, injections, pain, discomfort, and

Investigation of the prevalence of Legionella species in domestic hot water systems.

PubMed

Bates, M N; Maas, E; Martin, T; Harte, D; Grubner, M; Margolin, T

2000-06-09

To investigate the prevalence of Legionella spp. in the hot water systems of a representative sample of Wellington domestic residences with electrically heated hot water systems, and to investigate risk factors (eg water temperature, plumbing materials) for such contamination. 100 households with electrically heated hot water systems in the Wellington area were investigated. Samples of hot water from several hot water outlets were collected, and characteristics of the plumbing system were recorded. Water samples and swabs were cultured and further examined by polymerase chain reaction (PCR) and direct fluorescence antibody (DFA) testing to identify Legionella spp. and serogroups. No Legionella spp. were isolated by culture. PCR tested positive for Legionella in specimens from twelve residences. Six of these were also positive by DFA testing. The only environmental factor found to be associated with the presence of Legionella was recent plumbing work on the hot water system. Five of the twelve PCR-positive residences, and four of the six DFA-confirmed residences had hot water delivery temperatures in excess of 60 degrees C. The results suggest that either Legionellae colonise domestic hot water reticulation systems and/or that the organisms are killed during passage through the hot water tank. Both possibilities may be correct. Further work to characterise the microbial ecology of Legionella-positive hot water distribution systems would be useful, as would the development of improved methods for culturing the organisms from potable water.

Using BMDP and SPSS for a Q factor analysis.

PubMed

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Likelihood-Based Confidence Intervals in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Oort, Frans J.

2011-01-01

In exploratory or unrestricted factor analysis, all factor loadings are free to be estimated. In oblique solutions, the correlations between common factors are free to be estimated as well. The purpose of this article is to show how likelihood-based confidence intervals can be obtained for rotated factor loadings and factor correlations, by…

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

Entrainment to a real time fractal visual stimulus modulates fractal gait dynamics.

PubMed

Rhea, Christopher K; Kiefer, Adam W; D'Andrea, Susan E; Warren, William H; Aaron, Roy K

2014-08-01

Fractal patterns characterize healthy biological systems and are considered to reflect the ability of the system to adapt to varying environmental conditions. Previous research has shown that fractal patterns in gait are altered following natural aging or disease, and this has potential negative consequences for gait adaptability that can lead to increased risk of injury. However, the flexibility of a healthy neurological system to exhibit different fractal patterns in gait has yet to be explored, and this is a necessary step toward understanding human locomotor control. Fifteen participants walked for 15min on a treadmill, either in the absence of a visual stimulus or while they attempted to couple the timing of their gait with a visual metronome that exhibited a persistent fractal pattern (contained long-range correlations) or a random pattern (contained no long-range correlations). The stride-to-stride intervals of the participants were recorded via analog foot pressure switches and submitted to detrended fluctuation analysis (DFA) to determine if the fractal patterns during the visual metronome conditions differed from the baseline (no metronome) condition. DFA α in the baseline condition was 0.77±0.09. The fractal patterns in the stride-to-stride intervals were significantly altered when walking to the fractal metronome (DFA α=0.87±0.06) and to the random metronome (DFA α=0.61±0.10) (both p<.05 when compared to the baseline condition), indicating that a global change in gait dynamics was observed. A variety of strategies were identified at the local level with a cross-correlation analysis, indicating that local behavior did not account for the consistent global changes. Collectively, the results show that a gait dynamics can be shifted in a prescribed manner using a visual stimulus and the shift appears to be a global phenomenon. Copyright © 2014 Elsevier B.V. All rights reserved.

Hippotherapy acute impact on heart rate variability non-linear dynamics in neurological disorders.

PubMed

Cabiddu, Ramona; Borghi-Silva, Audrey; Trimer, Renata; Trimer, Vitor; Ricci, Paula Angélica; Italiano Monteiro, Clara; Camargo Magalhães Maniglia, Marcela; Silva Pereira, Ana Maria; Rodrigues das Chagas, Gustavo; Carvalho, Eliane Maria

2016-05-15

Neurological disorders are associated with autonomic dysfunction. Hippotherapy (HT) is a therapy treatment strategy that utilizes a horse in an interdisciplinary approach for the physical and mental rehabilitation of people with physical, mental and/or psychological disabilities. However, no studies have been carried out which evaluated the effects of HT on the autonomic control in these patients. Therefore, the objective of the present study was to investigate the effects of a single HT session on cardiovascular autonomic control by time domain and non-linear analysis of heart rate variability (HRV). The HRV signal was recorded continuously in twelve children affected by neurological disorders during a HT session, consisting in a 10-minute sitting position rest (P1), a 15-minute preparatory phase sitting on the horse (P2), a 15-minute HT session (P3) and a final 10-minute sitting position recovery (P4). Time domain and non-linear HRV indices, including Sample Entropy (SampEn), Lempel-Ziv Complexity (LZC) and Detrended Fluctuation Analysis (DFA), were calculated for each treatment phase. We observed that SampEn increased during P3 (SampEn=0.56±0.10) with respect to P1 (SampEn=0.40±0.14, p<0.05), while DFA decreased during P3 (DFA=1.10±0.10) with respect to P1 (DFA=1.26±0.14, p<0.05). A significant SDRR increase (p<0.05) was observed during the recovery period P4 (SDRR=50±30ms) with respect to the HT session period P3 (SDRR=30±10ms). Our results suggest that HT might benefit children with disabilities attributable to neurological disorders by eliciting an acute autonomic response during the therapy and during the recovery period. Copyright © 2016 Elsevier Inc. All rights reserved.

Biofeedback training effects on minimum toe clearance variability during treadmill walking.

PubMed

Tirosh, Oren; Cambell, Amity; Begg, Rezaul K; Sparrow, W A

2013-08-01

A number of variability analysis techniques, including Poincaré plots and detrended fluctuation analysis (DFA) were used to investigate minimum toe clearance (MTC) control during walking. Ten young adults walked on a treadmill for 10 min at preferred speed in three conditions: (i) no-intervention baseline, (ii) with biofeedback of MTC within a target range, and (iii) no-biofeedback retention. Mean, median, standard deviation (SD), and inter quartile range of MTC during biofeedback (45.57 ± 11.65, 44.98 ± 11.57, 7.08 ± 2.61, 8.58 ± 2.77 mm, respectively) and retention (56.95 ± 20.31, 56.69 ± 20.94, 10.68 ± 5.41, 15.38 ± 10.19 mm) were significantly greater than baseline (30.77 ± 9.49, 30.51 ± 9.49, 3.04 ± 0.77, 3.66 ± 0.91 mm). Relative to baseline, skewness was reduced in biofeedback and retention but only significantly for retention (0.88 ± 0.51, 0.63 ± 0.55, and 0.40 ± 0.40, respectively). Baseline Poincaré measures (SD1 = 0.25, SD2 = 0.34) and DFA (α1 = 0.72 and α2 = 0.64) were lower than biofeedback (SD1 = 0.58, SD2 = 0.83, DFA α1 = 0.76 and α2 = 0.92) with significantly greater variability in retention compared to biofeedback only in the long-term SD2 and α2 analyses. Increased DFA longer-term correlations α2 in retention confirm that a novel gait pattern was acquired with a longer-term variability structure. Short- and long-term variability analyses were both useful in quantifying gait adaptations with biofeedback. The findings provide evidence that MTC can be modified with feedback, suggesting future applications in gait training procedures for impaired populations designed to reduce tripping risk.

What School Psychologists Need to Know about Factor Analysis

ERIC Educational Resources Information Center

McGill, Ryan J.; Dombrowski, Stefan C.

2017-01-01

Factor analysis is a versatile class of psychometric techniques used by researchers to provide insight into the psychological dimensions (factors) that may account for the relationships among variables in a given dataset. The primary goal of a factor analysis is to determine a more parsimonious set of variables (i.e., fewer than the number of…

Item Factor Analysis: Current Approaches and Future Directions

ERIC Educational Resources Information Center

Wirth, R. J.; Edwards, Michael C.

2007-01-01

The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA)…

Q-Type Factor Analysis of Healthy Aged Men.

ERIC Educational Resources Information Center

Kleban, Morton H.

Q-type factor analysis was used to re-analyze baseline data collected in 1957, on 47 men aged 65-91. Q-type analysis is the use of factor methods to study persons rather than tests. Although 550 variables were originally studied involving psychiatry, medicine, cerebral metabolism and chemistry, personality, audiometry, dichotic and diotic memory,…

Evaluation of a PCR/ESI-MS platform to identify respiratory viruses from nasopharyngeal aspirates.

PubMed

Lin, Yong; Fu, Yongfeng; Xu, Menghua; Su, Liyun; Cao, Lingfeng; Xu, Jin; Cheng, Xunjia

2015-11-01

Acute respiratory tract infection is a major cause of morbidity and mortality worldwide, particularly in infants and young children. High-throughput, accurate, broad-range tools for etiologic diagnosis are critical for effective epidemic control. In this study, the diagnostic capacities of an Ibis platform based on the PCR/ESI-MS assay were evaluated using clinical samples. Nasopharyngeal aspirates (NPAs) were collected from 120 children (<5 years old) who were hospitalized with lower respiratory tract infections between November 2010 and October 2011. The respiratory virus detection assay was performed using the PCR/ESI-MS assay and the DFA. The discordant PCR/ESI-MS and DFA results were resolved with RT-PCR plus sequencing. The overall agreement for PCR/ESI-MS and DFA was 98.3% (118/120). Compared with the results from DFA, the sensitivity and specificity of the PCR/ESI-MS assay were 100% and 97.5%, respectively. The PCR/ESI-MS assay also detected more multiple virus infections and revealed more detailed subtype information than DFA. Among the 12 original specimens with discordant results between PCR/ESI-MS and DFA, 11 had confirmed PCR/ESI-MS results. Thus, the PCR/ESI-MS assay is a high-throughput, sensitive, specific and promising method to detect and subtype conventional viruses in respiratory tract infections and allows rapid identification of mixed pathogens. © 2015 Wiley Periodicals, Inc.

Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Mixture Factor Analysis for Approximating a Nonnormally Distributed Continuous Latent Factor with Continuous and Dichotomous Observed Variables

ERIC Educational Resources Information Center

Wall, Melanie M.; Guo, Jia; Amemiya, Yasuo

2012-01-01

Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus…

Designing Knowledge Scaffolds to Support Mathematical Problem Solving

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Koedinger, Kenneth R.

2005-01-01

We present a methodology for designing better learning environments. In Phase 1, 6th-grade students' (n = 223) prior knowledge was assessed using a difficulty factors assessment (DFA). The assessment revealed that scaffolds designed to elicit contextual, conceptual, or procedural knowledge each improved students' ability to add and subtract…

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Non-linear characteristics and long-range correlations in Asian stock markets

NASA Astrophysics Data System (ADS)

Jiang, J.; Ma, K.; Cai, X.

2007-05-01

We test several non-linear characteristics of Asian stock markets, which indicates the failure of efficient market hypothesis and shows the essence of fractal of the financial markets. In addition, by using the method of detrended fluctuation analysis (DFA) to investigate the long range correlation of the volatility in the stock markets, we find that the crossover phenomena exist in the results of DFA. Further, in the region of small volatility, the scaling behavior is more complicated; in the region of large volatility, the scaling exponent is close to 0.5, which suggests the market is more efficient. All these results may indicate the possibility of characteristic multifractal scaling behaviors of the financial markets.

Environmentally driven synchronies of Mediterranean cephalopod populations

NASA Astrophysics Data System (ADS)

Keller, Stefanie; Quetglas, Antoni; Puerta, Patricia; Bitetto, Isabella; Casciaro, Loredana; Cuccu, Danila; Esteban, Antonio; Garcia, Cristina; Garofalo, Germana; Guijarro, Beatriz; Josephides, Marios; Jadaud, Angelique; Lefkaditou, Evgenia; Maiorano, Porzia; Manfredi, Chiara; Marceta, Bojan; Micallef, Reno; Peristeraki, Panagiota; Relini, Giulio; Sartor, Paolo; Spedicato, Maria Teresa; Tserpes, George; Hidalgo, Manuel

2017-03-01

The Mediterranean Sea is characterized by large scale gradients of temperature, productivity and salinity, in addition to pronounced mesoscale differences. Such a heterogeneous system is expected to shape the population dynamics of marine species. On the other hand, prevailing environmental and climatic conditions at whole basin scale may force spatially distant populations to fluctuate in synchrony. Cephalopods are excellent case studies to test these hypotheses owing to their high sensitivity to environmental conditions. Data of two cephalopod species with contrasting life histories (benthic octopus vs nectobenthic squid), obtained from scientific surveys carried out throughout the Mediterranean during the last 20 years were analyzed. The objectives of this study and the methods used to achieve them (in parentheses) were: (i) to investigate synchronies in spatially separated populations (decorrelation analysis); (ii) detect underlying common abundance trends over distant regions (dynamic factor analysis, DFA); and (iii) analyse putative influences of key environmental drivers such as productivity and sea surface temperature on the population dynamics at regional scale (general linear models, GLM). In accordance with their contrasting spatial mobility, the distance from where synchrony could no longer be detected (decorrelation scale) was higher in squid than in octopus (349 vs 217 km); for comparison, the maximum distance between locations was 2620 km. The DFA revealed a general increasing trend in the abundance of both species in most areas, which agrees with the already reported worldwide proliferation of cephalopods. DFA results also showed that population dynamics are more similar in the eastern than in the western Mediterranean basin. According to the GLM models, cephalopod populations were negatively affected by productivity, which would be explained by an increase of competition and predation by fishes. While warmer years coincided with declining octopus

Dynamics of bid-ask spread return and volatility of the Chinese stock market

NASA Astrophysics Data System (ADS)

Qiu, Tian; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run

2012-04-01

The bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation function and the Detrended Fluctuation Analysis (DFA), we find that the spread return is the lack of long-range memory, while the spread volatility is long-range time correlated. Besides, the spread volatilities of different stocks present long-range cross-correlations. Moreover, by applying the Multifractal Detrended Fluctuation Analysis (MF-DFA), the spread return is observed to possess a strong multifractality, which is similar to the dynamics of a variety of financial quantities. Different from the spread return, the spread volatility exhibits a weak multifractal nature.

[Ultrastructure and Raman Spectral Characteristics of Two Kinds of Acute Myeloid Leukemia Cells].

PubMed

Liang, Hao-Yue; Cheng, Xue-Lian; Dong, Shu-Xu; Zhao, Shi-Xuan; Wang, Ying; Ru, Yong-Xin

2018-02-01

To investigate the Raman spectral characteristics of leukemia cells from 4 patients with acute promyelocytic leukemia (M 3 ) and 3 patients with acute monoblastic leukemia (M 5 ), establish a novel Raman label-free method to distinguish 2 kinds of acute myeloid leukemia cells so as to provide basis for clinical research. Leukemia cells were collected from bone marrow of above-mentioned patients. Raman spectra were acquired by Horiba Xplora Raman spectrometer and Raman spectra of 30-50 cells from each patient were recorded. The diagnostic model was established according to principle component analysis (PCA), discriminant function analysis (DFA) and cluster analysis, and the spectra of leukemia cells from 7 patients were analyzed and classified. Characteristics of Raman spectra were analyzed combining with ultrastructure of leukemia cells. There were significant differences between Raman spectra of 2 kinds of leukemia cells. Compared with acute monoblastic leukemia cells, the spectra of acute promyelocytic leukemia cells showed stronger peaks in 622, 643, 757, 852, 1003, 1033, 1117, 1157, 1173, 1208, 1340, 1551, 1581 cm -1 . The diagnostic models established by PCA-DFA and cluster analysis could successfully classify these Raman spectra of different samples with a high accuracy of 100% (233/233). The model was evaluated by "Leave-one-out" cross-validation and reached a high accuracy of 97% (226/233). The level of macromolecules of M 3 cells is higher than that of M 5 . The diagnostic models established by PCA-DFA can classify these Raman spectra of different cells with a high accuracy. Raman spectra shows consistent result with ultrastructure by TEM.

Derived Basic Ability Factors: A Factor Analysis Replication Study.

ERIC Educational Resources Information Center

Lee, Mickey, M.; Lee, Lynda Newby

The purpose of this study was to replicate the study conducted by Potter, Sagraves, and McDonald to determine whether their recommended analysis could separate criterion variables into similar factors that were stable from year to year and from school to school. The replication samples consisted of all students attending Louisiana State University…

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

PubMed

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors

PubMed Central

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-01-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection

On the Likelihood Ratio Test for the Number of Factors in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.; Yuan, Ke-Hai

2007-01-01

In the exploratory factor analysis, when the number of factors exceeds the true number of factors, the likelihood ratio test statistic no longer follows the chi-square distribution due to a problem of rank deficiency and nonidentifiability of model parameters. As a result, decisions regarding the number of factors may be incorrect. Several…

A Brief History of the Philosophical Foundations of Exploratory Factor Analysis.

ERIC Educational Resources Information Center

Mulaik, Stanley A.

1987-01-01

Exploratory factor analysis derives its key ideas from many sources, including Aristotle, Francis Bacon, Descartes, Pearson and Yule, and Kant. The conclusions of exploratory factor analysis are never complete without subsequent confirmatory factor analysis. (Author/GDC)

Graphic analysis and multifractal on percolation-based return interval series

NASA Astrophysics Data System (ADS)

Pei, A. Q.; Wang, J.

2015-05-01

A financial time series model is developed and investigated by the oriented percolation system (one of the statistical physics systems). The nonlinear and statistical behaviors of the return interval time series are studied for the proposed model and the real stock market by applying visibility graph (VG) and multifractal detrended fluctuation analysis (MF-DFA). We investigate the fluctuation behaviors of return intervals of the model for different parameter settings, and also comparatively study these fluctuation patterns with those of the real financial data for different threshold values. The empirical research of this work exhibits the multifractal features for the corresponding financial time series. Further, the VGs deviated from both of the simulated data and the real data show the behaviors of small-world, hierarchy, high clustering and power-law tail for the degree distributions.

Scaling analysis of heart beat fluctuations data and its relationship with cyclic alternating pattern data during sleep

NASA Astrophysics Data System (ADS)

de León-Lomelí, R.; Murguía, J. S.; Chouvarda, I.; Méndez, M. O.; González-Galván, E.; Alba, A.

2016-01-01

During sleep there exists a nonlinear dynamic phenomenon, which is called cyclic alternating pattern. This phenomenon is generated in the brain and is composed of a series of events of short duration known as A-phases. It has been shown that A-phases can be found in other physiological systems such as the cardiovascular. However, there is no evidence that shows the temporal influence of the A-phases with the cardiovascular system. For this purpose, we consider the scaling method known as detrended fluctuation analysis (DFA). The analysis was carried out in well sleepers and insomnia people, and the numerical results show an increment in the scaling parameter for the insomnia subjects compared with the normal ones. In addition, the results of the heart dynamics suggests a persistent behavior toward the 1/f-noise.

Hand function evaluation: a factor analysis study.

PubMed

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

Multivariate analysis of prognostic factors in synovial sarcoma.

PubMed

Koh, Kyoung Hwan; Cho, Eun Yoon; Kim, Dong Wook; Seo, Sung Wook

2009-11-01

Many studies have described the diversity of synovial sarcoma in terms of its biological characteristics and clinical features. Moreover, much effort has been expended on the identification of prognostic factors because of unpredictable behaviors of synovial sarcomas. However, with the exception of tumor size, published results have been inconsistent. We attempted to identify independent risk factors using survival analysis. Forty-one consecutive patients with synovial sarcoma were prospectively followed from January 1997 to March 2008. Overall and progression-free survival for age, sex, tumor size, tumor location, metastasis at presentation, histologic subtype, chemotherapy, radiation therapy, and resection margin were analyzed, and standard multivariate Cox proportional hazard regression analysis was used to evaluate potential prognostic factors. Tumor size (>5 cm), nonlimb-based tumors, metastasis at presentation, and a monophasic subtype were associated with poorer overall survival. Multivariate analysis showed metastasis at presentation and monophasic tumor subtype affected overall survival. For the progression-free survival, monophasic subtype was found to be only 1 prognostic factor. The study confirmed that histologic subtype is the single most important independent prognostic factors of synovial sarcoma regardless of tumor stage.

Multifractality and Network Analysis of Phase Transition

PubMed Central

Li, Wei; Yang, Chunbin; Han, Jihui; Su, Zhu; Zou, Yijiang

2017-01-01

Many models and real complex systems possess critical thresholds at which the systems shift dramatically from one sate to another. The discovery of early-warnings in the vicinity of critical points are of great importance to estimate how far the systems are away from the critical states. Multifractal Detrended Fluctuation analysis (MF-DFA) and visibility graph method have been employed to investigate the multifractal and geometrical properties of the magnetization time series of the two-dimensional Ising model. Multifractality of the time series near the critical point has been uncovered from the generalized Hurst exponents and singularity spectrum. Both long-term correlation and broad probability density function are identified to be the sources of multifractality. Heterogeneous nature of the networks constructed from magnetization time series have validated the fractal properties. Evolution of the topological quantities of the visibility graph, along with the variation of multifractality, serve as new early-warnings of phase transition. Those methods and results may provide new insights about the analysis of phase transition problems and can be used as early-warnings for a variety of complex systems. PMID:28107414

Multi-site evaluation of the LN34 pan-lyssavirus real-time RT-PCR assay for post-mortem rabies diagnostics

PubMed Central

Dettinger, Lisa; Powell, James W.; Seiders, Melanie; Condori, Rene Edgar Condori; Griesser, Richard; Okogi, Kenneth; Carlos, Maria; Pesko, Kendra; Breckenridge, Mike; Simon, Edson Michael M.; Chu, Maria Yna Joyce V.; Davis, April D.; Brunt, Scott J.; Orciari, Lillian; Yager, Pamela; Carson, William C.; Hartloge, Claire; Saliki, Jeremiah T.; Deldari, Mojgan; Hsieh, Kristina; Wadhwa, Ashutosh; Wilkins, Kimberly; Rabideau, Patricia; Gruhn, Nina; Cadet, Rolain; Isloor, Shrikrishna; Nath, Sujith S.; Joseph, Tomy; Gao, Jinxin; Wallace, Ryan; Reynolds, Mary; Olson, Victoria A.

