Evaluating CMA equalization of SOQPSK-TG data for aeronautical telemetry

NASA Astrophysics Data System (ADS)

Cole-Rhodes, Arlene; KoneDossongui, Serge; Umuolo, Henry; Rice, Michael

2015-05-01

This paper presents the results of using a constant modulus algorithm (CMA) to recover shaped offset quadrature-phase shift keying (SOQPSK)-TG modulated data, which has been transmitted using the iNET data packet structure. This standard is defined and used for aeronautical telemetry. Based on the iNET-packet structure, the adaptive block processing CMA equalizer can be initialized using the minimum mean square error (MMSE) equalizer [3]. This CMA equalizer is being evaluated for use on iNET structured data, with initial tests being conducted on measured data which has been received in a controlled laboratory environment. Thus the CMA equalizer is applied at the receiver to data packets which have been experimentally generated in order to determine the feasibility of our equalization approach, and its performance is compared to that of the MMSE equalizer. Performance evaluation is based on computed bit error rate (BER) counts for these equalizers.

Performance Comparison between CDTD and STTD for DS-CDMA/MMSE-FDE with Frequency-Domain ICI Cancellation

NASA Astrophysics Data System (ADS)

Takeda, Kazuaki; Kojima, Yohei; Adachi, Fumiyuki

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can provide a better bit error rate (BER) performance than rake combining. However, the residual inter-chip interference (ICI) is produced after MMSE-FDE and this degrades the BER performance. Recently, we showed that frequency-domain ICI cancellation can bring the BER performance close to the theoretical lower bound. To further improve the BER performance, transmit antenna diversity technique is effective. Cyclic delay transmit diversity (CDTD) can increase the number of equivalent paths and hence achieve a large frequency diversity gain. Space-time transmit diversity (STTD) can obtain antenna diversity gain due to the space-time coding and achieve a better BER performance than CDTD. Objective of this paper is to show that the BER performance degradation of CDTD is mainly due to the residual ICI and that the introduction of ICI cancellation gives almost the same BER performance as STTD. This study provides a very important result that CDTD has a great advantage of providing a higher throughput than STTD. This is confirmed by computer simulation. The computer simulation results show that CDTD can achieve higher throughput than STTD when ICI cancellation is introduced.

Investigation of adaptive filtering and MDL mitigation based on space-time block-coding for spatial division multiplexed coherent receivers

NASA Astrophysics Data System (ADS)

Weng, Yi; He, Xuan; Yao, Wang; Pacheco, Michelle C.; Wang, Junyi; Pan, Zhongqi

2017-07-01

In this paper, we explored the performance of space-time block-coding (STBC) assisted multiple-input multiple-output (MIMO) scheme for modal dispersion and mode-dependent loss (MDL) mitigation in spatial-division multiplexed optical communication systems, whereas the weight matrices of frequency-domain equalization (FDE) were updated heuristically using decision-directed recursive least squares (RLS) algorithm for convergence and channel estimation. The proposed STBC-RLS algorithm can achieve 43.6% enhancement on convergence rate over conventional least mean squares (LMS) for quadrature phase-shift keying (QPSK) signals with merely 16.2% increase in hardware complexity. The overall optical signal to noise ratio (OSNR) tolerance can be improved via STBC by approximately 3.1, 4.9, 7.8 dB for QPSK, 16-quadrature amplitude modulation (QAM) and 64-QAM with respective bit-error-rates (BER) and minimum-mean-square-error (MMSE).

A study on the achievable data rate in massive MIMO system

NASA Astrophysics Data System (ADS)

Salh, Adeeb; Audah, Lukman; Shah, Nor Shahida M.; Hamzah, Shipun A.

2017-09-01

The achievable high data rates depend on the ability of massive multi-input-multi-output (MIMO) for the fifth-generation (5G) cellular networks, where the massive MIMO systems can support very high energy and spectral efficiencies. A major challenge in mobile broadband networks is how to support the throughput in the future 5G, where the highlight of 5G expected to provide high speed internet for every user. The performance massive MIMO system increase with linear minimum mean square error (MMSE), zero forcing (ZF) and maximum ratio transmission (MRT) when the number of antennas increases to infinity, by deriving the closed-form approximation for achievable data rate expressions. Meanwhile, the high signal-to-noise ratio (SNR) can be mitigated by using MMSE, ZF and MRT, which are used to suppress the inter-cell interference signals between neighboring cells. The achievable sum rate for MMSE is improved based on the distributed users inside cell, mitigated the inter-cell interference caused when send the same signal by other cells. By contrast, MMSE is better than ZF in perfect channel state information (CSI) for approximately 20% of the achievable sum rate.

MMSE Estimator for Children’s Speech with Car and Weather Noise

NASA Astrophysics Data System (ADS)

Sayuthi, V.

2018-04-01

Previous research mentioned that most people need and use vehicles for various purposes, in this recent time and future, as a means of traveling. Many ways can be done in a vehicle, such as for enjoying entertainment, and doing work, so vehicles not just only as a means of traveling. In this study, we will examine the children’s speech from a girl in the vehicle that affected by noise disturbances from the sound source of car noise and the weather sound noise around it, in this case, the rainy weather noise. Vehicle sounds may be from car engine or car air conditioner. The minimum mean square error (MMSE) estimator is used as an attempt to obtain or detect the children’s clear speech by representing simulation research as random process signal that factored by the autocorrelation of both the child’s voice and the disturbance noise signal. This MMSE estimator can be considered as wiener filter as the clear sound are reconstructed again. We expected that the results of this study can help as the basis for development of entertainment or communication technology for passengers of vehicles in the future, particularly using MMSE estimators.

Validation of the Conversion between the Mini-Mental State Examination and Montreal Cognitive assessment in Korean Patients with Parkinson’s Disease

PubMed Central

Kim, Ryul; Kim, Han-Joon; Kim, Aryun; Jang, Mi-Hee; Kim, Hyun Jeong; Jeon, Beomseok

2018-01-01

Objective Two conversion tables between the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) have recently been established for Parkinson’s disease (PD). This study aimed to validate them in Korean patients with PD and to evaluate whether they could be influenced by educational level. Methods A total of 391 patients with PD who undertook both the Korean MMSE and the Korean MoCA during the same session were retrospectively assessed. The mean, median, and root mean squared error (RMSE) of the difference between the true and converted MMSE scores and the intraclass correlation coefficient (ICC) were calculated according to educational level (6 or fewer years, 7–12 years, or 13 or more years). Results Both conversions had a median value of 0, with a small mean and RMSE of differences, and a high correlation between the true and converted MMSE scores. In the classification according to educational level, all groups had roughly similar values of the median, mean, RMSE, and ICC both within and between the conversions. Conclusion Our findings suggest that both MMSE-MoCA conversion tables are useful instruments for transforming MoCA scores into converted MMSE scores in Korean patients with PD, regardless of educational level. These will greatly enhance the utility of the existing cognitive data from the Korean PD population in clinical and research settings. PMID:29316782

Improving Bandwidth Utilization in a 1 Tbps Airborne MIMO Communications Downlink

DTIC Science & Technology

2013-03-21

number of transmitters). C = log2 ∣∣∣∣∣INr + EsNtN0 HHH ∣∣∣∣∣ (2.32) In the signal to noise ratio, Es represents the total energy from all transmitters...channel matrix pseudo-inverse is computed by (2.36) [6, p. 970] 31 H+ = ( HHH )−1HH. (2.36) 2.6.5 Minimum Mean-Squared Error Detection. Minimum Mean Squared...H† = ( HHH + Nt SNR I )−1 HH . (3.14) Equation (3.14) was defined in [2] as an implementation of a MMSE equalizer, and was applied to the received

Tracking with time-delayed data in multisensor systems

NASA Astrophysics Data System (ADS)

Hilton, Richard D.; Martin, David A.; Blair, William D.

1993-08-01

When techniques for target tracking are expanded to make use of multiple sensors in a multiplatform system, the possibility of time delayed data becomes a reality. When a discrete-time Kalman filter is applied and some of the data entering the filter are delayed, proper processing of these late data is a necessity for obtaining an optimal estimate of a target's state. If this problem is not given special care, the quality of the state estimates can be degraded relative to that quality provided by a single sensor. A negative-time update technique is developed using the criteria of minimum mean-square error (MMSE) under the constraint that only the results of the most recent update are saved. The performance of the MMSE technique is compared to that of the ad hoc approach employed in the Cooperative Engagement Capabilities (CEC) system for processing data from multiple platforms. It was discovered that the MMSE technique is a stable solution to the negative-time update problem, while the CEC technique was found to be less than desirable when used with filters designed for tracking highly maneuvering targets at relatively low data rates. The MMSE negative-time update technique was found to be a superior alternative to the existing CEC negative-time update technique.

Screening an elderly hearing impaired population for mild cognitive impairment using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA).

PubMed

Lim, Magdalene Yeok Leng; Loo, Jenny Hooi Yin

2018-07-01

To determine if there is an association between hearing loss and poorer cognitive scores on Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) and to determine if poor hearing acuity affects scoring on the cognitive screening tests of MMSE and MoCA. One hundred fourteen elderly patients (Singapore residents) aged between 55 and 86 years were sampled. Participants completed a brief history questionnaire, pure tone audiometry, and 2 cognitive screening tests-the MMSE and MoCA. Average hearing thresholds of the better ear in the frequencies of 0.5, 1, 2, and 4 kHz were used for data analysis. Hearing loss was significantly associated with poorer cognitive scores in Poisson regression models adjusted for age. Mini-Mental State Examination scores were shown to decrease by 2.8% (P = .029), and MoCA scores by 3.5% (P = .013) for every 10 dB of hearing loss. Analysis of hearing-sensitive components of "Registration" and "Recall" in MMSE and MoCA using chi-square tests showed significantly poorer performance in the hearing loss group as compared to the normal hearing group. Phonetic analysis of target words with high error rates shows that the poor performance was likely contributed by decreased hearing acuity, on top of a possible true deficit in cognition in the hearing impaired. Hearing loss is associated with poorer cognitive scores on MMSE and MoCA, and cognitive scoring is likely confounded by poor hearing ability. This highlights an important, often overlooked aspect of sensory impairment during cognitive screening. Provisions should be made when testing for cognition in the hearing-impaired population to avoid over-referral and subsequent misdiagnoses of cognitive impairment. Copyright © 2018 John Wiley & Sons, Ltd.

Time-of-flight PET image reconstruction using origin ensembles.

PubMed

Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

2015-03-07

The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

Time-of-flight PET image reconstruction using origin ensembles

NASA Astrophysics Data System (ADS)

Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

2015-03-01

The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems.

PubMed

Liu, Xi; Qu, Hua; Zhao, Jihong; Yue, Pengcheng

2018-05-31

For a nonlinear system, the cubature Kalman filter (CKF) and its square-root version are useful methods to solve the state estimation problems, and both can obtain good performance in Gaussian noises. However, their performances often degrade significantly in the face of non-Gaussian noises, particularly when the measurements are contaminated by some heavy-tailed impulsive noises. By utilizing the maximum correntropy criterion (MCC) to improve the robust performance instead of traditional minimum mean square error (MMSE) criterion, a new square-root nonlinear filter is proposed in this study, named as the maximum correntropy square-root cubature Kalman filter (MCSCKF). The new filter not only retains the advantage of square-root cubature Kalman filter (SCKF), but also exhibits robust performance against heavy-tailed non-Gaussian noises. A judgment condition that avoids numerical problem is also given. The results of two illustrative examples, especially the SINS/GPS integrated systems, demonstrate the desirable performance of the proposed filter. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Iterative Overlap FDE for Multicode DS-CDMA

NASA Astrophysics Data System (ADS)

Takeda, Kazuaki; Tomeba, Hiromichi; Adachi, Fumiyuki

Recently, a new frequency-domain equalization (FDE) technique, called overlap FDE, that requires no GI insertion was proposed. However, the residual inter/intra-block interference (IBI) cannot completely be removed. In addition to this, for multicode direct sequence code division multiple access (DS-CDMA), the presence of residual interchip interference (ICI) after FDE distorts orthogonality among the spreading codes. In this paper, we propose an iterative overlap FDE for multicode DS-CDMA to suppress both the residual IBI and the residual ICI. In the iterative overlap FDE, joint minimum mean square error (MMSE)-FDE and ICI cancellation is repeated a sufficient number of times. The bit error rate (BER) performance with the iterative overlap FDE is evaluated by computer simulation.

MIMO equalization with adaptive step size for few-mode fiber transmission systems.

PubMed

van Uden, Roy G H; Okonkwo, Chigo M; Sleiffer, Vincent A J M; de Waardt, Hugo; Koonen, Antonius M J

2014-01-13

Optical multiple-input multiple-output (MIMO) transmission systems generally employ minimum mean squared error time or frequency domain equalizers. Using an experimental 3-mode dual polarization coherent transmission setup, we show that the convergence time of the MMSE time domain equalizer (TDE) and frequency domain equalizer (FDE) can be reduced by approximately 50% and 30%, respectively. The criterion used to estimate the system convergence time is the time it takes for the MIMO equalizer to reach an average output error which is within a margin of 5% of the average output error after 50,000 symbols. The convergence reduction difference between the TDE and FDE is attributed to the limited maximum step size for stable convergence of the frequency domain equalizer. The adaptive step size requires a small overhead in the form of a lookup table. It is highlighted that the convergence time reduction is achieved without sacrificing optical signal-to-noise ratio performance.

Channel estimation in few mode fiber mode division multiplexing transmission system

NASA Astrophysics Data System (ADS)

Hei, Yongqiang; Li, Li; Li, Wentao; Li, Xiaohui; Shi, Guangming

2018-03-01

It is abundantly clear that obtaining the channel state information (CSI) is of great importance for the equalization and detection in coherence receivers. However, to the best of the authors' knowledge, in most of the existing literatures, CSI is assumed to be perfectly known at the receiver. So far, few literature discusses the effects of imperfect CSI on MDM system performance caused by channel estimation. Motivated by that, in this paper, the channel estimation in few mode fiber (FMF) mode division multiplexing (MDM) system is investigated, in which two classical channel estimation methods, i.e., least square (LS) method and minimum mean square error (MMSE) method, are discussed with the assumption of the spatially white noise lumped at the receiver side of MDM system. Both the capacity and BER performance of MDM system affected by mode-dependent gain or loss (MDL) with different channel estimation errors have been studied. Simulation results show that the capacity and BER performance can be further deteriorated in MDM system by the channel estimation, and an 1e-3 variance of channel estimation error is acceptable in MDM system with 0-6 dB MDL values.

Digital transceiver design for two-way AF-MIMO relay systems with imperfect CSI

NASA Astrophysics Data System (ADS)

Hu, Chia-Chang; Chou, Yu-Fei; Chen, Kui-He

2013-09-01

In the paper, combined optimization of the terminal precoders/equalizers and single-relay precoder is proposed for an amplify-and-forward (AF) multiple-input multiple-output (MIMO) two-way single-relay system with correlated channel uncertainties. Both terminal transceivers and relay precoding matrix are designed based on the minimum mean square error (MMSE) criterion when terminals are unable to erase completely self-interference due to imperfect correlated channel state information (CSI). This robust joint optimization problem of beamforming and precoding matrices under power constraints belongs to neither concave nor convex so that a nonlinear matrix-form conjugate gradient (MCG) algorithm is applied to explore local optimal solutions. Simulation results show that the robust transceiver design is able to overcome effectively the loss of bit-error-rate (BER) due to inclusion of correlated channel uncertainties and residual self-interference.

Pilot-Assisted Channel Estimation for Orthogonal Multi-Carrier DS-CDMA with Frequency-Domain Equalization

NASA Astrophysics Data System (ADS)

Shima, Tomoyuki; Tomeba, Hiromichi; Adachi, Fumiyuki

Orthogonal multi-carrier direct sequence code division multiple access (orthogonal MC DS-CDMA) is a combination of time-domain spreading and orthogonal frequency division multiplexing (OFDM). In orthogonal MC DS-CDMA, the frequency diversity gain can be obtained by applying frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion to a block of OFDM symbols and can improve the bit error rate (BER) performance in a severe frequency-selective fading channel. FDE requires an accurate estimate of the channel gain. The channel gain can be estimated by removing the pilot modulation in the frequency domain. In this paper, we propose a pilot-assisted channel estimation suitable for orthogonal MC DS-CDMA with FDE and evaluate, by computer simulation, the BER performance in a frequency-selective Rayleigh fading channel.

Measurement Error, Reliability, and Minimum Detectable Change in the Mini-Mental State Examination, Montreal Cognitive Assessment, and Color Trails Test among Community Living Middle-Aged and Older Adults.

PubMed

Feeney, Joanne; Savva, George M; O'Regan, Claire; King-Kallimanis, Bellinda; Cronin, Hilary; Kenny, Rose Anne

2016-05-31

Knowing the reliability of cognitive tests, particularly those commonly used in clinical practice, is important in order to interpret the clinical significance of a change in performance or a low score on a single test. To report the intra-class correlation (ICC), standard error of measurement (SEM) and minimum detectable change (MDC) for the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Color Trails Test (CTT) among community dwelling older adults. 130 participants aged 55 and older without severe cognitive impairment underwent two cognitive assessments between two and four months apart. Half the group changed rater between assessments and half changed time of day. Mean (standard deviation) MMSE was 28.1 (2.1) at baseline and 28.4 (2.1) at repeat. Mean (SD) MoCA increased from 24.8 (3.6) to 25.2 (3.6). There was a rater effect on CTT, but not on the MMSE or MoCA. The SEM of the MMSE was 1.0, leading to an MDC (based on a 95% confidence interval) of 3 points. The SEM of the MoCA was 1.5, implying an MDC95 of 4 points. MoCA (ICC = 0.81) was more reliable than MMSE (ICC = 0.75), but all tests examined showed substantial within-patient variation. An individual's score would have to change by greater than or equal to 3 points on the MMSE and 4 points on the MoCA for the rater to be confident that the change was not due to measurement error. This has important implications for epidemiologists and clinicians in dementia screening and diagnosis.

Bayesian estimation of the discrete coefficient of determination.

PubMed

Chen, Ting; Braga-Neto, Ulisses M

2016-12-01

The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.

The Influence of Noise Reduction on Speech Intelligibility, Response Times to Speech, and Perceived Listening Effort in Normal-Hearing Listeners.

PubMed

van den Tillaart-Haverkate, Maj; de Ronde-Brons, Inge; Dreschler, Wouter A; Houben, Rolph

2017-01-01

Single-microphone noise reduction leads to subjective benefit, but not to objective improvements in speech intelligibility. We investigated whether response times (RTs) provide an objective measure of the benefit of noise reduction and whether the effect of noise reduction is reflected in rated listening effort. Twelve normal-hearing participants listened to digit triplets that were either unprocessed or processed with one of two noise-reduction algorithms: an ideal binary mask (IBM) and a more realistic minimum mean square error estimator (MMSE). For each of these three processing conditions, we measured (a) speech intelligibility, (b) RTs on two different tasks (identification of the last digit and arithmetic summation of the first and last digit), and (c) subjective listening effort ratings. All measurements were performed at four signal-to-noise ratios (SNRs): -5, 0, +5, and +∞ dB. Speech intelligibility was high (>97% correct) for all conditions. A significant decrease in response time, relative to the unprocessed condition, was found for both IBM and MMSE for the arithmetic but not the identification task. Listening effort ratings were significantly lower for IBM than for MMSE and unprocessed speech in noise. We conclude that RT for an arithmetic task can provide an objective measure of the benefit of noise reduction. For young normal-hearing listeners, both ideal and realistic noise reduction can reduce RTs at SNRs where speech intelligibility is close to 100%. Ideal noise reduction can also reduce perceived listening effort.

A hybrid demodulation method of fiber-optic Fabry-Perot pressure sensor

NASA Astrophysics Data System (ADS)

Yu, Le; Lang, Jianjun; Pan, Yong; Wu, Di; Zhang, Min

2013-12-01

The fiber-optic Fabry-Perot pressure sensors have been widely applied to measure pressure in oilfield. For multi-well it will take a long time (dozens of seconds) to demodulate downhole pressure values of all wells by using only one demodulation system and it will cost a lot when every well is equipped with one system, which heavily limits the sensor applied in oilfield. In present paper, a new hybrid demodulation method, combining the windowed nonequispaced discrete Fourier Transform (nDFT) method with segment search minimum mean square error estimation (MMSE) method, was developed, by which the demodulation time can be reduced to 200ms, i.e., measuring 10 channels/wells was less than 2s. Besides, experimental results showed the demodulation cavity length of the fiber-optic Fabry-Perot sensor has a maximum error of 0.5 nm and consequently pressure measurement accuracy can reach 0.4% F.S.

LS Channel Estimation and Signal Separation for UHF RFID Tag Collision Recovery on the Physical Layer.

PubMed

Duan, Hanjun; Wu, Haifeng; Zeng, Yu; Chen, Yuebin

2016-03-26

In a passive ultra-high frequency (UHF) radio-frequency identification (RFID) system, tag collision is generally resolved on a medium access control (MAC) layer. However, some of collided tag signals could be recovered on a physical (PHY) layer and, thus, enhance the identification efficiency of the RFID system. For the recovery on the PHY layer, channel estimation is a critical issue. Good channel estimation will help to recover the collided signals. Existing channel estimates work well for two collided tags. When the number of collided tags is beyond two, however, the existing estimates have more estimation errors. In this paper, we propose a novel channel estimate for the UHF RFID system. It adopts an orthogonal matrix based on the information of preambles which is known for a reader and applies a minimum-mean-square-error (MMSE) criterion to estimate channels. From the estimated channel, we could accurately separate the collided signals and recover them. By means of numerical results, we show that the proposed estimate has lower estimation errors and higher separation efficiency than the existing estimates.

Beamforming Based Full-Duplex for Millimeter-Wave Communication

PubMed Central

Liu, Xiao; Xiao, Zhenyu; Bai, Lin; Choi, Jinho; Xia, Pengfei; Xia, Xiang-Gen

2016-01-01

In this paper, we study beamforming based full-duplex (FD) systems in millimeter-wave (mmWave) communications. A joint transmission and reception (Tx/Rx) beamforming problem is formulated to maximize the achievable rate by mitigating self-interference (SI). Since the optimal solution is difficult to find due to the non-convexity of the objective function, suboptimal schemes are proposed in this paper. A low-complexity algorithm, which iteratively maximizes signal power while suppressing SI, is proposed and its convergence is proven. Moreover, two closed-form solutions, which do not require iterations, are also derived under minimum-mean-square-error (MMSE), zero-forcing (ZF), and maximum-ratio transmission (MRT) criteria. Performance evaluations show that the proposed iterative scheme converges fast (within only two iterations on average) and approaches an upper-bound performance, while the two closed-form solutions also achieve appealing performances, although there are noticeable differences from the upper bound depending on channel conditions. Interestingly, these three schemes show different robustness against the geometry of Tx/Rx antenna arrays and channel estimation errors. PMID:27455256

Falls and cognitive decline in Mexican Americans 75 years and older

PubMed Central

Padubidri, Anokha; Al Snih, Soham; Samper-Ternent, Rafael; Markides, Kyriakos S; Ottenbacher, Kenneth J; Raji, Mukaila A

2014-01-01

Background Little is known about long-term emotional and cognitive consequences of falls. We examined the association between falls and subsequent cognitive decline, and tested the hypothesis that depression would mediate any falls–cognition association among cognitively intact Hispanic Elders. Methods We used data from the Hispanic Established Population for the Epidemiological Study of the Elderly to examine change in Mini Mental State Examination (MMSE) scores over the 6-year period according to number of falls. All participants (N=1,119) had MMSE scores ≥21 and complete data on Center for Epidemiologic Studies of Depression Scale, social and demographic factors, medical conditions (diabetes, heart attack, stroke, and hypertension), and hand grip muscle strength. Results At baseline, participants’ mean age was 80.8 years (range, 74–109), mean education was 6.3 years (range, 0–17), and mean MMSE was 25.2 (range, 21–30). Of the 1,119 participants, 15.8% experienced one fall and 14.4% had two or more falls. In mixed model analyses, having two or more falls was associated with greater decline in MMSE score (estimate =−0.81, standard error =0.19, P<0.0001) compared to having no fall, after adjusting for age, sex, marital status, and education. The magnitude of the association decreased (estimate =−0.65, standard error =0.19, P=0.0007) when adjustment was made for high depressive symptoms, suggesting a possible mediating effect of depression on the falls–cognition association. Female sex, high level of education, and high performance in hand grip muscle strength were associated with a slower decline in MMSE scores. Conclusion Having two or more falls was independently associated with steeper decline in cognition over 6 years, with a possible mediating effect of depression on the falls–cognition association. PMID:24790424

Iterative Frequency Domain Decision Feedback Equalization and Decoding for Underwater Acoustic Communications

NASA Astrophysics Data System (ADS)

Zhao, Liang; Ge, Jian-Hua

2012-12-01

Single-carrier (SC) transmission with frequency-domain equalization (FDE) is today recognized as an attractive alternative to orthogonal frequency-division multiplexing (OFDM) for communication application with the inter-symbol interference (ISI) caused by multi-path propagation, especially in shallow water channel. In this paper, we investigate an iterative receiver based on minimum mean square error (MMSE) decision feedback equalizer (DFE) with symbol rate and fractional rate samplings in the frequency domain (FD) and serially concatenated trellis coded modulation (SCTCM) decoder. Based on sound speed profiles (SSP) measured in the lake and finite-element ray tracking (Bellhop) method, the shallow water channel is constructed to evaluate the performance of the proposed iterative receiver. Performance results show that the proposed iterative receiver can significantly improve the performance and obtain better data transmission than FD linear and adaptive decision feedback equalizers, especially in adopting fractional rate sampling.

Low-Complexity Polynomial Channel Estimation in Large-Scale MIMO With Arbitrary Statistics

NASA Astrophysics Data System (ADS)

Shariati, Nafiseh; Bjornson, Emil; Bengtsson, Mats; Debbah, Merouane

2014-10-01

This paper considers pilot-based channel estimation in large-scale multiple-input multiple-output (MIMO) communication systems, also known as massive MIMO, where there are hundreds of antennas at one side of the link. Motivated by the fact that computational complexity is one of the main challenges in such systems, a set of low-complexity Bayesian channel estimators, coined Polynomial ExpAnsion CHannel (PEACH) estimators, are introduced for arbitrary channel and interference statistics. While the conventional minimum mean square error (MMSE) estimator has cubic complexity in the dimension of the covariance matrices, due to an inversion operation, our proposed estimators significantly reduce this to square complexity by approximating the inverse by a L-degree matrix polynomial. The coefficients of the polynomial are optimized to minimize the mean square error (MSE) of the estimate. We show numerically that near-optimal MSEs are achieved with low polynomial degrees. We also derive the exact computational complexity of the proposed estimators, in terms of the floating-point operations (FLOPs), by which we prove that the proposed estimators outperform the conventional estimators in large-scale MIMO systems of practical dimensions while providing a reasonable MSEs. Moreover, we show that L needs not scale with the system dimensions to maintain a certain normalized MSE. By analyzing different interference scenarios, we observe that the relative MSE loss of using the low-complexity PEACH estimators is smaller in realistic scenarios with pilot contamination. On the other hand, PEACH estimators are not well suited for noise-limited scenarios with high pilot power; therefore, we also introduce the low-complexity diagonalized estimator that performs well in this regime. Finally, we ...

Performance Analysis of Integrated Wireless Sensor and Multibeam Satellite Networks Under Terrestrial Interference

PubMed Central

Li, Hongjun; Yin, Hao; Gong, Xiangwu; Dong, Feihong; Ren, Baoquan; He, Yuanzhi; Wang, Jingchao

2016-01-01

This paper investigates the performance of integrated wireless sensor and multibeam satellite networks (IWSMSNs) under terrestrial interference. The IWSMSNs constitute sensor nodes (SNs), satellite sinks (SSs), multibeam satellite and remote monitoring hosts (RMHs). The multibeam satellite covers multiple beams and multiple SSs in each beam. The SSs can be directly used as SNs to transmit sensing data to RMHs via the satellite, and they can also be used to collect the sensing data from other SNs to transmit to the RMHs. We propose the hybrid one-dimensional (1D) and 2D beam models including the equivalent intra-beam interference factor β from terrestrial communication networks (TCNs) and the equivalent inter-beam interference factor α from adjacent beams. The terrestrial interference is possibly due to the signals from the TCNs or the signals of sinks being transmitted to other satellite networks. The closed-form approximations of capacity per beam are derived for the return link of IWSMSNs under terrestrial interference by using the Haar approximations where the IWSMSNs experience the Rician fading channel. The optimal joint decoding capacity can be considered as the upper bound where all of the SSs’ signals can be jointly decoded by a super-receiver on board the multibeam satellite or a gateway station that knows all of the code books. While the linear minimum mean square error (MMSE) capacity is where all of the signals of SSs are decoded singularly by a multibeam satellite or a gateway station. The simulations show that the optimal capacities are obviously higher than the MMSE capacities under the same conditions, while the capacities are lowered by Rician fading and converge as the Rician factor increases. α and β jointly affect the performance of hybrid 1D and 2D beam models, and the number of SSs also contributes different effects on the optimal capacity and MMSE capacity of the IWSMSNs. PMID:27754438

Analysis of the Bayesian Cramér-Rao lower bound in astrometry. Studying the impact of prior information in the location of an object

NASA Astrophysics Data System (ADS)

Echeverria, Alex; Silva, Jorge F.; Mendez, Rene A.; Orchard, Marcos

2016-10-01

Context. The best precision that can be achieved to estimate the location of a stellar-like object is a topic of permanent interest in the astrometric community. Aims: We analyze bounds for the best position estimation of a stellar-like object on a CCD detector array in a Bayesian setting where the position is unknown, but where we have access to a prior distribution. In contrast to a parametric setting where we estimate a parameter from observations, the Bayesian approach estimates a random object (I.e., the position is a random variable) from observations that are statistically dependent on the position. Methods: We characterize the Bayesian Cramér-Rao (CR) that bounds the minimum mean square error (MMSE) of the best estimator of the position of a point source on a linear CCD-like detector, as a function of the properties of detector, the source, and the background. Results: We quantify and analyze the increase in astrometric performance from the use of a prior distribution of the object position, which is not available in the classical parametric setting. This gain is shown to be significant for various observational regimes, in particular in the case of faint objects or when the observations are taken under poor conditions. Furthermore, we present numerical evidence that the MMSE estimator of this problem tightly achieves the Bayesian CR bound. This is a remarkable result, demonstrating that all the performance gains presented in our analysis can be achieved with the MMSE estimator. Conclusions: The Bayesian CR bound can be used as a benchmark indicator of the expected maximum positional precision of a set of astrometric measurements in which prior information can be incorporated. This bound can be achieved through the conditional mean estimator, in contrast to the parametric case where no unbiased estimator precisely reaches the CR bound.

Reduced-rank technique for joint channel estimation in TD-SCDMA systems

NASA Astrophysics Data System (ADS)

Kamil Marzook, Ali; Ismail, Alyani; Mohd Ali, Borhanuddin; Sali, Adawati; Khatun, Sabira

2013-02-01

In time division-synchronous code division multiple access systems, increasing the system capacity by exploiting the inserting of the largest number of users in one time slot (TS) requires adding more estimation processes to estimate the joint channel matrix for the whole system. The increase in the number of channel parameters due the increase in the number of users in one TS directly affects the precision of the estimator's performance. This article presents a novel channel estimation with low complexity, which relies on reducing the rank order of the total channel matrix H. The proposed method exploits the rank deficiency of H to reduce the number of parameters that characterise this matrix. The adopted reduced-rank technique is based on truncated singular value decomposition algorithm. The algorithms for reduced-rank joint channel estimation (JCE) are derived and compared against traditional full-rank JCEs: least squares (LS) or Steiner and enhanced (LS or MMSE) algorithms. Simulation results of the normalised mean square error showed the superiority of reduced-rank estimators. In addition, the channel impulse responses founded by reduced-rank estimator for all active users offers considerable performance improvement over the conventional estimator along the channel window length.

The relationship between education level and Mini Mental State Examination domains among older Mexican Americans

PubMed Central

Matallana, Diana; de Santacruz, Cecilia; Cano, Carlos; Reyes, Pablo; Samper-Ternent, Rafael; Markides, Kyriakos S.; Ottenbacher, Kenneth J.; Reyes-Ortiz, Carlos A.

2011-01-01

To study the effect of education on the performance in the Mini-Mental State Examination (MMSE) domains, we included 2,861 Mexican Americans aged 65 and older from the Hispanic Established Populations for Epidemiologic Studies of the Elderly (EPESE) followed from 1993–1994 until 2004–2005. The MMSE was examined as total score (0–30) or divided in two global domains: 1) no-memory (score 0–24): Orientation, attention, and language; and 2) memory (score 0–6): working and delayed memory. Mean age and total MMSE were 72.7 and 24.6 at wave 1, and 81.7 and 20.5 at wave 5. Spanish speaking subjects had lower years of education (4.1 vs. 7.4, p<.0001), they had significantly higher adjusted (by age, education, and gender) mean scores for memory, no-memory and the total MMSE compared with English speaking subjects across the five waves of follow-up. In multivariate longitudinal analyses over 11 years of follow-up, subjects with more years of education performed better than those less educated, especially in no-memory and the total MMSE. Spanish speaking subjects with 4–6 years of education had higher memory scores than those speaking English (estimate 0.40, standard error [SE] = 0.14, p<.001), 7–11 (estimate 0.27, SE= 0.13, p<.01) or 12+ (estimate 0.44, SE= 0.13, p<.001). This suggests that cultural factors and factors related to preferred language use may determine variations in MMSE performance. Since the memory domain of the MMSE is less affected by education, it may be used along with other cognitive tests in older populations with low education. PMID:20538969

Topological Interference Management for K-User Downlink Massive MIMO Relay Network Channel.

PubMed

Selvaprabhu, Poongundran; Chinnadurai, Sunil; Li, Jun; Lee, Moon Ho

2017-08-17

In this paper, we study the emergence of topological interference alignment and the characterizing features of a multi-user broadcast interference relay channel. We propose an alternative transmission strategy named the relay space-time interference alignment (R-STIA) technique, in which a K -user multiple-input-multiple-output (MIMO) interference channel has massive antennas at the transmitter and relay. Severe interference from unknown transmitters affects the downlink relay network channel and degrades the system performance. An additional (unintended) receiver is introduced in the proposed R-STIA technique to overcome the above problem, since it has the ability to decode the desired signals for the intended receiver by considering cooperation between the receivers. The additional receiver also helps in recovering and reconstructing the interference signals with limited channel state information at the relay (CSIR). The Alamouti space-time transmission technique and minimum mean square error (MMSE) linear precoder are also used in the proposed scheme to detect the presence of interference signals. Numerical results show that the proposed R-STIA technique achieves a better performance in terms of the bit error rate (BER) and sum-rate compared to the existing broadcast channel schemes.

Topological Interference Management for K-User Downlink Massive MIMO Relay Network Channel

PubMed Central

Li, Jun; Lee, Moon Ho

2017-01-01

In this paper, we study the emergence of topological interference alignment and the characterizing features of a multi-user broadcast interference relay channel. We propose an alternative transmission strategy named the relay space-time interference alignment (R-STIA) technique, in which a K-user multiple-input-multiple-output (MIMO) interference channel has massive antennas at the transmitter and relay. Severe interference from unknown transmitters affects the downlink relay network channel and degrades the system performance. An additional (unintended) receiver is introduced in the proposed R-STIA technique to overcome the above problem, since it has the ability to decode the desired signals for the intended receiver by considering cooperation between the receivers. The additional receiver also helps in recovering and reconstructing the interference signals with limited channel state information at the relay (CSIR). The Alamouti space-time transmission technique and minimum mean square error (MMSE) linear precoder are also used in the proposed scheme to detect the presence of interference signals. Numerical results show that the proposed R-STIA technique achieves a better performance in terms of the bit error rate (BER) and sum-rate compared to the existing broadcast channel schemes. PMID:28817071

Color discrimination performance in patients with Alzheimer's disease.

PubMed

Salamone, Giovanna; Di Lorenzo, Concetta; Mosti, Serena; Lupo, Federica; Cravello, Luca; Palmer, Katie; Musicco, Massimo; Caltagirone, Carlo

2009-01-01

Visual deficits are frequent in Alzheimer's disease (AD), yet little is known about the nature of these disturbances. The aim of the present study was to investigate color discrimination in patients with AD to determine whether impairment of this visual function is a cognitive or perceptive/sensory disturbance. A cross-sectional clinical study was conducted in a specialized dementia unit on 20 patients with mild/moderate AD and 21 age-matched normal controls. Color discrimination was measured by the Farnsworth-Munsell 100 hue test. Cognitive functioning was measured with the Mini-Mental State Examination (MMSE) and a comprehensive battery of neuropsychological tests. The scores obtained on the color discrimination test were compared between AD patients and controls adjusting for global and domain-specific cognitive performance. Color discrimination performance was inversely related to MMSE score. AD patients had a higher number of errors in color discrimination than controls (mean +/- SD total error score: 442.4 +/- 84.5 vs. 304.1 +/- 45.9). This trend persisted even after adjustment for MMSE score and cognitive performance on specific cognitive domains. A specific reduction of color discrimination capacity is present in AD patients. This deficit does not solely depend upon cognitive impairment, and involvement of the primary visual cortex and/or retinal ganglionar cells may be contributory.

Diagnostic performance of short portable mental status questionnaire for screening dementia among patients attending cognitive assessment clinics in Singapore.

PubMed

Malhotra, Chetna; Chan, Angelique; Matchar, David; Seow, Dennis; Chuo, Adeline; Do, Young Kyung

2013-07-01

The Short Portable Mental Status Questionnaire (SPMSQ) is a brief cognitive screening instrument, which is easy to use by a healthcare worker with little training. However, the validity of this instrument has not been established in Singapore. Thus, the primary aim of this study was to determine the diagnostic performance of SPMSQ for screening dementia among patients attending outpatient cognitive assessment clinics and to assess whether the appropriate cut-off score varies by patient's age and education. A secondary aim of the study was to map the SPMSQ scores with Mini-Mental State Examination (MMSE) scores. SPMSQ and MMSE were administered by a trained interviewer to 127 patients visiting outpatient cognitive assessment clinics at the Singapore General Hospital, Changi General Hospital and Tan Tock Seng Hospital. The geriatricians at these clinics then diagnosed these patients with dementia or no dementia (reference standard). Sensitivity and specificity of SPMSQ with different cut-off points (number of errors) were calculated and compared to the reference standard using the Receiver Operator Characteristic (ROC) analysis. Correlation coefficient was also calculated between MMSE and SPMSQ scores. Based on the ROC analysis and a balance of sensitivity and specificity, the appropriate cut-off for SPMSQ was found to be 5 or more errors (sensitivity 78%, specificity 75%). The cut-off varied by education, but not by patient's age. There was a high correlation between SPMSQ and MMSE scores (r = 0.814, P <0.0001). Despite the advantage of being a brief screening instrument for dementia, the use of SPMSQ is limited by its low sensitivity and specificity, especially among patients with less than 6 years of education.

Handling missing Mini-Mental State Examination (MMSE) values: Results from a cross-sectional long-term-care study.

PubMed

Godin, Judith; Keefe, Janice; Andrew, Melissa K

2017-04-01

Missing values are commonly encountered on the Mini Mental State Examination (MMSE), particularly when administered to frail older people. This presents challenges for MMSE scoring in research settings. We sought to describe missingness in MMSEs administered in long-term-care facilities (LTCF) and to compare and contrast approaches to dealing with missing items. As part of the Care and Construction project in Nova Scotia, Canada, LTCF residents completed an MMSE. Different methods of dealing with missing values (e.g., use of raw scores, raw scores/number of items attempted, scale-level multiple imputation [MI], and blended approaches) are compared to item-level MI. The MMSE was administered to 320 residents living in 23 LTCF. The sample was predominately female (73%), and 38% of participants were aged >85 years. At least one item was missing from 122 (38.2%) of the MMSEs. Data were not Missing Completely at Random (MCAR), χ 2 (1110) = 1,351, p < 0.001. Using raw scores for those missing <6 items in combination with scale-level MI resulted in the regression coefficients and standard errors closest to item-level MI. Patterns of missing items often suggest systematic problems, such as trouble with manual dexterity, literacy, or visual impairment. While these observations may be relatively easy to take into account in clinical settings, non-random missingness presents challenges for research and must be considered in statistical analyses. We present suggestions for dealing with missing MMSE data based on the extent of missingness and the goal of analyses. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space.

PubMed

Huang, Jianyong; Qin, Lei; Peng, Xiaoling; Zhu, Tao; Xiong, Chunyang; Zhang, Youyi; Fang, Jing

2009-08-21

Quantitative estimation of cellular traction has significant physiological and clinical implications. As an inverse problem, traction force recovery is essentially susceptible to noise in the measured displacement data. For traditional procedure of Fourier transform traction cytometry (FTTC), noise amplification is accompanied in the force reconstruction and small tractions cannot be recovered from the displacement field with low signal-noise ratio (SNR). To improve the FTTC process, we develop an optimal filtering scheme to suppress the noise in the force reconstruction procedure. In the framework of the Wiener filtering theory, four filtering parameters are introduced in two-dimensional Fourier space and their analytical expressions are derived in terms of the minimum-mean-squared-error (MMSE) optimization criterion. The optimal filtering approach is validated with simulations and experimental data associated with the adhesion of single cardiac myocyte to elastic substrate. The results indicate that the proposed method can highly enhance SNR of the recovered forces to reveal tiny tractions in cell-substrate interaction.

Modeling the Atmospheric Phase Effects of a Digital Antenna Array Communications System

NASA Technical Reports Server (NTRS)

Tkacenko, A.

2006-01-01

In an antenna array system such as that used in the Deep Space Network (DSN) for satellite communication, it is often necessary to account for the effects due to the atmosphere. Typically, the atmosphere induces amplitude and phase fluctuations on the transmitted downlink signal that invalidate the assumed stationarity of the signal model. The degree to which these perturbations affect the stationarity of the model depends both on parameters of the atmosphere, including wind speed and turbulence strength, and on parameters of the communication system, such as the sampling rate used. In this article, we focus on modeling the atmospheric phase fluctuations in a digital antenna array communications system. Based on a continuous-time statistical model for the atmospheric phase effects, we show how to obtain a related discrete-time model based on sampling the continuous-time process. The effects of the nonstationarity of the resulting signal model are investigated using the sample matrix inversion (SMI) algorithm for minimum mean-squared error (MMSE) equalization of the received signal

An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT).

PubMed

Li, Ran; Duan, Xiaomeng; Li, Xu; He, Wei; Li, Yanling

2018-04-17

Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.

Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation

NASA Astrophysics Data System (ADS)

Sekhar, S. Chandra; Sreenivas, TV

2004-12-01

We address the problem of estimating instantaneous frequency (IF) of a real-valued constant amplitude time-varying sinusoid. Estimation of polynomial IF is formulated using the zero-crossings of the signal. We propose an algorithm to estimate nonpolynomial IF by local approximation using a low-order polynomial, over a short segment of the signal. This involves the choice of window length to minimize the mean square error (MSE). The optimal window length found by directly minimizing the MSE is a function of the higher-order derivatives of the IF which are not available a priori. However, an optimum solution is formulated using an adaptive window technique based on the concept of intersection of confidence intervals. The adaptive algorithm enables minimum MSE-IF (MMSE-IF) estimation without requiring a priori information about the IF. Simulation results show that the adaptive window zero-crossing-based IF estimation method is superior to fixed window methods and is also better than adaptive spectrogram and adaptive Wigner-Ville distribution (WVD)-based IF estimators for different signal-to-noise ratio (SNR).

Potential Seasonal Terrestrial Water Storage Monitoring from GPS Vertical Displacements: A Case Study in the Lower Three-Rivers Headwater Region, China.

PubMed

Zhang, Bao; Yao, Yibin; Fok, Hok Sum; Hu, Yufeng; Chen, Qiang

2016-09-19

This study uses the observed vertical displacements of Global Positioning System (GPS) time series obtained from the Crustal Movement Observation Network of China (CMONOC) with careful pre- and post-processing to estimate the seasonal crustal deformation in response to the hydrological loading in lower three-rivers headwater region of southwest China, followed by inferring the annual EWH changes through geodetic inversion methods. The Helmert Variance Component Estimation (HVCE) and the Minimum Mean Square Error (MMSE) criterion were successfully employed. The GPS inferred EWH changes agree well qualitatively with the Gravity Recovery and Climate Experiment (GRACE)-inferred and the Global Land Data Assimilation System (GLDAS)-inferred EWH changes, with a discrepancy of 3.2-3.9 cm and 4.8-5.2 cm, respectively. In the research areas, the EWH changes in the Lancang basin is larger than in the other regions, with a maximum of 21.8-24.7 cm and a minimum of 3.1-6.9 cm.

Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

NASA Astrophysics Data System (ADS)

Wang, Yunhua; DeBrunner, Linda; DeBrunner, Victor; Zhou, Dayong

2008-12-01

Tsatsanis and Xu have applied the constrained minimum output variance (CMOV) principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE) equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

Fusing Bluetooth Beacon Data with Wi-Fi Radiomaps for Improved Indoor Localization

PubMed Central

Kanaris, Loizos; Kokkinis, Akis; Liotta, Antonio; Stavrou, Stavros

2017-01-01

Indoor user localization and tracking are instrumental to a broad range of services and applications in the Internet of Things (IoT) and particularly in Body Sensor Networks (BSN) and Ambient Assisted Living (AAL) scenarios. Due to the widespread availability of IEEE 802.11, many localization platforms have been proposed, based on the Wi-Fi Received Signal Strength (RSS) indicator, using algorithms such as K-Nearest Neighbour (KNN), Maximum A Posteriori (MAP) and Minimum Mean Square Error (MMSE). In this paper, we introduce a hybrid method that combines the simplicity (and low cost) of Bluetooth Low Energy (BLE) and the popular 802.11 infrastructure, to improve the accuracy of indoor localization platforms. Building on KNN, we propose a new positioning algorithm (dubbed i-KNN) which is able to filter the initial fingerprint dataset (i.e., the radiomap), after considering the proximity of RSS fingerprints with respect to the BLE devices. In this way, i-KNN provides an optimised small subset of possible user locations, based on which it finally estimates the user position. The proposed methodology achieves fast positioning estimation due to the utilization of a fragment of the initial fingerprint dataset, while at the same time improves positioning accuracy by minimizing any calculation errors. PMID:28394268

Fusing Bluetooth Beacon Data with Wi-Fi Radiomaps for Improved Indoor Localization.

PubMed

Kanaris, Loizos; Kokkinis, Akis; Liotta, Antonio; Stavrou, Stavros

2017-04-10

Indoor user localization and tracking are instrumental to a broad range of services and applications in the Internet of Things (IoT) and particularly in Body Sensor Networks (BSN) and Ambient Assisted Living (AAL) scenarios. Due to the widespread availability of IEEE 802.11, many localization platforms have been proposed, based on the Wi-Fi Received Signal Strength (RSS) indicator, using algorithms such as K -Nearest Neighbour (KNN), Maximum A Posteriori (MAP) and Minimum Mean Square Error (MMSE). In this paper, we introduce a hybrid method that combines the simplicity (and low cost) of Bluetooth Low Energy (BLE) and the popular 802.11 infrastructure, to improve the accuracy of indoor localization platforms. Building on KNN, we propose a new positioning algorithm (dubbed i-KNN) which is able to filter the initial fingerprint dataset (i.e., the radiomap), after considering the proximity of RSS fingerprints with respect to the BLE devices. In this way, i-KNN provides an optimised small subset of possible user locations, based on which it finally estimates the user position. The proposed methodology achieves fast positioning estimation due to the utilization of a fragment of the initial fingerprint dataset, while at the same time improves positioning accuracy by minimizing any calculation errors.

Prediction of acoustic feature parameters using myoelectric signals.

PubMed

Lee, Ki-Seung

2010-07-01

It is well-known that a clear relationship exists between human voices and myoelectric signals (MESs) from the area of the speaker's mouth. In this study, we utilized this information to implement a speech synthesis scheme in which MES alone was used to predict the parameters characterizing the vocal-tract transfer function of specific speech signals. Several feature parameters derived from MES were investigated to find the optimal feature for maximization of the mutual information between the acoustic and the MES features. After the optimal feature was determined, an estimation rule for the acoustic parameters was proposed, based on a minimum mean square error (MMSE) criterion. In a preliminary study, 60 isolated words were used for both objective and subjective evaluations. The results showed that the average Euclidean distance between the original and predicted acoustic parameters was reduced by about 30% compared with the average Euclidean distance of the original parameters. The intelligibility of the synthesized speech signals using the predicted features was also evaluated. A word-level identification ratio of 65.5% and a syllable-level identification ratio of 73% were obtained through a listening test.

Potential Seasonal Terrestrial Water Storage Monitoring from GPS Vertical Displacements: A Case Study in the Lower Three-Rivers Headwater Region, China

PubMed Central

Zhang, Bao; Yao, Yibin; Fok, Hok Sum; Hu, Yufeng; Chen, Qiang

2016-01-01

This study uses the observed vertical displacements of Global Positioning System (GPS) time series obtained from the Crustal Movement Observation Network of China (CMONOC) with careful pre- and post-processing to estimate the seasonal crustal deformation in response to the hydrological loading in lower three-rivers headwater region of southwest China, followed by inferring the annual EWH changes through geodetic inversion methods. The Helmert Variance Component Estimation (HVCE) and the Minimum Mean Square Error (MMSE) criterion were successfully employed. The GPS inferred EWH changes agree well qualitatively with the Gravity Recovery and Climate Experiment (GRACE)-inferred and the Global Land Data Assimilation System (GLDAS)-inferred EWH changes, with a discrepancy of 3.2–3.9 cm and 4.8–5.2 cm, respectively. In the research areas, the EWH changes in the Lancang basin is larger than in the other regions, with a maximum of 21.8–24.7 cm and a minimum of 3.1–6.9 cm. PMID:27657064

Application of the clinical version of the narrow path walking test to identify elderly fallers.

PubMed

Gimmon, Yoav; Barash, Avi; Debi, Ronen; Snir, Yoram; Bar David, Yair; Grinshpon, Jacob; Melzer, Itshak

2016-01-01

Falling during walking is a common problem among the older population. Hence, the challenge facing clinicians is identifying who is at risk of falling during walking, for providing an effective intervention to reduce that risk. We aimed to assess whether the clinical version of the narrow path walking test (NPWT) could identify older adults who are reported falls. A total of 160 older adults were recruited and asked to recall fall events during the past year. Subjects were instructed to walk in the laboratory at a comfortable pace within a 6 meter long narrow path, 3 trials under single task (ST) and 3 trials dual task (DT) conditions without stepping outside the path (i.e., step errors). The average trial time, number of steps, trial velocity, number of step errors, and number of cognitive task errors were calculated for ST and DT. Fear of falling, performance oriented mobility assessment (POMA) and mini-metal state examination (MMSE) were measured as well. Sixty-one subjects reported that they had fallen during the past year and 99 did not. Fallers performed more steps, and were slower than non-fallers. There were no significant differences, however, in the number of steps errors, the cognitive task errors in ST and DT in POMA and MMSE. Our data demonstrates slower gait speed and more steps during the NPWT in ST and DT in fallers. There is no added value of DT over the ST for identification of faller's older adults. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Advanced diffraction-based overlay for double patterning

NASA Astrophysics Data System (ADS)

Li, Jie; Liu, Yongdong; Dasari, Prasad; Hu, Jiangtao; Smith, Nigel; Kritsun, Oleg; Volkman, Catherine

2010-03-01

Diffraction based overlay (DBO) technologies have been developed to address the tighter overlay control challenges as the dimensions of integrated circuit continue to shrink. Several studies published recently have demonstrated that the performance of DBO technologies has the potential to meet the overlay metrology budget for 22nm technology node. However, several hurdles must be cleared before DBO can be used in production. One of the major hurdles is that most DBO technologies require specially designed targets that consist of multiple measurement pads, which consume too much space and increase measurement time. A more advanced spectroscopic ellipsometry (SE) technology-Mueller Matrix SE (MM-SE) is developed to address the challenge. We use a double patterning sample to demonstrate the potential of MM-SE as a DBO candidate. Sample matrix (the matrix that describes the effects of the sample on the incident optical beam) obtained from MM-SE contains up to 16 elements. We show that the Mueller elements from the off-diagonal 2x2 blocks respond to overlay linearly and are zero when overlay errors are absent. This superior property enables empirical DBO (eDBO) using two pads per direction. Furthermore, the rich information in Mueller matrix and its direct response to overlay make it feasible to extract overlay errors from only one pad per direction using modeling approach (mDBO). We here present the Mueller overlay results using both eDBO and mDBO and compare the results with image-based overlay (IBO) and CD-SEM results. We also report the tool induced shifts (TIS) and dynamic repeatability.

Rigorous study of low-complexity adaptive space-time block-coded MIMO receivers in high-speed mode multiplexed fiber-optic transmission links using few-mode fibers

NASA Astrophysics Data System (ADS)

Weng, Yi; He, Xuan; Wang, Junyi; Pan, Zhongqi

2017-01-01

Spatial-division multiplexing (SDM) techniques have been purposed to increase the capacity of optical fiber transmission links by utilizing multicore fibers or few-mode fibers (FMF). The most challenging impairments of SDMbased long-haul optical links mainly include modal dispersion and mode-dependent loss (MDL), whereas MDL arises from inline component imperfections, and breaks modal orthogonality thus degrading the capacity of multiple-inputmultiple- output (MIMO) receivers. To reduce MDL, optical approaches include mode scramblers and specialty fiber designs, yet these methods were burdened with high cost, yet cannot completely remove the accumulated MDL in the link. Besides, space-time trellis codes (STTC) were purposed to lessen MDL, but suffered from high complexity. In this work, we investigated the performance of space-time block-coding (STBC) scheme to mitigate MDL in SDM-based optical communication by exploiting space and delay diversity, whereas weight matrices of frequency-domain equalization (FDE) were updated heuristically using decision-directed recursive-least-squares (RLS) algorithm for convergence and channel estimation. The STBC was evaluated in a six-mode multiplexed system over 30-km FMF via 6×6 MIMO FDE, with modal gain offset 3 dB, core refractive index 1.49, numerical aperture 0.5. Results show that optical-signal-to-noise ratio (OSNR) tolerance can be improved via STBC by approximately 3.1, 4.9, 7.8 dB for QPSK, 16- and 64-QAM with respective bit-error-rates (BER) and minimum-mean-square-error (MMSE). Besides, we also evaluate the complexity optimization of STBC decoding scheme with zero-forcing decision feedback (ZFDF) equalizer by shortening the coding slot length, which is robust to frequency-selective fading channels, and can be scaled up for SDM systems with more dynamic channels.

The advanced progress of precoding technology in 5g system

NASA Astrophysics Data System (ADS)

An, Chenyi

2017-09-01

With the development of technology, people began to put forward higher requirements for the mobile system, the emergence of the 5G subvert the track of the development of mobile communication technology. In the research of the core technology of 5G mobile communication, large scale MIMO, and precoding technology is a research hotspot. At present, the research on precoding technology in 5G system analyzes the various methods of linear precoding, the maximum ratio transmission (MRT) precoding algorithm, zero forcing (ZF) precoding algorithm, minimum mean square error (MMSE) precoding algorithm based on maximum signal to leakage and noise ratio (SLNR). Precoding algorithms are analyzed and summarized in detail. At the same time, we also do some research on nonlinear precoding methods, such as dirty paper precoding, THP precoding algorithm and so on. Through these analysis, we can find the advantages and disadvantages of each algorithm, as well as the development trend of each algorithm, grasp the development of the current 5G system precoding technology. Therefore, the research results and data of this paper can be used as reference for the development of precoding technology in 5G system.

A Space-Time Signal Decomposition Algorithm for Downlink MIMO DS-CDMA Receivers

NASA Astrophysics Data System (ADS)

Wang, Yung-Yi; Fang, Wen-Hsien; Chen, Jiunn-Tsair

We propose a dimension reduction algorithm for the receiver of the downlink of direct-sequence code-division multiple access (DS-CDMA) systems in which both the transmitters and the receivers employ antenna arrays of multiple elements. To estimate the high order channel parameters, we develop a layered architecture using dimension-reduced parameter estimation algorithms to estimate the frequency-selective multipath channels. In the proposed architecture, to exploit the space-time geometric characteristics of multipath channels, spatial beamformers and constrained (or unconstrained) temporal filters are adopted for clustered-multipath grouping and path isolation. In conjunction with the multiple access interference (MAI) suppression techniques, the proposed architecture jointly estimates the direction of arrivals, propagation delays, and fading amplitudes of the downlink fading multipaths. With the outputs of the proposed architecture, the signals of interest can then be naturally detected by using path-wise maximum ratio combining. Compared to the traditional techniques, such as the Joint-Angle-and-Delay-Estimation (JADE) algorithm for DOA-delay joint estimation and the space-time minimum mean square error (ST-MMSE) algorithm for signal detection, computer simulations show that the proposed algorithm substantially mitigate the computational complexity at the expense of only slight performance degradation.

A Framework of Covariance Projection on Constraint Manifold for Data Fusion.

PubMed

Bakr, Muhammad Abu; Lee, Sukhan

2018-05-17

A general framework of data fusion is presented based on projecting the probability distribution of true states and measurements around the predicted states and actual measurements onto the constraint manifold. The constraint manifold represents the constraints to be satisfied among true states and measurements, which is defined in the extended space with all the redundant sources of data such as state predictions and measurements considered as independent variables. By the general framework, we mean that it is able to fuse any correlated data sources while directly incorporating constraints and identifying inconsistent data without any prior information. The proposed method, referred to here as the Covariance Projection (CP) method, provides an unbiased and optimal solution in the sense of minimum mean square error (MMSE), if the projection is based on the minimum weighted distance on the constraint manifold. The proposed method not only offers a generalization of the conventional formula for handling constraints and data inconsistency, but also provides a new insight into data fusion in terms of a geometric-algebraic point of view. Simulation results are provided to show the effectiveness of the proposed method in handling constraints and data inconsistency.

Uplink transmit beamforming design for SINR maximization with full multiuser channel state information

NASA Astrophysics Data System (ADS)

Xi, Songnan; Zoltowski, Michael D.

2008-04-01

Multiuser multiple-input multiple-output (MIMO) systems are considered in this paper. We continue our research on uplink transmit beamforming design for multiple users under the assumption that the full multiuser channel state information, which is the collection of the channel state information between each of the users and the base station, is known not only to the receiver but also to all the transmitters. We propose an algorithm for designing optimal beamforming weights in terms of maximizing the signal-to-interference-plus-noise ratio (SINR). Through statistical modeling, we decouple the original mathematically intractable optimization problem and achieved a closed-form solution. As in our previous work, the minimum mean-squared error (MMSE) receiver with successive interference cancellation (SIC) is adopted for multiuser detection. The proposed scheme is compared with an existing jointly optimized transceiver design, referred to as the joint transceiver in this paper, and our previously proposed eigen-beamforming algorithm. Simulation results demonstrate that our algorithm, with much less computational burden, accomplishes almost the same performance as the joint transceiver for spatially independent MIMO channel and even better performance for spatially correlated MIMO channels. And it always works better than our previously proposed eigen beamforming algorithm.

Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

NASA Astrophysics Data System (ADS)

Azarpour, Masoumeh; Enzner, Gerald

2017-12-01

Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome reveals that the signals processed by the blocking-based algorithms are significantly preferred over the noisy signal in terms of instantaneous noise attenuation. Furthermore, the listening test data analysis confirms the conclusions drawn based on the objective evaluation.

Norms of the Mini-Mental state Examination for Japanese subjects that underwent comprehensive brain examinations: the Kashima Scan Study.

PubMed

Yakushiji, Yusuke; Horikawa, Etsuo; Eriguchi, Makoto; Nanri, Yusuke; Nishihara, Masashi; Hirotsu, Tatsumi; Hara, Hideo

2014-01-01

The distribution of the Mini-Mental State Examination (MMSE) scores by age and educational level was investigated in subjects that underwent comprehensive brain examinations. This cross-sectional study included 1,414 adults without neurological disorders who underwent health-screening tests of the brain, referred to as the "Brain Dock," in our center. The MMSE scores were compared between age groups (40-44, 45-49, 50-54, 55-59, 60-64, 65-69, or ≥70 years) and educational levels [the low education level group (6-12 years) and the high education level group (≥13 years)]. The median age was 59 years, and 763 (54%) were women. There was no significant difference in the MMSE total score between women and men. The stepwise method of the multiple linear regression analysis confirmed that a higher age [β value, -0.129; standard error (S.E.), 0.020; p<0.001], low education level (6-12 years) (β value, -0.226; S.E., 0.075; p=0.003), and women (β values, 0.148; S.E., 0.066; p=0.024) was significantly associated with decreased MMSE score. In general, both the percentile scores and mean scores decreased with aging and were lower in the low education level group than in the high education level group. The degree of decrement in scores with age was stronger in the low education level group than in the high education level group. The provided data for age- and education-specific reference norms will be useful for both clinicians and investigators who perform comprehensive brain examinations to assess the cognitive function of subjects.

Three screening methods for cognitive dysfunction using the Mini-Mental State Examination and Korean Dementia Screening Questionnaire.

PubMed

Choi, Seong Hye; Park, Moon Ho

2016-02-01

To screen for and determine cognitive dysfunction, cognitive tests and/or informant reports are commonly used. However, these cognitive tests and informant reports are not always available. The present study investigated three screening methods using the Mini-Mental State Examination (MMSE) as the cognitive test, and the Korean dementia screening questionnaire (KDSQ) as the informant report. Participants were recruited from the Korea Clinical Research Center for Dementia of South Korea, and included 2861 patients with Alzheimer's disease (dementia), 3519 patients with mild cognitive impairment and 1375 controls with no cognitive dysfunction. Three screening methods were tested: (i) MMSE alone (MMSE(cut-off) ); (ii) a conventional combination of MMSE and KDSQ (MMSE+KDSQ(cut-off) ); and (iii) a decision tree with MMSE and KDSQ (MMSE+KDSQ(decision tree) ). For discriminating any cognitive dysfunction from controls, MMSE+KDSQ(cut-off) had the highest area under the receiver operating characteristic curve (0.784). For discriminating dementia from controls, MMSE+KDSQ(cut-off) had the highest area under the receiver operating characteristic curve (0.899). For discriminating mild cognitive impairment from controls, MMSE(cut-off) had the highest area under the receiver operating characteristic curve (0.683). MMSE+KDSQ(decision tree) showed the highest sensitivity for all discriminations. For overall classification accuracy, MMSE+KDSQ(decision tree) had the highest value (70.0%). These three methods had different advantageous properties for screening and staging cognitive dysfunction. As there might be different availability across clinical settings, these three methods can be selected and used according to situational needs. © 2015 Japan Geriatrics Society.

Performance Evaluation of MIMO-UWB Systems Using Measured Propagation Data and Proposal of Timing Control Scheme in LOS Environments

NASA Astrophysics Data System (ADS)

Takanashi, Masaki; Nishimura, Toshihiko; Ogawa, Yasutaka; Ohgane, Takeo

Ultrawide-band impulse radio (UWB-IR) technology and multiple-input multiple-output (MIMO) systems have attracted interest regarding their use in next-generation high-speed radio communication. We have studied the use of MIMO ultrawide-band (MIMO-UWB) systems to enable higher-speed radio communication. We used frequency-domain equalization based on the minimum mean square error criterion (MMSE-FDE) to reduce intersymbol interference (ISI) and co-channel interference (CCI) in MIMO-UWB systems. Because UWB systems are expected to be used for short-range wireless communication, MIMO-UWB systems will usually operate in line-of-sight (LOS) environments and direct waves will be received at the receiver side. Direct waves have high power and cause high correlations between antennas in such environments. Thus, it is thought that direct waves will adversely affect the performance of spatial filtering and equalization techniques used to enhance signal detection. To examine the feasibility of MIMO-UWB systems, we conducted MIMO-UWB system propagation measurements in LOS environments. From the measurements, we found that the arrival time of direct waves from different transmitting antennas depends on the MIMO configuration. Because we can obtain high power from the direct waves, direct wave reception is critical for maximizing transmission performance. In this paper, we present our measurement results, and propose a way to improve performance using a method of transmit (Tx) and receive (Rx) timing control. We evaluate the bit error rate (BER) performance for this form of timing control using measured channel data.

The MMSE orientation for time domain is a strong predictor of subsequent cognitive decline in the elderly.