2018-01-01

Rabies is a fatal zoonotic disease that requires fast, accurate diagnosis to prevent disease in an exposed individual. The current gold standard for post-mortem diagnosis of human and animal rabies is the direct fluorescent antibody (DFA) test. While the DFA test has proven sensitive and reliable, it requires high quality antibody conjugates, a skilled technician, a fluorescence microscope and diagnostic specimen of sufficient quality. The LN34 pan-lyssavirus real-time RT-PCR assay represents a strong candidate for rabies post-mortem diagnostics due to its ability to detect RNA across the diverse Lyssavirus genus, its high sensitivity, its potential for use with deteriorated tissues, and its simple, easy to implement design. Here, we present data from a multi-site evaluation of the LN34 assay in 14 laboratories. A total of 2,978 samples (1,049 DFA positive) from Africa, the Americas, Asia, Europe, and the Middle East were tested. The LN34 assay exhibited low variability in repeatability and reproducibility studies and was capable of detecting viral RNA in fresh, frozen, archived, deteriorated and formalin-fixed brain tissue. The LN34 assay displayed high diagnostic specificity (99.68%) and sensitivity (99.90%) when compared to the DFA test, and no DFA positive samples were negative by the LN34 assay. The LN34 assay produced definitive findings for 80 samples that were inconclusive or untestable by DFA; 29 were positive. Five samples were inconclusive by the LN34 assay, and only one sample was inconclusive by both tests. Furthermore, use of the LN34 assay led to the identification of one false negative and 11 false positive DFA results. Together, these results demonstrate the reliability and robustness of the LN34 assay and support a role for the LN34 assay in improving rabies diagnostics and surveillance. PMID:29768505

13 CFR 120.211 - What limits are there on the amounts of direct loans?

Code of Federal Regulations, 2010 CFR

2010-01-01

... established an administrative limit of $150,000 for direct loans. The D/FA may authorize acceptance of an.... The administrative limit is the lesser of 75 percent of the loan or $150,000. The D/FA may authorize...

13 CFR 120.211 - What limits are there on the amounts of direct loans?

Code of Federal Regulations, 2011 CFR

2011-01-01

... established an administrative limit of $150,000 for direct loans. The D/FA may authorize acceptance of an.... The administrative limit is the lesser of 75 percent of the loan or $150,000. The D/FA may authorize...

Factor Analysis for Clustered Observations.

ERIC Educational Resources Information Center

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

Merkle, L. A.; Layne, C. S.; Bloomberg, J. J.; Zhang, J. J.

1998-01-01

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

A Factor Analysis of the BSRI and the PAQ.

ERIC Educational Resources Information Center

Edwards, Teresa A.; And Others

Factor analysis of the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) was undertaken to study the independence of the masculine and feminine scales within each instrument. Both instruments were administered to undergraduate education majors. Analysis of primary first and second order factors of the BSRI indicated…

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

The use of copula functions for modeling the risk of investment in shares traded on the Warsaw Stock Exchange

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz

2014-11-01

In our work copula functions and the Hurst exponent calculated using the local Detrended Fluctuation Analysis (DFA) were used to investigate the risk of investment made in shares traded on the Warsaw Stock Exchange. The combination of copula functions and the Hurst exponent calculated using local DFA is a new approach. For copula function analysis bivariate variables composed of shares prices of the PEKAO bank (a big bank with high capitalization) and other banks (PKOBP, BZ WBK, MBANK and HANDLOWY in decreasing capitalization order) and companies from other branches (KGHM-mining industry, PKNORLEN-petrol industry as well as ASSECO-software industry) were used. Hurst exponents were calculated for daily shares prices and used to predict high drops of those prices. It appeared to be a valuable indicator in the copula selection procedure, since Hurst exponent’s low values were pointing on heavily tailed copulas e.g. the Clayton one.

Research on the fractal structure in the Chinese stock market

NASA Astrophysics Data System (ADS)

Zhuang, Xin-tian; Huang, Xiao-yuan; Sha, Yan-li

2004-02-01

Applying fractal theory, this paper probes and discusses self-similarity and scale invariance of the Chinese stock market. It analyses three kinds of scale indexes, i.e., autocorrelation index, Hurst index and the scale index on the basis of detrended fluctuation analysis (DFA) algorithm and promotes DFA into a recursive algorithm. Using the three kinds of scale indexes, we conduct empirical research on the Chinese Shanghai and Shenzhen stock markets. The results indicate that the rate of returns of the two stock markets does not obey the normal distribution. A correlation exists between the stock price indexes over time scales. The stock price indexes exhibit fractal time series. It indicates that the policy guide hidden at the back influences the characteristic of the Chinese stock market.

Factors affecting job satisfaction in nurse faculty: a meta-analysis.

PubMed

Gormley, Denise K

2003-04-01

Evidence in the literature suggests job satisfaction can make a difference in keeping qualified workers on the job, but little research has been conducted focusing specifically on nursing faculty. Several studies have examined nurse faculty satisfaction in relationship to one or two influencing factors. These factors include professional autonomy, leader role expectations, organizational climate, perceived role conflict and role ambiguity, leadership behaviors, and organizational characteristics. This meta-analysis attempts to synthesize the various studies conducted on job satisfaction in nursing faculty and analyze which influencing factors have the greatest effect. The procedure used for this meta-analysis consisted of reviewing studies to identify factors influencing job satisfaction, research questions, sample size reported, instruments used for measurement of job satisfaction and influencing factors, and results of statistical analysis.

Water Quality Assessment of River Soan (Pakistan) and Source Apportionment of Pollution Sources Through Receptor Modeling.

PubMed

Nazeer, Summya; Ali, Zeshan; Malik, Riffat Naseem

2016-07-01

The present study was designed to determine the spatiotemporal patterns in water quality of River Soan using multivariate statistics. A total of 26 sites were surveyed along River Soan and its associated tributaries during pre- and post-monsoon seasons in 2008. Hierarchical agglomerative cluster analysis (HACA) classified sampling sites into three groups according to their degree of pollution, which ranged from least to high degradation of water quality. Discriminant function analysis (DFA) revealed that alkalinity, orthophosphates, nitrates, ammonia, salinity, and Cd were variables that significantly discriminate among three groups identified by HACA. Temporal trends as identified through DFA revealed that COD, DO, pH, Cu, Cd, and Cr could be attributed for major seasonal variations in water quality. PCA/FA identified six factors as potential sources of pollution of River Soan. Absolute principal component scores using multiple regression method (APCS-MLR) further explained the percent contribution from each source. Heavy metals were largely added through industrial activities (28 %) and sewage waste (28 %), nutrients through agriculture runoff (35 %) and sewage waste (28 %), organic pollution through sewage waste (27 %) and urban runoff (17 %) and macroelements through urban runoff (39 %), and mineralization and sewage waste (30 %). The present study showed that anthropogenic activities are the major source of variations in River Soan. In order to address the water quality issues, implementation of effective waste management measures are needed.

The Recoverability of P-Technique Factor Analysis

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…

Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong

2010-01-01

This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…

Recommendations for the Investigation of Vapor Intrusion

DTIC Science & Technology

2008-04-01

Abbreviations COC constituent of concern 1,1-dfa 1,1- difluoroethane EPA U.S. Environmental Protection Agency ESTCP Environmental Security...lines. During one sample event, the leak tracer itself caused significant problems. During this sample event, 1,1- difluoroethane (1,1-dfa, the

Recommendations for the Investigation of Vapor Intrusion

DTIC Science & Technology

2007-12-01

1,1-dfa 1,1- difluoroethane EPA U.S. Environmental Protection Agency ESTCP Environmental Security Technology Certification Program NHDES...the leak tracer itself caused significant problems. During this sample event, 1,1- difluoroethane (1,1-dfa, the propellant in duster spray) was used

Donor retention in health care in Iran: a factor analysis

PubMed Central

Aghababa, Sara; Nasiripour, Amir Ashkan; Maleki, Mohammadreza; Gohari, Mahmoodreza

2017-01-01

Background: Long-term financial support is essential for the survival of a charitable organization. Health charities need to identify the effective factors influencing donor retention. Methods: In the present study, the items of a questionnaire were derived from both literature review and semi-structured interviews related to donor retention. Using a purposive sampling, 300 academic and executive practitioners were selected. After the follow- up, a total of 243 usable questionnaires were prepared for factor analysis. The questionnaire was validated based on the face and content validity and reliability through Cronbach’s α-coefficient. Results: The results of exploratory factor analysis extracted 2 factors for retention: donor factor (variance = 33.841%; Cronbach’s α-coefficient = 90.2) and charity factor (variance = 29.038%; Cronbach’s α-coefficient = 82.8), respectively. Subsequently, confirmatory factor analysis was applied to support the overall reasonable fit. Conclusions: In this study, it was found that repeated monetary donations are supplied to the charitable organizations when both aspects of donor factor (retention factor and charity factor) for retention are taken into consideration. This model could provide a perspective for making sustainable donations and charitable giving PMID:28955663

The Factor Structure of the English Language Development Assessment: A Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Kuriakose, Anju

2011-01-01

This study investigated the internal factor structure of the English language development Assessment (ELDA) using confirmatory factor analysis. ELDA is an English language proficiency test developed by a consortium of multiple states and is used to identify and reclassify English language learners in kindergarten to grade 12. Scores on item…

Influential Observations in Principal Factor Analysis.

ERIC Educational Resources Information Center

Tanaka, Yutaka; Odaka, Yoshimasa

1989-01-01

A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)

Global and critical test of the perturbation density-functional theory based on extensive simulation of Lennard-Jones fluid near an interface and in confined systems.

PubMed

Zhou, Shiqi; Jamnik, Andrej

2005-09-22

The structure of a Lennard-Jones (LJ) fluid subjected to diverse external fields maintaining the equilibrium with the bulk LJ fluid is studied on the basis of the third-order+second-order perturbation density-functional approximation (DFA). The chosen density and potential parameters for the bulk fluid correspond to the conditions situated at "dangerous" regions of the phase diagram, i.e., near the critical temperature or close to the gas-liquid coexistence curve. The accuracy of DFA predictions is tested against the results of a grand canonical ensemble Monte Carlo simulation. It is found that the DFA theory presented in this work performs successfully for the nonuniform LJ fluid only on the condition of high accuracy of the required bulk second-order direct correlation function. The present report further indicates that the proposed perturbation DFA is efficient and suitable for both supercritical and subcritical temperatures.

Application of factor analysis to the water quality in reservoirs

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this work we present a Factor Analysis of chemical and environmental variables of the water column and hydro-morphological features of several Portuguese reservoirs. The objective is to reduce the initial number of variables, keeping their common characteristics. Using the Factor Analysis, the environmental variables measured in the epilimnion and in the hypolimnion, together with the hydromorphological characteristics of the dams were reduced from 63 variables to only 13 factors, which explained a total of 83.348% of the variance in the original data. After performing rotation using the Varimax method, the relations between the factors and the original variables got clearer and more explainable, which provided a Factor Analysis model for these environmental variables using 13 varifactors: Water quality and distance to the source, Hypolimnion chemical composition, Sulfite-reducing bacteria and nutrients, Coliforms and faecal streptococci, Reservoir depth, Temperature, Location, among other factors.

The evaluation of three diagnostic tests for the detection of equine influenza nucleoprotein in nasal swabs.

PubMed

Galvin, Pamela; Gildea, Sarah; Nelly, Maura; Quinlivan, Michelle; Arkins, Sean; Walsh, Cathal; Cullinane, Ann

2014-05-01

Equine influenza (EI) is a highly contagious respiratory disease of horses. The aim of this study was to evaluate two rapid antigen detection kits (Directigen or DFA, and Espline) and a commercial ELISA for the detection of EI nucleoprotein in nasal swabs. Nasal swab samples from naturally and experimentally infected horses were used to compare the sensitivity and specificity of these assays to virus isolation (VI) and real-time RT-PCR. If real-time RT-PCR was considered as the gold standard, the sensitivity of the other tests in field samples was 68% (DFA), 35% (ELISA), 29% (Espline), and 9% (VI). These tests had 100% specificity when compared to real-time RT-PCR. A receiver operating characteristic (ROC) curve indicated that decreasing the cutoff of the ELISA would increase sensitivity with some loss of specificity. In samples from experimentally infected horses, the sensitivity of the tests compared with real-time RT-PCR was 69% (VI), 27% (DFA), 6% (Espline), and 2% (ELISA). The specificity was 100% for Espline and ELISA and 95% for VI and DFA. This study illustrated that DFA is the most sensitive antigen detection test evaluated for the diagnosis of EI and that it can detect virus in some subclinical infected and vaccinated horses. The results suggest that DFA is a useful adjunct to laboratory tests and may be effective as a screening test in a quarantine station or similar facility where horses are monitored daily. © 2014 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.

Tipping point analysis of seismological data

NASA Astrophysics Data System (ADS)

Livina, Valerie N.; Tolkova, Elena

2014-05-01

We apply the tipping point toolbox [1-7] to study sensor data of pressure variations and vertical velocity of the sea floor after two seismic events: 21 October 2010, M6.9, D10km (California) and 11 March 2011, M9.0, D30km (Japan). One type of datasets was measured by nano-resolution pressure sensor [8], while the other, for comparison, by a co-located ocean bottom seismometer. Both sensors registered the seismic wave, and we investigated the early warning and detection signals of the wave arrival for possible application with a remote and cabled tsunami warning detector network (NOAA DART system and Japan Trench Tsunami Observation System). We study the early warning and detection signals of the wave arrival using methodology that combines degenerate fingerprinting and potential analysis techniques for anticipation, detection and forecast of tipping points in a dynamical system. Degenerate fingerprinting indicator is a dynamically derived lag-1 autocorrelation, ACF (or, alternatively, short-range scaling exponent of Detrended Fluctuation Analysis, DFA [1]), which shows short-term memory in a series. When such values rise monotonically, this indicates an upcoming transition or bifurcation in a series and can be used for early warning signals analysis. The potential analysis detects a transition or bifurcation in a series at the time when it happens, which is illustrated in a special contour plot mapping the potential dynamics of the system [2-6]. The methodology has been extensively tested on artificial data and on various geophysical, ecological and industrial sensor datasets [2-5,7], and proved to be applicable to trajectories of dynamical systems of arbitrary origin [9]. In this seismological application, we have obtained early warning signals in the described series using ACF- and DFA-indicators and detected the Rayleigh wave arrival in the potential contour plots. In the case of the event in 2010, the early warning signal starts appearing about 2 min before

Comparative Evaluation of Three Methods (Microscopic Examination, Direct Fluorescent Antibody Assay, and Immunochromatographic Method) for the Diagnosis of Giardia intestinalis From Stool Specimens.

PubMed

Karadam, Senem Yaman; Ertuğ, Sema; Ertabaklar, Hatice

2016-03-01

The aim of this study was to compare direct microscopic examination, direct fluorescent antibody assay (DFA), and the immunochromatographic method (IK) and identify the best suitable method for the diagnosis of Giardia intestinalis. In this study, 25 stool samples that had been diagnosed as being infected with G. intestinalis using the native-Lugol and/or formol-ethyl acetate concentration method and 25 non-parasite-infected samples (the control group) were examined. After microscopic examination of stools, they were kept at -20°C for examination using DFA and IK. Stool samples were studied using DFA (CeLLabs, Crypto/Giardia-Cel IF) and IK (RIDA QUICK, Cryptosporidium/Giardia Combi Dipstick), as per the manufacturers' instructions. In our study, using the DFA method, parasites were detected in all 25 stool samples in which G. intestinalis was diagnosed by direct microscopic examination. Using the IK method, a particular band indicative of the parasite was detected in 24 samples. No parasites were detected in all 25 samples in the control group. Thus, when direct microscopic examination is taken as reference, the senstivity and specificity of DFA for the diagnosis of G. intestinalis were found to be 100% each, while those of IK were found to be 96% and 100%, respectively.

De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.

PubMed

Lee, Juyong; Lee, Jinhyuk; Sasaki, Takeshi N; Sasai, Masaki; Seok, Chaok; Lee, Jooyoung

2011-08-01

Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods. Copyright © 2011 Wiley-Liss, Inc.

The origin of the medial circumflex femoral artery: a meta-analysis and proposal of a new classification system.

PubMed

Tomaszewski, Krzysztof A; Henry, Brandon M; Vikse, Jens; Roy, Joyeeta; Pękala, Przemysław A; Svensen, Maren; Guay, Daniel L; Saganiak, Karolina; Walocha, Jerzy A

2016-01-01

Background and Objectives. The medial circumflex femoral artery (MCFA) is a common branch of the deep femoral artery (DFA) responsible for supplying the femoral head and the greater trochanteric fossa. The prevalence rates of MCFA origin, its branching patterns and its distance to the mid-inguinal point (MIP) vary significantly throughout the literature. The aim of this study was to determine the true prevalence of these characteristics and to study their associated anatomical and clinical relevance. Methods. A search of the major electronic databases Pubmed, EMBASE, Scopus, ScienceDirect, Web of Science, SciELO, BIOSIS, and CNKI was performed to identify all articles reporting data on the origin of the MCFA, its branching patterns and its distance to the MIP. No data or language restriction was set. Additionally, an extensive search of the references of all relevant articles was performed. All data on origin, branching and distance to MIP was extracted and pooled into a meta-analysis using MetaXL v2.0. Results. A total of 38 (36 cadaveric and 2 imaging) studies (n = 4,351 lower limbs) were included into the meta-analysis. The pooled prevalence of the MCFA originating from the DFA was 64.6% (95% CI [58.0-71.5]), while the pooled prevalence of the MCFA originating from the CFA was 32.2% (95% CI [25.9-39.1]). The CFA-derived MCFA was found to originate as a single branch in 81.1% (95% CI [70.1-91.7]) of cases with a mean pooled distance of 50.14 mm (95% CI [42.50-57.78]) from the MIP. Conclusion. The MCFA's variability must be taken into account by surgeons, especially during orthopedic interventions in the region of the hip to prevent iatrogenic injury to the circulation of the femoral head. Based on our analysis, we present a new proposed classification system for origin of the MCFA.

A replication of a factor analysis of motivations for trapping

USGS Publications Warehouse

Schroeder, Susan; Fulton, David C.

2015-01-01

Using a 2013 sample of Minnesota trappers, we employed confirmatory factor analysis to replicate an exploratory factor analysis of trapping motivations conducted by Daigle, Muth, Zwick, and Glass (1998).  We employed the same 25 items used by Daigle et al. and tested the same five-factor structure using a recent sample of Minnesota trappers. We also compared motivations in our sample to those reported by Daigle et el.

Exercise training causes differential changes in gene expression in diaphragm arteries and 2A arterioles of obese rats.

PubMed

Laughlin, M Harold; Padilla, Jaume; Jenkins, Nathan T; Thorne, Pamela K; Martin, Jeffrey S; Rector, R Scott; Akter, Sadia; Davis, J Wade

2015-09-15

We employed next-generation, transcriptome-wide RNA sequencing (RNA-Seq) technology to assess the effects of two different exercise training protocols on transcriptional profiles in diaphragm second-order arterioles (D2a) and in the diaphragm feed artery (DFA) from Otsuka Long Evans Tokushima Fatty (OLETF) rats. Arterioles were isolated from the diaphragm of OLETF rats that underwent an endurance exercise training program (EX; n = 13), interval sprint training program (SPRINT; n = 14), or remained sedentary (Sed; n = 12). Our hypothesis was that exercise training would have similar effects on gene expression in the diaphragm and soleus muscle arterioles because diaphragm blood flow increases during exercise to a similar extent as in soleus. Results reveal that several canonical pathways that were significantly altered by exercise in limb skeletal muscles were not among the pathways significantly changed in the diaphragm arterioles including actin cytoskeleton signaling, role of NFAT in regulation of immune response, protein kinase A signaling, and protein ubiquitination pathway. EX training altered the expression of a smaller number of genes than did SPRINT in the DFA but induced a larger number of genes with altered expression in the D2a than did SPRINT. In fact, FDR differential expression analysis (FDR, 10%) indicated that only two genes exhibited altered expression in D2a of SPRINT rats. Very few of the genes that exhibited altered expression in the DFA or D2a were also altered in limb muscle arterioles. Finally, results indicate that the 2a arterioles of soleus muscle (S2a) from endurance-trained animals and the DFA of SPRINT animals exhibited the largest number of genes with altered expression.

Dual-force aggregation of magnetic particles enhances label-free quantification of DNA at the sub-single cell level.

PubMed

Nelson, Daniel A; Strachan, Briony C; Sloane, Hillary S; Li, Jingyi; Landers, James P

2014-03-28

We recently reported the 'pinwheel effect' as the foundation for a DNA assay based on a DNA concentration-dependent aggregation of silica-coated magnetic beads in a rotating magnetic field (RMF). Using a rotating magnet that generated a 5 cm magnetic field that impinged on a circular array of 5mm microwells, aggregation was found to only be effective in a single well at the center of the field. As a result, when multiple samples needed to be analyzed, the single-plex (single well) analysis was tedious, time-consuming and labor-intensive, as each well needed to be exposed to the center of the RMF in a serial manner for consistent well-to-well aggregation. For more effective multiplexing (simultaneous aggregation in 12 wells), we used a circular array of microwells and incorporated 'agitation' as a second force that worked in concert with the RMF to provide effective multiplexed aggregation-based DNA quantitation. The dual-force aggregation (DFA) approach allows for effective simultaneous aggregation in multiple wells (12 demonstrated) of the multi-well microdevice, allowing for 12 samples to be interrogated for DNA content in 140 s, providing a ∼35-fold improvement in time compared to single-plex approach (80 min) and ∼4-fold improvement over conventional fluorospectrometric methods. Furthermore, the increased interaction between DNA and beads provided by DFA improved the limit of detection to 250 fg μL(-1). The correlation between the DFA results and those from a fluorospectrometer, demonstrate DFA as an inexpensive and rapid alternative to more conventional methods (fluorescent and spectrophotometric). Copyright © 2014 Elsevier B.V. All rights reserved.

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

Development and testing of monoclonal antibody-based rapid immunodiagnostic test kits for direct detection of Vibrio cholerae O139 synonym Bengal.

PubMed

Hasan, J A; Huq, A; Nair, G B; Garg, S; Mukhopadhyay, A K; Loomis, L; Bernstein, D; Colwell, R R

1995-11-01

We report on the development and testing of two monoclonal antibody-based rapid immunodiagnostic test kits, BengalScreen, a coagglutination test, and Bengal DFA, a direct fluorescent-antibody test, for direct detection of Vibrio cholerae O139 synonym Bengal in clinical and environmental specimens. The BengalScreen test requires less than 5 min to complete and can be used in the field. Bengal DFA, being more sensitive than BengalScreen, requires only one reagent and less than 20 min for detection and enumeration of V. cholerae O139 synonym Bengal. In tests for specificity, all 40 strains of V. cholerae O139 reacted with both test kits, whereas 157 strains of heterologous species examined did not, yielding 100% specificity in this study. A field trial was conducted in with both BengalScreen and Bengal DFA, and the results were compared with those obtained by conventional culture methods. BengalScreen demonstrated a sensitivity of 95%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 94%. Results obtained by Bengal DFA, on the other hand, were 100% sensitive and 100% specific and yielded 100% positive and negative predictive values compared with culture methods. In a second evaluation, 93 stool specimens from Mexico that were negative for V. cholerae O139 by culture were also tested with both the BengalScreen and Bengal DFA kits. None of the 93 specimens were positive for V. cholerae O139 by both tests. A concentration method was optimized for screening of environmental water samples for V. cholerae O139 synonym Bengal with rapid test kits. BengalScreen results were unequivocally positive when water samples contained at least 2.0 x 10(3) CFU/ml, whereas Bengal DFA demonstrated an unequivocally positive reaction when the water sample contained at least 1.5 x 10(2) CFU/ml. When Bengal DFA was compared with conventional culture methods for enumeration of V. cholerae O139 synonym Bengal organisms, no difference was observed.

Assessing the reproducibility of discriminant function analyses

PubMed Central

Andrew, Rose L.; Albert, Arianne Y.K.; Renaut, Sebastien; Rennison, Diana J.; Bock, Dan G.

2015-01-01

Data are the foundation of empirical research, yet all too often the datasets underlying published papers are unavailable, incorrect, or poorly curated. This is a serious issue, because future researchers are then unable to validate published results or reuse data to explore new ideas and hypotheses. Even if data files are securely stored and accessible, they must also be accompanied by accurate labels and identifiers. To assess how often problems with metadata or data curation affect the reproducibility of published results, we attempted to reproduce Discriminant Function Analyses (DFAs) from the field of organismal biology. DFA is a commonly used statistical analysis that has changed little since its inception almost eight decades ago, and therefore provides an opportunity to test reproducibility among datasets of varying ages. Out of 100 papers we initially surveyed, fourteen were excluded because they did not present the common types of quantitative result from their DFA or gave insufficient details of their DFA. Of the remaining 86 datasets, there were 15 cases for which we were unable to confidently relate the dataset we received to the one used in the published analysis. The reasons ranged from incomprehensible or absent variable labels, the DFA being performed on an unspecified subset of the data, or the dataset we received being incomplete. We focused on reproducing three common summary statistics from DFAs: the percent variance explained, the percentage correctly assigned and the largest discriminant function coefficient. The reproducibility of the first two was fairly high (20 of 26, and 44 of 60 datasets, respectively), whereas our success rate with the discriminant function coefficients was lower (15 of 26 datasets). When considering all three summary statistics, we were able to completely reproduce 46 (65%) of 71 datasets. While our results show that a majority of studies are reproducible, they highlight the fact that many studies still are not the

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

PubMed Central

Sediyama, Cristina Y. N.; Moura, Ricardo; Garcia, Marina S.; da Silva, Antonio G.; Soraggi, Carolina; Neves, Fernando S.; Albuquerque, Maicon R.; Whiteside, Setephen P.; Malloy-Diniz, Leandro F.

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS. PMID:28484414

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale.

PubMed

Sediyama, Cristina Y N; Moura, Ricardo; Garcia, Marina S; da Silva, Antonio G; Soraggi, Carolina; Neves, Fernando S; Albuquerque, Maicon R; Whiteside, Setephen P; Malloy-Diniz, Leandro F

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach's alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

A Factor Analysis of Learning Data and Selected Ability Test Scores

ERIC Educational Resources Information Center

Jones, Dorothy L.

1976-01-01

A verbal concept-learning task permitting the externalizing and quantifying of learning behavior and 16 ability tests were administered to female graduate students. Data were analyzed by alpha factor analysis and incomplete image analysis. Six alpha factors and 12 image factors were extracted and orthogonally rotated. Four areas of cognitive…

Vocal individuality cues in the African penguin (Spheniscus demersus): a source-filter theory approach.

PubMed

Favaro, Livio; Gamba, Marco; Alfieri, Chiara; Pessani, Daniela; McElligott, Alan G

2015-11-25

The African penguin is a nesting seabird endemic to southern Africa. In penguins of the genus Spheniscus vocalisations are important for social recognition. However, it is not clear which acoustic features of calls can encode individual identity information. We recorded contact calls and ecstatic display songs of 12 adult birds from a captive colony. For each vocalisation, we measured 31 spectral and temporal acoustic parameters related to both source and filter components of calls. For each parameter, we calculated the Potential of Individual Coding (PIC). The acoustic parameters showing PIC ≥ 1.1 were used to perform a stepwise cross-validated discriminant function analysis (DFA). The DFA correctly classified 66.1% of the contact calls and 62.5% of display songs to the correct individual. The DFA also resulted in the further selection of 10 acoustic features for contact calls and 9 for display songs that were important for vocal individuality. Our results suggest that studying the anatomical constraints that influence nesting penguin vocalisations from a source-filter perspective, can lead to a much better understanding of the acoustic cues of individuality contained in their calls. This approach could be further extended to study and understand vocal communication in other bird species.

Vocal individuality cues in the African penguin (Spheniscus demersus): a source-filter theory approach

PubMed Central

Favaro, Livio; Gamba, Marco; Alfieri, Chiara; Pessani, Daniela; McElligott, Alan G.

2015-01-01

The African penguin is a nesting seabird endemic to southern Africa. In penguins of the genus Spheniscus vocalisations are important for social recognition. However, it is not clear which acoustic features of calls can encode individual identity information. We recorded contact calls and ecstatic display songs of 12 adult birds from a captive colony. For each vocalisation, we measured 31 spectral and temporal acoustic parameters related to both source and filter components of calls. For each parameter, we calculated the Potential of Individual Coding (PIC). The acoustic parameters showing PIC ≥ 1.1 were used to perform a stepwise cross-validated discriminant function analysis (DFA). The DFA correctly classified 66.1% of the contact calls and 62.5% of display songs to the correct individual. The DFA also resulted in the further selection of 10 acoustic features for contact calls and 9 for display songs that were important for vocal individuality. Our results suggest that studying the anatomical constraints that influence nesting penguin vocalisations from a source-filter perspective, can lead to a much better understanding of the acoustic cues of individuality contained in their calls. This approach could be further extended to study and understand vocal communication in other bird species. PMID:26602001

Biological risk factors for suicidal behaviors: a meta-analysis

PubMed Central

Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K

2016-01-01

Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09–1.81) and suicide death (wOR=1.28; CI: 1.13–1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias—cytokines (wOR=2.87; CI: 1.40–5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01–1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors. PMID:27622931

Resonance-enhanced two-photon ionization spectroscopy and theoretical calculations of 3,5-difluoroanisole and its Ar-containing complex.

PubMed

Zhang, Lijuan; Dong, Changwu; Cheng, Min; Hu, Lili; Du, Yikui; Zhu, Qihe; Zhang, Cunhao

2012-10-01

The structure and vibrations of 3,5-difluoroanisole (3,5-DFA) in the first electronically excited (S(1)) state were studied by mass-analyzed resonant two-photon ionization (R2PI) technique as well as the quantum chemical calculations. The ab initio and density functional theory (DFT) calculations reveal that only one structure is stable for each of the S(0), S(1), and D(0) states. In the one color R2PI spectrum, the band origin of the S(1)←S(0) electronic transition (0(0) band) of 3,5-DFA is found to be 37,595±3 cm(-1). In the S(1) state, most of the bands observed are related to the in-plane ring deformation and out-of-plane bending vibrations. The adiabatic ionization energy (IE) of 3,5-DFA is determined to be 70,096±15 cm(-1) by the two color R2PI technique, in agreement with the values predicted by the DFT approaches. The dihalogen-substitution effects on the molecular structure, vibrational frequencies, and electronic transition and ionization energies were discussed in detail. The van der Waals complex of 3,5-DFA with argon (3,5-DFA···Ar) was also observed and studied. The 0(0) band of 3,5-DFA···Ar complex is red-shifted by about 9 cm(-1) with respect to that of 3,5-DFA. Both the experimental data and the calculated results indicate that the formation of 3,5-DFA···Ar complex gives only a weak influence on the properties of 3,5-DFA moiety. Copyright © 2012 Elsevier B.V. All rights reserved.

Long memory in international financial markets trends and short movements during 2008 financial crisis based on variational mode decomposition and detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2015-11-01

The purpose of this study is to investigate long-range dependence in trend and short variation of stock market price and return series before, during, and after 2008 financial crisis. Variational mode decomposition (VMD), a newly introduced technique for signal processing, is adopted to decompose stock market data into a finite set of modes so as to obtain long term trends and short term movements of stock market data. Then, the detrended fluctuation analysis (DFA) and range scale (R/S) analysis are used to estimate Hurst exponent in each variational mode obtained from VMD. For both price and return series, the empirical results from twelve international stock markets show evidence that long term trends are persistent, whilst short term variations are anti-persistent before, during, and after 2008 financial crisis.

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

PubMed

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

Beyond precipitation: physiographic gradients dictate the relative importance of environmental drivers on Savanna vegetation.

PubMed

Campo-Bescós, Miguel A; Muñoz-Carpena, Rafael; Kaplan, David A; Southworth, Jane; Zhu, Likai; Waylen, Peter R

2013-01-01

Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation<750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions with precipitation>950 mm). We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global

Beyond Precipitation: Physiographic Gradients Dictate the Relative Importance of Environmental Drivers on Savanna Vegetation

PubMed Central

Campo-Bescós, Miguel A.; Muñoz-Carpena, Rafael; Kaplan, David A.; Southworth, Jane; Zhu, Likai; Waylen, Peter R.

2013-01-01

Background Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. Methodology/Principal Findings We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation<750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions with precipitation>950 mm). Conclusions/Significance We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of

Elemental analysis of fingernail of alcoholic and doping subjects by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Bahreini, M.; Ashrafkhani, B.; Tavassoli, S. H.

2014-03-01

Laser-induced breakdown spectroscopy (LIBS) is applied to investigate the effect of alcoholism and doping on elemental composition of fingernails of subjects. Measurements are made on 36 fingernail clippings including 8 doping, 8 alcoholic and 20 normal subjects. Classification of normal, alcoholic and doping subjects based on 46 atomic and ionic emission lines belonging to 13 elements of fingernail is examined using discriminant function analysis (DFA) method. The most affecting elements in classification of groups are discussed. In order to improve the repeatability of LIBS measurements, an auto-focus system has been designed and used in experiments. Results are promising and show that by improving the repeatability of experiments through improving the setup, some evidence of the impact of the alcohol and doping on elemental composition of fingernails is observed.

Human Factors Vehicle Displacement Analysis: Engineering In Motion

NASA Technical Reports Server (NTRS)

Atencio, Laura Ashley; Reynolds, David; Robertson, Clay

2010-01-01

While positioned on the launch pad at the Kennedy Space Center, tall stacked launch vehicles are exposed to the natural environment. Varying directional winds and vortex shedding causes the vehicle to sway in an oscillating motion. The Human Factors team recognizes that vehicle sway may hinder ground crew operation, impact the ground system designs, and ultimately affect launch availability . The objective of this study is to physically simulate predicted oscillation envelopes identified by analysis. and conduct a Human Factors Analysis to assess the ability to carry out essential Upper Stage (US) ground operator tasks based on predicted vehicle motion.

Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis.

PubMed

Valous, Nektarios A; Drakakis, Konstantinos; Sun, Da-Wen

2010-10-01

The visual texture of pork ham slices reveals information about the different qualities and perceived image heterogeneity, which is encapsulated as spatial variations in geometry and spectral characteristics. Detrended Fluctuation Analysis (DFA) detects long-range correlations in nonstationary spatial sequences, by a self-similarity scaling exponent alpha. In the current work, the aim is to investigate the usefulness of alpha, using different colour channels (R, G, B, L*, a*, b*, H, S, V, and Grey), as a quantitative descriptor of visual texture in sliced ham surface patterns for the detection of long-range correlations in unidimensional spatial series of greyscale intensity pixel values at 0 degrees , 30 degrees , 45 degrees , 60 degrees , and 90 degrees rotations. Images were acquired from three qualities of pre-sliced pork ham, typically consumed in Ireland (200 slices per quality). Results indicated that the DFA approach can be used to characterize and quantify the textural appearance of the three ham qualities, for different image orientations, with a global scaling exponent. The spatial series extracted from the ham images display long-range dependence, indicating an average behaviour around 1/f-noise. Results indicate that alpha has a universal character in quantifying the visual texture of ham surface intensity patterns, with no considerable crossovers that alter the behaviour of the fluctuations. Fractal correlation properties can thus be a useful metric for capturing information embedded in the visual texture of hams. Copyright (c) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis

NASA Astrophysics Data System (ADS)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Rodríguez-Achach, M. E.

In this chapter we present a simple data analysis of an ensemble of 20 time series, generated by averaging the spatial positions of the living cells for each state of the Game of Life Cellular Automaton (GoL). We show that at the macroscopic level described by these time series, complexity properties of GoL are also presented and the following emergent properties, typical of data extracted complex systems such as financial or economical come out: variations of the generated time series following an asymptotic power law distribution, large fluctuations tending to be followed by large fluctuations, and small fluctuations tending to be followed by small ones, and fast decay of linear correlations, however, the correlations associated to their absolute variations exhibit a long range memory. Finally, a Detrended Fluctuation Analysis (DFA) of the generated time series, indicates that the GoL spatial macro states described by the time series are not either completely ordered or random, in a measurable and very interesting way.

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

Deep Learning with Hierarchical Convolutional Factor Analysis

PubMed Central

Chen, Bo; Polatkan, Gungor; Sapiro, Guillermo; Blei, David; Dunson, David; Carin, Lawrence

2013-01-01

Unsupervised multi-layered (“deep”) models are considered for general data, with a particular focus on imagery. The model is represented using a hierarchical convolutional factor-analysis construction, with sparse factor loadings and scores. The computation of layer-dependent model parameters is implemented within a Bayesian setting, employing a Gibbs sampler and variational Bayesian (VB) analysis, that explicitly exploit the convolutional nature of the expansion. In order to address large-scale and streaming data, an online version of VB is also developed. The number of basis functions or dictionary elements at each layer is inferred from the data, based on a beta-Bernoulli implementation of the Indian buffet process. Example results are presented for several image-processing applications, with comparisons to related models in the literature. PMID:23787342

Factor Analysis by Generalized Least Squares.

ERIC Educational Resources Information Center

Joreskog, Karl G.; Goldberger, Arthur S.

Aitkin's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are scale free and asymptotically efficient. The estimates are computed by a rapidly…

Sputum direct fluorescent antibody (DFA) test

MedlinePlus

... chap 17. Murray PR. The clinician and the microbiology laboratory. In: Bennett JE, Dolin R, Blaser MJ, eds. Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases . 8th ed. Philadelphia, PA: Elsevier Saunders; 2015:chap 16.

Exploratory Factor Analysis of a Force Concept Inventory Data Set

ERIC Educational Resources Information Center

Scott, Terry F.; Schumayer, Daniel; Gray, Andrew R.

2012-01-01

We perform a factor analysis on a "Force Concept Inventory" (FCI) data set collected from 2109 respondents. We address two questions: the appearance of conceptual coherence in student responses to the FCI and some consequences of this factor analysis on the teaching of Newtonian mechanics. We will highlight the apparent conflation of Newton's…

[Factor Analysis: Principles to Evaluate Measurement Tools for Mental Health].

PubMed

Campo-Arias, Adalberto; Herazo, Edwin; Oviedo, Heidi Celina

2012-09-01

The validation of a measurement tool in mental health is a complex process that usually starts by estimating reliability, to later approach its validity. Factor analysis is a way to know the number of dimensions, domains or factors of a measuring tool, generally related to the construct validity of the scale. The analysis could be exploratory or confirmatory, and helps in the selection of the items with better performance. For an acceptable factor analysis, it is necessary to follow some steps and recommendations, conduct some statistical tests, and rely on a proper sample of participants. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Multiscale multifractal detrended-fluctuation analysis of two-dimensional surfaces

NASA Astrophysics Data System (ADS)

Wang, Fang; Fan, Qingju; Stanley, H. Eugene

2016-04-01

Two-dimensional (2D) multifractal detrended fluctuation analysis (MF-DFA) has been used to study monofractality and multifractality on 2D surfaces, but when it is used to calculate the generalized Hurst exponent in a fixed time scale, the presence of crossovers can bias the outcome. To solve this problem, multiscale multifractal analysis (MMA) was recent employed in a one-dimensional case. MMA produces a Hurst surface h (q ,s ) that provides a spectrum of local scaling exponents at different scale ranges such that the positions of the crossovers can be located. We apply this MMA method to a 2D surface and identify factors that influence the results. We generate several synthesized surfaces and find that crossovers are consistently present, which means that their fractal properties differ at different scales. We apply MMA to the surfaces, and the results allow us to observe these differences and accurately estimate the generalized Hurst exponents. We then study eight natural texture images and two real-world images and find (i) that the moving window length (WL) and the slide length (SL) are the key parameters in the MMA method, that the WL more strongly influences the Hurst surface than the SL, and that the combination of WL =4 and SL =4 is optimal for a 2D image; (ii) that the robustness of h (2 ,s ) to four common noises is high at large scales but variable at small scales; and (iii) that the long-term correlations in the images weaken as the intensity of Gaussian noise and salt and pepper noise is increased. Our findings greatly improve the performance of the MMA method on 2D surfaces.

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

This quantitative research examined factors that affect elementary students' creativity and how those factors correlate. Aiming to identify significant factors that affect creativity and to clarify the relationship between these factors by path analysis, this research was designed to be a stepping stone for creativity enhancement studies. Data…

Generalized five-dimensional dynamic and spectral factor analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Fakhri, Georges; Sitek, Arkadiusz; Zimmerman, Robert E.

2006-04-15

We have generalized the spectral factor analysis and the factor analysis of dynamic sequences (FADS) in SPECT imaging to a five-dimensional general factor analysis model (5D-GFA), where the five dimensions are the three spatial dimensions, photon energy, and time. The generalized model yields a significant advantage in terms of the ratio of the number of equations to that of unknowns in the factor analysis problem in dynamic SPECT studies. We solved the 5D model using a least-squares approach. In addition to the traditional non-negativity constraints, we constrained the solution using a priori knowledge of both time and energy, assuming thatmore » primary factors (spectra) are Gaussian-shaped with full-width at half-maximum equal to gamma camera energy resolution. 5D-GFA was validated in a simultaneous pre-/post-synaptic dual isotope dynamic phantom study where {sup 99m}Tc and {sup 123}I activities were used to model early Parkinson disease studies. 5D-GFA was also applied to simultaneous perfusion/dopamine transporter (DAT) dynamic SPECT in rhesus monkeys. In the striatal phantom, 5D-GFA yielded significantly more accurate and precise estimates of both primary {sup 99m}Tc (bias=6.4%{+-}4.3%) and {sup 123}I (-1.7%{+-}6.9%) time activity curves (TAC) compared to conventional FADS (biases=15.5%{+-}10.6% in {sup 99m}Tc and 8.3%{+-}12.7% in {sup 123}I, p<0.05). Our technique was also validated in two primate dynamic dual isotope perfusion/DAT transporter studies. Biases of {sup 99m}Tc-HMPAO and {sup 123}I-DAT activity estimates with respect to estimates obtained in the presence of only one radionuclide (sequential imaging) were significantly lower with 5D-GFA (9.4%{+-}4.3% for {sup 99m}Tc-HMPAO and 8.7%{+-}4.1% for {sup 123}I-DAT) compared to biases greater than 15% for volumes of interest (VOI) over the reconstructed volumes (p<0.05). 5D-GFA is a novel and promising approach in dynamic SPECT imaging that can also be used in other modalities. It allows accurate and

Fluctuations in Cerebral Hemodynamics

DTIC Science & Technology

2003-12-01

Determination of scaling properties Detrended Fluctuations Analysis (see (28) and references therein) is commonly used to determine scaling...pressure (averaged over a cardiac beat) of a healthy subject. First 1000 values of the time series are shown. (b) Detrended fluctuation analysis (DFA...1000 values of the time series are shown. (b) Detrended fluctuation analysis of the time series shown in (a). Fig . 3 Side-by-side boxplot for the

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Rail Risk Analysis Factors D Appendix D to Part... REQUIREMENTS, AND SECURITY PLANS Pt. 172, App. D Appendix D to Part 172—Rail Risk Analysis Factors A. This... safety and security risk analyses required by § 172.820. The risk analysis to be performed may be...

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Rail Risk Analysis Factors D Appendix D to Part... REQUIREMENTS, AND SECURITY PLANS Pt. 172, App. D Appendix D to Part 172—Rail Risk Analysis Factors A. This... safety and security risk analyses required by § 172.820. The risk analysis to be performed may be...

Spectroscopic characterization of biological agents using FTIR, normal Raman and surface-enhanced Raman spectroscopies

NASA Astrophysics Data System (ADS)

Luna-Pineda, Tatiana; Soto-Feliciano, Kristina; De La Cruz-Montoya, Edwin; Pacheco Londoño, Leonardo C.; Ríos-Velázquez, Carlos; Hernández-Rivera, Samuel P.

2007-04-01

FTIR, Raman spectroscopy and Surface Enhanced Raman Scattering (SERS) requires a minimum of sample allows fast identification of microorganisms. The use of this technique for characterizing the spectroscopic signatures of these agents and their stimulants has recently gained considerable attention due to the fact that these techniques can be easily adapted for standoff detection from considerable distances. The techniques also show high sensitivity and selectivity and offer near real time detection duty cycles. This research focuses in laying the grounds for the spectroscopic differentiation of Staphylococcus spp., Pseudomonas spp., Bacillus spp., Salmonella spp., Enterobacter aerogenes, Proteus mirabilis, Klebsiella pneumoniae, and E. coli, together with identification of their subspecies. In order to achieve the proponed objective, protocols to handle, cultivate and analyze the strains have been developed. Spectroscopic similarities and marked differences have been found for Spontaneous or Normal Raman spectra and for SERS using silver nanoparticles have been found. The use of principal component analysis (PCA), discriminate factor analysis (DFA) and a cluster analysis were used to evaluate the efficacy of identifying potential threat bacterial from their spectra collected on single bacteria. The DFA from the bacteria Raman spectra show a little discrimination between the diverse bacterial species however the results obtained from the SERS demonstrate to be high discrimination technique. The spectroscopic study will be extended to examine the spores produced by selected strains since these are more prone to be used as Biological Warfare Agents due to their increased mobility and possibility of airborne transport. Micro infrared spectroscopy as well as fiber coupled FTIR will also be used as possible sensors of target compounds.