PubMed

Guerrero-Berroa, Elizabeth; Luo, Xiaodong; Schmeidler, James; Rapp, Michael A; Dahlman, Karen; Grossman, Hillel T; Haroutunian, Vahram; Beeri, Michal Schnaider

2009-12-01

The mini-mental state exam (MMSE) has been used to address questions such as determination of appropriate cutoff scores for differentiation of individuals with intact cognitive function from patients with dementia and rate of cognitive decline. However, little is known about the relationship of performance in specific cognitive domains to subsequent overall decline. To examine the specific and/or combined contribution of four MMSE domains (orientation for time, orientation for place, delayed recall, and attention) to prediction of overall cognitive decline on the MMSE. Linear mixed models were applied to 505 elderly nursing home residents (mean age = 85, > 12 years education = 27%; 79% F, mean follow-up = 3.20 years) to examine the relationship between baseline scores of these domains and total MMSE scores over time. Orientation for time was the only domain significantly associated with MMSE decline over time. Combination of poor delayed recall with either attention or orientation for place was associated with significantly increased decline on the MMSE. The MMSE orientation for time predicts overall decline on MMSE scores over time. A good functioning domain added to good functioning delayed recall was associated with slower rate of decline. Copyright (c) 2009 John Wiley & Sons, Ltd.

Using Least Squares for Error Propagation

ERIC Educational Resources Information Center

Tellinghuisen, Joel

2015-01-01

The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…

Clinical utility of the mini-mental status examination when assessing decision-making capacity.

PubMed

Pachet, Arlin; Astner, Kevin; Brown, Lenora

2010-03-01

The main objectives of this study were to examine the relationship between cognitive deficits, as measured by the Mini-Mental Status Examination (MMSE), and decision-making capacity and to determine whether the sensitivity and specificity of the MMSE varied based upon the patient population assessed. Using a sample size of 152 patients and varying cutoff scores, the MMSE demonstrated extremely poor sensitivity. In contrast, the MMSE had excellent specificity when scores of 19 or less were obtained. In our sample, not one patient, regardless of diagnosis, was deemed to have capacity if their MMSE score was below 20. However, reliance on the MMSE for scores above 19 would too frequently lead to misclassification and incorrect assumptions about a patient's decision-making abilities. Although a score below 20 consistently yielded findings of incapability in our sample, it remains our opinion that the MMSE should not be used as a stand-alone tool to make determinations related to capacity, especially when considering the complexities associated with capacity evaluations and the vital areas, such as executive functioning and individual values and beliefs, which are omitted by the MMSE.

Conversion of the Mini-Mental State Examination to the International Classification of Functioning, Disability and Health terminology and scoring system.

PubMed

De Vriendt, P; Gorus, E; Bautmans, I; Mets, T

2012-01-01

In older patients, evaluation of the cognitive status is crucial. The Mini-Mental State Examination (MMSE) is widely used for screening of cognition, providing fairly high sensitivity, specificity and reproducibility. Recently, a consensus emerged on the necessity of an international and transparent language, as provided by the WHO's International Classification of Functioning, Disability and Health (ICF). Most assessment tools however are not in accordance with the ICF. To reformulate the MMSE according to the ICF, both for the individual items and for the scoring system. MMSE data (scores varying from 3 to 30/30) of (1) 217 cognitively healthy elderly, (2) 60 persons with mild cognitive impairment, (3) 60 patients with mild Alzheimer's disease (AD), and (4) 60 patients with moderate/severe AD were obtained from studies at a university hospital setting. Subjects were aged 65 years or more and recruited either through advertisement (group 1), from the geriatric day hospital (groups 2 and 3), or the geriatric ward (group 4). The allocation to the groups was done after multidisciplinary evaluation. The conversion of the MMSE to ICF-MMSE was done by content comparison and by subsequent translation of the scoring system using automatic algorithms. All MMSE items were converted to the corresponding ICF categories. Three ICF domains were addressed: global and specific mental functions, general tasks and demands, divided over 6 ICF categories (orientation time/place, sustaining attention, memory functions, mental functions of language, undertaking a simple task). Scores on individual items were transformed according to their relative weight on the original MMSE scale, and a total ICF-MMSE score from 0 (no problem) to 100 (complete problem) was generated. Translation was satisfying, as illustrated by a good correlation between MMSE and ICF-MMSE. The diagnostic groups were distributed over the ICF-MMSE scores as expected. For each ICF domain, ICF-MMSE subscores were higher with increasing severity in cognitive decline. There was a higher dispersion, in accordance with the more detailed scoring possibilities of the ICF-MMSE. It is possible to adapt the MMSE to the ICF concept. This adaptation enhances interdisciplinary communication since it provides more clarity in assessment, with better visibility of the areas covered by the instrument. Copyright © 2011 S. Karger AG, Basel.

Increased Muscle Sympathetic Nerve Activity and Impaired Executive Performance Capacity in Obstructive Sleep Apnea.

PubMed

Goya, Thiago T; Silva, Rosyvaldo F; Guerra, Renan S; Lima, Marta F; Barbosa, Eline R F; Cunha, Paulo Jannuzzi; Lobo, Denise M L; Buchpiguel, Carlos A; Busatto-Filho, Geraldo; Negrão, Carlos E; Lorenzi-Filho, Geraldo; Ueno-Pardi, Linda M

2016-01-01

To investigate muscle sympathetic nerve activity (MSNA) response and executive performance during mental stress in obstructive sleep apnea (OSA). Individuals with no other comorbidities (age = 52 ± 1 y, body mass index = 29 ± 0.4, kg/m2) were divided into two groups: (1) control (n = 15) and (2) untreated OSA (n = 20) defined by polysomnography. Mini-Mental State of Examination (MMSE) and Inteligence quocient (IQ) were assessed. Heart rate (HR), blood pressure (BP), and MSNA (microneurography) were measured at baseline and during 3 min of the Stroop Color Word Test (SCWT). Sustained attention and inhibitory control were assessed by the number of correct answers and errors during SCWT. Control and OSA groups (apnea-hypopnea index, AHI = 8 ± 1 and 47 ± 1 events/h, respectively) were similar in age, MMSE, and IQ. Baseline HR and BP were similar and increased similarly during SCWT in control and OSA groups. In contrast, baseline MSNA was higher in OSA compared to controls. Moreover, MSNA significantly increased in the third minute of SCWT in OSA, but remained unchanged in controls (P < 0.05). The number of correct answers was lower and the number of errors was significantly higher during the second and third minutes of SCWT in the OSA group (P < 0.05). There was a significant correlation (P < 0.01) between the number of errors in the third minute of SCWT with AHI (r = 0.59), arousal index (r = 0.55), and minimum O2 saturation (r = -0.57). As compared to controls, MSNA is increased in patients with OSA at rest, and further significant MSNA increments and worse executive performance are seen during mental stress. URL: http://www.clinicaltrials.gov, registration number: NCT002289625. © 2016 Associated Professional Sleep Societies, LLC.

Demand Forecasting: An Evaluation of DODs Accuracy Metric and Navys Procedures

DTIC Science & Technology

2016-06-01

inventory management improvement plan, mean of absolute scaled error, lead time adjusted squared error, forecast accuracy, benchmarking, naïve method...Manager JASA Journal of the American Statistical Association LASE Lead-time Adjusted Squared Error LCI Life Cycle Indicator MA Moving Average MAE...Mean Squared Error xvi NAVSUP Naval Supply Systems Command NDAA National Defense Authorization Act NIIN National Individual Identification Number

Measurement System Characterization in the Presence of Measurement Errors

NASA Technical Reports Server (NTRS)

Commo, Sean A.

2012-01-01

In the calibration of a measurement system, data are collected in order to estimate a mathematical model between one or more factors of interest and a response. Ordinary least squares is a method employed to estimate the regression coefficients in the model. The method assumes that the factors are known without error; yet, it is implicitly known that the factors contain some uncertainty. In the literature, this uncertainty is known as measurement error. The measurement error affects both the estimates of the model coefficients and the prediction, or residual, errors. There are some methods, such as orthogonal least squares, that are employed in situations where measurement errors exist, but these methods do not directly incorporate the magnitude of the measurement errors. This research proposes a new method, known as modified least squares, that combines the principles of least squares with knowledge about the measurement errors. This knowledge is expressed in terms of the variance ratio - the ratio of response error variance to measurement error variance.

Reconstruction of elasticity: a stochastic model-based approach in ultrasound elastography

PubMed Central

2013-01-01

Background The convectional strain-based algorithm has been widely utilized in clinical practice. It can only provide the information of relative information of tissue stiffness. However, the exact information of tissue stiffness should be valuable for clinical diagnosis and treatment. Methods In this study we propose a reconstruction strategy to recover the mechanical properties of the tissue. After the discrepancies between the biomechanical model and data are modeled as the process noise, and the biomechanical model constraint is transformed into a state space representation the reconstruction of elasticity can be accomplished through one filtering identification process, which is to recursively estimate the material properties and kinematic functions from ultrasound data according to the minimum mean square error (MMSE) criteria. In the implementation of this model-based algorithm, the linear isotropic elasticity is adopted as the biomechanical constraint. The estimation of kinematic functions (i.e., the full displacement and velocity field), and the distribution of Young’s modulus are computed simultaneously through an extended Kalman filter (EKF). Results In the following experiments the accuracy and robustness of this filtering framework is first evaluated on synthetic data in controlled conditions, and the performance of this framework is then evaluated in the real data collected from elastography phantom and patients using the ultrasound system. Quantitative analysis verifies that strain fields estimated by our filtering strategy are more closer to the ground truth. The distribution of Young’s modulus is also well estimated. Further, the effects of measurement noise and process noise have been investigated as well. Conclusions The advantage of this model-based algorithm over the conventional strain-based algorithm is its potential of providing the distribution of elasticity under a proper biomechanical model constraint. We address the model-data discrepancy and measurement noise by introducing process noise and measurement noise in our framework, and then the absolute values of Young’s modulus are estimated through the EFK in the MMSE sense. However, the initial conditions, and the mesh strategy will affect the performance, i.e., the convergence rate, and computational cost, etc. PMID:23937814

Reconstruction of elasticity: a stochastic model-based approach in ultrasound elastography.

PubMed

Lu, Minhua; Zhang, Heye; Wang, Jun; Yuan, Jinwei; Hu, Zhenghui; Liu, Huafeng

2013-08-10

The convectional strain-based algorithm has been widely utilized in clinical practice. It can only provide the information of relative information of tissue stiffness. However, the exact information of tissue stiffness should be valuable for clinical diagnosis and treatment. In this study we propose a reconstruction strategy to recover the mechanical properties of the tissue. After the discrepancies between the biomechanical model and data are modeled as the process noise, and the biomechanical model constraint is transformed into a state space representation the reconstruction of elasticity can be accomplished through one filtering identification process, which is to recursively estimate the material properties and kinematic functions from ultrasound data according to the minimum mean square error (MMSE) criteria. In the implementation of this model-based algorithm, the linear isotropic elasticity is adopted as the biomechanical constraint. The estimation of kinematic functions (i.e., the full displacement and velocity field), and the distribution of Young's modulus are computed simultaneously through an extended Kalman filter (EKF). In the following experiments the accuracy and robustness of this filtering framework is first evaluated on synthetic data in controlled conditions, and the performance of this framework is then evaluated in the real data collected from elastography phantom and patients using the ultrasound system. Quantitative analysis verifies that strain fields estimated by our filtering strategy are more closer to the ground truth. The distribution of Young's modulus is also well estimated. Further, the effects of measurement noise and process noise have been investigated as well. The advantage of this model-based algorithm over the conventional strain-based algorithm is its potential of providing the distribution of elasticity under a proper biomechanical model constraint. We address the model-data discrepancy and measurement noise by introducing process noise and measurement noise in our framework, and then the absolute values of Young's modulus are estimated through the EFK in the MMSE sense. However, the initial conditions, and the mesh strategy will affect the performance, i.e., the convergence rate, and computational cost, etc.

[Cost relation between severity of Alzheimer's disease and cognitive and functional impairment].

PubMed

López-Pousa, Secundino; Garre-Olmo, Josep; Turon-Estrada, Antoni; Hernández, Francisco; Expósito, Inmaculada; Lozano-Gallego, Manoli; Hernández-Ferrándiz, Marta; Gelada-Batlle, Esther; Pericot-Nierga, Imma; Vilalta-Franch, Joan

2004-05-29

This study aims to identify the relationship between costs of medical and social attention in patients with dementia of Alzheimer disease (AD) type and clinical and sociodemographic data of patients and their caregivers. It was an analytic observational study in a cohort of patients diagnosed with Alzheimer's disease who received ambulatory attention. Information about the use of health-related resources was collected and costs were estimated from a societal perspective. Indirect costs were calculated using a replacement cost approach. Patients and caregivers were examined with the Mini-Mental State Examination (MMSE), the Rapid Disability Rating Scale (RDRS-2), the Neuropsychiatric Inventory (NPI), the Burden Interview (BI) and the Resource Utilization in Dementia (RUD). Patients were grouped taking into account the score obtained in the MMSE. A cohort of 417 patients, mean age (SD) 75.2 (6.6) years, 71% females, was studied. Disease severity levels were distributed as follows: MMSE, 26% for MMSE > 19, 66% for MMSE = 19-11, and 8% for MMSE < 11. 69% of caregivers were women, with a mean age of 57.1 (15.8) years. The cost per patient and per month was estimated to be 419.3 Euro for MMSE > 19, 641.9 Euro for MMSE = 19-11, and 1150.6 Euro for MMSE < 11. The societal cost of AD increases dramatically with increasing disease severity. Caregiver burden and sex as well as the marital status of patients are associated with the cost of the disease.

Two Enhancements of the Logarithmic Least-Squares Method for Analyzing Subjective Comparisons

DTIC Science & Technology

1989-03-25

error term. 1 For this model, the total sum of squares ( SSTO ), defined as n 2 SSTO = E (yi y) i=1 can be partitioned into error and regression sums...of the regression line around the mean value. Mathematically, for the model given by equation A.4, SSTO = SSE + SSR (A.6) A-4 where SSTO is the total...sum of squares (i.e., the variance of the yi’s), SSE is error sum of squares, and SSR is the regression sum of squares. SSTO , SSE, and SSR are given

Mini-Mental Status Examination: mixed Rasch model item analysis derived two different cognitive dimensions of the MMSE.

PubMed

Schultz-Larsen, Kirsten; Kreiner, Svend; Lomholt, Rikke Kirstine

2007-03-01

This study published in two companion papers assesses properties of the Mini-Mental State Examination (MMSE) with the purpose of improving the efficiencies of the methods of screening for cognitive impairment and dementia. An item analysis by conventional and mixed Rasch models was used to explore empirically derived cognitive dimensions of the MMSE, to assess item bias, and to construct diagnostic cut-points. The scores of 1,189 elderly residents were analyzed. Two dimensions of cognitive function, which are statistically and conceptually different from those obtained in previous studies, were derived. The corresponding sum scales were (1) age-correlated MMSE scale (A-MMSE scale: orientation to time, attention/calculation, naming, repetition, and three-stage command) and (2) non-age-correlated MMSE scale (B-MMSE scale: orientation to place, registration, recall, reading, and copying). The "writing" item was not included due to differential effects of age and sex. The analysis also showed that the study sample consisted of two cognitively different groups of elderly. The findings indicate that a two-scale solution is a stable and statistically supported framework for interpreting data obtained by means of the MMSE. Supplementary analyses are presented in the companion paper to explore the performance of this item response theory calibration as a screening test for dementia.

AKLSQF - LEAST SQUARES CURVE FITTING

NASA Technical Reports Server (NTRS)

Kantak, A. V.

1994-01-01

The Least Squares Curve Fitting program, AKLSQF, computes the polynomial which will least square fit uniformly spaced data easily and efficiently. The program allows the user to specify the tolerable least squares error in the fitting or allows the user to specify the polynomial degree. In both cases AKLSQF returns the polynomial and the actual least squares fit error incurred in the operation. The data may be supplied to the routine either by direct keyboard entry or via a file. AKLSQF produces the least squares polynomial in two steps. First, the data points are least squares fitted using the orthogonal factorial polynomials. The result is then reduced to a regular polynomial using Sterling numbers of the first kind. If an error tolerance is specified, the program starts with a polynomial of degree 1 and computes the least squares fit error. The degree of the polynomial used for fitting is then increased successively until the error criterion specified by the user is met. At every step the polynomial as well as the least squares fitting error is printed to the screen. In general, the program can produce a curve fitting up to a 100 degree polynomial. All computations in the program are carried out under Double Precision format for real numbers and under long integer format for integers to provide the maximum accuracy possible. AKLSQF was written for an IBM PC X/AT or compatible using Microsoft's Quick Basic compiler. It has been implemented under DOS 3.2.1 using 23K of RAM. AKLSQF was developed in 1989.

A Longitudinal Study of the Mini-Mental State Examination in Late Nonagenarians and Its Relationship with Dementia, Mortality, and Education.

PubMed

Skoog, Johan; Backman, Kristoffer; Ribbe, Mats; Falk, Hanna; Gudmundsson, Pia; Thorvaldsson, Valgeir; Borjesson-Hanson, Anne; Ostling, Svante; Johansson, Boo; Skoog, Ingmar

2017-06-01

To examine level of and change in cognitive status using the Mini-Mental State Examination (MMSE) in relation to dementia, mortality, education, and sex in late nonagenarians. Three-year longitudinal study with examinations at ages 97, 99, and 100. Trained psychiatric research nurses examined participants at their place of living. A representative population-based sample of 97-year-old Swedes (N = 591; 107 men, 484 women) living in Gothenburg, Sweden. A Swedish version of the MMSE was used to measure cognitive status. Geriatric psychiatrists diagnosed dementia according to the Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised. Mixed models were fitted to the data to model the longitudinal relationship between MMSE score and explanatory variables. Individuals with dementia between age 97 and 100 had lower mean MMSE scores than those without dementia. Those who died during the 3-year follow-up had lower MMSE scores than those who survived. MMSE scores at baseline did not differ between those without dementia and those who developed dementia during the 3-year follow-up. Participants with more education had higher MMSE scores, but there was no association between education and linear change. MMSE score is associated with dementia and subsequent mortality even in very old individuals, although the preclinical phase of dementia may be short in older age. Level of education is positively associated with MMSE score but not rate of decline in individuals approaching age 100. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

Study of Mini-Mental State Exam evolution in community-dwelling subjects aged over 60 years without dementia.

PubMed

Watfa, G; Husson, N; Buatois, S; Laurain, M C; Miget, P; Benetos, A

2011-12-01

In recent years, the Mini-Mental State Examination (MMSE) has been widely used and has been proposed for cognitive decline screening in the framework of a systematic geriatric evaluation in health centers. The aim of the present longitudinal study was to identify the potential determinants of MMSE score and its evolution over a 4-year period in a population aged over sixty years with good general health without dementia and consulting for a health check-up. Longitudinal study. The preventive medical center (CMP) in Nancy. 687 subjects over 60 years of age (mean age 65.6 ± 5.07 years) were included from the Senior health examination study. All subjects underwent 2 visits over a period of 4 years. MMSE measurement and a self-administered questionnaire of emotional and psychological state were evaluated at baseline and at the follow-up visit. The major components of total variance of baseline MMSE were represented by education level, practice of regular physical activity, nervousness and despair. Multivariate analysis identified 3 variables at baseline visit that independently predicted annual changes in MMSE: MMSE score, education level and "Difficulty in social relations" (r= -0.222, 0.154 and -0.255 respectively). Education level and several psychological factors may influence MMSE score and its evolution over time in community-dwelling subjects aged over 60 years without dementia. In these subjects, a low MMSE score does not predict cognitive decline over a period of 4 years. Therefore, the reliability of MMSE in this type of population is questionable.

Cognition and quality of life after chemotherapy plus radiotherapy (RT) vs. RT for pure and mixed anaplastic oligodendrogliomas: radiation therapy oncology group trial 9402.

PubMed

Wang, Meihua; Cairncross, Gregory; Shaw, Edward; Jenkins, Robert; Scheithauer, Bernd; Brachman, David; Buckner, Jan; Fink, Karen; Souhami, Luis; Laperriere, Normand; Mehta, Minesh; Curran, Walter

2010-07-01

Radiation Therapy Oncology Group 9402 compared procarbazine, lomustine, and vincristine (PCV) chemotherapy plus radiation therapy (PCV + RT) vs. RT alone for anaplastic oligodendroglioma. Here we report longitudinal changes in cognition and quality of life, effects of patient factors and treatments on cognition, quality of life and survival, and prognostic implications of cognition and quality of life. Cognition was assessed by Mini Mental Status Examination (MMSE) and quality of life by Brain-Quality of Life (B-QOL). Scores were analyzed for survivors and within 5 years of death. Shared parameter models evaluated MMSE/B-QOL with survival. For survivors, MMSE and B-QOL scores were similar longitudinally and between treatments. For those who died, MMSE scores remained stable initially, whereas B-QOL slowly declined; both declined rapidly in the last year of life and similarly between arms. In the aggregate, scores decreased over time (p = 0.0413 for MMSE; p = 0.0016 for B-QOL) and were superior with age <50 years (p < 0.001 for MMSE; p = 0.0554 for B-QOL) and Karnofsky Performance Score (KPS) 80-100 (p < 0.001). Younger age and higher KPS were associated with longer survival. After adjusting for patient factors and drop-out, survival was longer after PCV + RT (HR = 0.66, 95% CI = 0.49-0.9, p = 0.0084; HR = 0.74, 95% CI = 0.54-1.01, p = 0.0592) in models with MMSE and B-QOL. In addition, there were no differences in MMSE and B-QOL scores between arms (p = 0.4752 and p = 0.2767, respectively); higher scores predicted longer survival. MMSE and B-QOL scores held steady in the upper range in both arms for survivors. Younger, fitter patients had better MMSE and B-QOL and longer survival. (c) 2010 Elsevier Inc. All rights reserved.

Cognition and Quality of Life After Chemotherapy Plus Radiotherapy (RT) vs. RT for Pure and Mixed Anaplastic Oligodendrogliomas: Radiation Therapy Oncology Group Trial 9402

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

Wang Meihua, E-mail: mwang@phila.acr.or; Cairncross, Gregory; Shaw, Edward

2010-07-01

Purpose: Radiation Therapy Oncology Group 9402 compared procarbazine, lomustine, and vincristine (PCV) chemotherapy plus radiation therapy (PCV + RT) vs. RT alone for anaplastic oligodendroglioma. Here we report longitudinal changes in cognition and quality of life, effects of patient factors and treatments on cognition, quality of life and survival, and prognostic implications of cognition and quality of life. Methods and Materials: Cognition was assessed by Mini Mental Status Examination (MMSE) and quality of life by Brain-Quality of Life (B-QOL). Scores were analyzed for survivors and within 5 years of death. Shared parameter models evaluated MMSE/B-QOL with survival. Results: For survivors,more » MMSE and B-QOL scores were similar longitudinally and between treatments. For those who died, MMSE scores remained stable initially, whereas B-QOL slowly declined; both declined rapidly in the last year of life and similarly between arms. In the aggregate, scores decreased over time (p = 0.0413 for MMSE; p = 0.0016 for B-QOL) and were superior with age <50 years (p < 0.001 for MMSE; p = 0.0554 for B-QOL) and Karnofsky Performance Score (KPS) 80-100 (p < 0.001). Younger age and higher KPS were associated with longer survival. After adjusting for patient factors and drop-out, survival was longer after PCV + RT (HR = 0.66, 95% CI = 0.49-0.9, p = 0.0084; HR = 0.74, 95% CI = 0.54-1.01, p = 0.0592) in models with MMSE and B-QOL. In addition, there were no differences in MMSE and B-QOL scores between arms (p = 0.4752 and p = 0.2767, respectively); higher scores predicted longer survival. Conclusion: MMSE and B-QOL scores held steady in the upper range in both arms for survivors. Younger, fitter patients had better MMSE and B-QOL and longer survival.« less

Using the Folstein Mini Mental State Exam (MMSE) to explore methodological issues in cognitive aging research.

PubMed

Monroe, Todd; Carter, Michael

2012-09-01

Cognitive scales are used frequently in geriatric research and practice. These instruments are constructed with underlying assumptions that are a part of their validation process. A common measurement scale used in older adults is the Folstein Mini Mental State Exam (MMSE). The MMSE was designed to screen for cognitive impairment and is used often in geriatric research. This paper has three aims. Aim one was to explore four potential threats to validity in the use of the MMSE: (1) administering the exam without meeting the underlying assumptions, (2) not reporting that the underlying assumptions were assessed prior to test administration, (3) use of variable and inconsistent cut-off scores for the determination of presence of cognitive impairment, and (4) failure to adjust the scores based on the demographic characteristics of the tested subject. Aim two was to conduct a literature search to determine if the assumptions of (1) education level assessment, (2) sensory assessment, and (3) language fluency were being met and clearly reported in published research using the MMSE. Aim three was to provide recommendations to minimalize threats to validity in research studies that use cognitive scales, such as the MMSE. We found inconsistencies in published work in reporting whether or not subjects meet the assumptions that underlie a reliable and valid MMSE score. These inconsistencies can pose threats to the reliability of exam results. Fourteen of the 50 studies reviewed reported inclusion of all three of these assumptions. Inconsistencies in reporting the inclusion of the underlying assumptions for a reliable score could mean that subjects were not appropriate to be tested by use of the MMSE or that an appropriate test administration of the MMSE was not clearly reported. Thus, the research literature could have threats to both validity and reliability based on misuse of or improper reported use of the MMSE. Six recommendations are provided to minimalize these threats in future research.

An analysis of the least-squares problem for the DSN systematic pointing error model

NASA Technical Reports Server (NTRS)

Alvarez, L. S.

1991-01-01

A systematic pointing error model is used to calibrate antennas in the Deep Space Network. The least squares problem is described and analyzed along with the solution methods used to determine the model's parameters. Specifically studied are the rank degeneracy problems resulting from beam pointing error measurement sets that incorporate inadequate sky coverage. A least squares parameter subset selection method is described and its applicability to the systematic error modeling process is demonstrated on Voyager 2 measurement distribution.

[Performance of an abbreviated mini mental examination to detect dementia in older people].

PubMed

Jiménez, Daniel; Lavados, Manuel; Rojas, Paula; Henríquez, Claudio; Silva, Fernando; Guillón, Marta

2017-07-01

The usefulness of the abbreviated Mini-Mental State Examination included in the Chilean Functional assessment of elderly people (MM-SE-EFAM) to detect Dementia has not been determined. To assess the performance of the MMSE-EFAM to detect dementia. We studied a non-probabilistic sample of subjects older than 65 years who had been assessed by the MMSE-EFAM in a Chilean primary care center during a period of 6 months. Patients underwent clinical evaluation by a neurologist blinded to MMSE-EFAM score, to establish the diagnosis of dementia using DSM-IV-TR criteria. Besides, the full Mini-Mental State Examination (MMSE) was applied. The clinical diagnosis of Dementia was established in 13 of the 54 peoples evaluated. MMSE-EFAM had a sensitivity of 30.8% (95% confidence intervals (CI); 9-61.4) and a specificity of 90.2% (95% CI; 76.9%-97.3%), while MMSE had a sensitivity of 84.6% (95% CI; 54.6-98.1) and a specificity of 58.5% (95% CI; 42.1-73.7). In a receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) were 0.77 (95% CI; 0.61-0.93) and 0.82 (95% CI; 0.70-0.95) for MMSE-EFAM and MMSE, respectively. Socio-demographic variables did not influence test performance in both cases. MMSE-EFAM has a low sensitivity to detect patients with Dementia and it is not an effective screening tool. These results are in agreement with the evidence and international guidelines that do not support the use of cognitive screening tools to detect dementia in the older general population.

Response Surface Analysis of Experiments with Random Blocks

DTIC Science & Technology

1988-09-01

partitioned into a lack of fit sum of squares, SSLOF, and a pure error sum of squares, SSPE . The latter is obtained by pooling the pure error sums of squares...from the blocks. Tests concerning the polynomial effects can then proceed using SSPE as the error term in the denominators of the F test statistics. 3.2...the center point in each of the three blocks is equal to SSPE = 2.0127 with 5 degrees of freedom. Hence, the lack of fit sum of squares is SSLoF

Least-Squares Curve-Fitting Program

NASA Technical Reports Server (NTRS)

Kantak, Anil V.

1990-01-01

Least Squares Curve Fitting program, AKLSQF, easily and efficiently computes polynomial providing least-squares best fit to uniformly spaced data. Enables user to specify tolerable least-squares error in fit or degree of polynomial. AKLSQF returns polynomial and actual least-squares-fit error incurred in operation. Data supplied to routine either by direct keyboard entry or via file. Written for an IBM PC X/AT or compatible using Microsoft's Quick Basic compiler.

Cognitive performance on the mini-mental state examination and the montreal cognitive assessment across the healthy adult lifespan.

PubMed

Gluhm, Shea; Goldstein, Jody; Loc, Kiet; Colt, Alexandra; Liew, Charles Van; Corey-Bloom, Jody

2013-03-01

We sought to compare age-related performance on the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) across the adult lifespan in an asymptomatic, presumably normal, sample. The MMSE is the most commonly used brief cognitive screening test; however, the MoCA may be better at detecting early cognitive dysfunction. We gave the MMSE and MoCA to 254 community-dwelling participants ranging in age from 20 to 89, stratified by decade, and we compared their scores using the Wilcoxon signed rank test. For the total sample, the MMSE and MoCA differed significantly in total scores as well as in visuospatial, language, and memory domains (for all of these scores, P<0.001). Mean MMSE scores declined only modestly across the decades; mean MoCA scores declined more dramatically. There were no consistent domain differences between the MMSE and MoCA during the third and fourth decades; however, significant differences in memory (P<0.05) and language (P<0.001) emerged in the fifth through ninth decades. We conclude that the MoCA may be a better detector of age-related decrements in cognitive performance than the MMSE, as shown in this community-dwelling adult population.

Optical scatterometry of quarter-micron patterns using neural regression

NASA Astrophysics Data System (ADS)

Bischoff, Joerg; Bauer, Joachim J.; Haak, Ulrich; Hutschenreuther, Lutz; Truckenbrodt, Horst

1998-06-01

With shrinking dimensions and increasing chip areas, a rapid and non-destructive full wafer characterization after every patterning cycle is an inevitable necessity. In former publications it was shown that Optical Scatterometry (OS) has the potential to push the attainable feature limits of optical techniques from 0.8 . . . 0.5 microns for imaging methods down to 0.1 micron and below. Thus the demands of future metrology can be met. Basically being a nonimaging method, OS combines light scatter (or diffraction) measurements with modern data analysis schemes to solve the inverse scatter issue. For very fine patterns with lambda-to-pitch ratios grater than one, the specular reflected light versus the incidence angle is recorded. Usually, the data analysis comprises two steps -- a training cycle connected the a rigorous forward modeling and the prediction itself. Until now, two data analysis schemes are usually applied -- the multivariate regression based Partial Least Squares method (PLS) and a look-up-table technique which is also referred to as Minimum Mean Square Error approach (MMSE). Both methods are afflicted with serious drawbacks. On the one hand, the prediction accuracy of multivariate regression schemes degrades with larger parameter ranges due to the linearization properties of the method. On the other hand, look-up-table methods are rather time consuming during prediction thus prolonging the processing time and reducing the throughput. An alternate method is an Artificial Neural Network (ANN) based regression which combines the advantages of multivariate regression and MMSE. Due to the versatility of a neural network, not only can its structure be adapted more properly to the scatter problem, but also the nonlinearity of the neuronal transfer functions mimic the nonlinear behavior of optical diffraction processes more adequately. In spite of these pleasant properties, the prediction speed of ANN regression is comparable with that of the PLS-method. In this paper, the viability and performance of ANN-regression will be demonstrated with the example of sub-quarter-micron resist metrology. To this end, 0.25 micrometer line/space patterns have been printed in positive photoresist by means of DUV projection lithography. In order to evaluate the total metrology chain from light scatter measurement through data analysis, a thorough modeling has been performed. Assuming a trapezoidal shape of the developed resist profile, a training data set was generated by means of the Rigorous Coupled Wave Approach (RCWA). After training the model, a second data set was computed and deteriorated by Gaussian noise to imitate real measuring conditions. Then, these data have been fed into the models established before resulting in a Standard Error of Prediction (SEP) which corresponds to the measuring accuracy. Even with putting only little effort in the design of a back-propagation network, the ANN is clearly superior to the PLS-method. Depending on whether a network with one or two hidden layers was used, accuracy gains between 2 and 5 can be achieved compared with PLS regression. Furthermore, the ANN is less noise sensitive, for there is only a doubling of the SEP at 5% noise for ANN whereas for PLS the accuracy degrades rapidly with increasing noise. The accuracy gain also depends on the light polarization and on the measured parameters. Finally, these results have been proven experimentally, where the OS-results are in good accordance with the profiles obtained from cross- sectioning micrographs.

Use of the MC-FAQ and MMSE-FAQ in cognitive screening of older African Americans, Hispanic Americans, and European Americans.

PubMed

Tappen, Ruth M; Rosselli, Monica; Engstrom, Gabriella

2012-11-01

The purpose of this study was to examine the performance of the Mini-Cog-Functional Activities Questionnaire (MC-FAQ) and the Mini-Mental State Examination-Functional Activities Questionnaire (MMSE-FAQ) in cognitive screening of a multiethnic sample of older adults. This is a descriptive psychometric study. Cognitive screening was done in senior centers, at health fairs, and within the nine participating memory disorder centers in the State of Florida. African American, Hispanic American, and European American older adults who participated in this screening were matched on gender, age within 3 years and education within 3 years yielding a sample of 225. The MC-FAQ is a combination of the Mini-Cog and Functional Activities Questionnaire. The MMSE-FAQ combines the MMSE with the FAQ. The Geriatric Depression Scale was used to assess depressive symptoms. African Americans reported significantly less depressive symptoms (F[2, 217] = 10.31, p <0.001) and European Americans had significantly higher mean MMSE scores than the other two groups (F[2, 222] = 3.33, p = 0.037). Participants did not differ by ethnic group on the MC-FAQ or MMSE-FAQ classifications of normal, mild cognitive impairment, or dementia. Age, years of education, and depressive symptoms were significant predictors of MC-FAQ and MMSE-FAQ classifications. The results suggest that these combinations of screening measures may have less culture bias than the MMSE alone. Sensitivity and specificity should be evaluated in these groups with confirmatory neurological and psychiatric diagnosis. 2012 American Association for Geriatric Psychiatry

Cognitive Evolution by MMSE in Poststroke Patients

ERIC Educational Resources Information Center

da Costa, Fabricia Azevedo

2010-01-01

The aim of this study was to investigate the cognitive and clinical evolution of post-acute stroke patients and the evolution of each Mini-Mental State Examination (MMSE) item. A longitudinal study was conducted with 42 poststroke individuals in rehabilitation. The MMSE and the National Institutes of Health Stroke Scale were used to assess…

Coordinated Analysis of Age, Sex, and Education Effects on Change in MMSE Scores

PubMed Central

2013-01-01

Objectives. We describe and compare the expected performance trajectories of older adults on the Mini-Mental Status Examination (MMSE) across six independent studies from four countries in the context of a collaborative network of longitudinal studies of aging. A coordinated analysis approach is used to compare patterns of change conditional on sample composition differences related to age, sex, and education. Such coordination accelerates evaluation of particular hypotheses. In particular, we focus on the effect of educational attainment on cognitive decline. Method. Regular and Tobit mixed models were fit to MMSE scores from each study separately. The effects of age, sex, and education were examined based on more than one centering point. Results. Findings were relatively consistent across studies. On average, MMSE scores were lower for older individuals and declined over time. Education predicted MMSE score, but, with two exceptions, was not associated with decline in MMSE over time. Conclusion. A straightforward association between educational attainment and rate of cognitive decline was not supported. Thoughtful consideration is needed when synthesizing evidence across studies, as methodologies adopted and sample characteristics, such as educational attainment, invariably differ. PMID:23033357

Coordinated analysis of age, sex, and education effects on change in MMSE scores.

PubMed

Piccinin, Andrea M; Muniz-Terrera, Graciela; Clouston, Sean; Reynolds, Chandra A; Thorvaldsson, Valgeir; Deary, Ian J; Deeg, Dorly J H; Johansson, Boo; Mackinnon, Andrew; Spiro, Avron; Starr, John M; Skoog, Ingmar; Hofer, Scott M

2013-05-01

We describe and compare the expected performance trajectories of older adults on the Mini-Mental Status Examination (MMSE) across six independent studies from four countries in the context of a collaborative network of longitudinal studies of aging. A coordinated analysis approach is used to compare patterns of change conditional on sample composition differences related to age, sex, and education. Such coordination accelerates evaluation of particular hypotheses. In particular, we focus on the effect of educational attainment on cognitive decline. Regular and Tobit mixed models were fit to MMSE scores from each study separately. The effects of age, sex, and education were examined based on more than one centering point. Findings were relatively consistent across studies. On average, MMSE scores were lower for older individuals and declined over time. Education predicted MMSE score, but, with two exceptions, was not associated with decline in MMSE over time. A straightforward association between educational attainment and rate of cognitive decline was not supported. Thoughtful consideration is needed when synthesizing evidence across studies, as methodologies adopted and sample characteristics, such as educational attainment, invariably differ.

Error propagation of partial least squares for parameters optimization in NIR modeling.

PubMed

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

Error propagation of partial least squares for parameters optimization in NIR modeling

NASA Astrophysics Data System (ADS)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

[Effects of COPD on cognitive functions: a case control study].

PubMed

Sarınç Ulaşlı, Sevinç; Oruç, Serdar; Günay, Ersin; Aktaş, Orçun; Akar, Olcay; Koyuncu, Tülay; Ünlü, Mehmet

2013-01-01

Assessment of disease severity, effects of disease on health status and future events should be considered to direct treatment strategies in chronic obstructive pulmonary disease (COPD) management. Although extrapulmonary effects of COPD are well known, effects of COPD on cognitive functions have not been evaluated sufficiently. therefore we aimed to determine cognitive functions of copd patients in the present study. 112 COPD patients with moderate, severe and very severe irreversible airway obstruction and 44 age matched healthy subjects without COPD and systemic diseases as control group were enrolled to the study. Mini mental state examination (MMSE) was performed to evaluate cognitive functions. MMSE results were compared between patient and control groups. Moreover relationship between exacerbation frequency and cognitive functions was evaluated. Total 156 subjects as 112 COPD patients and 44 healthy subjects were included to the study. Mean age of COPD patients was 65.03 ± 7.63 years, and mean age of control group was 63.63 ± 8.96 years (p= 0.364). Mean score of MMSE in COPD patients was 23.8 ± 4.39, and mean score of MMSE in control group was 26.7 ± 2.88. We determined a significant difference in terms of MMSE scores betweeen patient and control group (p< 0.0001). MMSE scores and FEV1 values were significantly different among patients with moderate, sevre and very severe airflow obstruction (p= 0.001; p< 0.0001 respectively). We found a significant negative correlation between MMSE results and exacerbation frequency during last year (p= 0.003; r= -0.239). Lower MMSE scores of COPD patients than subjects in control group indicates the impairment of cognitive functions in COPD patients. Moreover a negative relationship between MMSE scores with exacerbation frequency during last year suggests that prevention from exacerbation can decrease cognitive impairment in COPD patients. We believe that assessment of cognitive functions and preventive strategies should be considered in COPD management.

Role of physical activity in reducing cognitive decline in older Mexican-American adults.

PubMed

Ottenbacher, Allison J; Snih, Soham Al; Bindawas, Saad M; Markides, Kyriakos S; Graham, James E; Samper-Ternent, Rafael; Raji, Mukaila; Ottenbacher, Kenneth J

2014-09-01

The effect of physical activity on cognitive function in older adults from minority and disadvantaged populations is not well understood. This study examined the longitudinal association between physical activity and cognition in older Mexican Americans. The study methodology included a prospective cohort with longitudinal analysis of data from the Hispanic Established Populations for the Epidemiologic Study of the Elderly. General linear mixed models were used to assess the associations and interactions between physical activity and cognitive function over 14 years. Community-based assessments were performed in participants' homes. Physical activity was recorded for 1,669 older Mexican Americans using the Physical Activity Scale for the Elderly. Cognition was measured using the Mini-Mental State Examination (MMSE) and separated into memory and nonmemory components. A statistically significant positive association was observed between levels of physical activity and cognitive function after adjusting for age, sex, marital status, education, and comorbid health conditions. There was a statistically significant difference in MMSE scores over time between participants in the third (β = 0.11, standard error (SE) = 0.05) and fourth (β = 0.10, SE = 0.2) quartiles of physical activity and those in the first. The protective effect of physical activity on cognitive decline was evident for the memory component of the MMSE but not the nonmemory component after adjusting for covariates. Greater physical activity at baseline was associated with less cognitive decline over 14 years in older Mexican Americans. The reduction in cognitive decline appeared to be related to the memory components of cognitive function. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

Discordance between net analyte signal theory and practical multivariate calibration.

PubMed

Brown, Christopher D

2004-08-01

Lorber's concept of net analyte signal is reviewed in the context of classical and inverse least-squares approaches to multivariate calibration. It is shown that, in the presence of device measurement error, the classical and inverse calibration procedures have radically different theoretical prediction objectives, and the assertion that the popular inverse least-squares procedures (including partial least squares, principal components regression) approximate Lorber's net analyte signal vector in the limit is disproved. Exact theoretical expressions for the prediction error bias, variance, and mean-squared error are given under general measurement error conditions, which reinforce the very discrepant behavior between these two predictive approaches, and Lorber's net analyte signal theory. Implications for multivariate figures of merit and numerous recently proposed preprocessing treatments involving orthogonal projections are also discussed.

Do subjective memory complaints predict senile Alzheimer dementia?

PubMed

Jungwirth, Susanne; Zehetmayer, Sonja; Weissgram, Silvia; Weber, Germain; Tragl, Karl Heinz; Fischer, Peter

2008-01-01

Many elderly complain about their memory and undergo dementia screening by the Mini-Mental State Examination (MMSE). While objective memory impairment always precedes Alzheimer dementia (AD) it is unclear whether subjective memory complaints are predicting AD. We tried to answer this question in a prospective cohort study. The 75-years old non-demented inhabitants of Vienna-Transdanube were investigated for conversion to AD after 30 months. The predictive value of subjective memory complaints was analysed in two groups: subjects with high MMSE-score (28-30) and subjects with low MMSE-score (23-27). Only in subjects with high MMSE univariate analyses showed an association between subjective memory complaints and incident AD. In both groups the verbal memory test was the main predictor of AD in multivariate analyses. We suggest to perform memory testing in subjects complaining about memory irrespective of their performance in a screening procedure like the MMSE.

[Using the MMSE as a cognitive screener among Turkish and Moroccan migrants].

PubMed

Zwart, L A R; Goudsmit, M; van Campen, J P C M; Rijkers, C J M; Wind, A W

2015-02-01

The Dutch population of first generation Turkish and Moroccan migrants is ageing. Among them hypertension and diabetes mellitus are frequent findings, which will probably cause an increased incidence of dementia. The language barrier, low education and cultural differences make the diagnosis more difficult. To what extent the MMSE can be used as a cognitive screener in this population will be investigated in this retrospective study.Patients received standard diagnostics, a professional translator addressed the language barrier. Correspondence was scored on characteristics of dementia, a procedure was used to diagnose without including the MMSE score. The optimal cut-off was calculated with the Youden Index and Area under the ROC (AUROC).106 patients were included, 61% had no education. Average MMSE-score was 16, with dementia 12, without 19. The AUROC was 0.85, optimal cut-off was 18 with a Youden index of 0.61.By using a professional translator the MMSE can possibly be used as a cognitive screener in this population. However, the cognitive skills addressed by the MMSE require an education and language skills. Developing a test that is independent of education and language barrier will probably be better.

Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults.

PubMed

Trzepacz, Paula T; Hochstetler, Helen; Wang, Shufang; Walker, Brett; Saykin, Andrew J

2015-09-07

The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores. For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases. Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥ 17 on MoCA (96.3%) and ≥ 24 on MMSE (98.3%). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1%) versus MMSE (71.4%). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3%) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC. MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥ 17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥ 18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

Using the Oxford Cognitive Screen to Detect Cognitive Impairment in Stroke Patients: A Comparison with the Mini-Mental State Examination.

PubMed

Mancuso, Mauro; Demeyere, Nele; Abbruzzese, Laura; Damora, Alessio; Varalta, Valentina; Pirrotta, Fabio; Antonucci, Gabriella; Matano, Alessandro; Caputo, Marina; Caruso, Maria Giovanna; Pontiggia, Giovanna Teresa; Coccia, Michela; Ciancarelli, Irene; Zoccolotti, Pierluigi

2018-01-01

The Oxford Cognitive Screen (OCS) was recently developed with the aim of describing the cognitive deficits after stroke. The scale consists of 10 tasks encompassing five cognitive domains: attention and executive function, language, memory, number processing, and praxis. OCS was devised to be inclusive and un-confounded by aphasia and neglect. As such, it may have a greater potential to be informative on stroke cognitive deficits of widely used instruments, such as the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment, which were originally devised for demented patients. The present study compared the OCS with the MMSE with regards to their ability to detect cognitive impairments post-stroke. We further aimed to examine performance on the OCS as a function of subtypes of cerebral infarction and clinical severity. 325 first stroke patients were consecutively enrolled in the study over a 9-month period. The OCS and MMSE, as well as the Bamford classification and NIHSS, were given according to standard procedures. About a third of patients (35.3%) had a performance lower than the cutoff (<22) on the MMSE, whereas 91.6% were impaired in at least one OCS domain, indicating higher incidences of impairment for the OCS. More than 80% of patients showed an impairment in two or more cognitive domains of the OCS. Using the MMSE as a standard of clinical practice, the comparative sensitivity of OCS was 100%. Out of the 208 patients with normal MMSE performance 180 showed impaired performance in at least one domain of the OCS. The discrepancy between OCS and MMSE was particularly strong for patients with milder strokes. As for subtypes of cerebral infarction, fewer patients demonstrated widespread impairments in the OCS in the Posterior Circulation Infarcts category than in the other categories. Overall, the results showed a much higher incidence of cognitive impairment with the OCS than with the MMSE and demonstrated no false negatives for OCS vs MMSE. It is concluded that OCS is a sensitive screen tool for cognitive deficits after stroke. In particular, the OCS detects high incidences of stroke-specific cognitive impairments, not detected by the MMSE, demonstrating the importance of cognitive profiling.

People with Parkinson Disease and Normal MMSE Score Have a Broad Range of Cognitive Performance

PubMed Central

Burdick, DJ; Cholerton, B; Watson, GS; Siderowf, A; Trojanowski, JQ; Weintraub, D; Ritz, B; Rhodes, SL; Rausch, R; Factor, SA; Wood-Siverio, C; Quinn, JF; Chung, KA; Srivatsal, S; Edwards, KL; Montine, TJ; Zabetian, CP; Leverenz, JB

2014-01-01

Background Cognitive impairment, including dementia, is common in Parkinson disease (PD). The Mini-Mental State Examination (MMSE) has been recommended as a screening tool for PDD, with values below 26 indicative of possible dementia. Using a detailed neuropsychological battery, we examined the range of cognitive impairment in PD patients with a MMSE score ≥ 26. Methods In this multi-center, cross-sectional, observational study, we performed neuropsychological testing in a sample of 788 PD patients with MMSE ≥ 26. Evaluation included tests of global cognition, executive function, language, memory, and visuospatial skills. A consensus panel reviewed results for 342 subjects and assigned a diagnosis of no cognitive impairment, mild cognitive impairment, or dementia. Results 67% of the 788 subjects performed 1.5 standard deviations below the normative mean on at least one test. On eight of the 15 tests, more than 20% of subjects scored 1.5 standard deviations or more below the normative mean. Greatest impairments were found on Hopkins Verbal Learning and Digit Symbol Coding tests. The sensitivity of the MMSE to detect dementia was 45% in a subset of participants who underwent clinical diagnostic procedures. Conclusions A remarkably wide range of cognitive impairment can be found in PD patients with a relatively high score on the MMSE, including a level of cognitive impairment consistent with dementia. Given these findings, clinicians must be aware of the limitations of the MMSE in detecting cognitive impairment, including dementia, in PD. PMID:25073717

Predictors of Cognitive and Functional Decline in Patients With Alzheimer Disease Dementia From Brazil.

PubMed

Oliveira, Fabricio F; Chen, Elizabeth S; Smith, Marilia C; Bertolucci, Paulo H F

2016-01-01

Little is known on how risk factors for Alzheimer disease (AD) dementia affect disease progression, much less for populations with low mean schooling, whereas the transcription of APOE may be regulated by nongenetic factors. In this 44-month cohort study, 214 consecutive outpatients with late-onset AD were assessed for rates of cognitive and functional decline by way of Clinical Dementia Rating and Mini-Mental State Examination (MMSE) scores, keeping blinded assessment of APOE haplotypes. Subjects were evaluated for sex, schooling, age of dementia onset, and cerebrovascular risk factors (including Framingham risk scores). Of the 214 patients, there were 146 (68.2%) women and 113 (52.8%) APOE4+ carriers. The mean age of AD onset was 73.4±6.5 years-old, negatively correlated with time to Clinical Dementia Rating >1.0 (β=-0.132; ρ<0.001), MMSE=20 (β=-0.105; ρ<0.001), and MMSE=15 (β=-0.124; ρ=0.003), more significantly for women and APOE4+ carriers. Mean schooling was 4.18±3.7 years, correlated with time to MMSE=20 and MMSE=15 for women and APOE4+ carriers. Body mass index was correlated with time to MMSE=20 only for men (ρ=0.006). The 10-year coronary heart disease risk was correlated with time to MMSE=20 only for APOE4+ carriers (ρ=0.015). These outcomes suggest interactions among genomic effects of cognitive reserve, cerebral perfusion, and hormonal changes over mechanisms of neurodegeneration.

Physical activity and cognition in the northern Manhattan study.

PubMed

Willey, Joshua Z; Park Moon, Yeseon; Ruder, Rachel; Cheung, Yuen K; Sacco, Ralph L; Elkind, Mitchell S V; Wright, Clinton B

2014-01-01

To test the hypothesis that leisure time physical activity (PA) is associated with cognitive status. We assessed cognition using the Mini-Mental Status Examination (MMSE) at enrollment and using the modified Telephone Interview for Cognitive Status (TICS-m) administered annually since 2001 in the Northern Manhattan Study. Baseline measures of leisure time PA were collected via in-person questionnaires. Total PA was categorized into 3 groups based on the metabolic equivalent (MET) score, a composite of total reported intensity and time. We used linear regression models to examine the association of PA with MMSE, and generalized estimating equations for change in TICS-m over time. There were 3,298 stroke-free participants with MMSE data (mean MMSE 26.0 ± 3.8) and 2,279 with TICS-m scores available. Compared to no PA, those with the upper quartile of MET scores had greater baseline MMSE scores (adjusted β = 0.4, p = 0.01) but no association with change in TICS-m over time. There were interactions (p < 0.05) between PA and both insurance and education; compared to no PA, those in the upper quartile of MET scores had a greater MMSE score only among those with Medicaid/no insurance (adjusted β = 0.83, p = 0.0005) and those who did not complete high school (adjusted β = 0.68, p = 0.001). Increased levels of PA were associated with better baseline MMSE, particularly among those with socioeconomic disadvantages, but not with cognitive decline. © 2013 S. Karger AG, Basel.

Chemical library subset selection algorithms: a unified derivation using spatial statistics.

PubMed

Hamprecht, Fred A; Thiel, Walter; van Gunsteren, Wilfred F

2002-01-01

If similar compounds have similar activity, rational subset selection becomes superior to random selection in screening for pharmacological lead discovery programs. Traditional approaches to this experimental design problem fall into two classes: (i) a linear or quadratic response function is assumed (ii) some space filling criterion is optimized. The assumptions underlying the first approach are clear but not always defendable; the second approach yields more intuitive designs but lacks a clear theoretical foundation. We model activity in a bioassay as realization of a stochastic process and use the best linear unbiased estimator to construct spatial sampling designs that optimize the integrated mean square prediction error, the maximum mean square prediction error, or the entropy. We argue that our approach constitutes a unifying framework encompassing most proposed techniques as limiting cases and sheds light on their underlying assumptions. In particular, vector quantization is obtained, in dimensions up to eight, in the limiting case of very smooth response surfaces for the integrated mean square error criterion. Closest packing is obtained for very rough surfaces under the integrated mean square error and entropy criteria. We suggest to use either the integrated mean square prediction error or the entropy as optimization criteria rather than approximations thereof and propose a scheme for direct iterative minimization of the integrated mean square prediction error. Finally, we discuss how the quality of chemical descriptors manifests itself and clarify the assumptions underlying the selection of diverse or representative subsets.

Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks

PubMed Central

Al-Samman, A. M.; Rahman, T. A.; Azmi, M. H.; Hindia, M. N.; Khan, I.; Hanafi, E.

2016-01-01

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios. PMID:27654703

Comparative Study of Speckle Filtering Methods in PolSAR Radar Images

NASA Astrophysics Data System (ADS)

Boutarfa, S.; Bouchemakh, L.; Smara, Y.

2015-04-01

Images acquired by polarimetric SAR (PolSAR) radar systems are characterized by the presence of a noise called speckle. This noise has a multiplicative nature, corrupts both the amplitude and phase images, which complicates data interpretation, degrades segmentation performance and reduces the detectability of targets. Hence, the need to preprocess the images by adapted filtering methods before analysis.In this paper, we present a comparative study of implemented methods for reducing speckle in PolSAR images. These developed filters are: refined Lee filter based on the estimation of the minimum mean square error MMSE, improved Sigma filter with detection of strong scatterers based on the calculation of the coherency matrix to detect the different scatterers in order to preserve the polarization signature and maintain structures that are necessary for image interpretation, filtering by stationary wavelet transform SWT using multi-scale edge detection and the technique for improving the wavelet coefficients called SSC (sum of squared coefficients), and Turbo filter which is a combination between two complementary filters the refined Lee filter and the wavelet transform SWT. One filter can boost up the results of the other.The originality of our work is based on the application of these methods to several types of images: amplitude, intensity and complex, from a satellite or an airborne radar, and on the optimization of wavelet filtering by adding a parameter in the calculation of the threshold. This parameter will control the filtering effect and get a good compromise between smoothing homogeneous areas and preserving linear structures.The methods are applied to the fully polarimetric RADARSAT-2 images (HH, HV, VH, VV) acquired on Algiers, Algeria, in C-band and to the three polarimetric E-SAR images (HH, HV, VV) acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band.To evaluate the performance of each filter, we used the following criteria: smoothing homogeneous areas, preserving edges and polarimetric information.Experimental results are included to illustrate the different implemented methods.

Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks.

PubMed

Al-Samman, A M; Rahman, T A; Azmi, M H; Hindia, M N; Khan, I; Hanafi, E

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios.

Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.

PubMed

Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia

2017-06-01

Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors (RSS) from the three quantitative analyses were compared. In methane gas analysis, SWLS yielded the lowest SEP and RSS among the three methods. In methane/toluene mixture gas analysis, a modification of the SWLS has been presented to tackle the bias error from other components. The SWLS without modification presents the lowest SEP in all cases but not bias and RSS. The modification of SWLS reduced the bias, which showed a lower RSS than CLS, especially for small components.

Microwave Photonic Architecture for Direction Finding of LPI Emitters: Post-Processing for Angle of Arrival Estimation

DTIC Science & Technology

2016-09-01

mean- square (RMS) error of 0.29° at ə° resolution. For a P4 coded signal, the RMS error in estimating the AOA is 0.32° at 1° resolution. 14...FMCW signal, it was demonstrated that the system is capable of estimating the AOA with a root-mean- square (RMS) error of 0.29° at ə° resolution. For a...Modulator PCB printed circuit board PD photodetector RF radio frequency RMS root-mean- square xvi THIS PAGE INTENTIONALLY LEFT BLANK xvii

Influence of anxiety symptoms on improvement of neurocognitive functions in patients with major depressive disorder: A 12-week, multicenter, randomized trial of tianeptine versus escitalopram, the CAMPION study.

PubMed

Yoo, Ikki; Woo, Jong-Min; Lee, Seung-Hwan; Fava, Maurizio; Mischoulon, David; Papakostas, George I; Kim, Eui-Joong; Chung, Seockhoon; Ha, Jee Hyun; Jeon, Hong Jin

2015-10-01

Previous research has reported evidence that patients with major depressive disorder (MDD) show anxiety symptoms and neurocognitive impairments. However, the influence of anxiety on neurocognitive function in MDD patients during antidepressant treatment is unclear. MDD patients (n=164) completed a 12-week, multicenter, randomized trial assigned in a 1:1 ratio to either tianeptine or escitalopram. Changes of anxiety symptoms were assessed by the Hamilton Anxiety Rating Scale (HAM-A), and the Hamilton Depression Rating Scale (HAM-D), self-rated subjective cognitive impairment on memory and concentration, the Mini-Mental Status Examination (MMSE), Continuous Performance Test (CPT), Verbal Learning Test (VLT), and Raven's Progressive Matrices (RPM) were assessed every 4 weeks. During 12 weeks of treatment, decrease in the HAM-A score was significantly associated with improvement of subjective cognitive impairments on memory (p<0.001) and concentration (p<0.001), and objective measures on delayed memory (p=0.006) and reasoning ability (p=0.002), after adjusting for covariates such as baseline HAM-A scores, time, sex, age, education years and assigned medication using the Mixed effects and Generalized Estimated Equation model analysis. However, the other cognitive outcome variables, immediate memory, commission error, and MMSE, which showed significant improvement through 12-week study period, showed no significant association with improvement of anxiety. Improvement of anxiety symptoms was significantly associated with improvement in subjective and objective neurocognitive functions such as delayed memory and reasoning ability in elderly MDD patients during antidepressant treatment, but not significantly associated with improvement of immediate memory and commission error. ClinicalTrials.gov identifier NCT01309776. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison between mini mental state examination (MMSE) and Montreal cognitive assessment Indonesian version (MoCA-Ina) as an early detection of cognitive impairments in post-stroke patients

NASA Astrophysics Data System (ADS)

Lestari, S.; Mistivani, I.; Rumende, C. M.; Kusumaningsih, W.

2017-08-01

Mild cognitive impairment (MCI) is defined as cognitive impairment that may never develop into dementia. Cognitive impairment is one long-term complication of a stroke. The Mini Mental State Examination (MMSE), which is commonly used as a screening tool for cognitive impairment, has a low sensitivity to detect cognitive impairment, especially MCI. Alternatively, the Montreal Cognitive Assessment Indonesian version (MoCA-Ina) has been reported to have a higher sensitivity than the MMSE. The aim of this study was to compare the proportion of MCI identified between the MMSE and MoCA-Ina in stroke patients. This was a cross-sectional study of stroke outpatients who attended the Polyclinic Neuromuscular Division, Rehabilitation Department, and Polyclinic Stroke, Neurology Department Cipto Mangunkusumo General Hospital, Jakarta. The proportion of MCI identified using the MMSE was 31.03% compared to 72.41% when using the MoCA-Ina. This difference was statistically significant (Fisher’s exact test, p = 0.033). The proportion of MCI in stroke patients was higher when using the MoCA-Ina compared to the MMSE. The MoCA-Ina should be used as an alternative in the early detection of MCI in stroke patients, especially those undergoing rehabilitation.

Item and scale differential functioning of the Mini-Mental State Exam assessed using the Differential Item and Test Functioning (DFIT) Framework.

PubMed

Morales, Leo S; Flowers, Claudia; Gutierrez, Peter; Kleinman, Marjorie; Teresi, Jeanne A

2006-11-01

To illustrate the application of the Differential Item and Test Functioning (DFIT) method using English and Spanish versions of the Mini-Mental State Examination (MMSE). Study participants were 65 years of age or older and lived in North Manhattan, New York. Of the 1578 study participants who were administered the MMSE 665 completed it in Spanish. : The MMSE contains 20 items that measure the degree of cognitive impairment in the areas of orientation, attention and calculation, registration, recall and language, as well as the ability to follow verbal and written commands. After assessing the dimensionality of the MMSE scale, item response theory person and item parameters were estimated separately for the English and Spanish sample using Samejima's 2-parameter graded response model. Then the DFIT framework was used to assess differential item functioning (DIF) and differential test functioning (DTF). Nine items were found to show DIF; these were items that ask the respondent to name the correct season, day of the month, city, state, and 2 nearby streets, recall 3 objects, repeat the phrase no ifs, no ands, no buts, follow the command, "close your eyes," and the command, "take the paper in your right hand, fold the paper in half with both hands, and put the paper down in your lap." At the scale level, however, the MMSE did not show differential functioning. Respondents to the English and Spanish versions of the MMSE are comparable on the basis of scale scores. However, assessments based on individual MMSE items may be misleading.

Neuropsychometric tests in cross sectional and longitudinal studies - a regression analysis of ADAS - cog, SKT and MMSE.

PubMed

Ihl, R; Grass-Kapanke, B; Jänner, M; Weyer, G

1999-11-01

In clinical and drug studies, different neuropsychometric tests are used. So far, no empirical data have been published to compare studies using different tests. The purpose of this study was to calculate a regression formula allowing a comparison of cross-sectional and longitudinal data from three neuropsychometric tests that are frequently used in drug studies (Alzheimer's Disease Assessment Scale, ADAS-cog; Syndrom Kurz Test, SKT; Mini Mental State Examination, MMSE). 177 patients with dementia according to ICD10 criteria were studied for the cross sectional and 61 for the longitudinal analysis. Correlations and linear regressions were calculated between tests. Significance was proven with ANOVA and t-tests using the SPSS statistical package. Significant Spearman correlations and slopes in the regression occurred in the cross sectional analysis (ADAS-cog-SKT r(s) = 0.77, slope = 0.45, SKT-ADAS-cog slope = 1.3, r2 = 0.59; ADAS-cog-MMSE r2 = 0.76, slope = -0.42, MMSE-ADAS-cog slope = -1.5, r2 = 0.64; MMSE-SKT r(s) = -0.79, slope = -0.87, SKT-MMSE slope = -0.71, r2 = 0.62; p<0.001 after Bonferroni correction; N = 177) and in the longitudinal analysis (SKT-ADAS-cog, r(s) = 0.48, slope = 0.69, ADAS-cog-SKT slope = 0.69, p<0.001, r2 = 0.32, MMSE-SKT, r(s) = 0.44, slope = -0.41, SKT-MMSE, slope = -0.55, p<0.001, r2 = 0.21). The results allow calculation of ADAS-scores when SKT scores are given, and vice versa. In longitudinal studies or in the course of the disease, scores assessed with the ADAS-cog and the SKT may now be statistically compared. In all comparisons, bottom and ceiling effects of the tests have to be taken into account.

Age, education, and changes in the Mini-Mental State Exam scores of older women: findings from the Nun Study.

PubMed

Butler, S M; Ashford, J W; Snowdon, D A

1996-06-01

To describe the relationship of Mini-Mental State Exam (MMSE) scores and changes over time in MMSE scores to age and education in a population of older women. A prospective study of a defined population. Various motherhouses and church-run health care facilities in the Eastern, Midwestern, and Southern regions of the United States. Catholic sisters (nuns) participating in the Nun Study, a study of aging and Alzheimer's Disease. The 678 participants were 75 to 102 years old (mean 83.3, standard deviation 5.5, median 82.3) at the time of the first functional assessment. Second assessments were obtained an average of 1.6 years later on 575 survivors. The outcome variables were MMSE scores at the first assessment (Time-one), and MMSE scores at the second assessment (Time-two). The independent variables were age at Time-one, and education (bachelor's degree or no bachelor's degree). Time-one MMSE scores decreased with age at Time-one. The decrease in MMSE scores with age was less in sisters with bachelor's degrees than in sisters without bachelor's degrees. The changes in MMSE scores had a "U-shaped" relationship with Time-one score, where the greatest declines occurred in sisters with intermediate Time-one scores. Stratified analysis by age, education, and Time-one MMSE scores of 20 or greater because of the small numbers of sisters with Time-one scores less than 20. In sisters with Time-one MMSE scores in the categories 20 to 23, 24 to 26, or 27 to 30, older ages at Time-one were associated with greater decline in those with bachelor's degrees, but not in those without bachelor's degrees. Also, lower education was associated with greater decline in sisters aged 75 to 84 years at Time-one, but this education effect disappeared or reversed in sisters who were 85 years of age or older at Time-one. Cognitive function as measured by the MMSE decreased with age at Time-one, most steeply as a function of age in those without bachelor's degrees. Cognitive function declined over 1.6 years within individuals, and the extent of decline increased with age in the sisters with bachelor's degrees. The extent of decline varied with age and education in an interactive manner, which may have been attributable to a hardy survivor effect in lower educated sisters. It may be necessary to consider such interactions whenever changes in function are studied, particularly when analyses are stratified by the initial level of function.

A retrospective analysis of the sentence writing component of the Mini Mental State Examination: cognitive and affective aspects.

PubMed

Press, Yan; Velikiy, Natalia; Berzak, Alex; Tandeter, Howard; Peleg, Roni; Freud, Tamar; Punchik, Boris; Dwolatzky, Tzvi

2012-01-01

One of the components of the Mini Mental State Examination (MMSE) is the request to write a sentence. We investigated the relationship between the characteristics of the written sentence of the MMSE and the cognitive and affective status of elderly patients. The characteristics of the sentence were compared to the total MMSE score, sociodemographic characteristics, tests evaluating cognition and affective status, and diagnoses. The number of words was significantly associated with the degree of cognitive impairment, whereas the emotional polarity of sentences and concerns about health were associated with depression. Characteristics of the MMSE sentence may provide important additional information regarding both cognition and affect when assessing older people. Copyright © 2012 S. Karger AG, Basel.

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

Correcting Four Similar Correlational Measures for Attenuation Due to Errors of Measurement in the Dependent Variable: Eta, Epsilon, Omega, and Intraclass r.

ERIC Educational Resources Information Center

Stanley, Julian C.; Livingston, Samuel A.

Besides the ubiquitous Pearson product-moment r, there are a number of other measures of relationship that are attenuated by errors of measurement and for which the relationship between true measures can be estimated. Among these are the correlation ratio (eta squared), Kelley's unbiased correlation ratio (epsilon squared), Hays' omega squared,…

Study on the Rationality and Validity of Probit Models of Domino Effect to Chemical Process Equipment caused by Overpressure

NASA Astrophysics Data System (ADS)

Sun, Dongliang; Huang, Guangtuan; Jiang, Juncheng; Zhang, Mingguang; Wang, Zhirong

2013-04-01

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Some models considering propagation probability and threshold values of the domino effect caused by overpressure have been proposed in previous study. In order to prove the rationality and validity of the models reported in the reference, two boundary values of three damage degrees reported were considered as random variables respectively in the interval [0, 100%]. Based on the overpressure data for damage to the equipment and the damage state, and the calculation method reported in the references, the mean square errors of the four categories of damage probability models of overpressure were calculated with random boundary values, and then a relationship of mean square error vs. the two boundary value was obtained, the minimum of mean square error was obtained, compared with the result of the present work, mean square error decreases by about 3%. Therefore, the error was in the acceptable range of engineering applications, the models reported can be considered reasonable and valid.

Associations of cumulative Pb exposure and longitudinal changes in Mini-Mental Status Exam scores, global cognition and domains of cognition: The VA Normative Aging Study.

PubMed

Farooqui, Zishaan; Bakulski, Kelly M; Power, Melinda C; Weisskopf, Marc G; Sparrow, David; Spiro, Avron; Vokonas, Pantel S; Nie, Linda H; Hu, Howard; Park, Sung Kyun

2017-01-01

Lead (Pb) exposure has been associated with poorer cognitive function cross-sectionally in aging adults, however the association between cumulative Pb exposure and longitudinal changes in cognition is little characterized. In a 1993-2007 subcohort of the VA Normative Aging Study (Mini-mental status exam (MMSE) n=741; global cognition summary score n=715), we used linear mixed effects models to test associations between cumulative Pb exposure (patella or tibia bone Pb) and repeated measures of cognition (MMSE, individual cognitive tests, and global cognition summary). Cox proportional hazard modeling assessed the risk of an MMSE score falling below 25. Among men 51-98 at baseline, higher patella Pb concentration (IQR: 21μg/g) was associated with -0.13 lower baseline MMSE (95% CI: -0.25, -0.004) and faster longitudinal MMSE decline (-0.016 units/year, 95% CI: -0.032, -0.0004) over 15 years. Each IQR increase in patella Pb was associated with increased risk of a MMSE score below 25 (HR=1.21, 95% CI: 0.99, 1.49; p=0.07). There were no significant associations between Pb and global cognition (both baseline and longitudinal change). Patella Pb was associated with faster longitudinal decline in Word List Total Recall in the language domain (0.014 units/year, 95% CI: -0.026, -0.001) and Word List Delayed Recall in the memory domain (0.014 units/year, 95% CI: -0.027, -0.002). We found weaker associations with tibia Pb. Cumulative Pb exposure is associated with faster declines in MMSE and Word List Total and Delayed Recall tests. These findings support the hypothesis that Pb exposure accelerates cognitive aging. Copyright © 2016 Elsevier Inc. All rights reserved.

Cognitive impairment and mortality among the oldest-old Chinese.

PubMed

An, Ruopeng; Liu, Gordon G

2016-12-01

This study examined the relationship between cognitive impairment status and all-cause mortality among the oldest-old Chinese. A total of 7474 survey participants 80 years of age and above came from the Chinese Longitudinal Healthy Longevity Survey 1998-2012 waves. Baseline cognitive impairment status was assessed using the Chinese version of the mini-mental state examination (MMSE), with total score ranging from 0 to 30. Cox proportional hazards regressions were performed to examine the relationship between baseline cognitive impairment status in 1998 and subsequent all-cause mortality during 1998-2012, adjusting for various individual characteristics at baseline. Compared with those with no or mild cognitive impairment (18 ≤ MMSE score ≤ 30) at baseline, participants with moderate-to-severe cognitive impairment (0 ≤ MMSE score ≤ 17) were 28% (95% confidence interval = 20%, 37%) more likely to die during the follow-up period from 1998 to 2012. A dose-response relationship between baseline severity level of cognitive impairment and mortality was evident. Compared with those without cognitive impairment (25 ≤ MMSE score ≤ 30) at baseline, those having mild cognitive impairment (18 ≤ MMSE score ≤ 24), moderate cognitive impairment (10 ≤ MMSE score ≤ 17), and severe cognitive impairment (0 ≤ MMSE score ≤ 9), were 20% (13%, 28%), 38% (27%, 51%), and 47% (33%, 62%) more likely to die during the follow-up period. No statistically significant gender differences in the relationship between cognitive impairment status and mortality were found. Baseline cognitive impairment was inversely associated with longevity among the oldest-old Chinese. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Total homocysteine and cognition in a tri-ethnic cohort

PubMed Central

Wright, C.B.; Lee, H.-S.; Paik, M.C.; Stabler, S.P.; Allen, R.H.; Sacco, R.L.

2005-01-01

Objective: Several studies implicate elevated homocysteine as a risk factor for dementia and cognitive decline, but most studies have involved subjects older than 55 years from homogeneous populations. The authors examined homocysteine and cognition in a tri-ethnic community sample 40 years and older. Method: The Northern Manhattan Study includes 3,298 stroke-free subjects. Of these 2,871 had baseline fasting total homocysteine (tHcy) levels and Mini-Mental State Examination (MMSE) scores available. The authors used multiple linear regression to examine the cross-sectional association between baseline tHcy levels and mean MMSE scores adjusting for sociodemographic and vascular risk factors. Results: Homocysteine levels were related to age, renal function, and B12 deficiency. Those with B12 deficiency had tHcy levels five points higher (9.4 vs 14.4 nmol/L). Mean MMSE scores differed by age, sex, and race-ethnic group. Those with hypertension, diabetes, cardiac disease, and B12 deficiency had lower MMSE scores. In multivariate analyses, elevated tHcy was associated with lower mean MMSE scores for those older than 65 but not for those 40 to 64. Adjusting for B12 deficiency and sociodemographic factors the mean MMSE was 2.2 points lower for each unit increase in the log tHcy level (95% CI −3.6, −0.9). Adding vascular risk factors to the model did not attenuate this effect (mean MMSE −2.2 points; 95% CI −3.5, −0.9). Conclusions: Elevated homocysteine was independently associated with decreased cognition in subjects older than 65 in this tri-ethnic cohort, adjusting for sociodemographic and vascular risk factors. PMID:15277617

Methylation and demethylation of intermediates selenide and methylselenol in the metabolism of selenium

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

Ohta, Yuki; Suzuki, Kazuo T.

2008-01-15

All nutritional selenium sources are transformed into the assumed common intermediate selenide for the syntheses of selenoproteins for utilization and/or of selenosugar for excretion. Methylselenol [monomethylselenide, MMSe] is the assumed intermediate leading to other methylated metabolites, dimethylselenide (DMSe) and trimethylselenonium (TMSe) for excretion, and also to the intermediate selenide from methylselenocysteine and methylseleninic acid (MSA). Here, related methylation and demethylation reactions were studied in vitro by providing chemically reactive starting substrates ({sup 76}Se-selenide, {sup 77}Se-MMSe and {sup 82}Se-DMSe) which were prepared in situ by the reduction of the corresponding labeled proximate precursors ({sup 76}Se-selenite, {sup 77}Se-MSA and {sup 82}Se-dimethylselenoxide (DMSeO),more » respectively) with glutathione, the three substrates being incubated simultaneously in rat organ supernatants and homogenates. The resulting chemically labile reaction products were detected simultaneously by speciation analysis with HPLC-ICP-MS after converting the products and un-reacted substrates to the corresponding oxidized derivatives (selenite, MSA and DMSeO). The time-related changes in selenium isotope profiles showed that demethylation of MMSe to selenide was efficient but that of DMSe to MMSe was negligible, whereas methylation of selenide to MMSe, and MMSe to DMSe were efficient, and that of DMSe to TMSe occurred less efficiently. The present methylation and demethylation reactions on equilibrium between selenide, MMSe and DMSe without producing selenosugar and selenoproteins indicated that DMSe rather than TMSe is produced as the end product, suggesting that DMSe is to be excreted more abundantly than TMSe. Organ-dependent differences in the methylation and demethylation reactions were characterized for the liver, kidney and lung.« less

Cross-validation of a Shortened Battery for the Assessment of Dysexecutive Disorders in Alzheimer Disease.

PubMed

Godefroy, Olivier; Martinaud, Olivier; Verny, Marc; Mosca, Chrystèle; Lenoir, Hermine; Bretault, Eric; Devendeville, Agnès; Diouf, Momar; Pere, Jean-Jacques; Bakchine, Serge; Delabrousse-Mayoux, Jean-Philippe; Roussel, Martine

2016-01-01

The frequency of executive disorders in mild-to-moderate Alzheimer disease (AD) has been demonstrated by the application of a comprehensive battery. The present study analyzed data from 2 recent multicenter studies based on the same executive battery. The objective was to derive a shortened battery by using the GREFEX population as a training dataset and by cross-validating the results in the REFLEX population. A total of 102 AD patients of the GREFEX study (MMSE=23.2±2.9) and 72 patients of the REFLEX study (MMSE=20.8±3.5) were included. Tests were selected and receiver operating characteristic curves were generated relative to the performance of 780 controls from the GREFEX study. Stepwise logistic regression identified 3 cognitive tests (Six Elements Task, categorical fluency and Trail Making Test B error) and behavioral disorders globally referred as global hypoactivity (P=0.0001, all). This shortened battery was as accurate as the entire GREFEX battery in diagnosing dysexecutive disorders in both training group and the validation group. Bootstrap procedure confirmed the stability of AUC. A shortened battery based on 3 cognitive tests and 3 behavioral domains provides a high diagnosis accuracy of executive disorders in mild-to-moderate AD.

Increased Risk for Falling Associated with Subtle Cognitive Impairment: Secondary Analysis of a Randomized Clinical Trial

PubMed Central

Gleason, Carey E.; Gangnon, Ronald E.; Fischer, Barbara L.; Mahoney, Jane E.

2009-01-01

Background/Aims Having dementia increases patients’ risk for accidental falls. However, it is unknown if having mild cognitive deficits also elevates a person's risk for falls. This study sought to clarify the relationship between subtle cognitive impairment, measured with a widely-used, clinic-based assessment, the Mini Mental State Exam (MMSE), and risk for falls. Methods In a secondary analysis of the Kenosha County Falls Prevention Study, a randomized controlled trial targeting older adults at risk for falls, we examined the association between baseline MMSE and prospective rate of falls over 12 months in 172 subjects randomized to control group. Results Using univariate analysis, the rate of falls increased with each unit decrease in MMSE score down to at least 22 (rate ratio 1.25, 95% confidence interval (CI) 1.09–1.45, p = 0.0026). Using stepwise multivariate regression, controlling for ability to perform activities of daily living, use of assistive device, current exercise, and arthritis, the association between MMSE score and falls rate persisted (rate ratio 1.20, 95% CI 1.03–1.40, p = 0.021). Conclusion Minimal decrements on the MMSE were associated with elevations in rate of falls, suggesting that subtle cognitive deficits reflected in MMSE scores above a cut-off consistent with a diagnosis of dementia, can influence risk for falls. PMID:19602883

Transitions across cognitive states and death among older adults in relation to education: A multistate survival model using data from six longitudinal studies.

PubMed

Robitaille, Annie; van den Hout, Ardo; Machado, Robson J M; Bennett, David A; Čukić, Iva; Deary, Ian J; Hofer, Scott M; Hoogendijk, Emiel O; Huisman, Martijn; Johansson, Boo; Koval, Andriy V; van der Noordt, Maaike; Piccinin, Andrea M; Rijnhart, Judith J M; Singh-Manoux, Archana; Skoog, Johan; Skoog, Ingmar; Starr, John; Vermunt, Lisa; Clouston, Sean; Muniz Terrera, Graciela

2018-04-01

This study examines the role of educational attainment, an indicator of cognitive reserve, on transitions in later life between cognitive states (normal Mini-Mental State Examination (MMSE), mild MMSE impairment, and severe MMSE impairment) and death. Analysis of six international longitudinal studies was performed using a coordinated approach. Multistate survival models were used to estimate the transition patterns via different cognitive states. Life expectancies were estimated. Across most studies, a higher level of education was associated with a lower risk of transitioning from normal MMSE to mild MMSE impairment but was not associated with other transitions. Those with higher levels of education and socioeconomic status had longer nonimpaired life expectancies. This study highlights the importance of education in later life and that early life experiences can delay later compromised cognitive health. This study also demonstrates the feasibility and benefit in conducting coordinated analysis across multiple studies to validate findings. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Weak independent association signals between IDE polymorphisms, Alzheimer's disease and cognitive measures.

PubMed

Mueller, Jakob C; Riemenschneider, Matthias; Schoepfer-Wendels, Andreas; Gohlke, Henning; Konta, Lidija; Friedrich, Patricia; Illig, Thomas; Laws, Simon M; Förstl, Hans; Kurz, Alexander

2007-05-01

Functional and genetic studies suggest that insulin-degrading enzyme (IDE) may be a strong functional and positional candidate. As there is a lack of consensus in regards to the level and location of IDE association signals we aimed to clarify these discrepancies through genotyping 28 SNPs in a large case-control collective together with quantitative measures of cognitive ability (MMSE). Four SNPs (rs11187007, rs2149632_ide12, rs11187033, rs11187040) were found to be associated with AD (nominal p<0.01). Tests with MMSE scores adjusted for disease duration identified associations, with the most significant result for rs1999763 (nominal p=0.008). Similarly, different reconstructed IDE haplotypes were associated with AD and higher MMSE scores. The association signals are only borderline significant after adjustment for multiple testing, but add further evidence to previous published results on the association between IDE and AD or MMSE. A subgroup analysis indicated more prominent associations with AD in younger, and with MMSE in older patients. There may be two independent effects mediated by IDE variants, risk for AD and modification of disease progression.

An Empirical State Error Covariance Matrix for the Weighted Least Squares Estimation Method

NASA Technical Reports Server (NTRS)

Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the un-certainty in the estimated states. By a reinterpretation of the equations involved in the weighted least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. This proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. Results based on the proposed technique will be presented for a simple, two observer, measurement error only problem.

Analysis of tractable distortion metrics for EEG compression applications.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-07-01

Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio.

Increased Muscle Sympathetic Nerve Activity and Impaired Executive Performance Capacity in Obstructive Sleep Apnea

PubMed Central

Goya, Thiago T.; Silva, Rosyvaldo F.; Guerra, Renan S.; Lima, Marta F.; Barbosa, Eline R.F.; Cunha, Paulo Jannuzzi; Lobo, Denise M.L.; Buchpiguel, Carlos A.; Busatto-Filho, Geraldo; Negrão, Carlos E.; Lorenzi-Filho, Geraldo; Ueno-Pardi, Linda M.

2016-01-01

Study Objectives: To investigate muscle sympathetic nerve activity (MSNA) response and executive performance during mental stress in obstructive sleep apnea (OSA). Methods: Individuals with no other comorbidities (age = 52 ± 1 y, body mass index = 29 ± 0.4, kg/m2) were divided into two groups: (1) control (n = 15) and (2) untreated OSA (n = 20) defined by polysomnography. Mini-Mental State of Examination (MMSE) and Inteligence quocient (IQ) were assessed. Heart rate (HR), blood pressure (BP), and MSNA (microneurography) were measured at baseline and during 3 min of the Stroop Color Word Test (SCWT). Sustained attention and inhibitory control were assessed by the number of correct answers and errors during SCWT. Results: Control and OSA groups (apnea-hypopnea index, AHI = 8 ± 1 and 47 ± 1 events/h, respectively) were similar in age, MMSE, and IQ. Baseline HR and BP were similar and increased similarly during SCWT in control and OSA groups. In contrast, baseline MSNA was higher in OSA compared to controls. Moreover, MSNA significantly increased in the third minute of SCWT in OSA, but remained unchanged in controls (P < 0.05). The number of correct answers was lower and the number of errors was significantly higher during the second and third minutes of SCWT in the OSA group (P < 0.05). There was a significant correlation (P < 0.01) between the number of errors in the third minute of SCWT with AHI (r = 0.59), arousal index (r = 0.55), and minimum O2 saturation (r = −0.57). Conclusions: As compared to controls, MSNA is increased in patients with OSA at rest, and further significant MSNA increments and worse executive performance are seen during mental stress. Clinical Trial Registration: URL: http://www.clinicaltrials.gov, registration number: NCT002289625. Citation: Goya TT, Silva RF, Guerra RS, Lima MF, Barbosa ER, Cunha PJ, Lobo DM, Buchpiguel CA, Busatto-Filho G, Negrão CE, Lorenzi-Filho G, Ueno-Pardi LM. Increased muscle sympathetic nerve activity and impaired executive performance capacity in obstructive sleep apnea. SLEEP 2016;39(1):25–33. PMID:26237773

A Survey of Terrain Modeling Technologies and Techniques

DTIC Science & Technology

2007-09-01

Washington , DC 20314-1000 ERDC/TEC TR-08-2 ii Abstract: Test planning, rehearsal, and distributed test events for Future Combat Systems (FCS) require...distance) for all five lines of control points. Blue circles are errors of DSM (original data), red squares are DTM (bare Earth, processed by Intermap...circles are DSM, red squares are DTM ........... 8 5 Distribution of errors for line No. 729. Blue circles are DSM, red squares are DTM

Comparison of clock drawing with Mini Mental State Examination as a screening test in elderly acute hospital admissions.

PubMed Central

Death, J.; Douglas, A.; Kenny, R. A.

1993-01-01

Clock drawing is a quick, easy to remember test that is well received by patients. It is a good screening test for Alzheimer's disease in the outpatient setting. We evaluated its usefulness compared with the standard Mini Mental State Examination (MMSE) in elderly acute medical and surgical hospital admissions. Within 48 hours of admission, 117 patients over 70 years old were administered the MMSE and asked to draw a clock. Using the MMSE as the standard, clock drawing had a sensitivity of 77% and a specificity of 87%. Patients with discrepant scores were then further evaluated. The findings suggest that normal clock drawing ability reasonably excludes cognitive impairment or other causes of an abnormal MMSE in elderly acute medical and surgical hospital admissions, where cognitive impairment is common and frequently missed. PMID:8255833

The Telephone Interview for Cognitive Status: Creating a crosswalk with the Mini-Mental State Exam

PubMed Central

Fong, Tamara G.; Fearing, Michael A.; Jones, Richard N.; Shi, Peilin; Marcantonio, Edward R.; Rudolph, James L.; Yang, Frances M.; Kiely, Dan K.; Inouye, Sharon K.

2009-01-01

Background Brief cognitive screening measures are valuable tools for both research and clinical applications. The most widely used instrument, the Mini-Mental State Examination (MMSE) is limited in that it must be administered face-to-face, cannot be used in participants with visual or motor impairments, and is protected by copyright. Alternative screening instruments, such as the Telephone Interview for Cognitive Status (TICS) have been developed and may provide a valid alternative with comparable cut point scores to rate global cognitive function. Methods MMSE, TICS-30, and TICS-40 scores from 746 community dwelling elders who participated in the Aging, Demographics, and Memory Study (ADAMS) were analyzed with equipercentile equating, a statistical process of determining comparable scores based on percentile equivalents on different forms of an examination. Results Scores from the MMSE and the TICS-30 and TICS-40 corresponded well and clinically relevant cut point scores were determined; for example, an MMSE score of 23 is equivalent to 17 and 20 on the TICS-30 and TICS-40, respectively. Conclusions These findings provide scores that can be used to link TICS and MMSE scores directly. Clinically relevant and important MMSE cut points and the respective ADAMS TICS-30 and TICS-40 cut point scores have been included to identify the degree of cognitive impairment among respondents with any type of cognitive disorder. These results will help with the widespread application of the TICS in both research and clinical practice. PMID:19647495

Factors Influencing Cognitive Function in Subjects With COPD.

PubMed

Dag, Ersel; Bulcun, Emel; Turkel, Yakup; Ekici, Aydanur; Ekici, Mehmet

2016-08-01

The aim of this study was to assess the association between cognitive function and age, pulmonary function, comorbidity index, and the 6-min walk distance in subjects with COPD as well as to compare the Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) in terms of their ability to identify cognitive dysfunction in subjects with COPD. A total of 52 individuals with stable COPD were included in this study. Cognitive function was assessed using MMSE and MoCA. Age, body mass index, the Modified Cumulative Illness Rating Scale, 6-min walk distance, arterial blood gases, and pulmonary function tests were assessed and recorded. The range and SD of scores in subjects with COPD were larger with MoCA than with MMSE. MMSE and MoCA scores are associated with 6-min walk distance and comorbidity index in subjects with COPD. General cognitive function measured by MoCA was negatively correlated with the comorbidity index but was positively associated with 6-min walk distance in subjects with COPD after controlling for possible confounding factors in the multivariate model. However, general cognitive function measured by MMSE was not correlated with the comorbidity index and 6-min walk distance in subjects with COPD, after controlling for possible confounding factors in the multivariate model. MoCA may be a more reliable screening test than MMSE in detecting cognitive impairment in subjects with COPD. The addition of cognitive tests on assessment of subjects with COPD can provide further benefit. Copyright © 2016 by Daedalus Enterprises.

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

NASA Astrophysics Data System (ADS)

Rahman, Samiur; Ullah, Sana; Ullah, Sehat

2018-01-01

Obstacle detection can improve the mobility as well as the safety of visually impaired people. In this paper, we present a system using mobile camera for visually impaired people. The proposed algorithm works in indoor environment and it uses a very simple technique of using few pre-stored floor images. In indoor environment all unique floor types are considered and a single image is stored for each unique floor type. These floor images are considered as reference images. The algorithm acquires an input image frame and then a region of interest is selected and is scanned for obstacle using pre-stored floor images. The algorithm compares the present frame and the next frame and compute mean square error of the two frames. If mean square error is less than a threshold value α then it means that there is no obstacle in the next frame. If mean square error is greater than α then there are two possibilities; either there is an obstacle or the floor type is changed. In order to check if the floor is changed, the algorithm computes mean square error of next frame and all stored floor types. If minimum of mean square error is less than a threshold value α then flour is changed otherwise there exist an obstacle. The proposed algorithm works in real-time and 96% accuracy has been achieved.

Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error

NASA Astrophysics Data System (ADS)

Khair, Ummul; Fahmi, Hasanul; Hakim, Sarudin Al; Rahim, Robbi

2017-12-01

Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.

Montreal Cognitive Assessment (MoCA): validation study for frontotemporal dementia.

PubMed

Freitas, Sandra; Simões, Mário R; Alves, Lara; Duro, Diana; Santana, Isabel

2012-09-01

The Montreal Cognitive Assessment (MoCA) is a brief instrument developed for the screening of milder forms of cognitive impairment, having surpassed the well-known limitations of the Mini-Mental State Examination (MMSE). The aim of the present study was to validate the MoCA as a cognitive screening test for behavioral-variant frontotemporal dementia (bv-FTD) by examining its psychometric properties and diagnostic accuracy. Three matched subgroups of participants were considered: bv-FTD (n = 50), Alzheimer disease (n = 50), and a control group of healthy adults (n = 50). Compared with the MMSE, the MoCA demonstrated consistently superior psychometric properties and discriminant capacity, providing comprehensive information about the patients' cognitive profiles. The diagnostic accuracy of MoCA for bv-FTD was extremely high (area under the curve AUC [MoCA] = 0.934, 95% confidence interval [CI] = 0.866-.974; AUC [MMSE] = 0.772, 95% CI = 0.677-0.850). With a cutoff below 17 points, the MoCA results for sensitivity, specificity, positive predictive value, negative predictive value, and classification accuracy were significantly superior to those of the MMSE. The MoCA is a sensitive and accurate instrument for screening the patients with bv-FTD and represents a better option than the MMSE.

Associations of cumulative Pb exposure and longitudinal changes in Mini-Mental Status Exam scores, global cognition and domains of cognition: The VA Normative Aging Study

PubMed Central

Farooqui, Zishaan; Bakulski, Kelly M.; Power, Melinda C.; Weisskopf, Marc G.; Sparrow, David; Spiro, Avron; Vokonas, Pantel S.; Nie, Huiling; Hu, Howard; Park, Sung Kyun

2016-01-01

Background Lead (Pb) exposure has been associated with poorer cognitive function cross-sectionally in aging adults, however the association between cumulative Pb exposure and longitudinal changes in cognition is little characterized. Methods In a 1993–2007 subcohort of the VA Normative Aging Study (Mini-mental status exam (MMSE) n=741; global cognition summary score n=715), we used linear mixed effects models to test associations between cumulative Pb exposure (patella or tibia bone Pb) and repeated measures of cognition (MMSE, individual cognitive tests, and global cognition summary). Cox proportional hazard modeling assessed the risk of an MMSE score falling below 25. Results Among men 51–98 at baseline, higher patella Pb concentration (IQR: 21 µg/g) was associated with −0.13 lower baseline MMSE (95% CI: −0.25, −0.004) and faster longitudinal MMSE decline (−0.016 units/year, 95% CI: −0.032, −0.0004) over 15 years. Each IQR increase in patella Pb was associated with increased risk of a MMSE score below 25 (HR=1.21, 95% CI: 0.99, 1.49; p=0.07). There were no significant associations between Pb and global cognition (both baseline and longitudinal change). Patella Pb was associated with faster longitudinal decline in Word List Total Recall in the language domain (0.014 units/year, 95% CI: −0.026, −0.001) and Word List Delayed Recall in the memory domain (0.014 units/year, 95% CI: −0.027, −0.002). We found weaker associations with tibia Pb. Conclusions Cumulative Pb exposure is associated with faster declines in MMSE and Word List Total and Delayed Recall tests. These findings support the hypothesis that Pb exposure accelerates cognitive aging. PMID:27770710

Converting MMSE to MoCA and MoCA 5-minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack.

PubMed

Wong, Adrian; Black, Sandra E; Yiu, Stanley Y P; Au, Lisa W C; Lau, Alexander Y L; Soo, Yannie O Y; Chan, Anne Y Y; Leung, Thomas W H; Wong, Lawrence K S; Kwok, Timothy C Y; Cheung, Theodore C K; Leung, Kam-Tat; Lam, Bonnie Y K; Kwan, Joseph S K; Mok, Vincent C T

2018-05-01

The Montreal Cognitive Assessment (MoCA) is psychometrically superior over the Mini-mental State Examination (MMSE) for cognitive screening in stroke or transient ischemic attack (TIA). It is free for clinical and research use. The objective of this study is to convert scores from the MMSE to MoCA and MoCA-5-minute protocol (MoCA-5 min) and to examine the ability of the converted scores in detecting cognitive impairment after stroke or TIA. A total of 904 patients were randomly divided into training (n = 623) and validation (n = 281) samples matched for demography and cognition. MMSE scores were converted to MoCA and MoCA-5 min using (1) equipercentile method with log-linear smoothing and (2) Poisson regression adjusting for age and education. Receiver operating characteristics curve analysis was used to examine the ability of the converted scores in differentiating patients with cognitive impairment. The mean education was 5.8 (SD = 4.6; ranged 0-20) years. The entire spectrum of MMSE scores was converted to MoCA and MoCA-5 min using equipercentile method. Relationship between MMSE and MoCA scores was confounded by age and education, and a conversion equation with adjustment for age and education was derived. In the validation sample, the converted scores differentiated cognitively impaired patients with area under receiver operating characteristics curve 0.826 to 0.859. We provided 2 methods to convert scores from the MMSE to MoCA and MoCA-5 min based on a large sample of patients with stroke or TIA having a wide range of education and cognitive levels. The converted scores differentiated patients with cognitive impairment after stroke or TIA with high accuracy. Copyright © 2018 John Wiley & Sons, Ltd.

Rivastigmine Patch in Chinese Patients with Probable Alzheimer's disease: A 24-week, Randomized, Double-Blind Parallel-Group Study Comparing Rivastigmine Patch (9.5 mg/24 h) with Capsule (6 mg Twice Daily).

PubMed

Zhang, Zhen-Xin; Hong, Zhen; Wang, Yan-Ping; He, Li; Wang, Ning; Zhao, Zhong-Xin; Zhao, Gang; Shang, Lan; Weisskopf, Marianne; Callegari, Francesca; Strohmaier, Christine

2016-06-01

To compare the once-daily rivastigmine patch 9.5 mg/24 h (10 cm(2) ) versus twice-daily capsule (12 mg/day) in Chinese patients with probable Alzheimer's disease (AD) (mini-mental state examination [MMSE] scores of 10-20). The primary objective was to demonstrate the noninferiority of patch to capsule in Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) change from baseline to 24 week. Secondary endpoints included cognition (MMSE), overall clinical response (Alzheimer's Disease Cooperative Study-Clinical Global Impression of Change [ADCS-CGIC]), activities of daily living (Alzheimer's Disease Cooperative Study-Activities of Daily Living [ADCS-ADL]), behavior (Neuropsychiatric Inventory [NPI-12]), and safety. Similar cognitive improvement was observed in both patch (n = 248) and capsule (n = 253) groups. Statistical noninferiority for ADAS-Cog was not established (least-square means difference, 0.1; 95% confidence interval, -1.2; 1.5). Considering all efficacy parameters into account, both treatments showed similar performance at Week 24. Treatment-related adverse events (AEs) were lower for patch (39.7%) compared with capsule (49.8%). Application site pruritus was reported in 10.9% of patients receiving patch; most cases were mild. Gastrointestinal AEs including nausea, vomiting, and diarrhea occurred less frequently in the patch group (15.8% vs. 28.7%). Rivastigmine patch 9.5 mg/24 h is effective and well tolerated in Chinese patients with probable AD. © 2016 John Wiley & Sons Ltd.

47 CFR 87.145 - Acceptability of transmitters for licensing.

Code of Federal Regulations, 2014 CFR

2014-10-01

... square error which assumes zero error for the received ground earth station signal and includes the AES transmit/receive frequency reference error and the AES automatic frequency control residual errors.) The...

47 CFR 87.145 - Acceptability of transmitters for licensing.

Code of Federal Regulations, 2013 CFR

2013-10-01

... square error which assumes zero error for the received ground earth station signal and includes the AES transmit/receive frequency reference error and the AES automatic frequency control residual errors.) The...

47 CFR 87.145 - Acceptability of transmitters for licensing.

Code of Federal Regulations, 2012 CFR

2012-10-01

... square error which assumes zero error for the received ground earth station signal and includes the AES transmit/receive frequency reference error and the AES automatic frequency control residual errors.) The...

47 CFR 87.145 - Acceptability of transmitters for licensing.

Code of Federal Regulations, 2011 CFR

2011-10-01

... square error which assumes zero error for the received ground earth station signal and includes the AES transmit/receive frequency reference error and the AES automatic frequency control residual errors.) The...

Shapes of the Trajectories of Five Major Biomarkers of Alzheimer’s Disease

PubMed Central

Jack, Clifford R.; Vemuri, Prashanthi; Wiste, Heather J.; Weigand, Stephen D.; Lesnick, Timothy G.; Lowe, Val; Kantarci, Kejal; Bernstein, Matt A.; Senjem, Matthew L.; Gunter, Jeffrey L.; Boeve, Bradley F.; Trojanowski, John Q.; Shaw, Leslie M.; Aisen, Paul S.; Weiner, Michael W.; Petersen, Ronald C.; Knopman, David S.

2013-01-01

Objective To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE. Design Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Patients Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline. Main Outcome Measures The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI). Results Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model. Conclusions Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants. PMID:22409939

Microbleeds do not affect rate of cognitive decline in Alzheimer disease.

PubMed

van der Vlies, Annelies E; Goos, Jeroen D C; Barkhof, Frederik; Scheltens, Philip; van der Flier, Wiesje M

2012-08-21

To investigate the relationship between brain microbleeds (MBs) and the rate of cognitive decline in Alzheimer disease (AD). In this cohort study, we studied 221 patients with AD with available baseline MRI scans (1.0 or 1.5 T) and at least 2 Mini-Mental State Examinations (MMSE) scores obtained more than 1 year apart from our memory clinic. Mean ± SD follow-up time was 3 ± 1 years, and patients had a median of 4 MMSE scores (range 2-17). We used linear mixed models with sex and age as covariates to investigate whether MBs influenced the rate of cognitive decline. Mean age was 68 ± 9 years, 109 (49%) patients were female, and the baseline MMSE score was 22 ± 4. There were 39 patients (18%) with MBs (median 2, range 1-27) and 182 without. Linear mixed models showed that overall patients declined 2 MMSE points per year. We found no association of the presence of MBs with baseline MMSE or change in MMSE. Adjustment for atrophy, white matter hyperintensities, lacunes, and vascular risk factors did not change the results nor did stratification for MB location, APOE ε4 carriership, or age at onset (≤65 years vs >65 years). Repeating the analyses with number of MBs as predictor rendered similar results. MBs did not influence the rate of cognitive decline in patients with AD. The formerly reported increased risk of mortality in patients with MBs seems not to be attributable to a steeper rate of decline per se but might be due to vascular events, including (hemorrhagic) stroke.

Validity of a semantically cued recall procedure for the mini-mental state examination.

PubMed

Yuspeh, R L; Vanderploeg, R D; Kershaw, D A

1998-10-01

The validity of supplementing the three-item recall portion of the Mini-Mental State Examination (MMSE) with a cued recall procedure to help specify the nature of patients' memory problems was examined. Subjects were 247 individuals representing three diagnostic groups: Alzheimer's disease (AD), subcortical vascular ischemic dementia (SVaD), and normal controls. Individuals were administered a battery of neuropsychological tests, including the MMSE, as part of a comprehensive evaluation for the presence of dementia or other neurologic disorder. MMSE performance differed among groups. The three-item free recall performance also differed among groups, with post hoc analyses revealing the AD and SVaD groups were more impaired than controls but did not differ significantly from each other. Following a cued recall procedure of the MMSE three-items, groups differed, with post hoc analyses showing that AD patients failed to benefit from cues, whereas SVaD patients performed significantly better and comparable to control subjects. Significant correlations between the MMSE three-item cued recall performance and other memory measures demonstrated concurrent validity. Consistent with previous research indicating that SVaD is associated with memory encoding and retrieval deficits, whereas AD is associated with consolidation and storage problems, the present study supported the validity of the cued recall procedure of the three items on the MMSE in helping to distinguish between patients with AD and those with a vascular dementia with primarily subcortical pathology; however, despite these findings, a more extensive battery of neuropsychological measures is still recommended to consistently assess subtle diagnostic differences in these memory processes.

Describing the Sequence of Cognitive Decline in Alzheimer's Disease Patients: Results from an Observational Study.

PubMed

Henneges, Carsten; Reed, Catherine; Chen, Yun-Fei; Dell'Agnello, Grazia; Lebrec, Jeremie

2016-01-01

Improved understanding of the pattern of cognitive decline in Alzheimer's disease (AD) would be useful to assist primary care physicians in explaining AD progression to patients and caregivers. To identify the sequence in which cognitive abilities decline in community-dwelling patients with AD. Baseline data were analyzed from 1,495 patients diagnosed with probable AD and a Mini-Mental State Examination (MMSE) score ≤ 26 enrolled in the 18-month observational GERAS study. Proportional odds logistic regression models were applied to model MMSE subscores (orientation, registration, attention and concentration, recall, language, and drawing) and the corresponding subscores of the cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog), using MMSE total score as the index of disease progression. Probabilities of impairment start and full impairment were estimated at each MMSE total score level. From the estimated probabilities for each MMSE subscore as a function of the MMSE total score, the first aspect of cognition to start being impaired was recall, followed by orientation in time, attention and concentration, orientation in place, language, drawing, and registration. For full impairment in subscores, the sequence was recall, drawing, attention and concentration, orientation in time, orientation in place, registration, and language. The sequence of cognitive decline for the corresponding ADAS-cog subscores was remarkably consistent with this pattern. The sequence of cognitive decline in AD can be visualized in an animation using probability estimates for key aspects of cognition. This might be useful for clinicians to set expectations on disease progression for patients and caregivers.

Cereal Intake Increases and Dairy Products Decrease Risk of Cognitive Decline among Elderly Female Japanese.

PubMed

Otsuka, R; Kato, Y; Nishita, Y; Tange, C; Nakamoto, M; Tomida, M; Imai, T; Ando, F; Shimokata, H

2014-01-01

If cognitive decline can be prevented through changes in daily diet with no medical intervention, it will be highly significant for dementia prevention. This longitudinal study examined the associations of different food intakes on cognitive decline among Japanese subjects. Prospective cohort study. The National Institute for Longevity Sciences - Longitudinal Study of Aging, a community-based study. Participants included 298 males and 272 females aged 60 to 81 years at baseline who participated in the follow-up study (third to seventh wave) at least one time. Cognitive function was assessed with the Mini-Mental State Examination (MMSE) in all study waves. Nutritional intake was assessed using a 3-day dietary record in the second wave. Cumulative data among participants with an MMSE >27 in the second wave were analyzed using a generalized estimating equation. Multivariate adjusted odds ratios (OR) and 95% confidence intervals (CI) for an MMSE score ≤27 in each study wave according to a 1 standard deviation (SD) increase of each food intake at baseline were estimated, after adjusting for age, follow-up time, MMSE score at baseline, education, body mass index, annual household income, current smoking status, energy intake, and history of diseases. In men, after adjusting for age, and follow-up period, MMSE score at baseline, the adjusted OR for a decline in MMSE score was 1.20 (95% CI, 1.02-1.42; p=0.032) with a 1-SD increase in cereal intake. After adjusting for education and other confounding variables, the OR for a decrease in MMSE score did not reach statistical significance for this variable. In women, multivariate adjusted OR for MMSE decline was 1.43 (95% CI, 1.15-1.77; p=0.001) with a 1-SD increase in cereal intake and 0.80 (95% CI, 0.65-0.98; p=0.034) with a 1-SD increase in milk and dairy product intake. This study indicates that a 1-SD (108 g/day) decrease in cereal intake and a 1-SD (128 g/day) increase in milk and dairy product intake may have an influence of cognitive decline in community-dwelling Japanese women aged 60 years and older. Further studies are needed in order to explore the potential causal relationship.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

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

Malinowski, Kathleen T.; Fischell Department of Bioengineering, University of Maryland, College Park, MD; McAvoy, Thomas J.

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precisionmore » in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.« less

Three filters for visualization of phase objects with large variations of phase gradients

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

Sagan, Arkadiusz; Antosiewicz, Tomasz J.; Szoplik, Tomasz

2009-02-20

We propose three amplitude filters for visualization of phase objects. They interact with the spectra of pure-phase objects in the frequency plane and are based on tangent and error functions as well as antisymmetric combination of square roots. The error function is a normalized form of the Gaussian function. The antisymmetric square-root filter is composed of two square-root filters to widen its spatial frequency spectral range. Their advantage over other known amplitude frequency-domain filters, such as linear or square-root graded ones, is that they allow high-contrast visualization of objects with large variations of phase gradients.

Spiral tracing on a touchscreen is influenced by age, hand, implement, and friction.

PubMed

Heintz, Brittany D; Keenan, Kevin G

2018-01-01

Dexterity impairments are well documented in older adults, though it is unclear how these influence touchscreen manipulation. This study examined age-related differences while tracing on high- and low-friction touchscreens using the finger or stylus. 26 young and 24 older adults completed an Archimedes spiral tracing task on a touchscreen mounted on a force sensor. Root mean square error was calculated to quantify performance. Root mean square error increased by 29.9% for older vs. young adults using the fingertip, but was similar to young adults when using the stylus. Although other variables (e.g., touchscreen usage, sensation, and reaction time) differed between age groups, these variables were not related to increased error in older adults while using their fingertip. Root mean square error also increased on the low-friction surface for all subjects. These findings suggest that utilizing a stylus and increasing surface friction may improve touchscreen use in older adults.

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Self-administered Gerocognitive Examination (SAGE): a brief cognitive assessment Instrument for mild cognitive impairment (MCI) and early dementia.

PubMed

Scharre, Douglas W; Chang, Shu-Ing; Murden, Robert A; Lamb, James; Beversdorf, David Q; Kataki, Maria; Nagaraja, Haikady N; Bornstein, Robert A

2010-01-01

To develop a self-administered cognitive assessment instrument to facilitate the screening of mild cognitive impairment (MCI) and early dementia and determine its association with gold standard clinical assessments including neuropsychologic evaluation. Adults aged above 59 years with sufficient vision and English literacy were recruited from geriatric and memory disorder clinics, educational talks, independent living facilities, senior centers, and memory screens. After Self-administered Gerocognitive Examination (SAGE) screening, subjects were randomly selected to complete a clinical evaluation, neurologic examination, neuropsychologic battery, functional assessment, and mini-mental state examination (MMSE). Subjects were identified as dementia, MCI, or normal based on standard clinical criteria and neuropsychologic testing. Two hundred fifty-four participants took the SAGE screen and 63 subjects completed the extensive evaluation (21 normal, 21 MCI, and 21 dementia subjects). Spearman rank correlation between SAGE and neuropsychologic battery was 0.84 (0.76 for MMSE). SAGE receiver operating characteristics on the basis of clinical diagnosis showed 95% specificity (90% for MMSE) and 79% sensitivity (71% for MMSE) in detecting those with cognitive impairment from normal subjects. This study suggests that SAGE is a reliable instrument for detecting cognitive impairment and compares favorably with the MMSE. The self-administered feature may promote cognitive testing by busy clinicians prompting earlier diagnosis and treatment.

A comparative study of behavioral and psychological symptoms of dementia in patients with Alzheimer's disease and vascular dementia referred to psychogeriatric services in Korea and the U.K.

PubMed

Shah, Ajit; Ellanchenny, Nalini; Suh, Guk-Hee

2005-06-01

There is a paucity of cross-cultural studies of behavioral and psychological symptoms of dementia (BPSD). BPSD were examined in consecutive series of referrals to a psychogeriatric service in Korea and the U.K. using the Behavioral Pathology in Alzheimer's Disease (BEHAVE-AD) rating scale and the Cornell Scale for Depression in Dementia (CSDD). Results were analyzed separately for Alzheimer's disease and vascular dementia. Koreans in both diagnostic groups had lower Mini-mental State Examination (MMSE) scores and higher BEHAVE-AD total and subscale scores for most subscales. In both countries, for both diagnostic groups, the total BEHAVE-AD score and several subscale scores were negatively correlated with the MMSE scores. Logistic regression analysis for Alzheimer's disease revealed that BEHAVE-AD total and most subscale scores independently predicted the country of origin in addition to the MMSE scores predicting the same. These differences in BPSD are most likely explained by the lower MMSE scores in the Korean sample. However, genuine differences in BPSD between the two countries can only be critically examined in a cross-cultural population-based epidemiological study for both diagnostic categories using validated instruments to measure BPSD and controlling for the influence of MMSE score.

Mini-Mental State Exam performance of older African Americans: effect of age, gender, education, hypertension, diabetes, and the inclusion of serial 7s subtraction versus "world" backward on score.

PubMed

Hawkins, Keith A; Cromer, Jennifer R; Piotrowski, Andrea S; Pearlson, Godfrey D

2011-11-01

The Mini-Mental State Exam (MMSE) is a clinically ubiquitous yet incompletely standardized instrument. Though the test offers considerable examiner leeway, little data exist on the normative consequences of common administration variations. We sought to: (a) determine the effects of education, age, gender, health status, and a common administration variation (serial 7s subtraction vs. "world" spelled backward) on MMSE score within a minority sample, (b) provide normative data stratified on the most empirically relevant bases, and (c) briefly address item failure rates. African American citizens (N = 298) aged 55-87 living independently in the community were recruited by advertisement, community recruitment, and word of mouth. Total score with "world" spelled backward exceeded total score with serial 7s subtraction across all levels of education, replicating findings in Caucasian samples. Education is the primary source of variance on MMSE score, followed by age. In this cohort, women out-performed men when "world" spelled backward was included, but there was no gender effect when serial 7s subtraction was included in MMSE total score. To ensure an appropriate interpretation of MMSE scores, reports, whether clinical or in publications of research findings, should be explicit regarding the administration method. Stratified normative data are provided.

[Association between cerumen impaction, cognitive function and hearing in Japanese elderly].

PubMed

Sugiura, Saiko; Uchida, Yasue; Nakashima, Tsutomu; Nishita, Yukiko; Tange, Chikako; Ando, Fujiko; Shimokata, Hiroshi

2012-01-01

In this study we aimed to evaluate the frequency of cerumen impaction in Japanese elderly and clarify the associations between cerumen, cognitive function, and hearing impairment. The subjects enrolleded in this study were participants in the National Institute for Longevity Sciences, Longitudinal Study of Aging (NILS-LSA). The data of 792 community-dwelling participants aged 60 to 88 years old were collected. All had taken the Mini-Mental State Examination (MMSE) and had undergone pure tone audiometry (PTA) assessment and video recording of an otoscopic examination. We then analyzed associations between the incidence of the cerumen impaction of better-hearing ear, hearing level and MMSE scores using a general linear model. Cerumen impaction of the better-hearing ear was observed in 10.7% of all participants. In participants with an MMSE score of less than 24, the frequency of cerumen impaction was 23.3%. Cerumen was significant associated with poorer hearing after adjustment for sex and age (p=0.0001). Cerumen impaction also showed a significant association with a low MMSE score after adjustment for sex, age, hearing level and education (p=0.02). The frequency of cerumen impaction in Japanese elderly was estimated to be approximately 10%. The existence of cerumen impaction was associated with poorer hearing level and lower MMSE score.

Evaluation of the Addenbrooke's Cognitive Examination's validity in a brain injury rehabilitation setting.

PubMed

Gaber, Tarek A-Z K

2008-07-01

Several reports have warned of the Mini Mental State Examination's (MMSE) inability to detect gross memory and high executive impairments. Addenbrooke's Cognitive Examination-Revised (ACE-R) has gained enormous popularity in dementia screening as it addresses the main shortcomings of MMSE. This study aimed at evaluating the use of ACE-R and to establish its sensitivity compared to MMSE in a cohort of brain injury patients. ACE-R was administered to a cohort of chronic brain injury patients. All patients had a cognitive impairment which was severe enough to prevent them working or studying. Patients with significant mental health, sensory, communication or physical impairments were excluded. Thirty-six patients were recruited, 31 males with a mean age of 37 years. For an upper cut-off value of 27/30 for MMSE and 88/100 for ACE-R, their sensitivities were 36% and 72%, respectively. For a lower cut-off value of 24/30 and 82/100 the tests sensitivities were 11% and 56%, respectively. Analysis of the ACE-R sub-tests indicated that memory and verbal fluency sub-tests showed the most dramatic impairment. MMSE is insensitive as a screening test in brain injury patients. The results show ACE-R to be a sensitive, easily administered test.

Interleukin-6 is associated with cognitive function: the Northern Manhattan Study

PubMed Central

Wright, C.B.; Sacco, R.L.; Rundek, T.R.; Delman, J.B.; Rabbani, L.E.; Elkind, M.S.V.

2006-01-01

Background and purpose Inflammation has been linked to cognitive decline and dementia but the mechanism is not clear and few studies have included Hispanic and black subjects that may be at increased risk of these disorders. Methods We performed a cross-sectional analysis of the association between inflammatory marker levels and cognition in the stroke-free population-based cohort of the Northern Manhattan Study. Mini Mental State Exam (MMSE) scores were the continuous outcome and we adjusted for sociodemographic and vascular risk factors as well as subclinical atherosclerosis. Results Of the inflammatory markers, only interleukin (IL)-6 levels were associated with the MMSE. In univariate analysis age, hypertension, diabetes, smoking, moderate alcohol use, total homocysteine, carotid intima media thickness, and body mass index were positively associated with IL-6 levels. Hispanics compared to whites, those with less than a high school education, hypertension, cardiac disease, and total homocysteine were associated with lower MMSE scores. In a multivariate linear regression model, IL-6 was negatively associated with MMSE score adjusting for sociodemographic and vascular risk factors. Conclusions IL-6 levels were negatively associated with performance on the MMSE in this multiethnic cohort. Adjusting for vascular disease and subclinical atherosclerosis did not attenuate the association, suggesting a direct effect on the brain. PMID:16501663

Hypothesis Testing Using Factor Score Regression

PubMed Central

Devlieger, Ines; Mayer, Axel; Rosseel, Yves

2015-01-01

In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and with structural equation modeling (SEM) by using analytic calculations and two Monte Carlo simulation studies to examine their finite sample characteristics. Several performance criteria are used, such as the bias using the unstandardized and standardized parameterization, efficiency, mean square error, standard error bias, type I error rate, and power. The results show that the bias correcting method, with the newly developed standard error, is the only suitable alternative for SEM. While it has a higher standard error bias than SEM, it has a comparable bias, efficiency, mean square error, power, and type I error rate. PMID:29795886

Some Results on Mean Square Error for Factor Score Prediction

ERIC Educational Resources Information Center

Krijnen, Wim P.

2006-01-01

For the confirmatory factor model a series of inequalities is given with respect to the mean square error (MSE) of three main factor score predictors. The eigenvalues of these MSE matrices are a monotonic function of the eigenvalues of the matrix gamma[subscript rho] = theta[superscript 1/2] lambda[subscript rho] 'psi[subscript rho] [superscript…

Weighted linear regression using D2H and D2 as the independent variables

Treesearch

Hans T. Schreuder; Michael S. Williams

1998-01-01

Several error structures for weighted regression equations used for predicting volume were examined for 2 large data sets of felled and standing loblolly pine trees (Pinus taeda L.). The generally accepted model with variance of error proportional to the value of the covariate squared ( D2H = diameter squared times height or D...

The Relationship between Root Mean Square Error of Approximation and Model Misspecification in Confirmatory Factor Analysis Models

ERIC Educational Resources Information Center

Savalei, Victoria

2012-01-01

The fit index root mean square error of approximation (RMSEA) is extremely popular in structural equation modeling. However, its behavior under different scenarios remains poorly understood. The present study generates continuous curves where possible to capture the full relationship between RMSEA and various "incidental parameters," such as…

A method of bias correction for maximal reliability with dichotomous measures.

PubMed

Penev, Spiridon; Raykov, Tenko

2010-02-01

This paper is concerned with the reliability of weighted combinations of a given set of dichotomous measures. Maximal reliability for such measures has been discussed in the past, but the pertinent estimator exhibits a considerable bias and mean squared error for moderate sample sizes. We examine this bias, propose a procedure for bias correction, and develop a more accurate asymptotic confidence interval for the resulting estimator. In most empirically relevant cases, the bias correction and mean squared error correction can be performed simultaneously. We propose an approximate (asymptotic) confidence interval for the maximal reliability coefficient, discuss the implementation of this estimator, and investigate the mean squared error of the associated asymptotic approximation. We illustrate the proposed methods using a numerical example.

On the appropriateness of applying chi-square distribution based confidence intervals to spectral estimates of helicopter flyover data

NASA Technical Reports Server (NTRS)

Rutledge, Charles K.

1988-01-01

The validity of applying chi-square based confidence intervals to far-field acoustic flyover spectral estimates was investigated. Simulated data, using a Kendall series and experimental acoustic data from the NASA/McDonnell Douglas 500E acoustics test, were analyzed. Statistical significance tests to determine the equality of distributions of the simulated and experimental data relative to theoretical chi-square distributions were performed. Bias and uncertainty errors associated with the spectral estimates were easily identified from the data sets. A model relating the uncertainty and bias errors to the estimates resulted, which aided in determining the appropriateness of the chi-square distribution based confidence intervals. Such confidence intervals were appropriate for nontonally associated frequencies of the experimental data but were inappropriate for tonally associated estimate distributions. The appropriateness at the tonally associated frequencies was indicated by the presence of bias error and noncomformity of the distributions to the theoretical chi-square distribution. A technique for determining appropriate confidence intervals at the tonally associated frequencies was suggested.

Delayed Recall and Working Memory MMSE Domains Predict Delirium following Cardiac Surgery.

PubMed

Price, Catherine C; Garvan, Cynthia; Hizel, Loren P; Lopez, Marcos G; Billings, Frederic T

2017-01-01

Reduced preoperative cognition is a risk factor for postoperative delirium. The significance for type of preoperative cognitive deficit, however, has yet to be explored and could provide important insights into mechanisms and prediction of delirium. Our goal was to determine if certain cognitive domains from the general cognitive screener, the Mini-Mental State Exam (MMSE), predict delirium after cardiac surgery. Patients completed a preoperative MMSE prior to undergoing elective cardiac surgery. Following surgery, delirium was assessed throughout ICU stay using the Confusion Assessment Method for ICU delirium and the Richmond Agitation and Sedation Scale. Cardiac surgery patients who developed delirium (n = 137) had lower total MMSE scores than patients who did not develop delirium (n = 457). In particular, orientation to place, working memory, delayed recall, and language domain scores were lower. Of these, only the working memory and delayed recall domains predicted delirium in a regression model adjusting for history of chronic obstructive pulmonary disease, age, sex, and duration of cardiopulmonary bypass. For each word not recalled on the three-word delayed recall assessment, the odds of delirium increased by 50%. For each item missed on the working memory index, the odds of delirium increased by 36%. Of the patients who developed delirium, 47% had a primary impairment in memory, 21% in working memory, and 33% in both domains. The area under the receiver operating characteristics curve using only the working memory and delayed recall domains was 0.75, compared to 0.76 for total MMSE score. Delirium risk is greater for individuals with reduced MMSE scores on the delayed recall and working memory domains. Research should address why patients with memory and executive vulnerabilities are more prone to postoperative delirium than those with other cognitive limitations.

Comparison of two commonly used clinical cognitive screening tests to diagnose mild cognitive impairment in heart failure with the golden standard European Consortium Criteria.

PubMed

Alagiakrishnan, Kannayiram; Mah, Darren; Dyck, Jason R B; Senthilselvan, Ambikaipakan; Ezekowitz, Justin

2017-02-01

This study on mild cognitive impairment (MCI) in heart failure (HF) compares the utility of Montreal Cognitive Assessment (MoCA) to the Mini-Mental Status Exam (MMSE) for diagnosing MCI in a HF population when compared to the golden standard European Consortium Criteria (ECC). Participants were recruited from the Alberta HEART study at the Mazankowski Alberta Heart Institute in Edmonton and St. Mary's hospital in Camrose. This study enrolled 53 community adults aged>50years: 33 HF and 20 controls. Participants were assessed using both the MMSE and MoCA for MCI. MCI was diagnosed using the golden standard, European Consortium Criteria. Sensitivity and specificity analysis, positive and negative predictive values, likelihood ratios and kappa statistic were calculated. The mean age was 72.8years (SD 8.4), 60.4% were females and 34% had underlying ischemic heart disease. Overall, two thirds of patients (22/33, 66%) with HF had MCI. In comparison to European Consortium Criteria, the sensitivity and specificity of MoCA were 82% and 91% in identifying individuals with MCI, and MMSE were 9% and 91%, respectively. The positive and negative predictive values for MoCA were 95% and 71%, and for MMSE were 67% and 33%, respectively. Kappa statistics showed good agreement between MoCA and consortium criteria (kappa=0.68) and a low agreement between MMSE and consortium criteria (kappa=0.07). Cognitive dysfunction is common in patients with HF. Overall, the MoCA seems to be a better screening tool than MMSE for MCI in HF patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Influence of habitual chocolate consumption over the Mini-Mental State Examination in Spanish older adults].

PubMed

Orozco Arbelaez, Edilbeto; Banegas, José Ramón; Rodríguez Artalejo, Fernando; López García, Esther

2017-07-28

There are associations described between dementia, mild cognitive impairment (MCI) and foods with a high content of polyphenols. To assess the infl uence of habitual chocolate consumption over the MMSE in Spanish older adults. Cross-sectional study, using data of the follow-up of the Seniors-Study on Nutrition and Cardiovascular Risk in Spain (ENRICA) cohort. Habitual chocolate consumption in the last year was assessed with a computerized dietary history; differences between dark chocolate and milk chocolate were recorded. Chocolate intake was classified into the following categories: no consumption, < 10 g/day, and ≥ 10 g/day. Validated MMSE scores for Spain were obtained during an interview and different cutoff points were used to define ≤ 25, ≤ 24 and ≤ 23. Linear and logistic regression models were used to calculate adjusted beta coefficients and odds ratios (OR). Compared to non-consumers, participants with a habitual chocolate consumption of ≥ 10 g/d had a better MMSE score (adjusted beta coefficient and 95% confidence interval: 0.26 (0.02-0.50; p trend = 0.05); for dark chocolate, the results were also statistically significant (0.48 [0.18-0.78]; p trend < 0.001). Total chocolate consumption was not associated with higher likelihood of having MCI. However, dark chocolate consumption was associated with less likelihood of MCI (OR and 95%CI for MMSE ≤ 25: 0.39 [0.20-0.77]; for MMSE ≤ 24: 0.26 [0.10-0.67]; and for MMSE ≤ 23: 0.25 [0.07-0.82]). Our results suggest that habitual dark chocolate consumption might improve cognitive function among the older population.

Cognitive impairment, the Mini-Mental State Examination and socio-demographic and dental variables in the elderly in Brazil.

PubMed

Miranda, Leonardo de Paula; Silveira, Marise F; Oliveira, Thatiane L; Alves, Sâmia F F; Júnior, Hercílio M; Batista, André U D; Bonan, Paulo R F

2012-06-01

Dementia, a syndrome characterised by multiple cognitive impairments, is an increasing medical and social problem across the world. The Mini-Mental State Examination (MMSE) is the instrument most often used in the evaluation of cognitive compromise and dementia in elderly individuals. It is noteworthy that there is a scarcity of works in the literature on the dimensions of the MMSE and its relation to dental variables in the elderly. To evaluate the condition of cognitive impairment, the dimensions of the MMSE, and the latter's relation to socio-demographic and dental variables in elderly individuals of Montes Claros, Minas Gerais, Brazil. This is a cross-sectional descriptive study, whereby 218 elderly users of the system were evaluated at the Sistema Único de Saúde (Brazilian health service) in Montes Claros. The collection of data involved the realisation of structured interviews and clinical dentistry examinations. The screening of cognitive impairment was carried out with the Portuguese version of MMSE. The data were subjected to descriptive and bivariate analyses. The prevalence of cognitive impairment found was 6.4%. A statistically significant association was observed between cognitive decline and age, marital status and use of dental prostheses. An association was also noted between several dimensions of MMSE and edentulism (time orientation, attention and calculation, and final score) and use of prostheses (except evocation memory and language). It was noticed that those who were 80 years old or more, not married and using prostheses were more likely to manifest cognitive impairment. Associations between some MMSE dimensions were established, including the final score, with edentulism and the use of prostheses. © 2011 The Gerodontology Society and John Wiley & Sons A/S.

Methylphenidate hydrochloride improves cognitive function in patients with advanced cancer and hypoactive delirium: a prospective clinical study

PubMed Central

Gagnon, Bruno; Low, Graeme; Schreier, Gil

2005-01-01

Objective To investigate the clinical improvement observed in patients with advanced cancer and hypoactive delirium after the administration of methylphenidate hydrochloride. Methods Fourteen patients with advanced cancer and hypoactive delirium were seen between March 1999 and August 2000 at the Palliative Care Day Hospital and the inpatient Tertiary Palliative Care Unit of Montreal General Hospital, Montréal. They were chosen for inclusion in a prospective clinical study on the basis of (1) cognitive failure documented by the Mini-Mental State Examination (MMSE), (2) sleep–wake pattern disturbances, (3) psychomotor retardation, (4) absence of delusions or hallucinations, and (5) absence of an underlying cause to explain the delirium. All patients were treated with methylphenidate, and changes in their cognitive function were measured using the MMSE. Results All 14 patients showed improvement in their cognitive function as documented by the MMSE. The median pretreatment MMSE score (maximum score 30) was 21 (mean 20.9, standard deviation [SD] 4.9), which improved to a median of 27 (mean 24.9, SD 4.7) after the first dose of methylphenidate (p < 0.001, matched, paired Wilcoxon signed rank test). One patient died before reaching a stable dose of methylphenidate. In the other 13 patients, the median MMSE score further improved to 28 (mean 27.8, SD 2.4) (p = 0.02 compared with the median MMSE score documented 1 hour after the first dose of methylphenidate). All patients showed an improvement in psychomotor activities. Conclusions Hypoactive delirium that cannot be explained by an underlying cause (metabolic or drug-induced) in patients with advanced cancer appears to be a specific syndrome that could be improved by the administration of methylphenidate. PMID:15798785

Eta Squared, Partial Eta Squared, and Misreporting of Effect Size in Communication Research.

ERIC Educational Resources Information Center

Levine, Timothy R.; Hullett, Craig R.

2002-01-01

Alerts communication researchers to potential errors stemming from the use of SPSS (Statistical Package for the Social Sciences) to obtain estimates of eta squared in analysis of variance (ANOVA). Strives to clarify issues concerning the development and appropriate use of eta squared and partial eta squared in ANOVA. Discusses the reporting of…

Usefulness of the Montreal Cognitive Assessment (MoCA) in Huntington's disease.

PubMed

Gluhm, Shea; Goldstein, Jody; Brown, Daniel; Van Liew, Charles; Gilbert, Paul E; Corey-Bloom, Jody

2013-10-01

The Montreal Cognitive Assessment (MoCA) is a brief screening instrument for dementia that is sensitive to executive dysfunction. This study examined its usefulness for assessing cognitive performance in mild, moderate, and severe Huntington's disease (HD), compared with the use of the Mini-Mental State Examination (MMSE). We compared MoCA and MMSE total scores and the number of correct answers in 5 cognitive-specific domains in 104 manifest HD patients and 100 matched controls. For the total HD sample, and for the moderate and severe patients, significant differences between both MoCA and MMSE total scores and almost all cognitive-specific domains emerged. Even mild HD subjects showed significant differences with regard to total score and several cognitive domains on both instruments. We conclude that the MoCA, although not necessarily superior to the MMSE, is a useful instrument for assessing cognitive performance over a broad level of functioning in HD. © 2013 Movement Disorder Society.

Normative data for the Tygerberg Cognitive Battery and Mini-Mental Status Examination in a South African population.

PubMed

Roos, Annerine; Calata, Dorothy; Jonkers, Liesl; Maritz, Stephan J; Kidd, Martin; Daniels, Willie M U; Hugo, Frans J

2010-01-01

Normative data for the Tygerberg Cognitive Battery (TCB) and Mini-Mental Status Examination (MMSE) (in South Africa) have not been formally examined before. The TCB was developed for the bedside pen-and-paper screening of cognitive impairment in each of the 6 main cognitive domains, including attention and concentration, speech, memory, praxis, gnosis, and executive functioning. The test is also used to diagnose different neuropsychiatric conditions. The MMSE is an established screen of cognitive status, which is often used as a comparative standard for novel screening tests such as the TCB. The TCB was initially developed in English and Afrikaans, and a Xhosa version was also initiated with this study so that the 3 most common languages of the region could be accommodated. The first aim of the study was to estimate normative test performance on the TCB and MMSE among controls, and the second aim was to develop a Xhosa version of the TCB. Assessments of the TCB and MMSE were carried out in a population of healthy individuals (n = 157). In addition, healthy Xhosa-speaking participants (n = 14) were screened using a Xhosa version of the TCB. Reliability scores for all forms of the TCB were satisfactory. Age and education correlated significantly with TCB scores (r = -0.26, P < .01; r = 0.64, P < .01, respectively), whereas only education significantly correlated with MMSE scores (r = 0.32, P < .05). Normative values were calculated accordingly, that is, controlled for the effects of age and education. The TCB scores also correlated significantly with MMSE scores (r = 0.49, P < .05), demonstrating the potential of the TCB to serve as an alternate cognitive assessment tool, along with the MMSE, to focus neuropsychiatric investigations. Scores on the Xhosa version differed significantly on speech, praxis, and gnosis between the Afrikaans and English participant scores. These normative data can be used to increase precision and to provide an impartial evaluation when applying TCB to evaluate the cognitive ability of neuropsychiatrically impaired adult patients. However, age and education effects should be considered when computing the results of cognitive assessment. Copyright 2010 Elsevier Inc. All rights reserved.