Examining evolving performance on the Force Concept Inventory using factor analysis

NASA Astrophysics Data System (ADS)

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W.

2017-06-01

The application of factor analysis to the Force Concept Inventory (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a pre- and post-test, we see factor analysis as a tool by which the changes in conceptual associations made by our students may be gauged given the evolution of their response patterns. This analysis allows us to identify and track conceptual linkages, affording us insight as to how our students have matured due to instruction. We report on our analysis of 427 pre- and post-tests. The factor models for the pre- and post-tests are explored and compared along with the methodology by which these models were fit to the data. The post-test factor pattern is more aligned with an expert's interpretation of the questions' content, as it allows for a more readily identifiable relationship between factors and physical concepts. We discuss this evolution in the context of approaching the characteristics of an expert with force concepts. Also, we find that certain test items do not significantly contribute to the pre- or post-test factor models and attempt explanations as to why this is so. This may suggest that such questions may not be effective in probing the conceptual understanding of our students.

Confirmatory factor analysis using Microsoft Excel.

PubMed

Miles, Jeremy N V

2005-11-01

This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

Use of fatty acid methyl ester profiles for discrimination of Bacillus cereus T-strain spores grown on different media.

PubMed

Ehrhardt, Christopher J; Chu, Vivian; Brown, TeeCie; Simmons, Terrie L; Swan, Brandon K; Bannan, Jason; Robertson, James M

2010-03-01

The goal of this study was to determine if cellular fatty acid methyl ester (FAME) profiling could be used to distinguish among spore samples from a single species (Bacillus cereus T strain) that were prepared on 10 different medium formulations. To analyze profile differences and identify FAME biomarkers diagnostic for the chemical constituents in each sporulation medium, a variety of statistical techniques were used, including nonmetric multidimensional scaling (nMDS), analysis of similarities (ANOSIM), and discriminant function analysis (DFA). The results showed that one FAME biomarker, oleic acid (18:1 omega9c), was exclusively associated with spores grown on Columbia agar supplemented with sheep blood and was indicative of blood supplements that were present in the sporulation medium. For spores grown in other formulations, multivariate comparisons across several FAME biomarkers were required to discern profile differences. Clustering patterns in nMDS plots and R values from ANOSIM revealed that dissimilarities among FAME profiles were most pronounced when spores grown with disparate sources of complex additives or protein supplements were compared (R > 0.8), although other factors also contributed to FAME differences. DFA indicated that differentiation could be maximized with a targeted subset of FAME variables, and the relative contributions of branched FAME biomarkers to group dissimilarities changed when different media were compared. When taken together, these analyses indicate that B. cereus spore samples grown in different media can be resolved with FAME profiling and that this may be a useful technique for providing intelligence about the production methods of Bacillus organisms in a forensic investigation.

Use of Fatty Acid Methyl Ester Profiles for Discrimination of Bacillus cereus T-Strain Spores Grown on Different Media▿

PubMed Central

Ehrhardt, Christopher J.; Chu, Vivian; Brown, TeeCie; Simmons, Terrie L.; Swan, Brandon K.; Bannan, Jason; Robertson, James M.

2010-01-01

The goal of this study was to determine if cellular fatty acid methyl ester (FAME) profiling could be used to distinguish among spore samples from a single species (Bacillus cereus T strain) that were prepared on 10 different medium formulations. To analyze profile differences and identify FAME biomarkers diagnostic for the chemical constituents in each sporulation medium, a variety of statistical techniques were used, including nonmetric multidimensional scaling (nMDS), analysis of similarities (ANOSIM), and discriminant function analysis (DFA). The results showed that one FAME biomarker, oleic acid (18:1 ω9c), was exclusively associated with spores grown on Columbia agar supplemented with sheep blood and was indicative of blood supplements that were present in the sporulation medium. For spores grown in other formulations, multivariate comparisons across several FAME biomarkers were required to discern profile differences. Clustering patterns in nMDS plots and R values from ANOSIM revealed that dissimilarities among FAME profiles were most pronounced when spores grown with disparate sources of complex additives or protein supplements were compared (R > 0.8), although other factors also contributed to FAME differences. DFA indicated that differentiation could be maximized with a targeted subset of FAME variables, and the relative contributions of branched FAME biomarkers to group dissimilarities changed when different media were compared. When taken together, these analyses indicate that B. cereus spore samples grown in different media can be resolved with FAME profiling and that this may be a useful technique for providing intelligence about the production methods of Bacillus organisms in a forensic investigation. PMID:20097814

13 CFR 120.660 - Suspension or revocation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... rules and regulations. The D/FA may suspend or revoke the privilege of a Lender, broker, dealer, or.../FA may suspend or revoke the privilege of any broker or dealer to sell or otherwise deal in...) Notice to suspend or revoke. The D/FA shall notify the affected party in writing, providing the reasons...

Testing all six person-oriented principles in dynamic factor analysis.

PubMed

Molenaar, Peter C M

2010-05-01

All six person-oriented principles identified by Sterba and Bauer's Keynote Article can be tested by means of dynamic factor analysis in its current form. In particular, it is shown how complex interactions and interindividual differences/intraindividual change can be tested in this way. In addition, the necessity to use single-subject methods in the analysis of developmental processes is emphasized, and attention is drawn to the possibility to optimally treat developmental psychopathology by means of new computational techniques that can be integrated with dynamic factor analysis.

Gait performance is not influenced by working memory when walking at a self-selected pace.

PubMed

Grubaugh, Jordan; Rhea, Christopher K

2014-02-01

Gait performance exhibits patterns within the stride-to-stride variability that can be indexed using detrended fluctuation analysis (DFA). Previous work employing DFA has shown that gait patterns can be influenced by constraints, such as natural aging or disease, and they are informative regarding a person's functional ability. Many activities of daily living require concurrent performance in the cognitive and gait domains; specifically working memory is commonly engaged while walking, which is considered dual-tasking. It is unknown if taxing working memory while walking influences gait performance as assessed by DFA. This study used a dual-tasking paradigm to determine if performance decrements are observed in gait or working memory when performed concurrently. Healthy young participants (N = 16) performed a working memory task (automated operation span task) and a gait task (walking at a self-selected speed on a treadmill) in single- and dual-task conditions. A second dual-task condition (reading while walking) was included to control for visual attention, but also introduced a task that taxed working memory over the long term. All trials involving gait lasted at least 10 min. Performance in the working memory task was indexed using five dependent variables (absolute score, partial score, speed error, accuracy error, and math error), while gait performance was indexed by quantifying the mean, standard deviation, and DFA α of the stride interval time series. Two multivariate analyses of variance (one for gait and one for working memory) were used to examine performance in the single- and dual-task conditions. No differences were observed in any of the gait or working memory dependent variables as a function of task condition. The results suggest the locomotor system is adaptive enough to complete a working memory task without compromising gait performance when walking at a self-selected pace.

Exploratory factor analysis of borderline personality disorder criteria in hospitalized adolescents.

PubMed

Becker, Daniel F; McGlashan, Thomas H; Grilo, Carlos M

2006-01-01

The authors examined the factor structure of borderline personality disorder (BPD) in hospitalized adolescents and also sought to add to the theoretical and clinical understanding of any homogeneous components by determining whether they may be related to specific forms of Axis I pathology. Subjects were 123 adolescent inpatients, who were reliably assessed with structured diagnostic interviews for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition Axes I and II disorders. Exploratory factor analysis identified BPD components, and logistic regression analyses tested whether these components were predictive of specific Axis I disorders. Factor analysis revealed a 4-factor solution that accounted for 67.0% of the variance. Factor 1 ("suicidal threats or gestures" and "emptiness or boredom") predicted depressive disorders and alcohol use disorders. Factor 2 ("affective instability," "uncontrolled anger," and "identity disturbance") predicted anxiety disorders and oppositional defiant disorder. Factor 3 ("unstable relationships" and "abandonment fears") predicted only anxiety disorders. Factor 4 ("impulsiveness" and "identity disturbance") predicted conduct disorder and substance use disorders. Exploratory factor analysis of BPD criteria in adolescent inpatients revealed 4 BPD factors that appear to differ from those reported for similar studies of adults. The factors represent components of self-negation, irritability, poorly modulated relationships, and impulsivity--each of which is associated with characteristic Axis I pathology. These findings shed light on the nature of BPD in adolescents and may also have implications for treatment.

Exploratory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Reissmann, D R; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Szabo, G; Rener-Sitar, K

2014-09-01

Although oral health-related quality of life (OHRQoL) as measured by the Oral Health Impact Profile (OHIP) is thought to be multidimensional, the nature of these dimensions is not known. The aim of this report was to explore the dimensionality of the OHIP using the Dimensions of OHRQoL (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Learning Sample (n = 5173), we conducted an exploratory factor analysis on the 46 OHIP items not specifically referring to dentures for 5146 subjects with sufficiently complete data. The first eigenvalue (27·0) of the polychoric correlation matrix was more than ten times larger than the second eigenvalue (2·6), suggesting the presence of a dominant, higher-order general factor. Follow-up analyses with Horn's parallel analysis revealed a viable second-order, four-factor solution. An oblique rotation of this solution revealed four highly correlated factors that we named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact. These four dimensions and the strong general factor are two viable hypotheses for the factor structure of the OHIP. © 2014 John Wiley & Sons Ltd.

Factor analysis of an instrument to measure the impact of disease on daily life.

PubMed

Pedrosa, Rafaela Batista Dos Santos; Rodrigues, Roberta Cunha Matheus; Padilha, Kátia Melissa; Gallani, Maria Cecília Bueno Jayme; Alexandre, Neusa Maria Costa

2016-01-01

to verify the structure of factors of an instrument to measure the Heart Valve Disease Impact on Daily Life (IDCV) when applied to coronary artery disease patients. the study included 153 coronary artery disease patients undergoing outpatient follow-up care. The IDCV structure of factors was initially assessed by means of confirmatory factor analysis and, subsequently, by exploratory factor analysis. The Varimax rotation method was used to estimate the main components of analysis, eigenvalues greater than one for extraction of factors, and factor loading greater than 0.40 for selection of items. Internal consistency was estimated using Cronbach's alpha coefficient. confirmatory factor analysis did not confirm the original structure of factors of the IDCV. Exploratory factor analysis showed three dimensions, which together explained 78% of the measurement variance. future studies with expansion of case selection are necessary to confirm the IDCV new structure of factors.

AUTOMATED DEAD-END ULTRAFILTRATION FOR ENHANCED SURVEILLANCE OF LEGIONELLA 2 PNEUMOPHILA AND LEGIONELLA SPP. IN COOLING TOWER WATERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brigmon, R.; Leskinen, S.; Kearns, E.

2011-10-10

Detection of Legionella pneumophila in cooling towers and domestic hot water systems involves concentration by centrifugation or membrane filtration prior to inoculation onto growth media or analysis using techniques such as PCR or immunoassays. The Portable Multi-use Automated Concentration System (PMACS) was designed for concentrating microorganisms from large volumes of water in the field and was assessed for enhancing surveillance of L. pneumophila at the Savannah River Site, SC. PMACS samples (100 L; n = 28) were collected from six towers between August 2010 and April 2011 with grab samples (500 ml; n = 56) being collected before and aftermore » each PMACS sample. All samples were analyzed for the presence of L. pneumophila by direct fluorescence immunoassay (DFA) using FITC-labeled monoclonal antibodies targeting serogroups 1, 2, 4 and 6. QPCR was utilized for detection of Legionella spp. in the same samples. Counts of L. pneumophila from DFA and of Legionella spp. from qPCR were normalized to cells/L tower water. Concentrations were similar between grab and PMACS samples collected throughout the study by DFA analysis (P = 0.4461; repeated measures ANOVA). The same trend was observed with qPCR. However, PMACS concentration proved advantageous over membrane filtration by providing larger volume, more representative samples of the cooling tower environment, which led to reduced variability among sampling events and increasing the probability of detection of low level targets. These data highlight the utility of the PMACS for enhanced surveillance of L. pneumophila by providing improved sampling of the cooling tower environment.« less

A human factors analysis of EVA time requirements

NASA Technical Reports Server (NTRS)

Pate, D. W.

1996-01-01

Human Factors Engineering (HFE), also known as Ergonomics, is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. A human factors motion and time study was initiated with the goal of developing a database of EVA task times and a method of utilizing the database to predict how long an ExtraVehicular Activity (EVA) should take. Initial development relied on the EVA activities performed during the STS-61 mission (Hubble repair). The first step of the analysis was to become familiar with EVAs and with the previous studies and documents produced on EVAs. After reviewing these documents, an initial set of task primitives and task time modifiers was developed. Videotaped footage of STS-61 EVAs were analyzed using these primitives and task time modifiers. Data for two entire EVA missions and portions of several others, each with two EVA astronauts, was collected for analysis. Feedback from the analysis of the data will be used to further refine the primitives and task time modifiers used. Analysis of variance techniques for categorical data will be used to determine which factors may, individually or by interactions, effect the primitive times and how much of an effect they have.

Anti-correlation and multifractal features of Spain electricity spot market

NASA Astrophysics Data System (ADS)

Norouzzadeh, P.; Dullaert, W.; Rahmani, B.

2007-07-01

We use multifractal detrended fluctuation analysis (MF-DFA) to numerically investigate correlation, persistence, multifractal properties and scaling behavior of the hourly spot prices for the Spain electricity exchange-Compania O Peradora del Mercado de Electricidad (OMEL). Through multifractal analysis, fluctuations behavior, the scaling exponents and generalized Hurst exponents are studied. Moreover, contribution of fat-tailed probability distributions and nonlinear temporal correlations to multifractality is studied.

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rankmore » impacts both overcompleteness and sparsity.« less

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-01-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

Confirmatory factor analysis applied to the Force Concept Inventory

NASA Astrophysics Data System (ADS)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

Toward Reflective Judgment in Exploratory Factor Analysis Decisions: Determining the Extraction Method and Number of Factors To Retain.

ERIC Educational Resources Information Center

Knight, Jennifer L.

This paper considers some decisions that must be made by the researcher conducting an exploratory factor analysis. The primary purpose is to aid the researcher in making informed decisions during the factor analysis instead of relying on defaults in statistical programs or traditions of previous researchers. Three decision areas are addressed.…

Visual Analytics of integrated Data Systems for Space Weather Purposes

NASA Astrophysics Data System (ADS)

Rosa, Reinaldo; Veronese, Thalita; Giovani, Paulo

Analysis of information from multiple data sources obtained through high resolution instrumental measurements has become a fundamental task in all scientific areas. The development of expert methods able to treat such multi-source data systems, with both large variability and measurement extension, is a key for studying complex scientific phenomena, especially those related to systemic analysis in space and environmental sciences. In this talk, we present a time series generalization introducing the concept of generalized numerical lattice, which represents a discrete sequence of temporal measures for a given variable. In this novel representation approach each generalized numerical lattice brings post-analytical data information. We define a generalized numerical lattice as a set of three parameters representing the following data properties: dimensionality, size and post-analytical measure (e.g., the autocorrelation, Hurst exponent, etc)[1]. From this representation generalization, any multi-source database can be reduced to a closed set of classified time series in spatiotemporal generalized dimensions. As a case study, we show a preliminary application in space science data, highlighting the possibility of a real time analysis expert system. In this particular application, we have selected and analyzed, using detrended fluctuation analysis (DFA), several decimetric solar bursts associated to X flare-classes. The association with geomagnetic activity is also reported. DFA method is performed in the framework of a radio burst automatic monitoring system. Our results may characterize the variability pattern evolution, computing the DFA scaling exponent, scanning the time series by a short windowing before the extreme event [2]. For the first time, the application of systematic fluctuation analysis for space weather purposes is presented. The prototype for visual analytics is implemented in a Compute Unified Device Architecture (CUDA) by using the K20 Nvidia

SEPARABLE FACTOR ANALYSIS WITH APPLICATIONS TO MORTALITY DATA

PubMed Central

Fosdick, Bailey K.; Hoff, Peter D.

2014-01-01

Human mortality data sets can be expressed as multiway data arrays, the dimensions of which correspond to categories by which mortality rates are reported, such as age, sex, country and year. Regression models for such data typically assume an independent error distribution or an error model that allows for dependence along at most one or two dimensions of the data array. However, failing to account for other dependencies can lead to inefficient estimates of regression parameters, inaccurate standard errors and poor predictions. An alternative to assuming independent errors is to allow for dependence along each dimension of the array using a separable covariance model. However, the number of parameters in this model increases rapidly with the dimensions of the array and, for many arrays, maximum likelihood estimates of the covariance parameters do not exist. In this paper, we propose a submodel of the separable covariance model that estimates the covariance matrix for each dimension as having factor analytic structure. This model can be viewed as an extension of factor analysis to array-valued data, as it uses a factor model to estimate the covariance along each dimension of the array. We discuss properties of this model as they relate to ordinary factor analysis, describe maximum likelihood and Bayesian estimation methods, and provide a likelihood ratio testing procedure for selecting the factor model ranks. We apply this methodology to the analysis of data from the Human Mortality Database, and show in a cross-validation experiment how it outperforms simpler methods. Additionally, we use this model to impute mortality rates for countries that have no mortality data for several years. Unlike other approaches, our methodology is able to estimate similarities between the mortality rates of countries, time periods and sexes, and use this information to assist with the imputations. PMID:25489353

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

NASA Astrophysics Data System (ADS)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

Physics Metacognition Inventory Part Ii: Confirmatory Factor Analysis and Rasch Analysis

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-01-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition,…

Connectivism in Postsecondary Online Courses: An Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hogg, Nanette; Lomicky, Carol S.

2012-01-01

This study explores 465 postsecondary students' experiences in online classes through the lens of connectivism. Downes' 4 properties of connectivism (diversity, autonomy, interactivity, and openness) were used as the study design. An exploratory factor analysis was performed. This study found a 4-factor solution. Subjects indicated that autonomy…

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

PubMed Central

2012-01-01

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.

PubMed

Duffy, Frank H; Als, Heidelise

2012-06-26

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences

Evaluating voice characteristics of first-year acting students in Israel: factor analysis.

PubMed

Amir, Ofer; Primov-Fever, Adi; Kushnir, Tami; Kandelshine-Waldman, Osnat; Wolf, Michael

2013-01-01

Acting students require diverse, high-quality, and high-intensity vocal performance from early stages of their training. Demanding vocal activities, before developing the appropriate vocal skills, put them in high risk for developing vocal problems. A retrospective analysis of voice characteristics of first-year acting students using several voice evaluation tools. A total of 79 first-year acting students (55 women and 24 men) were assigned into two study groups: laryngeal findings (LFs) and no laryngeal findings, based on stroboscopic findings. Their voice characteristics were evaluated using acoustic analysis, aerodynamic examination, perceptual scales, and self-report questionnaires. Results obtained from each set of measures were examined using a factor analysis approach. Significant differences between the two groups were found for a single fundamental frequency (F(0))-Regularity factor; a single Grade, Roughness, Breathiness, Asthenia, Strain perceptual factor; and the three self-evaluation factors. Gender differences were found for two acoustic analysis factors, which were based on F(0) and its derivatives, namely an aerodynamic factor that represents expiratory volume measurements and a single self-evaluation factor that represents the tendency to seek therapy. Approximately 50% of the first-year acting students had LFs. These students differed from their peers in the control group in a single acoustic analysis factor, as well as perceptual and self-report factors. No group differences, however, were found for the aerodynamic factors. Early laryngeal examination and voice evaluation of future professional voice users could provide a valuable individual baseline, to which later examinations could be compared, and assist in providing personally tailored treatment. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Establishing Evidence for Internal Structure Using Exploratory Factor Analysis

ERIC Educational Resources Information Center

Watson, Joshua C.

2017-01-01

Exploratory factor analysis (EFA) is a data reduction technique used to condense data into smaller sets of summary variables by identifying underlying factors potentially accounting for patterns of collinearity among said variables. Using an illustrative example, the 5 general steps of EFA are described with best practices for decision making…

An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

NASA Astrophysics Data System (ADS)

Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

2017-12-01

For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

Price-volume multifractal analysis of the Moroccan stock market

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2017-11-01

In this paper, we analyzed price-volume multifractal cross-correlations of Moroccan Stock Exchange. We chose the period from January 1st 2000 to January 20th 2017 to investigate the multifractal behavior of price change and volume change series. Then, we used multifractal detrended cross-correlations analysis method (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) to analyze the series. We computed bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively cross-correlations. Furthermore, we used detrended cross-correlations coefficient (DCCA) and cross-correlation test (Q(m)) to analyze cross-correlation quantitatively and qualitatively. By analyzing results, we found existence of price-volume multifractal cross-correlations. The spectrum width has a strong multifractal cross-correlation. We remarked that volume change series is anti-persistent when we analyzed the generalized Hurst exponent for all moments q. The cross-correlation test showed the presence of a significant cross-correlation. However, DCCA coefficient had a small positive value, which means that the level of correlation is not very significant. Finally, we analyzed sources of multifractality and their degree of contribution in the series.

Analysis of the influencing factors of global energy interconnection development

NASA Astrophysics Data System (ADS)

Zhang, Yi; He, Yongxiu; Ge, Sifan; Liu, Lin

2018-04-01

Under the background of building global energy interconnection and achieving green and low-carbon development, this paper grasps a new round of energy restructuring and the trend of energy technology change, based on the present situation of global and China's global energy interconnection development, established the index system of the impact of global energy interconnection development factors. A subjective and objective weight analysis of the factors affecting the development of the global energy interconnection was conducted separately by network level analysis and entropy method, and the weights are summed up by the method of additive integration, which gives the comprehensive weight of the influencing factors and the ranking of their influence.

Determination of trace metal concentrations in ginseng (Panax Quinquefolius (American)) roots for forensic comparison using Inductively Coupled Plasma Mass-Spectrometry.