Glucose impairment and ghrelin gene variants are associated to cognitive dysfunction.

PubMed

Mora, M; Mansego, M L; Serra-Prat, M; Palomera, E; Boquet, X; Chaves, J F; Puig-Domingo, M

2014-04-01

Cognitive state and brain volume have been related to body mass index, abdominal fat, waist-hip ratio, components of metabolic syndrome (MS) and ghrelin. Genetic variations within the ghrelin gene have been recently associated to MS. The aim of our study was to investigate cognitive state by Mini-Mental State Examination (MMSE) in relation to MS components (ATP-III criteria) and ghrelin gene polymorphisms in dwelling individuals aged ≥70. 280 subjects (137 men/143 women, age 77.03 ± 5.92) from the Mataró Ageing Study were included. Individuals were phenotypically characterized by anthropometric variables, lipids, glucose, blood pressure and MMSE. SNPs -501AC (rs26802), -994CT (rs26312), -604GA (rs27647), M72L (rs696217) and L90G (rs4684677) of the ghrelin gene were studied. Genotypes were determined by polymerase chain reaction and SNapshot minisequencing. 22.1 % had MMSE <24. MMSE <24 was associated with age (p < 0.001), female gender (p = 0.016), low education (p < 0.001) and glucose impairment or diabetes (p = 0.040). MMSE was influenced by obesity, central obesity, MS and glucose impairment. This latter association remained significant after adjustment by gender, age, alcohol, educational level, GDS and ApoE genotype (p = 0.009). Ghrelin SNPs were associated to MMSE: M72L C/A genotype showed lower score than C/C (p = 0.032, after adjusting for confounders 0.049); L90G A/T genotype showed lower score than A/A (p = 0.054, after adjusting 0.005). MMSE <24 was associated to L90G (39.1 % in A/T genotype vs 19.3 % in A/A, p = 0.026, after adjusting for confounders p = 0.002, OR 6.18 CI 1.93-21.75). Glucose impairment and L90G Ghrelin gene variant influence cognitive function in old dwelling individuals participating in the Mataró Ageing Study.

POOLMS: A computer program for fitting and model selection for two level factorial replication-free experiments

NASA Technical Reports Server (NTRS)

Amling, G. E.; Holms, A. G.

1973-01-01

A computer program is described that performs a statistical multiple-decision procedure called chain pooling. It uses a number of mean squares assigned to error variance that is conditioned on the relative magnitudes of the mean squares. The model selection is done according to user-specified levels of type 1 or type 2 error probabilities.

Validating Clusters with the Lower Bound for Sum-of-Squares Error

ERIC Educational Resources Information Center

Steinley, Douglas

2007-01-01

Given that a minor condition holds (e.g., the number of variables is greater than the number of clusters), a nontrivial lower bound for the sum-of-squares error criterion in K-means clustering is derived. By calculating the lower bound for several different situations, a method is developed to determine the adequacy of cluster solution based on…

A suggestion for computing objective function in model calibration

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang

2014-01-01

A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).

Efficacy of acetylcholinesterase inhibitors versus nootropics in Alzheimer's disease: a retrospective, longitudinal study.

PubMed

Tsolaki, M; Pantazi, T; Kazis, A

2001-01-01

The aim of this study was to investigate the efficacy of nootropics (piracetam, aniracetam, nimodopine and dihydroergicristine) versus acetylcholinesterase inhibitors (AChE-Is) (tacrine and donepezil) in the treatment of Alzheimer's disease. This is a retrospective study of 510 patients with Alzheimer's disease. To determine clinical efficacy of treatment, we used the mean change over time in scores for the following tests: the Mini-Mental State Examination (MMSE); the Cambridge Cognitive Examination for the Elderly; and the Functional Rating Scale for Symptoms of Dementia. In all patients and in patients with severe Alzheimer's disease (baseline MMSE < 11), no significant differences were seen in the neuropsychological test scores between the two treatment groups. In patients with moderate dementia (baseline MMSE between 11 and 20), however, there was a significantly greater deterioration, as shown on the CAMCOG scale, after 12 months' treatment for patients receiving AChE-Is compared with those receiving nootropics (-4.38 for AChE-Is group versus 1.48 for nootropics group). For patients with mild dementia (baseline MMSE score between 21 and 26), there was a significantly greater deterioration on the MMSE scale for each time-point in the nootropics group compared with the AChE-Is group. In conclusion, we did not find any strong evidence that a difference in efficacy exists between AChE-Is and nootropics in the treatment of Alzheimer's disease.

Cognitive Function in Ambulatory Patients with Systolic Heart Failure: Insights from the Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) Trial

PubMed Central

Graham, Susan; Ye, Siqin; Qian, Min; Sanford, Alexandra R.; Di Tullio, Marco R.; Sacco, Ralph L.; Mann, Douglas L.; Levin, Bruce; Pullicino, Patrick M.; Freudenberger, Ronald S.; Teerlink, John R.; Mohr, J. P.; Labovitz, Arthur J.; Lip, Gregory Y. H.; Estol, Conrado J.; Lok, Dirk J.; Ponikowski, Piotr; Anker, Stefan D.; Thompson, John L. P.; Homma, Shunichi

2014-01-01

We sought to determine whether cognitive function in stable outpatients with heart failure (HF) is affected by HF severity. A retrospective, cross-sectional analysis was performed using data from 2, 043 outpatients with systolic HF and without prior stroke enrolled in the Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) Trial. Multivariable regression analysis was used to assess the relationship between cognitive function measured using the Mini-Mental Status Exam (MMSE) and markers of HF severity (left ventricular ejection fraction [LVEF], New York Heart Association [NYHA] functional class, and 6-minute walk distance). The mean (SD) for the MMSE was 28.6 (2.0), with 64 (3.1%) of the 2,043 patients meeting the cut-off of MMSE <24 that indicates need for further evaluation of cognitive impairment. After adjustment for demographic and clinical covariates, 6-minute walk distance (β-coefficient 0.002, p<0.0001), but not LVEF or NYHA functional class, was independently associated with the MMSE as a continuous measure. Age, education, smoking status, body mass index, and hemoglobin level were also independently associated with the MMSE. In conclusion, six-minute walk distance, but not LVEF or NYHA functional class, was an important predictor of cognitive function in ambulatory patients with systolic heart failure. PMID:25426862

[Formula: see text]-regularized recursive total least squares based sparse system identification for the error-in-variables.

PubMed

Lim, Jun-Seok; Pang, Hee-Suk

2016-01-01

In this paper an [Formula: see text]-regularized recursive total least squares (RTLS) algorithm is considered for the sparse system identification. Although recursive least squares (RLS) has been successfully applied in sparse system identification, the estimation performance in RLS based algorithms becomes worse, when both input and output are contaminated by noise (the error-in-variables problem). We proposed an algorithm to handle the error-in-variables problem. The proposed [Formula: see text]-RTLS algorithm is an RLS like iteration using the [Formula: see text] regularization. The proposed algorithm not only gives excellent performance but also reduces the required complexity through the effective inversion matrix handling. Simulations demonstrate the superiority of the proposed [Formula: see text]-regularized RTLS for the sparse system identification setting.

An algorithm for propagating the square-root covariance matrix in triangular form

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Choe, C. Y.

1976-01-01

A method for propagating the square root of the state error covariance matrix in lower triangular form is described. The algorithm can be combined with any triangular square-root measurement update algorithm to obtain a triangular square-root sequential estimation algorithm. The triangular square-root algorithm compares favorably with the conventional sequential estimation algorithm with regard to computation time.

Fitting a function to time-dependent ensemble averaged data.

PubMed

Fogelmark, Karl; Lomholt, Michael A; Irbäck, Anders; Ambjörnsson, Tobias

2018-05-03

Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion constants). A commonly overlooked challenge in such function fitting procedures is that fluctuations around mean values, by construction, exhibit temporal correlations. We show that the only available general purpose function fitting methods, correlated chi-square method and the weighted least squares method (which neglects correlation), fail at either robust parameter estimation or accurate error estimation. We remedy this by deriving a new closed-form error estimation formula for weighted least square fitting. The new formula uses the full covariance matrix, i.e., rigorously includes temporal correlations, but is free of the robustness issues, inherent to the correlated chi-square method. We demonstrate its accuracy in four examples of importance in many fields: Brownian motion, damped harmonic oscillation, fractional Brownian motion and continuous time random walks. We also successfully apply our method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software.

Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration.

PubMed

Parastar, Hadi; Mostafapour, Sara; Azimi, Gholamhasan

2016-01-01

Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make calibration samples. Appropriate statistical parameters of regression coefficient of 0.996-0.998, root-mean square error of prediction of 0.005-0.010 and relative error of prediction of 1.54-3.82% for the calibration set show the reliability of the developed method. In addition, the developed method is externally validated with three samples in validation set (with a relative error of prediction below 10.0%). Finally, to test the applicability of the proposed strategy for the analysis of real samples, five real gasoline samples collected from gas stations are used for this purpose and the gasoline proportions were in range of 70-85%. Also, the relative standard deviations were below 8.5% for different samples in the prediction set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Derivation of formulas for root-mean-square errors in location, orientation, and shape in triangulation solution of an elongated object in space

NASA Technical Reports Server (NTRS)

Long, S. A. T.

1974-01-01

Formulas are derived for the root-mean-square (rms) displacement, slope, and curvature errors in an azimuth-elevation image trace of an elongated object in space, as functions of the number and spacing of the input data points and the rms elevation error in the individual input data points from a single observation station. Also, formulas are derived for the total rms displacement, slope, and curvature error vectors in the triangulation solution of an elongated object in space due to the rms displacement, slope, and curvature errors, respectively, in the azimuth-elevation image traces from different observation stations. The total rms displacement, slope, and curvature error vectors provide useful measure numbers for determining the relative merits of two or more different triangulation procedures applicable to elongated objects in space.

Least-squares model-based halftoning

NASA Astrophysics Data System (ADS)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach permits the halftoner to be tuned to the individual printer, whose characteristics may vary considerably from those of other printers, for example, write-black vs. write-white laser printers.

Psychometric Properties of the Folstein Mini-Mental State Examination

ERIC Educational Resources Information Center

Lopez, Michael N.; Charter, Richard A.; Mostafavi, Beeta; Nibut, Lorraine P.; Smith, Whitney E.

2005-01-01

Criterion-referenced (Livingston) and norm-referenced (Gilmer-Feldt) techniques were used to measure the internal consistency reliability of Folsteins Mini-Mental State Examination (MMSE) on a large sample (N = 418) of elderly medical patients. Two administration and scoring variants of the MMSE Attention and Calculation section (Serial 7s only…

Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

PubMed Central

McGregor, Heather R.; Pun, Henry C. H.; Buckingham, Gavin; Gribble, Paul L.

2016-01-01

The human sensorimotor system is routinely capable of making accurate predictions about an object's weight, which allows for energetically efficient lifts and prevents objects from being dropped. Often, however, poor predictions arise when the weight of an object can vary and sensory cues about object weight are sparse (e.g., picking up an opaque water bottle). The question arises, what strategies does the sensorimotor system use to make weight predictions when one is dealing with an object whose weight may vary? For example, does the sensorimotor system use a strategy that minimizes prediction error (minimal squared error) or one that selects the weight that is most likely to be correct (maximum a posteriori)? In this study we dissociated the predictions of these two strategies by having participants lift an object whose weight varied according to a skewed probability distribution. We found, using a small range of weight uncertainty, that four indexes of sensorimotor prediction (grip force rate, grip force, load force rate, and load force) were consistent with a feedforward strategy that minimizes the square of prediction errors. These findings match research in the visuomotor system, suggesting parallels in underlying processes. We interpret our findings within a Bayesian framework and discuss the potential benefits of using a minimal squared error strategy. NEW & NOTEWORTHY Using a novel experimental model of object lifting, we tested whether the sensorimotor system models the weight of objects by minimizing lifting errors or by selecting the statistically most likely weight. We found that the sensorimotor system minimizes the square of prediction errors for object lifting. This parallels the results of studies that investigated visually guided reaching, suggesting an overlap in the underlying mechanisms between tasks that involve different sensory systems. PMID:27760821

Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks

NASA Astrophysics Data System (ADS)

Zhang, Ling; Cai, Yunlong; Li, Chunguang; de Lamare, Rodrigo C.

2017-12-01

In this work, we present low-complexity variable forgetting factor (VFF) techniques for diffusion recursive least squares (DRLS) algorithms. Particularly, we propose low-complexity VFF-DRLS algorithms for distributed parameter and spectrum estimation in sensor networks. For the proposed algorithms, they can adjust the forgetting factor automatically according to the posteriori error signal. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithms and derive mathematical expressions for the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed low-complexity VFF-DRLS algorithms achieve superior performance to the existing DRLS algorithm with fixed forgetting factor when applied to scenarios of distributed parameter and spectrum estimation. Besides, the simulation results also demonstrate a good match for our proposed analytical expressions.

Application of Rapid Visco Analyser (RVA) viscograms and chemometrics for maize hardness characterisation.

PubMed

Guelpa, Anina; Bevilacqua, Marta; Marini, Federico; O'Kennedy, Kim; Geladi, Paul; Manley, Marena

2015-04-15

It has been established in this study that the Rapid Visco Analyser (RVA) can describe maize hardness, irrespective of the RVA profile, when used in association with appropriate multivariate data analysis techniques. Therefore, the RVA can complement or replace current and/or conventional methods as a hardness descriptor. Hardness modelling based on RVA viscograms was carried out using seven conventional hardness methods (hectoliter mass (HLM), hundred kernel mass (HKM), particle size index (PSI), percentage vitreous endosperm (%VE), protein content, percentage chop (%chop) and near infrared (NIR) spectroscopy) as references and three different RVA profiles (hard, soft and standard) as predictors. An approach using locally weighted partial least squares (LW-PLS) was followed to build the regression models. The resulted prediction errors (root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP)) for the quantification of hardness values were always lower or in the same order of the laboratory error of the reference method. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Relationship between Mean Square Differences and Standard Error of Measurement: Comment on Barchard (2012)

ERIC Educational Resources Information Center

Pan, Tianshu; Yin, Yue

2012-01-01

In the discussion of mean square difference (MSD) and standard error of measurement (SEM), Barchard (2012) concluded that the MSD between 2 sets of test scores is greater than 2(SEM)[superscript 2] and SEM underestimates the score difference between 2 tests when the 2 tests are not parallel. This conclusion has limitations for 2 reasons. First,…

Quantified Choice of Root-Mean-Square Errors of Approximation for Evaluation and Power Analysis of Small Differences between Structural Equation Models

ERIC Educational Resources Information Center

Li, Libo; Bentler, Peter M.

2011-01-01

MacCallum, Browne, and Cai (2006) proposed a new framework for evaluation and power analysis of small differences between nested structural equation models (SEMs). In their framework, the null and alternative hypotheses for testing a small difference in fit and its related power analyses were defined by some chosen root-mean-square error of…

[Locally weighted least squares estimation of DPOAE evoked by continuously sweeping primaries].

PubMed

Han, Xiaoli; Fu, Xinxing; Cui, Jie; Xiao, Ling

2013-12-01

Distortion product otoacoustic emission (DPOAE) signal can be used for diagnosis of hearing loss so that it has an important clinical value. Continuously using sweeping primaries to measure DPOAE provides an efficient tool to record DPOAE data rapidly when DPOAE is measured in a large frequency range. In this paper, locally weighted least squares estimation (LWLSE) of 2f1-f2 DPOAE is presented based on least-squares-fit (LSF) algorithm, in which DPOAE is evoked by continuously sweeping tones. In our study, we used a weighted error function as the loss function and the weighting matrixes in the local sense to obtain a smaller estimated variance. Firstly, ordinary least squares estimation of the DPOAE parameters was obtained. Then the error vectors were grouped and the different local weighting matrixes were calculated in each group. And finally, the parameters of the DPOAE signal were estimated based on least squares estimation principle using the local weighting matrixes. The simulation results showed that the estimate variance and fluctuation errors were reduced, so the method estimates DPOAE and stimuli more accurately and stably, which facilitates extraction of clearer DPOAE fine structure.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information; with a section on theory and application of generalized least squares

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1987-01-01

This report documents the results of an analysis of the surface-water data network in Kansas for its effectiveness in providing regional streamflow information. The network was analyzed using generalized least squares regression. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-, low-, and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow-gaging-station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations, and (or) adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and for discontinued stations for which unregulated flow characteristics, as well as physical and climatic characteristics, were available. The State was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for the three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean-square error for each cost level could be obtained by adding new stations and discontinuing some current network stations. Large reductions in sampling mean-square error for low-flow information could be achieved in all three network areas, the reduction in western Kansas being the most dramatic. The addition of new stations would be most beneficial for mean-flow information in western Kansas. The reduction of sampling mean-square error for high-flow information would benefit most from the addition of new stations in western Kansas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas.

An Application of Interactive Computer Graphics to the Study of Inferential Statistics and the General Linear Model

DTIC Science & Technology

1991-09-01

matrix, the Regression Sum of Squares (SSR) and Error Sum of Squares (SSE) are also displayed as a percentage of the Total Sum of Squares ( SSTO ...vector when the student compares the SSR to the SSE. In addition to the plot, the actual values of SSR, SSE, and SSTO are also provided. Figure 3 gives the...Es ainSpace = E 3 Error- Eor Space =n t! L . Pro~cio q Yonto Pro~rct on of Y onto the simaton, pac ror Space SSR SSEL0.20 IV = 14,1 +IErrorI 2 SSTO

Predictors of Performance on the MMSE and the DRS-2 Among American Indian Elders

PubMed Central

Jervis, Lori L.; Fickenscher, Alexandra; Beals, Janette; Cullum, C. Munro; Novins, Douglas K.; Manson, Spero M.; Arciniegas, David B.

2015-01-01

Little is known about factors that predict older American Indians’ performance on cognitive tests. This study examined 137 American Indian elders’ performance on the MMSE and the Dementia Rating Scale—Second Edition (DRS-2). Multivariate regression identified younger age, more education, not receiving Supplemental Security Income, and frequent receipt of needed health care as predictors of better performance on the MMSE. Better performance on the DRS-2 was predicted by more education, boarding school attendance, not receiving Supplemental Security Income, and frequent receipt of needed health care. This study points to the importance of economic and educational factors on cognitive test performance among American Indian elders. PMID:21037127

Predictors of performance on the MMSE and the DRS-2 among American Indian elders.

PubMed

Jervis, Lori L; Fickenscher, Alexandra; Beals, Janette; Cullum, C Munro; Novins, Douglas K; Manson, Spero M; Arciniegas, David B

2010-01-01

Little is known about factors that predict older American Indians' performance on cognitive tests. This study examined 137 American Indian elders' performance on the MMSE and the Dementia Rating Scale-Second Edition (DRS-2). Multivariate regression identified younger age, more education, not receiving Supplemental Security Income, and frequent receipt of needed health care as predictors of better performance on the MMSE. Better performance on the DRS-2 was predicted by more education, boarding school attendance, not receiving Supplemental Security Income, and frequent receipt of needed health care. This study points to the importance of economic and educational factors on cognitive test performance among American Indian elders.

Bayesian demosaicing using Gaussian scale mixture priors with local adaptivity in the dual tree complex wavelet packet transform domain

NASA Astrophysics Data System (ADS)

Goossens, Bart; Aelterman, Jan; Luong, Hiep; Pizurica, Aleksandra; Philips, Wilfried

2013-02-01

In digital cameras and mobile phones, there is an ongoing trend to increase the image resolution, decrease the sensor size and to use lower exposure times. Because smaller sensors inherently lead to more noise and a worse spatial resolution, digital post-processing techniques are required to resolve many of the artifacts. Color filter arrays (CFAs), which use alternating patterns of color filters, are very popular because of price and power consumption reasons. However, color filter arrays require the use of a post-processing technique such as demosaicing to recover full resolution RGB images. Recently, there has been some interest in techniques that jointly perform the demosaicing and denoising. This has the advantage that the demosaicing and denoising can be performed optimally (e.g. in the MSE sense) for the considered noise model, while avoiding artifacts introduced when using demosaicing and denoising sequentially. In this paper, we will continue the research line of the wavelet-based demosaicing techniques. These approaches are computationally simple and very suited for combination with denoising. Therefore, we will derive Bayesian Minimum Squared Error (MMSE) joint demosaicing and denoising rules in the complex wavelet packet domain, taking local adaptivity into account. As an image model, we will use Gaussian Scale Mixtures, thereby taking advantage of the directionality of the complex wavelets. Our results show that this technique is well capable of reconstructing fine details in the image, while removing all of the noise, at a relatively low computational cost. In particular, the complete reconstruction (including color correction, white balancing etc) of a 12 megapixel RAW image takes 3.5 sec on a recent mid-range GPU.

Effect of Numerical Error on Gravity Field Estimation for GRACE and Future Gravity Missions

NASA Astrophysics Data System (ADS)

McCullough, Christopher; Bettadpur, Srinivas

2015-04-01

In recent decades, gravity field determination from low Earth orbiting satellites, such as the Gravity Recovery and Climate Experiment (GRACE), has become increasingly more effective due to the incorporation of high accuracy measurement devices. Since instrumentation quality will only increase in the near future and the gravity field determination process is computationally and numerically intensive, numerical error from the use of double precision arithmetic will eventually become a prominent error source. While using double-extended or quadruple precision arithmetic will reduce these errors, the numerical limitations of current orbit determination algorithms and processes must be accurately identified and quantified in order to adequately inform the science data processing techniques of future gravity missions. The most obvious numerical limitation in the orbit determination process is evident in the comparison of measured observables with computed values, derived from mathematical models relating the satellites' numerically integrated state to the observable. Significant error in the computed trajectory will corrupt this comparison and induce error in the least squares solution of the gravitational field. In addition, errors in the numerically computed trajectory propagate into the evaluation of the mathematical measurement model's partial derivatives. These errors amalgamate in turn with numerical error from the computation of the state transition matrix, computed using the variational equations of motion, in the least squares mapping matrix. Finally, the solution of the linearized least squares system, computed using a QR factorization, is also susceptible to numerical error. Certain interesting combinations of each of these numerical errors are examined in the framework of GRACE gravity field determination to analyze and quantify their effects on gravity field recovery.

Identification and compensation of the temperature influences in a miniature three-axial accelerometer based on the least squares method

NASA Astrophysics Data System (ADS)

Grigorie, Teodor Lucian; Corcau, Ileana Jenica; Tudosie, Alexandru Nicolae

2017-06-01

The paper presents a way to obtain an intelligent miniaturized three-axial accelerometric sensor, based on the on-line estimation and compensation of the sensor errors generated by the environmental temperature variation. Taking into account that this error's value is a strongly nonlinear complex function of the values of environmental temperature and of the acceleration exciting the sensor, its correction may not be done off-line and it requires the presence of an additional temperature sensor. The proposed identification methodology for the error model is based on the least square method which process off-line the numerical values obtained from the accelerometer experimental testing for different values of acceleration applied to its axes of sensitivity and for different values of operating temperature. A final analysis of the error level after the compensation highlights the best variant for the matrix in the error model. In the sections of the paper are shown the results of the experimental testing of the accelerometer on all the three sensitivity axes, the identification of the error models on each axis by using the least square method, and the validation of the obtained models with experimental values. For all of the three detection channels was obtained a reduction by almost two orders of magnitude of the acceleration absolute maximum error due to environmental temperature variation.

Accurate phase extraction algorithm based on Gram–Schmidt orthonormalization and least square ellipse fitting method

NASA Astrophysics Data System (ADS)

Lei, Hebing; Yao, Yong; Liu, Haopeng; Tian, Yiting; Yang, Yanfu; Gu, Yinglong

2018-06-01

An accurate algorithm by combing Gram-Schmidt orthonormalization and least square ellipse fitting technology is proposed, which could be used for phase extraction from two or three interferograms. The DC term of background intensity is suppressed by subtraction operation on three interferograms or by high-pass filter on two interferograms. Performing Gram-Schmidt orthonormalization on pre-processing interferograms, the phase shift error is corrected and a general ellipse form is derived. Then the background intensity error and the corrected error could be compensated by least square ellipse fitting method. Finally, the phase could be extracted rapidly. The algorithm could cope with the two or three interferograms with environmental disturbance, low fringe number or small phase shifts. The accuracy and effectiveness of the proposed algorithm are verified by both of the numerical simulations and experiments.

Variables Associated with Cognitive Function in Elderly California Seventh-day Adventists

PubMed Central

Fraser, Gary E.; Singh, Pramil N.; Bennett, Hannelore

2012-01-01

From a cohort of white, non-Hispanic California Seventh-day Adventists, 99 subjects over age 75 years in 1991 were randomly selected. Dietary habits and educational status had been measured in 1976. Subjects completed the Mini-Mental State Examination (MMSE) in 1991, and at that time, they or caregivers also gave information on current medical problems and drug therapy. Those who ate more calories in 1976 had lower MMSE scores in 1991 (p = 0.03), an association strengthened by excluding those with previous stroke or Parkinson’s disease by 1991. This raises the possibility that higher consumption of calories in middle age may accelerate the decline in cognitive function seen with aging, as apparently occurs in some animals. Less-educated subjects had lower MMSE scores, especially among the very elderly. The statistical model predicts that the negative association between use of psychotropic drugs and MMSE score (p = 0.004) is particularly potent in those cognitively impaired for other reasons. If causal, this suggests that physicians should use these agents very cautiously in such subjects. PMID:8651216

Variables associated with cognitive function in elderly California Seventh-day Adventists.

PubMed

Fraser, G E; Singh, P N; Bennett, H

1996-06-15

From a cohort of white, non-Hispanic California Seventh-day Adventists, 99 subjects over age 75 years in 1991 were randomly selected. Dietary habits and educational status had been measured in 1976. Subjects completed the Mini-Mental State Examination (MMSE) in 1991, and at that time, they or caregivers also gave information on current medical problems and drug therapy. Those who ate more calories in 1976 had lower MMSE scores in 1991 (p = 0.03), an association strengthened by excluding those with previous stroke or Parkinson's disease by 1991. This raises the possibility that higher consumption of calories in middle age may accelerate the decline in cognitive function seen with aging, as apparently occurs in some animals. Less-educated subjects had lower MMSE scores, especially among the very elderly. The statistical model predicts that the negative association between use of psychotropic drugs and MMSE score (p = 0.004) is particularly potent in those cognitively impaired for other reasons. If causal, this suggests that physicians should use these agents very cautiously in such subjects.

The mini mental state examination at the time of Alzheimer's disease and related disorders diagnosis, according to age, education, gender and place of residence: a cross-sectional study among the French National Alzheimer database.

PubMed

Pradier, Christian; Sakarovitch, Charlotte; Le Duff, Franck; Layese, Richard; Metelkina, Asya; Anthony, Sabine; Tifratene, Karim; Robert, Philippe

2014-01-01

was firstly to describe the MMSE (Mini-Mental State Examination) score upon initial diagnosis of Alzheimer's disease and related disorders among the French population, according to age. Secondly, education, gender and place of residence were studied as factors potentially associated with delayed Alzheimer's disease diagnosis. we conducted a cross sectional analysis of the French National Alzheimer database (BNA). Data from 2008 to 2012 were extracted. Patients were selected at the moment of their first diagnosis of AD (n = 39,451). The MMSE score at initial diagnosis dropped significantly with increasing age. The test score increased with the degree of educational background regardless of age. Gender and place of residence were significantly related to the MMSE score, women and persons living in medical institutions having lower MMSE scores under the age of 90 years and at all educational levels. Health care professionals should be aware of these risk factors in order to maximize chances of earliest possible diagnosis of Alzheimer's disease and related disorders.

Influence of mental practice and movement observation on motor memory, cognitive function and motor performance in the elderly

PubMed Central

Altermann, Caroline D. C.; Martins, Alexandre S.; Carpes, Felipe P.; Mello-Carpes, Pâmela B.

2014-01-01

Background With aging, it is important to maintain cognitive and motor functions to ensure autonomy and quality of life. During the acquisition of motor skills, it is necessary for the elderly to understand the purpose of the proposed activities. Physical and mental practice, as well as demonstrations, are strategies used to learn movements. Objectives To investigate the influence of mental practice and the observation of movement on motor memory and to understand the relationship between cognitive function and motor performance in the execution of a sequence of digital movements in the elderly. Method This was a cross-sectional study conducted with 45 young and 45 aged subjects. The instruments used were Mini-Mental State Examination (MMSE), Manual Preference Inventory and a Digital Motor Task (composed of a training of a sequence of movements, an interval and a test phase). The subjects were divided into three subgroups: control, mental practice and observation of movement. Results The elderly depend more strongly on mental practice for the acquisition of a motor memory. In comparing the performances of people in different age groups, we found that in the elderly, there was a negative correlation between the MMSE score and the execution time as well as the number of errors in the motor task. Conclusions For the elderly, mental practice can advantage motor performance. Also, there is a significant relationship between cognitive function, learning and the execution of new motor skills. PMID:24839046

Effects of education on very mild dementia among Chinese people in Hong Kong: potential mediators in the Cantonese Mini-Mental State Examination tasks.

PubMed

Tse, C S; Chang, J F; Leung, Grace T Y; Fung, Ada W T; Hau, K T; Chiu, Helen F K; Lam, Linda C W

2013-01-01

In Hong Kong, older Chinese adults generally have a low level of education. This study examined the effect of education on very mild Alzheimer's disease (AD), as quantified by Clinical Dementia Rating (CDR) scale (CDR 0.5 versus 0), in a Chinese community. The Cantonese version of the Mini-Mental State Examination (C-MMSE) was used to estimate cognitive abilities that were related to the level of education, and that in turn serve as protective factors for AD. A total of 788 community-dwelling older adults (383 CDR 0 and 405 CDR 0.5) were recruited in this cross-sectional study, which was derived from a population-based prevalence project. The participants' number of years of education and C-MMSE scores were used to predict their CDR scores using logistic regression and the mediation effects of C-MMSE scores were analyzed. Consistent with previous studies, the chance of being rated as having very mild AD increased with age, but decreased with years of education, among the older adult community of Hong Kong. The effect of education on very mild dementia was weakened substantially when C-MMSE scores were included as mediating variables. The findings indicate that the protective effects of education on dementia were mediated by an enhancement of older adults' performance on some C-MMSE items, including attention and orientation to time and place.

Exposure to smoking in movies and smoking initiation among black youth.

PubMed

Dal Cin, Sonya; Stoolmiller, Mike; Sargent, James D

2013-04-01

Black adolescents see more substance use in mainstream media but seem less responsive to it than other U.S. adolescents. Black-oriented media may be more personally relevant to them. To determine smoking exposure separately for black-oriented (BSME) and mainstream (MMSE) movies and assess their longitudinal relationships with smoking among black and other-race adolescents. Two-wave (2007-2009) national cohort survey of 2341 nonsmoking (at baseline) U.S. adolescents (aged 13-19 years), analyzed in 2012. The surveys determined BMSE and MMSE based on respondents' exposure to random subsets of 50 movies from a contemporary sample of 95 black-oriented and 288 mainstream movies previously content-coded for smoking. Outcome was smoking initiation. Black teens had significantly more BMSE and MMSE than other teens (p's <0.001). At follow-up, 23.5% of black and 29.0% of nonblack respondents had tried smoking. Among black respondents, BMSE was related to smoking initiation at follow-up but MMSE was not. For other adolescents, both BMSE and MMSE were related to smoking initiation. A prospective relationship was found between exposure to smoking in movies and smoking initiation. Among black adolescents in the U.S., this was only for black-oriented movies, suggesting the importance of personal relevance of the exposures. Parents, practitioners, and producers should be aware of these potential influences of media on black teen viewers. Copyright © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Cross-cultural comparisons of the Mini-mental State Examination between Japanese and U.S. cohorts

PubMed Central

Meguro, Kenichi; Ishii, Hiroshi; Yamaguchi, Satoshi; Saxton, Judith A.; Ganguli, Mary

2009-01-01

Background The Mini-mental State Examination (MMSE) is widely used in Japan and the U.S.A. for cognitive screening in the clinical setting and in epidemiological studies. A previous Japanese community study reported distributions of the MMSE total score very similar to that of the U.S.A. Methods Data were obtained from the Monongahela Valley Independent Elder's Study (MoVIES), a representative sample of community-dwelling elderly people aged 65 and older living near Pittsburgh, U.S.A., and from the Tajiri Project, with similar aims in Tajiri, Japan. We examined item-by-item distributions of the MMSE between two cohorts, comparing (1) percentage of correct answers for each item within each cohort, and (2) relative difficulty of each item measured by Item Characteristic Curve analysis (ICC), which estimates log odds of obtaining a correct answer adjusted for the remaining MMSE items, demographic variables (age, gender, education) and interactions of demographic variables and cohort. Results Median MMSE scores were very similar between the two samples within the same education groups. However, the relative difficulty of each item differed substantially between the two cohorts. Specifically, recall and auditory comprehension were easier for the Tajiri group, but reading comprehension and sentence construction were easier for the MoVIES group. Conclusions Our results reaffirm the importance of validation and examination of thresholds in each cohort to be studied when a common instrument is used as a dementia screening tool or for defining cognitive impairment. PMID:18925977

Utility of TICS-M for the assessment of cognitive function in older adults.

PubMed

de Jager, Celeste A; Budge, Marc M; Clarke, Robert

2003-04-01

Routine screening of high-risk elderly people for early cognitive impairment is constrained by the limitations of currently available cognitive function tests. The Telephone Interview of Cognitive Status is a novel instrument for assessment of cognitive function that can be administered in person or by telephone. To evaluate the determinants and utility of TICS-M (13-item modified version) for assessment of cognitive function in healthy elderly people. The utility of TICS-M was compared with more widely used MMSE and CAMCOG in a cross-sectional survey of 120 older (62 to 89 years) UK adults. The TICS-M cognitive test scores (27.97, SD 4.15) were normally distributed in contrast with those for MMSE and CAMCOG that had a negatively skewed distribution. TICS-M scores were inversely correlated with age (r = -0.21) and with the NART fullscale IQ (r = -0.35), but were independent of years of education in this cohort. TICS-M was highly correlated with MMSE (r = 0.57) and with CAMCOG (r = 0.62) scores. The time required to complete the test is comparable to MMSE and substantially less than CAMCOG. The normal distribution of TICS-M test scores suggest that this test is less constrained by the ceiling effect which limits the utility of MMSE and CAMCOG test scores in detecting early cognitive impairment. TICS-M is an appropriate instrument to assess cognitive function in both research and in clinical practice. Copyright 2003 John Wiley & Sons, Ltd.

Albumin, Hemoglobin, and the Trajectory of Cognitive Function in Community-Dwelling Older Japanese: A 13-Year Longitudinal Study.

PubMed

Murayama, H; Shinkai, S; Nishi, M; Taniguchi, Y; Amano, H; Seino, S; Yokoyama, Y; Yoshida, H; Fujiwara, Y; Ito, H

2017-01-01

Cognitive function can substantially decline over a long period, and understanding the trajectory of cognitive function is important. However, little is known about the linkage between nutritional biomarkers and long-term cognitive change. We analyzed 13-year longitudinal data for older Japanese to examine the associations of serum albumin and hemoglobin levels with the trajectory of cognitive function. Longitudinal study. Community-based. A total of 1,744 community-dwelling adults aged 65 years or older who participated in annual health examinations in Kusatsu town, Gunma Prefecture, Japan, from 2002-2014. Cognitive function was assessed annually by the Mini-Mental State Examination (MMSE). Albumin and hemoglobin levels at baseline (the year when a respondent first participated in the health examination) were divided into quartiles. Hierarchical linear modeling was used to analyze intrapersonal and interpersonal differences in cognitive function. Participants' MMSE scores decreased at an accelerated rate over the 13-year period. Participants with the lowest baseline albumin level (below the first quartile line) showed a greater accelerated decline in MMSE scores over time, compared with those with the highest level (above the third quartile line). Moreover, MMSE scores in participants with a lower hemoglobin level and lower MMSE score at baseline tended to decline faster over time at an accelerated rate. These findings yield new insights about the complex and diverse roles of these nutritional biomarkers on the trajectory of cognitive function in old age.

Tracking Cognitive Decline in Amnestic Mild Cognitive Impairment and Early-Stage Alzheimer Dementia: Mini-Mental State Examination versus Neuropsychological Battery.

PubMed

Kim, Joonho; Na, Han Kyu; Byun, Justin; Shin, Jiwon; Kim, Sungsoo; Lee, Byung Hwa; Na, Duk L

2017-01-01

Although the Mini-Mental State Examination (MMSE), Clinical Dementia Rating-Sum of Boxes (CDR-SOB), and neuropsychological batteries are widely used for evaluating cognitive function, it remains elusive which instrument best reflects the longitudinal disease progression in amnestic mild cognitive impairment (aMCI) and probable Alzheimer disease (AD). We investigated whether changes in these three instruments over time correlate with loss of cortical gray matter volume (cGMV). We retrospectively investigated 204 patients (aMCI, n = 114; AD, n = 90) who had undergone MMSE, CDR-SOB, the dementia version of the Seoul Neuropsychological Screening Battery (SNSB-D), and 3-dimensional T1-weighted magnetic resonance images at least twice. We investigated the partial correlation between annual decline in test scores and percent change of cGMV. In aMCI patients, changes in the SNSB-D total score (r = 0.340, p < 0.001) and CDR-SOB (r = 0.222, p = 0.020), but not MMSE, showed a correlation with cGMV loss, with the SNSB-D total score showing the strongest correlation. In AD patients, decline in all three test scores correlated significantly with cGMV loss, with MMSE exhibiting the strongest correlation (r = 0.464, p < 0.001). In aMCI patients, neuropsychological battery, though time-consuming, was the most adequate tool in tracking disease progression. In AD patients, however, MMSE may be the most effective longitudinal monitoring tool when considering cost-effectiveness. © 2017 S. Karger AG, Basel.

Exposure to Smoking in Movies and Smoking Initiation Among Black Youth

PubMed Central

Dal Cin, Sonya; Stoolmiller, Mike; Sargent, James D.

2013-01-01

Background Black adolescents see more substance use in mainstream media but seem less responsive to it than other U.S. adolescents. Black-oriented media may be more personally relevant to them. Purpose To determine smoking exposure separately for black-oriented (BSME) and mainstream (MMSE) movies and assess their longitudinal relationships with smoking among black and other-race adolescents. Methods Two-wave (2007–2009) national cohort survey of 2341 nonsmoking (at baseline) U.S. adolescents (aged 13–19 years), analyzed in 2012. The surveys determined BMSE and MMSE based on respondents’ exposure to random subsets of 50 movies from a contemporary sample of 95 black-oriented and 288 mainstream movies previously content-coded for smoking. Outcome was smoking initiation. Results Black teens had significantly more BMSE and MMSE than other teens (p’s <0.001). At follow-up, 23.5% of black and 29.0% of nonblack respondents had tried smoking. Among black respondents, BMSE was related to smoking initiation at follow-up but MMSE was not. For other adolescents, both BMSE and MMSE were related to smoking initiation. Conclusions A prospective relationship was found between exposure to smoking in movies and smoking initiation. Among black adolescents in the U.S., this was only for black-oriented movies, suggesting the importance of personal relevance of the exposures. Parents, practitioners, and producers should be aware of these potential influences of media on black teen viewers. PMID:23498099

Intrinsic Raman spectroscopy for quantitative biological spectroscopy Part II

PubMed Central

Bechtel, Kate L.; Shih, Wei-Chuan; Feld, Michael S.

2009-01-01

We demonstrate the effectiveness of intrinsic Raman spectroscopy (IRS) at reducing errors caused by absorption and scattering. Physical tissue models, solutions of varying absorption and scattering coefficients with known concentrations of Raman scatterers, are studied. We show significant improvement in prediction error by implementing IRS to predict concentrations of Raman scatterers using both ordinary least squares regression (OLS) and partial least squares regression (PLS). In particular, we show that IRS provides a robust calibration model that does not increase in error when applied to samples with optical properties outside the range of calibration. PMID:18711512

Effects of Transient Versus Chronic Loneliness on Cognitive Function in Older Adults: Findings From the Chinese Longitudinal Healthy Longevity Survey.

PubMed

Zhong, Bao-Liang; Chen, Shu-Lin; Conwell, Yeates

2016-05-01

Loneliness is a risk factor for poor cognitive function in older adults (OAs); to date, however, no studies have explored whether transient and chronic loneliness have differential effects on OAs' cognitive function. The present study evaluates the impacts of transient versus chronic loneliness on cognitive function in OAs. A 6-year follow-up cohort study. Rural and urban communities of 22 provinces in China. 2,995 OAs who were cognitively healthy (the modified Mini-Mental State Examination [mMMSE] ≥ 14) and completed the 2005, 2008, and 2011 waves of the Chinese Longitudinal Healthy Longevity Survey. Self-report loneliness and mMMSE. Both transient (β = -0.389, t = -2.191, df = 2994, p = 0.029) and chronic loneliness (β = -0.640, t = -2.109, df = 2994, p = 0.035) were significantly associated with lower mMMSE scores 6 years later, net of potential confounding effects of baseline covariates. Sensitivity analyses found that regression coefficients of mMMSE scores on transient loneliness were statistically significant and relatively stable across samples with various levels of cognitive function. In contrast, coefficients of mMMSE scores on chronic loneliness were statistically significant only among samples with normal cognitive function and the absolute values of these coefficients increased with the degree of cognitive health of the analytic sample. In the sample with mMMSE greater than or equal to 21, the coefficient of chronic loneliness was 2.59 times as large as that of transient loneliness (-1.017 versus -0.392). Both transient and chronic loneliness are significant predictors of cognitive decline in OAs. Relative to transient loneliness, chronic loneliness has more pronounced negative effects on the brain health of OAs. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Assessment of cognitive impairment in long-term oxygen therapy-dependent COPD patients.

PubMed

Karamanli, Harun; Ilik, Faik; Kayhan, Fatih; Pazarli, Ahmet Cemal

2015-01-01

A number of studies have shown that COPD, particularly in its later and more severe stages, is associated with various cognitive deficits. Thus, the primary goal of the present study was to elucidate the extent of cognitive impairment in patients with long-term oxygen therapy-dependent (LTOTD) COPD. In addition, this study aimed to determine the effectiveness of two cognitive screening tests, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), for COPD patients and the ability of oxygen therapy to mitigate COPD-related deficits in cognitive function. The present study enrolled 45 subjects: 24 nonuser and 21 regular-user LTOTD-COPD patients. All subjects had a similar grade of education, and there were no significant differences regarding age or sex. The MoCA (cutoff: <26 points) and MMSE (cutoff: ≤24 points) scores were compared between these two groups. The nonuser LTOTD-COPD group had a significantly lower MoCA score than that of the regular-user LTOTD-COPD group (19.38±2.99 vs 21.68±2.14, respectively) as well as a significantly lower MMSE score. Moreover, the absence of supplemental oxygen therapy increased the risk of cognitive impairment (MoCA, P=0.007 and MMSE, P=0.014), and the MoCA and MMSE scores significantly correlated with the number of emergency admissions and the number of hospitalizations in the last year. In the present study, the nonuser LTOTD-COPD group exhibited a significant decrease in cognitive status compared with the regular-user LTOTD-COPD group. This suggests that the assessment of cognitive function in nonuser LTOTD-COPD patients and the use of protective strategies, such as continuous supplemental oxygen treatment, should be considered during the management of COPD in this population. In addition, the MoCA score was superior to the MMSE score for the determination of cognitive impairment in the nonuser LTOTD-COPD patients.

A Pilot Study: The Beneficial Effects of Combined Statin-exercise Therapy on Cognitive Function in Patients with Coronary Artery Disease and Mild Cognitive Decline.

PubMed

Toyama, Kensuke; Sugiyama, Seigo; Oka, Hideki; Hamada, Mari; Iwasaki, Yuri; Horio, Eiji; Rokutanda, Taku; Nakamura, Shinichi; Spin, Joshua M; Tsao, Philip S; Ogawa, Hisao

2017-01-01

Objective Hypercholesterolemia, a risk factor in cognitive impairment, can be treated with statins. However, cognitive decline associated with "statins" (HMG-CoA reductase inhibitors) is a clinical concern. This pilot study investigated the effects of combining statins and regular exercise on cognitive function in coronary artery disease (CAD) patients with prior mild cognitive decline. Methods We recruited 43 consecutive CAD patients with mild cognitive decline. These patients were treated with a statin and weekly in-hospital aerobic exercise for 5 months. We measured serum lipids, exercise capacity, and cognitive function using the mini mental state examination (MMSE). Results Low-density lipoprotein cholesterol levels were significantly decreased, and maximum exercise capacity (workload) was significantly increased in patients with CAD and mild cognitive decline after treatment compared with before. Combined statin-exercise therapy significantly increased the median (range) MMSE score from 24 (22-25) to 25 (23-27) across the cohort (p<0.01). Changes in body mass index (BMI) were significantly and negatively correlated with changes in the MMSE. After treatment, MMSE scores in the subgroup of patients that showed a decrease in BMI were significantly improved, but not in the BMI-increased subgroup. Furthermore, the patients already on a statin at the beginning of the trial displayed a more significant improvement in MMSE score than statin-naïve patients, implying that exercise might be the beneficial aspect of this intervention as regards cognition. In a multivariate logistic regression analysis adjusted for age >65 years, sex, and presence of diabetes mellitus, a decrease in BMI during statin-exercise therapy was significantly correlated with an increase in the MMSE score (odds ratio: 4.57, 95% confidence interval: 1.05-20.0; p<0.05). Conclusion Statin-exercise therapy may help improve cognitive dysfunction in patients with CAD and pre-existing mild cognitive decline.

How Can We Best Screen for Cognitive Impairment in Malaysia? A Pilot of the IDEA Cognitive Screen and Picture-Based Memory Impairment Scale and Comparison of Criterion Validity with the Mini Mental State Examination.

PubMed

Rosli, Roshaslina; Tan, Maw Pin; Gray, William K; Subramanian, Pathmawathi; Mohd Hairi, Noran Naqiah; Chin, Ai-Vyrn

2017-01-01

To pilot two new cognitive screening tools for use in an urban Malaysian population and to compare their criterion validity against a gold standard, the well-established Mini-Mental State Examination (MMSE). The IDEA cognitive screen, Picture-based Memory Impairment Scale (PMIS), and MMSE were administered to a convenience sample of elderly (≥ 65 years) from the community and outpatient clinics at an urban teaching hospital. Consensus diagnosis was performed by two geriatricians blinded to PMIS and IDEA cognitive screen scores using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) clinical criteria. The MMSE performance was used as a reference. The study enrolled 66 participants, with a median age of 78.5 years (interquartile range [IQR], 72.5-83.0) years and 11.0 median years of education (IQR, 9.0-13.0). Forty-three (65.2%) were female, and 32 (48.4%) were Chinese. The area under the receiver operating characteristic (AUROC) curve values were .962 (IDEA cognitive screen), .970 (PMIS), and .935 (MMSE). The optimal cutoff values for sensitivity and specificity were: IDEA cognitive screen: ≤ 11, 90.9% and 89.7%; PMIS: ≤ 6, 97.3% and 69.0%; and MMSE: ≤ 23, 84.6% and 76.0%. Although the sample size was small, multivariable logistic regression modelling suggested that all three screen scores did not appear to be educationally biased. The IDEA and PMIS tools are potentially valid screening tools for dementia in urban Malaysia, and perform at least as well as the MMSE. Further work on larger representative, cohorts is needed to further assess the psychometric properties. Study provides alternative screening tools for dementia for both non-specialists and specialists.

Cognitive changes after parathyroidectomy in patients with secondary hyperparathyroidism.

PubMed

Chou, Fong-Fu; Chen, Jin-Bor; Hsieh, Kun-Chou; Liou, Chia-Wei

2008-04-01

Cognitive impairment was frequently reported in uremic patients with dialysis, but improvements of cognition after parathyroidectomy for symptomatic secondary hyperparathyroidism have never been reported before. Thirty-nine patients, who were successfully operated on with total parathyroidectomy plus autotransplantation were enrolled. Twenty-three dialysis patients, age >50 years, who had a serum level of intact parathyroid hormone (iPTH) greater than 650 pg/ml, and who did not undergo parathyroidectomy were selected as the control group. The mini-mental state examination (MMSE) and the clinical dementia rating (CDR) test were administered to all patients. Before the operation, educational level, symptoms of bone pain, skin itching, general weakness and insomnia were recorded and serum levels of calcium, phosphorus, alkaline phosphatase (Alk-ptase), iPTH, aluminum, and hemoglobin were measured in the study and control groups. At 12-week postoperatively, serum levels of calcium, phosphorus, Alk-ptase, iPTH, and aluminum were measured again and at 16-week postoperatively, the MMSE and the CDR test were administered again. In the control group, both MMSE and CDR test were administered again after the period or 16-week. Serum calcium level was only significant difference (p = 0.002), whereas clinical symptoms, gender, etiologies of secondary hyperparathyroidism, duration of dialysis, educational level, age, and serum levels of phosphorus, Alk-ptase, iPTH, aluminum, and hemoglobin were not significantly different between the two groups. The educational level was the only factor affecting MMSE scores (p = 0.003). In the study group, at 12-week postoperatively, symptoms improved significantly, serum levels of calcium, phosphorus, Alk-ptase, iPTH, and aluminum decreased significantly, and at 16-week postoperatively, MMSE scores increased from 25 +/- 5 (mean +/- SD) to 26 +/- 5 (p < 0.001) and CDR scales decreased significantly (p < 0.001). Neither MMSE scores nor CDR scales of the control group changed significantly after the 16-week period. Parathyroidectomy for symptomatic secondary hyperparathyroidism can improve cognition.

[Toward constructing a system for detecting and coping with senile dementia in early stages among community-dwelling older people].

PubMed

Fujiwara, Yoshinori; Amano, Hidenori; Mori, Setsuko; Watanabe, Shuichiro; Kumagai, Shu; Yoshida, Yuko; Kim, Jungnim; Takabayashi, Koji; Yoshida, Hiroto; Ishihara, Miyuki; Eguchi, Fusako; Fuse, Sumie; Morita, Masahiro; Nagai, Hiroko; Shinkai, Shoji

2003-08-01

To establish a community health care system for screening community-dwelling older people with mild cognitive decline (MCD) and early diagnosis by a medical specialist. Out of all the elderly residents aged 65 years and over living in Yoita town in 2000 (n = 1673), 1544 participated in the interview survey held at community halls or at home (92.3% response). They underwent a Mini-Mental State Examination (MMSE) for assessment of cognitive function and answered questionnaires covering socio-demographic, psychological, physical and medical, and social activity items (2000/11). We defined cognitive decline as an MMSE < or = 1 SD below the age-specific mean (n = 371). Out of a total eligible population of 332, 158 pairs of subjects and their proxies participated in a follow-up survey (2001/11). The subjects themselves underwent MMSE again, and were asked for complaints of memory-related problems. Proxies answered about functional capacity and memory-related problems of subjects, for which we assessed the level of dementia with the Clinical Dementia Rating (CDR). We established criteria for encouragement to undergo detailed examination by a medical specialist as follows. 1) MMSE scores < or = 1 SD below age-specific means at both baseline and follow-up surveys, or 2) CDR > or = 0.5, and 3) not due to mental retardation. Non-participants had significant higher MMSE scores but were younger in the follow-up survey. Out of 96 subjects eligible for the detailed examination, 47 participants showed a tendency for older age with lower MMSE scores or younger age with higher MMSE scores than the average in the follow-up survey. The detailed examinations confirmed dementia of Alzheimer's type in 22 and vascular dementia in 13 on DSM-IV or magnetic resonance imaging. During our screening, 8 community care saloons were opened and the number of facilities for older people with cognitive decline is increasing. To establish a community health care system to screen and cope with community-dwelling older people with MCD in earlier stages, increased awareness of residents with slight MCD is especially important. Our attempt also suggested the importance of educational lectures, methods for testing cognitive function, and dementia care activity.

Error Analyses of the North Alabama Lightning Mapping Array (LMA)

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Solokiewicz, R. J.; Blakeslee, R. J.; Goodman, S. J.; Christian, H. J.; Hall, J. M.; Bailey, J. C.; Krider, E. P.; Bateman, M. G.; Boccippio, D. J.

2003-01-01

Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA-MSFC and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results, except that the chi-squared theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

Synthesis and optimization of four bar mechanism with six design parameters

NASA Astrophysics Data System (ADS)

Jaiswal, Ankur; Jawale, H. P.

2018-04-01

Function generation is synthesis of mechanism for specific task, involves complexity for specially synthesis above five precision of coupler points. Thus pertains to large structural error. The methodology for arriving to better precision solution is to use the optimization technique. Work presented herein considers methods of optimization of structural error in closed kinematic chain with single degree of freedom, for generating functions like log(x), ex, tan(x), sin(x) with five precision points. The equation in Freudenstein-Chebyshev method is used to develop five point synthesis of mechanism. The extended formulation is proposed and results are obtained to verify existing results in literature. Optimization of structural error is carried out using least square approach. Comparative structural error analysis is presented on optimized error through least square method and extended Freudenstein-Chebyshev method.

Construct validation of two music-based assessments for people with dementia.

PubMed

Lipe, Anne W; York, Elizabeth; Jensen, Eric

2007-01-01

The purpose of this study was to substantiate the usefulness of the tasks on two music-based assessments in providing information about music cognition among people with dementia and to more fully understand the nature of this construct and its relationship to general cognition. Individuals with dementia (N = 50) received 3 evaluations: the Mini-Mental State Exam (MMSE), the MBECF, and the RMST. Results of the study revealed significant correlations between the MMSE and both music-based assessments. A pattern of correlations between the MMSE and the subsets of tasks contained in both music-based assessments showed that while there are strong relationships between music and general cognition, that there also is uniqueness to the melodic, singing and rhythmic aspects of music cognition.

Theoretical and experimental studies of error in square-law detector circuits

NASA Technical Reports Server (NTRS)

Stanley, W. D.; Hearn, C. P.; Williams, J. B.

1984-01-01

Square law detector circuits to determine errors from the ideal input/output characteristic function were investigated. The nonlinear circuit response is analyzed by a power series expansion containing terms through the fourth degree, from which the significant deviation from square law can be predicted. Both fixed bias current and flexible bias current configurations are considered. The latter case corresponds with the situation where the mean current can change with the application of a signal. Experimental investigations of the circuit arrangements are described. Agreement between the analytical models and the experimental results are established. Factors which contribute to differences under certain conditions are outlined.

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Peelle's pertinent puzzle using the Monte Carlo technique

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

Kawano, Toshihiko; Talou, Patrick; Burr, Thomas

2009-01-01

We try to understand the long-standing problem of the Peelle's Pertinent Puzzle (PPP) using the Monte Carlo technique. We allow the probability density functions to be any kind of form to assume the impact of distribution, and obtain the least-squares solution directly from numerical simulations. We found that the standard least squares method gives the correct answer if a weighting function is properly provided. Results from numerical simulations show that the correct answer of PPP is 1.1 {+-} 0.25 if the common error is multiplicative. The thought-provoking answer of 0.88 is also correct, if the common error is additive, andmore » if the error is proportional to the measured values. The least squares method correctly gives us the most probable case, where the additive component has a negative value. Finally, the standard method fails for PPP due to a distorted (non Gaussian) joint distribution.« less

Analysis of Point Based Image Registration Errors With Applications in Single Molecule Microscopy

PubMed Central

Cohen, E. A. K.; Ober, R. J.

2014-01-01

We present an asymptotic treatment of errors involved in point-based image registration where control point (CP) localization is subject to heteroscedastic noise; a suitable model for image registration in fluorescence microscopy. Assuming an affine transform, CPs are used to solve a multivariate regression problem. With measurement errors existing for both sets of CPs this is an errors-in-variable problem and linear least squares is inappropriate; the correct method being generalized least squares. To allow for point dependent errors the equivalence of a generalized maximum likelihood and heteroscedastic generalized least squares model is achieved allowing previously published asymptotic results to be extended to image registration. For a particularly useful model of heteroscedastic noise where covariance matrices are scalar multiples of a known matrix (including the case where covariance matrices are multiples of the identity) we provide closed form solutions to estimators and derive their distribution. We consider the target registration error (TRE) and define a new measure called the localization registration error (LRE) believed to be useful, especially in microscopy registration experiments. Assuming Gaussianity of the CP localization errors, it is shown that the asymptotic distribution for the TRE and LRE are themselves Gaussian and the parameterized distributions are derived. Results are successfully applied to registration in single molecule microscopy to derive the key dependence of the TRE and LRE variance on the number of CPs and their associated photon counts. Simulations show asymptotic results are robust for low CP numbers and non-Gaussianity. The method presented here is shown to outperform GLS on real imaging data. PMID:24634573

[Revalidation and standardization of the cognition mini-exam (first Spanish version of the Mini-Mental Status Examination) in the general geriatric population].

PubMed

Lobo, A; Saz, P; Marcos, G; Día, J L; de la Cámara, C; Ventura, T; Morales Asín, F; Fernando Pascual, L; Montañés, J A; Aznar, S

1999-06-05

The revalidation of the Mini Examen Cognoscitivo (MEC), first Spanish version (1978) of the Mini-Mental Status Examination (MMSE) and documentation of "population-based norms" should clarify the potential confusion induced by later versions of MMSE. The Zaragoza Study on the prevalence of dementia and depression in a representative sample of the elderly community (N = 1,080). MEC-35 and MEC-30 points, and validated, Spanish versions of Geriatric Mental State (GMS), History and Aetiology Schedule (HAS) and Social Status Schedule (SSS). a) validation of MEC (standardized lay interviewers) against the gold standard of psychiatric diagnosis (DSM-III-R), two months later; b) "population-based norms" in the "healthy" population, and c) comparison with other MMSE versions. The instrument fulfills criteria of "feasibility", "content", "procedural" and "construct validity". Test-retest reliability: weighted kappa = 0.637. MEC-30 (cut-off point 23/24), sensitivity = 89.8%, specificity = 75.1% (80.8% with the cut-off at 22/23), and ROC curve, AUC = 0.920. The coefficients of individual items were satisfactory and the specificity increases in MEC-35 (83.9%). Other MMSE Spanish versions have not improved these coefficients. "Population-based norms" confirm the hypothesized influence of age and education level. MEC-30 is the version with most comparable results with the MMSE in USA. The validity of MEC is confirmed in the elderly population, with the same cut-off points recommended in the original standardization. MEC-30 is the best version for international comparisons.

Comparison of the montreal cognitive assessment and the mini-mental state examination as screening tests in hemodialysis patients without symptoms.

PubMed

Lee, Sun Hwa; Cho, AJin; Min, Yang-Ki; Lee, Young-Ki; Jung, San

2018-11-01

Cognitive impairment in end-stage renal disease patients is associated with an increased risk of mortality. We examined the cognitive function in hemodialysis (HD) patients and compared the Korean versions of the Montreal Cognitive Assessment (K-MoCA) and of the Mini-Mental State Examination (K-MMSE) to identify the better cognitive screening instrument in these patients. Thirty patients undergoing hemodialysis and 30 matched reference group of apparently healthy control were included. All subjects underwent the K-MoCA, K-MMSE and a neuropsychological test battery to measure attention, visuospatial function, language, memory and executive function. All cognitive data were converted to z-scores with appropriate age and education level prior to group comparisons. Cognitive performance 1.0 SD below the mean was defined as modest cognitve impairment while 1.5 below the mean was defined as severe cognitive impairment. Modest cognitive impairment in memory plus other cognitive domains was detected in 27 patients (90%) while severe cognitive impairment in memory plus other cognitive domains was detected in 23 (77%) patients. Total scores in the K-MoCA were significantly lower in HD patients than in the reference group. However, no significant group difference was found in the K-MMSE. The K-MMSE ROC AUC (95% confidence interval) was 0.72 (0.59-0.85) and K-MoCA ROC AUC was 0.77 (0.65-0.89). Cognitive impairment is common but under-diagnosed in this population. The K-MoCA seems to be more sensitive than the K-MMSE in HD patients.

Major depressive disorder with psychotic features may lead to misdiagnosis of dementia: a case report and review of the literature.

PubMed

Wagner, Gerhardt S; McClintock, Shawn M; Rosenquist, Peter B; McCall, W Vaughn; Kahn, David A

2011-11-01

Major depressive disorder (MDD) with psychotic features is relatively frequent in patients with greater depressive symptom severity and is associated with a poorer course of illness and greater functional impairment than MDD without psychotic features. Multiple studies have found that patients with psychotic mood disorders demonstrate significantly poorer cognitive performance in a variety of areas than those with nonpsychotic mood disorders. The Mini Mental State Examination (MMSE) and the Dementia Rating Scale, Second Edition (DRS-2) are widely used to measure cognitive functions in research on MDD with psychotic features. Established total raw score cut-offs of 24 on the MMSE and 137 on the DRS-2 in published manuals suggest possible global cognitive impairment and dementia, respectively. Limited research is available on these suggested cut-offs for patients with MDD with psychotic features. We document the therapeutic benefit of electroconvulsive therapy (ECT), which is usually associated with short-term cognitive impairment, in a 68-year-old woman with psychotic depression whose MMSE and DRS-2 scores initially suggested possible global cognitive impairment and dementia. Over the course of four ECT treatments, the patient's MMSE scores progressively increased. After the second ECT treatment, the patient no longer met criteria for global cognitive impairment. With each treatment, depression severity, measured by the 24-item Hamilton Rating Scale for Depression, improved sequentially. Thus, the suggested cut-off scores for the MMSE and the DRS-2 in patients with MDD with psychotic features may in some cases produce false-positive indications of dementia.

Finger displacement in Parkinson disease: up? down? sideways?

PubMed

Lieberman, Abraham; Dhall, Rohit; Salins, Naomi; Sadreddin, Arshia; Moguel-Cobos, Guillermo; Karis, John; Krishnamurthi, Narayanan

2014-05-01

We previously reported that patients with tremor preponderant Parkinson disease (PD) displayed upward or lateral displacement of their more tremulous finger when they pointed both their index fingers at a target and closed their eyes for 15 seconds. In this study, we examined the phenomenon in 104 PD patients: 72 patients without tremor and 32 with minimal tremor to see if the displacement is related to the disease or the tremor. Sixty-eight of the 72 patients without tremor, 94%, exhibited finger displacement suggesting the phenomenon is related to the disease. None of the 104 patients were demented: mini-mental status examination (MMSE) score 29.0 ± 0. 75. Ninety patients displayed upward displacement (56 patients) or lateral or medial displacement (34 patients). MMSE score of the 90 patients: 29.2 ± 0.74 with no score < 28. Eight patients (6 without tremor) displayed downward displacement. MMSE score of the 8 patients: 27.5 ± 0.35 with 5 having MMSE score of 27. Although not significant the results suggest that patients with downward displacement and lower MMSE score may be evolving a dementia. Upward displacement with eyes closed for 15 seconds requires an ability to "remember" the position of the finger in space and to alter tone to overcome gravity. Downward displacement implies an inability to "remember" the position of the finger in space an inability to overcome the effects of gravity. This may be more likely in patients who are evolving a dementia. Two patients, with PD-like symptoms, and specific anatomical abnormalities are also presented as they illustrate the anatomy of finger displacement.

Cognitive abilities screening instrument-short form, mini-mental state examination and functional activities questionnaire in the illiterate elderly.

PubMed

Rezende, Gabriela Pravatta; Cecato, Juliana; Martinelli, José Eduardo

2013-01-01

Dementia prevalence is increasing in developing countries due to population aging. Brief tests for assessing cognition and activities of daily living are very useful for the diagnosis of dementia by the clinician. Low education, particularly illiteracy, is a hindrance to the diagnosis of dementia in several regions of the world. To compare the Brazilian version of the Cognitive Abilities Screening Instrument-Short Form (CASI-S) with the Mini-Mental State Examination (MMSE) and Pfeffer Functional Activities Questionnaire (PFAQ) for the diagnosis of dementia in illiterate elderly. A cross-sectional study with illiterate elderly of both genders seen at the outpatient clinics of the Institute of Gerontology and Geriatrics Jundiaí, São Paulo state was performed. Spearman's correlation coefficient was used to correlate CASI-S, MMSE and PFAQ scores. The sample comprised 29 elderly over 57 years old whose mean scores on the CASI-S (scores ranging from 3 to 23) and the MMSE (scores ranging from 2 to 23) were 11.69 and 12.83, respectively. There was a strong significant correlation between the CASI-S and MMSE (r=0.75, p<0.001) and a moderate correlation coefficient that was significant and negative between the PFAQ and CASI-S (r= -0.53 p=0.003),similar to that between the MMSE and PFAQ (r= -0.41 p=0.025). The Brazilian version of the CASI-S demonstrates ease of application and correction in the illiterate elderly, and warrants further studies regarding its applicability for the diagnosis of dementia in populations with a heterogeneous educational background.