PubMed

Peake, Barrie M; Tong, Alfred Y C; Wells, William J; Harraway, John A; Niven, Brian E; Weege, Butch; LaFollette, Douglas J

2015-06-01

The trace metal content of roots of samples of the American ginseng natural herbal plant species (Panax quinquefolius) was investigated as a means of differentiating between this species grown on Wisconsin and New Zealand farms, and from Canadian and Chinese sources. ICP-MS measurements were undertaken by ashing samples of the roots and then digestion with conc. HNO3 and H2O2. There was considerable variation in the concentrations of 28 detectable elements along the length of a root, between different roots, between different farms/sources and between different countries. Statistical processing of the log-transformed concentration data was undertaken using principal component analysis (PCA) and discriminant function analysis (DFA). Although PCA showed some differentiation between samples, a much clearer discrimination of the Panax quinquefolius species of ginseng from the four countries was observed using DFA. 88% of the variation between countries could be accounted for by only using discriminant function 1 while 80% of the remaining 12% of the variation between countries is accounted for by discriminant function 2. The Fisher Classification Functions classify 98% of the 87 samples to the correct country of origin with 97% of the cross-validated cases correctly classified. The predictive ability of this DFA model was further tested by constructing 100 discriminant models each using a random selection of the data for two thirds of the 87 sampled ginseng root tops, and then using the resulting classification functions to determine correctly the country of origin of the remaining third of the cases. The mean success rate of the 100 classifications was 92%. These results suggest that measurement and statistical analysis of just the trace metal content of the roots of Panax quinquefolius promises to be an excellent predictor of the country of origin of this ginseng species. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Examining Evolving Performance on the Force Concept Inventory Using Factor Analysis

ERIC Educational Resources Information Center

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W

2017-01-01

The application of factor analysis to the "Force Concept Inventory" (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a…

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Edwards, Michael C.

2010-01-01

Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR

ERIC Educational Resources Information Center

Baglin, James

2014-01-01

Exploratory factor analysis (EFA) methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many…

Factor analysis of the contextual fine motor questionnaire in children.

PubMed

Lin, Chin-Kai; Meng, Ling-Fu; Yu, Ya-Wen; Chen, Che-Kuo; Li, Kuan-Hua

2014-02-01

Most studies treat fine motor as one subscale in a developmental test, hence, further factor analysis of fine motor has not been conducted. In fact, fine motor has been treated as a multi-dimensional domain from both clinical and theoretical perspectives, and therefore to know its factors would be valuable. The aim of this study is to analyze the internal consistency and factor validity of the Contextual Fine Motor Questionnaire (CFMQ). Based on the ecological observation and literature, the Contextual Fine Motor Questionnaire (CFMQ) was developed and includes 5 subscales: Pen Control, Tool Use During Handicraft Activities, the Use of Dining Utensils, Connecting and Separating during Dressing and Undressing, and Opening Containers. The main purpose of this study is to establish the factorial validity of the CFMQ through conducting this factor analysis study. Among 1208 questionnaires, 904 were successfully completed. Data from the children's CFMQ submitted by primary care providers was analyzed, including 485 females (53.6%) and 419 males (46.4%) from grades 1 to 5, ranging in age from 82 to 167 months (M=113.9, SD=16.3). Cronbach's alpha was used to measure internal consistency and explorative factor analysis was applied to test the five factor structures within the CFMQ. Results showed that Cronbach's alpha coefficient of the CFMQ for 5 subscales ranged from .77 to .92 and all item-total correlations with corresponding subscales were larger than .4 except one item. The factor loading of almost all items classified to their factor was larger than .5 except 3 items. There were five factors, explaining a total of 62.59% variance for the CFMQ. In conclusion, the remaining 24 items in the 5 subscales of the CFMQ had appropriate internal consistency, test-retest reliability and construct validity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Investigation of tool wear and surface roughness on machining of titanium alloy with MT-CVD cutting tool

NASA Astrophysics Data System (ADS)

Maity, Kalipada; Pradhan, Swastik

2018-04-01

In this study, machining of titanium alloy (grade 5) is carried out using MT-CVD coated cutting tool. Titanium alloys possess superior strength-to-weight ratio with good corrosion resistance. Most of the industries used titanium alloy for the manufacturing of various types of lightweight components. The parts made from Ti-6Al-4V largely used in aerospace, biomedical, automotive and marine sectors. The conventional machining of this material is very difficult, due to low thermal conductivity and high chemical reactivity properties. To achieve a good surface finish with minimum tool wear of cutting tool, the machining is carried out using MT-CVD coated cutting tool. The experiment is carried out using of Taguchi L27 array layout with three cutting variables and levels. To find out the optimum parametric setting desirability function analysis (DFA) approach is used. The analysis of variance is studied to know the percentage contribution of each cutting variables. The optimum parametric setting results calculated from DFA were validated through the confirmation test.

Statistical properties of DNA sequences

NASA Technical Reports Server (NTRS)

Peng, C. K.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Simons, M.; Stanley, H. E.

1995-01-01

We review evidence supporting the idea that the DNA sequence in genes containing non-coding regions is correlated, and that the correlation is remarkably long range--indeed, nucleotides thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationarity" feature of the sequence of base pairs by applying a new algorithm called detrended fluctuation analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and non-coding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33301 coding and 29453 non-coding) in the entire GenBank database. Finally, we describe briefly some recent work showing that the non-coding sequences have certain statistical features in common with natural and artificial languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts. These statistical properties of non-coding sequences support the possibility that non-coding regions of DNA may carry biological information.

Scaling of seismic memory with earthquake size

NASA Astrophysics Data System (ADS)

Zheng, Zeyu; Yamasaki, Kazuko; Tenenbaum, Joel; Podobnik, Boris; Tamura, Yoshiyasu; Stanley, H. Eugene

2012-07-01

It has been observed that discrete earthquake events possess memory, i.e., that events occurring in a particular location are dependent on the history of that location. We conduct an analysis to see whether continuous real-time data also display a similar memory and, if so, whether such autocorrelations depend on the size of earthquakes within close spatiotemporal proximity. We analyze the seismic wave form database recorded by 64 stations in Japan, including the 2011 “Great East Japan Earthquake,” one of the five most powerful earthquakes ever recorded, which resulted in a tsunami and devastating nuclear accidents. We explore the question of seismic memory through use of mean conditional intervals and detrended fluctuation analysis (DFA). We find that the wave form sign series show power-law anticorrelations while the interval series show power-law correlations. We find size dependence in earthquake autocorrelations: as the earthquake size increases, both of these correlation behaviors strengthen. We also find that the DFA scaling exponent α has no dependence on the earthquake hypocenter depth or epicentral distance.

Assessing suicide risk among callers to crisis hotlines: a confirmatory factor analysis.

PubMed

Witte, Tracy K; Gould, Madelyn S; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E; Kalafat, John

2010-09-01

Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. We conducted an Exploratory Factor Analysis (EFA), an EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and a CFA on independent subsamples derived from a total sample of 1,085. Similar to previous studies, we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations; RPP) and one factor representing milder suicidal ideation (i.e., Suicidal Desire and Ideation; SDI). The RPP factor trended toward being more predictive of suicidal ideation at follow-up than the SDI factor. (c) 2010 Wiley Periodicals, Inc.

Factor analysis of serogroups botanica and aurisina of Leptospira biflexa.

PubMed

Cinco, M

1977-11-01

Factor analysis is performed on serovars of Botanica and Aurisina serogroup of Leptospira biflexa. The results show the arrangement of main factors serovar and serogroup specific, as well as the antigens common with serovars of heterologous serogroups.

Risk factors for baclofen pump infection in children: a multivariate analysis.

PubMed

Spader, Heather S; Bollo, Robert J; Bowers, Christian A; Riva-Cambrin, Jay

2016-06-01

OBJECTIVE Intrathecal baclofen infusion systems to manage severe spasticity and dystonia are associated with higher infection rates in children than in adults. Factors unique to this population, such as poor nutrition and physical limitations for pump placement, have been hypothesized as the reasons for this disparity. The authors assessed potential risk factors for infection in a multivariate analysis. METHODS Patients who underwent implantation of a programmable pump and intrathecal catheter for baclofen infusion at a single center between January 1, 2000, and March 1, 2012, were identified in this retrospective cohort study. The primary end point was infection. Potential risk factors investigated included preoperative (i.e., demographics, body mass index [BMI], gastrostomy tube, tracheostomy, previous spinal fusion), intraoperative (i.e., surgeon, antibiotics, pump size, catheter location), and postoperative (i.e., wound dehiscence, CSF leak, and number of revisions) factors. Univariate analysis was performed, and a multivariate logistic regression model was created to identify independent risk factors for infection. RESULTS A total of 254 patients were evaluated. The overall infection rate was 9.8%. Univariate analysis identified young age, shorter height, lower weight, dehiscence, CSF leak, and number of revisions within 6 months of pump placement as significantly associated with infection. Multivariate analysis identified young age, dehiscence, and number of revisions as independent risk factors for infection. CONCLUSIONS Young age, wound dehiscence, and number of revisions were independent risk factors for infection in this pediatric cohort. A low BMI and the presence of either a gastrostomy or tracheostomy were not associated with infection and may not be contraindications for this procedure.

FACTOR 9.2: A Comprehensive Program for Fitting Exploratory and Semiconfirmatory Factor Analysis and IRT Models

ERIC Educational Resources Information Center

Lorenzo-Seva, Urbano; Ferrando, Pere J.

2013-01-01

FACTOR 9.2 was developed for three reasons. First, exploratory factor analysis (FA) is still an active field of research although most recent developments have not been incorporated into available programs. Second, there is now renewed interest in semiconfirmatory (SC) solutions as suitable approaches to the complex structures are commonly found…

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Process factors of enzyme concentration, time, power and frequency were investigated for ultrasound-enhanced bioscouring of greige cotton. A fractional factorial experimental design and subsequent regression analysis of the process factors were employed to determine the significance of each factor a...

Identifying influential factors of business process performance using dependency analysis

NASA Astrophysics Data System (ADS)

Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

2011-02-01

We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

The detection and stabilisation of limit cycle for deterministic finite automata

NASA Astrophysics Data System (ADS)

Han, Xiaoguang; Chen, Zengqiang; Liu, Zhongxin; Zhang, Qing

2018-04-01

In this paper, the topological structure properties of deterministic finite automata (DFA), under the framework of the semi-tensor product of matrices, are investigated. First, the dynamics of DFA are converted into a new algebraic form as a discrete-time linear system by means of Boolean algebra. Using this algebraic description, the approach of calculating the limit cycles of different lengths is given. Second, we present two fundamental concepts, namely, domain of attraction of limit cycle and prereachability set. Based on the prereachability set, an explicit solution of calculating domain of attraction of a limit cycle is completely characterised. Third, we define the globally attractive limit cycle, and then the necessary and sufficient condition for verifying whether all state trajectories of a DFA enter a given limit cycle in a finite number of transitions is given. Fourth, the problem of whether a DFA can be stabilised to a limit cycle by the state feedback controller is discussed. Criteria for limit cycle-stabilisation are established. All state feedback controllers which implement the minimal length trajectories from each state to the limit cycle are obtained by using the proposed algorithm. Finally, an illustrative example is presented to show the theoretical results.

Confirmatory Factor Analysis of the WISC-III with Child Psychiatric Inpatients.

ERIC Educational Resources Information Center

Tupa, David J.; Wright, Margaret O'Dougherty; Fristad, Mary A.

1997-01-01

Factor models of the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) for one, two, three, and four factors were tested using confirmatory factor analysis with a sample of 177 child psychiatric inpatients. The four-factor model proposed in the WISC-III manual provided the best fit to the data. (SLD)

Emotional experiences and motivating factors associated with fingerprint analysis.

PubMed

Charlton, David; Fraser-Mackenzie, Peter A F; Dror, Itiel E

2010-03-01

In this study, we investigated the emotional and motivational factors involved in fingerprint analysis in day-to-day routine case work and in significant and harrowing criminal investigations. Thematic analysis was performed on interviews with 13 experienced fingerprint examiners from a variety of law enforcement agencies. The data revealed factors relating to job satisfaction and the use of skill. Individual satisfaction related to catching criminals was observed; this was most notable in solving high profile, serious, or long-running cases. There were positive emotional effects associated with matching fingerprints and apparent fear of making errors. Finally, we found evidence for a need of cognitive closure in fingerprint examiner decision-making.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

Asymmetric multiscale detrended fluctuation analysis of California electricity spot price

NASA Astrophysics Data System (ADS)

Fan, Qingju

2016-01-01

In this paper, we develop a new method called asymmetric multiscale detrended fluctuation analysis, which is an extension of asymmetric detrended fluctuation analysis (A-DFA) and can assess the asymmetry correlation properties of series with a variable scale range. We investigate the asymmetric correlations in California 1999-2000 power market after filtering some periodic trends by empirical mode decomposition (EMD). Our findings show the coexistence of symmetric and asymmetric correlations in the price series of 1999 and strong asymmetric correlations in 2000. What is more, we detect subtle correlation properties of the upward and downward price series for most larger scale intervals in 2000. Meanwhile, the fluctuations of Δα(s) (asymmetry) and | Δα(s) | (absolute asymmetry) are more significant in 2000 than that in 1999 for larger scale intervals, and they have similar characteristics for smaller scale intervals. We conclude that the strong asymmetry property and different correlation properties of upward and downward price series for larger scale intervals in 2000 have important implications on the collapse of California power market, and our findings shed a new light on the underlying mechanisms of power price.

What Is Rotating in Exploratory Factor Analysis?

ERIC Educational Resources Information Center

Osborne, Jason W.

2015-01-01

Exploratory factor analysis (EFA) is one of the most commonly-reported quantitative methodology in the social sciences, yet much of the detail regarding what happens during an EFA remains unclear. The goal of this brief technical note is to explore what "rotation" is, what exactly is rotating, and why we use rotation when performing…

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

NASA Astrophysics Data System (ADS)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Confirmatory Factor Analysis of the Delirium Rating Scale Revised-98 (DRS-R98).

PubMed

Thurber, Steven; Kishi, Yasuhiro; Trzepacz, Paula T; Franco, Jose G; Meagher, David J; Lee, Yanghyun; Kim, Jeong-Lan; Furlanetto, Leticia M; Negreiros, Daniel; Huang, Ming-Chyi; Chen, Chun-Hsin; Kean, Jacob; Leonard, Maeve

2015-01-01

Principal components analysis applied to the Delirium Rating Scale-Revised-98 contributes to understanding the delirium construct. Using a multisite pooled international delirium database, the authors applied confirmatory factor analysis to Delirium Rating Scale-Revised-98 scores from 859 adult patients evaluated by delirium experts (delirium, N=516; nondelirium, N=343). Confirmatory factor analysis found all diagnostic features and core symptoms (cognitive, language, thought process, sleep-wake cycle, motor retardation), except motor agitation, loaded onto factor 1. Motor agitation loaded onto factor 2 with noncore symptoms (delusions, affective lability, and perceptual disturbances). Factor 1 loading supports delirium as a single construct, but when accompanied by psychosis, motor agitation's role may not be solely as a circadian activity indicator.

Factor Analysis of the Aberrant Behavior Checklist in Individuals with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Brinkley, Jason; Nations, Laura; Abramson, Ruth K.; Hall, Alicia; Wright, Harry H.; Gabriels, Robin; Gilbert, John R.; Pericak-Vance, Margaret A. O.; Cuccaro, Michael L.

2007-01-01

Exploratory factor analysis (varimax and promax rotations) of the aberrant behavior checklist-community version (ABC) in 275 individuals with Autism spectrum disorder (ASD) identified four- and five-factor solutions which accounted for greater than 70% of the variance. Confirmatory factor analysis (Lisrel 8.7) revealed indices of moderate fit for…

A factor analysis of landscape pattern and structure metrics

Treesearch

Kurt H. Riitters; R.V. O' Neill; C.T. Hunsaker; James D. Wickham; D.H. Yankee; S.P. Timmins; K.B. Jones; B.L. Jackson

1995-01-01

Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These...

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

PubMed

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Bayes factor design analysis: Planning for compelling evidence.

PubMed

Schönbrodt, Felix D; Wagenmakers, Eric-Jan

2018-02-01

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis significance testing (NHST) paradigm to facilitate the design of informative experiments. In contrast, there is almost no literature that discusses the design of experiments when Bayes factors (BFs) are used as a measure of evidence. Here we explore Bayes Factor Design Analysis (BFDA) as a useful tool to design studies for maximum efficiency and informativeness. We elaborate on three possible BF designs, (a) a fixed-n design, (b) an open-ended Sequential Bayes Factor (SBF) design, where researchers can test after each participant and can stop data collection whenever there is strong evidence for either [Formula: see text] or [Formula: see text], and (c) a modified SBF design that defines a maximal sample size where data collection is stopped regardless of the current state of evidence. We demonstrate how the properties of each design (i.e., expected strength of evidence, expected sample size, expected probability of misleading evidence, expected probability of weak evidence) can be evaluated using Monte Carlo simulations and equip researchers with the necessary information to compute their own Bayesian design analyses.

Application of the Bootstrap Methods in Factor Analysis.

ERIC Educational Resources Information Center

Ichikawa, Masanori; Konishi, Sadanori

1995-01-01

A Monte Carlo experiment was conducted to investigate the performance of bootstrap methods in normal theory maximum likelihood factor analysis when the distributional assumption was satisfied or unsatisfied. Problems arising with the use of bootstrap methods are highlighted. (SLD)

Exploratory Factor Analysis with Small Sample Sizes

ERIC Educational Resources Information Center

de Winter, J. C. F.; Dodou, D.; Wieringa, P. A.

2009-01-01

Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…

Space Human Factors Engineering Gap Analysis Project Final Report

NASA Technical Reports Server (NTRS)

Hudy, Cynthia; Woolford, Barbara

2006-01-01

Humans perform critical functions throughout each phase of every space mission, beginning with the mission concept and continuing to post-mission analysis (Life Sciences Division, 1996). Space missions present humans with many challenges - the microgravity environment, relative isolation, and inherent dangers of the mission all present unique issues. As mission duration and distance from Earth increases, in-flight crew autonomy will increase along with increased complexity. As efforts for exploring the moon and Mars advance, there is a need for space human factors research and technology development to play a significant role in both on-orbit human-system interaction, as well as the development of mission requirements and needs before and after the mission. As part of the Space Human Factors Engineering (SHFE) Project within the Human Research Program (HRP), a six-month Gap Analysis Project (GAP) was funded to identify any human factors research gaps or knowledge needs. The overall aim of the project was to review the current state of human factors topic areas and requirements to determine what data, processes, or tools are needed to aid in the planning and development of future exploration missions, and also to prioritize proposals for future research and technology development.

Psychiatric research and science policy in Germany: the history of the Deutsche Forschungsanstalt fur Psychiatrie (German Institute for Psychiatric Research) in Munich from 1917 to 1945).

PubMed

Weber, M M

2000-09-01

The Deutsche Forschungsanstalt fur Psychiatrie (DFA) in Munich, one of the most important research institutes in the field of theoretical and clinical psychiatry, was founded in 1917 by Emil Kraepelin. Its financial existence between the world wars was assured by generous donations from the Jewish American scholar and philanthropist James Loeb. The scientific work done by Walther Spielmeyer (neuropathology), Felix Plaut (serology), Kurt Schneider (clinical psychiatry) and Ernst Rudin (psychiatric genetics) earned the DFA a reputation as an international center for psychiatry and neurology. During the 'Third Reich' Ernst Rudin cooperated with the National Socialist health system. His genetic concepts provided support for eugenic programmes such as forced sterilization of individuals with psychoses. These complex interactions underscore the importance of the DFA in understanding the recent history of medicine in Germany.

Assessing Suicide Risk Among Callers to Crisis Hotlines: A Confirmatory Factor Analysis

PubMed Central

Witte, Tracy K.; Gould, Madelyn S.; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E.; Kalafat, John

2012-01-01

Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. 1,085 suicidal callers to crisis hotlines were divided into three sub-samples, which allowed us to conduct an independent Exploratory Factor Analysis (EFA), EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and CFA. Similar to previous factor analytic studies (Beck et al., 1997; Holden & DeLisle, 2005; Joiner, Rudd, & Rajab, 1997; Witte et al., 2006), we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations) and one factor representing more mild suicidal ideation (i.e., Suicidal Desire and Ideation). Using structural equation modeling techniques, we found preliminary evidence that the Resolved Plans and Preparations factor trended toward being more predictive of suicidal ideation than the Suicidal Desire and Ideation factor. This factor analytic study is the first longitudinal study of the obtained factors. PMID:20578186

Factor analysis of some socio-economic and demographic variables for Bangladesh.

PubMed

Islam, S M

1986-01-01

The author carries out an exploratory factor analysis of some socioeconomic and demographic variables for Bangladesh using the classical or common factor approach with the varimax rotation method. The socioeconomic and demographic indicators used in this study include literacy, rate of growth, female employment, economic development, urbanization, population density, childlessness, sex ratio, proportion of women ever married, and fertility. The 18 administrative districts of Bangladesh constitute the unit of analysis. 3 common factors--modernization, fertility, and social progress--are identified in this study to explain the correlations among the set of selected socioeconomic and demographic variables.

Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

PubMed

Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-09-01

Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. �

Bayesian Factor Analysis as a Variable Selection Problem: Alternative Priors and Consequences

PubMed Central

Lu, Zhao-Hua; Chow, Sy-Miin; Loken, Eric

2016-01-01

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, a Bayesian structural equation modeling (BSEM) approach (Muthén & Asparouhov, 2012) has been proposed as a way to explore the presence of cross-loadings in CFA models. We show that the issue of determining factor loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov’s approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike and slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set (Byrne, 2012; Pettegrew & Wolf, 1982) is used to demonstrate our approach. PMID:27314566

Confirmatory Factor Analysis of the Cancer Locus of Control Scale.

ERIC Educational Resources Information Center

Henderson, Jessica W.; Donatelle, Rebecca J.; Acock, Alan C.

2002-01-01

Conducted a confirmatory factor analysis of the Cancer Locus of Control scale (M. Watson and others, 1990), administered to 543 women with a history of breast cancer. Results support a three-factor model of the scale and support use of the scale to assess control dimensions. (SLD)

Analysis of Social Cohesion in Health Data by Factor Analysis Method: The Ghanaian Perspective

ERIC Educational Resources Information Center

Saeed, Bashiru I. I.; Xicang, Zhao; Musah, A. A. I.; Abdul-Aziz, A. R.; Yawson, Alfred; Karim, Azumah

2013-01-01

We investigated the study of the overall social cohesion of Ghanaians. In this study, we considered the paramount interest of the involvement of Ghanaians in their communities, their views of other people and institutions, and their level of interest in both local and national politics. The factor analysis method was employed for analysis using R…

Evidence Regarding the Internal Structure: Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Lewis, Todd F.

2017-01-01

American Educational Research Association (AERA) standards stipulate that researchers show evidence of the internal structure of instruments. Confirmatory factor analysis (CFA) is one structural equation modeling procedure designed to assess construct validity of assessments that has broad applicability for counselors interested in instrument…

Factor Structure of the Student-Teacher Relationship Scale for Norwegian School-Age Children Explored with Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Drugli, May Britt; Hjemdal, Odin

2013-01-01

The validity of the Student-Teacher Relationship Scale (STRS) was examined in a national sample of 863 Norwegian schoolchildren in grades 1-7 (aged 6-13). The original factor structure of the STRS was tested by confirmatory factor analysis (CFA). The CFA results did not support the original three-factor structure of the STRS. Subsequent CFA of the…

The School Counselor Leadership Survey: Instrument Development and Exploratory Factor Analysis

ERIC Educational Resources Information Center

Young, Anita; Bryan, Julia

2015-01-01

This study examined the factor structure of the School Counselor Leadership Survey (SCLS). Survey development was a threefold process that resulted in a 39-item survey of 801 school counselors and school counselor supervisors. The exploratory factor analysis indicated a five-factor structure that revealed five key dimensions of school counselor…

Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Cheng, Ying; Zhang, Wei

2010-01-01

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found.…

A Primer on Bootstrap Factor Analysis as Applied to Health Studies Research

ERIC Educational Resources Information Center

Lu, Wenhua; Miao, Jingang; McKyer, E. Lisako J.

2014-01-01

Objectives: To demonstrate how the bootstrap method could be conducted in exploratory factor analysis (EFA) with a syntax written in SPSS. Methods: The data obtained from the Texas Childhood Obesity Prevention Policy Evaluation project (T-COPPE project) were used for illustration. A 5-step procedure to conduct bootstrap factor analysis (BFA) was…

Understanding Older Adults' Perceptions of Internet Use: An Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zheng, Robert; Spears, Jeffrey; Luptak, Marilyn; Wilby, Frances

2015-01-01

The current study examined factors related to older adults' perceptions of Internet use. Three hundred ninety five older adults participated in the study. The factor analysis revealed four factors perceived by older adults as critical to their Internet use: social connection, self-efficacy, the need to seek financial information, and the need to…

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Confirmatory factor analysis of the Child Oral Health Impact Profile (Korean version).

PubMed

Cho, Young Il; Lee, Soonmook; Patton, Lauren L; Kim, Hae-Young

2016-04-01

Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score. © 2016 Eur J Oral Sci.

Risk analysis of the thermal sterilization process. Analysis of factors affecting the thermal resistance of microorganisms.

PubMed

Akterian, S G; Fernandez, P S; Hendrickx, M E; Tobback, P P; Periago, P M; Martinez, A

1999-03-01

A risk analysis was applied to experimental heat resistance data. This analysis is an approach for processing experimental thermobacteriological data in order to study the variability of D and z values of target microorganisms depending on the deviations range of environmental factors, to determine the critical factors and to specify their critical tolerance. This analysis is based on sets of sensitivity functions applied to a specific case of experimental data related to the thermoresistance of Clostridium sporogenes and Bacillus stearothermophilus spores. The effect of the following factors was analyzed: the type of target microorganism; nature of the heating substrate; pH, temperature; type of acid employed and NaCl concentration. The type of target microorganism to be inactivated, the nature of the substrate (reference or real food) and the heating temperature were identified as critical factors, determining about 90% of the alteration of the microbiological risk. The effect of the type of acid used for the acidification of products and the concentration of NaCl can be assumed to be negligible factors for the purposes of engineering calculations. The critical non-uniformity in temperature during thermobacteriological studies was set as 0.5% and the critical tolerances of pH value and NaCl concentration were 5%. These results are related to a specific case study, for that reason their direct generalization is not correct.

Chemical factor analysis of skin cancer FTIR-FEW spectroscopic data

NASA Astrophysics Data System (ADS)

Bruch, Reinhard F.; Sukuta, Sydney

2002-03-01

Chemical Factor Analysis (CFA) algorithms were applied to transform complex Fourier transform infrared fiberoptical evanescent wave (FTIR-FEW) normal and malignant skin tissue spectra into factor spaces for analysis and classification. The factor space approach classified melanoma beyond prior pathological classifications related to specific biochemical alterations to health states in cluster diagrams allowing diagnosis with more biochemical specificity, resolving biochemical component spectra and employing health state eigenvector angular configurations as disease state sensors. This study demonstrated a wealth of new information from in vivo FTIR-FEW spectral tissue data, without extensive a priori information or clinically invasive procedures. In particular, we employed a variety of methods used in CFA to select the rank of spectroscopic data sets of normal benign and cancerous skin tissue. We used the Malinowski indicator function (IND), significance level and F-Tests to rank our data matrices. Normal skin tissue, melanoma and benign tumors were modeled by four, two and seven principal abstract factors, respectively. We also showed that the spectrum of the first eigenvalue was equivalent to the mean spectrum. The graphical depiction of angular disparities between the first abstract factors can be adopted as a new way to characterize and diagnose melanoma cancer.

Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

PubMed Central

Flora, David B.; LaBrish, Cathy; Chalmers, R. Philip

2011-01-01

We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables. PMID:22403561

Pathogenic Escherichia coli strain discrimination using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Diedrich, Jonathan; Rehse, Steven J.; Palchaudhuri, Sunil

2007-07-01

A pathogenic strain of bacteria, Escherichia coli O157:H7 (enterohemorrhagic E. coli or EHEC), has been analyzed by laser-induced breakdown spectroscopy (LIBS) with nanosecond pulses and compared to three nonpathogenic E. coli strains: a laboratory strain of K-12 (AB), a derivative of the same strain termed HF4714, and an environmental strain, E. coli C (Nino C). A discriminant function analysis (DFA) was performed on the LIBS spectra obtained from live colonies of all four strains. Utilizing the emission intensity of 19 atomic and ionic transitions from trace inorganic elements, the DFA revealed significant differences between EHEC and the Nino C strain, suggesting the possibility of identifying and discriminating the pathogenic strain from commonly occurring environmental strains. EHEC strongly resembled the two K-12 strains, in particular, HF4714, making discrimination between these strains difficult. DFA was also used to analyze spectra from two of the nonpathogenic strains cultured in different media: on a trypticase soy (TS) agar plate and in a liquid TS broth. Strains cultured in different media were identified and effectively discriminated, being more similar than different strains cultured in identical media. All bacteria spectra were completely distinct from spectra obtained from the nutrient medium or ablation substrate alone. The ability to differentiate strains prepared and tested in different environments indicates that matrix effects and background contaminations do not necessarily preclude the use of LIBS to identify bacteria found in a variety of environments or grown under different conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skordas, E. S., E-mail: eskordas@phys.uoa.gr

By applying Detrended Fluctuation Analysis (DFA) to the time series of the geomagnetic data recorded at three measuring stations in Japan, Rong et al. in 2012 recently reported that anomalous magnetic field variations were identified well before the occurrence of the disastrous Tohoku M{sub w}9.0 earthquake that occurred on 11 March 2011 in Japan exhibiting increased “non-uniform” scaling behavior. Here, we provide an explanation for the appearance of this increase of “non-uniform” scaling on the following grounds: These magnetic field variations are the ones that accompany the electric field variations termed Seismic Electric Signals (SES) activity which have been repeatedlymore » reported that precede major earthquakes. DFA as well as multifractal DFA reveal that the latter electric field variations exhibit scaling behavior as shown by analyzing SES activities observed before major earthquakes in Greece. Hence, when these variations are superimposed on a background of pseudosinusoidal trend, their long range correlation properties—quantified by DFA—are affected resulting in an increase of the “non-uniform” scaling behavior. The same is expected to hold for the former magnetic field variations. This explanation is strengthened by recent findings showing that the fluctuations of the order parameter of seismicity exhibited an unprecedented minimum almost two months before the Tohoku earthquake occurrence which is characteristic for an almost simultaneous emission of Seismic Electric Signals activity.« less

Determinants of job stress in chemical process industry: A factor analysis approach.

PubMed

Menon, Balagopal G; Praveensal, C J; Madhu, G

2015-01-01

Job stress is one of the active research domains in industrial safety research. The job stress can result in accidents and health related issues in workers in chemical process industries. Hence it is important to measure the level of job stress in workers so as to mitigate the same to avoid the worker's safety related problems in the industries. The objective of this study is to determine the job stress factors in the chemical process industry in Kerala state, India. This study also aims to propose a comprehensive model and an instrument framework for measuring job stress levels in the chemical process industries in Kerala, India. The data is collected through a questionnaire survey conducted in chemical process industries in Kerala. The collected data out of 1197 surveys is subjected to principal component and confirmatory factor analysis to develop the job stress factor structure. The factor analysis revealed 8 factors that influence the job stress in process industries. It is also found that the job stress in employees is most influenced by role ambiguity and the least by work environment. The study has developed an instrument framework towards measuring job stress utilizing exploratory factor analysis and structural equation modeling.

Exploratory analysis of TOF-SIMS data from biological surfaces

NASA Astrophysics Data System (ADS)

Vaidyanathan, Seetharaman; Fletcher, John S.; Henderson, Alex; Lockyer, Nicholas P.; Vickerman, John C.

2008-12-01

The application of multivariate analytical tools enables simplification of TOF-SIMS datasets so that useful information can be extracted from complex spectra and images, especially those that do not give readily interpretable results. There is however a challenge in understanding the outputs from such analyses. The problem is complicated when analysing images, given the additional dimensions in the dataset. Here we demonstrate how the application of simple pre-processing routines can enable the interpretation of TOF-SIMS spectra and images. For the spectral data, TOF-SIMS spectra used to discriminate bacterial isolates associated with urinary tract infection were studied. Using different criteria for picking peaks before carrying out PC-DFA enabled identification of the discriminatory information with greater certainty. For the image data, an air-dried salt stressed bacterial sample, discussed in another paper by us in this issue, was studied. Exploration of the image datasets with and without normalisation prior to multivariate analysis by PCA or MAF resulted in different regions of the image being highlighted by the techniques.

An Empirical Analysis of Factors Affecting Honors Program Completion Rates

ERIC Educational Resources Information Center

Savage, Hallie; Raehsler, Rod D.; Fiedor, Joseph

2014-01-01

One of the most important issues in any educational environment is identifying factors that promote academic success. A plethora of research on such factors exists across most academic fields, involving a wide range of student demographics, and the definition of student success varies across the range of studies published. The analysis in this…

Factors of Spatial Visualization: An Analysis of the PSVT:R

ERIC Educational Resources Information Center

Ernst, Jeremy V.; Willams, Thomas O.; Clark, Aaron C.; Kelly, Daniel P.

2017-01-01

The Purdue Spatial Visualization Test: Visualization of Rotations (PVST:R) is among the most commonly used measurement instruments to assess spatial ability among engineering students. Previous analysis that explores the factor structure of the PSVT:R indicates a single-factor measure of the instrument. With this as a basis, this research seeks to…

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

The risk factors for avian influenza on poultry farms: a meta-analysis.

PubMed

Wang, Youming; Li, Peng; Wu, Yangli; Sun, Xiangdong; Yu, Kangzhen; Yu, Chuanhua; Qin, Aijian

2014-11-01

Avian influenza is a severe threat both to humans and poultry, but so far, no systematic review on the identification and evaluation of the risk factors of avian influenza infection has been published. The objective of this meta-analysis is to provide evidence for decision-making and further research on AI prevention through identifying the risk factors associated with AI infection on poultry farms. The results from 15 selected studies on risk factors for AI infections on poultry farms were analyzed quantitatively by meta-analysis. Open water source (OR=2.89), infections on nearby farms (OR=4.54), other livestock (OR=1.90) and disinfection of farm (OR=0.54) have significant association with AI infection on poultry farms. The subgroup analysis results indicate that there exist different risk factors for AI infections in different types of farms. The main risk factors for AI infection in poultry farms are environmental conditions (open water source, infections on nearby farms), keeping other livestock on the same farm and no disinfection of the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

PubMed Central

Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-01-01

Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor

[Introduction to Exploratory Factor Analysis (EFA)].

PubMed

Martínez, Carolina Méndez; Sepúlveda, Martín Alonso Rondón

2012-03-01

Exploratory Factor Analysis (EFA) has become one of the most frequently used statistical techniques, especially in the medical and social sciences. Given its popularity, it is essential to understand the basic concepts necessary for its proper application and to take into consideration the main strengths and weaknesses of this technique. To present in a clear and concise manner the main applications of this technique, to determine the basic requirements for its use providing a description step by step of its methodology, and to establish the elements that must be taken into account during its preparation in order to not incur in erroneous results and interpretations. Narrative review. This review identifies the basic concepts and briefly describes the objectives, design, assumptions, and methodology to achieve factor derivation, global adjustment evaluation, and adequate interpretation of results. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method

Investigation on Constrained Matrix Factorization for Hyperspectral Image Analysis

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for

Confirmatory Factor Analysis of the Minnesota Nicotine Withdrawal Scale

PubMed Central

Toll, Benjamin A.; O’Malley, Stephanie S.; McKee, Sherry A.; Salovey, Peter; Krishnan-Sarin, Suchitra

2008-01-01

The authors examined the factor structure of the Minnesota Nicotine Withdrawal Scale (MNWS) using confirmatory factor analysis in clinical research samples of smokers trying to quit (n = 723). Three confirmatory factor analytic models, based on previous research, were tested with each of the 3 study samples at multiple points in time. A unidimensional model including all 8 MNWS items was found to be the best explanation of the data. This model produced fair to good internal consistency estimates. Additionally, these data revealed that craving should be included in the total score of the MNWS. Factor scores derived from this single-factor, 8-item model showed that increases in withdrawal were associated with poor smoking outcome for 2 of the clinical studies. Confirmatory factor analyses of change scores showed that the MNWS symptoms cohere as a syndrome over time. Future investigators should report a total score using all of the items from the MNWS. PMID:17563141

Comparative analysis of time-scaling properties about water pH in Poyang Lake Inlet and Outlet on the basis of fractal methods.

PubMed

Shi, K; Liu, C Q; Huang, Z W; Zhang, B; Su, Y

2010-01-01

Detrended fluctuation analysis (DFA) and multifractal methods are applied to the time-scaling properties analysis of water pH series in Poyang Lake Inlet and Outlet in China. The results show that these pH series are characterised by long-term memory and multifractal scaling, and these characteristics have obvious differences between the Lake Inlet and Outlet. The comparison results suggest that monofractal and multifractal parameters can be quantitative dynamical indexes reflecting the capability of anti-acidification of Poyang Lake. Furthermore, we investigated the frequency-size distribution of pH series in Poyang Lake Inlet and Outlet. Our findings suggest that water pH is an example of a self-organised criticality (SOC) process. The results show that it is different SOC behaviours that result in the differences of power-law relations between pH series in Poyang Lake Inlet and Outlet. This work can be helpful to improvement of modelling of lake water quality.

Morphometric sexing of Northwest Atlantic Roseate Terns

USGS Publications Warehouse

Palestis, Brian G.; Nisbet, Ian C.T.; Hatch, Jeremy J.; Szczys, Patricia; Spendelow, Jeffrey A.

2012-01-01

A difficulty in the study of monomorphic species is the inability of observers to visually distinguish females from males. Based on a sample of 745 known-sex birds nesting at Bird Island, MA, USA, a discriminant function analysis (DFA) was used to sex Roseate Terns (Sterna dougallii) of the Northwest Atlantic population using morphological measurements. DFA using only the total length of the head (including the bill) correctly identified the sex of approximately 86% of the terns, which increased to 88% if both members of a pair were measured. Including additional measurements increased these percentages slightly, to 87% and 90%, respectively. These levels of accuracy are generally higher than those reported for other species of terns. Because female-female pairs are frequent in this population, one cannot assume that the member of a pair with the larger head is a male, and additional discriminant functions were developed to help separate female-female from male-female pairs.

Investigating Long-Range Dependence in American Treasury Bills Variations and Volatilities during Stable and Unstable Periods

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2016-05-01

Detrended fluctuation analysis (DFA) is used to examine long-range dependence in variations and volatilities of American treasury bills (TB) during periods of low and high movements in TB rates. Volatility series are estimated by generalized autoregressive conditional heteroskedasticity (GARCH) model under Gaussian, Student, and the generalized error distribution (GED) assumptions. The DFA-based Hurst exponents from 3-month, 6-month, and 1-year TB data indicates that in general the dynamics of the TB variations process is characterized by persistence during stable time period (before 2008 international financial crisis) and anti-persistence during unstable time period (post-2008 international financial crisis). For volatility series, it is found that; for stable period; 3-month volatility process is more likely random, 6-month volatility process is anti-persistent, and 1-year volatility process is persistent. For unstable period, estimation results show that the generating process is persistent for all maturities and for all distributional assumptions.

Synthesis of Prebiotic Caramels Catalyzed by Ion-Exchange Resin Particles: Kinetic Model for the Formation of Di-d-fructose Dianhydrides.

PubMed

Ortiz Cerda, Imelda-Elizabeth; Thammavong, Phahath; Caqueret, Vincent; Porte, Catherine; Mabille, Isabelle; Garcia Fernandez, José Manuel; Moscosa Santillan, Mario; Havet, Jean-Louis

2018-02-21

Caramel enriched in di-d-fructose dianhydrides (DFAs, a family of prebiotic cyclic fructodisaccharides) is a functional food with beneficial properties for health. The aim of this work was to study the conversion of fructose into DFAs catalyzed by acid ion-exchange resin, in order to establish a simplified mechanism of the caramelization reaction and a kinetic model for DFA formation. Batch reactor experiments were carried out in a 250 mL spherical glass flask and afforded up to 50% DFA yields. The mechanism proposed entails order 2 reactions that describe fructose conversion on DFAs or formation of byproducts such as HMF or melanoidines. A third order 1 reaction defines DFA transformation into fructosyl-DFAs or fructo-oligosaccharides. The influence of fructose concentration, resin loading and temperature was studied to calculate the kinetic parameters necessary to scale up the process.

76 FR 17047 - Authority To Designate Financial Market Utilities as Systemically Important

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-28

...Section 804 of the Dodd-Frank Wall Street Reform and Consumer Protection Act (the ``DFA'') provides the Financial Stability Oversight Council (the ``Council'') the authority to designate a financial market utility (an ``FMU'') the Council determines is or is likely to become systemically important--that is, the failure of or a disruption to the functioning of which could create, or increase, the risk of significant liquidity or credit problems spreading among financial institutions or markets and thereby threaten the stability of the United States financial system. This notice of proposed rulemaking (NPR) describes the criteria that will inform, and the processes and procedures established under the DFA for, the Council's designation of FMUs as systemically important under the DFA. The Council, on December 21, 2010, published an advance notice of proposed rulemaking regarding the designation criteria in section 804.

Meta-analysis of the Brief Psychiatric Rating Scale Factor Structure

ERIC Educational Resources Information Center

Shafer, Alan

2005-01-01

A meta-analysis (N=17,620; k=26) of factor analyses of the Brief Psychiatric Rating Scale (BPRS) was conducted. Analysis of the 12 items from Overall et al.'s (J. E. Overall, L. E. Hollister, & P. Pichot, 1974) 4 subscales found support for his 4 subscales. Analysis of all 18 BPRS items found 4 components similar to those of Overall et al. In a…

A Human Factors Analysis of EVA Time Requirements

NASA Technical Reports Server (NTRS)

Pate, Dennis W.

1997-01-01

Human Factors Engineering (HFE) is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. During the summer of 1995, a human factors motion and time study was initiated with the goals of developing a database of EVA task times and developing a method of utilizing the database to predict how long an EVA should take. Initial development relied on the EVA activities performed during the STS-61 (Hubble) mission. The first step of the study was to become familiar with EVA's, the previous task-time studies, and documents produced on EVA's. After reviewing these documents, an initial set of task primitives and task-time modifiers was developed. Data was collected from videotaped footage of two entire STS-61 EVA missions and portions of several others, each with two EVA astronauts. Feedback from the analysis of the data was used to further refine the primitives and modifiers used. The project was continued during the summer of 1996, during which data on human errors was also collected and analyzed. Additional data from the STS-71 mission was also collected. Analysis of variance techniques for categorical data was used to determine which factors may affect the primitive times and how much of an effect they have. Probability distributions for the various task were also generated. Further analysis of the modifiers and interactions is planned.

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Quantitative Analysis of Guanine Nucleotide Exchange Factors (GEFs) as Enzymes

PubMed Central

Randazzo, Paul A; Jian, Xiaoying; Chen, Pei-Wen; Zhai, Peng; Soubias, Olivier; Northup, John K

2014-01-01

The proteins that possess guanine nucleotide exchange factor (GEF) activity, which include about ~800 G protein coupled receptors (GPCRs),1 15 Arf GEFs,2 81 Rho GEFs,3 8 Ras GEFs,4 and others for other families of GTPases,5 catalyze the exchange of GTP for GDP on all regulatory guanine nucleotide binding proteins. Despite their importance as catalysts, relatively few exchange factors (we are aware of only eight for ras superfamily members) have been rigorously characterized kinetically.5–13 In some cases, kinetic analysis has been simplistic leading to erroneous conclusions about mechanism (as discussed in a recent review14). In this paper, we compare two approaches for determining the kinetic properties of exchange factors: (i) examining individual equilibria, and; (ii) analyzing the exchange factors as enzymes. Each approach, when thoughtfully used,14,15 provides important mechanistic information about the exchange factors. The analysis as enzymes is described in further detail. With the focus on the production of the biologically relevant guanine nucleotide binding protein complexed with GTP (G•GTP), we believe it is conceptually simpler to connect the kinetic properties to cellular effects. Further, the experiments are often more tractable than those used to analyze the equilibrium system and, therefore, more widely accessible to scientists interested in the function of exchange factors. PMID:25332840

Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price

NASA Astrophysics Data System (ADS)

Zhuang, Xiaoyang; Wei, Yu; Ma, Feng

2015-07-01

In this paper, the multifractality and efficiency degrees of ten important Chinese sectoral indices are evaluated using the methods of MF-DFA and generalized Hurst exponents. The study also scrutinizes the dynamics of the efficiency of Chinese sectoral stock market by the rolling window approach. The overall empirical findings revealed that all the sectoral indices of Chinese stock market exist different degrees of multifractality. The results of different efficiency measures have agreed on that the 300 Materials index is the least efficient index. However, they have a slight diffidence on the most efficient one. The 300 Information Technology, 300 Telecommunication Services and 300 Health Care indices are comparatively efficient. We also investigate the cross-correlations between the ten sectoral indices and WTI crude oil price based on Multifractal Detrended Cross-correlation Analysis. At last, some relevant discussions and implications of the empirical results are presented.

Enforcing Memory Policy Specifications in Reconfigurable Hardware

DTIC Science & Technology

2008-10-01

we explain the algorithms behind our reference monitor design flow. In Section 4, we describe our access policy language including several example...NFA from this regular expression using Thompson’s Algorithm [1] as implemented by Gerzic [19]. Figure 4 shows the NFA for our policy. Notice that the... Algorithm [1] as implemented by Grail [49] to minimize the DFA. Figure 5 shows the minimized DFA for our policy. Processing the Ranges Before we can

Students' motivation to study dentistry in Malaysia: an analysis using confirmatory factor analysis.