MMSE and MoCA in Parkinson’s disease and dementia with Lewy bodies: a multicenter 1-year follow-up study

PubMed Central

Weis, L.; Bostantjopoulou, S.; Stefanova, E.; Falup-Pecurariu, C.; Kramberger, M. G.; Geurtsen, G. J.; Antonini, A.; Weintraub, D.; Aarsland, D.

2016-01-01

The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are the most commonly used scales to test cognitive impairment in Lewy body disease (LBD), but there is no consensus on which is best suited to assess cognition in clinical practice and most sensitive to cognitive decline. Retrospective cohort study of 265 LBD patients [Parkinson’s disease (PD) without dementia (PDnD, N = 197), PD with dementia (PDD, N = 40), and dementia with Lewy bodies (DLB, N = 28)] from an international consortium who completed both the MMSE and MoCA at baseline and 1-year follow-up (N = 153). Percentage of relative standard deviation (RSD%) at baseline was the measure of inter-individual variance, and estimation of change (Cohen’s d) over time was calculated. RSD% for the MoCA (21 %) was greater than for the MMSE (13 %) (p = 0.03) in the whole group. This difference was significant only in PDnD (11 vs. 5 %, p < 0.01), but not in PDD (30 vs. 19 %, p = 0.37) or DLB (15 vs. 14 %, p = 0.78). In contrast, the 1-year estimation of change did not differ between the two tests in any of the groups (Cohen’s effect <0.20 in each group). MMSE and MoCA are equal in measuring the rate of cognitive changes over time in LBD. However, in PDnD, the MoCA is a better measure of cognitive status as it lacks both ceiling and floor effects. PMID:26852137

Correlates of Level and Change in the Mini-Mental State Examination

ERIC Educational Resources Information Center

Soubelet, Andrea; Salthouse, Timothy A.

2011-01-01

The goal of the current project was to determine (a) the cognitive abilities assessed by the Mini Mental State Examination (MMSE; M. F. Folstein, S. E. Folstein, & P. R. McHugh, 1975), (b) whether the same abilities are associated with MMSE performance among people of different ages, and (c) whether the same abilities are involved in changes…

Characteristic differences in the mini-mental state examination used in Asian countries.

PubMed

Shim, Yong S; Yang, Dong Won; Kim, Hee-Jin; Park, Young Ho; Kim, SangYun

2017-07-21

The mini-mental state examination (MMSE) was adapted by individual countries according to their languages and cultures, though it has not been systematically compared. The objective of this study was to compare the linguistic and cultural variations of the MMSE used in various Asian countries. With this, we can analyze the strengths and weaknesses of the MMSE and consider using a common version in future international clinical studies in Asia. We collected the MMSEs used in 11 Asian nations. After translating those into English, we compared them to understand the differences in the questionnaires with regard to cultural aspects. Many items may be applicable or comparable with a little modification, for Asian countries. However, attention and calculation and repetition may be incomparable. There were some differences in the contents and the ways to administer. The lack of consideration of the cultural differences and their influences on the interpretation of the same cognitive test makes cross-cultural studies difficult. Some items of MMSE tasks need readjusting for, if any, multi-national studies. This study might serve as a first step in the development of a standardized cross-cultural cognitive instrument, especially in Asia.

Tai Ji Quan and global cognitive function in older adults with cognitive impairment: a pilot study.

PubMed

Li, Fuzhong; Harmer, Peter; Liu, Yu; Chou, Li-Shan

2014-01-01

This study evaluated whether Tai Ji Quan: Moving for Better Balance (TJQMBB) could improve global cognitive function in older adults with cognitive impairment. Using a nonrandomized control group pretest-posttest design, participants aged ≥65 years who scored between 20 and 25 on the Mini-Mental State Examination (MMSE) were allocated into either a 14-week TJQMBB program (n=22) or a control group (n=24). The primary outcome was MMSE as a measure of global cognitive function with secondary outcomes of 50-ft speed walk, Timed Up&Go, and Activities-Specific Balance Confidence (ABC) scale. At 14 weeks, Tai Ji Quan participants showed significant improvement on MMSE (mean=2.26, p<0.001) compared to controls (mean=0.63, p=0.08). Similarly, Tai Ji Quan participants performed significantly better compared to the controls in both physical performance and balance efficacy measures (p<0.05). Improvement in cognition as measured by MMSE was related to improved physical performance and balance efficacy. These results provide preliminary evidence of the utility of the TJQMBB program to promote cognitive function in older adults in addition to physical benefits. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

'Yes' ifs, ands or buts: examining performance and correlates of the repetition task in the mini-mental state examination.

PubMed

Werner, P; Heinik, J; Lin, R; Bleich, A

1999-09-01

The aim of this study was to examine whether the type of sentence used in the repetition task included in the Mini-Mental State Examination (MMSE) affected performance in a group of 79 demented and 19 non-demented Hebrew-speaking elderly persons. The cognitive functioning of the participants was assessed using the MMSE and CAMCOG examinations. The performance of the repetition task was evaluated by using three sentences: the literal translation of the English language expression used in the original MMSE; a well-known Hebrew proverb consisting of monosyllabic words and rhythmic effects; and another well-known Hebrew proverb without such attributes. Only a third of the participants successfully repeated the literally translated expression. It showed low predictive value and was highly affected by education. The well-known Hebrew monosyllabic proverb showed moderate predictive value but no discriminatory ability. The other well-known Hebrew proverb performed the best. The translation of the repetition task in the MMSE to other languages is problematic. Strict adherence to the original language proved to be the least desirable choice. Copyright 1999 John Wiley & Sons, Ltd.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Optimum nonparametric estimation of population density based on ordered distances

USGS Publications Warehouse

Patil, S.A.; Kovner, J.L.; Burnham, Kenneth P.

1982-01-01

The asymptotic mean and error mean square are determined for the nonparametric estimator of plant density by distance sampling proposed by Patil, Burnham and Kovner (1979, Biometrics 35, 597-604. On the basis of these formulae, a bias-reduced version of this estimator is given, and its specific form is determined which gives minimum mean square error under varying assumptions about the true probability density function of the sampled data. Extension is given to line-transect sampling.

Ambiguity resolution for satellite Doppler positioning systems

NASA Technical Reports Server (NTRS)

Argentiero, P. D.; Marini, J. W.

1977-01-01

A test for ambiguity resolution was derived which was the most powerful in the sense that it maximized the probability of a correct decision. When systematic error sources were properly included in the least squares reduction process to yield an optimal solution, the test reduced to choosing the solution which provided the smaller valuation of the least squares loss function. When systematic error sources were ignored in the least squares reduction, the most powerful test was a quadratic form comparison with the weighting matrix of the quadratic form obtained by computing the pseudo-inverse of a reduced rank square matrix. A formula is presented for computing the power of the most powerful test. A numerical example is included in which the power of the test is computed for a situation which may occur during an actual satellite aided search and rescue mission.

Credit Risk Evaluation Using a C-Variable Least Squares Support Vector Classification Model

NASA Astrophysics Data System (ADS)

Yu, Lean; Wang, Shouyang; Lai, K. K.

Credit risk evaluation is one of the most important issues in financial risk management. In this paper, a C-variable least squares support vector classification (C-VLSSVC) model is proposed for credit risk analysis. The main idea of this model is based on the prior knowledge that different classes may have different importance for modeling and more weights should be given to those classes with more importance. The C-VLSSVC model can be constructed by a simple modification of the regularization parameter in LSSVC, whereby more weights are given to the lease squares classification errors with important classes than the lease squares classification errors with unimportant classes while keeping the regularized terms in its original form. For illustration purpose, a real-world credit dataset is used to test the effectiveness of the C-VLSSVC model.

Error analysis on squareness of multi-sensor integrated CMM for the multistep registration method

NASA Astrophysics Data System (ADS)

Zhao, Yan; Wang, Yiwen; Ye, Xiuling; Wang, Zhong; Fu, Luhua

2018-01-01

The multistep registration(MSR) method in [1] is to register two different classes of sensors deployed on z-arm of CMM(coordinate measuring machine): a video camera and a tactile probe sensor. In general, it is difficult to obtain a very precise registration result with a single common standard, instead, this method is achieved by measuring two different standards with a constant distance between them two which are fixed on a steel plate. Although many factors have been considered such as the measuring ability of sensors, the uncertainty of the machine and the number of data pairs, there is no exact analysis on the squareness between the x-axis and the y-axis on the xy plane. For this sake, error analysis on the squareness of multi-sensor integrated CMM for the multistep registration method will be made to examine the validation of the MSR method. Synthetic experiments on the squareness on the xy plane for the simplified MSR with an inclination rotation are simulated, which will lead to a regular result. Experiments have been carried out with the multi-standard device designed also in [1], meanwhile, inspections with the help of a laser interferometer on the xy plane have been carried out. The final results are conformed to the simulations, and the squareness errors of the MSR method are also similar to the results of interferometer. In other word, the MSR can also adopted/utilized to verify the squareness of a CMM.

Random errors in interferometry with the least-squares method

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

Wang Qi

2011-01-20

This investigation analyzes random errors in interferometric surface profilers using the least-squares method when random noises are present. Two types of random noise are considered here: intensity noise and position noise. Two formulas have been derived for estimating the standard deviations of the surface height measurements: one is for estimating the standard deviation when only intensity noise is present, and the other is for estimating the standard deviation when only position noise is present. Measurements on simulated noisy interferometric data have been performed, and standard deviations of the simulated measurements have been compared with those theoretically derived. The relationships havemore » also been discussed between random error and the wavelength of the light source and between random error and the amplitude of the interference fringe.« less

Least Squares Metric, Unidimensional Scaling of Multivariate Linear Models.

ERIC Educational Resources Information Center

Poole, Keith T.

1990-01-01

A general approach to least-squares unidimensional scaling is presented. Ordering information contained in the parameters is used to transform the standard squared error loss function into a discrete rather than continuous form. Monte Carlo tests with 38,094 ratings of 261 senators, and 1,258 representatives demonstrate the procedure's…

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1985-01-01

The surface water data network in Kansas was analyzed using generalized least squares regression for its effectiveness in providing regional streamflow information. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-flow, low-flow and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow gaging station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations; and/or adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and discontinued stations for which unregulated flow characteristics , as well as physical and climatic characteristics, were available. The state was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean square error for each cost level could be obtained by adding new stations and discontinuing some of the present network stations. Large reductions in sampling mean square error for low-flow information could be accomplished in all three network areas, with western Kansas having the most dramatic reduction. The addition of new stations would be most beneficial for man- flow information in western Kansas, and to lesser degrees in the other two areas. The reduction of sampling mean square error for high-flow information would benefit most from the addition of new stations in western Kansas, and the effect diminishes to lesser degrees in the other two areas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas. (Author 's abstract)

Evaluation of the efficacy of animal-assisted therapy based on the reality orientation therapy protocol in Alzheimer's disease patients: a pilot study.

PubMed

Menna, Lucia Francesca; Santaniello, Antonio; Gerardi, Federica; Di Maggio, Annamaria; Milan, Graziella

2016-07-01

The aim of this study was to evaluate the efficacy of animal-assisted therapy (AAT) in elderly patients affected by Alzheimer's disease based on the formal reality orientation therapy (ROT) protocol. Our study was carried out at an Alzheimer's centre for 6 months. A homogeneous sample (age, Mini-Mental State Examination (MMSE), 15-item Geriatric Depression Scale (GDS)) of 50 patients was selected at random and successively. Patients were divided into three groups: (i) 20 patients received a course of AAT (AAT group) based on the ROT protocol; (ii) 20 patients were engaged exclusively in activities based on the ROT group; and (iii) 10 patients (control group) participated in no stimulations. MMSE and GDS were administered at time 0 (T0 ) and time 1 (T1 ) to all three groups. Differences within groups between T0 and T1 for GDS and MMSE scores were analyzed by Student's t-test. Differences between group means were analyzed using an anova test with the Bonferroni-Dunn test for post-hoc comparisons. Both the AAT group and ROT group had improved GDS scores and showed a slight improvement in terms of mood. On the GDS, the AAT group improved from 11.5 (T0 ) to 9.5 (T1 ), and the ROT group improved from 11.6 (T0 ) to 10.5 (T1 ). At the same time, a slight improvement in cognitive function, as measured by the MMSE, was observed. In the AAT group, mean MMSE was 20.2 at T0 and 21.5 at T1 , and in the ROT group, it was 19.9 at T0 and 20.0 at T1 . In the control group, the average values of both the GDS and MMSE remained unchanged. The Bonferroni-Dunn results showed statistically significant differences between groups, particularly between the AAT group and the other two (P < 0.001). Pet therapy interventions based on the formal ROT protocol were effective and, compared to the ROT, provided encouraging and statistically significant results. © 2015 The Authors. Psychogeriatrics © 2015 Japanese Psychogeriatric Society.

The sensitivity and specificity of subjective memory complaints and the subjective memory rating scale, deterioration cognitive observee, mini-mental state examination, six-item screener and clock drawing test in dementia screening.

PubMed

Ramlall, S; Chipps, J; Bhigjee, A I; Pillay, B J

2013-01-01

The effectiveness of dementia screening depends on the availability of suitable screening tools with good sensitivity and specificity to confidently distinguish normal age-related cognitive decline from dementia. The aim of this study was to evaluate the discriminant validity of 7 screening measures for dementia. A sample of 140 participants aged ≥60 years living in a residential facility for the aged were assessed clinically and assigned caseness for dementia using the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revised diagnostic criteria. Sensitivity and specificity of a selection of the following screening measures were tested using receiver operating characteristic (ROC) analysis for individual and combined tests: the Mini-Mental State Examination (MMSE), Six-Item Screener (SIS), Subjective Memory Complaint, Subjective Memory Complaint Clinical (SMCC), Subjective Memory Rating Scale (SMRS), Deterioration Cognitive Observee (DECO) and the Clock Drawing Test (CDT). Using ROC analyses, the SMCC, MMSE and CDT were found to be 'moderately accurate' in screening for dementia with an area under the curve (AUC) >0.70. The AUCs for the SIS (0.526), SMRS (0.661) and DECO (0.687) classified these measures as being 'less accurate'. At recommended cutoff scores, the SMCC had a sensitivity of 90.9% and specificity of 45.7%; the MMSE had a sensitivity of 63.6% and a specificity of 76.0%, and the CDT had a sensitivity of 44.4% and a specificity of 88.9%. Combining the SMCC and MMSE did not improve their predictive power except for a modest increase when using the sequential rule. The SMCC is composed of valid screening questions that have high sensitivity, are simple to administer and ideal for administration at the community or primary health care level as a first level of 'rule-out' screening. The MMSE can be included at a second stage of screening at the general hospital level and the CDT in specialist clinical settings. Sequential use of the SMCC and MMSE will improve the specificity of the former and the sensitivity of the latter. Copyright © 2013 S. Karger AG, Basel.

Modelling of the batch biosorption system: study on exchange of protons with cell wall-bound mineral ions.

PubMed

Mishra, Vishal

2015-01-01

The interchange of the protons with the cell wall-bound calcium and magnesium ions at the interface of solution/bacterial cell surface in the biosorption system at various concentrations of protons has been studied in the present work. A mathematical model for establishing the correlation between concentration of protons and active sites was developed and optimized. The sporadic limited residence time reactor was used to titrate the calcium and magnesium ions at the individual data point. The accuracy of the proposed mathematical model was estimated using error functions such as nonlinear regression, adjusted nonlinear regression coefficient, the chi-square test, P-test and F-test. The values of the chi-square test (0.042-0.017), P-test (<0.001-0.04), sum of square errors (0.061-0.016), root mean square error (0.01-0.04) and F-test (2.22-19.92) reported in the present research indicated the suitability of the model over a wide range of proton concentrations. The zeta potential of the bacterium surface at various concentrations of protons was observed to validate the denaturation of active sites.

Simple Forest Canopy Thermal Exitance Model

NASA Technical Reports Server (NTRS)

Smith J. A.; Goltz, S. M.

1999-01-01

We describe a model to calculate brightness temperature and surface energy balance for a forest canopy system. The model is an extension of an earlier vegetation only model by inclusion of a simple soil layer. The root mean square error in brightness temperature for a dense forest canopy was 2.5 C. Surface energy balance predictions were also in good agreement. The corresponding root mean square errors for net radiation, latent, and sensible heat were 38.9, 30.7, and 41.4 W/sq m respectively.

Plasma Klotho and Cognitive Decline in Older Adults: Findings From the InCHIANTI Study

PubMed Central

Semba, Richard D.; Rosano, Caterina; Kalyani, Rita R.; Bandinelli, Stefania; Chia, Chee W.; Ferrucci, Luigi

2016-01-01

Background. The hormone klotho, encoded by the gene klotho, is primarily expressed in the kidney and choroid plexus of the brain. Higher klotho concentrations and certain genetic variants of klotho have been linked to better cognition; however, it is unknown whether klotho relates prospectively to slower cognitive decline in older adults. Methods: Plasma klotho was measured in 833 participants aged 55 or older without dementia enrolled in InCHIANTI, a prospective cohort study comprising Italian adults. Cognition was measured by Mini-Mental State Examination (MMSE) and Trail-Making Tests A and B (Trails A and Trails B) at enrollment and at 3 and 6 years after enrollment. We assessed whether klotho concentrations measured at the 3-year visit related to cognition and cognitive decline. Results: Each additional natural logarithm of klotho (pg/mL) was associated with 35% lower risk of meaningful decline in MMSE, defined as decline exceeding three points (relative risk = 0.65; 95% confidence interval 0.45, 0.95; p value = .02), and 0.75-point smaller average 3-year decline (baseline to 3-year visit) in MMSE (95% confidence interval 0.02, 1.48; p value = .04). No statistically significant associations were found between klotho and declining Trails A (relative risk = 0.99; 95% confidence interval 0.75, 1.32; p value = .97) and B (relative risk = 1.02; 95% confidence interval 0.84, 1.24; p value = .82). Conclusions: Higher plasma klotho concentrations were associated with lower risk of meaningful decline and smaller average decline in MMSE. We did not observe such findings with Trails A and B, perhaps because they test executive function and motor skills, whereas MMSE measures global cognition. Future studies should investigate mechanisms through which klotho may affect domain-specific cognitive changes. PMID:26297657

The level of cognitive function and recognition of emotions in older adults

PubMed Central

Singh-Manoux, Archana; Batty, G. David; Ebmeier, Klaus P.; Jokela, Markus; Harmer, Catherine J.; Kivimäki, Mika

2017-01-01

Background The association between cognitive decline and the ability to recognise emotions in interpersonal communication is not well understood. We aimed to investigate the association between cognitive function and the ability to recognise emotions in other people’s facial expressions across the full continuum of cognitive capacity. Methods Cross-sectional analysis of 4039 participants (3016 men, 1023 women aged 59 to 82 years) in the Whitehall II study. Cognitive function was assessed using a 30-item Mini-Mental State Examination (MMSE), further classified into 8 groups: 30, 29, 28, 27, 26, 25, 24, and <24 (possible dementia) MMSE points. The Facial Expression Recognition Task (FERT) was used to examine recognition of anger, fear, disgust, sadness, and happiness. Results The multivariable adjusted difference in the percentage of accurate recognition between the highest and lowest MMSE group was 14.9 (95%CI, 11.1–18.7) for anger, 15.5 (11.9–19.2) for fear, 18.5 (15.2–21.8) for disgust, 11.6 (7.3–16.0) for sadness, and 6.3 (3.1–9.4) for happiness. However, recognition of several emotions was reduced already after 1 to 2-point reduction in MMSE and with further points down in MMSE, the recognition worsened at an accelerated rate. Conclusions The ability to recognize emotion in facial expressions is affected at an early stage of cognitive impairment and might decline at an accelerated rate with the deterioration of cognitive function. Accurate recognition of happiness seems to be less affected by a severe decline in cognitive performance than recognition of negatively valued emotions. PMID:28977015

Screening cognitive impairment among institutionalized older Chinese men in Taiwan: a new minimum data set-based dementia screening tool is needed.

PubMed

Lin, Chu-Sheng; Lin, Ming-Hsien; Peng, Li-Ning; Chen, Liang-Kung; Hwang, Shinn-Jang; Lan, Chung-Fu

2011-01-01

Dementia screening is of great importance in various health settings for older people, long-term care facilities are no exception. The need for an effective dementia screening tool being culture sensitive is important. Minimum data set (MDS) is a population instrument for health care management in the world, which also covers dementia screening. The main purpose of this study was to evaluate the effectiveness of the MDS-based dementia screening tools among older Chinese men in the Veteran Home in Taiwan. Overall, 576 participants (mean age: 80.9±5.3 years, all males, 92.7% physically independent), 18.6% had cognitive impairment according to the mini-mental state examination (MMSE) (mean score: 26.7±3.9). However, the prevalence of cognitive impairment was 5.5% by MDS cognitive performance scale (CPS) and 18.9% by MDS cognition scale (MDS-COGS). The screening results of CPS and MDS-COGS were highly interrelated (γ=0.93, p<0.001), and MMSE scores were also significantly associated with CPS and MDS-COGS status (γ=-0.50, p<0.001 and γ=-0.52, p<0.001, respectively). Although the prevalence of cognitive impairment by MMSE and MDS-COGS are similar, the results are significantly inconsistent (p<0.001). In conclusion, both MDS-COGS and CPS were significantly correlated with MMSE scores, but significant inconsistence was noted between screening results of MMSE, CPS and MDS-COGS. Further study is needed to develop MDS-based dementia screening tools for older Chinese men in Taiwan. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Drug Burden Index and change in cognition over time in community-dwelling older men: the CHAMP study.

PubMed

Jamsen, Kris M; Gnjidic, Danijela; Hilmer, Sarah N; Ilomäki, Jenni; Le Couteur, David G; Blyth, Fiona M; Handelsman, David J; Naganathan, Vasi; Waite, Louise M; Cumming, Robert G; Bell, J Simon

2017-03-01

Anticholinergic and sedative medications are associated with acute cognitive impairment, but the long-term impact on change in cognition is unclear. This study investigated the effect of anticholinergic and sedative medications, quantified using the Drug Burden Index (DBI), on change in cognition over time in community-dwelling older men. This was a prospective cohort study of men aged ≥70 years in Sydney, Australia. DBI was assessed at baseline, 2, and 5 years. Cognitive performance was assessed using the Mini-Mental State Exam (MMSE) at each wave. Logistic quantile mixed-effects modelling was used to assess the adjusted effect of DBI on the median MMSE-time profile. Analyses were restricted to men with English-speaking backgrounds (n = 1059, 862, and 611 at baseline, 2, and 5 years). Overall, 292 (27.7%), 258 (29.9%), and 189 (31.3%) men used anticholinergic or sedative medications at baseline, 2, and 5 years. There was a concave relationship between MMSE and time, where higher DBI corresponded to lower MMSE scores (coefficient: -0.161; 95% CI: -0.250 to -0.071) but not acceleration of declining MMSE over time. Exposure to anticholinergic and sedative medications is associated with a small impairment in cognitive performance but not decline in cognition over time. KEY MESSAGES Exposure to anticholinergic and sedative medications, quantified using the Drug Burden Index, is associated with small cross-sectional impairments in cognitive performance. There was no evidence that exposure to anticholinergic and sedative medications is associated with accelerating decline in cognitive performance over a 5-year follow-up. Older people taking anticholinergic and sedative medications may derive immediate but small benefits in cognitive performance from clinical medication reviews to minimize or cease prescribing of these medications.

The relationship of bilingualism to cognitive decline: The Australian Longitudinal Study of Ageing.

PubMed

Mukadam, Naaheed; Jichi, Fatima; Green, David; Livingston, Gill

2018-02-01

We wished to clarify the link between bilingualism and cognitive decline, and examine whether improved executive function due to bilingualism may be a factor in preventing cognitive decline. We used the Australian Longitudinal Study of Ageing which collected data on 2087 participants aged over 65 over 20 years. We compared baseline demographics, health, and social characteristics between bilingual and non-bilingual participants. We used linear mixed models analysis to explore the effect of bilingualism on MMSE score over time and linear regression to explore the effect of bilingualism on baseline MMSE scores, controlling for pre-specified potential confounders. Bilingual participants had lower baseline MMSE scores than the non-bilingual population (mean difference = -2.3 points; 95% confidence intervals = 1.56-2.90). This was fully explained by education and National Adult Reading Test scores (17.4; standard deviation [SD] =7.7 versus 28.1; SD = 8.2) which also partly explained baseline executive function test scores differences. Bilingual and non-bilingual participants did not differ in MMSE decline over time (-0.33 points, P = 0.31) nor on baseline tests of executive function (-0.26, P = 0.051). In this cohort, education rather than bilingualism was a predictor of MMSE score, and being bilingual did not protect from cognitive decline. We conclude that bilingualism is complex, and when it is not the result of greater educational attainment, it does not always protect from cognitive decline. Neuroprotective effects of bilingualism over time may be attributable to the precise patterns of language use but not to bilingualism per se. Copyright © 2017 John Wiley & Sons, Ltd.

Validation of the Chinese version of the NUCOG cognitive screening tool in patients with epilepsy, dementia and other neurological disorders.

PubMed

Gao, Lan; Li, Shu-Chuen; Xia, Li; Pan, Songqing; Velakoulis, Dennis; Walterfang, Mark

2014-06-01

We aimed to develop and validate a Chinese version of the Neuropsychiatry Unit Cognitive Assessment Tool (NUCOG) for use in Chinese-speaking subjects internationally. Patients and healthy controls were recruited from two hospitals between July and October 2012. Receiver operating characteristic (ROC) curves were utilized to test criterion validity. Convergent validity was assessed via correlations between NUCOG and the Mini-Mental State Examination (MMSE). Reliability was measured by internal consistency (Cronbach's α). Patients with epilepsy (n=144), neurological diseases (n=81), dementia (n=44), and controls (n=260) completed the NUCOG and the MMSE. Overall, both NUCOG and MMSE scores differed significantly across the four groups with the highest scores in the control group and the lowest in the dementia group (p<0.0001). The NUCOG scores could differentiate between patients with certain seizure types, stroke and transient ischemic attack. Compared to the MMSE, the NUCOG exhibited a higher area under the ROC curve. The convergent validity was substantially correlated, and internal consistency was very high (0.922). The Chinese version of NUCOG was demonstrated to be a sensitive and reliable screening tool for cognitive impairment in a Chinese-speaking population not only in China, but also in countries where there is a sizeable population of ethnic Chinese. Additionally, our study also showed the NUCOG could better differentiate cognitive function in patients with certain seizure types, stroke and transient ischemic attack than the MMSE. This potentially expands the clinical usefulness of NUCOG, enabling clinicians to measure the cognitive profile of patients with epilepsy and ischemic cerebrovascular diseases. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interaction Effects between HIV and Aging on Selective Neurocognitive Impairment.

PubMed

Ding, Yingying; Lin, Haijiang; Shen, Weiwei; Wu, Qionghai; Gao, Meiyang; He, Na

2017-12-01

HIV infection and aging are each associated with neurocognitive impairment (NCI). This study examined the combined effects of HIV infection and aging on NCI. We performed a cross-sectional survey among 345 HIV-infected and 345 HIV-uninfected participants aged at least 40 years. The International HIV Dementia Scale (IHDS) and Chinese version of Mini-mental State Examination (MMSE) were administered to screen for NCI. HIV-infected individuals had higher prevalence of NCI than uninfected individuals (46.7% vs 15.1% for IHDS using cut-off of ≤ 10; 17.1% vs 2.6% for MMSE). Significant main effects of HIV and age were observed on IHDS and MMSE composite scores and all domains except for HIV on attention and calculation. Significant interaction effects between HIV and age were observed on motor speed, orientation, registration and recall, and mainly attributed to the inferior performance of HIV-infected patients aged over 60 years. Among HIV-infected individuals, in multivariable logistic models, older age, depressive symptoms and history of nevirapine treatment were associated with NCI using both IHDS and MMSE, whereas lower education current smoker and current CD4 ≥ 800 cells/μL were associated only with NCI using IHDS, and hypertension was associated only with NCI using MMSE. Findings suggest that HIV and older age may confer interactive effects on cognitive function in several domains with older HIV-infected adults experiencing greater NCI, which requires further longitudinal investigation. Furthermore, HIV early diagnosis and treatment may prevent or reverse NCI, but extra attention should be given to adverse effects including metabolic changes associated with long-term treatment.

Correlates of self-reported, autobiographical, and mini-mental status examination defined memory deficits following electroconvulsive therapy in South India.

PubMed

Rajkumar, Anto P; Petit, Cheryl P; Rachana, Arun; Deinde, Funmi; Shyamsundar, G; Thangadurai, P; Jacob, Kuruthukulangara S

2018-04-01

Cognitive deficits, self-reported or found following electroconvulsive therapy (ECT), and their correlates are diverse. Despite the characteristics of people receiving ECT in Asia differ widely from the west, pertinent research from Asia remains sparse. We investigated the correlates of self-reported, mini-mental status examination (MMSE) defined, and autobiographical memory deficits in a cohort that received ECT in a south Indian tertiary-care setting. 76 consecutive consenting people were recruited within seven days of completing their ECT course. Memory was assessed by a subjective Likert scale, MMSE, and an autobiographical memory scale (AMS). Psychopathology was assessed by brief psychiatric rating scale, and serum cortisol levels were estimated by chemi-luminescence immunoassays. Relevant sociodemographic and clinical data were collected from the participants, and their medical records. The correlates were analysed using generalised linear models after adjusting for the effects of potential confounders. Self-reported, MMSE-defined, and autobiographical memory deficits were present in 27.6% (95%CI 17.6-37.7%), 42.1% (95%CI 31.0-53.2%), and 36.8% (95%CI 26.0-47.7%) of participants, respectively. Agreement between the memory deficits was poor. Age, less education, duration of illness, hypothyroidism, and past history of another ECT course were significantly associated with MMSE-defined deficits. Age, anaemia, past ECT course, and pre-ECT blood pressure were significantly associated with autobiographical memory deficits, while residual psychopathology and cortisol levels were significantly associated with self-reported memory deficits. Self-reported, MMSE-defined, and autobiographical memory deficits are common at the completion of ECT course, and their correlates differ. All service users receiving ECT need periodic cognitive assessments evaluating multiple cognitive domains. Copyright © 2018 Elsevier B.V. All rights reserved.

The effect of CPAP therapy on insulin-like growth factor and cognitive functions in obstructive sleep apnea patients.

PubMed

Kanbay, Asiye; Demir, Neslihan Cerrah; Tutar, Nuri; Köstek, Osman; Özer Şimşek, Zuhal; Buyukoglan, Hakan; Demir, Ramazan; Parrino, Liborio

2017-07-01

Cognitive impairment is common among patients with obstructive sleep apnea syndrome (OSAS). In this study, we aimed to investigate the effect of continuous positive airway pressure (CPAP) therapy on serum insulin-like growth factor-1 (IGF-1) levels and cognitive functions in patients with OSAS. Thirty-three patients with newly diagnosed OSAS and 17 healthy-control subjects enrolled in the study. All individuals completed the mini-mental state examination (MMSE) to evaluate cognitive function. Blood samples were taken at the end of the polysomnography in the morning and the same procedures were repeated 3 months after starting CPAP treatment. In the OSAS group, the baseline MMSE score was 23.5 ± 3.6, and serum IGF-1 level was 79.1 ± 36.1 ng/mL. Both values were significantly lower compared with the control group (mean MMSE score = 28.1 ± 1.4, P = 0.0001; mean serum IGF-1 level = 147.1 ± 49.1 ng/mL, P < 0.0001). Three months after CPAP treatment, OSAS patients showed a significant improvement in MMSE scores (26.5 ± 2.8, P = 0.0001) and serum IGF-1 level (129.1 ± 58.2, P = 0.0001). In contrast, baseline and third-month measurements for IGF-1 levels and MMSE scores were not significantly different in the control group. The results indicate that effective CPAP therapy in OSAS patients leads to significant improvement in cognitive functions and IGF-1 even in a short-term follow-up. Cognitive function assessment might be a part of evaluation in OSAS patients. © 2015 John Wiley & Sons Ltd.

Effects of transient versus chronic loneliness on cognitive function in older adults: Findings from the Chinese Longitudinal Healthy Longevity Survey

PubMed Central

Zhong, Bao-Liang; Chen, Shu-Lin; Conwell, Yeates

2016-01-01

Objectives Loneliness is a risk factor for poor cognitive function in older adults (OAs), however, to date, no studies have explored whether transient and chronic loneliness have differential effects on OAs’ cognitive function. The present study evaluates the impacts of transient versus chronic loneliness on cognitive function in OAs. Design A 6-year follow-up cohort study. Setting Rural and urban communities of 23 provinces in China. Participants 2995 OAs who were cognitively healthy (the modified Mini-mental State Examination [mMMSE] ≥ 14) and completed the 2005, 2008 and 2011 waves of the Chinese Longitudinal Healthy Longevity Survey. Measurements Self-report loneliness and mMMSE. Results Both transient (β=−0.389, t=−2.191, df=2994, P=0.029) and chronic loneliness (β=−0.640, t=−2.109, df=2994, P=0.035) were significantly associated with lower mMMSE scores six years later, net of potential confounding effects of baseline covariates. Sensitivity analyses found that regression coefficients of mMMSE scores on transient loneliness were statistically significant and relatively stable across samples with various levels of cognitive function. In contrast, coefficients of mMMSE scores on chronic loneliness were statistically significant only among samples with normal cognitive function and the absolute values of these coefficients increased with the degree of cognitive health of the analytic sample. In the sample with mMMSE≥21, the coefficient of chronic loneliness was 2.59 times as large as that of transient loneliness (−1.017 versus −0.392). Conclusions Both transient and chronic loneliness are significant predictors of cognitive decline in OAs. Relative to transient loneliness, chronic loneliness has more pronounced negative effects on the brain health of OAs. PMID:26905049

Cognitive function variations in postmenopausal women treated with continuous, combined HRT or tibolone. A comparison.

PubMed

Pan, Hsien-An; Wang, Shan-Tair; Pai, Ming-Chyi; Chen, Chih-Hung; Wu, Meng-Hsing; Huang, Ko-En

2003-05-01

To compare cognitive function in postmenopausal women receiving continuous hormone replacement therapy and those receiving tibolone. This was a 6-month, prospective, single-blind, single center, randomized study. A total of 50 healthy, postmenopausal women were enrolled. In the end, 40 women completed the 6-month follow-up. One group (23 subjects) received conjugated equine estrogens (CEE), 0.625 mg/d, and medroxyprogesterone acetate (MPA), 5 mg/d. The other group (17 subjects) received tibolone, 2.5 mg/d. Their serum estradiol levels and Cognitive Abilities Screening Instrument (CASI) and Mini-Mental State Examination (MMSE) scores were obtained before starting and after 3 and 6 months of treatment. There was a significant increase in the serum estradiol level in the CEE + MPA group, especially after 3 months of treatment, but there was no increase in the estradiol level in the tibolone group. The CASI and MMSE scores of the CEE + MPA group and the tibolone group after 3 and 6 months of treatment showed no significant difference between the two groups apart from the MMSE at the 3-month follow-up. We saw an increasing trend in CASI and MMSE scores after treatment in both groups; however, the increases were not statistically significant. The rate of increase of both CASI and MMSE scores in the CEE + MPA group was greater than in the tibolone group, though the difference was not significant. This preliminary study demonstrated that both CEE + MPA and tibolone can preserve cognitive function and may be able to prevent cognitive decline in postmenopausal women during short-term treatment. Our results also show that continuous, combined CEE + MPA seems to be marginally more effective than tibolone in improving cognitive processes; however, long-term study is needed to follow-up such effect.

Mild cognitive impairment is associated with poor physical function but not bone structure or density in late adulthood: findings from the Hertfordshire cohort study.

PubMed

Patel, A; Jameson, K A; Edwards, M H; Ward, K; Gale, C R; Cooper, C; Dennison, Elaine M

2018-04-24

This study investigated the association between mild cognitive impairment (MCI) and physical function and bone health in older adults. MCI was associated with poor physical performance but not bone mineral density or bone microarchitecture. Cross-sectional study to investigate the association between mild cognitive impairment (MCI) and physical performance, and bone health, in a community-dwelling cohort of older adults. Cognitive function of 222 men and 221 women (mean age 75.5 and 75.8 years in men and women, respectively) was assessed by the Strawbridge questionnaire and Mini Mental State Exam (MMSE). Participants underwent dual-energy X-ray absorptiometry (DXA), peripheral-quantitative computed tomography (pQCT) and high-resolution peripheral-quantitative computed tomography (HR-pQCT) scans to assess their bone density, strength and microarchitecture. Their physical function was assessed and a physical performance (PP) score was recorded. In the study, 11.8% of women and 8.1% of men were cognitively impaired on the MMSE (score < 24). On the Strawbridge questionnaire, 24% of women were deemed cognitively impaired compared to 22.3% of men. Cognitive impairment on the Strawbridge questionnaire was associated with poorer physical performance score in men but not in women in the unadjusted analysis. MMSE < 24 was strongly associated with the risk of low physical performance in men (OR 12.9, 95% CI 1.67, 99.8, p = 0.01). Higher MMSE score was associated with better physical performance in both sexes. Poorer cognitive function, whether assessed by the Strawbridge questionnaire, or by MMSE score, was not associated with bone density, shape or microarchitecture, in either sex. MCI in older adults was associated with poor physical performance, but not bone density, shape or microarchitecture.

Cognitive impairment associated with locomotive syndrome in community-dwelling elderly women in Japan.

PubMed

Nakamura, Misa; Tazaki, Fumie; Nomura, Kazuki; Takano, Taeko; Hashimoto, Masashi; Hashizume, Hiroshi; Kamei, Ichiro

2017-01-01

In our worldwide aging society, elderly people should maintain cognitive and physical function to help avoid health problems. Dementia is a major brain disease among elderly people, and is caused by cognitive impairment. The locomotive syndrome (LS) refers to a condition in which people require healthcare services because of problems associated with locomotion. The purpose of this study was to determine the association between cognitive impairment and LS. Study participants were 142 healthy elderly female volunteers living in a rural area in Japan. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). A score of ≤26 points on the MMSE was used to indicate categorically defined poor cognitive performance (cognitive impairment). The LS was defined by a score ≥16 points, and non-LS as <16 points, on the 25-question Geriatric Locomotive Function Scale (GLFS-25). Twenty-one participants (14.8%) had an MMSE score ≤26, and 19.0% were found to have LS. Compared with the MMSE >26 group, the ≤26 group was significantly older, had a higher percentage of body fat, and a higher GLFS-25 score. Those with LS were significantly older, had a higher body mass index, a higher percentage of body fat, and a lower MMSE score. Participants in the LS group had higher odds of cognitive impairment than those without LS [odds ratio (OR) =3.08] by logistic regression analysis adjusted for age. Furthermore, participants with GLFS-25 scores ≥6 had higher odds of cognitive impairment than those with a GLFS-25 score <6 by logistic regression analysis adjusted for both age (OR =4.44), and age and percent body fat (OR =4.12). These findings suggest that a strong relationship exists between the early stage of decreased motor function and cognitive impairment.

Cognitive abilities screening instrument-short form, mini-mental state examination and functional activities questionnaire in the illiterate elderly

PubMed Central

Rezende, Gabriela Pravatta; Cecato, Juliana; Martinelli, José Eduardo

2013-01-01

Dementia prevalence is increasing in developing countries due to population aging. Brief tests for assessing cognition and activities of daily living are very useful for the diagnosis of dementia by the clinician. Low education, particularly illiteracy, is a hindrance to the diagnosis of dementia in several regions of the world. OBJECTIVES To compare the Brazilian version of the Cognitive Abilities Screening Instrument-Short Form (CASI-S) with the Mini-Mental State Examination (MMSE) and Pfeffer Functional Activities Questionnaire (PFAQ) for the diagnosis of dementia in illiterate elderly. METHODS A cross-sectional study with illiterate elderly of both genders seen at the outpatient clinics of the Institute of Gerontology and Geriatrics Jundiaí, São Paulo state was performed. Spearman's correlation coefficient was used to correlate CASI-S, MMSE and PFAQ scores. RESULTS The sample comprised 29 elderly over 57 years old whose mean scores on the CASI-S (scores ranging from 3 to 23) and the MMSE (scores ranging from 2 to 23) were 11.69 and 12.83, respectively. There was a strong significant correlation between the CASI-S and MMSE (r=0.75, p<0.001) and a moderate correlation coefficient that was significant and negative between the PFAQ and CASI-S (r= –0.53 p=0.003),similar to that between the MMSE and PFAQ (r= –0.41 p=0.025). CONCLUSION The Brazilian version of the CASI-S demonstrates ease of application and correction in the illiterate elderly, and warrants further studies regarding its applicability for the diagnosis of dementia in populations with a heterogeneous educational background. PMID:29213866

[Effects of physical activity on cognitive functions, balance and risk of falls in elderly patients with Alzheimer's dementia].

PubMed

Hernandez, Salma S S; Coelho, Flávia G M; Gobbi, Sebastião; Stella, Florindo

2010-01-01

To analyze the effects of regular, systematic and supervised activity on the cognitive functions, balance and risk of falls of elderly patients with Alzheimer's Dementia (AD). Sixteen elderly patients (mean age 78.5+/-6.8 years) were divided into two groups: intervention group (IG; n=9) and routine group (RG; n=7). The IG exercised systematically for six months, and both groups were submitted to the following tests: Mini-Mental State Examination (MMSE), Berg Balance Scale (BBS), Timed Up-and-Go (TUG) and the agility/dynamic balance (AGIBAL) item of the American Alliance for Health, Physical Education, Recreation and Dance (AAHPERD) test battery. There was a statistically significant interaction (two-way ANOVA; F1,14=32.07; p=0.01) between groups and moments for the AGIBAL. The Mann Whitney U test indicated significant differences between groups (p=0.03), only at the post-intervention moment for the TUG measured in steps and for BBS. Therefore, no significant intergroup differences were found for the TUG, BBS and MMSE at the pre-intervention moment or at post-intervention moment for the TUG measured in seconds and MMSE. The intragroup analysis by means of the Wilcoxon test showed a significant decline in the TUG, BBS and MMSE for the RG, but not for the IG. Spearman's coefficient showed a significant correlation between the results of the MMSE and AGIBAL. Physical activity may be an important non-pharmacological approach that can benefit cognitive functions and balance and reduce the risk of falls. Moreover, agility and balance are associated with cognitive functions in elderly patients with AD.

Effects of Exercise on Cognitive Function in Older People with Dementia: A Randomized Controlled Trial.

PubMed

Toots, Annika; Littbrand, Håkan; Boström, Gustaf; Hörnsten, Carl; Holmberg, Henrik; Lundin-Olsson, Lillemor; Lindelöf, Nina; Nordström, Peter; Gustafson, Yngve; Rosendahl, Erik

2017-01-01

Although physical exercise has been suggested to influence cognitive function, previous exercise studies show inconsistent results in people with dementia. To investigate effects of exercise on cognitive function in people with dementia. The Umeå Dementia and Exercise (UMDEX) study, a cluster-randomized controlled trial, was set in 16 nursing homes in Umeå, Sweden. One hundred-and-forty-one women and 45 men with dementia; mean age of 85 y and mean Mini-Mental State Examination (MMSE) score of 15, were randomized to a High-Intensity Functional Exercise program or a seated attention control activity. Blinded assessors measured global cognitive function using the MMSE and the Alzheimer's disease Assessment Scale - Cognitive subscale (ADAS-Cog), and executive function using Verbal fluency (VF) at baseline and 4 months (directly after intervention completion), and MMSE and VF at 7 months. Linear mixed models showed no between-group effects in mean difference from baseline (95% confidence intervals, CI) at 4 months in MMSE (-0.27; 95% CI -1.4 to 0.87, p = 0.644), ADAS-Cog (-1.04, 95% CI -4 to 1.92, p = 0.491), or VF (-0.53, 95% CI -1.42 to 0.35, p = 0.241) or at 7 months in MMSE (-1.15, 95% CI -2.32 to 0.03, p = 0.056) or VF (-0.18, 95% CI -1.09 to 0.74, p = 0.707). A 4-month, high-intensity functional exercise program had no superior effects on global cognition or executive function in people with dementia living in nursing homes when compared with an attention control activity.

Long-term cumulative depressive symptom burden and risk of cognitive decline and dementia among very old women.

PubMed

Zeki Al Hazzouri, Adina; Vittinghoff, Eric; Byers, Amy; Covinsky, Ken; Blazer, Dan; Diem, Susan; Ensrud, Kristine E; Yaffe, Kristine

2014-05-01

Depressive symptoms and cognitive outcomes are strongly interrelated. Despite that rates of depressive symptoms fluctuate during late life, little is known about the impact of long-term cumulative depressive symptom burden on cognitive decline and dementia in older adults. This study examines the association of nearly 20 years of cumulative depressive symptoms with cognitive outcomes in a cohort of older women. We assessed depressive symptoms in 7,240 women using the Geriatric Depression scale (GDS) at serial visits. We used a Poisson model with random slopes to estimate GDS trajectories for each participant from baseline to death or end of follow-up, and then characterized depressive symptom burden by quartile of the area under the curve. We assessed cognitive outcomes using repeated measures of the Mini-Mental State Examination (MMSE) and Trails B score over 20 years, Year-20 neuropsychological test battery, and adjudicated dementia and mild cognitive impairment (MCI). Adjusting for potential confounders, compared with women in the lowest quartile of cumulative depressive symptoms burden, women in the highest quartile had 21% more MMSE errors over time (95% CI = 17%, 26%), 20% worse Trails B score over time (95% CI = 17%, 23%), worse scores on most of the Year-20 cognitive tests, and a twofold greater likelihood of developing dementia or MCI (95% CI = 1.48, 3.11). Long-term cumulative depressive symptom burden was associated with cognitive decline and risk of dementia or MCI. Older adults with a history of depression should be closely monitored for recurrent episodes or unresolved depressive symptoms as well as any cognitive deficits.

Measuring Dispersion Effects of Factors in Factorial Experiments.

DTIC Science & Technology

1988-01-01

error is MSE =i=l j=1 i n r (SSE/(N-p)), the sum of squares of pure error is SSPE = Z E Y i=1 j=1 and the mean square of pure error is MSPE - ( SSPE /n...the level of the factor in the ith run is 0. 3.1. First Measure We have n r n r SSPE = 1 Is it -yi) 2 + E r (1-8 )(yjj li-l j=l (iYjj +i= j=l l - i...The first component in SSPE corresponds to level I of the factor and has n degrees of freedom ( E 6i)(r-I). The second component corresponds to i=l n

Smooth empirical Bayes estimation of observation error variances in linear systems

NASA Technical Reports Server (NTRS)

Martz, H. F., Jr.; Lian, M. W.

1972-01-01

A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.

Comparison of Three Cognitive Screening Tools in Older Urban and Regional Aboriginal Australians.

PubMed

Radford, Kylie; Mack, Holly A; Draper, Brian; Chalkley, Simon; Delbaere, Kim; Daylight, Gail; Cumming, Robert G; Bennett, Hayley; Broe, Gerald A

2015-01-01

Validated cognitive screening tools for use in urban and regional Aboriginal populations in Australia are lacking. In a cross-sectional community-based study, 235 participants were assessed on the Mini-Mental State Examination (MMSE), the Rowland Universal Dementia Assessment Scale (RUDAS) and an urban modification of the Kimberley Indigenous Cognitive Assessment (mKICA). Performance on these cognitive screening tools was compared to dementia diagnosis by clinical consensus. All tests were culturally acceptable with good psychometric properties. Receiver operating characteristic curve analyses revealed that the MMSE and mKICA were the most accurate. The MMSE is an effective cognitive screening tool in urban Aboriginal populations. The mKICA is a good alternative when illiteracy, language or cultural considerations deem it appropriate. The RUDAS also has adequate validity in this population. © 2015 S. Karger AG, Basel.

Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

Treesearch

Bernard R. Parresol

1993-01-01

In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

Application of Least Mean Square Algorithms to Spacecraft Vibration Compensation

NASA Technical Reports Server (NTRS)

Woodard , Stanley E.; Nagchaudhuri, Abhijit

1998-01-01

This paper describes the application of the Least Mean Square (LMS) algorithm in tandem with the Filtered-X Least Mean Square algorithm for controlling a science instrument's line-of-sight pointing. Pointing error is caused by a periodic disturbance and spacecraft vibration. A least mean square algorithm is used on-orbit to produce the transfer function between the instrument's servo-mechanism and error sensor. The result is a set of adaptive transversal filter weights tuned to the transfer function. The Filtered-X LMS algorithm, which is an extension of the LMS, tunes a set of transversal filter weights to the transfer function between the disturbance source and the servo-mechanism's actuation signal. The servo-mechanism's resulting actuation counters the disturbance response and thus maintains accurate science instrumental pointing. A simulation model of the Upper Atmosphere Research Satellite is used to demonstrate the algorithms.

A partial least squares based spectrum normalization method for uncertainty reduction for laser-induced breakdown spectroscopy measurements

NASA Astrophysics Data System (ADS)

Li, Xiongwei; Wang, Zhe; Lui, Siu-Lung; Fu, Yangting; Li, Zheng; Liu, Jianming; Ni, Weidou

2013-10-01

A bottleneck of the wide commercial application of laser-induced breakdown spectroscopy (LIBS) technology is its relatively high measurement uncertainty. A partial least squares (PLS) based normalization method was proposed to improve pulse-to-pulse measurement precision for LIBS based on our previous spectrum standardization method. The proposed model utilized multi-line spectral information of the measured element and characterized the signal fluctuations due to the variation of plasma characteristic parameters (plasma temperature, electron number density, and total number density) for signal uncertainty reduction. The model was validated by the application of copper concentration prediction in 29 brass alloy samples. The results demonstrated an improvement on both measurement precision and accuracy over the generally applied normalization as well as our previously proposed simplified spectrum standardization method. The average relative standard deviation (RSD), average of the standard error (error bar), the coefficient of determination (R2), the root-mean-square error of prediction (RMSEP), and average value of the maximum relative error (MRE) were 1.80%, 0.23%, 0.992, 1.30%, and 5.23%, respectively, while those for the generally applied spectral area normalization were 3.72%, 0.71%, 0.973, 1.98%, and 14.92%, respectively.

Super-linear Precision in Simple Neural Population Codes

NASA Astrophysics Data System (ADS)

Schwab, David; Fiete, Ila

2015-03-01

A widely used tool for quantifying the precision with which a population of noisy sensory neurons encodes the value of an external stimulus is the Fisher Information (FI). Maximizing the FI is also a commonly used objective for constructing optimal neural codes. The primary utility and importance of the FI arises because it gives, through the Cramer-Rao bound, the smallest mean-squared error achievable by any unbiased stimulus estimator. However, it is well-known that when neural firing is sparse, optimizing the FI can result in codes that perform very poorly when considering the resulting mean-squared error, a measure with direct biological relevance. Here we construct optimal population codes by minimizing mean-squared error directly and study the scaling properties of the resulting network, focusing on the optimal tuning curve width. We then extend our results to continuous attractor networks that maintain short-term memory of external stimuli in their dynamics. Here we find similar scaling properties in the structure of the interactions that minimize diffusive information loss.

COMPASS: A computational model to predict changes in MMSE scores 24-months after initial assessment of Alzheimer's disease.

PubMed

Zhu, Fan; Panwar, Bharat; Dodge, Hiroko H; Li, Hongdong; Hampstead, Benjamin M; Albin, Roger L; Paulson, Henry L; Guan, Yuanfang

2016-10-05

We present COMPASS, a COmputational Model to Predict the development of Alzheimer's diSease Spectrum, to model Alzheimer's disease (AD) progression. This was the best-performing method in recent crowdsourcing benchmark study, DREAM Alzheimer's Disease Big Data challenge to predict changes in Mini-Mental State Examination (MMSE) scores over 24-months using standardized data. In the present study, we conducted three additional analyses beyond the DREAM challenge question to improve the clinical contribution of our approach, including: (1) adding pre-validated baseline cognitive composite scores of ADNI-MEM and ADNI-EF, (2) identifying subjects with significant declines in MMSE scores, and (3) incorporating SNPs of top 10 genes connected to APOE identified from functional-relationship network. For (1) above, we significantly improved predictive accuracy, especially for the Mild Cognitive Impairment (MCI) group. For (2), we achieved an area under ROC of 0.814 in predicting significant MMSE decline: our model has 100% precision at 5% recall, and 91% accuracy at 10% recall. For (3), "genetic only" model has Pearson's correlation of 0.15 to predict progression in the MCI group. Even though addition of this limited genetic model to COMPASS did not improve prediction of progression of MCI group, the predictive ability of SNP information extended beyond well-known APOE allele.

Sources of Variation on the Mini-Mental State Examination in a Population-Based Sample of Centenarians

PubMed Central

Dai, Ting; Davey, Adam; Woodard, John L.; Miller, L. Stephen; Gondo, Yasuyuki; Kim, Seock-Ho; Poon, Leonard W.

2013-01-01

Centenarians represent a rare but rapidly growing segment of the oldest-old. This study presents item-level data from the Mini-Mental State Examination (MMSE, M=16.2, SD=8.8, Range 0–30) in a cross-sectional, population-based sample of 244 centenarians and near-centenarians (aged 98–108, 16% men, 21% African-American, 38% community-dwelling) from the Georgia Centenarian Study (2001–2008) by age, education, sex, race, and residential status. Multiple-Indicator Multiple-Causes (MIMIC) models were used to identify systematic domain-level differences on MMSE scores by key demographic characteristics in this age group. Indirect effects of age, educational attainment, race, and residential status were found on MMSE scores. Direct effects were limited to concentration for education and race, and orientation for residential status. Mean levels of cognitive functioning in centenarians were low, with mean values below most commonly-used cut-offs. Overall scores on the MMSE differed as a function of age, education, race, and residential status, with differences in scale performance limited primarily to concentration and orientation, with no evidence for interactions among centenarian characteristics. Adjusting for education was not sufficient to account for differences by race; adjusting for residential status was not sufficient to account for differences by age. PMID:23889552

Prognosis of Treatment Outcomes by Cognitive and Physical Scales.

PubMed

Jakavonytė-Akstinienė, Agnė; Dikčius, Vytautas; Macijauskienė, Jūratė

2018-01-01

The aim of this study was to assess the possibility of using scales for measuring cognitive and physical functions for a prognosis of care outcomes in elderly patients. The survey was carried out in one of the Vilnius City Hospitals for Nursing and Support Treatment. A total number of 177 respondents were involved in the study. The Mini-Mental State Examination (MMSE), The Barthel Index (BI) and The Morse Fall Scale were used. A statistically significant correlation was revealed between the scores of MMSE and BI (Pearson R = 0.41, p < 0.01); those with severe cognitive impairment were more dependent. A statistically significant correlation (Pearson R = -0.181, p < 0.01) was reported between the scores of MMSE and the Morse Fall Scale - the risk of falling was higher in patients with severe cognitive impairment. The Morse Fall Scale was not suitable for the prognosis of outcomes. The MMSE was suitable for the prognosis of a patient's discharge. The Barthel Index should be considered as the most suitable tool for the prognosis of care outcomes: the sum-score of the Barthel Index above 25 may suggest that the patient would be discharged home; the sum-score below this level was associated with a higher likelihood of patient death.

[Cognitive disorders and falls: experience of the Lille multidisciplinary falls service].

PubMed

Maeker, E; Bombois, S; Pardessus, V; Tiberghien, F; Dipompeo, C; Thevenon, A; Dewailly, P; Puisieux, F

2005-04-01

Falls and dementia are two major public health problems which concern the elderly population. Cognitive impairment, as a result of Alzheimer's disease or non-Alzheimer dementia, is recognized as a risk factor for falling. Through the experience of the Multidisciplinary Falls Consultation, our aims were first, to evaluate the prevalence of a cognitive decline among outpatients who consult for falls, and second, to determine whether the cognitive impairment was known and diagnosed before the consultation or not. Data concerning the first 300 outpatients who completed the initial evaluation are reported. Each patient was assessed by a geriatrician, a neurologist, and a physiatrist, who visited him or her at home. Cognitive impairment was defined as a Mini-Mental State Examination (MMSE) score<24. Of the 300 patients, 228 patients completed the initial evaluation. Among them, 97 (42.5 percent) had a MMSE score<24; 55 had mild stage dementia (MMSE score between 23 and 18) and 42 were at a moderate or severe stage (MMSE score< or =17/30). The cognitive decline was not diagnosed before the consultation in 80 of the 97 patients (82 percent). The findings show that a large proportion of old persons presenting with gait disturbance at the Multidisciplinary Falls Consultation have an underlying cognitive decline. Assessment of cognitive functions is required in every elderly faller.

Engaged Lifestyle, Personality, and Mental Status Among Centenarians

PubMed Central

Baenziger, Joan; MacDonald, Maurice; Siegler, Ilene C.; Poon, Leonard W.

2010-01-01

This study assessed engaged lifestyle activities (e.g., volunteering, traveling, and public speaking) for centenarians of the Georgia Centenarian Study. A total of 285 centenarians and near-centenarians (i.e., 98 years and older) and their proxy informants participated in this study. The Mini-Mental Status Examination (MMSE) was assessed for all centenarians, and proxy informants reported on lifestyle activities and personality traits of the centenarians. Results suggested that participants who had volunteered, traveled, and those who had given public talks and balanced their checkbooks were more likely to show relatively high mental status scores (i.e., MMSE > 17). Personality traits were found to be moderators in the relationship between engaged lifestyle and mental status: Participants with high levels of Emotional Stability, Extraversion, Openness, and Conscientiousness and with high levels of engaged lifestyle were more likely to show relatively high mental status scores (i.e., MMSE > 17), whereas participants with low levels of Emotional Stability, Extraversion, Openness, Agreeableness, and Conscientiousness and with low levels of engaged lifestyle were more likely to show relatively low mental status scores (i.e., MMSE < 18). The results suggest that engaged lifestyle, particularly in combination with personality traits, plays an important role in the level of cognitive functioning among oldest old adults. PMID:21132076

Predicting the Rate of Cognitive Decline in Alzheimer Disease: Data From the ICTUS Study.

PubMed

Canevelli, Marco; Kelaiditi, Eirini; Del Campo, Natalia; Bruno, Giuseppe; Vellas, Bruno; Cesari, Matteo

2016-01-01

Different rates of cognitive progression have been observed among Alzheimer disease (AD) patients. The present study aimed at evaluating whether the rate of cognitive worsening in AD may be predicted by widely available and easy-to-assess factors. Mild to moderate AD patients were recruited in the ICTUS study. Multinomial logistic regression analysis was performed to measure the association between several sociodemographic and clinical variables and 3 different rates of cognitive decline defined by modifications (after 1 year of follow-up) of the Mini Mental State Examination (MMSE) score: (1) "slow" progression, as indicated by a decrease in the MMSE score ≤1 point; (2) "intermediate" progression, decrease in the MMSE score between 2 and 5 points; and (3) "rapid" progression, decrease in the MMSE score ≥6 points. A total of 1005 patients were considered for the present analyses. Overall, most of the study participants (52%) exhibited a slow cognitive course. Higher ADAS-Cog scores at baseline were significantly associated with both "intermediate" and "rapid" decline. Conversely, increasing age was negatively associated with "rapid" cognitive worsening. A slow progression of cognitive decline is common among AD patients. The influence of age and baseline cognitive impairment should always be carefully considered when designing AD trials and defining study populations.

Geospatial distribution modeling and determining suitability of groundwater quality for irrigation purpose using geospatial methods and water quality index (WQI) in Northern Ethiopia

NASA Astrophysics Data System (ADS)

Gidey, Amanuel

2018-06-01

Determining suitability and vulnerability of groundwater quality for irrigation use is a key alarm and first aid for careful management of groundwater resources to diminish the impacts on irrigation. This study was conducted to determine the overall suitability of groundwater quality for irrigation use and to generate their spatial distribution maps in Elala catchment, Northern Ethiopia. Thirty-nine groundwater samples were collected to analyze and map the water quality variables. Atomic absorption spectrophotometer, ultraviolet spectrophotometer, titration and calculation methods were used for laboratory groundwater quality analysis. Arc GIS, geospatial analysis tools, semivariogram model types and interpolation methods were used to generate geospatial distribution maps. Twelve and eight water quality variables were used to produce weighted overlay and irrigation water quality index models, respectively. Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation. The overall weighted overlay model result showed that 146 km2 areas are highly suitable, 135 km2 moderately suitable and 60 km2 area unsuitable for irrigation use. The result of irrigation water quality index confirms 10.26% with no restriction, 23.08% with low restriction, 20.51% with moderate restriction, 15.38% with high restriction and 30.76% with the severe restriction for irrigation use. GIS and irrigation water quality index are better methods for irrigation water resources management to achieve a full yield irrigation production to improve food security and to sustain it for a long period, to avoid the possibility of increasing environmental problems for the future generation.

Methods for estimating the magnitude and frequency of peak streamflows at ungaged sites in and near the Oklahoma Panhandle

USGS Publications Warehouse

Smith, S. Jerrod; Lewis, Jason M.; Graves, Grant M.

2015-09-28

Generalized-least-squares multiple-linear regression analysis was used to formulate regression relations between peak-streamflow frequency statistics and basin characteristics. Contributing drainage area was the only basin characteristic determined to be statistically significant for all percentage of annual exceedance probabilities and was the only basin characteristic used in regional regression equations for estimating peak-streamflow frequency statistics on unregulated streams in and near the Oklahoma Panhandle. The regression model pseudo-coefficient of determination, converted to percent, for the Oklahoma Panhandle regional regression equations ranged from about 38 to 63 percent. The standard errors of prediction and the standard model errors for the Oklahoma Panhandle regional regression equations ranged from about 84 to 148 percent and from about 76 to 138 percent, respectively. These errors were comparable to those reported for regional peak-streamflow frequency regression equations for the High Plains areas of Texas and Colorado. The root mean square errors for the Oklahoma Panhandle regional regression equations (ranging from 3,170 to 92,000 cubic feet per second) were less than the root mean square errors for the Oklahoma statewide regression equations (ranging from 18,900 to 412,000 cubic feet per second); therefore, the Oklahoma Panhandle regional regression equations produce more accurate peak-streamflow statistic estimates for the irrigated period of record in the Oklahoma Panhandle than do the Oklahoma statewide regression equations. The regression equations developed in this report are applicable to streams that are not substantially affected by regulation, impoundment, or surface-water withdrawals. These regression equations are intended for use for stream sites with contributing drainage areas less than or equal to about 2,060 square miles, the maximum value for the independent variable used in the regression analysis.

[NIR Assignment of Magnolol by 2D-COS Technology and Model Application Huoxiangzhengqi Oral Liduid].

PubMed

Pei, Yan-ling; Wu, Zhi-sheng; Shi, Xin-yuan; Pan, Xiao-ning; Peng, Yan-fang; Qiao, Yan-jiang

2015-08-01

Near infrared (NIR) spectroscopy assignment of Magnolol was performed using deuterated chloroform solvent and two-dimensional correlation spectroscopy (2D-COS) technology. According to the synchronous spectra of deuterated chloroform solvent and Magnolol, 1365~1455, 1600~1720, 2000~2181 and 2275~2465 nm were the characteristic absorption of Magnolol. Connected with the structure of Magnolol, 1440 nm was the stretching vibration of phenolic group O-H, 1679 nm was the stretching vibration of aryl and methyl which connected with aryl, 2117, 2304, 2339 and 2370 nm were the combination of the stretching vibration, bending vibration and deformation vibration for aryl C-H, 2445 nm were the bending vibration of methyl which linked with aryl group, these bands attribut to the characteristics of Magnolol. Huoxiangzhengqi Oral Liduid was adopted to study the Magnolol, the characteristic band by spectral assignment and the band by interval Partial Least Squares (iPLS) and Synergy interval Partial Least Squares (SiPLS) were used to establish Partial Least Squares (PLS) quantitative model, the coefficient of determination Rcal(2) and Rpre(2) were greater than 0.99, the Root Mean of Square Error of Calibration (RM-SEC), Root Mean of Square Error of Cross Validation (RMSECV) and Root Mean of Square Error of Prediction (RMSEP) were very small. It indicated that the characteristic band by spectral assignment has the same results with the Chemometrics in PLS model. It provided a reference for NIR spectral assignment of chemical compositions in Chinese Materia Medica, and the band filters of NIR were interpreted.

An empirical model for estimating solar radiation in the Algerian Sahara

NASA Astrophysics Data System (ADS)

Benatiallah, Djelloul; Benatiallah, Ali; Bouchouicha, Kada; Hamouda, Messaoud; Nasri, Bahous

2018-05-01

The present work aims to determine the empirical model R.sun that will allow us to evaluate the solar radiation flues on a horizontal plane and in clear-sky on the located Adrar city (27°18 N and 0°11 W) of Algeria and compare with the results measured at the localized site. The expected results of this comparison are of importance for the investment study of solar systems (solar power plants for electricity production, CSP) and also for the design and performance analysis of any system using the solar energy. Statistical indicators used to evaluate the accuracy of the model where the mean bias error (MBE), root mean square error (RMSE) and coefficient of determination. The results show that for global radiation, the daily correlation coefficient is 0.9984. The mean absolute percentage error is 9.44 %. The daily mean bias error is -7.94 %. The daily root mean square error is 12.31 %.