PubMed

Musa, Muhd Firdaus Che; Bernabé, Eduardo; Gallagher, Jennifer E

2015-06-12

Malaysia has experienced a significant expansion of dental schools over the past decade. Research into students' motivation may inform recruitment and retention of the future dental workforce. The objectives of this study were to explore students' motivation to study dentistry and whether that motivation varied by students' and school characteristics. All 530 final-year students in 11 dental schools (6 public and 5 private) in Malaysia were invited to participate at the end of 2013. The self-administered questionnaire, developed at King's College London, collected information on students' motivation to study dentistry and demographic background. Responses on students' motivation were collected using five-point ordinal scales. Confirmatory factor analysis (CFA) was used to evaluate the underlying structure of students' motivation to study dentistry. Multivariate analysis of variance (MANOVA) was used to compare factor scores for overall motivation and sub-domains by students' and school characteristics. Three hundred and fifty-six final-year students in eight schools (all public and two private) participated in the survey, representing an 83% response rate for these schools and 67% of all final-year students nationally. The majority of participants were 24 years old (47%), female (70%), Malay (56%) and from middle-income families (41%) and public schools (78%). CFA supported a model with five first-order factors (professional job, healthcare and people, academic, careers advising and family and friends) which were linked to a single second-order factor representing overall students' motivation. Academic factors and healthcare and people had the highest standardized factor loadings (0.90 and 0.71, respectively), suggesting they were the main motivation to study dentistry. MANOVA showed that students from private schools had higher scores for healthcare and people than those in public schools whereas Malay students had lower scores for family and friends than those

An Analysis of Selected Factors Influencing Enrollment Patterns.

ERIC Educational Resources Information Center

Heck, James

This report presents an analysis of factors influencing enrollment patterns at Lake City Community College (LCCC; Florida) and recommends ways to increase enrollments at the college. Section I reviews the methods of collecting data for the report, which included interviews with key college personnel, an examination of social indicators such as…

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

2011-01-01

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

Recovery of Weak Factor Loadings When Adding the Mean Structure in Confirmatory Factor Analysis: A Simulation Study

PubMed Central

Ximénez, Carmen

2016-01-01

This article extends previous research on the recovery of weak factor loadings in confirmatory factor analysis (CFA) by exploring the effects of adding the mean structure. This issue has not been examined in previous research. This study is based on the framework of Yung and Bentler (1999) and aims to examine the conditions that affect the recovery of weak factor loadings when the model includes the mean structure, compared to analyzing the covariance structure alone. A simulation study was conducted in which several constraints were defined for one-, two-, and three-factor models. Results show that adding the mean structure improves the recovery of weak factor loadings and reduces the asymptotic variances for the factor loadings, particularly for the models with a smaller number of factors and a small sample size. Therefore, under certain circumstances, modeling the means should be seriously considered for covariance models containing weak factor loadings. PMID:26779071

Affective Outcomes of Schooling: Full-Information Item Factor Analysis of a Student Questionnaire.

ERIC Educational Resources Information Center

Muraki, Eiji; Engelhard, George, Jr.

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise joint…

The use of the multi-cumulant tensor analysis for the algorithmic optimisation of investment portfolios

NASA Astrophysics Data System (ADS)

Domino, Krzysztof

2017-02-01

The cumulant analysis plays an important role in non Gaussian distributed data analysis. The shares' prices returns are good example of such data. The purpose of this research is to develop the cumulant based algorithm and use it to determine eigenvectors that represent investment portfolios with low variability. Such algorithm is based on the Alternating Least Square method and involves the simultaneous minimisation 2'nd- 6'th cumulants of the multidimensional random variable (percentage shares' returns of many companies). Then the algorithm was tested during the recent crash on the Warsaw Stock Exchange. To determine incoming crash and provide enter and exit signal for the investment strategy the Hurst exponent was calculated using the local DFA. It was shown that introduced algorithm is on average better that benchmark and other portfolio determination methods, but only within examination window determined by low values of the Hurst exponent. Remark that the algorithm is based on cumulant tensors up to the 6'th order calculated for a multidimensional random variable, what is the novel idea. It can be expected that the algorithm would be useful in the financial data analysis on the world wide scale as well as in the analysis of other types of non Gaussian distributed data.

Evaluation of cardiac modulation in children in response to apnea/hypopnea using the Phone Oximeter(™).

PubMed

Dehkordi, Parastoo; Garde, Ainara; Karlen, Walter; Petersen, Christian L; Wensley, David; Dumont, Guy A; Mark Ansermino, J

2016-02-01

Individuals with sleep disordered breathing (SDB) can experience changes in automatic cardiac regulation as a result of frequent sleep fragmentation and disturbance in normal respiration and oxygenation that accompany most apnea/hypopnea events. In adults, these changes are reflected in enhanced sympathetic and reduced parasympathetic activity. In this study, we examined the autonomic cardiac regulation in children with and without SDB, through spectral and detrended fluctuation analysis (DFA) of pulse rate variability (PRV). PRV was measured from pulse-to-pulse intervals (PPIs) of the photoplethysmogram (PPG) recorded from 160 children using the Phone Oximeter(™) in the standard setting of overnight polysomnography. Spectral analysis of PRV showed the cardiac parasympathetic index (high frequency, HF) was lower (p < 0.01) and cardiac sympathetic indices (low frequency, LF and LF/HF ratio) were higher (p < 0.01) during apnea/hypopnea events for more than 95% of children with SDB. DFA showed the short- and long-range fluctuations of heart rate were more strongly correlated in children with SDB compared to children without SDB. These findings confirm that the analysis of the PPG recorded using the Phone Oximeter(™) could be the basis for a new screening tool for assessing PRV in non-clinical environment.

A Study of Algorithms for Covariance Structure Analysis with Specific Comparisons Using Factor Analysis.

ERIC Educational Resources Information Center

Lee, S. Y.; Jennrich, R. I.

1979-01-01

A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)

An Analysis of Factors that Influence Enlistment Decisions in the U.S. Army

DTIC Science & Technology

1998-03-01

NAVAL POSTGRADUATE SCHOOL Monterey, California CM THESIS AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY by Young...TITLE AND SUBTITLE : AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY 6. AUTHOR(S) Oh, Young Yeol 7...200 words) The purpose of this thesis is to analyze factors that influence decisions to enlist in the U.S. Army. This thesis uses 1997 New Recruit

Risky Business: Factor Analysis of Survey Data – Assessing the Probability of Incorrect Dimensionalisation

PubMed Central

van der Eijk, Cees; Rose, Jonathan

2015-01-01

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered-categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations. We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of over-dimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems. PMID:25789992

Teacher's Corner: Examining Identification Issues in Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Marcoulides, George A.

2006-01-01

One hundred years have passed since the birth of factor analysis, during which time there have been some major developments and extensions to the methodology. Unfortunately, one issue where the widespread accumulation of knowledge has been rather slow concerns identification. This article provides a didactic discussion of the topic in an attempt…

Modular Open-Source Software for Item Factor Analysis

ERIC Educational Resources Information Center

Pritikin, Joshua N.; Hunter, Micheal D.; Boker, Steven M.

2015-01-01

This article introduces an item factor analysis (IFA) module for "OpenMx," a free, open-source, and modular statistical modeling package that runs within the R programming environment on GNU/Linux, Mac OS X, and Microsoft Windows. The IFA module offers a novel model specification language that is well suited to programmatic generation…

Perception on obesity among university students: A case study using factor analysis

NASA Astrophysics Data System (ADS)

Hassan, Suriani; Rahman, Nur Amira Abdol; Ghazali, Khadizah; Ismail, Norlita; Budin, Kamsia

2014-07-01

The purpose of this study was to examine the university students' perceptions on obesity and to compare the difference in mean scores factor based on demographic factors. Data was collected randomly using questionnaires. There were 321 university students participated in this study. Descriptive statistics, factor analysis, normality test, independent t test, one-way ANOVA and non-parametric tests were used in this study. Factor analysis results managed to retrieve three new factors namely impact of the health, impact of the physical appearance and personal factors. The study found that Science students have higher awareness and perceptions than Art students on Factor 1, impact of the health towards overweight problems and obesity. The findings of the study showed students, whose family background has obesity problem have higher awareness and perceptions than students' whose family background has no obesity problem on Factor 1, impact of the health towards overweight problems and obesity. The study also found that students' whose father with primary school level had the lowest awareness and perceptions on Factor 2, impact of the physical appearance towards overweight problems and obesity than other students whose father with higher academic level.

Study of risk factors for gastric cancer by populational databases analysis

PubMed Central

Ferrari, Fangio; Reis, Marco Antonio Moura

2013-01-01

AIM: To study the association between the incidence of gastric cancer and populational exposure to risk/protective factors through an analysis of international databases. METHODS: Open-access global databases concerning the incidence of gastric cancer and its risk/protective factors were identified through an extensive search on the Web. As its distribution was neither normal nor symmetric, the cancer incidence of each country was categorized according to ranges of percentile distribution. The association of each risk/protective factor with exposure was measured between the extreme ranges of the incidence of gastric cancer (under the 25th percentile and above the 75th percentile) by the use of the Mann-Whitney test, considering a significance level of 0.05. RESULTS: A variable amount of data omission was observed among all of the factors under study. A weak or nonexistent correlation between the incidence of gastric cancer and the study variables was shown by a visual analysis of scatterplot dispersion. In contrast, an analysis of categorized incidence revealed that the countries with the highest human development index (HDI) values had the highest rates of obesity in males and the highest consumption of alcohol, tobacco, fruits, vegetables and meat, which were associated with higher incidences of gastric cancer. There was no significant difference for the risk factors of obesity in females and fish consumption. CONCLUSION: Higher HDI values, coupled with a higher prevalence of male obesity and a higher per capita consumption of alcohol, tobacco, fruits, vegetables and meat, are associated with a higher incidence of gastric cancer based on an analysis of populational global data. PMID:24409066

An Evaluation of the Effects of Variable Sampling on Component, Image, and Factor Analysis.

ERIC Educational Resources Information Center

Velicer, Wayne F.; Fava, Joseph L.

1987-01-01

Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…

Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics

NASA Technical Reports Server (NTRS)

Ho, K. K.; Moody, G. B.; Peng, C. K.; Mietus, J. E.; Larson, M. G.; Levy, D.; Goldberger, A. L.

1997-01-01

BACKGROUND: Despite much recent interest in quantification of heart rate variability (HRV), the prognostic value of conventional measures of HRV and of newer indices based on nonlinear dynamics is not universally accepted. METHODS AND RESULTS: We have designed algorithms for analyzing ambulatory ECG recordings and measuring HRV without human intervention, using robust methods for obtaining time-domain measures (mean and SD of heart rate), frequency-domain measures (power in the bands of 0.001 to 0.01 Hz [VLF], 0.01 to 0.15 Hz [LF], and 0.15 to 0.5 Hz [HF] and total spectral power [TP] over all three of these bands), and measures based on nonlinear dynamics (approximate entropy [ApEn], a measure of complexity, and detrended fluctuation analysis [DFA], a measure of long-term correlations). The study population consisted of chronic congestive heart failure (CHF) case patients and sex- and age-matched control subjects in the Framingham Heart Study. After exclusion of technically inadequate studies and those with atrial fibrillation, we used these algorithms to study HRV in 2-hour ambulatory ECG recordings of 69 participants (mean age, 71.7+/-8.1 years). By use of separate Cox proportional-hazards models, the conventional measures SD (P<.01), LF (P<.01), VLF (P<.05), and TP (P<.01) and the nonlinear measure DFA (P<.05) were predictors of survival over a mean follow-up period of 1.9 years; other measures, including ApEn (P>.3), were not. In multivariable models, DFA was of borderline predictive significance (P=.06) after adjustment for the diagnosis of CHF and SD. CONCLUSIONS: These results demonstrate that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognostic value to complement traditional HRV measures.

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale).

PubMed

Akeroyd, Michael A; Guy, Fiona H; Harrison, Dawn L; Suller, Sharon L

2014-02-01

The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. 1220 people who have attended MRC IHR over the last decade. We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed "speech understanding", "spatial perception", and "clarity, separation, and identification". Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, "effort and concentration", representing two more questions. These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores.

Perceptual security of encrypted images based on wavelet scaling analysis

NASA Astrophysics Data System (ADS)

Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

2016-08-01

The scaling behavior of the pixel fluctuations of encrypted images is evaluated by using the detrended fluctuation analysis based on wavelets, a modern technique that has been successfully used recently for a wide range of natural phenomena and technological processes. As encryption algorithms, we use the Advanced Encryption System (AES) in RBT mode and two versions of a cryptosystem based on cellular automata, with the encryption process applied both fully and partially by selecting different bitplanes. In all cases, the results show that the encrypted images in which no understandable information can be visually appreciated and whose pixels look totally random present a persistent scaling behavior with the scaling exponent α close to 0.5, implying no correlation between pixels when the DFA with wavelets is applied. This suggests that the scaling exponents of the encrypted images can be used as a perceptual security criterion in the sense that when their values are close to 0.5 (the white noise value) the encrypted images are more secure also from the perceptual point of view.

Psychological Factors and Conditioned Pain Modulation: A Meta-Analysis.

PubMed

Nahman-Averbuch, Hadas; Nir, Rony-Reuven; Sprecher, Elliot; Yarnitsky, David

2016-06-01

Conditioned pain modulation (CPM) responses may be affected by psychological factors such as anxiety, depression, and pain catastrophizing; however, most studies on CPM do not address these relations as their primary outcome. The aim of this meta-analysis was to analyze the findings regarding the associations between CPM responses and psychological factors in both pain-free individuals and pain patients. After a comprehensive PubMed search, 37 articles were found to be suitable for inclusion. Analyses used DerSimonian and Laird's random-effects model on Fisher's z-transforms of correlations; potential publication bias was tested using funnel plots and Egger's regression test for funnel plot asymmetry. Six meta-analyses were performed examining the correlations between anxiety, depression, and pain catastrophizing, and CPM responses in healthy individuals and pain patients. No significant correlations between CPM responses and any of the examined psychological factors were found. However, a secondary analysis, comparing modality-specific CPM responses and psychological factors in healthy individuals, revealed the following: (1) pressure-based CPM responses were correlated with anxiety (grand mean correlation in original units r=-0.1087; 95% confidence limits, -0.1752 to -0.0411); (2) heat-based CPM was correlated with depression (r=0.2443; 95% confidence limits, 0.0150 to 0.4492); and (3) electrical-based CPM was correlated with pain catastrophizing levels (r=-0.1501; 95% confidence limits, -0.2403 to -0.0574). Certain psychological factors seem to be associated with modality-specific CPM responses in healthy individuals. This potentially supports the notion that CPM paradigms evoked by different stimulation modalities represent different underlying mechanisms.

Exploring factors that influence work analysis data: A meta-analysis of design choices, purposes, and organizational context.

PubMed

DuVernet, Amy M; Dierdorff, Erich C; Wilson, Mark A

2015-09-01

Work analysis is fundamental to designing effective human resource systems. The current investigation extends previous research by identifying the differential effects of common design decisions, purposes, and organizational contexts on the data generated by work analyses. The effects of 19 distinct factors that span choices of descriptor, collection method, rating scale, and data source, as well as project purpose and organizational features, are explored. Meta-analytic results cumulated from 205 articles indicate that many of these variables hold significant consequences for work analysis data. Factors pertaining to descriptor choice, collection method, rating scale, and the purpose for conducting the work analysis each showed strong associations with work analysis data. The source of the work analysis information and organizational context in which it was conducted displayed fewer relationships. Findings can be used to inform choices work analysts make about methodology and postcollection evaluations of work analysis information. (c) 2015 APA, all rights reserved).

A Confirmatory Factor Analysis of the Structure of Abbreviated Math Anxiety Scale

PubMed Central

Farrokhi, Farahman

2011-01-01

Objective The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Abbreviated Math Anxiety Scale (AMAS), proposed by Hopko, Mahadevan, Bare & Hunt. Method The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. The confirmatory factor analysis (CFA) was carried out to determine the factor structures of the Persian version of AMAS. Results As expected, the two-factor solution provided a better fit to the data than a single factor. Moreover, multi-group analyses showed that this two-factor structure was invariant across sex. Hence, AMAS provides an equally valid measure for use among college students. Conclusions Brief AMAS demonstrates adequate reliability and validity. The AMAS scores can be used to compare symptoms of math anxiety between male and female students. The study both expands and adds support to the existing body of math anxiety literature. PMID:22952521

Analysis of risk factors in the development of retinopathy of prematurity.

PubMed

Knezević, Sanja; Stojanović, Nadezda; Oros, Ana; Savić, Dragana; Simović, Aleksandra; Knezević, Jasmina

2011-01-01

Retinopathy of prematurity (ROP) is a multifactorial disease that occurs most frequently in very small and very sick preterm infants, and it has been identified as the major cause of childhood blindness. The aim of this study was to evaluate ROP incidence and risk factors associated with varying degrees of illness. The study was conducted at the Centre for Neonatology, Paediatric Clinic of the Clinical Centre Kragujevac, Serbia, in the period from June 2006 to December 2008. Ophthalmologic screening was performed in all children with body weight lower than 2000 g or gestational age lower than 36 weeks. We analyzed eighteen postnatal and six perinatal risk factors and the group correlations for each of the risk factors. Out of 317 children that were screened, 56 (17.7%) developed a mild form of ROP, while 68 (21.5%) developed a severe form. Univariate analysis revealed a large number of statistically significant risk factors for the development of ROP, especially the severe form. Multivariate logistical analysis further separated two independent risk factors: small birth weight (p = 0.001) and damage of central nervous system (p = 0.01). Independent risk factors for transition from mild to severe forms of ROP were identified as: small birth weight (p = 0.05) and perinatal risk factors (p = 0.02). Small birth weight and central nervous system damage were risk factors for the development of ROP, perinatal risk factors were identified as significant for transition from mild to severe form of ROP.

A Comparison of Distribution Free and Non-Distribution Free Factor Analysis Methods

ERIC Educational Resources Information Center

Ritter, Nicola L.

2012-01-01

Many researchers recognize that factor analysis can be conducted on both correlation matrices and variance-covariance matrices. Although most researchers extract factors from non-distribution free or parametric methods, researchers can also extract factors from distribution free or non-parametric methods. The nature of the data dictates the method…

Factor Analysis of the Modified Sexual Adjustment Questionnaire-Male

PubMed Central

Wilmoth, Margaret C.; Hanlon, Alexandra L.; Ng, Lit Soo; Bruner, Debra W.

2015-01-01

Background and Purpose The Sexual Adjustment Questionnaire (SAQ) is used in National Cancer Institute–sponsored clinical trials as an outcome measure for sexual functioning. The tool was revised to meet the needs for a clinically useful, theory-based outcome measure for use in both research and clinical settings. This report describes the modifications and validity testing of the modified Sexual Adjustment Questionnaire-Male (mSAQ-Male). Methods This secondary analysis of data from a large Radiation Therapy Oncology Group trial employed principal axis factor analytic techniques in estimating validity of the revised tool. The sample size was 686; most subjects were White, older than the age 60 years, and with a high school education and a Karnofsky performance scale (KPS) score of greater than 90. Results A 16-item, 3-factor solution resulted from the factor analysis. The mSAQ-Male was also found to be sensitive to changes in physical sexual functioning as measured by the KPS. Conclusion The mSAQ-Male is a valid self-report measure of sexuality that can be used clinically to detect changes in male sexual functioning. PMID:25255676

Landslides geotechnical analysis. Qualitative assessment by valuation factors

NASA Astrophysics Data System (ADS)

Cuanalo Oscar, Sc D.; Oliva Aldo, Sc D.; Polanco Gabriel, M. E.

2012-04-01

In general, a landslide can cause a disaster when it is combined a number of factors such as an extreme event related to a geological phenomenon, vulnerable elements exposed in a specific geographic area, and the probability of loss and damage evaluated in terms of lives and economic assets, in a certain period of time. This paper presents the qualitative evaluation of slope stability through of Valuation Factors, obtained from the characterization of the determinants and triggers factors that influence the instability; for the first the morphology and topography, geology, soil mechanics, hydrogeology and vegetation to the second, the rain, earthquakes, erosion and scour, human activity, and ultimately dependent factors of the stability analysis, and its influence ranges which greatly facilitate the selection of construction processes best suited to improve the behavior of a slope or hillside. The Valuation Factors are a set of parameters for assessing the influence of conditioning and triggering factors that influence the stability of slopes and hillsides. The characteristics of each factor must be properly categorized to involve its effect on behavior; a way to do this is by assigning a weighted value range indicating its effect on the stability of a slope. It is proposed to use Valuation Factors with weighted values between 0 and 1 (arbitrarily selected but common sense and logic), the first corresponds to no or minimal effect on stability (no effect or very little influence) and the second, the greatest impact on it (has a significant influence). The meddle effects are evaluated with intermediate values.

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Reporting Practices in Confirmatory Factor Analysis: An Overview and Some Recommendations

ERIC Educational Resources Information Center

Jackson, Dennis L.; Gillaspy, J. Arthur, Jr.; Purc-Stephenson, Rebecca

2009-01-01

Reporting practices in 194 confirmatory factor analysis studies (1,409 factor models) published in American Psychological Association journals from 1998 to 2006 were reviewed and compared with established reporting guidelines. Three research questions were addressed: (a) how do actual reporting practices compare with published guidelines? (b) how…

Factor analysis and Mokken scaling of the Organizational Commitment Questionnaire in nurses.

PubMed

Al-Yami, M; Galdas, P; Watson, R

2018-03-22

To generate an Arabic version of the Organizational Commitment Questionnaire that would be easily understood by Arabic speakers and would be sensitive to Arabic culture. The nursing workforce in Saudi Arabia is undergoing a process of Saudization but there is a need to understand the factors that will help to retain this workforce. No organizational commitment tools exist in Arabic that are specifically designed for health organizations. An Arabic version of the organizational commitment tool could aid Arabic speaking employers to understand their employees' perceptions of their organizations. Translation and back-translation followed by factor analysis (principal components analysis and confirmatory factor analysis) to test the factorial validity and item response theory (Mokken scaling). A two-factor structure was obtained for the Organizational Commitment Questionnaire comprising Factor 1: Value commitment; and Factor 2: Commitment to stay with acceptable reliability measured by internal consistency. A Mokken scale was obtained including items from both factors showing a hierarchy of items running from commitment to the organization and commitment to self. This study shows that the Arabic version of the OCQ retained the established two-factor structure of the original English-language version. Although the two factors - 'value commitment' and 'commitment to stay' - repudiate the original developers' single factor claim. A useful insight into the structure of the Organizational Commitment Questionnaire has been obtained with the novel addition of a hierarchical scale. The Organizational Commitment Questionnaire is now ready to be used with nurses in the Arab speaking world and could be used a tool to measure the contemporary commitment of nursing employees and in future interventions aimed at increasing commitment and retention of valuable nursing staff. © 2018 International Council of Nurses.