Response Surface Modeling Using Multivariate Orthogonal Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; DeLoach, Richard

2001-01-01

A nonlinear modeling technique was used to characterize response surfaces for non-dimensional longitudinal aerodynamic force and moment coefficients, based on wind tunnel data from a commercial jet transport model. Data were collected using two experimental procedures - one based on modem design of experiments (MDOE), and one using a classical one factor at a time (OFAT) approach. The nonlinear modeling technique used multivariate orthogonal functions generated from the independent variable data as modeling functions in a least squares context to characterize the response surfaces. Model terms were selected automatically using a prediction error metric. Prediction error bounds computed from the modeling data alone were found to be- a good measure of actual prediction error for prediction points within the inference space. Root-mean-square model fit error and prediction error were less than 4 percent of the mean response value in all cases. Efficacy and prediction performance of the response surface models identified from both MDOE and OFAT experiments were investigated.

Effective Algorithm for Detection and Correction of the Wave Reconstruction Errors Caused by the Tilt of Reference Wave in Phase-shifting Interferometry

NASA Astrophysics Data System (ADS)

Xu, Xianfeng; Cai, Luzhong; Li, Dailin; Mao, Jieying

2010-04-01

In phase-shifting interferometry (PSI) the reference wave is usually supposed to be an on-axis plane wave. But in practice a slight tilt of reference wave often occurs, and this tilt will introduce unexpected errors of the reconstructed object wave-front. Usually the least-square method with iterations, which is time consuming, is employed to analyze the phase errors caused by the tilt of reference wave. Here a simple effective algorithm is suggested to detect and then correct this kind of errors. In this method, only some simple mathematic operation is used, avoiding using least-square equations as needed in most methods reported before. It can be used for generalized phase-shifting interferometry with two or more frames for both smooth and diffusing objects, and the excellent performance has been verified by computer simulations. The numerical simulations show that the wave reconstruction errors can be reduced by 2 orders of magnitude.

Validation of Core Temperature Estimation Algorithm

DTIC Science & Technology

2016-01-29

plot of observed versus estimated core temperature with the line of identity (dashed) and the least squares regression line (solid) and line equation...estimated PSI with the line of identity (dashed) and the least squares regression line (solid) and line equation in the top left corner. (b) Bland...for comparison. The root mean squared error (RMSE) was also computed, as given by Equation 2.

Systematic Error Modeling and Bias Estimation

PubMed Central

Zhang, Feihu; Knoll, Alois

2016-01-01

This paper analyzes the statistic properties of the systematic error in terms of range and bearing during the transformation process. Furthermore, we rely on a weighted nonlinear least square method to calculate the biases based on the proposed models. The results show the high performance of the proposed approach for error modeling and bias estimation. PMID:27213386

Relationship between dietary pattern and cognitive function in elderly patients with type 2 diabetes mellitus.

PubMed

Enomoto, Mari; Yoshii, Hidenori; Mita, Tomoya; Sanke, Haruna; Yokota, Ayako; Yamashiro, Keiko; Inagaki, Noriko; Gosho, Masahiko; Ohmura, Chie; Kudo, Kayo; Watada, Hirotaka; Onuma, Tomio

2015-08-01

To analyse the relationships between dietary patterns and cognitive function in elderly patients with type 2 diabetes mellitus (T2DM). Patients with T2DM completed a 3-day dietary record and Mini-mental State Examination (MMSE). Dietary patterns were identified by factor analysis. The study included 73 patients and identified five dietary patterns, one of which was characterized by high loading for vegetables and fish. A higher consumption of vegetables and fish was significantly associated with improved MMSE score (unadjusted model, model adjusted for age and sex, and model adjusted for age, sex, education, diabetic nephropathy and alcohol consumption), and decreased prevalence of suspected mild dementia (unadjusted model, model adjusted for age and sex). A high score in the vegetables and fish dietary pattern was associated with high MMSE score and low prevalence of suspected mild dementia in elderly patients with T2DM. © The Author(s) 2015.

Photogrammetric Method and Software for Stream Planform Identification

NASA Astrophysics Data System (ADS)

Stonedahl, S. H.; Stonedahl, F.; Lohberg, M. M.; Lusk, K.; Miller, D.

2013-12-01

Accurately characterizing the planform of a stream is important for many purposes, including recording measurement and sampling locations, monitoring change due to erosion or volumetric discharge, and spatial modeling of stream processes. While expensive surveying equipment or high resolution aerial photography can be used to obtain planform data, our research focused on developing a close-range photogrammetric method (and accompanying free/open-source software) to serve as a cost-effective alternative. This method involves securing and floating a wooden square frame on the stream surface at several locations, taking photographs from numerous angles at each location, and then post-processing and merging data from these photos using the corners of the square for reference points, unit scale, and perspective correction. For our test field site we chose a ~35m reach along Black Hawk Creek in Sunderbruch Park (Davenport, IA), a small, slow-moving stream with overhanging trees. To quantify error we measured 88 distances between 30 marked control points along the reach. We calculated error by comparing these 'ground truth' distances to the corresponding distances extracted from our photogrammetric method. We placed the square at three locations along our reach and photographed it from multiple angles. The square corners, visible control points, and visible stream outline were hand-marked in these photos using the GIMP (open-source image editor). We wrote an open-source GUI in Java (hosted on GitHub), which allows the user to load marked-up photos, designate square corners and label control points. The GUI also extracts the marked pixel coordinates from the images. We also wrote several scripts (currently in MATLAB) that correct the pixel coordinates for radial distortion using Brown's lens distortion model, correct for perspective by forcing the four square corner pixels to form a parallelogram in 3-space, and rotate the points in order to correctly orient all photos of the same square location. Planform data from multiple photos (and multiple square locations) are combined using weighting functions that mitigate the error stemming from the markup-process, imperfect camera calibration, etc. We have used our (beta) software to mark and process over 100 photos, yielding an average error of only 1.5% relative to our 88 measured lengths. Next we plan to translate the MATLAB scripts into Python and release their source code, at which point only free software, consumer-grade digital cameras, and inexpensive building materials will be needed for others to replicate this method at new field sites. Three sample photographs of the square with the created planform and control points

Cursor Control Device Test Battery

NASA Technical Reports Server (NTRS)

Holden, Kritina; Sandor, Aniko; Pace, John; Thompson, Shelby

2013-01-01

The test battery was developed to provide a standard procedure for cursor control device evaluation. The software was built in Visual Basic and consists of nine tasks and a main menu that integrates the set-up of the tasks. The tasks can be used individually, or in a series defined in the main menu. Task 1, the Unidirectional Pointing Task, tests the speed and accuracy of clicking on targets. Two rectangles with an adjustable width and adjustable center- to-center distance are presented. The task is to click back and forth between the two rectangles. Clicks outside of the rectangles are recorded as errors. Task 2, Multidirectional Pointing Task, measures speed and accuracy of clicking on targets approached from different angles. Twenty-five numbered squares of adjustable width are arranged around an adjustable diameter circle. The task is to point and click on the numbered squares (placed on opposite sides of the circle) in consecutive order. Clicks outside of the squares are recorded as errors. Task 3, Unidirectional (horizontal) Dragging Task, is similar to dragging a file into a folder on a computer desktop. Task 3 requires dragging a square of adjustable width from one rectangle and dropping it into another. The width of each rectangle is adjustable, as well as the distance between the two rectangles. Dropping the square outside of the rectangles is recorded as an error. Task 4, Unidirectional Path Following, is similar to Task 3. The task is to drag a square through a tunnel consisting of two lines. The size of the square and the width of the tunnel are adjustable. If the square touches any of the lines, it is counted as an error and the task is restarted. Task 5, Text Selection, involves clicking on a Start button, and then moving directly to the underlined portion of the displayed text and highlighting it. The pointing distance to the text is adjustable, as well as the to-be-selected font size and the underlined character length. If the selection does not include all of the underlined characters, or includes non-underlined characters, it is recorded as an error. Task 6, Multi-size and Multi-distance Pointing, presents the participant with 24 consecutively numbered buttons of different sizes (63 to 163 pixels), and at different distances (60 to 80 pixels) from the Start button. The task is to click on the Start button, and then move directly to, and click on, each numbered target button in consecutive order. Clicks outside of the target area are errors. Task 7, Standard Interface Elements Task, involves interacting with standard interface elements as instructed in written procedures, including: drop-down menus, sliders, text boxes, radio buttons, and check boxes. Task completion time is recorded. In Task 8, a circular track is presented with a disc in it at the top. Track width and disc size are adjustable. The task is to move the disc with circular motion within the path without touching the boundaries of the track. Time and errors are recorded. Task 9 is a discrete task that allows evaluation of discrete cursor control devices that tab from target to target, such as a castle switch. The task is to follow a predefined path and to click on the yellow targets along the path.

A Bayesian approach to parameter and reliability estimation in the Poisson distribution.

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1972-01-01

For life testing procedures, a Bayesian analysis is developed with respect to a random intensity parameter in the Poisson distribution. Bayes estimators are derived for the Poisson parameter and the reliability function based on uniform and gamma prior distributions of that parameter. A Monte Carlo procedure is implemented to make possible an empirical mean-squared error comparison between Bayes and existing minimum variance unbiased, as well as maximum likelihood, estimators. As expected, the Bayes estimators have mean-squared errors that are appreciably smaller than those of the other two.

Insights into the Earth System mass variability from CSR-RL05 GRACE gravity fields

NASA Astrophysics Data System (ADS)

Bettadpur, S.

2012-04-01

The next-generation Release-05 GRACE gravity field data products are the result of extensive effort applied to the improvements to the GRACE Level-1 (tracking) data products, and to improvements in the background gravity models and processing methodology. As a result, the squared-error upper-bound in RL05 fields is half or less than the squared-error upper-bound in RL04 fields. The CSR-RL05 field release consists of unconstrained gravity fields as well as a regularized gravity field time-series that can be used for several applications without any post-processing error reduction. This paper will describe the background and the nature of these improvements in the data products, and provide an error characterization. We will describe the insights these new series offer in measuring the mass flux due to diverse Hydrologic, Oceanographic and Cryospheric processes.

Retrieval of the aerosol optical thickness from UV global irradiance measurements

NASA Astrophysics Data System (ADS)

Costa, M. J.; Salgueiro, V.; Bortoli, D.; Obregón, M. A.; Antón, M.; Silva, A. M.

2015-12-01

The UV irradiance is measured at Évora since several years, where a CIMEL sunphotometer integrated in AERONET is also installed. In the present work, measurements of UVA (315 - 400 nm) irradiances taken with Kipp&Zonen radiometers, as well as satellite data of ozone total column values, are used in combination with radiative transfer calculations, to estimate the aerosol optical thickness (AOT) in the UV. The retrieved UV AOT in Évora is compared with AERONET AOT (at 340 and 380 nm) and a fairly good agreement is found with a root mean square error of 0.05 (normalized root mean square error of 8.3%) and a mean absolute error of 0.04 (mean percentage error of 2.9%). The methodology is then used to estimate the UV AOT in Sines, an industrialized site on the Atlantic western coast, where the UV irradiance is monitored since 2013 but no aerosol information is available.

Uncertainty based pressure reconstruction from velocity measurement with generalized least squares

NASA Astrophysics Data System (ADS)

Zhang, Jiacheng; Scalo, Carlo; Vlachos, Pavlos

2017-11-01

A method using generalized least squares reconstruction of instantaneous pressure field from velocity measurement and velocity uncertainty is introduced and applied to both planar and volumetric flow data. Pressure gradients are computed on a staggered grid from flow acceleration. The variance-covariance matrix of the pressure gradients is evaluated from the velocity uncertainty by approximating the pressure gradient error to a linear combination of velocity errors. An overdetermined system of linear equations which relates the pressure and the computed pressure gradients is formulated and then solved using generalized least squares with the variance-covariance matrix of the pressure gradients. By comparing the reconstructed pressure field against other methods such as solving the pressure Poisson equation, the omni-directional integration, and the ordinary least squares reconstruction, generalized least squares method is found to be more robust to the noise in velocity measurement. The improvement on pressure result becomes more remarkable when the velocity measurement becomes less accurate and more heteroscedastic. The uncertainty of the reconstructed pressure field is also quantified and compared across the different methods.

An Empirical State Error Covariance Matrix for Batch State Estimation

NASA Technical Reports Server (NTRS)

Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty. Also, in its most straight forward form, the technique only requires supplemental calculations to be added to existing batch algorithms. The generation of this direct, empirical form of the state error covariance matrix is independent of the dimensionality of the observations. Mixed degrees of freedom for an observation set are allowed. As is the case with any simple, empirical sample variance problems, the presented approach offers an opportunity (at least in the case of weighted least squares) to investigate confidence interval estimates for the error covariance matrix elements. The diagonal or variance terms of the error covariance matrix have a particularly simple form to associate with either a multiple degree of freedom chi-square distribution (more approximate) or with a gamma distribution (less approximate). The off diagonal or covariance terms of the matrix are less clear in their statistical behavior. However, the off diagonal covariance matrix elements still lend themselves to standard confidence interval error analysis. The distributional forms associated with the off diagonal terms are more varied and, perhaps, more approximate than those associated with the diagonal terms. Using a simple weighted least squares sample problem, results obtained through use of the proposed technique are presented. The example consists of a simple, two observer, triangulation problem with range only measurements. Variations of this problem reflect an ideal case (perfect knowledge of the range errors) and a mismodeled case (incorrect knowledge of the range errors).

Proposing a new iterative learning control algorithm based on a non-linear least square formulation - Minimising draw-in errors

NASA Astrophysics Data System (ADS)

Endelt, B.

2017-09-01

Forming operation are subject to external disturbances and changing operating conditions e.g. new material batch, increasing tool temperature due to plastic work, material properties and lubrication is sensitive to tool temperature. It is generally accepted that forming operations are not stable over time and it is not uncommon to adjust the process parameters during the first half hour production, indicating that process instability is gradually developing over time. Thus, in-process feedback control scheme might not-be necessary to stabilize the process and an alternative approach is to apply an iterative learning algorithm, which can learn from previously produced parts i.e. a self learning system which gradually reduces error based on historical process information. What is proposed in the paper is a simple algorithm which can be applied to a wide range of sheet-metal forming processes. The input to the algorithm is the final flange edge geometry and the basic idea is to reduce the least-square error between the current flange geometry and a reference geometry using a non-linear least square algorithm. The ILC scheme is applied to a square deep-drawing and the Numisheet’08 S-rail benchmark problem, the numerical tests shows that the proposed control scheme is able control and stabilise both processes.

Online measurement of urea concentration in spent dialysate during hemodialysis.

PubMed

Olesberg, Jonathon T; Arnold, Mark A; Flanigan, Michael J

2004-01-01

We describe online optical measurements of urea in the effluent dialysate line during regular hemodialysis treatment of several patients. Monitoring urea removal can provide valuable information about dialysis efficiency. Spectral measurements were performed with a Fourier-transform infrared spectrometer equipped with a flow-through cell. Spectra were recorded across the 5000-4000 cm(-1) (2.0-2.5 microm) wavelength range at 1-min intervals. Savitzky-Golay filtering was used to remove baseline variations attributable to the temperature dependence of the water absorption spectrum. Urea concentrations were extracted from the filtered spectra by use of partial least-squares regression and the net analyte signal of urea. Urea concentrations predicted by partial least-squares regression matched concentrations obtained from standard chemical assays with a root mean square error of 0.30 mmol/L (0.84 mg/dL urea nitrogen) over an observed concentration range of 0-11 mmol/L. The root mean square error obtained with the net analyte signal of urea was 0.43 mmol/L with a calibration based only on a set of pure-component spectra. The error decreased to 0.23 mmol/L when a slope and offset correction were used. Urea concentrations can be continuously monitored during hemodialysis by near-infrared spectroscopy. Calibrations based on the net analyte signal of urea are particularly appealing because they do not require a training step, as do statistical multivariate calibration procedures such as partial least-squares regression.

Criterion Predictability: Identifying Differences Between [r-squares

ERIC Educational Resources Information Center

Malgady, Robert G.

1976-01-01

An analysis of variance procedure for testing differences in r-squared, the coefficient of determination, across independent samples is proposed and briefly discussed. The principal advantage of the procedure is to minimize Type I error for follow-up tests of pairwise differences. (Author/JKS)

Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model

ERIC Educational Resources Information Center

Kang, Taehoon; Chen, Troy T.

2011-01-01

The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…

Chemometrics resolution and quantification power evaluation: Application on pharmaceutical quaternary mixture of Paracetamol, Guaifenesin, Phenylephrine and p-aminophenol

NASA Astrophysics Data System (ADS)

Yehia, Ali M.; Mohamed, Heba M.

2016-01-01

Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference.

An Interactive Computer Package for Use with Simulation Models Which Performs Multidimensional Sensitivity Analysis by Employing the Techniques of Response Surface Methodology.

DTIC Science & Technology

1984-12-01

total sum of squares at the center points minus the correction factor for the mean at the center points ( SSpe =Y’Y-nlY), where n1 is the number of...SSlac=SSres- SSpe ). The sum of squares due to pure error estimates 0" and the sum of squares due to lack-of-fit estimates 0’" plus a bias term if...Response Surface Methodology Source d.f. SS MS Regression n b’X1 Y b’XVY/n Residual rn-n Y’Y-b’X’ *Y (Y’Y-b’X’Y)/(n-n) Pure Error ni-i Y’Y-nl1Y SSpe / (ni

RM2: rms error comparisons

NASA Technical Reports Server (NTRS)

Rice, R. F.

1976-01-01

The root-mean-square error performance measure is used to compare the relative performance of several widely known source coding algorithms with the RM2 image data compression system. The results demonstrate that RM2 has a uniformly significant performance advantage.

Cervicocephalic kinesthetic sensibility in young and middle-aged adults with or without a history of mild neck pain.

PubMed

Teng, C-C; Chai, H; Lai, D-M; Wang, S-F

2007-02-01

Previous research has shown that there is no significant relationship between the degree of structural degeneration of the cervical spine and neck pain. We therefore sought to investigate the potential role of sensory dysfunction in chronic neck pain. Cervicocephalic kinesthetic sensibility, expressed by how accurately an individual can reposition the head, was studied in three groups of individuals, a control group of 20 asymptomatic young adults and two groups of middle-aged adults (20 subjects in each group) with or without a history of mild neck pain. An ultrasound-based three-dimensional coordinate measuring system was used to measure the position of the head and to test the accuracy of repositioning. Constant error (indicating that the subject overshot or undershot the intended position) and root mean square errors (representing total errors of accuracy and variability) were measured during repositioning of the head to the neutral head position (Head-to-NHP) and repositioning of the head to the target (Head-to-Target) in three cardinal planes (sagittal, transverse, and frontal). Analysis of covariance (ANCOVA) was used to test the group effect, with age used as a covariate. The constant errors during repositioning from a flexed position and from an extended position to the NHP were significantly greater in the middle-aged subjects than in the control group (beta=0.30 and beta=0.60, respectively; P<0.05 for both). In addition, the root mean square errors during repositioning from a flexed or extended position to the NHP were greater in the middle-aged subjects than in the control group (beta=0.27 and beta=0.49, respectively; P<0.05 for both). The root mean square errors also increased during Head-to-Target in left rotation (beta=0.24;P<0.05), but there was no difference in the constant errors or root mean square errors during Head-to-NHP repositioning from other target positions (P>0.05). The results indicate that, after controlling for age as a covariate, there was no group effect. Thus, age appears to have a profound effect on an individual's ability to accurately reposition the head toward the neutral position in the sagittal plane and repositioning the head toward left rotation. A history of mild chronic neck pain alone had no significant effect on cervicocephalic kinesthetic sensibility.

What Are Error Rates for Classifying Teacher and School Performance Using Value-Added Models?

ERIC Educational Resources Information Center

Schochet, Peter Z.; Chiang, Hanley S.

2013-01-01

This article addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using a realistic performance measurement system scheme based on hypothesis testing, the authors develop error rate formulas based on ordinary least squares and…

Quantitative Modelling of Trace Elements in Hard Coal.

PubMed

Smoliński, Adam; Howaniec, Natalia

2016-01-01

The significance of coal in the world economy remains unquestionable for decades. It is also expected to be the dominant fossil fuel in the foreseeable future. The increased awareness of sustainable development reflected in the relevant regulations implies, however, the need for the development and implementation of clean coal technologies on the one hand, and adequate analytical tools on the other. The paper presents the application of the quantitative Partial Least Squares method in modeling the concentrations of trace elements (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Sr, V and Zn) in hard coal based on the physical and chemical parameters of coal, and coal ash components. The study was focused on trace elements potentially hazardous to the environment when emitted from coal processing systems. The studied data included 24 parameters determined for 132 coal samples provided by 17 coal mines of the Upper Silesian Coal Basin, Poland. Since the data set contained outliers, the construction of robust Partial Least Squares models for contaminated data set and the correct identification of outlying objects based on the robust scales were required. These enabled the development of the correct Partial Least Squares models, characterized by good fit and prediction abilities. The root mean square error was below 10% for all except for one the final Partial Least Squares models constructed, and the prediction error (root mean square error of cross-validation) exceeded 10% only for three models constructed. The study is of both cognitive and applicative importance. It presents the unique application of the chemometric methods of data exploration in modeling the content of trace elements in coal. In this way it contributes to the development of useful tools of coal quality assessment.

On the multivariate total least-squares approach to empirical coordinate transformations. Three algorithms

NASA Astrophysics Data System (ADS)

Schaffrin, Burkhard; Felus, Yaron A.

2008-06-01

The multivariate total least-squares (MTLS) approach aims at estimating a matrix of parameters, Ξ, from a linear model ( Y- E Y = ( X- E X ) · Ξ) that includes an observation matrix, Y, another observation matrix, X, and matrices of randomly distributed errors, E Y and E X . Two special cases of the MTLS approach include the standard multivariate least-squares approach where only the observation matrix, Y, is perturbed by random errors and, on the other hand, the data least-squares approach where only the coefficient matrix X is affected by random errors. In a previous contribution, the authors derived an iterative algorithm to solve the MTLS problem by using the nonlinear Euler-Lagrange conditions. In this contribution, new lemmas are developed to analyze the iterative algorithm, modify it, and compare it with a new ‘closed form’ solution that is based on the singular-value decomposition. For an application, the total least-squares approach is used to estimate the affine transformation parameters that convert cadastral data from the old to the new Israeli datum. Technical aspects of this approach, such as scaling the data and fixing the columns in the coefficient matrix are investigated. This case study illuminates the issue of “symmetry” in the treatment of two sets of coordinates for identical point fields, a topic that had already been emphasized by Teunissen (1989, Festschrift to Torben Krarup, Geodetic Institute Bull no. 58, Copenhagen, Denmark, pp 335-342). The differences between the standard least-squares and the TLS approach are analyzed in terms of the estimated variance component and a first-order approximation of the dispersion matrix of the estimated parameters.

Quantitative Modelling of Trace Elements in Hard Coal

PubMed Central

Smoliński, Adam; Howaniec, Natalia

2016-01-01

The significance of coal in the world economy remains unquestionable for decades. It is also expected to be the dominant fossil fuel in the foreseeable future. The increased awareness of sustainable development reflected in the relevant regulations implies, however, the need for the development and implementation of clean coal technologies on the one hand, and adequate analytical tools on the other. The paper presents the application of the quantitative Partial Least Squares method in modeling the concentrations of trace elements (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Rb, Sr, V and Zn) in hard coal based on the physical and chemical parameters of coal, and coal ash components. The study was focused on trace elements potentially hazardous to the environment when emitted from coal processing systems. The studied data included 24 parameters determined for 132 coal samples provided by 17 coal mines of the Upper Silesian Coal Basin, Poland. Since the data set contained outliers, the construction of robust Partial Least Squares models for contaminated data set and the correct identification of outlying objects based on the robust scales were required. These enabled the development of the correct Partial Least Squares models, characterized by good fit and prediction abilities. The root mean square error was below 10% for all except for one the final Partial Least Squares models constructed, and the prediction error (root mean square error of cross–validation) exceeded 10% only for three models constructed. The study is of both cognitive and applicative importance. It presents the unique application of the chemometric methods of data exploration in modeling the content of trace elements in coal. In this way it contributes to the development of useful tools of coal quality assessment. PMID:27438794

A preliminary study of the Six-Item Screener in detecting cognitive impairment.

PubMed

Chen, Mei-Rong; Guo, Qi-Hao; Cao, Xin-Yi; Hong, Zhen; Liu, Xiao-Hong

2010-08-01

The present retrospective study was to explore the clinical value of Six-Item Screener (SIS), which is constituted by 6 items from mini-mental status examination (MMSE), to identify cognitive impairment. A total number of 1976 patients aged over 50 years, from the Memory Clinic of Huashan Hospital were employed in a battery of neuropsychological tests including MMSE. Subjects with severe conditions, unable to cooperate, or having been previously enrolled, were excluded from this study. The employed subjects were divided into 3 groups: subjective memory complaints (SMCs) (475 cases), patients with mild cognitive impairment (MCI) (440 cases), and patients with Alzheimer's disease (AD) (1061 cases, including 555 mild, 339 moderate, and 167 severe). A total score of MMSE and a score of SIS composed of date, month, year, three-word delayed recall from MMSE were calculated. Data were analyzed based on educational background. The cut-off of SIS score was <2 for illiterate, <3 for elementary, and <4 for junior high school or above. The sensitivity and specificity of SIS for detecting mild AD were 88.5% and 78.3%, respectively, with an overall accuracy of 83.8%, while for detecting MCI, the sensitivity and specificity were 34.3% and 90.1%, respectively, with an overall accuracy of 63.2%. SIS is an effective and reliable instrument for dementia detection in outpatient department. However, it has limited value for MCI identification.

Improving detection of dementia in Asian patients with low education: combining the Mini-Mental State Examination and the Informant Questionnaire on Cognitive Decline in the Elderly.

PubMed

Narasimhalu, Kaavya; Lee, June; Auchus, Alexander P; Chen, Christopher P L H

2008-01-01

Previous work combining the Mini-Mental State Examination (MMSE) and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) has been conducted in western populations. We ascertained, in an Asian population, (1) the best method of combining the tests, (2) the effects of educational level, and (3) the effect of different dementia etiologies. Data from 576 patients were analyzed (407 nondemented controls, 87 Alzheimer's disease and 82 vascular dementia patients). Sensitivity, specificity and AUC values were obtained using three methods, the 'And' rule, the 'Or' rule, and the 'weighted sum' method. The 'weighted sum' rule had statistically superior AUC and specificity results, while the 'Or' rule had the best sensitivity results. The IQCODE outperformed the MMSE in all analyses. Patients with no education benefited more from combined tests. There was no difference between Alzheimer's disease and vascular dementia populations in the predictive value of any of the combined methods. We recommend that the IQCODE be used to supplement the MMSE whenever available and that the 'weighted sum' method be used to combine the MMSE and the IQCODE, particularly in populations with low education. As the study population selected may not be representative of the general population, further studies are required before generalization to nonclinical samples. (c) 2007 S. Karger AG, Basel.

Clinically insubstantial cognitive side effects of bitemporal electroconvulsive therapy at 0.5 msec pulse width.

PubMed

Warnell, Ronald L; Swartz, Conrad M; Thomson, Alice

2011-11-01

We measured cognitive side effects from bitemporal electroconvulsive therapy (ECT) using stimuli of 0.5 msec pulse width 900 milliamperes (mA). Mini-Mental State Exam (MMSE) and 21-item Hamilton Rating Scale for Depression (HRSD-21) were rated within 36 hours before and 36 hours after a series of 6 bitemporal ECT sessions on 15 patients age ≥45. MMSE remained high after ECT (pre-ECT mean 29, standard deviation [SD] 1.60, post-ECT mean 28.53, SD 1.36) with no significant change. The mean HRSD-21 fell from 27.5 to 16.3. Post-ECT MMSE was significantly and markedly higher than in previous studies of bitemporal ECT; all had used ECT stimuli of pulse width at least 1 msec. With stimuli of 0.5 msec pulse width and 900 mA, 6 bitemporal ECTs did not decrease MMSE score. This result leaves no opportunity for further decrease in basic cognitive side effects, and complements published reports of stronger physiological effects with stimuli of 0.5 msec pulse width and 900 mA. ECT stimuli of 0.5 msec pulse width and 900 mA are more desirable than wider pulse widths. Six bitemporal ECT sessions using these stimuli generally will not have more cognitive side effects than treatments with other placements, allowing maintenance of full efficacy with clinically insubstantial side effects.

Selection of neural network structure for system error correction of electro-optical tracker system with horizontal gimbal

NASA Astrophysics Data System (ADS)

Liu, Xing-fa; Cen, Ming

2007-12-01

Neural Network system error correction method is more precise than lest square system error correction method and spheric harmonics function system error correction method. The accuracy of neural network system error correction method is mainly related to the frame of Neural Network. Analysis and simulation prove that both BP neural network system error correction method and RBF neural network system error correction method have high correction accuracy; it is better to use RBF Network system error correction method than BP Network system error correction method for little studying stylebook considering training rate and neural network scale.

Determining particle size and water content by near-infrared spectroscopy in the granulation of naproxen sodium.

PubMed

Bär, David; Debus, Heiko; Brzenczek, Sina; Fischer, Wolfgang; Imming, Peter

2018-03-20

Near-infrared spectroscopy is frequently used by the pharmaceutical industry to monitor and optimize several production processes. In combination with chemometrics, a mathematical-statistical technique, the following advantages of near-infrared spectroscopy can be applied: It is a fast, non-destructive, non-invasive, and economical analytical method. One of the most advanced and popular chemometric technique is the partial least square algorithm with its best applicability in routine and its results. The required reference analytic enables the analysis of various parameters of interest, for example, moisture content, particle size, and many others. Parameters like the correlation coefficient, root mean square error of prediction, root mean square error of calibration, and root mean square error of validation have been used for evaluating the applicability and robustness of these analytical methods developed. This study deals with investigating a Naproxen Sodium granulation process using near-infrared spectroscopy and the development of water content and particle-size methods. For the water content method, one should consider a maximum water content of about 21% in the granulation process, which must be confirmed by the loss on drying. Further influences to be considered are the constantly changing product temperature, rising to about 54 °C, the creation of hydrated states of Naproxen Sodium when using a maximum of about 21% water content, and the large quantity of about 87% Naproxen Sodium in the formulation. It was considered to use a combination of these influences in developing the near-infrared spectroscopy method for the water content of Naproxen Sodium granules. The "Root Mean Square Error" was 0.25% for calibration dataset and 0.30% for the validation dataset, which was obtained after different stages of optimization by multiplicative scatter correction and the first derivative. Using laser diffraction, the granules have been analyzed for particle sizes and obtaining the summary sieve sizes of >63 μm and >100 μm. The following influences should be considered for application in routine production: constant changes in water content up to 21% and a product temperature up to 54 °C. The different stages of optimization result in a "Root Mean Square Error" of 2.54% for the calibration data set and 3.53% for the validation set by using the Kubelka-Munk conversion and first derivative for the near-infrared spectroscopy method for a particle size >63 μm. For the near-infrared spectroscopy method using a particle size >100 μm, the "Root Mean Square Error" was 3.47% for the calibration data set and 4.51% for the validation set, while using the same pre-treatments. - The robustness and suitability of this methodology has already been demonstrated by its recent successful implementation in a routine granulate production process. Copyright © 2018 Elsevier B.V. All rights reserved.

The Influence of Dimensionality on Estimation in the Partial Credit Model.

ERIC Educational Resources Information Center

De Ayala, R. J.

1995-01-01

The effect of multidimensionality on partial credit model parameter estimation was studied with noncompensatory and compensatory data. Analysis results, consisting of root mean square error bias, Pearson product-moment corrections, standardized root mean squared differences, standardized differences between means, and descriptive statistics…

Modeling Water Temperature in the Yakima River, Washington, from Roza Diversion Dam to Prosser Dam, 2005-06

USGS Publications Warehouse

Voss, Frank D.; Curran, Christopher A.; Mastin, Mark C.

2008-01-01

A mechanistic water-temperature model was constructed by the U.S. Geological Survey for use by the Bureau of Reclamation for studying the effect of potential water management decisions on water temperature in the Yakima River between Roza and Prosser, Washington. Flow and water temperature data for model input were obtained from the Bureau of Reclamation Hydromet database and from measurements collected by the U.S. Geological Survey during field trips in autumn 2005. Shading data for the model were collected by the U.S. Geological Survey in autumn 2006. The model was calibrated with data collected from April 1 through October 31, 2005, and tested with data collected from April 1 through October 31, 2006. Sensitivity analysis results showed that for the parameters tested, daily maximum water temperature was most sensitive to changes in air temperature and solar radiation. Root mean squared error for the five sites used for model calibration ranged from 1.3 to 1.9 degrees Celsius (?C) and mean error ranged from ?1.3 to 1.6?C. The root mean squared error for the five sites used for testing simulation ranged from 1.6 to 2.2?C and mean error ranged from 0.1 to 1.3?C. The accuracy of the stream temperatures estimated by the model is limited by four errors (model error, data error, parameter error, and user error).

The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.

PubMed

Fiyadh, Seef Saadi; AlSaadi, Mohammed Abdulhakim; AlOmar, Mohamed Khalid; Fayaed, Sabah Saadi; Hama, Ako R; Bee, Sharifah; El-Shafie, Ahmed

2017-11-01

The main challenge in the lead removal simulation is the behaviour of non-linearity relationships between the process parameters. The conventional modelling technique usually deals with this problem by a linear method. The substitute modelling technique is an artificial neural network (ANN) system, and it is selected to reflect the non-linearity in the interaction among the variables in the function. Herein, synthesized deep eutectic solvents were used as a functionalized agent with carbon nanotubes as adsorbents of Pb 2+ . Different parameters were used in the adsorption study including pH (2.7 to 7), adsorbent dosage (5 to 20 mg), contact time (3 to 900 min) and Pb 2+ initial concentration (3 to 60 mg/l). The number of experimental trials to feed and train the system was 158 runs conveyed in laboratory scale. Two ANN types were designed in this work, the feed-forward back-propagation and layer recurrent; both methods are compared based on their predictive proficiency in terms of the mean square error (MSE), root mean square error, relative root mean square error, mean absolute percentage error and determination coefficient (R 2 ) based on the testing dataset. The ANN model of lead removal was subjected to accuracy determination and the results showed R 2 of 0.9956 with MSE of 1.66 × 10 -4 . The maximum relative error is 14.93% for the feed-forward back-propagation neural network model.

[Mini Mental State Examination (MMSE): determination of cutoff scores according to age and educational level].

PubMed

Solias, A; Skapinakis, P; Degleris, N; Pantoleon, M; Katirtzoglou, E; Politis, A

2014-01-01

For the last 38 years, Mini Mental State Examination (MMSE) has been widely used as a dementia screening measure in everyday clinical practice as well as in both cohort and cross-sectional studies. Its validity and reliability for the Greek population has explicitly been documented. However, the effect of age and education on the subject's performance makes it necessary to reckon them in the estimation of the "cutoff score". The purpose of this study is to estimate the prevalence of dementia in Greek population and determine the "cutoff score" by age and education-corrected norms. Cross sectional study of 630 patients older than 55 years, who live independently in Ilion and Helioupolis Municipalities was conducted, 27.3% of the subjects tested in the study were diagnosed with memory disorder according to their MMSE scores and the validation for the Greek population. The effect of age and education to the subjects' performance was statistically significant (p=.000). The use of standard "cutoff score" was not proved to be useful for the personalized interpretation of the results, as documented by the fact that older individuals with lower education had a poorer performance relatively to younger, highly educated subjects. Comparatively to the group age of 55-60 years, the odds ratio after the age of 75 years varies from 2.58 to 4.91. Regarding the variable factor of education, the odds ratio for the first degree education graduates decreases from 1.43 to 3.19 for the third degree education graduates in comparison with the group of illiterates. In conclusion, the use of the "cutoff score" algorithm and the simultaneous estimation of age and education effect on MMSE score may prove useful for the proper evaluation of MMSE performance. According to the age and education of examine candidates in the community and the primary care, we propose the use of the 25th percentile as a more useful cutoff score in order to decrease the false positive results.

Cognitive problems in patients in a cardiac rehabilitation program after an out-of-hospital cardiac arrest.

PubMed

Boyce-van der Wal, L W; Volker, W G; Vliet Vlieland, T P M; van den Heuvel, D M J; van Exel, H J; Goossens, P H

2015-08-01

Estimate prevalence of cognitive problems due to hypoxic brain injury in out-of-hospital cardiac arrest (OHCA) survivors referred for cardiac rehabilitation and association with quality of life as well as autonomy and participation. Prospective cohort study. Consecutive OHCA patients. The Mini-Mental State Examination (MMSE), Cognitive Failures Questionnaire (CFQ) and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) were administered 4 weeks after the OHCA. Cognitive problems were defined if MMSE <28, CFQ >32 or IQCODE >3.6. The Impact on Participation and Autonomy Questionnaire (IPAQ) (participation/autonomy), the SF-36 Health Survey (SF-36) (quality of life) and the Hospital Anxiety Depression Scale (HADS) (anxiety/depression) were administered. Correlations between cognitive problems and participation/autonomy and quality of life were calculated. 63 of 77 patients were male (82%), median age 59 years (range 15-84). MMSE median 29 (interquartile range 28-30), CFQ mean 20.9 (SD 9.4) and IQCODE mean 3.1 (SD 0.2). Eighteen patients (23%) scored positive for cognitive problems. Significant correlations were found between MMSE and IPAQ: autonomy inside (r = -0.38), family role (r = -0.26), autonomy outside (r = -0.32), social relations (r = -0.38) and social functioning (r = 0.32). MMSE was related to SF-36: social functioning (r = 0.32). The CFQ was related to IPAQ: autonomy outdoors (r = 0.29) and SF-36: bodily pain (r = -0.37), vitality (r = -0.25), mental health (r = -0.35) and role emotional (r = -0.40). The IQCODE was related to IPAQ: autonomy indoors (r = 0.26) and to SF-36: vitality (r = -0.33) and social functioning (r = -0.41). Twenty-three percent of the patients referred for cardiac rehabilitation showed cognitive problems. Associations were found between cognitive problems and several aspects of participation/autonomy and perceived quality of life. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Discrimination between stages of Alzheimer's disease with subsets of Mini-Mental State Examination items. An analysis of Consortium to Establish a Registry for Alzheimer's Disease data.

PubMed

Fillenbaum, G G; Wilkinson, W E; Welsh, K A; Mohs, R C

1994-09-01

To identify minimal sets of Mini-Mental State Examination (MMSE) items that can distinguish normal control subjects from patients with mild Alzheimer's disease (AD), patients with mild from those with moderate AD, and those with moderate from those with severe AD. Two randomly selected equivalent half samples. Results of logistic regression analysis from data from the first half of the sample were confirmed by receiver operating characteristic curves on the second half. Memory disorders clinics at major medical centers in the United States affiliated with the Consortium to establish a Registry for Alzheimer's Disease (CERAD). White, normal control subjects (n = 412) and patients with AD (n = 621) who met CERAD criteria; nonwhite subjects (n = 165) and persons with missing data (n = 27) were excluded. Three four-item sets of MMSE items that discriminate, respectively, (1) normal controls from patients with mild AD, (2) patients with mild from those with moderate AD, and (3) patients with moderate from those with severe AD. The MMSE items discriminating normal controls from patients with mild AD were day, date, recall of apple, and recall of penny; those discriminating patients with mild from those with moderate AD were month, city, spelling world backward, and county, and those discriminating patients with moderate from those with severe AD were floor of building, repeating the word table, naming watch, and folding paper in half. Performance on the first two four-item sets was comparable with that of the full MMSE; the third set distinguished patients with moderate from those with severe AD better than chance. A minimum set of MMSE items can effectively discriminate normal controls from patients with mild AD and between successive levels of severity of AD. Data apply only to white patients with AD. Performance in minorities, more heterogeneous groups, or normal subjects with questionable cognitive status has not been assessed.

Association of physical activity with the visuospatial/executive functions of the montreal cognitive assessment in patients with vascular cognitive impairment.

PubMed

Ihara, Masafumi; Okamoto, Yoko; Hase, Yoshiki; Takahashi, Ryosuke

2013-10-01

The Montreal Cognitive Assessment (MoCA) is more suitable than the Mini-Mental State Examination (MMSE) for the detection of vascular cognitive impairment. In this study, we performed a correlation analysis of MoCA/MMSE scores with daily physical activity in patients with subcortical ischemic white matter changes. Ten patients (average 75.9 ± 9.1 years old) with extensive leukoaraiosis detected on magnetic resonance imaging underwent cognitive testing, including the MMSE and the Japanese version of the MoCA (MoCA-J). Physical activity was monitored with the Kenz Lifecorder EX device (Suzuken, Nagoya, Japan) to assess daily physical activity in terms of caloric expenditure, motor activity, number of steps, and walking distance for 6 months. Correlations of individual physical activity with total and subscale scores of MMSE/MoCA-J or 6-month interval change of MoCA-J scores were assessed. The total or subscale scores of the MMSE did not correlate with any parameters of physical activity. However, the mean number of steps and walking distance significantly correlated with the total MoCA-J scores (r = .67 and .64, respectively) and its visuospatial/executive subscores (r = .66 and .66, respectively). The mean interval change of MoCA-J was + .6; those who improved number of steps (n = 4; 80.5 ± 3.0 years of age) had significantly preserved MoCA-J scores compared to those who did not (n = 6; 73.0 ± 11.6 years of age; +2.0 versus - .3; P = .016). These results suggest that MoCA is useful to detect a biologically determined specific relationship between physical activity and executive function. In addition, physical exercise, such as walking, may help enhance cognitive function in patients with vascular cognitive impairment of subcortical origin. Copyright © 2013 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Cognitive Assessment of Patients With Alzheimer's Disease by Telemedicine: Pilot Study

PubMed Central

Carotenuto, Anna; Rea, Raffaele; Ricci, Giovanna; Fasanaro, Angiola Maria; Amenta, Francesco

2018-01-01

Background Approximately 46.8 million people are living with dementia worldwide and their number will grow in the next years. Any potential treatment should be administered as early as possible because it is important to provide an early cognitive assessment and to regularly monitor the mental function of patients. Information and communication technologies can be helpful to reach and follow patients without displacing them, but there may be doubts about the reliability of cognitive tests performed by telemedicine. Objective The purpose of this study was to evaluate the reliability of the Mini Mental State Examination (MMSE) and the Alzheimer’s Disease Assessment Scale cognitive subscale (ADAS-cog) tests administered in hospital by videoconference to patients with mild to moderate Alzheimer's disease. Methods The tests were administered to 28 Alzheimer's disease outpatients (8 male, mean age 73.88, SD 7.45 years; 20 female mean age 76.00, SD 5.40 years) recruited and followed in the Alzheimer’s Unit of the A Cardarelli National Hospital (Naples, Italy) at baseline and after 6, 12, 18, and 24 months of observation. Patients were evaluated first face-to-face by a psychologist and then, after 2 weeks, by another psychologist via videoconference in hospital. Results This study showed no differences in the MMSE and ADAS-cog scores when the tests were administered face-to-face or by videoconference, except in patients with more pronounced cognitive deficits (MMSE<17), in which the assessment via videoconference overestimated the cognitive impairment (face to face, MMSE mean 13.9, SD 4.9 and ADAS-cog mean 9.0, SD 3.8; videoconference, MMSE mean 42.8, SD 12.5 and ADAS-cog mean 56.9, SD 5.5). Conclusions We found that videoconferencing is a reliable approach to document cognitive stability or decline, and to measure treatment effects in patients with mild to moderate dementia. A more extended study is needed to confirm these results. PMID:29752254

The temporal limits of cognitive change from music therapy in elderly persons with dementia or dementia-like cognitive impairment: a randomized controlled trial.

PubMed

Bruer, Robert A; Spitznagel, Edward; Cloninger, C Robert

2007-01-01

This study explored the temporal limits of cognitive change from an intention-to-treat with group music therapy. Elderly cognitively-impaired psychiatric inpatients (N = 28) participated in an 8-week randomized control trial using a crossover design. Once a week, subjects were assigned either to music therapy or a control treatment (age-appropriate movie). The Mini-Mental State Exam (MMSE) assessed cognition 3 times every week: prior to the intervention, immediately after the mid-afternoon intervention, and the morning following the intervention. Comparisons between conditions included weekly changes in individual subject's MMSE scores from weekly baseline to both the 2 follow-ups and the following week's baseline. Significant next morning improvements in MMSE scores were found within intent-to-treat music therapy cases as compared to control cases. While all the subjects in this study were cognitively impaired, only 17 had been formally diagnosed with dementia. Based on a Cochrane Collaboration suggestion that music therapy studies within geriatric populations look specifically at the treatment of dementia, a final generalized estimating equation model considered only the change within the 17 dementia-diagnosed subjects. Immediately after the intervention, MMSE scores in the dementia-diagnosed subjects assigned to music therapy improved 2.00 points compared to the dementia-diagnosed subjects assigned to the control group (Z = 1.99, p < .05). Next-day MMSE test scores in the dementia-diagnosed subjects assigned to music therapy showed average improvements of 3.69 points compared to the control subjects (Z = 3.38, p < .001). By the following week, no significant cognitive differences remained between the two groups. It was concluded that a reasonable music therapy intervention facilitated by a trained and accredited music therapist significantly improved next-morning cognitive functioning among dementia patients. With many music therapists working in geriatric settings, more research is justified to both replicate this study and provide better guidance into the effective use of music therapy in the treatment of dementia.

Rapid Detection of Volatile Oil in Mentha haplocalyx by Near-Infrared Spectroscopy and Chemometrics.

PubMed

Yan, Hui; Guo, Cheng; Shao, Yang; Ouyang, Zhen

2017-01-01

Near-infrared spectroscopy combined with partial least squares regression (PLSR) and support vector machine (SVM) was applied for the rapid determination of chemical component of volatile oil content in Mentha haplocalyx . The effects of data pre-processing methods on the accuracy of the PLSR calibration models were investigated. The performance of the final model was evaluated according to the correlation coefficient ( R ) and root mean square error of prediction (RMSEP). For PLSR model, the best preprocessing method combination was first-order derivative, standard normal variate transformation (SNV), and mean centering, which had of 0.8805, of 0.8719, RMSEC of 0.091, and RMSEP of 0.097, respectively. The wave number variables linking to volatile oil are from 5500 to 4000 cm-1 by analyzing the loading weights and variable importance in projection (VIP) scores. For SVM model, six LVs (less than seven LVs in PLSR model) were adopted in model, and the result was better than PLSR model. The and were 0.9232 and 0.9202, respectively, with RMSEC and RMSEP of 0.084 and 0.082, respectively, which indicated that the predicted values were accurate and reliable. This work demonstrated that near infrared reflectance spectroscopy with chemometrics could be used to rapidly detect the main content volatile oil in M. haplocalyx . The quality of medicine directly links to clinical efficacy, thus, it is important to control the quality of Mentha haplocalyx . Near-infrared spectroscopy combined with partial least squares regression (PLSR) and support vector machine (SVM) was applied for the rapid determination of chemical component of volatile oil content in Mentha haplocalyx . For SVM model, 6 LVs (less than 7 LVs in PLSR model) were adopted in model, and the result was better than PLSR model. It demonstrated that near infrared reflectance spectroscopy with chemometrics could be used to rapidly detect the main content volatile oil in Mentha haplocalyx . Abbreviations used: 1 st der: First-order derivative; 2 nd der: Second-order derivative; LOO: Leave-one-out; LVs: Latent variables; MC: Mean centering, NIR: Near-infrared; NIRS: Near infrared spectroscopy; PCR: Principal component regression, PLSR: Partial least squares regression; RBF: Radial basis function; RMSEC: Root mean square error of cross validation, RMSEC: Root mean square error of calibration; RMSEP: Root mean square error of prediction; SNV: Standard normal variate transformation; SVM: Support vector machine; VIP: Variable Importance in projection.

Decline in cognitive function and risk of elder self-neglect: finding from the Chicago Health Aging Project.

PubMed

Dong, XinQi; Simon, Melissa A; Wilson, Robert S; Mendes de Leon, Carlos F; Rajan, K Bharat; Evans, Denis A

2010-12-01

To examine the longitudinal association between decline in cognitive function and risk of elder self-neglect in a community-dwelling population. Prospective population-based study. Geographically defined community in Chicago. Community-dwelling subjects reported to the social services agency from 1993 to 2005 for self-neglect who also participated in the Chicago Health Aging Project (CHAP). Of the 5,519 participants in CHAP, 1,017 were reported to social services agency for suspected elder self-neglect from 1993 to 2005. Social services agency identified reported elder self-neglect. The primary predictor was decline in cognitive function assessed using the Mini-Mental State Examination (MMSE), the Symbol Digit Modalities Test (Executive Function), and immediate and delayed recall of the East Boston Memory Test (Episodic Memory). An index of global cognitive function scores was derived by averaging z-scores of all tests. Outcome of interest was elder self-neglect. Logistic and linear regression models were used to assess these longitudinal associations. After adjusting for potential confounding factors, decline in global cognitive function, MMSE score, and episodic memory were not independently associated with greater risk of reported and confirmed elder self-neglect. Decline in executive function was associated with greater risk of reported and confirmed elder self-neglect. Decline in global cognitive function was associated with greater risk of greater self-neglect severity (parameter estimate=0.76, standard error=0.31, P=.01). Decline in executive function was associated with risk of reported and confirmed elder self-neglect. Decline in global cognitive function was associated with risk of greater self-neglect severity. © 2010, Copyright the Authors. Journal compilation © 2010, The American Geriatrics Society.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

PubMed Central

Chou, Yi-Yu; Leporé, Natasha; Avedissian, Christina; Madsen, Sarah K.; Parikshak, Neelroop; Hua, Xue; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer’s disease, NeuroImage 40(2): 615–630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimer’s disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimer’s Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Aβ1–42 protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials. PMID:19236926

Navy Fuel Composition and Screening Tool (FCAST) v2.8

DTIC Science & Technology

2016-05-10

allowed us to develop partial least squares (PLS) models based on gas chromatography–mass spectrometry (GC-MS) data that predict fuel properties. The...Chemometric property modeling Partial least squares PLS Compositional profiler Naval Air Systems Command Air-4.4.5 Patuxent River Naval Air Station Patuxent...Cumulative predicted residual error sum of squares DiEGME Diethylene glycol monomethyl ether FCAST Fuel Composition and Screening Tool FFP Fit for

Robust Mean and Covariance Structure Analysis through Iteratively Reweighted Least Squares.

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2000-01-01

Adapts robust schemes to mean and covariance structures, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is weighted according to its distance, based on first and second order moments. Test statistics and standard error estimators are given. (SLD)

Latin-square three-dimensional gage master

DOEpatents

Jones, L.

1981-05-12

A gage master for coordinate measuring machines has an nxn array of objects distributed in the Z coordinate utilizing the concept of a Latin square experimental design. Using analysis of variance techniques, the invention may be used to identify sources of error in machine geometry and quantify machine accuracy.

Latin square three dimensional gage master

DOEpatents

Jones, Lynn L.

1982-01-01

A gage master for coordinate measuring machines has an nxn array of objects distributed in the Z coordinate utilizing the concept of a Latin square experimental design. Using analysis of variance techniques, the invention may be used to identify sources of error in machine geometry and quantify machine accuracy.

Effect of nonideal square-law detection on static calibration in noise-injection radiometers

NASA Technical Reports Server (NTRS)

Hearn, C. P.

1984-01-01

The effect of nonideal square-law detection on the static calibration for a class of Dicke radiometers is examined. It is shown that fourth-order curvature in the detection characteristic adds a nonlinear term to the linear calibration relationship normally ascribed to noise-injection, balanced Dicke radiometers. The minimum error, based on an optimum straight-line fit to the calibration curve, is derived in terms of the power series coefficients describing the input-output characteristics of the detector. These coefficients can be determined by simple measurements, and detection nonlinearity is, therefore, quantitatively related to radiometric measurement error.

VizieR Online Data Catalog: delta Cep VEGA/CHARA observing log (Nardetto+, 2016)

NASA Astrophysics Data System (ADS)

Nardetto, N.; Merand, A.; Mourard, D.; Storm, J.; Gieren, W.; Fouque, P.; Gallenne, A.; Graczyk, D.; Kervella, P.; Neilson, H.; Pietrzynski, G.; Pilecki, B.; Breitfelder, J.; Berio, P.; Challouf, M.; Clausse, J.-M.; Ligi, R.; Mathias, P.; Meilland, A.; Perraut, K.; Poretti, E.; Rainer, M.; Spang, A.; Stee, P.; Tallon-Bosc, I.; Ten Brummelaar, T.

2016-07-01

The columns give, respectively, the date, the RJD, the hour angle (HA), the minimum and maximum wavelengths over which the squared visibility is calculated, the projected baseline length Bp and its orientation PA, the signal-to-noise ratio on the fringe peak; the last column provides the calibrated squared visibility V2 together with the statistic error on V2, and the systematic error on V2 (see text for details). The data are available on the Jean-Marie Mariotti Center OiDB service (Available at http://oidb.jmmc.fr). (1 data file).

A network application for modeling a centrifugal compressor performance map

NASA Astrophysics Data System (ADS)

Nikiforov, A.; Popova, D.; Soldatova, K.

2017-08-01

The approximation of aerodynamic performance of a centrifugal compressor stage and vaneless diffuser by neural networks is presented. Advantages, difficulties and specific features of the method are described. An example of a neural network and its structure is shown. The performances in terms of efficiency, pressure ratio and work coefficient of 39 model stages within the range of flow coefficient from 0.01 to 0.08 were modeled with mean squared error 1.5 %. In addition, the loss and friction coefficients of vaneless diffusers of relative widths 0.014-0.10 are modeled with mean squared error 2.45 %.

Tissue resistivity estimation in the presence of positional and geometrical uncertainties.

PubMed

Baysal, U; Eyüboğlu, B M

2000-08-01

Geometrical uncertainties (organ boundary variation and electrode position uncertainties) are the biggest sources of error in estimating electrical resistivity of tissues from body surface measurements. In this study, in order to decrease estimation errors, the statistically constrained minimum mean squared error estimation algorithm (MiMSEE) is constrained with a priori knowledge of the geometrical uncertainties in addition to the constraints based on geometry, resistivity range, linearization and instrumentation errors. The MiMSEE calculates an optimum inverse matrix, which maps the surface measurements to the unknown resistivity distribution. The required data are obtained from four-electrode impedance measurements, similar to injected-current electrical impedance tomography (EIT). In this study, the surface measurements are simulated by using a numerical thorax model. The data are perturbed with additive instrumentation noise. Simulated surface measurements are then used to estimate the tissue resistivities by using the proposed algorithm. The results are compared with the results of conventional least squares error estimator (LSEE). Depending on the region, the MiMSEE yields an estimation error between 0.42% and 31.3% compared with 7.12% to 2010% for the LSEE. It is shown that the MiMSEE is quite robust even in the case of geometrical uncertainties.

A nonlinear model of gold production in Malaysia

NASA Astrophysics Data System (ADS)

Ramli, Norashikin; Muda, Nora; Umor, Mohd Rozi

2014-06-01

Malaysia is a country which is rich in natural resources and one of it is a gold. Gold has already become an important national commodity. This study is conducted to determine a model that can be well fitted with the gold production in Malaysia from the year 1995-2010. Five nonlinear models are presented in this study which are Logistic model, Gompertz, Richard, Weibull and Chapman-Richard model. These model are used to fit the cumulative gold production in Malaysia. The best model is then selected based on the model performance. The performance of the fitted model is measured by sum squares error, root mean squares error, coefficient of determination, mean relative error, mean absolute error and mean absolute percentage error. This study has found that a Weibull model is shown to have significantly outperform compare to the other models. To confirm that Weibull is the best model, the latest data are fitted to the model. Once again, Weibull model gives the lowest readings at all types of measurement error. We can concluded that the future gold production in Malaysia can be predicted according to the Weibull model and this could be important findings for Malaysia to plan their economic activities.

Comparison of structural and least-squares lines for estimating geologic relations

USGS Publications Warehouse

Williams, G.P.; Troutman, B.M.

1990-01-01

Two different goals in fitting straight lines to data are to estimate a "true" linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating "true" straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal-predicting the dependent variable-OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples. ?? 1990 International Association for Mathematical Geology.

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

Estimating errors in least-squares fitting

NASA Technical Reports Server (NTRS)

Richter, P. H.

1995-01-01

While least-squares fitting procedures are commonly used in data analysis and are extensively discussed in the literature devoted to this subject, the proper assessment of errors resulting from such fits has received relatively little attention. The present work considers statistical errors in the fitted parameters, as well as in the values of the fitted function itself, resulting from random errors in the data. Expressions are derived for the standard error of the fit, as a function of the independent variable, for the general nonlinear and linear fitting problems. Additionally, closed-form expressions are derived for some examples commonly encountered in the scientific and engineering fields, namely ordinary polynomial and Gaussian fitting functions. These results have direct application to the assessment of the antenna gain and system temperature characteristics, in addition to a broad range of problems in data analysis. The effects of the nature of the data and the choice of fitting function on the ability to accurately model the system under study are discussed, and some general rules are deduced to assist workers intent on maximizing the amount of information obtained form a given set of measurements.

Methods of automatic nucleotide-sequence analysis. Multicomponent spectrophotometric analysis of mixtures of nucleic acid components by a least-squares procedure

PubMed Central

Lee, Sheila; McMullen, D.; Brown, G. L.; Stokes, A. R.

1965-01-01

1. A theoretical analysis of the errors in multicomponent spectrophotometric analysis of nucleoside mixtures, by a least-squares procedure, has been made to obtain an expression for the error coefficient, relating the error in calculated concentration to the error in extinction measurements. 2. The error coefficients, which depend only on the `library' of spectra used to fit the experimental curves, have been computed for a number of `libraries' containing the following nucleosides found in s-RNA: adenosine, guanosine, cytidine, uridine, 5-ribosyluracil, 7-methylguanosine, 6-dimethylaminopurine riboside, 6-methylaminopurine riboside and thymine riboside. 3. The error coefficients have been used to determine the best conditions for maximum accuracy in the determination of the compositions of nucleoside mixtures. 4. Experimental determinations of the compositions of nucleoside mixtures have been made and the errors found to be consistent with those predicted by the theoretical analysis. 5. It has been demonstrated that, with certain precautions, the multicomponent spectrophotometric method described is suitable as a basis for automatic nucleotide-composition analysis of oligonucleotides containing nine nucleotides. Used in conjunction with continuous chromatography and flow chemical techniques, this method can be applied to the study of the sequence of s-RNA. PMID:14346087

From least squares to multilevel modeling: A graphical introduction to Bayesian inference

NASA Astrophysics Data System (ADS)

Loredo, Thomas J.

2016-01-01

This tutorial presentation will introduce some of the key ideas and techniques involved in applying Bayesian methods to problems in astrostatistics. The focus will be on the big picture: understanding the foundations (interpreting probability, Bayes's theorem, the law of total probability and marginalization), making connections to traditional methods (propagation of errors, least squares, chi-squared, maximum likelihood, Monte Carlo simulation), and highlighting problems where a Bayesian approach can be particularly powerful (Poisson processes, density estimation and curve fitting with measurement error). The "graphical" component of the title reflects an emphasis on pictorial representations of some of the math, but also on the use of graphical models (multilevel or hierarchical models) for analyzing complex data. Code for some examples from the talk will be available to participants, in Python and in the Stan probabilistic programming language.

Chemometrics resolution and quantification power evaluation: Application on pharmaceutical quaternary mixture of Paracetamol, Guaifenesin, Phenylephrine and p-aminophenol.

PubMed

Yehia, Ali M; Mohamed, Heba M

2016-01-05

Three advanced chemmometric-assisted spectrophotometric methods namely; Concentration Residuals Augmented Classical Least Squares (CRACLS), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis-Artificial Neural Networks (PCA-ANN) were developed, validated and benchmarked to PLS calibration; to resolve the severely overlapped spectra and simultaneously determine; Paracetamol (PAR), Guaifenesin (GUA) and Phenylephrine (PHE) in their ternary mixture and in presence of p-aminophenol (AP) the main degradation product and synthesis impurity of Paracetamol. The analytical performance of the proposed methods was described by percentage recoveries, root mean square error of calibration and standard error of prediction. The four multivariate calibration methods could be directly used without any preliminary separation step and successfully applied for pharmaceutical formulation analysis, showing no excipients' interference. Copyright © 2015 Elsevier B.V. All rights reserved.

CARS Spectral Fitting with Multiple Resonant Species using Sparse Libraries

NASA Technical Reports Server (NTRS)

Cutler, Andrew D.; Magnotti, Gaetano

2010-01-01

The dual pump CARS technique is often used in the study of turbulent flames. Fast and accurate algorithms are needed for fitting dual-pump CARS spectra for temperature and multiple chemical species. This paper describes the development of such an algorithm. The algorithm employs sparse libraries, whose size grows much more slowly with number of species than a conventional library. The method was demonstrated by fitting synthetic "experimental" spectra containing 4 resonant species (N2, O2, H2 and CO2), both with noise and without it, and by fitting experimental spectra from a H2-air flame produced by a Hencken burner. In both studies, weighted least squares fitting of signal, as opposed to least squares fitting signal or square-root signal, was shown to produce the least random error and minimize bias error in the fitted parameters.

Nondestructive quantification of the soluble-solids content and the available acidity of apples by Fourier-transform near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Ying, Yibin; Liu, Yande; Tao, Yang

2005-09-01

This research evaluated the feasibility of using Fourier-transform near-infrared (FT-NIR) spectroscopy to quantify the soluble-solids content (SSC) and the available acidity (VA) in intact apples. Partial least-squares calibration models, obtained from several preprocessing techniques (smoothing, derivative, etc.) in several wave-number ranges were compared. The best models were obtained with the high coefficient determination (r) 0.940 for the SSC and a moderate r of 0.801 for the VA, root-mean-square errors of prediction of 0.272% and 0.053%, and root-mean-square errors of calibration of 0.261% and 0.046%, respectively. The results indicate that the FT-NIR spectroscopy yields good predictions of the SSC and also showed the feasibility of using it to predict the VA of apples.

Rovibrational spectra of ammonia. I. Unprecedented accuracy of a potential energy surface used with nonadiabatic corrections.

PubMed

Huang, Xinchuan; Schwenke, David W; Lee, Timothy J

2011-01-28

In this work, we build upon our previous work on the theoretical spectroscopy of ammonia, NH(3). Compared to our 2008 study, we include more physics in our rovibrational calculations and more experimental data in the refinement procedure, and these enable us to produce a potential energy surface (PES) of unprecedented accuracy. We call this the HSL-2 PES. The additional physics we include is a second-order correction for the breakdown of the Born-Oppenheimer approximation, and we find it to be critical for improved results. By including experimental data for higher rotational levels in the refinement procedure, we were able to greatly reduce our systematic errors for the rotational dependence of our predictions. These additions together lead to a significantly improved total angular momentum (J) dependence in our computed rovibrational energies. The root-mean-square error between our predictions using the HSL-2 PES and the reliable energy levels from the HITRAN database for J = 0-6 and J = 7∕8 for (14)NH(3) is only 0.015 cm(-1) and 0.020∕0.023 cm(-1), respectively. The root-mean-square errors for the characteristic inversion splittings are approximately 1∕3 smaller than those for energy levels. The root-mean-square error for the 6002 J = 0-8 transition energies is 0.020 cm(-1). Overall, for J = 0-8, the spectroscopic data computed with HSL-2 is roughly an order of magnitude more accurate relative to our previous best ammonia PES (denoted HSL-1). These impressive numbers are eclipsed only by the root-mean-square error between our predictions for purely rotational transition energies of (15)NH(3) and the highly accurate Cologne database (CDMS): 0.00034 cm(-1) (10 MHz), in other words, 2 orders of magnitude smaller. In addition, we identify a deficiency in the (15)NH(3) energy levels determined from a model of the experimental data.

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

NASA Astrophysics Data System (ADS)

Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad

2018-02-01

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.

Ambiguity resolution for satellite Doppler positioning systems

NASA Technical Reports Server (NTRS)

Argentiero, P.; Marini, J.

1979-01-01

The implementation of satellite-based Doppler positioning systems frequently requires the recovery of transmitter position from a single pass of Doppler data. The least-squares approach to the problem yields conjugate solutions on either side of the satellite subtrack. It is important to develop a procedure for choosing the proper solution which is correct in a high percentage of cases. A test for ambiguity resolution which is the most powerful in the sense that it maximizes the probability of a correct decision is derived. When systematic error sources are properly included in the least-squares reduction process to yield an optimal solution the test reduces to choosing the solution which provides the smaller valuation of the least-squares loss function. When systematic error sources are ignored in the least-squares reduction, the most powerful test is a quadratic form comparison with the weighting matrix of the quadratic form obtained by computing the pseudoinverse of a reduced-rank square matrix. A formula for computing the power of the most powerful test is provided. Numerical examples are included in which the power of the test is computed for situations that are relevant to the design of a satellite-aided search and rescue system.

Red Wine Age Estimation by the Alteration of Its Color Parameters: Fourier Transform Infrared Spectroscopy as a Tool to Monitor Wine Maturation Time

PubMed Central

Basalekou, M.; Pappas, C.; Kotseridis, Y.; Tarantilis, P. A.; Kontaxakis, E.

2017-01-01

Color, phenolic content, and chemical age values of red wines made from Cretan grape varieties (Kotsifali, Mandilari) were evaluated over nine months of maturation in different containers for two vintages. The wines differed greatly on their anthocyanin profiles. Mid-IR spectra were also recorded with the use of a Fourier Transform Infrared Spectrophotometer in ZnSe disk mode. Analysis of Variance was used to explore the parameter's dependency on time. Determination models were developed for the chemical age indexes using Partial Least Squares (PLS) (TQ Analyst software) considering the spectral region 1830–1500 cm−1. The correlation coefficients (r) for chemical age index i were 0.86 for Kotsifali (Root Mean Square Error of Calibration (RMSEC) = 0.067, Root Mean Square Error of Prediction (RMSEP) = 0,115, and Root Mean Square Error of Validation (RMSECV) = 0.164) and 0.90 for Mandilari (RMSEC = 0.050, RMSEP = 0.040, and RMSECV = 0.089). For chemical age index ii the correlation coefficients (r) were 0.86 and 0.97 for Kotsifali (RMSEC 0.044, RMSEP = 0.087, and RMSECV = 0.214) and Mandilari (RMSEC = 0.024, RMSEP = 0.033, and RMSECV = 0.078), respectively. The proposed method is simpler, less time consuming, and more economical and does not require chemical reagents. PMID:29225994

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Quick method (FT-NIR) for the determination of oil and major fatty acids content in whole achenes of milk thistle (Silybum marianum (L.) Gaertn.).

PubMed

Koláčková, Pavla; Růžičková, Gabriela; Gregor, Tomáš; Šišperová, Eliška

2015-08-30

Calibration models for the Fourier transform-near infrared (FT-NIR) instrument were developed for quick and non-destructive determination of oil and fatty acids in whole achenes of milk thistle. Samples with a range of oil and fatty acid levels were collected and their transmittance spectra were obtained by the FT-NIR instrument. Based on these spectra and data gained by the means of the reference method - Soxhlet extraction and gas chromatography (GC) - calibration models were created by means of partial least square (PLS) regression analysis. Precision and accuracy of the calibration models was verified via the cross-validation of validation samples whose spectra were not part of the calibration model and also according to the root mean square error of prediction (RMSEP), root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV) and the validation coefficient of determination (R(2) ). R(2) for whole seeds were 0.96, 0.96, 0.83 and 0.67 and the RMSEP values were 0.76, 1.68, 1.24, 0.54 for oil, linoleic (C18:2), oleic (C18:1) and palmitic (C16:0) acids, respectively. The calibration models are appropriate for the non-destructive determination of oil and fatty acids levels in whole seeds of milk thistle. © 2014 Society of Chemical Industry.

Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations.

PubMed

da Silva, Fabiana E B; Flores, Érico M M; Parisotto, Graciele; Müller, Edson I; Ferrão, Marco F

2016-03-01

An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.

Performance of the Automated Neuropsychological Assessment Metrics (ANAM) in detecting cognitive impairment in heart failure patients.

PubMed

Xie, Susan S; Goldstein, Carly M; Gathright, Emily C; Gunstad, John; Dolansky, Mary A; Redle, Joseph; Hughes, Joel W

2015-01-01

Evaluate capacity of the Automated Neuropsychological Assessment Metrics (ANAM) to detect cognitive impairment (CI) in heart failure (HF) patients. CI is a key prognostic marker in HF. Though the most widely used cognitive screen in HF, the Mini-Mental State Examination (MMSE) is insufficiently sensitive. The ANAM has demonstrated sensitivity to cognitive domains affected by HF, but has not been assessed in this population. Investigators administered the ANAM and MMSE to 57 HF patients, compared against a composite model of cognitive function. ANAM efficiency (p < .05) and accuracy scores (p < .001) successfully differentiated CI and non-CI. ANAM efficiency and accuracy scores classified 97.7% and 93.0% of non-CI patients, and 14.3% and 21.4% with CI, respectively. The ANAM is more effective than the MMSE for detecting CI, but further research is needed to develop a more optimal cognitive screen for routine use in HF patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Payload specialist station study: Volume 2, part 3: Program analysis and planning for phase C/D

NASA Technical Reports Server (NTRS)

1976-01-01

The controls and displays (C&D) required at the Orbiter aft-flight deck (AFD) and the core C&D required at the Payload Specialist Station (PSS) are identified in this document. The AFD C&D Concept consists of a multifunction display system (MFDS) and elements of multiuse mission support equipment (MMSE). The MFDS consists of two CRTs, a display electronics unit (DEU), and a keyboard. The MMSE consists of a manual pointing controller (MPC), five digit numeric displays, 10 character alphanumeric legends, event timers, analog meters, rotary and toggle switches. The MMSE may be hardwired to the experiment, or interface with a data bus at the PSS for signal processing. The MFDS has video capability, with alphanumeric and graphic overlay features, on one CRT and alphanumeric and graphic (tricolor) capability on a second CRT. The DEU will have the capability to communicate, via redundant data buses, with both the spacelab experiment and subsystem computers.

Cognitive impairment in patients with fibromyalgia syndrome as assessed by the mini-mental state examination.

PubMed

Rodríguez-Andreu, Jose; Ibáñez-Bosch, Rosario; Portero-Vázquez, Amparo; Masramon, Xavier; Rejas, Javier; Gálvez, Rafael

2009-12-21

This study evaluated the frequency of cognitive impairment in patients with Fibromyalgia syndrome (FMS) using the Mini Mental State Examination (MMSE). We analyzed baseline data from all 46 patients with FMS and 92 age- and sex-matched controls per diagnosis of neuropathic (NeP) or mixed pain (MP) selected from a larger prospective study. FMS had a slight but statistically significant lower score in the adjusted MMSE score (26.9; 95% CI 26.7-27.1) than either NeP (27.3; 95% CI 27.2-27.4) or MP (27.3; 27.2-27.5). The percentage of patients with congnitive impairment (adjusted MMSE

New method for propagating the square root covariance matrix in triangular form. [using Kalman-Bucy filter

NASA Technical Reports Server (NTRS)

Choe, C. Y.; Tapley, B. D.

1975-01-01

A method proposed by Potter of applying the Kalman-Bucy filter to the problem of estimating the state of a dynamic system is described, in which the square root of the state error covariance matrix is used to process the observations. A new technique which propagates the covariance square root matrix in lower triangular form is given for the discrete observation case. The technique is faster than previously proposed algorithms and is well-adapted for use with the Carlson square root measurement algorithm.

Predictors of driving safety in early Alzheimer disease

PubMed Central

Dawson, J D.; Anderson, S W.; Uc, E Y.; Dastrup, E; Rizzo, M

2009-01-01

Objective: To measure the association of cognition, visual perception, and motor function with driving safety in Alzheimer disease (AD). Methods: Forty drivers with probable early AD (mean Mini-Mental State Examination score 26.5) and 115 elderly drivers without neurologic disease underwent a battery of cognitive, visual, and motor tests, and drove a standardized 35-mile route in urban and rural settings in an instrumented vehicle. A composite cognitive score (COGSTAT) was calculated for each subject based on eight neuropsychological tests. Driving safety errors were noted and classified by a driving expert based on video review. Results: Drivers with AD committed an average of 42.0 safety errors/drive (SD = 12.8), compared to an average of 33.2 (SD = 12.2) for drivers without AD (p < 0.0001); the most common errors were lane violations. Increased age was predictive of errors, with a mean of 2.3 more errors per drive observed for each 5-year age increment. After adjustment for age and gender, COGSTAT was a significant predictor of safety errors in subjects with AD, with a 4.1 increase in safety errors observed for a 1 SD decrease in cognitive function. Significant increases in safety errors were also found in subjects with AD with poorer scores on Benton Visual Retention Test, Complex Figure Test-Copy, Trail Making Subtest-A, and the Functional Reach Test. Conclusion: Drivers with Alzheimer disease (AD) exhibit a range of performance on tests of cognition, vision, and motor skills. Since these tests provide additional predictive value of driving performance beyond diagnosis alone, clinicians may use these tests to help predict whether a patient with AD can safely operate a motor vehicle. GLOSSARY AD = Alzheimer disease; AVLT = Auditory Verbal Learning Test; Blocks = Block Design subtest; BVRT = Benton Visual Retention Test; CFT = Complex Figure Test; CI = confidence interval; COWA = Controlled Oral Word Association; CS = contrast sensitivity; FVA = far visual acuity; JLO = Judgment of Line Orientation; MCI = mild cognitive impairment; MMSE = Mini-Mental State Examination; NVA = near visual acuity; SFM = structure from motion; TMT = Trail-Making Test; UFOV = Useful Field of View. PMID:19204261

A Comparison of Normal and Elliptical Estimation Methods in Structural Equation Models.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Cheevatanarak, Suchittra

Monte Carlo simulation compared chi-square statistics, parameter estimates, and root mean square error of approximation values using normal and elliptical estimation methods. Three research conditions were imposed on the simulated data: sample size, population contamination percent, and kurtosis. A Bentler-Weeks structural model established the…

Phase modulation for reduced vibration sensitivity in laser-cooled clocks in space

NASA Technical Reports Server (NTRS)

Klipstein, W.; Dick, G.; Jefferts, S.; Walls, F.

2001-01-01

The standard interrogation technique in atomic beam clocks is square-wave frequency modulation (SWFM), which suffers a first order sensitivity to vibrations as changes in the transit time of the atoms translates to perceived frequency errors. Square-wave phase modulation (SWPM) interrogation eliminates sensitivity to this noise.

An Examination of Statistical Power in Multigroup Dynamic Structural Equation Models

ERIC Educational Resources Information Center

Prindle, John J.; McArdle, John J.

2012-01-01

This study used statistical simulation to calculate differential statistical power in dynamic structural equation models with groups (as in McArdle & Prindle, 2008). Patterns of between-group differences were simulated to provide insight into how model parameters influence power approximations. Chi-square and root mean square error of…

Parameter estimation of Monod model by the Least-Squares method for microalgae Botryococcus Braunii sp

NASA Astrophysics Data System (ADS)

See, J. J.; Jamaian, S. S.; Salleh, R. M.; Nor, M. E.; Aman, F.

2018-04-01

This research aims to estimate the parameters of Monod model of microalgae Botryococcus Braunii sp growth by the Least-Squares method. Monod equation is a non-linear equation which can be transformed into a linear equation form and it is solved by implementing the Least-Squares linear regression method. Meanwhile, Gauss-Newton method is an alternative method to solve the non-linear Least-Squares problem with the aim to obtain the parameters value of Monod model by minimizing the sum of square error ( SSE). As the result, the parameters of the Monod model for microalgae Botryococcus Braunii sp can be estimated by the Least-Squares method. However, the estimated parameters value obtained by the non-linear Least-Squares method are more accurate compared to the linear Least-Squares method since the SSE of the non-linear Least-Squares method is less than the linear Least-Squares method.

Understanding Scaling Relations in Fracture and Mechanical Deformation of Single Crystal and Polycrystalline Silicon by Performing Atomistic Simulations at Mesoscale

DTIC Science & Technology

2009-07-16

0.25 0.26 -0.85 1 SSR SSE R SSTO SSTO = = − 2 2 ˆ( ) : Regression sum of square, ˆwhere : mean value, : value from the fitted line ˆ...Error sum of square : Total sum of square i i i i SSR Y Y Y Y SSE Y Y SSTO SSE SSR = − = − = + ∑ ∑ Statistical analysis: Coefficient of correlation

Comparative Diagnostic Accuracy of the ACE-III, MIS, MMSE, MoCA, and RUDAS for Screening of Alzheimer Disease.

PubMed

Matías-Guiu, Jordi A; Valles-Salgado, María; Rognoni, Teresa; Hamre-Gil, Frank; Moreno-Ramos, Teresa; Matías-Guiu, Jorge

2017-01-01

Our aim was to evaluate and compare the diagnostic properties of 5 screening tests for the diagnosis of mild Alzheimer disease (AD). We conducted a prospective and cross-sectional study of 92 patients with mild AD and of 68 healthy controls from our Department of Neurology. The diagnostic properties of the following tests were compared: Mini-Mental State Examination (MMSE), Addenbrooke's Cognitive Examination III (ACE-III), Memory Impairment Screen (MIS), Montreal Cognitive Assessment (MoCA), and Rowland Universal Dementia Assessment Scale (RUDAS). All tests yielded high diagnostic accuracy, with the ACE-III achieving the best diagnostic properties. The area under the curve was 0.897 for the ACE-III, 0.889 for the RUDAS, 0.874 for the MMSE, 0.866 for the MIS, and 0.856 for the MoCA. The Mini-ACE score from the ACE-III showed the highest diagnostic capacity (area under the curve 0.939). Memory scores of the ACE-III and of the RUDAS showed a better diagnostic accuracy than those of the MMSE and of the MoCA. All tests, especially the ACE-III, conveyed a higher diagnostic accuracy in patients with full primary education than in the less educated group. Implementing normative data improved the diagnostic accuracy of the ACE-III but not that of the other tests. The ACE-III achieved the highest diagnostic accuracy. This better discrimination was more evident in the more educated group. © 2017 S. Karger AG, Basel.

A systematic review of cognitive decline in dementia with Lewy bodies versus Alzheimer’s disease

PubMed Central

2014-01-01

Introduction The aim of this review was to investigate whether there is a faster cognitive decline in dementia with Lewy bodies (DLB) than in Alzheimer’s disease (AD) over time. Methods PsycINFO and Medline were searched from 1946 to February 2013. A quality rating from 1 to 15 (best) was applied to the included studies. A quantitative meta-analysis was done on studies with mini mental state examination (MMSE) as the outcome measure. Results A total of 18 studies were included. Of these, six (36%) reported significant differences in the rate of cognitive decline. Three studies reported a faster cognitive decline on MMSE in patients with mixed DLB and AD compared to pure forms, whereas two studies reported a faster decline on delayed recall and recognition in AD and one in DLB on verbal fluency. Mean quality scores for studies that did or did not differ were not significantly different. Six studies reported MMSE scores and were included in the meta-analysis, which showed no significant difference in annual decline on MMSE between DLB (mean 3.4) and AD (mean 3.3). Conclusions Our findings do not support the hypothesis of a faster rate of cognitive decline in DLB compared to AD. Future studies should apply recent diagnostic criteria, as well as extensive diagnostic evaluation and ideally autopsy diagnosis. Studies with large enough samples, detailed cognitive tests, at least two years follow up and multivariate statistical analysis are also needed. PMID:25478024

Electroencephalographic characteristics of Iranian schizophrenia patients.

PubMed

Chaychi, Irman; Foroughipour, Mohsen; Haghir, Hossein; Talaei, Ali; Chaichi, Ashkan

2015-12-01

Schizophrenia is a prevalent psychiatric disease with heterogeneous causes that is diagnosed based on history and mental status examination. Applied electrophysiology is a non-invasive method to investigate the function of the involved brain areas. In a previously understudied population, we examined acute phase electroencephalography (EEG) records along with pertinent Positive and Negative Syndrome Scale (PANSS) and Mini Mental State Examination (MMSE) scores for each patient. Sixty-four hospitalized patients diagnosed to have schizophrenia in Ebn-e-Sina Hospital were included in this study. PANSS and MMSE were completed and EEG tracings for every patient were recorded. Also, EEG tracings were recorded for 64 matched individuals of the control group. Although the predominant wave pattern in both patients and controls was alpha, theta waves were almost exclusively found in eight (12.5 %) patients with schizophrenia. Pathological waves in schizophrenia patients were exclusively found in the frontal brain region, while identified pathological waves in controls were limited to the temporal region. No specific EEG finding supported laterality in schizophrenia patients. PANSS and MMSE scores were significantly correlated with specific EEG parameters (all P values <0.04). Patients with schizophrenia demonstrate specific EEG patterns and show a clear correlation between EEG parameters and PANSS and MMSE scores. These characteristics are not observed in all patients, which imply that despite an acceptable specificity, they are not applicable for the majority of schizophrenia patients. Any deduction drawn based on EEG and scoring systems is in need of larger studies incorporating more patients and using better functional imaging techniques for the brain.

End-stage dementia spark of life: reliability and validity of the "GATOS" questionnaire.

PubMed

Tsoucalas, Gregory; Bourelia, Stamati; Kalogirou, Vaso; Giatsiou, Styliani; Mavrogiannaki, Eirini; Gatos, Georgios; Galanos, Antonis; Repana, Olga; Iliadou, Eleni; Antoniou, Antonis; Sgantzos, Markos; Gatos, Konstantinos

2015-01-01

Fl oor effects are present in most dementia assessment tools as dementia progresses and the in-depth assessment of patients considered more or less on vegetative state is questionable. To develop a questionnaire (the "Gatos Clinical Test-GCT") for the assessment of end-stage demented patients. Five hundred patients with dementia of various causes and an MMSE score between 0 and 2 were enrolled in the study. The GCT consists of 14 closed type questions rated on a Likert scale. The total score is used to evaluate patient's dementia. Various aspects of validity and reliability (including face, content and structural validity as well as test-retest reliability) were examined. Three subscales "Autonomy/Alertness", "Gnosias" and "Somatokinetic function" were defined, with a Cronbach equal to 0.851, 0.756 and 0.598 respectively. The GCT subscales and total score were statistically significant higher in patients with MMSE score 1 or 2 compared with those with MMSE score 0 (p<0.0005). Patients with GCT total score less than 12.5 had 75% probability to have zero MMSE score. The "GATOS" questionnaire is a valid and reliable test for patients with severe dementia, aiming at identification of those patients who could sustain some quality of life. It is a relatively short and easy to administer tool. As dementia prevalence is expected to rise further worldwide we believe that GCT could offer valuable services to health professionals, caregivers and patients.

Correlation between the Quality of Attention and Cognitive Competence with Motor Action in Stroke Patients.

PubMed

Arsic, S; Konstantinovic, Lj; Eminovic, F; Pavlovic, D; Popovic, M B; Arsic, V

2015-01-01

It is considered that cognitive function and attention could affect walking, motion control, and proper conduct during the walk. To determine whether there is a difference in the quality of attention and cognitive ability in stroke patients and patients without neurological damage of similar age and education and to determine whether the connection of attention and cognition affects motor skills, the sample consisted of 50 stroke patients tested with hemiparesis, involved in the process of rehabilitation, and 50 persons, randomly chosen, without neurological damage. The survey used the following tests: Trail Making (TMT A B) test for assessing the flexibility of attention; Mini-Mental State Examination (MMSE) for cognitive status; Functional Ambulation Category (FAC) test to assess the functional status and parameters of walk: speed, frequency, and length of stride; STEP test for assessing the precision of movement and balance. With stroke patients, relationship between age and performance on the MMSE test was marginally significant. The ratio of performance to TMT A B test and years does not indicate statistical significance, while statistical significance between the MMSE test performance and education exists. In stroke patients, performance on MMSE test is correlated with the frequency and length of stride walk. The quality of cognitive function and attention is associated with motor skills but differs in stroke patients and people without neurological damage of similar age. The significance of this correlation can supplement research in neurorehabilitation, improve the quality of medical rehabilitation, and contribute to efficient recovery of these patients.

Synthesis of hover autopilots for rotary-wing VTOL aircraft

NASA Technical Reports Server (NTRS)

Hall, W. E.; Bryson, A. E., Jr.

1972-01-01

The practical situation is considered where imperfect information on only a few rotor and fuselage state variables is available. Filters are designed to estimate all the state variables from noisy measurements of fuselage pitch/roll angles and from noisy measurements of both fuselage and rotor pitch/roll angles. The mean square response of the vehicle to a very gusty, random wind is computed using various filter/controllers and is found to be quite satisfactory although, of course, not so good as when one has perfect information (idealized case). The second part of the report considers precision hover over a point on the ground. A vehicle model without rotor dynamics is used and feedback signals in position and integral of position error are added. The mean square response of the vehicle to a very gusty, random wind is computed, assuming perfect information feedback, and is found to be excellent. The integral error feedback gives zero position error for a steady wind, and smaller position error for a random wind.

Bayesian generalized least squares regression with application to log Pearson type 3 regional skew estimation

NASA Astrophysics Data System (ADS)

Reis, D. S.; Stedinger, J. R.; Martins, E. S.

2005-10-01

This paper develops a Bayesian approach to analysis of a generalized least squares (GLS) regression model for regional analyses of hydrologic data. The new approach allows computation of the posterior distributions of the parameters and the model error variance using a quasi-analytic approach. Two regional skew estimation studies illustrate the value of the Bayesian GLS approach for regional statistical analysis of a shape parameter and demonstrate that regional skew models can be relatively precise with effective record lengths in excess of 60 years. With Bayesian GLS the marginal posterior distribution of the model error variance and the corresponding mean and variance of the parameters can be computed directly, thereby providing a simple but important extension of the regional GLS regression procedures popularized by Tasker and Stedinger (1989), which is sensitive to the likely values of the model error variance when it is small relative to the sampling error in the at-site estimator.

Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.

PubMed

Piatrou, Piotr; Gilles, Luc

2005-02-20

Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.

A Comprehensive Study of Gridding Methods for GPS Horizontal Velocity Fields

NASA Astrophysics Data System (ADS)

Wu, Yanqiang; Jiang, Zaisen; Liu, Xiaoxia; Wei, Wenxin; Zhu, Shuang; Zhang, Long; Zou, Zhenyu; Xiong, Xiaohui; Wang, Qixin; Du, Jiliang

2017-03-01

Four gridding methods for GPS velocities are compared in terms of their precision, applicability and robustness by analyzing simulated data with uncertainties from 0.0 to ±3.0 mm/a. When the input data are 1° × 1° grid sampled and the uncertainty of the additional error is greater than ±1.0 mm/a, the gridding results show that the least-squares collocation method is highly robust while the robustness of the Kriging method is low. In contrast, the spherical harmonics and the multi-surface function are moderately robust, and the regional singular values for the multi-surface function method and the edge effects for the spherical harmonics method become more significant with increasing uncertainty of the input data. When the input data (with additional errors of ±2.0 mm/a) are decimated by 50% from the 1° × 1° grid data and then erased in three 6° × 12° regions, the gridding results in these three regions indicate that the least-squares collocation and the spherical harmonics methods have good performances, while the multi-surface function and the Kriging methods may lead to singular values. The gridding techniques are also applied to GPS horizontal velocities with an average error of ±0.8 mm/a over the Chinese mainland and the surrounding areas, and the results show that the least-squares collocation method has the best performance, followed by the Kriging and multi-surface function methods. Furthermore, the edge effects of the spherical harmonics method are significantly affected by the sparseness and geometric distribution of the input data. In general, the least-squares collocation method is superior in terms of its robustness, edge effect, error distribution and stability, while the other methods have several positive features.

Analysis of S-box in Image Encryption Using Root Mean Square Error Method

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-07-01

The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes

An Error-Entropy Minimization Algorithm for Tracking Control of Nonlinear Stochastic Systems with Non-Gaussian Variables

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

Liu, Yunlong; Wang, Aiping; Guo, Lei

This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.

Error-Based Design Space Windowing

NASA Technical Reports Server (NTRS)

Papila, Melih; Papila, Nilay U.; Shyy, Wei; Haftka, Raphael T.; Fitz-Coy, Norman

2002-01-01

Windowing of design space is considered in order to reduce the bias errors due to low-order polynomial response surfaces (RS). Standard design space windowing (DSW) uses a region of interest by setting a requirement on response level and checks it by a global RS predictions over the design space. This approach, however, is vulnerable since RS modeling errors may lead to the wrong region to zoom on. The approach is modified by introducing an eigenvalue error measure based on point-to-point mean squared error criterion. Two examples are presented to demonstrate the benefit of the error-based DSW.

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

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

Zhou, Ping; Wang, Chenyu; Li, Mingjie

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First,more » the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.« less

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

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

Zhou, Ping; Wang, Chenyu; Li, Mingjie

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) cannot fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, themore » modeling error PDF by the traditional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. However, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.« less

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

DOE PAGES

Zhou, Ping; Wang, Chenyu; Li, Mingjie; ...

2018-01-31

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) cannot fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, themore » modeling error PDF by the traditional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. However, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.« less

Error in telemetry studies: Effects of animal movement on triangulation

USGS Publications Warehouse

Schmutz, Joel A.; White, Gary C.

1990-01-01

We used Monte Carlo simulations to investigate the effects of animal movement on error of estimated animal locations derived from radio-telemetry triangulation of sequentially obtained bearings. Simulated movements of 0-534 m resulted in up to 10-fold increases in average location error but <10% decreases in location precision when observer-to-animal distances were <1,000 m. Location error and precision were minimally affected by censorship of poor locations with Chi-square goodness-of-fit tests. Location error caused by animal movement can only be eliminated by taking simultaneous bearings.

The theory precision analyse of RFM localization of satellite remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhang, Jianqing; Xv, Biao

2009-11-01

The tradition method of detecting precision of Rational Function Model(RFM) is to make use of a great deal check points, and it calculates mean square error through comparing calculational coordinate with known coordinate. This method is from theory of probability, through a large number of samples to statistic estimate value of mean square error, we can think its estimate value approaches in its true when samples are well enough. This paper is from angle of survey adjustment, take law of propagation of error as the theory basis, and it calculates theory precision of RFM localization. Then take the SPOT5 three array imagery as experiment data, and the result of traditional method and narrated method in the paper are compared, while has confirmed tradition method feasible, and answered its theory precision question from the angle of survey adjustment.

Fundamental Analysis of the Linear Multiple Regression Technique for Quantification of Water Quality Parameters from Remote Sensing Data. Ph.D. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Whitlock, C. H., III

1977-01-01

Constituents with linear radiance gradients with concentration may be quantified from signals which contain nonlinear atmospheric and surface reflection effects for both homogeneous and non-homogeneous water bodies provided accurate data can be obtained and nonlinearities are constant with wavelength. Statistical parameters must be used which give an indication of bias as well as total squared error to insure that an equation with an optimum combination of bands is selected. It is concluded that the effect of error in upwelled radiance measurements is to reduce the accuracy of the least square fitting process and to increase the number of points required to obtain a satisfactory fit. The problem of obtaining a multiple regression equation that is extremely sensitive to error is discussed.

Diffuse-flow conceptualization and simulation of the Edwards aquifer, San Antonio region, Texas

USGS Publications Warehouse

Lindgren, R.J.

2006-01-01

A numerical ground-water-flow model (hereinafter, the conduit-flow Edwards aquifer model) of the karstic Edwards aquifer in south-central Texas was developed for a previous study on the basis of a conceptualization emphasizing conduit development and conduit flow, and included simulating conduits as one-cell-wide, continuously connected features. Uncertainties regarding the degree to which conduits pervade the Edwards aquifer and influence ground-water flow, as well as other uncertainties inherent in simulating conduits, raised the question of whether a model based on the conduit-flow conceptualization was the optimum model for the Edwards aquifer. Accordingly, a model with an alternative hydraulic conductivity distribution without conduits was developed in a study conducted during 2004-05 by the U.S. Geological Survey, in cooperation with the San Antonio Water System. The hydraulic conductivity distribution for the modified Edwards aquifer model (hereinafter, the diffuse-flow Edwards aquifer model), based primarily on a conceptualization in which flow in the aquifer predominantly is through a network of numerous small fractures and openings, includes 38 zones, with hydraulic conductivities ranging from 3 to 50,000 feet per day. Revision of model input data for the diffuse-flow Edwards aquifer model was limited to changes in the simulated hydraulic conductivity distribution. The root-mean-square error for 144 target wells for the calibrated steady-state simulation for the diffuse-flow Edwards aquifer model is 20.9 feet. This error represents about 3 percent of the total head difference across the model area. The simulated springflows for Comal and San Marcos Springs for the calibrated steady-state simulation were within 2.4 and 15 percent of the median springflows for the two springs, respectively. The transient calibration period for the diffuse-flow Edwards aquifer model was 1947-2000, with 648 monthly stress periods, the same as for the conduit-flow Edwards aquifer model. The root-mean-square error for a period of drought (May-November 1956) for the calibrated transient simulation for 171 target wells is 33.4 feet, which represents about 5 percent of the total head difference across the model area. The root-mean-square error for a period of above-normal rainfall (November 1974-July 1975) for the calibrated transient simulation for 169 target wells is 25.8 feet, which represents about 4 percent of the total head difference across the model area. The root-mean-square error ranged from 6.3 to 30.4 feet in 12 target wells with long-term water-level measurements for varying periods during 1947-2000 for the calibrated transient simulation for the diffuse-flow Edwards aquifer model, and these errors represent 5.0 to 31.3 percent of the range in water-level fluctuations of each of those wells. The root-mean-square errors for the five major springs in the San Antonio segment of the aquifer for the calibrated transient simulation, as a percentage of the range of discharge fluctuations measured at the springs, varied from 7.2 percent for San Marcos Springs and 8.1 percent for Comal Springs to 28.8 percent for Leona Springs. The root-mean-square errors for hydraulic heads for the conduit-flow Edwards aquifer model are 27, 76, and 30 percent greater than those for the diffuse-flow Edwards aquifer model for the steady-state, drought, and above-normal rainfall synoptic time periods, respectively. The goodness-of-fit between measured and simulated springflows is similar for Comal, San Marcos, and Leona Springs for the diffuse-flow Edwards aquifer model and the conduit-flow Edwards aquifer model. The root-mean-square errors for Comal and Leona Springs were 15.6 and 21.3 percent less, respectively, whereas the root-mean-square error for San Marcos Springs was 3.3 percent greater for the diffuse-flow Edwards aquifer model compared to the conduit-flow Edwards aquifer model. The root-mean-square errors for San Antonio and San Pedro Springs were appreciably greater, 80.2 and 51.0 percent, respectively, for the diffuse-flow Edwards aquifer model. The simulated water budgets for the diffuse-flow Edwards aquifer model are similar to those for the conduit-flow Edwards aquifer model. Differences in percentage of total sources or discharges for a budget component are 2.0 percent or less for all budget components for the steady-state and transient simulations. The largest difference in terms of the magnitude of water budget components for the transient simulation for 1956 was a decrease of about 10,730 acre-feet per year (about 2 per-cent) in springflow for the diffuse-flow Edwards aquifer model compared to the conduit-flow Edwards aquifer model. This decrease in springflow (a water budget discharge) was largely offset by the decreased net loss of water from storage (a water budget source) of about 10,500 acre-feet per year.

Study on the Effects of Individualized Learning Therapy on Cognitive Function and Behavioral and Psychological Symptoms of Dementia in the Institutionalized Older Adults.

PubMed

Chen, Hsiao-Mei; Tsai, Li-Jane; Chao, Shu-Yuan; Clark, Mary Jo

2016-12-01

The increasing number of elderly people affected by dementia in Taiwan has made dementia care a crucial issue of concern. This issue is particularly important in terms of the proper management of behavioral symptoms and improvement of the cognitive functions of those affected by this disease. This study examined the effects of individualized learning therapy on cognition and neuropsychiatric symptoms among elderly people with dementia. A quasi-experimental, pretest-posttest research design was adopted. We recruited elderly people with dementia at the only two institutions for elderly patients with dementia in Central Taiwan. These institutions were assigned randomly as the experimental or control group, with totals of 23 and 21 participants, respectively. The participants in the experimental group received individualized learning therapy for 30 minutes twice weekly for 3 months. The comparison group received usual care only. The cognitive function and neuropsychiatric symptoms of all participants were measured using the Mini-Mental Status Examination (MMSE) before the start of and immediately after the 12-week intervention and the Chinese version of the Neuropsychiatric Inventory (CNPI), which was administered once per week during the intervention. Independent t tests (or Mann-Whitney U tests), chi-square tests (or Fisher's exact tests), paired t test, and generalized estimating equations were used for data analysis. Participants in the experimental group had significantly higher MMSE scores (p < .01) and lower CNPI scores (p < .01) than their comparison group peers after the intervention. Furthermore, the neuropsychiatric symptoms in the experimental group such as hallucinations, bizarre behavior, depression, apathetic expression, irritability, and sleep disorder had significantly improved by the seventh week. Individualized learning therapy may be an effective approach to improve cognitive function and reduce neuropsychiatric symptoms among older people with dementia. Therefore, future clinical application is warranted.

Quantitative determination of additive Chlorantraniliprole in Abamectin preparation: Investigation of bootstrapping soft shrinkage approach by mid-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yan, Hong; Song, Xiangzhong; Tian, Kuangda; Chen, Yilin; Xiong, Yanmei; Min, Shungeng

2018-02-01

A novel method, mid-infrared (MIR) spectroscopy, which enables the determination of Chlorantraniliprole in Abamectin within minutes, is proposed. We further evaluate the prediction ability of four wavelength selection methods, including bootstrapping soft shrinkage approach (BOSS), Monte Carlo uninformative variable elimination (MCUVE), genetic algorithm partial least squares (GA-PLS) and competitive adaptive reweighted sampling (CARS) respectively. The results showed that BOSS method obtained the lowest root mean squared error of cross validation (RMSECV) (0.0245) and root mean squared error of prediction (RMSEP) (0.0271), as well as the highest coefficient of determination of cross-validation (Qcv2) (0.9998) and the coefficient of determination of test set (Q2test) (0.9989), which demonstrated that the mid infrared spectroscopy can be used to detect Chlorantraniliprole in Abamectin conveniently. Meanwhile, a suitable wavelength selection method (BOSS) is essential to conducting a component spectral analysis.

Accuracy of least-squares methods for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Bochev, Pavel B.; Gunzburger, Max D.

1993-01-01

Recently there has been substantial interest in least-squares finite element methods for velocity-vorticity-pressure formulations of the incompressible Navier-Stokes equations. The main cause for this interest is the fact that algorithms for the resulting discrete equations can be devised which require the solution of only symmetric, positive definite systems of algebraic equations. On the other hand, it is well-documented that methods using the vorticity as a primary variable often yield very poor approximations. Thus, here we study the accuracy of these methods through a series of computational experiments, and also comment on theoretical error estimates. It is found, despite the failure of standard methods for deriving error estimates, that computational evidence suggests that these methods are, at the least, nearly optimally accurate. Thus, in addition to the desirable matrix properties yielded by least-squares methods, one also obtains accurate approximations.

Nondestructive quantification of the soluble-solids content and the available acidity of apples by Fourier-transform near-infrared spectroscopy

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

Ying Yibin; Liu Yande; Tao Yang

2005-09-01

This research evaluated the feasibility of using Fourier-transform near-infrared (FT-NIR) spectroscopy to quantify the soluble-solids content (SSC) and the available acidity (VA) in intact apples. Partial least-squares calibration models, obtained from several preprocessing techniques (smoothing, derivative, etc.) in several wave-number ranges were compared. The best models were obtained with the high coefficient determination (r{sup 2}) 0.940 for the SSC and a moderate r{sup 2} of 0.801 for the VA, root-mean-square errors of prediction of 0.272% and 0.053%, and root-mean-square errors of calibration of 0.261% and 0.046%, respectively. The results indicate that the FT-NIR spectroscopy yields good predictions of the SSCmore » and also showed the feasibility of using it to predict the VA of apples.« less

Aerodynamic coefficient identification package dynamic data accuracy determinations: Lessons learned

NASA Technical Reports Server (NTRS)

Heck, M. L.; Findlay, J. T.; Compton, H. R.

1983-01-01

The errors in the dynamic data output from the Aerodynamic Coefficient Identification Packages (ACIP) flown on Shuttle flights 1, 3, 4, and 5 were determined using the output from the Inertial Measurement Units (IMU). A weighted least-squares batch algorithm was empolyed. Using an averaging technique, signal detection was enhanced; this allowed improved calibration solutions. Global errors as large as 0.04 deg/sec for the ACIP gyros, 30 mg for linear accelerometers, and 0.5 deg/sec squared in the angular accelerometer channels were detected and removed with a combination is bias, scale factor, misalignment, and g-sensitive calibration constants. No attempt was made to minimize local ACIP dynamic data deviations representing sensed high-frequency vibration or instrument noise. Resulting 1sigma calibrated ACIP global accuracies were within 0.003 eg/sec, 1.0 mg, and 0.05 deg/sec squared for the gyros, linear accelerometers, and angular accelerometers, respectively.

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

An empirical Bayes approach for the Poisson life distribution.

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1973-01-01

A smooth empirical Bayes estimator is derived for the intensity parameter (hazard rate) in the Poisson distribution as used in life testing. The reliability function is also estimated either by using the empirical Bayes estimate of the parameter, or by obtaining the expectation of the reliability function. The behavior of the empirical Bayes procedure is studied through Monte Carlo simulation in which estimates of mean-squared errors of the empirical Bayes estimators are compared with those of conventional estimators such as minimum variance unbiased or maximum likelihood. Results indicate a significant reduction in mean-squared error of the empirical Bayes estimators over the conventional variety.

Reliable and accurate extraction of Hamaker constants from surface force measurements.

PubMed

Miklavcic, S J

2018-08-15

A simple and accurate closed-form expression for the Hamaker constant that best represents experimental surface force data is presented. Numerical comparisons are made with the current standard least squares approach, which falsely assumes error-free separation measurements, and a nonlinear version assuming independent measurements of force and separation are subject to error. The comparisons demonstrate that not only is the proposed formula easily implemented it is also considerably more accurate. This option is appropriate for any value of Hamaker constant, high or low, and certainly for any interacting system exhibiting an inverse square distance dependent van der Waals force. Copyright © 2018 Elsevier Inc. All rights reserved.

Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems

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

Lee, Kookjin; Carlberg, Kevin; Elman, Howard C.

Here, we consider the numerical solution of parameterized linear systems where the system matrix, the solution, and the right-hand side are parameterized by a set of uncertain input parameters. We explore spectral methods in which the solutions are approximated in a chosen finite-dimensional subspace. It has been shown that the stochastic Galerkin projection technique fails to minimize any measure of the solution error. As a remedy for this, we propose a novel stochatic least-squares Petrov--Galerkin (LSPG) method. The proposed method is optimal in the sense that it produces the solution that minimizes a weightedmore » $$\\ell^2$$-norm of the residual over all solutions in a given finite-dimensional subspace. Moreover, the method can be adapted to minimize the solution error in different weighted $$\\ell^2$$-norms by simply applying a weighting function within the least-squares formulation. In addition, a goal-oriented seminorm induced by an output quantity of interest can be minimized by defining a weighting function as a linear functional of the solution. We establish optimality and error bounds for the proposed method, and extensive numerical experiments show that the weighted LSPG method outperforms other spectral methods in minimizing corresponding target weighted norms.« less

[Gaussian process regression and its application in near-infrared spectroscopy analysis].

PubMed

Feng, Ai-Ming; Fang, Li-Min; Lin, Min

2011-06-01

Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.

Optimal least-squares finite element method for elliptic problems

NASA Technical Reports Server (NTRS)

Jiang, Bo-Nan; Povinelli, Louis A.

1991-01-01

An optimal least squares finite element method is proposed for two dimensional and three dimensional elliptic problems and its advantages are discussed over the mixed Galerkin method and the usual least squares finite element method. In the usual least squares finite element method, the second order equation (-Delta x (Delta u) + u = f) is recast as a first order system (-Delta x p + u = f, Delta u - p = 0). The error analysis and numerical experiment show that, in this usual least squares finite element method, the rate of convergence for flux p is one order lower than optimal. In order to get an optimal least squares method, the irrotationality Delta x p = 0 should be included in the first order system.

Performance of the S - [chi][squared] Statistic for Full-Information Bifactor Models

ERIC Educational Resources Information Center

Li, Ying; Rupp, Andre A.

2011-01-01

This study investigated the Type I error rate and power of the multivariate extension of the S - [chi][squared] statistic using unidimensional and multidimensional item response theory (UIRT and MIRT, respectively) models as well as full-information bifactor (FI-bifactor) models through simulation. Manipulated factors included test length, sample…

F-Test Alternatives to Fisher's Exact Test and to the Chi-Square Test of Homogeneity in 2x2 Tables.

ERIC Educational Resources Information Center

Overall, John E.; Starbuck, Robert R.

1983-01-01

An alternative to Fisher's exact test and the chi-square test for homogeneity in two-by-two tables is developed. The method provides for Type I error rates which are closer to the stated alpha level than either of the alternatives. (JKS)

Multilevel Modeling and Ordinary Least Squares Regression: How Comparable Are They?

ERIC Educational Resources Information Center

Huang, Francis L.

2018-01-01

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

Discrete Tchebycheff orthonormal polynomials and applications

NASA Technical Reports Server (NTRS)

Lear, W. M.

1980-01-01

Discrete Tchebycheff orthonormal polynomials offer a convenient way to make least squares polynomial fits of uniformly spaced discrete data. Computer programs to do so are simple and fast, and appear to be less affected by computer roundoff error, for the higher order fits, than conventional least squares programs. They are useful for any application of polynomial least squares fits: approximation of mathematical functions, noise analysis of radar data, and real time smoothing of noisy data, to name a few.

Nondestructive evaluation of soluble solid content in strawberry by near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Guo, Zhiming; Huang, Wenqian; Chen, Liping; Wang, Xiu; Peng, Yankun

This paper indicates the feasibility to use near infrared (NIR) spectroscopy combined with synergy interval partial least squares (siPLS) algorithms as a rapid nondestructive method to estimate the soluble solid content (SSC) in strawberry. Spectral preprocessing methods were optimized selected by cross-validation in the model calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R2 c) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R2 p) in prediction set. The optimal siPLS model was obtained with after first derivation spectra preprocessing. The measurement results of best model were achieved as follow: RMSEC = 0.2259, R2 c = 0.9590 in the calibration set; and RMSEP = 0.2892, R2 p = 0.9390 in the prediction set. This work demonstrated that NIR spectroscopy and siPLS with efficient spectral preprocessing is a useful tool for nondestructively evaluation SSC in strawberry.

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Cognitive Assessment of Patients With Alzheimer's Disease by Telemedicine: Pilot Study.

PubMed

Carotenuto, Anna; Rea, Raffaele; Traini, Enea; Ricci, Giovanna; Fasanaro, Angiola Maria; Amenta, Francesco

2018-05-11

Approximately 46.8 million people are living with dementia worldwide and their number will grow in the next years. Any potential treatment should be administered as early as possible because it is important to provide an early cognitive assessment and to regularly monitor the mental function of patients. Information and communication technologies can be helpful to reach and follow patients without displacing them, but there may be doubts about the reliability of cognitive tests performed by telemedicine. The purpose of this study was to evaluate the reliability of the Mini Mental State Examination (MMSE) and the Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-cog) tests administered in hospital by videoconference to patients with mild to moderate Alzheimer's disease. The tests were administered to 28 Alzheimer's disease outpatients (8 male, mean age 73.88, SD 7.45 years; 20 female mean age 76.00, SD 5.40 years) recruited and followed in the Alzheimer's Unit of the A Cardarelli National Hospital (Naples, Italy) at baseline and after 6, 12, 18, and 24 months of observation. Patients were evaluated first face-to-face by a psychologist and then, after 2 weeks, by another psychologist via videoconference in hospital. This study showed no differences in the MMSE and ADAS-cog scores when the tests were administered face-to-face or by videoconference, except in patients with more pronounced cognitive deficits (MMSE<17), in which the assessment via videoconference overestimated the cognitive impairment (face to face, MMSE mean 13.9, SD 4.9 and ADAS-cog mean 9.0, SD 3.8; videoconference, MMSE mean 42.8, SD 12.5 and ADAS-cog mean 56.9, SD 5.5). We found that videoconferencing is a reliable approach to document cognitive stability or decline, and to measure treatment effects in patients with mild to moderate dementia. A more extended study is needed to confirm these results. ©Anna Carotenuto, Raffaele Rea, Enea Traini, Giovanna Ricci, Angiola Maria Fasanaro, Francesco Amenta. Originally published in JMIR Mental Health (http://mental.jmir.org), 11.05.2018.

Telomere Length, Long-Term Black Carbon Exposure, and Cognitive Function in a Cohort of Older Men: The VA Normative Aging Study.

PubMed

Colicino, Elena; Wilson, Ander; Frisardi, Maria Chiara; Prada, Diddier; Power, Melinda C; Hoxha, Mirjam; Dioni, Laura; Spiro, Avron; Vokonas, Pantel S; Weisskopf, Marc G; Schwartz, Joel D; Baccarelli, Andrea A

2017-01-01

Long-term air pollution exposure has been associated with age-related cognitive impairment, possibly because of enhanced inflammation. Leukocytes with longer telomere length (TL) are more responsive to inflammatory stimuli, yet TL has not been evaluated in relation to air pollution and cognition. We assessed whether TL modifies the association of 1-year exposure to black carbon (BC), a marker of traffic-related air pollution, with cognitive function in older men, and we examined whether this modification is independent of age and of C-reactive protein (CRP), a marker of inflammation. Between 1999 and 2007, we conducted 1-3 cognitive examinations of 428 older men in the Veterans Affairs (VA) Normative Aging Study. We used covariate-adjusted repeated-measure logistic regression to estimate associations of 1-year BC exposure with relative odds of being a low scorer (≤ 25) on the Mini-Mental State Examination (MMSE), which is a proxy of poor cognition. Confounders included age, CRP, and lifestyle and sociodemographic factors. Each doubling in BC level was associated with 1.57 (95% CI: 1.20, 2.05) times higher odds of low MMSE scores. The BC-MMSE association was greater only among individuals with longer blood TL (5th quintile) (OR = 3.23; 95% CI: 1.37, 7.59; p = 0.04 for BC-by-TL-interaction). TL and CRP were associated neither with each other nor with MMSE. However, CRP modified the BC-MMSE relationship, with stronger associations only at higher CRP (5th quintile) and reference TL level (1st quintile) (OR = 2.68; 95% CI: 1.06, 6.79; p = 0.04 for BC-by-CRP-interaction). TL and CRP levels may help predict the impact of BC exposure on cognitive function in older men. Citation: Colicino E, Wilson A, Frisardi MC, Prada D, Power MC, Hoxha M, Dioni L, Spiro A III, Vokonas PS, Weisskopf MG, Schwartz JD, Baccarelli AA. 2017. Telomere length, long-term black carbon exposure, and cognitive function in a cohort of older men: the VA Normative Aging Study. Environ Health Perspect 125:76-81; http://dx.doi.org/10.1289/EHP241.

Depression and dementia in Parkinson's disease.

PubMed

Sinanović, Osman; Hudić, Josip; Zukić, Sanela; Kapidžić, Almasa; Zonić, Lejla; Vidović, Mirjana

2015-03-01

Parkinson's disease (PD) is a neurodegenerative disorder causing not only motor dysfunction but also cognitive, psychiatric, autonomic and sensory disturbances. Depression is the most common psychiatric disturbance identified in patients with PD and has been shown to be more common in PD than in other chronic and disabling disorders, occurring in approximately 40% of PD patients. However, the prevalence and clinical features associated with depression in PD remain controversial. Dementia is increasingly recognized as a symptom associated with idiopathic PD, and is found in up to 40% of all patients suffering from that condition. The aim of this study was to estimate the prevalence of depressive and dementia symptoms in PD patients. The study included 35 consecutive patients with PD, 13 (37.4%) male and 22 (62.6%) female (mean age 62.9 ± 11.0, range 36-85 years), mean duration of disease 4.7 ± 2.9 (range 1-10) years, hospitalized during one year at Clinical Department of Neurology, Tuzla University Clinical Center, Tuzla, Bosnia and Herzegovina. The Mini Mental State Examination (MMSE) was used for assessment of cognitive deterioration and Beck Depression Inventory (BDI) for depression. Computerized tomography was performed in all patients. According to BDI scale, depressive symptoms were present in all 35 PD patients: minimal in 4 (11.4%), low in 7 (20%), moderate in 8 (22.8%), severe in 9 (25.4%) and extreme in 7 (20%) patients. On MMSE scale, 9 (25.4%) patients were free from cognitive deterioration and 26 (74.6%) patients had moderate to severe deterioration, but 21 (60%) patients (7 (33.33%) male and 14 (66.66%) female) had symptoms of dementia (MMSE score ≤ 23). Using MMSE scale, 8 (22.8%) patients were free from dementia and 27 (77.2%) patients had some cognitive deterioration. Very mild symptoms of dementia were found in 6 (25.9%) and overt features of dementia in 21 (74.1%) PD patients. So, out of 35 PD study patients, 21 (60%) (7 (33.3%) male and 14 (66.7%) female) had symptoms of dementia (MMSE score ≤ 23). In conclusion, depressive and dementia symptoms are common in PD patients.

Does cognitive/physical screening in an outpatient setting predict institutionalization after hip fracture?

PubMed

Hongisto, Markus T; Nuotio, Maria; Luukkaala, Tiina; Väistö, Olli; Pihlajamäki, Harri K

2016-10-22

Institutionalization after hip fracture is a socio-economical burden. We examined the predictive value of Instrumental Activities of Daily Living (IADL) and Mini Mental State Examination (MMSE) for institutionalization after hip fracture to identify patients at risk for institutionalization. Fragility hip fracture patients ≥65 years of age (n = 584) were comprehensively examined at a geriatric outpatient clinic 4 to 6 months after surgery and followed 1 year postoperatively. A telephone interview with a structured inquiry was performed at 1, 4, and 12 months after hip fracture. Age-adjusted univariate logistic regression analysis revealed that IADL and MMSE scores measured at the outpatient clinic were significantly associated with living arrangements 1 year after hip fracture. Multivariate logistic regression analysis established that institutionalization 1 year after hip fracture was significantly predicted by institutionalization at 4 months (odds ratio [OR] 16.26, 95 % confidence interval [CI] 7.37-35.86), IADL <5 (OR 12.96, 95 % CI 1.62-103.9), and MMSE <20 (OR 4.19, 95 % CI 1.82-9.66). A cut-off value of 5 was established for IADL with 100 % (95 % CI 96 %-100 %) sensitivity and 38 % (95 % CI 33 %-43 %) specificity and for MMSE, a cut-off value of 20 had 83 % (95 % CI 74 %-91 %) sensitivity and 65 % (95 % CI 60 %-70 %) specificity for institutionalization. During the time period from 4 to 12 months, 66 (11 %) patients changed living arrangements, and 36 (55 %) of these patients required more supportive accommodations. IADL and MMSE scores obtained 4 to 6 months after hospital discharge may be applicable for predicting institutionalization among fragility hip fracture patients ≥65 years of age at 1 year after hip fracture. An IADL score of ≥5 predicted the ability to remain in the community. Changes in living arrangements also often occur after 4 months.

[Relationship between status of physical and mental function and quality of life among the elderly people admitted from long-term care insurance].

PubMed

Kim, Hyeong Seon; Bae, Nam Kyou; Kwon, In Sun; Cho, Young Chae

2010-07-01

This study was performed to determine the levels of quality of life (QOL) according to the grade of long-term care service for the elderly people who were admitted from long-term care insurance, and to reveal its association with the physical and mental functioning such as the Activity of Daily Living (ADL), the Instrumental Activity of Daily Living (IADL), the Center for Epidemiologic Studies Depression Scale (CES-D), and the Mini-Mental State Examination-Korean version (MMSE-K). The interviews were performed during the period from March 1 to May 31, 2009, for 958 elderly people in urban and rural areas. The questionnaire items included various indices such as the ADL, IADL, CES-D, and MMSE-K, as independent variables and the index of QOL, as the dependent ones. For statistical analysis, t-tests were used for the mean scores of QOL according to gender and the grade of long-term care services, and Spearman's correlation was used for each variable. The effects of physical and mental functioning for QOL were assessed by covariance structure analysis. The statistical significance was set at p<0.05. The mean scores of QOL among all the subjects was 55.4 ± 15.62 (Grade I: 49.7 ± 14.17, Grade II: 56.8 ± 14.62, Grade III: 59.4 ± 16.36), and it was lower according to the higher grade of long-term care insurance. In terms of the correlation matrix of the QOL and the physical and mental function factors, the QOL showed positive correlation with the ADL, IADL and MMSE-K, while it had negative correlation with depression. On the analysis of covariance, mental functioning (depression and the MMSE-K) had a greater influence on the level of QOL than the physical functioning (ADL and IADL). The level of the QOL in the elderly people who were admitted from long-term care insurance was lower according to higher the grade of long-term care insurance. Also, the mental functioning (depression and MMSE-K) was more influential on the level of the QOL than the physical functioning (ADL and IADL).

Predictive factors for dementia and cognitive impairment among residents living in the veterans' retirement communities in Taiwan: Implications for cognitive health promotion activities.

PubMed

Chen, Liang-Yu; Wu, Yi-Hui; Huang, Chung-Yu; Liu, Li-Kuo; Hwang, An-Chun; Peng, Li-Ning; Lin, Ming-Hsieh; Chen, Liang-Kung

2017-04-01

To identify potentially modifiable risk factors for cognitive decline among veterans' home residents in Taiwan METHODS: The present retrospective cohort study was part of the Veteran Affairs-Comprehensive Geriatric Assessment study that retrieved data of the comprehensive geriatric assessment for 946 residents living at four veterans' homes in Taiwan. The study participants were interviewed every 3-6 months from January 2012 and December 2014. Demographic characteristics,multimorbidity by Charlson's Comorbidities Index, physical function by the Barthel Index, cognition by the Mini-Mental State Examination (MMSE), depression by the five-item Geriatric Depression Scale and nutritional status by the Mini-Nutrition Assessment-Short Form were collected for analysis. A generalized estimating equation model was used after it was adjusted for age, educational level, five-item Geriatric Depression Scale, and problem of communication difficulty to identify potential modifiable risk factors for cognitive decline. The mean age of the participants was 85.7 ± 5.2 years, with a mean follow-up period of 41 ± 21.6 weeks. The prevalence of cognitive impairment (defined by MMSE <24) was 65.6%, whereas 34% of the study participants were positive for depressive symptoms. Approximately one-fifth of the study participants were using psychotropic agents, which was higher among participants with cognitive impairment (23.6% vs 15.6%, P < 0.05) than those without. In the generalized estimating equation model, physical function, nutritional status, depressive symptoms, ex-drinker, multimorbidity and stool incontinence were positively correlated with MMSE score; whereas advanced age, low educational level (<6 years), presence of communication difficulty and use of psychotropic agents were inversely associated with the MMSE score. Physical function and nutritional status were positively associated with the MMSE score, and use of psychotropic agents was negatively correlated with cognitive function. Further intervention study is required to improve the cognitive health of older adults living in the veterans' retirement communities. Geriatr Gerontol Int 2017: 17 (Suppl. 1): 7-13. © 2017 Japan Geriatrics Society.

Determining the Uncertainty of X-Ray Absorption Measurements

PubMed Central

Wojcik, Gary S.

2004-01-01

X-ray absorption (or more properly, x-ray attenuation) techniques have been applied to study the moisture movement in and moisture content of materials like cement paste, mortar, and wood. An increase in the number of x-ray counts with time at a location in a specimen may indicate a decrease in moisture content. The uncertainty of measurements from an x-ray absorption system, which must be known to properly interpret the data, is often assumed to be the square root of the number of counts, as in a Poisson process. No detailed studies have heretofore been conducted to determine the uncertainty of x-ray absorption measurements or the effect of averaging data on the uncertainty. In this study, the Poisson estimate was found to adequately approximate normalized root mean square errors (a measure of uncertainty) of counts for point measurements and profile measurements of water specimens. The Poisson estimate, however, was not reliable in approximating the magnitude of the uncertainty when averaging data from paste and mortar specimens. Changes in uncertainty from differing averaging procedures were well-approximated by a Poisson process. The normalized root mean square errors decreased when the x-ray source intensity, integration time, collimator size, and number of scanning repetitions increased. Uncertainties in mean paste and mortar count profiles were kept below 2 % by averaging vertical profiles at horizontal spacings of 1 mm or larger with counts per point above 4000. Maximum normalized root mean square errors did not exceed 10 % in any of the tests conducted. PMID:27366627

Direct and simultaneous quantification of tannin mean degree of polymerization and percentage of galloylation in grape seeds using diffuse reflectance fourier transform-infrared spectroscopy.

PubMed

Pappas, Christos; Kyraleou, Maria; Voskidi, Eleni; Kotseridis, Yorgos; Taranilis, Petros A; Kallithraka, Stamatina

2015-02-01

The direct and simultaneous quantitative determination of the mean degree of polymerization (mDP) and the degree of galloylation (%G) in grape seeds were quantified using diffuse reflectance infrared Fourier transform spectroscopy and partial least squares (PLS). The results were compared with those obtained using the conventional analysis employing phloroglucinolysis as pretreatment followed by high performance liquid chromatography-UV and mass spectrometry detection. Infrared spectra were recorded in solid state samples after freeze drying. The 2nd derivative of the 1832 to 1416 and 918 to 739 cm(-1) spectral regions for the quantification of mDP, the 2nd derivative of the 1813 to 607 cm(-1) spectral region for the degree of %G determination and PLS regression were used. The determination coefficients (R(2) ) of mDP and %G were 0.99 and 0.98, respectively. The corresponding values of the root-mean-square error of calibration were found 0.506 and 0.692, the root-mean-square error of cross validation 0.811 and 0.921, and the root-mean-square error of prediction 0.612 and 0.801. The proposed method in comparison with the conventional method is simpler, less time consuming, more economical, and requires reduced quantities of chemical reagents and fewer sample pretreatment steps. It could be a starting point for the design of more specific models according to the requirements of the wineries. © 2015 Institute of Food Technologists®

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Local Linear Regression for Data with AR Errors.

PubMed

Li, Runze; Li, Yan

2009-07-01

In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques. We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one. From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.

A study of GPS measurement errors due to noise and multipath interference for CGADS

NASA Technical Reports Server (NTRS)

Axelrad, Penina; MacDoran, Peter F.; Comp, Christopher J.

1996-01-01

This report describes a study performed by the Colorado Center for Astrodynamics Research (CCAR) on GPS measurement errors in the Codeless GPS Attitude Determination System (CGADS) due to noise and multipath interference. Preliminary simulation models fo the CGADS receiver and orbital multipath are described. The standard FFT algorithms for processing the codeless data is described and two alternative algorithms - an auto-regressive/least squares (AR-LS) method, and a combined adaptive notch filter/least squares (ANF-ALS) method, are also presented. Effects of system noise, quantization, baseband frequency selection, and Doppler rates on the accuracy of phase estimates with each of the processing methods are shown. Typical electrical phase errors for the AR-LS method are 0.2 degrees, compared to 0.3 and 0.5 degrees for the FFT and ANF-ALS algorithms, respectively. Doppler rate was found to have the largest effect on the performance.

Linear regression in astronomy. II

NASA Technical Reports Server (NTRS)

Feigelson, Eric D.; Babu, Gutti J.

1992-01-01

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

Application of Adaptive Neuro-Fuzzy Inference System for Prediction of Neutron Yield of IR-IECF Facility in High Voltages

NASA Astrophysics Data System (ADS)

Adineh-Vand, A.; Torabi, M.; Roshani, G. H.; Taghipour, M.; Feghhi, S. A. H.; Rezaei, M.; Sadati, S. M.

2013-09-01

This paper presents a soft computing based artificial intelligent technique, adaptive neuro-fuzzy inference system (ANFIS) to predict the neutron production rate (NPR) of IR-IECF device in wide discharge current and voltage ranges. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the ANFIS model. The performance of the proposed ANFIS model is tested using the experimental data using four performance measures: correlation coefficient, mean absolute error, mean relative error percentage (MRE%) and root mean square error. The obtained results show that the proposed ANFIS model has achieved good agreement with the experimental results. In comparison to the experimental data the proposed ANFIS model has MRE% <1.53 and 2.85 % for training and testing data respectively. Therefore, this model can be used as an efficient tool to predict the NPR in the IR-IECF device.

Determinants of Quality of Life in the Acute Stage Following Stroke

PubMed Central

Jeong, Bo-Ok; Kang, Hee-Ju; Bae, Kyung-Yeol; Kim, Sung-Wan; Shin, Il-Seon; Kim, Joon-Tae; Park, Man-Seok; Cho, Ki-Hyun; Yoon, Jin-Sang

2012-01-01

Objective This study aimed to investigate the factors influence the quality of life (QOL) of survivors of an acute stroke. Methods For 422 stroke patients, assessments were made within two weeks of the index event. QOL was measured using the World Health Organization Quality of Life-Abbreviated form (WHOQOL-BREF), which has four domains related to physical factors, psychological factors, social relationships, and environmental context. Associations of each four WHOQOL-BREF domain score with socio-demographic characteristics (age, sex, education, marital status, religion, and occupation), stroke severity (National Institutes of Health Stroke Scale), physical disability (Barthel Index), cognitive function (Mini-Mental Status Examination: MMSE), grip strength, and psychological distress (Hospital Anxiety and Depression Scale depression and anxiety subscale: HADS-D and HADS-A) were investigated using the linear regression models. Results Higher physical domain scores were independently associated with higher MMSE scores, stronger hand-grip strength, and lower HADS-D and HADS-A scores; higher psychological domain scores were independently associated with higher educational level, higher MMSE scores, and lower HADS-D and HADS-A scores; higher social relationships domain scores were independently associated with lower HADS-D and HADS-A scores; and higher environmental domain scores were independently associated with higher educational level, higher MMSE scores, and lower HADS-D scores. Conclusion Psychological distress and impaired cognitive function were independently associated with lower QOL in patients with acute stroke. However, stroke severity, physical disability and other socio-demographic factors were less significantly associated with QOL. These findings underscore the importance of psychological interventions for improving QOL during the acute phase following stroke. PMID:22707962

Differential effects of enriched environment at work on cognitive decline in old age.

PubMed

Then, Francisca S; Luck, Tobias; Luppa, Melanie; König, Hans-Helmut; Angermeyer, Matthias C; Riedel-Heller, Steffi G

2015-05-26

The aim of the present study was to investigate how different mentally demanding work conditions during the professional life-i.e., enriched environments at work-might influence the rate of cognitive decline in old age. Individuals (n = 1,054) of the Leipzig Longitudinal Study of the Aged, a representative population-based cohort study of individuals aged 75 years and older, underwent cognitive testing via the Mini-Mental State Examination (MMSE) in up to 6 measurement waves. Type and level of mentally demanding work conditions in the participants' former professional life were classified based on the O*NET job descriptor database. In multivariate mixed-model analyses (controlling for sociodemographic and health-related factors), a high level of mentally demanding work tasks stimulating verbal intelligence was significantly associated with a better cognitive functioning at baseline (on average 5 MMSE points higher) as well as a lower rate of cognitive decline (on average 2 MMSE points less) over the 8-year follow-up period compared with a low level. The rate of cognitive decline in old age was also significantly lower (on average 3 MMSE points less) in individuals who had a high level of mentally demanding work tasks stimulating executive functions than those who had a low level. The results suggest that a professional life enriched with work tasks stimulating verbal intelligence and executive functions may help to sustain a good cognitive functioning in old age (75+ years). The findings thus emphasize that today's challenging work conditions may also promote positive health effects. © 2015 American Academy of Neurology.

Exploring the Role of Cognitive Factors in a New Instrument for Elders' Financial Capacity Assessment.

PubMed

Giannouli, Vaitsa; Stamovlasis, Dimitrios; Tsolaki, Magda

2018-01-01

The influence of cognitive factors on financial capacity across the dementia spectrum of cognitive aging, Alzheimer's disease (AD), and mild cognitive impairment (MCI) has been little investigated, while it has not been investigated at all in other types of dementia as well as in extended samples of elders in Greece. The aim of this study is to investigate financial capacity, to develop a tool, test its psychometric properties, validate, and then test the tool in groups of healthy controls compared to elders with dementia, while examining other facets of their cognitive performance. 719 elders from Greece including healthy participants and patients with different types of dementia were examined with Legal Capacity for Property Law Transactions Assessment Scale (LCPLTAS) and a battery of neuropsychological tests concerning various cognitive functions. Significantly different profiles in the scores and subscores of LCPLTAS for all the groups of dementia patients were found, with a general incapacity finding for all the dementia groups including the MCI patients. Logistic regression showed that Mini-Mental State Examination (MMSE), Geriatric Depression Scale, and Trail Making Part B predicted competence on LCPLTAS for the dementia patients. Persons with MCI and dementia had lower financial knowledge scores than those without cognitive impairment, with MMSE scores below 27 suggestive as an indication of financial incapacity. The LCPLTAS provides information for a strong positive correlation with MMSE, while the use both of MMSE and LCPLTAS as adequate measures of financial (in)capacity is discussed for the Greek legal procedures regarding elder guardianship cases.