Indonesian railway accidents--utilizing Human Factors Analysis and Classification System in determining potential contributing factors.

PubMed

Iridiastadi, Hardianto; Ikatrinasari, Zulfa Fitri

2012-01-01

The prevalence of Indonesian railway accidents has not been declining, with hundreds of fatalities reported in the past decade. As an effort to help the National Transportation Safety Committee (NTSC), this study was conducted that aimed at understanding factors that might have contributed to the accidents. Human Factors Analysis and Classification System (HFACS) was utilized for this purpose. A total of nine accident reports (provided by the Indonesian NTSC) involving fatalities were studied using the technique. Results of this study indicated 72 factors that were closely related to the accidents. Of these, roughly 22% were considered as operator acts while about 39% were related to preconditions for operator acts. Supervisory represented 14% of the factors, and the remaining (about 25%) were associated with organizational factors. It was concluded that, while train drivers indeed played an important role in the accidents, interventions solely directed toward train drivers may not be adequate. A more comprehensive approach in minimizing the accidents should be conducted that addresses all the four aspects of HFACS.

Time indices of multiphasic development in genotypes of sweet cherry are similar from dormancy to cessation of pit growth

PubMed Central

Gibeaut, David M.; Whiting, Matthew D.; Einhorn, Todd

2017-01-01

Background and Aims The archetypical double sigmoid-shaped growth curve of the sweet cherry drupe (Prunus avium) does not address critical development from eco-dormancy to anthesis and has not been correlated to reproductive bud development. Accurate representation of the growth and development of post-anthesis ovaries is confounded by anthesis timing, fruiting-density and the presence of unfertilized and defective ovaries whose growth differs from those that persist to maturation. These factors were addressed to assess pre-anthesis and full-season growth and development of three sweet cherry cultivars, ‘Chelan’, ‘Bing’ and ‘Sweetheart’, differing primarily in seasonal duration and fruit size. Methods Volume was calculated from photographic measurements of reproductive buds, ovaries and pits at all phases of development. A population of unfertilized ovaries was produced using bee-exclusion netting to enable a statistical comparison with an open pollinated population to detect differences in size and shape between successful and failing fruit growth. Anthesis timing and fruiting-density were manipulated by floral extinction at the spur and whole-tree scales. Developmental time indices were analysed using polynomial curve fitting of log-transformed data supported by Richards and logistic functions of asymptotic growth of the pit and maturing fruit, respectively. Key Results Pre-anthesis growth began at the completion of eco-dormancy. A slight decline in relative growth rate (RGR) was observed during bud scale separation approx. −16 d from anthesis (DFA) before resumption of exponential growth to a maximum about 14 DFA. After anthesis, reduced growth of unfertilized or defective ovaries was partly discriminated from successful fruit at 5 DFA and completely at 25 DFA. Time indices of RGR inflections were similar among cultivars when adjusted for anthesis date alone, until the end of pit growth. Asymptotic growth of the pit underpinned the declining growth

Comparison of Biotinylated Monoclonal and Polyclonal Antibodies in an Evaluation of a Direct Rapid Immunohistochemical Test for the Routine Diagnosis of Rabies in Southern Africa

PubMed Central

Coetzer, Andre; Sabeta, Claude T.; Markotter, Wanda; Rupprecht, Charles E.; Nel, Louis H.

2014-01-01

The major etiological agent of rabies, rabies virus (RABV), accounts for tens of thousands of human deaths per annum. The majority of these deaths are associated with rabies cycles in dogs in resource-limited countries of Africa and Asia. Although routine rabies diagnosis plays an integral role in disease surveillance and management, the application of the currently recommended direct fluorescent antibody (DFA) test in countries on the African and Asian continents remains quite limited. A novel diagnostic assay, the direct rapid immunohistochemical test (dRIT), has been reported to have a diagnostic sensitivity and specificity equal to that of the DFA test while offering advantages in cost, time and interpretation. Prior studies used the dRIT utilized monoclonal antibody (MAb) cocktails. The objective of this study was to test the hypothesis that a biotinylated polyclonal antibody (PAb) preparation, applied in the dRIT protocol, would yield equal or improved results compared to the use of dRIT with MAbs. We also wanted to compare the PAb dRIT with the DFA test, utilizing the same PAb preparation with a fluorescent label. The PAb dRIT had a diagnostic sensitivity and specificity of 100%, which was shown to be marginally higher than the diagnostic efficacy observed for the PAb DFA test. The classical dRIT, relying on two-biotinylated MAbs, was applied to the same panel of samples and a reduced diagnostic sensitivity (83.50% and 90.78% respectively) was observed. Antigenic typing of the false negative samples indicated all of these to be mongoose RABV variants. Our results provided evidence that a dRIT with alternative antibody preparations, conjugated to a biotin moiety, has a diagnostic efficacy equal to that of a DFA relying on the same antibody and that the antibody preparation should be optimized for virus variants specific to the geographical area of focus. PMID:25254652

Comparison of biotinylated monoclonal and polyclonal antibodies in an evaluation of a direct rapid immunohistochemical test for the routine diagnosis of rabies in southern Africa.

PubMed

Coetzer, Andre; Sabeta, Claude T; Markotter, Wanda; Rupprecht, Charles E; Nel, Louis H

2014-09-01

The major etiological agent of rabies, rabies virus (RABV), accounts for tens of thousands of human deaths per annum. The majority of these deaths are associated with rabies cycles in dogs in resource-limited countries of Africa and Asia. Although routine rabies diagnosis plays an integral role in disease surveillance and management, the application of the currently recommended direct fluorescent antibody (DFA) test in countries on the African and Asian continents remains quite limited. A novel diagnostic assay, the direct rapid immunohistochemical test (dRIT), has been reported to have a diagnostic sensitivity and specificity equal to that of the DFA test while offering advantages in cost, time and interpretation. Prior studies used the dRIT utilized monoclonal antibody (MAb) cocktails. The objective of this study was to test the hypothesis that a biotinylated polyclonal antibody (PAb) preparation, applied in the dRIT protocol, would yield equal or improved results compared to the use of dRIT with MAbs. We also wanted to compare the PAb dRIT with the DFA test, utilizing the same PAb preparation with a fluorescent label. The PAb dRIT had a diagnostic sensitivity and specificity of 100%, which was shown to be marginally higher than the diagnostic efficacy observed for the PAb DFA test. The classical dRIT, relying on two-biotinylated MAbs, was applied to the same panel of samples and a reduced diagnostic sensitivity (83.50% and 90.78% respectively) was observed. Antigenic typing of the false negative samples indicated all of these to be mongoose RABV variants. Our results provided evidence that a dRIT with alternative antibody preparations, conjugated to a biotin moiety, has a diagnostic efficacy equal to that of a DFA relying on the same antibody and that the antibody preparation should be optimized for virus variants specific to the geographical area of focus.

Replication Analysis in Exploratory Factor Analysis: What It Is and Why It Makes Your Analysis Better

ERIC Educational Resources Information Center

Osborne, Jason W.; Fitzpatrick, David C.

2012-01-01

Exploratory Factor Analysis (EFA) is a powerful and commonly-used tool for investigating the underlying variable structure of a psychometric instrument. However, there is much controversy in the social sciences with regard to the techniques used in EFA (Ford, MacCallum, & Tait, 1986; Henson & Roberts, 2006) and the reliability of the outcome.…

One month of contemporary dance modulates fractal posture in aging

PubMed Central

Coubard, Olivier A.; Ferrufino, Lena; Nonaka, Tetsushi; Zelada, Oscar; Bril, Blandine; Dietrich, Gilles

2013-01-01

Understanding the human aging of postural control and how physical or motor activity improves balance and gait is challenging for both clinicians and researchers. Previous studies have evidenced that physical and sporting activity focusing on cardiovascular and strength conditioning help older adults develop their balance and gait and/or decrease their frequency of falls. Motor activity based on motor-skill learning has also been put forward as an alternative to develop balance and/or prevent falls in aging. Specifically dance has been advocated as a promising program to boost motor control. In this study, we examined the effects of contemporary dance (CD) on postural control of older adults. Upright stance posturography was performed in 38 participants aged 54–89 years before and after the intervention period, during which one half of the randomly assigned participants was trained to CD and the other half was not trained at all (no dance, ND). CD training lasted 4 weeks, 3 times a week. We performed classical statistic scores of postural signal and dynamic analyses, namely signal diffusion analysis (SDA), recurrence quantification analysis (RQA), and detrended fluctuation analysis (DFA). CD modulated postural control in older trainees, as revealed in the eyes closed condition by a decrease in fractal dimension and an increase in DFA alpha component in the mediolateral plane. The ND group showed an increase in length and mean velocity of postural signal, and the eyes open a decrease in RQA maximal diagonal line in the anteroposterior plane and an increase in DFA alpha component in the mediolateral plane. No change was found in SDA in either group. We suggest that such a massed practice of CD reduced the quantity of exchange between the subject and the environment by increasing their postural confidence. Since CD has low-physical but high-motor impact, we conclude that it may be recommended as a useful program to rehabilitate posture in aging. PMID:24611047

Multidisciplinary insight into clonal expansion of HTLV-1-infected cells in adult T-cell leukemia via modeling by deterministic finite automata coupled with high-throughput sequencing.

PubMed

Farmanbar, Amir; Firouzi, Sanaz; Park, Sung-Joon; Nakai, Kenta; Uchimaru, Kaoru; Watanabe, Toshiki

2017-01-31

Clonal expansion of leukemic cells leads to onset of adult T-cell leukemia (ATL), an aggressive lymphoid malignancy with a very poor prognosis. Infection with human T-cell leukemia virus type-1 (HTLV-1) is the direct cause of ATL onset, and integration of HTLV-1 into the human genome is essential for clonal expansion of leukemic cells. Therefore, monitoring clonal expansion of HTLV-1-infected cells via isolation of integration sites assists in analyzing infected individuals from early infection to the final stage of ATL development. However, because of the complex nature of clonal expansion, the underlying mechanisms have yet to be clarified. Combining computational/mathematical modeling with experimental and clinical data of integration site-based clonality analysis derived from next generation sequencing technologies provides an appropriate strategy to achieve a better understanding of ATL development. As a comprehensively interdisciplinary project, this study combined three main aspects: wet laboratory experiments, in silico analysis and empirical modeling. We analyzed clinical samples from HTLV-1-infected individuals with a broad range of proviral loads using a high-throughput methodology that enables isolation of HTLV-1 integration sites and accurate measurement of the size of infected clones. We categorized clones into four size groups, "very small", "small", "big", and "very big", based on the patterns of clonal growth and observed clone sizes. We propose an empirical formal model based on deterministic finite state automata (DFA) analysis of real clinical samples to illustrate patterns of clonal expansion. Through the developed model, we have translated biological data of clonal expansion into the formal language of mathematics and represented the observed clonality data with DFA. Our data suggest that combining experimental data (absolute size of clones) with DFA can describe the clonality status of patients. This kind of modeling provides a basic

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale)

PubMed Central

2014-01-01

Objective The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. Design Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. Study sample 1220 people who have attended MRC IHR over the last decade. Results We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed “speech understanding”, “spatial perception”, and “clarity, separation, and identification”. Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, “effort and concentration”, representing two more questions. Conclusions These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores. PMID:24417459

Gradient spectral analysis of solar radio flare superevents

NASA Astrophysics Data System (ADS)

Rosa, R. R.; Veronese, T. B.; Sych, R. A.; Bolzan, M. A.; Sandri, S. A.; Drummond, I. A.; Becceneri, J. C.; Sawant, H. S.

2011-12-01

Some of complex solar active regions exhibit rare and sudden transitions that occur over time intervals that are short compared to the characteristic time scales of their evolution. Usually, extreme radio emission is driven by a latent nonlinear process involving magnetic reconnection among coronal loops and such extreme events (e.g., X-class flares and coronal mass ejections) express the presence of plasma and magnetic activity usually hidden inside the solar convective layer. Recently, the scaling exponent obtained from Detrended Fluctuation Analysis has been used to characterize the formation of solar flare superevents - SFS (integrated flux of radiation greater than 1.5 J/m2) when it is observed in the decimetric range of 1-3 GHz (Veronese et al., 2011). Here, we show a complementary computational analisys of four X-class solar flares observed in 17GHz from Nobeyama Radioheliograph. Our analysis is based on the combination of DFA and Gradient Spectral Analysis (GSA) which can be used to characterize the evolution of SFSs under the condition that the emission threshold is large enough (fmax > 300 S.F.U.) and the solar flux unit variability is greater than 50% of the average taken from the minimum flux to the extreme value. Preliminary studies of the gradient spectra of Nobeyama data in 17 GHz can be found in Sawant et al. (JASTP 73(11), 2011). Future applications of GSA on the images which will be observed from the Brazilian Decimetric Array (BDA) are discusssed.

Multifractal Detrended Fluctuation Analysis of Regional Precipitation Sequences Based on the CEEMDAN-WPT

NASA Astrophysics Data System (ADS)

Liu, Dong; Cheng, Chen; Fu, Qiang; Liu, Chunlei; Li, Mo; Faiz, Muhammad Abrar; Li, Tianxiao; Khan, Muhammad Imran; Cui, Song

2018-03-01

In this paper, the complete ensemble empirical mode decomposition with the adaptive noise (CEEMDAN) algorithm is introduced into the complexity research of precipitation systems to improve the traditional complexity measure method specific to the mode mixing of the Empirical Mode Decomposition (EMD) and incomplete decomposition of the ensemble empirical mode decomposition (EEMD). We combined the CEEMDAN with the wavelet packet transform (WPT) and multifractal detrended fluctuation analysis (MF-DFA) to create the CEEMDAN-WPT-MFDFA, and used it to measure the complexity of the monthly precipitation sequence of 12 sub-regions in Harbin, Heilongjiang Province, China. The results show that there are significant differences in the monthly precipitation complexity of each sub-region in Harbin. The complexity of the northwest area of Harbin is the lowest and its predictability is the best. The complexity and predictability of the middle and Midwest areas of Harbin are about average. The complexity of the southeast area of Harbin is higher than that of the northwest, middle, and Midwest areas of Harbin and its predictability is worse. The complexity of Shuangcheng is the highest and its predictability is the worst of all the studied sub-regions. We used terrain and human activity as factors to analyze the causes of the complexity of the local precipitation. The results showed that the correlations between the precipitation complexity and terrain are obvious, and the correlations between the precipitation complexity and human influence factors vary. The distribution of the precipitation complexity in this area may be generated by the superposition effect of human activities and natural factors such as terrain, general atmospheric circulation, land and sea location, and ocean currents. To evaluate the stability of the algorithm, the CEEMDAN-WPT-MFDFA was compared with the equal probability coarse graining LZC algorithm, fuzzy entropy, and wavelet entropy. The results show

Transannular E···E' Interactions in Neutral, Radical Cationic, and Dicationic Forms of cyclo-[E(CH2CH2CH2)2E'] (E, E' = S, Se, Te, and O) with Structural Feature: Dynamic and Static Behavior of E···E' Elucidated by QTAIM Dual Functional Analysis.

PubMed

Hayashi, Satoko; Matsuiwa, Kohei; Nishizawa, Nozomu; Nakanishi, Waro

2015-12-18

The nature of the transannular E-∗-E' interactions in neutral, radical cationic, and dicationic forms of cyclo-E(CH2CH2CH2)2E' (1) (E, E' = S, Se, Te, and O) (1, 1(•+), and 1(2+), respectively) is elucidated by applying QTAIM dual functional analysis (QTAIM-DFA). Hb(rc) are plotted versus Hb(rc) - Vb(rc)/2 for the data of E-∗-E' at BCPs in QTAIM-DFA, where ∗ emphasizes the existence of BCP. Plots for the fully optimized structures are analyzed by the polar coordinate (R, θ) representation. Those containing the perturbed structures are by (θp, κp): θp corresponds to the tangent line of the plot, and κp is the curvature. While (R, θ) describes the static nature, (θp, κp) represents the dynamic nature of interactions. The nature is well-specified by (R, θ) and (θp, κp). E-∗-E' becomes stronger in the order of 1 < 1(•+) < 1(2+), except for O-∗-O. While E-∗-E' (E, E' = S, Se, and Te) in 1(2+) are characterized as weak covalent bonds, except for S-∗-Te (MC nature through CT) and Se-∗-Te (TBP nature through CT), O-∗-E' seems more complex. The behavior of E-∗-E' in 1(2+) is very close to that of cyclo-E(CH2CH2CH2)E' (E, E' = S, Se, Te, and O), except for O-∗-O.

Exploratory factor analysis of the functional movement screen in elite athletes.

PubMed

Li, Yongming; Wang, Xiong; Chen, Xiaoping; Dai, Boyi

2015-01-01

The functional movement screen is developed to examine individuals' movement patterns through 7 functional tasks. The purpose of this study was to identify the internal consistency and factor structure of the 7 tasks of the functional movement screen in elite athletes; 290 elite athletes from a variety of Chinese national teams were assessed using the functional movement screen. Cronbach's alpha was calculated for the scores of the 7 tasks. Exploratory factor analysis was performed to explore the factor structure of the functional movement screen. The mean and standard deviation of the sum score were 15.2 ± 3.0. A low Cronbach's alpha (0.58) was found for the scores of the 7 tasks. Exploratory factor analysis extracted 2 factors with eigenvalues greater than 1, and these 2 factors explained 47.3% of the total variance. The first factor had a high loading on the rotatory stability (loading = 0.99) and low loadings on the other 6 tasks (loading range: 0.04-0.34). The second factor had high loadings on the deep squat, hurdle step and inline lunge (loading range: 0.46-0.61) and low loadings on the other 3 tasks (loading range: 0.12-0.32). The 7 tasks of the functional movement screen had low internal consistency and were not indicators of a single factor. Evidence for unidimensionality was not found for the functional movement screen in elite athletes. More attention should be paid to the score of each task rather than the sum score when we interpret the functional movement screen scores.

Combined target factor analysis and Bayesian soft-classification of interference-contaminated samples: forensic fire debris analysis.

PubMed

Williams, Mary R; Sigman, Michael E; Lewis, Jennifer; Pitan, Kelly McHugh

2012-10-10

A bayesian soft classification method combined with target factor analysis (TFA) is described and tested for the analysis of fire debris data. The method relies on analysis of the average mass spectrum across the chromatographic profile (i.e., the total ion spectrum, TIS) from multiple samples taken from a single fire scene. A library of TIS from reference ignitable liquids with assigned ASTM classification is used as the target factors in TFA. The class-conditional distributions of correlations between the target and predicted factors for each ASTM class are represented by kernel functions and analyzed by bayesian decision theory. The soft classification approach assists in assessing the probability that ignitable liquid residue from a specific ASTM E1618 class, is present in a set of samples from a single fire scene, even in the presence of unspecified background contributions from pyrolysis products. The method is demonstrated with sample data sets and then tested on laboratory-scale burn data and large-scale field test burns. The overall performance achieved in laboratory and field test of the method is approximately 80% correct classification of fire debris samples. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Untangling Trends and Drivers of Changing River Discharge Along Florida's Gulf Coast

NASA Astrophysics Data System (ADS)

Glodzik, K.; Kaplan, D. A.; Klarenberg, G.

2017-12-01

Along the relatively undeveloped Big Bend coastline of Florida, discharge in many rivers and springs is decreasing. The causes are unclear, though they likely include a combination of groundwater extraction for water supply, climate variability, and altered land use. Saltwater intrusion from altered freshwater influence and sea level rise is causing transformative ecosystem impacts along this flat coastline, including coastal forest die-off and oyster reef collapse. A key uncertainty for understanding river discharge change is predicting discharge from rainfall, since Florida's karstic bedrock stores large amounts of groundwater, which has a long residence time. This study uses Dynamic Factor Analysis (DFA), a multivariate data reduction technique for time series, to find common trends in flow and reveal hydrologic variables affecting flow in eight Big Bend rivers since 1965. The DFA uses annual river flows as response time series, and climate data (annual rainfall and evapotranspiration by watershed) and climatic indices (El Niño Southern Oscillation [ENSO] Index and North Atlantic Oscillation [NAO] Index) as candidate explanatory variables. Significant explanatory variables (one evapotranspiration and three rainfall time series) explained roughly 50% of discharge variation across rivers. Significant trends (representing unexplained variation) were shared among rivers, with geographical grouping of five northern rivers and three southern rivers, along with a strong downward trend affecting six out of eight systems. ENSO and NAO had no significant impact. Advancing knowledge of these dynamics is necessary for forecasting how altered rainfall and temperatures from climate change may impact flows. Improved forecasting is especially important given Florida's reliance on groundwater extraction to support its growing population.

Confirmatory factor analysis of the female sexual function index.

PubMed

Opperman, Emily A; Benson, Lindsay E; Milhausen, Robin R

2013-01-01

The Female Sexual Functioning Index (Rosen et al., 2000 ) was designed to assess the key dimensions of female sexual functioning using six domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. A full-scale score was proposed to represent women's overall sexual function. The fifth revision to the Diagnostic and Statistical Manual (DSM) is currently underway and includes a proposal to combine desire and arousal problems. The objective of this article was to evaluate and compare four models of the Female Sexual Functioning Index: (a) single-factor model, (b) six-factor model, (c) second-order factor model, and (4) five-factor model combining the desire and arousal subscales. Cross-sectional and observational data from 85 women were used to conduct a confirmatory factor analysis on the Female Sexual Functioning Index. Local and global goodness-of-fit measures, the chi-square test of differences, squared multiple correlations, and regression weights were used. The single-factor model fit was not acceptable. The original six-factor model was confirmed, and good model fit was found for the second-order and five-factor models. Delta chi-square tests of differences supported best fit for the six-factor model validating usage of the six domains. However, when revisions are made to the DSM-5, the Female Sexual Functioning Index can adapt to reflect these changes and remain a valid assessment tool for women's sexual functioning, as the five-factor structure was also supported.

The School Counseling Program Implementation Survey: Initial Instrument Development and Exploratory Factor Analysis