Decision trees for the analysis of genes involved in Alzheimer's disease pathology.

PubMed

Mestizo Gutiérrez, Sonia L; Herrera Rivero, Marisol; Cruz Ramírez, Nicandro; Hernández, Elena; Aranda-Abreu, Gonzalo E

2014-09-21

Alzheimer's disease (AD) is characterized by a gradual loss of memory, orientation, judgement and language. There is still no cure for this disorder. AD pathogenesis remains fairly unknown and its underlying molecular mechanisms are not yet fully understood. Several studies have shown that the abnormal accumulation of beta-amyloid and tau proteins occurs 10 to 20 years before the onset of symptoms of the disease, so it is extremely important to identify changes in the brain before the first symptoms. We used decision trees to classify 31 individuals (9 healthy controls and 22 AD patients in three different stages of disease) according to the expression of 69 genes previously reported in a meta-analysis, plus the expression levels of APP, APOE, BACE1, NCSTN, PSEN1, PSEN2 and MAPT. We also included in our analysis the MMSE (Mini-Mental State Examination) scores and number of NFT (neurofibrillary tangles). Results allowed us to generate a model of classification values for different AD stages of severity, according to MMSE scores, and achieve the identification of the expression level of protein tau that may possibly determine the onset (incipient stage) of AD. We used decision trees to model the different stages of AD (severe, moderate, incipient and control) based on the meta-analysis of gene expression levels plus MMSE and NFT scores. Both classifiers reported the variable MMSE as most informative, however it we were found that the protein tau also an important role in the onset of AD. Copyright © 2014 Elsevier Ltd. All rights reserved.

Going outdoors and cognitive function among community-dwelling older adults: Moderating role of physical function.

PubMed

Harada, Kazuhiro; Lee, Sangyoon; Park, Hyuntae; Shimada, Hiroyuki; Makizako, Hyuma; Doi, Takehiko; Yoshida, Daisuke; Tsutsumimoto, Kota; Anan, Yuya; Uemura, Kazuki; Suzuki, Takao

2016-01-01

Identifying the risk factors of cognitive impairment is essential for implementing effective prevention strategies for dementia. Previous studies have shown that the frequency of going outdoors is inversely associated with cognitive decline. Little research has examined whether the relationship between going outdoors and cognitive decline varies with physical functioning in older adults. The aim of the present study was to examine the relationship between going outdoors and cognitive function in older adults with and without physical function limitations. The present study analyzed the data of 4450 individuals (aged 65 years or older) who participated in the Obu Study of Health Promotion for the Elderly. The measures were the Mini-Mental State Examination (MMSE), going outdoors (at least once a week or not), self-reported physical function limitations (with or without), and demographic and health-related factors as potential confounders. Analysis of covariance and post-hoc comparisons showed that although going outdoors at least once a week was associated with higher MMSE scores among older adults with limited physical function, it was not significantly associated with the MMSE scores among older adults without limited physical function. Similarly, logistic regression analyses, stratified by physical function, showed a significant association between going outdoors and MMSE (<24 points or not) among older adults with limited physical function. The results show that going outdoors less than once a week is associated with decreased cognitive function among older adults with limited physical function, but it is not associated with cognitive function among older adults without limited physical function. © 2015 Japan Geriatrics Society.

Carotid intima-media thickness and cognitive function in a middle-aged and older adult community: a cross-sectional study.

PubMed

Wang, Anxin; Chen, Guojuan; Su, Zhaoping; Liu, Xiaoxue; Yuan, Xiaodong; Jiang, Ruixuan; Cao, Yibin; Chen, Shuohua; Luo, Yanxia; Guo, Xiuhua; Wu, Shouling; Zhao, Xingquan

2016-10-01

The relationship between atherosclerosis and cognitive function is less well studied in Chinese populations. In addition, the results among middle-aged adults have been mixed. We aimed to investigate the association of atherosclerosis measured by carotid intima-media thickness (CIMT) and cognitive function in middle-aged and older adults from a Chinese community. Participants in the Asymptomatic Polyvascular Abnormalities in Community study (APAC) who had completed the CIMT detection and cognitive function measurements in 2012/2013 were included. Cognitive function was measured using the Mini-Mental State Examination (MMSE). Multivariate linear regression analysis was used to analyze the association between CIMT and MMSE. Then, a stratified analysis was performed separately in middle-aged and older adults. A total of 3227 participants were included in this study (mean age 57.9 years, range 43-93 years); 56.6 % of them were men, 66.0 % were middle-aged adults. After adjusting for potential confounders, larger CIMT was associated with lower MMSE scores, with a 0.75-point decrease in MMSE score for every 1-mm increase in CIMT (β = - 0.75, P = 0.0020). The association remained statistically significant in middle-aged adults (β = - 0.57, P = 0.0390), and was stronger in older adults and adults with low education levels. There is a significant association between CIMT and cognitive function among middle-aged and older adults sampled from a Chinese population. This association was stronger in older adults and adults with low education levels.

Correlation Between Vision and Cognitive Function in the Elderly

PubMed Central

Spierer, Oriel; Fischer, Naomi; Barak, Adiel; Belkin, Michael

2016-01-01

Abstract The correlation between vision and cognition is not fully understood. Visual impairment in the elderly has been associated with impaired cognitive function, dementia, and Alzheimer disease. The aim was to study the correlation between near visual acuity (VA), refraction, and cognitive state in an elderly population. Subjects ≥75 years were enrolled in this cross-sectional study. Refraction and near VA was tested. Cognitive function was evaluated with a version of the mini-mental state examination for the visually impaired (MMSE-blind). The eye with better VA and no cataract or refractive surgery was analyzed. One-hundred ninety subjects (81.6 ± 5.1 years, 69.5% female) were included. Good VA (≤J3) was associated with high MMSE-blind (>17) (OR = 3.18, 95% CI = 1.57–6.43, P = 0.001). This remained significant adjusting for sex, age, and years of education. Wearing reading glasses correlated significantly with high MMSE-blind after adjustment for sex and age (OR = 2.14, 95% CI = 1.16–3.97, P = 0.016), but reached borderline significance after adjustment for education. There was a trend toward correlation between myopia and better MMSE-blind (r = −0.123, P = 0.09, Pearson correlation). Good VA and wearing glasses seem to correlate with better cognitive function. Reading glasses can serve as a protective factor against cognitive deterioration associated with sensory (visual) deprivation in old age. The association between myopia and cognition requires further investigation. PMID:26817872

Walking stabilizes cognitive functioning in Alzheimer's disease (AD) across one year

PubMed Central

Winchester, J.; Dick, M.B.; Gillen, D.; Reed, B.; Miller, B.; Tinklenberg, J.; Mungas, D.; Chui, H.; Galasko, D.; Hewett, L.; Cotman, C.W.

2013-01-01

AD is a public health epidemic, which seriously impacts cognition, mood and daily activities; however, one type of activity, exercise, has been shown to alter these states. Accordingly, we sought to investigate the relationship between exercise and mood, in early-stage AD patients (N = 104) from California, over a 1-year period. Patients completed the Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Blessed-Roth Dementia Rating Scale (BRDRS), while their caregivers completed the Yale Physical Activity Survey (YALE), Profile of Mood States (POMS), the Neuropsychiatric Inventory (NPI) and Functional Abilities Questionnaire (FAQ). Approximately half of the participants were female, from a variety of ethnic groups (Caucasian = 69.8%; Latino/Hispanic Americans = 20.1%). Our results demonstrated that the patients spent little time engaged in physical activity in general, their overall activity levels decreased over time, and this was paired with a change in global cognition (e.g., MMSE total score) and affect/mood (e.g., POMS score). Patients were parsed into Active and Sedentary groups based on their Yale profiles, with Active participants engaged in walking activities, weekly, over 1 year. Here, Sedentary patients had a significant decline in MMSE scores, while the Active patients had an attenuation in global cognitive decline. Importantly, among the Active AD patients, those individuals who engaged in walking for more than 2 h/week had a significant improvement in MMSE scores. Structured clinical trials which seek to increase the amount of time AD patients were engaged in walking activities and evaluate the nature and scope of beneficial effects in the brain are warranted. PMID:22959822

Validation of the Sinhala version of the Repeatable Battery for Assessment of Neuropsychological Status (RBANS)

PubMed

Suraweera, Chathurie; Anandakumar, D; Dahanayake, D; Subendran, M; Perera, U T; Hanwella, Raveen; de Silva, Varuni

2016-12-30

Only the Mini mental state examination (MMSE) and Montreal Cognitive Assessment scale have been validated in a Sri Lankan population for the assessment of cognitive functions. Both tests are deficient in the number of domains assessed. Therefore validation of Repeatable Battery for Assessment of Neuropsychological Status is important as it assesses most of the cognitive domains. To culturally adapt RBANS and investigate the validity and reliability of culturally adapted RBANS (RBANS-S). Fifty four participants with major neurocognitive disorder and 60 normal controls aged >50 were administered with RBANS-S at the Cognitive Assessment Unit, Faculty of Medicine, Colombo and National Hospital of Sri Lanka. The participants were selected after a detailed clinical assessment according to Diagnostic and Statistical Manual – 5 criteria. Data were analysed using SPSS data package. The mean age of the sample was 69.5 years. RBANS-S total scale correlated highly with MMSE total score, (Pearson correlational coefficient = 0.793 p=0.01). Criterion validity was assessed using receiver operating curve characteristic analysis and the area under the curve was 0.937. RBANS-S showed strong concurrent validity us indicated by its significant correlations with the MMSE. All of the RBANS-S subtests demonstrated significant correlations with the MMSE subsets. The sensitivity and specificity for RBANS-S was 89% and 85% respectively at a totals score of 80.5. The RBANS-S yielded a reliability coefficient of 0.929. Culturally adapted RBANS-S is a valid and reliable instrument which can be used in assessment of cognitive functions.

Development and validation of a new cognitive screening test: The Hong Kong Brief Cognitive Test (HKBC).

PubMed

Chiu, Helen F K; Zhong, Bao-Liang; Leung, Tony; Li, S W; Chow, Paulina; Tsoh, Joshua; Yan, Connie; Xiang, Yu-Tao; Wong, Mike

2018-07-01

To develop and examine the validity of a new brief cognitive test with less educational bias for screening cognitive impairment. A new cognitive test, Hong Kong Brief Cognitive Test (HKBC), was developed based on review of the literature, as well as the views of an expert panel. Three groups of subjects aged 65 or above were recruited after written consent: normal older people recruited in elderly centres, people with mild NCD (neurocognitive disorder), and people with major NCD. The brief cognitive test, Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA), were administered to the subjects. The performance of HKBC in differentiating subjects with major NCD, mild NCD, and normal older people were compared with the clinical diagnosis, as well as the MMSE and MoCA scores. In total, 359 subjects were recruited, with 99 normal controls, 132 subjects with major NCD, and 128 with mild NCD. The mean MMSE, MoCA, and HKBC scores showed significant differences among the 3 groups of subjects. In the receiving operating characteristic curve analysis of the HKBC in differentiating normal subjects from those with cognitive impairment (mild NCD + major NCD), the area under the curve was 0.955 with an optimal cut-off score of 21/22. The performances of MMSE and MoCA in differentiating normal from cognitively impaired subjects are slightly inferior to the HKBC. The HKBC is a brief instrument useful for screening cognitive impairment in older adults and is also useful in populations with low educational level. Copyright © 2018 John Wiley & Sons, Ltd.

Depressive status explains a significant amount of the variance in COPD assessment test (CAT) scores

PubMed Central

Miravitlles, Marc; Molina, Jesús; Quintano, José Antonio; Campuzano, Anna; Pérez, Joselín; Roncero, Carlos

2018-01-01

Background COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. Methods This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). Results A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson’s coefficient r=−0.371) and the BDI (r=0.620), both p<0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. Conclusion CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables. PMID:29563782

Association between functional alterations of senescence and senility and disorders of gait and balance

PubMed Central

Teixeira-Leite, Homero; Manhães, Alex C.

2012-01-01

OBJECTIVES: Declines in cognition and mobility are frequently observed in the elderly, and it has been suggested that the appearance of gait disorders in older individuals may constitute a marker of cognitive decline that precedes significant findings in functional performance screening tests. This study sought to evaluate the relationship between functional capacities and gait and balance in an elderly community monitored by the Preventive and Integrated Care Unit of the Hospital Adventista Silvestre in Rio de Janeiro, RJ, Brazil. METHODS: Elderly individuals (193 females and 90 males) were submitted to a broad geriatric evaluation, which included the following tests: 1) a performance-oriented mobility assessment (POMA) to evaluate gait; 2) a mini-mental state examination (MMSE); 3) the use of Katz and Lawton scales to assess functional capacity; 4) the application of the geriatric depression scale (GDS); and 5) a mini-nutritional assessment (MNA) scale. RESULTS: Reductions in MMSE, Katz and Lawton scores were associated with reductions in POMA scores, and we also observed that significant reductions in POMA scores were present in persons for whom the MMSE and Katz scores did not clearly indicate cognitive dysfunction. We also demonstrated that a decline in the scores obtained with the GDS and MNA scales was associated with a decline in the POMA scores. CONCLUSIONS: Considering that significant alterations in the POMA scores were observed prior to the identification of significant alterations in cognitive capacity using either the MMSE or the Katz systems, a prospective study seems warranted to assess the predictive capacity of POMA scores regarding the associated decline in functional capacity. PMID:22892914

Association between functional alterations of senescence and senility and disorders of gait and balance.

PubMed

Teixeira-Leite, Homero; Manhães, Alex C

2012-07-01

Declines in cognition and mobility are frequently observed in the elderly, and it has been suggested that the appearance of gait disorders in older individuals may constitute a marker of cognitive decline that precedes significant findings in functional performance screening tests. This study sought to evaluate the relationship between functional capacities and gait and balance in an elderly community monitored by the Preventive and Integrated Care Unit of the Hospital Adventista Silvestre in Rio de Janeiro, RJ, Brazil. Elderly individuals (193 females and 90 males) were submitted to a broad geriatric evaluation, which included the following tests: 1) a performance-oriented mobility assessment (POMA) to evaluate gait; 2) a mini-mental state examination (MMSE); 3) the use of Katz and Lawton scales to assess functional capacity; 4) the application of the geriatric depression scale (GDS); and 5) a mini-nutritional assessment (MNA) scale. Reductions in MMSE, Katz and Lawton scores were associated with reductions in POMA scores, and we also observed that significant reductions in POMA scores were present in persons for whom the MMSE and Katz scores did not clearly indicate cognitive dysfunction. We also demonstrated that a decline in the scores obtained with the GDS and MNA scales was associated with a decline in the POMA scores. Considering that significant alterations in the POMA scores were observed prior to the identification of significant alterations in cognitive capacity using either the MMSE or the Katz systems, a prospective study seems warranted to assess the predictive capacity of POMA scores regarding the associated decline in functional capacity.

Efficacy of video-music therapy on quality of life improvement in a group of patients with Alzheimer's disease: a pre-post study.

PubMed

Rubbi, Ivan; Magnani, Daniela; Naldoni, Giada; Di Lorenzo, Rosaria; Cremonini, Valeria; Capucci, Patrizia; Artioli, Giovanna; Ferri, Paola

2016-11-22

Alzheimer's disease is the most common degenerative dementia with a predominantly senile onset. The difficult management of altered behaviour related to this disorder, poorly responsive to pharmacological treatments, has stimulated growth in non-pharmacological interventions, such as music therapy, whose effectiveness has not been supported by the literature up to now. The aim of this study was to evaluate the efficacy of video-music therapy on quality of life improvement in Patients affected by Alzheimer's Disease (AD). A pre-post study was conducted in a residential facility. 32 AD Patients, who attended this facility daily to participate in supportive and rehabilitative programs, were treated with 2 cycles of 6 video-music-therapy sessions, which consisted of folk music and video, recalling local traditions. In order to investigate their cognitive status, Mini Mental State Examination (MMSE) was administered and Patients were divided into stages according to MMSE scores. After each session of video-music-therapy, Quality of Life in Alzheimer's Disease Scale (QOL-AD) was administered to our Patients. 21 AD Patients completed the 2 cycles of video-music therapy. Among them, only the Patients with questionable, mild and moderate neurocognitive impairment (MMSE Stages 1, 2, 3) reported an improvement in their quality of life, whereas the Patients with severe deterioration (MMSE stage 4) did not report any change. Many items of QOL-AD improved, showing a statistically significantly correlation to each other. Video-music therapy was a valuable tool for improving the quality of life only in Patients affected by less severe neurocognitive impairment.

Is there information contained within the sentence-writing component of the mini mental state examination? A retrospective study of community dwelling older people.

PubMed

Shenkin, Susan D; Starr, John M; Dunn, Joanne M; Carter, Samantha; Deary, Ian J

2008-12-01

To investigate the relationship between features of the MMSE written sentence and cognitive function, depression and disability. MMSE sentences from 191 community dwelling individuals without dementia from the Lothian Birth Cohort 1921 (LBC1921) study were: (a) photocopied and (b) typed as written. Sentences were rated for objective criteria: word number and frequency, first person usage, time orientation, and letter case. Twenty healthy raters (50% male, age 20-26 years), blind to all other data, rated each handwritten and typed sentence for subjective criteria: legibility, 'emotional' tone (positive to negative), estimated age, health, and intelligence. As part of the LBC1921 volunteers had results available for cognitive ability tests (from which we extracted a general cognitive ability factor, g), Hospital Anxiety and Depression Score (HADS), and Townsend disability scores. 43.5% of subjects were male, mean age 78.6, SD 0.43 years. There was no significant association between the objective sentence criteria, legibility or tone and measured cognitive ability or physical disability. However, estimates of intelligence from the MMSE written sentence correlated significantly with current cognitive ability (r = 0.29, p < 0.001). There was a trend towards sentences with a negative tone being associated with a higher HADS-depression score (rho = -0.12, p = 0.09). In community dwelling people aged around 80 years, despite no association between objectively rated features of the MMSE sentence and intelligence or disability, raters were able to make better-than-chance estimates of subjects' intelligence test scores. (c) 2008 John Wiley & Sons, Ltd.

Mental status testing in the elderly nursing home population.

PubMed

Nadler, J D; Relkin, N R; Cohen, M S; Hodder, R A; Reingold, J; Plum, F

1995-07-01

The clinical utility of selected brief cognitive screening instruments in detecting dementia in an elderly nursing home population was examined. One hundred twenty nursing home residents (mean age 87.9) were administered the Mini-Mental State Exam (MMSE) and the Modified Mini-Mental State Exam (3MS). The majority of the subjects (75%) were also administered the Dementia Rating Scale (DRS). Both clinically diagnosed demented (n = 57) and non-demented (n = 63) subjects participated in the study. Dementia was diagnosed in accordance with DSM-III-R criteria by physicians specializing in geriatric medicine. Using standard cutoffs for impairment, the 3MS, MMSE, and DRS achieved high sensitivity (82% to 100%) but low specificity (33% to 52%) in the detection of dementia among nursing home residents. Positive predictive values ranged from 52% to 61%, and negative predictive values from 77% to 100%. Higher age, lower education, and history of depression were significantly associated with misclassification of non-demented elderly subjects. Receiver Operating Characteristic (ROC) curve analyses revealed optimal classification of dementia with cutoff values of 74 for the 3MS, 22 for the MMSE, and 110 for the DRS. The results suggest that the 3MS, MMSE, and DRS do not differ significantly with respect to classification accuracy of dementia in a nursing home population. Elderly individuals of advanced age (i.e., the oldest-old) with lower education and a history of depression appear at particular risk for dementia misclassification with these instruments. Revised cutoff values for impairment should be employed when these instruments are applied to elderly residents of nursing homes and the oldest-old.

Mild cognitive impairment in symptomatic and asymptomatic cerebrovascular disease.

PubMed

Popović, Irena Martinić; Serić, Vesna; Demarin, Vida

2007-06-15

We tried to evaluate and to compare usefulness of two brief cognitive tests in early detection of cognitive decline in subjects with increased cerebrovascular (CV) risk. As CV risk factors are recognised as important in etiology of dementia, we also aimed to determine the possible associations of specific CV risk factors and cognitive results. Patients (PGs) with first-ever stroke or TIA (N=110) and CV symptoms-free controls (CGs) with CV risk factors present (N=45) matched for age, gender and education level were tested using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) on admission, at three- and six-month points. In all subjects, detailed CV risk factors profile was assessed. We observed the decrement in cognitive performance during the six-month study period in both groups, more evident if MoCA (p<0.001) than if MMSE was used (p=0.022). Six months after first stroke/TIA 83.6% PGs scored below normal range on MoCA. In PGs, positive associations for cognitive decrement and multiple CV risk factors (>2) were found (p=0.034 for MMSE; p=0.002 for MoCA). In CGs, positive associations were found for cognitive decrement and arterial hypertension with increased IMT values (p<0.001 for MMSE) and for multiple CV risk factors and arterial hypertension (p=0.003 for MoCA). The use of MoCA could aid to early recognition of cognitive deficits in persons with increased CV risk. Individuals with multiple CV risk factors seem to have increased risk of cognitive decline.

Effects of nutritional status and cognitive ability on olfactory function in geriatric patients.

PubMed

Jin, Sung-Yong; Jeong, Hye Seon; Lee, Jin Woo; Kwon, Ki Ryun; Rha, Ki-Sang; Kim, Yong Min

2016-02-01

The aim of this study was to investigate the prevalence of olfactory dysfunction and evaluate the relationship between olfactory function and nutritional status, comorbidity, and the results of a neurocognitive test in geriatric patients who do not suffer from neurodegenerative disease. A total of 45 patients who visited the Geriatric Health Center of Chungnam National University Hospital were enrolled in this study. Olfactory function was assessed using a Korean Version of Sniffin' Stick Test II. Cognitive status of all participants was assessed with the MMSE-K (Korean version of the Mini-Mental State Examination). Nutritional status was assessed with body mass index, Mini-Nutritional Assessment (MNA), and serum total protein and albumin. A total of 45 participants were enrolled in this study. Of these subjects, 28 were men and 17 were women, with a mean age of 71.7±5.16 years. Nine (20%) were normosmia, 13 (28.9%) were hyposmia, and 23 (51.1%) were anosmia. Thirty-six patients (80%) suffered from olfactory dysfunction (anosmia or hyposmia). MMSE score showed significant correlation with MNA score. There were significant negative correlations between age and total TDI (threshold, discrimination, and identification) score, discrimination score, identification score, and MMSE score. MMSE score showed significant correlation with discrimination score and identification score. However, MNA score did not show any significant correlation with olfactory function test results. Although olfactory function was not influenced by nutritional status, abilities of discrimination and identification of odors were associated with cognitive function in geriatric patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Depressive status explains a significant amount of the variance in COPD assessment test (CAT) scores.

PubMed

Miravitlles, Marc; Molina, Jesús; Quintano, José Antonio; Campuzano, Anna; Pérez, Joselín; Roncero, Carlos

2018-01-01

COPD assessment test (CAT) is a short, easy-to-complete health status tool that has been incorporated into the multidimensional assessment of COPD in order to guide therapy; therefore, it is important to understand the factors determining CAT scores. This is a post hoc analysis of a cross-sectional, observational study conducted in respiratory medicine departments and primary care centers in Spain with the aim of identifying the factors determining CAT scores, focusing particularly on the cognitive status measured by the Mini-Mental State Examination (MMSE) and levels of depression measured by the short Beck Depression Inventory (BDI). A total of 684 COPD patients were analyzed; 84.1% were men, the mean age of patients was 68.7 years, and the mean forced expiratory volume in 1 second (%) was 55.1%. Mean CAT score was 21.8. CAT scores correlated with the MMSE score (Pearson's coefficient r =-0.371) and the BDI ( r =0.620), both p <0.001. In the multivariate analysis, the usual COPD severity variables (age, dyspnea, lung function, and comorbidity) together with MMSE and BDI scores were significantly associated with CAT scores and explained 45% of the variability. However, a model including only MMSE and BDI scores explained up to 40% and BDI alone explained 38% of the CAT variance. CAT scores are associated with clinical variables of severity of COPD. However, cognitive status and, in particular, the level of depression explain a larger percentage of the variance in the CAT scores than the usual COPD clinical severity variables.

Spectrophotometric determination of ternary mixtures of thiamin, riboflavin and pyridoxal in pharmaceutical and human plasma by least-squares support vector machines.

PubMed

Niazi, Ali; Zolgharnein, Javad; Afiuni-Zadeh, Somaie

2007-11-01

Ternary mixtures of thiamin, riboflavin and pyridoxal have been simultaneously determined in synthetic and real samples by applications of spectrophotometric and least-squares support vector machines. The calibration graphs were linear in the ranges of 1.0 - 20.0, 1.0 - 10.0 and 1.0 - 20.0 microg ml(-1) with detection limits of 0.6, 0.5 and 0.7 microg ml(-1) for thiamin, riboflavin and pyridoxal, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graph concentrations of vitamins. The simultaneous determination of these vitamin mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares (PLS) modeling and least-squares support vector machines were used for the multivariate calibration of the spectrophotometric data. An excellent model was built using LS-SVM, with low prediction errors and superior performance in relation to PLS. The root mean square errors of prediction (RMSEP) for thiamin, riboflavin and pyridoxal with PLS and LS-SVM were 0.6926, 0.3755, 0.4322 and 0.0421, 0.0318, 0.0457, respectively. The proposed method was satisfactorily applied to the rapid simultaneous determination of thiamin, riboflavin and pyridoxal in commercial pharmaceutical preparations and human plasma samples.

Modeling error analysis of stationary linear discrete-time filters

NASA Technical Reports Server (NTRS)

Patel, R.; Toda, M.

1977-01-01

The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal and optimal (Kalman) filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a design can easily compare the performance of a suboptimal filter with that of the optimal filter, when only the range of errors in the elements of the model matrices is available.

An error analysis of least-squares finite element method of velocity-pressure-vorticity formulation for Stokes problem

NASA Technical Reports Server (NTRS)

Chang, Ching L.; Jiang, Bo-Nan

1990-01-01

A theoretical proof of the optimal rate of convergence for the least-squares method is developed for the Stokes problem based on the velocity-pressure-vorticity formula. The 2D Stokes problem is analyzed to define the product space and its inner product, and the a priori estimates are derived to give the finite-element approximation. The least-squares method is found to converge at the optimal rate for equal-order interpolation.

The Modified Telephone Interview for Cognitive Status is More Predictive of Memory Abilities Than the Mini-Mental State Examination.

PubMed

Duff, Kevin; Tometich, Danielle; Dennett, Kathryn

2015-09-01

Although not as popular as the Mini-Mental State Examination (MMSE), the modified Telephone Interview for Cognitive Status (mTICS) has some distinct advantages when screening cognitive functioning in older adults. The current study compared these 2 cognitive screening measures in their ability to predict performance on a memory composite (ie, delayed recall of verbal and visual information) in a cohort of 121 community-dwelling older adults, both at baseline and after 1 year. Both the MMSE and the mTICS significantly correlated with the memory composite at baseline (r's of .41 and .62, respectively) and at 1 year (r's of .36 and .50, respectively). At baseline, stepwise linear regression indicated that the mTICS and gender best predicted the memory composite score (R (2) = .45, P < .001), and the MMSE and other demographic variables did not significantly improve the prediction. At 1 year, the results were very similar. Despite its lesser popularity, the mTICS may be a more attractive option when screening for cognitive abilities in this age range. © The Author(s) 2015.

On the optimum signal constellation design for high-speed optical transport networks.

PubMed

Liu, Tao; Djordjevic, Ivan B

2012-08-27

In this paper, we first describe an optimum signal constellation design algorithm, which is optimum in MMSE-sense, called MMSE-OSCD, for channel capacity achieving source distribution. Secondly, we introduce a feedback channel capacity inspired optimum signal constellation design (FCC-OSCD) to further improve the performance of MMSE-OSCD, inspired by the fact that feedback channel capacity is higher than that of systems without feedback. The constellations obtained by FCC-OSCD are, however, OSNR dependent. The optimization is jointly performed together with regular quasi-cyclic low-density parity-check (LDPC) code design. Such obtained coded-modulation scheme, in combination with polarization-multiplexing, is suitable as both 400 Gb/s and multi-Tb/s optical transport enabling technology. Using large girth LDPC code, we demonstrate by Monte Carlo simulations that a 32-ary signal constellation, obtained by FCC-OSCD, outperforms previously proposed optimized 32-ary CIPQ signal constellation by 0.8 dB at BER of 10(-7). On the other hand, the LDPC-coded 16-ary FCC-OSCD outperforms 16-QAM by 1.15 dB at the same BER.

Cognitive cooperation groups mediated by computers and internet present significant improvement of cognitive status in older adults with memory complaints: a controlled prospective study.

PubMed

Krug, Rodrigo de Rosso; Silva, Anna Quialheiro Abreu da; Schneider, Ione Jayce Ceola; Ramos, Luiz Roberto; d'Orsi, Eleonora; Xavier, André Junqueira

2017-04-01

To estimate the effect of participating in cognitive cooperation groups, mediated by computers and the internet, on the Mini-Mental State Examination (MMSE) percent variation of outpatients with memory complaints attending two memory clinics. A prospective controlled intervention study carried out from 2006 to 2013 with 293 elders. The intervention group (n = 160) attended a cognitive cooperation group (20 sessions of 1.5 hours each). The control group (n = 133) received routine medical care. Outcome was the percent variation in the MMSE. Control variables included gender, age, marital status, schooling, hypertension, diabetes, dyslipidaemia, hypothyroidism, depression, vascular diseases, polymedication, use of benzodiazepines, exposure to tobacco, sedentary lifestyle, obesity and functional capacity. The final model was obtained by multivariate linear regression. The intervention group obtained an independent positive variation of 24.39% (CI 95% = 14.86/33.91) in the MMSE compared to the control group. The results suggested that cognitive cooperation groups, mediated by computers and the internet, are associated with cognitive status improvement of older adults in memory clinics.

Gender, Resources Across the Life Course, and Cognitive Functioning in Egypt

PubMed Central

YOUNT, KATHRYN M.

2008-01-01

In this article, I evaluate the life-course determinants of cognitive functioning among 1,003 women and men aged 50 and older in Ismailia, Egypt. Three questions motivate this analysis: (1) Do older women have poorer cognitive functioning than do older men?; (2) Do cognitive resources accrued in childhood and adulthood have net positive associations with later-life cognitive functioning for women and men?; and (3) To what extent do differences in the amounts and effects of women’s and men’s cognitive resources account for gaps in their cognitive functioning? Compared with men, women have lower Modified-Mini Mental Status Exam (M-MMSE) scores for overall cognitive functioning. Cognitive resources in childhood and adulthood are jointly associated with the M-MMSE score. About 83% of the gender gap in mean M-MMSE scores is attributable to gaps in men’s and women’s attributes across the life course. Gender gaps in childhood cognitive resources—and especially schooling attainment—account for the largest share (18%) of the residual gender gap in cognitive functioning. PMID:19110904

Cognitive impairment in patients with Fibromyalgia syndrome as assessed by the Mini-Mental State Examination

PubMed Central

2009-01-01

Background This study evaluated the frequency of cognitive impairment in patients with Fibromyalgia syndrome (FMS) using the Mini Mental State Examination (MMSE). Methods We analyzed baseline data from all 46 patients with FMS and 92 age- and sex-matched controls per diagnosis of neuropathic (NeP) or mixed pain (MP) selected from a larger prospective study. Results FMS had a slight but statistically significant lower score in the adjusted MMSE score (26.9; 95% CI 26.7-27.1) than either NeP (27.3; 95% CI 27.2-27.4) or MP (27.3; 27.2-27.5). The percentage of patients with congnitive impairment (adjusted MMSE ≤ 26) was numerically higher in FMS (15%; 95% CI 6.3-29) compared with NeP (5%; 95% CI 1.8-12.2) or MP (5%; 95% CI 1.8-12.2) and higher than in the same age stratum of the general population (0.05%). Conclusions Compared with the population reference value, patients with FMS showed high frequency of cognitive impairment. PMID:20025750

Cultural adaptation, standardization and clinical validity of the test your memory dementia screening instrument in Greek.

PubMed

Iatraki, Eliza; Simos, Panagiotis G; Lionis, Christos; Zaganas, Ioannis; Symvoulakis, Emmanouil K; Papastefanakis, Emmanouil; Panagiotakis, Simeon; Pantelidakis, Heraklis; Papadopoulos, Konstantinos; Tziraki, Chariklia

2014-01-01

To adapt and standardize the Test Your Memory (TYM) dementia screening instrument in Greek. Normative data on the Greek version of the TYM were obtained from a community sample of 239 adults aged 21-92 years. Clinical validity was assessed in a cohort of 134 Neurology Clinic patients. Concurrent validity was examined through comparisons with the Mini-Mental State Examination (MMSE) and the Greek Everyday Function Scale. Correlations between the TYM and the MMSE were 0.73 and 0.82 in the community and patient samples, respectively. Scores on both tests were moderately associated with everyday functional capacity. Using age- and education-corrected cutoff scores ranging from 26/50 to 45/50 points, the sensitivity of the TYM for Alzheimer's disease detection was found to be higher than that of the MMSE (0.82 vs. 0.70), although its specificity was lower (0.71 vs. 0.90). Findings are consistent with previous reports in a variety of cultural settings supporting the potential utility of the TYM as a dementia screening tool.

An observational clinical study of the efficacy and tolerability of donepezil in the treatment of Alzheimer's disease.

PubMed

Hager, Klaus; Calabrese, Pasquale; Frölich, Lutz; Göbel, Claus; Berger, Frank M

2003-01-01

An open-label, observational Post-Marketing Surveillance (PMS) study was undertaken in Germany to examine the efficacy and tolerability of donepezil in routine clinical practice. Alzheimer's disease (AD) patients were treated with donepezil (5 or 10 mg once daily) and observed for a period of approximately 3 months. Study assessments included the Mini-Mental State Examination (MMSE), the Nurses' Observation Scale for Geriatric Patients (NOSGER), and adverse events (AEs). A total of 2,092 patients (mean age 73.0 years; mean +/- SD MMSE score 17.8 +/- 5.8) were included in the efficacy assessments. MMSE and NOSGER scores showed statistically significant improvements in the total patient population and in the subpopulations with severe AD or AD with concomitant Parkinsonian symptoms (ADPS cohort). AEs were reported in a total of 12% of patients and were mostly due to peripheral cholinergic effects. In this observational PMS study, donepezil was shown to be an effective and well-tolerated therapy in the overall patient population, in patients with severe AD, and in the ADPS cohort. Copyright 2003 S. Karger AG, Basel

Memantine in the prevention or alleviation of electroconvulsive therapy induces cognitive disorders: A placebo controlled trial.

PubMed

Abbasinazari, Mohammad; Adib-Eshgh, Ladan; Rostami, Azin; Beyraghi, Narges; Dabir, Shideh; Jafari, Reyhaneh

2015-06-01

The purpose of this study was to evaluate the effect of memantine administration on the adverse cognitive effects of electroconvulsive therapy (ECT). Forty patients diagnosed with a major depressive disorder for which ECT was indicated as a treatment for their current episode were randomly allocated to either the memantine (5mg/day) group or the placebo group. All patients underwent the same protocol for anaesthesia and ECT procedures. The patients received memantine or the placebo for the whole period of ECT treatment, starting the day before ECT and continuing until the fourth session of ECT. The Modified Mental State Examination (MMSE) was used for the assessment of cognition before and after the trial. Regarding MMSE and item 3 MMSE (related to recent memory), the memantine group scored significantly higher at the end of ECT sessions than the control group (P=0.02, P<0.001, respectively). Our data support the hypothesis that memantine may reduce cognitive impairment following ECT. Memantine could be both a safe and well-tolerated treatment for use with ECT. Copyright © 2015 Elsevier B.V. All rights reserved.

Coupling finite element and spectral methods: First results

NASA Technical Reports Server (NTRS)

Bernardi, Christine; Debit, Naima; Maday, Yvon

1987-01-01

A Poisson equation on a rectangular domain is solved by coupling two methods: the domain is divided in two squares, a finite element approximation is used on the first square and a spectral discretization is used on the second one. Two kinds of matching conditions on the interface are presented and compared. In both cases, error estimates are proved.

Building on crossvalidation for increasing the quality of geostatistical modeling

USGS Publications Warehouse

Olea, R.A.

2012-01-01

The random function is a mathematical model commonly used in the assessment of uncertainty associated with a spatially correlated attribute that has been partially sampled. There are multiple algorithms for modeling such random functions, all sharing the requirement of specifying various parameters that have critical influence on the results. The importance of finding ways to compare the methods and setting parameters to obtain results that better model uncertainty has increased as these algorithms have grown in number and complexity. Crossvalidation has been used in spatial statistics, mostly in kriging, for the analysis of mean square errors. An appeal of this approach is its ability to work with the same empirical sample available for running the algorithms. This paper goes beyond checking estimates by formulating a function sensitive to conditional bias. Under ideal conditions, such function turns into a straight line, which can be used as a reference for preparing measures of performance. Applied to kriging, deviations from the ideal line provide sensitivity to the semivariogram lacking in crossvalidation of kriging errors and are more sensitive to conditional bias than analyses of errors. In terms of stochastic simulation, in addition to finding better parameters, the deviations allow comparison of the realizations resulting from the applications of different methods. Examples show improvements of about 30% in the deviations and approximately 10% in the square root of mean square errors between reasonable starting modelling and the solutions according to the new criteria. ?? 2011 US Government.

Analysis of Students' Error in Learning of Quadratic Equations

ERIC Educational Resources Information Center

Zakaria, Effandi; Ibrahim; Maat, Siti Mistima

2010-01-01

The purpose of the study was to determine the students' error in learning quadratic equation. The samples were 30 form three students from a secondary school in Jambi, Indonesia. Diagnostic test was used as the instrument of this study that included three components: factorization, completing the square and quadratic formula. Diagnostic interview…

Nonparametric probability density estimation by optimization theoretic techniques

NASA Technical Reports Server (NTRS)

Scott, D. W.

1976-01-01

Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.

Discrete-time state estimation for stochastic polynomial systems over polynomial observations

NASA Astrophysics Data System (ADS)

Hernandez-Gonzalez, M.; Basin, M.; Stepanov, O.

2018-07-01

This paper presents a solution to the mean-square state estimation problem for stochastic nonlinear polynomial systems over polynomial observations confused with additive white Gaussian noises. The solution is given in two steps: (a) computing the time-update equations and (b) computing the measurement-update equations for the state estimate and error covariance matrix. A closed form of this filter is obtained by expressing conditional expectations of polynomial terms as functions of the state estimate and error covariance. As a particular case, the mean-square filtering equations are derived for a third-degree polynomial system with second-degree polynomial measurements. Numerical simulations show effectiveness of the proposed filter compared to the extended Kalman filter.

Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

PubMed

Wang, Rong

2015-01-01

In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

Cortical dipole imaging using truncated total least squares considering transfer matrix error.

PubMed

Hori, Junichi; Takeuchi, Kosuke

2013-01-01

Cortical dipole imaging has been proposed as a method to visualize electroencephalogram in high spatial resolution. We investigated the inverse technique of cortical dipole imaging using a truncated total least squares (TTLS). The TTLS is a regularization technique to reduce the influence from both the measurement noise and the transfer matrix error caused by the head model distortion. The estimation of the regularization parameter was also investigated based on L-curve. The computer simulation suggested that the estimation accuracy was improved by the TTLS compared with Tikhonov regularization. The proposed method was applied to human experimental data of visual evoked potentials. We confirmed the TTLS provided the high spatial resolution of cortical dipole imaging.

Development and effect of a cognitive enhancement gymnastics program for elderly people with dementia

PubMed Central

Han, Yoon-Soo; Araki, Tatsuo; Lee, Pil-Young; Choi, Jung-Hyun; Kwon, In-Seon; Kwon, Ki-Nam; Kim, Ji-Youn

2016-01-01

The purpose of this study was to develop a cognitive enhancement gymnastics program for the elderly with dementia and to verify its effect. The study was conducted on 27 people with dementia being treated in a dementia day care center in Incheon city. No statistically significant differences were found in the measures Mini-Mental State Examination for Dementia Screening (MMSE-DS), Short Geriatric Depression Scale (SGDS), Seoul Activities of Daily Living (S-ADL), or rock-paper-scissors. However, the MMSE-DS and rock-paper-scissors showed improvement after 12 weeks. PMID:27656632

Spectral combination of spherical gravitational curvature boundary-value problems

NASA Astrophysics Data System (ADS)

PitoÅák, Martin; Eshagh, Mehdi; Šprlák, Michal; Tenzer, Robert; Novák, Pavel

2018-04-01

Four solutions of the spherical gravitational curvature boundary-value problems can be exploited for the determination of the Earth's gravitational potential. In this article we discuss the combination of simulated satellite gravitational curvatures, i.e., components of the third-order gravitational tensor, by merging these solutions using the spectral combination method. For this purpose, integral estimators of biased- and unbiased-types are derived. In numerical studies, we investigate the performance of the developed mathematical models for the gravitational field modelling in the area of Central Europe based on simulated satellite measurements. Firstly, we verify the correctness of the integral estimators for the spectral downward continuation by a closed-loop test. Estimated errors of the combined solution are about eight orders smaller than those from the individual solutions. Secondly, we perform a numerical experiment by considering the Gaussian noise with the standard deviation of 6.5× 10-17 m-1s-2 in the input data at the satellite altitude of 250 km above the mean Earth sphere. This value of standard deviation is equivalent to a signal-to-noise ratio of 10. Superior results with respect to the global geopotential model TIM-r5 are obtained by the spectral downward continuation of the vertical-vertical-vertical component with the standard deviation of 2.104 m2s-2, but the root mean square error is the largest and reaches 9.734 m2s-2. Using the spectral combination of all gravitational curvatures the root mean square error is more than 400 times smaller but the standard deviation reaches 17.234 m2s-2. The combination of more components decreases the root mean square error of the corresponding solutions while the standard deviations of the combined solutions do not improve as compared to the solution from the vertical-vertical-vertical component. The presented method represents a weight mean in the spectral domain that minimizes the root mean square error of the combined solutions and improves standard deviation of the solution based only on the least accurate components.

Distribution of kriging errors, the implications and how to communicate them

NASA Astrophysics Data System (ADS)

Li, Hong Yi; Milne, Alice; Webster, Richard

2016-04-01

Kriging in one form or another has become perhaps the most popular method for spatial prediction in environmental science. Each prediction is unbiased and of minimum variance, which itself is estimated. The kriging variances depend on the mathematical model chosen to describe the spatial variation; different models, however plausible, give rise to different minimized variances. Practitioners often compare models by so-called cross-validation before finally choosing the most appropriate for their kriging. One proceeds as follows. One removes a unit (a sampling point) from the whole set, kriges the value there and compares the kriged value with the value observed to obtain the deviation or error. One repeats the process for each and every point in turn and for all plausible models. One then computes the mean errors (MEs) and the mean of the squared errors (MSEs). Ideally a squared error should equal the corresponding kriging variance (σK2), and so one is advised to choose the model for which on average the squared errors most nearly equal the kriging variances, i.e. the ratio MSDR = MSE/σK2 ≈ 1. Maximum likelihood estimation of models almost guarantees that the MSDR equals 1, and so the kriging variances are unbiased predictors of the squared error across the region. The method is based on the assumption that the errors have a normal distribution. The squared deviation ratio (SDR) should therefore be distributed as χ2 with one degree of freedom with a median of 0.455. We have found that often the median of the SDR (MedSDR) is less, in some instances much less, than 0.455 even though the mean of the SDR is close to 1. It seems that in these cases the distributions of the errors are leptokurtic, i.e. they have an excess of predictions close to the true values, excesses near the extremes and a dearth of predictions in between. In these cases the kriging variances are poor measures of the uncertainty at individual sites. The uncertainty is typically under-estimated for the extreme observations and compensated for by over estimating for other observations. Statisticians must tell users when they present maps of predictions. We illustrate the situation with results from mapping salinity in land reclaimed from the Yangtze delta in the Gulf of Hangzhou, China. There the apparent electrical conductivity (ECa) of the topsoil was measured at 525 points in a field of 2.3 ha. The marginal distribution of the observations was strongly positively skewed, and so the observed ECas were transformed to their logarithms to give an approximately symmetric distribution. That distribution was strongly platykurtic with short tails and no evident outliers. The logarithms were analysed as a mixed model of quadratic drift plus correlated random residuals with a spherical variogram. The kriged predictions that deviated from their true values with an MSDR of 0.993, but with a medSDR=0.324. The coefficient of kurtosis of the deviations was 1.45, i.e. substantially larger than 0 for a normal distribution. The reasons for this behaviour are being sought. The most likely explanation is that there are spatial outliers, i.e. points at which the observed values that differ markedly from those at their their closest neighbours.

Distribution of kriging errors, the implications and how to communicate them

NASA Astrophysics Data System (ADS)

Li, HongYi; Milne, Alice; Webster, Richard

2015-04-01

Kriging in one form or another has become perhaps the most popular method for spatial prediction in environmental science. Each prediction is unbiased and of minimum variance, which itself is estimated. The kriging variances depend on the mathematical model chosen to describe the spatial variation; different models, however plausible, give rise to different minimized variances. Practitioners often compare models by so-called cross-validation before finally choosing the most appropriate for their kriging. One proceeds as follows. One removes a unit (a sampling point) from the whole set, kriges the value there and compares the kriged value with the value observed to obtain the deviation or error. One repeats the process for each and every point in turn and for all plausible models. One then computes the mean errors (MEs) and the mean of the squared errors (MSEs). Ideally a squared error should equal the corresponding kriging variance (σ_K^2), and so one is advised to choose the model for which on average the squared errors most nearly equal the kriging variances, i.e. the ratio MSDR=MSE/ σ_K2 ≈1. Maximum likelihood estimation of models almost guarantees that the MSDR equals 1, and so the kriging variances are unbiased predictors of the squared error across the region. The method is based on the assumption that the errors have a normal distribution. The squared deviation ratio (SDR) should therefore be distributed as χ2 with one degree of freedom with a median of 0.455. We have found that often the median of the SDR (MedSDR) is less, in some instances much less, than 0.455 even though the mean of the SDR is close to 1. It seems that in these cases the distributions of the errors are leptokurtic, i.e. they have an excess of predictions close to the true values, excesses near the extremes and a dearth of predictions in between. In these cases the kriging variances are poor measures of the uncertainty at individual sites. The uncertainty is typically under-estimated for the extreme observations and compensated for by over estimating for other observations. Statisticians must tell users when they present maps of predictions. We illustrate the situation with results from mapping salinity in land reclaimed from the Yangtze delta in the Gulf of Hangzhou, China. There the apparent electrical conductivity (EC_a) of the topsoil was measured at 525 points in a field of 2.3~ha. The marginal distribution of the observations was strongly positively skewed, and so the observed EC_as were transformed to their logarithms to give an approximately symmetric distribution. That distribution was strongly platykurtic with short tails and no evident outliers. The logarithms were analysed as a mixed model of quadratic drift plus correlated random residuals with a spherical variogram. The kriged predictions that deviated from their true values with an MSDR of 0.993, but with a medSDR=0.324. The coefficient of kurtosis of the deviations was 1.45, i.e. substantially larger than 0 for a normal distribution. The reasons for this behaviour are being sought. The most likely explanation is that there are spatial outliers, i.e. points at which the observed values that differ markedly from those at their their closest neighbours.

Evaluation of LiDAR-Acquired Bathymetric and Topographic Data Accuracy in Various Hydrogeomorphic Settings in the Lower Boise River, Southwestern Idaho, 2007

USGS Publications Warehouse

Skinner, Kenneth D.

2009-01-01

Elevation data in riverine environments can be used in various applications for which different levels of accuracy are required. The Experimental Advanced Airborne Research LiDAR (Light Detection and Ranging) - or EAARL - system was used to obtain topographic and bathymetric data along the lower Boise River, southwestern Idaho, for use in hydraulic and habitat modeling. The EAARL data were post-processed into bare earth and bathymetric raster and point datasets. Concurrently with the EAARL data collection, real-time kinetic global positioning system and total station ground-survey data were collected in three areas within the lower Boise River basin to assess the accuracy of the EAARL elevation data in different hydrogeomorphic settings. The accuracies of the EAARL-derived elevation data, determined in open, flat terrain, to provide an optimal vertical comparison surface, had root mean square errors ranging from 0.082 to 0.138 m. Accuracies for bank, floodplain, and in-stream bathymetric data had root mean square errors ranging from 0.090 to 0.583 m. The greater root mean square errors for the latter data are the result of high levels of turbidity in the downstream ground-survey area, dense tree canopy, and horizontal location discrepancies between the EAARL and ground-survey data in steeply sloping areas such as riverbanks. The EAARL point to ground-survey comparisons produced results similar to those for the EAARL raster to ground-survey comparisons, indicating that the interpolation of the EAARL points to rasters did not introduce significant additional error. The mean percent error for the wetted cross-sectional areas of the two upstream ground-survey areas was 1 percent. The mean percent error increases to -18 percent if the downstream ground-survey area is included, reflecting the influence of turbidity in that area.

Recursive least-squares learning algorithms for neural networks

NASA Astrophysics Data System (ADS)

Lewis, Paul S.; Hwang, Jenq N.

1990-11-01

This paper presents the development of a pair of recursive least squares (ItLS) algorithms for online training of multilayer perceptrons which are a class of feedforward artificial neural networks. These algorithms incorporate second order information about the training error surface in order to achieve faster learning rates than are possible using first order gradient descent algorithms such as the generalized delta rule. A least squares formulation is derived from a linearization of the training error function. Individual training pattern errors are linearized about the network parameters that were in effect when the pattern was presented. This permits the recursive solution of the least squares approximation either via conventional RLS recursions or by recursive QR decomposition-based techniques. The computational complexity of the update is 0(N2) where N is the number of network parameters. This is due to the estimation of the N x N inverse Hessian matrix. Less computationally intensive approximations of the ilLS algorithms can be easily derived by using only block diagonal elements of this matrix thereby partitioning the learning into independent sets. A simulation example is presented in which a neural network is trained to approximate a two dimensional Gaussian bump. In this example RLS training required an order of magnitude fewer iterations on average (527) than did training with the generalized delta rule (6 1 BACKGROUND Artificial neural networks (ANNs) offer an interesting and potentially useful paradigm for signal processing and pattern recognition. The majority of ANN applications employ the feed-forward multilayer perceptron (MLP) network architecture in which network parameters are " trained" by a supervised learning algorithm employing the generalized delta rule (GDIt) [1 2]. The GDR algorithm approximates a fixed step steepest descent algorithm using derivatives computed by error backpropagatiori. The GDII algorithm is sometimes referred to as the backpropagation algorithm. However in this paper we will use the term backpropagation to refer only to the process of computing error derivatives. While multilayer perceptrons provide a very powerful nonlinear modeling capability GDR training can be very slow and inefficient. In linear adaptive filtering the analog of the GDR algorithm is the leastmean- squares (LMS) algorithm. Steepest descent-based algorithms such as GDR or LMS are first order because they use only first derivative or gradient information about the training error to be minimized. To speed up the training process second order algorithms may be employed that take advantage of second derivative or Hessian matrix information. Second order information can be incorporated into MLP training in different ways. In many applications especially in the area of pattern recognition the training set is finite. In these cases block learning can be applied using standard nonlinear optimization techniques [3 4 5].

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

A fast least-squares algorithm for population inference

PubMed Central

2013-01-01

Background Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual’s genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. Results We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. Conclusions The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate. PMID:23343408

A fast least-squares algorithm for population inference.

PubMed

Parry, R Mitchell; Wang, May D

2013-01-23

Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual's genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate.

Empirical State Error Covariance Matrix for Batch Estimation

NASA Technical Reports Server (NTRS)

Frisbee, Joe

2015-01-01

State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the uncertainty in the estimated states. By a reinterpretation of the equations involved in the weighted batch least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. The proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. This empirical error covariance matrix may be calculated as a side computation for each unique batch solution. Results based on the proposed technique will be presented for a simple, two observer and measurement error only problem.

Optimal estimation of large structure model errors. [in Space Shuttle controller design

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1979-01-01

In-flight estimation of large structure model errors is usually required as a means of detecting inevitable deficiencies in large structure controller/estimator models. The present paper deals with a least-squares formulation which seeks to minimize a quadratic functional of the model errors. The properties of these error estimates are analyzed. It is shown that an arbitrary model error can be decomposed as the sum of two components that are orthogonal in a suitably defined function space. Relations between true and estimated errors are defined. The estimates are found to be approximations that retain many of the significant dynamics of the true model errors. Current efforts are directed toward application of the analytical results to a reference large structure model.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

Implementation of neural network for color properties of polycarbonates

NASA Astrophysics Data System (ADS)

Saeed, U.; Ahmad, S.; Alsadi, J.; Ross, D.; Rizvi, G.

2014-05-01

In present paper, the applicability of artificial neural networks (ANN) is investigated for color properties of plastics. The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. An optimal design is completed for 10, 12, 14,16,18 & 20 hidden neurons on single hidden layer with five different algorithms: batch gradient descent (GD), batch variable learning rate (GDX), resilient back-propagation (RP), scaled conjugate gradient (SCG), levenberg-marquardt (LM) in the feed forward back-propagation neural network model. The training data for ANN is obtained from experimental measurements. There were twenty two inputs including resins, additives & pigments while three tristimulus color values L*, a* and b* were used as output layer. Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R squared), as well as mean square error is used to investigate the performance of ANN. LM algorithm with fourteen neurons on hidden layer in Feed Forward Back-Propagation of ANN model has shown best result in the present study. The degree of accuracy of the ANN model in reduction of errors is proven acceptable in all statistical analysis and shown in results. However, it was concluded that ANN provides a feasible method in error reduction in specific color tristimulus values.

Development of a Nonlinear Soft-Sensor Using a GMDH Network for a Refinery Crude Distillation Tower

NASA Astrophysics Data System (ADS)

Fujii, Kenzo; Yamamoto, Toru

In atmospheric distillation processes, the stabilization of processes is required in order to optimize the crude-oil composition that corresponds to product market conditions. However, the process control systems sometimes fall into unstable states in the case where unexpected disturbances are introduced, and these unusual phenomena have had an undesirable affect on certain products. Furthermore, a useful chemical engineering model has not yet been established for these phenomena. This remains a serious problem in the atmospheric distillation process. This paper describes a new modeling scheme to predict unusual phenomena in the atmospheric distillation process using the GMDH (Group Method of Data Handling) network which is one type of network model. According to the GMDH network, the model structure can be determined systematically. However, the least squares method has been commonly utilized in determining weight coefficients (model parameters). Estimation accuracy is not entirely expected, because the sum of squared errors between the measured values and estimates is evaluated. Therefore, instead of evaluating the sum of squared errors, the sum of absolute value of errors is introduced and the Levenberg-Marquardt method is employed in order to determine model parameters. The effectiveness of the proposed method is evaluated by the foaming prediction in the crude oil switching operation in the atmospheric distillation process.

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

PubMed

Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

2015-05-01

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

Artificial Vector Calibration Method for Differencing Magnetic Gradient Tensor Systems

PubMed Central

Li, Zhining; Zhang, Yingtang; Yin, Gang

2018-01-01

The measurement error of the differencing (i.e., using two homogenous field sensors at a known baseline distance) magnetic gradient tensor system includes the biases, scale factors, nonorthogonality of the single magnetic sensor, and the misalignment error between the sensor arrays, all of which can severely affect the measurement accuracy. In this paper, we propose a low-cost artificial vector calibration method for the tensor system. Firstly, the error parameter linear equations are constructed based on the single-sensor’s system error model to obtain the artificial ideal vector output of the platform, with the total magnetic intensity (TMI) scalar as a reference by two nonlinear conversions, without any mathematical simplification. Secondly, the Levenberg–Marquardt algorithm is used to compute the integrated model of the 12 error parameters by nonlinear least-squares fitting method with the artificial vector output as a reference, and a total of 48 parameters of the system is estimated simultaneously. The calibrated system outputs along the reference platform-orthogonal coordinate system. The analysis results show that the artificial vector calibrated output can track the orientation fluctuations of TMI accurately, effectively avoiding the “overcalibration” problem. The accuracy of the error parameters’ estimation in the simulation is close to 100%. The experimental root-mean-square error (RMSE) of the TMI and tensor components is less than 3 nT and 20 nT/m, respectively, and the estimation of the parameters is highly robust. PMID:29373544

Bias correction by use of errors-in-variables regression models in studies with K-X-ray fluorescence bone lead measurements.

PubMed

Lamadrid-Figueroa, Héctor; Téllez-Rojo, Martha M; Angeles, Gustavo; Hernández-Ávila, Mauricio; Hu, Howard

2011-01-01

In-vivo measurement of bone lead by means of K-X-ray fluorescence (KXRF) is the preferred biological marker of chronic exposure to lead. Unfortunately, considerable measurement error associated with KXRF estimations can introduce bias in estimates of the effect of bone lead when this variable is included as the exposure in a regression model. Estimates of uncertainty reported by the KXRF instrument reflect the variance of the measurement error and, although they can be used to correct the measurement error bias, they are seldom used in epidemiological statistical analyzes. Errors-in-variables regression (EIV) allows for correction of bias caused by measurement error in predictor variables, based on the knowledge of the reliability of such variables. The authors propose a way to obtain reliability coefficients for bone lead measurements from uncertainty data reported by the KXRF instrument and compare, by the use of Monte Carlo simulations, results obtained using EIV regression models vs. those obtained by the standard procedures. Results of the simulations show that Ordinary Least Square (OLS) regression models provide severely biased estimates of effect, and that EIV provides nearly unbiased estimates. Although EIV effect estimates are more imprecise, their mean squared error is much smaller than that of OLS estimates. In conclusion, EIV is a better alternative than OLS to estimate the effect of bone lead when measured by KXRF. Copyright © 2010 Elsevier Inc. All rights reserved.

Identifying model error in metabolic flux analysis - a generalized least squares approach.

PubMed

Sokolenko, Stanislav; Quattrociocchi, Marco; Aucoin, Marc G

2016-09-13

The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range). The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.

Tests of Independence in Contingency Tables with Small Samples: A Comparison of Statistical Power.

ERIC Educational Resources Information Center

Parshall, Cynthia G.; Kromrey, Jeffrey D.

1996-01-01

Power and Type I error rates were estimated for contingency tables with small sample sizes for the following four types of tests: (1) Pearson's chi-square; (2) chi-square with Yates's continuity correction; (3) the likelihood ratio test; and (4) Fisher's Exact Test. Various marginal distributions, sample sizes, and effect sizes were examined. (SLD)

A Generalized Least Squares Regression Approach for Computing Effect Sizes in Single-Case Research: Application Examples

ERIC Educational Resources Information Center

Maggin, Daniel M.; Swaminathan, Hariharan; Rogers, Helen J.; O'Keeffe, Breda V.; Sugai, George; Horner, Robert H.

2011-01-01

A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of…

Difference-based ridge-type estimator of parameters in restricted partial linear model with correlated errors.

PubMed

Wu, Jibo

2016-01-01

In this article, a generalized difference-based ridge estimator is proposed for the vector parameter in a partial linear model when the errors are dependent. It is supposed that some additional linear constraints may hold to the whole parameter space. Its mean-squared error matrix is compared with the generalized restricted difference-based estimator. Finally, the performance of the new estimator is explained by a simulation study and a numerical example.

[Application of near infrared spectroscopy combined with particle swarm optimization based least square support vactor machine to rapid quantitative analysis of Corni Fructus].

PubMed

Liu, Xue-song; Sun, Fen-fang; Jin, Ye; Wu, Yong-jiang; Gu, Zhi-xin; Zhu, Li; Yan, Dong-lan

2015-12-01

A novel method was developed for the rapid determination of multi-indicators in corni fructus by means of near infrared (NIR) spectroscopy. Particle swarm optimization (PSO) based least squares support vector machine was investigated to increase the levels of quality control. The calibration models of moisture, extractum, morroniside and loganin were established using the PSO-LS-SVM algorithm. The performance of PSO-LS-SVM models was compared with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN). The calibration and validation results of PSO-LS-SVM were superior to both PLS and BP-ANN. For PSO-LS-SVM models, the correlation coefficients (r) of calibrations were all above 0.942. The optimal prediction results were also achieved by PSO-LS-SVM models with the RMSEP (root mean square error of prediction) and RSEP (relative standard errors of prediction) less than 1.176 and 15.5% respectively. The results suggest that PSO-LS-SVM algorithm has a good model performance and high prediction accuracy. NIR has a potential value for rapid determination of multi-indicators in Corni Fructus.

Least Median of Squares Filtering of Locally Optimal Point Matches for Compressible Flow Image Registration

PubMed Central

Castillo, Edward; Castillo, Richard; White, Benjamin; Rojo, Javier; Guerrero, Thomas

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. PMID:22797602

High-Accuracy Decoupling Estimation of the Systematic Coordinate Errors of an INS and Intensified High Dynamic Star Tracker Based on the Constrained Least Squares Method

PubMed Central

Jiang, Jie; Yu, Wenbo; Zhang, Guangjun

2017-01-01

Navigation accuracy is one of the key performance indicators of an inertial navigation system (INS). Requirements for an accuracy assessment of an INS in a real work environment are exceedingly urgent because of enormous differences between real work and laboratory test environments. An attitude accuracy assessment of an INS based on the intensified high dynamic star tracker (IHDST) is particularly suitable for a real complex dynamic environment. However, the coupled systematic coordinate errors of an INS and the IHDST severely decrease the attitude assessment accuracy of an INS. Given that, a high-accuracy decoupling estimation method of the above systematic coordinate errors based on the constrained least squares (CLS) method is proposed in this paper. The reference frame of the IHDST is firstly converted to be consistent with that of the INS because their reference frames are completely different. Thereafter, the decoupling estimation model of the systematic coordinate errors is established and the CLS-based optimization method is utilized to estimate errors accurately. After compensating for error, the attitude accuracy of an INS can be assessed based on IHDST accurately. Both simulated experiments and real flight experiments of aircraft are conducted, and the experimental results demonstrate that the proposed method is effective and shows excellent performance for the attitude accuracy assessment of an INS in a real work environment. PMID:28991179

The GEOS Ozone Data Assimilation System: Specification of Error Statistics

NASA Technical Reports Server (NTRS)

Stajner, Ivanka; Riishojgaard, Lars Peter; Rood, Richard B.

2000-01-01

A global three-dimensional ozone data assimilation system has been developed at the Data Assimilation Office of the NASA/Goddard Space Flight Center. The Total Ozone Mapping Spectrometer (TOMS) total ozone and the Solar Backscatter Ultraviolet (SBUV) or (SBUV/2) partial ozone profile observations are assimilated. The assimilation, into an off-line ozone transport model, is done using the global Physical-space Statistical Analysis Scheme (PSAS). This system became operational in December 1999. A detailed description of the statistical analysis scheme, and in particular, the forecast and observation error covariance models is given. A new global anisotropic horizontal forecast error correlation model accounts for a varying distribution of observations with latitude. Correlations are largest in the zonal direction in the tropics where data is sparse. Forecast error variance model is proportional to the ozone field. The forecast error covariance parameters were determined by maximum likelihood estimation. The error covariance models are validated using x squared statistics. The analyzed ozone fields in the winter 1992 are validated against independent observations from ozone sondes and HALOE. There is better than 10% agreement between mean Halogen Occultation Experiment (HALOE) and analysis fields between 70 and 0.2 hPa. The global root-mean-square (RMS) difference between TOMS observed and forecast values is less than 4%. The global RMS difference between SBUV observed and analyzed ozone between 50 and 3 hPa is less than 15%.

Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations.

PubMed

Creavin, Sam T; Wisniewski, Susanna; Noel-Storr, Anna H; Trevelyan, Clare M; Hampton, Thomas; Rayment, Dane; Thom, Victoria M; Nash, Kirsty J E; Elhamoui, Hosam; Milligan, Rowena; Patel, Anish S; Tsivos, Demitra V; Wing, Tracey; Phillips, Emma; Kellman, Sophie M; Shackleton, Hannah L; Singleton, Georgina F; Neale, Bethany E; Watton, Martha E; Cullum, Sarah

2016-01-13

The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia. To determine the diagnostic accuracy of the Mini-Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia. We searched the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), LILACS (BIREME), ALOIS, BIOSIS previews (Thomson Reuters Web of Science), and Web of Science Core Collection, including the Science Citation Index and the Conference Proceedings Citation Index (Thomson Reuters Web of Science). We also searched specialised sources of diagnostic test accuracy studies and reviews: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). We attempted to locate possibly relevant but unpublished data by contacting researchers in this field. We first performed the searches in November 2012 and then fully updated them in May 2014. We did not apply any language or date restrictions to the electronic searches, and we did not use any methodological filters as a method to restrict the search overall. We included studies that compared the 11-item (maximum score 30) MMSE test (at any cut point) in people who had not undergone prior testing versus a commonly accepted clinical reference standard for all-cause dementia and subtypes (Alzheimer disease dementia, Lewy body dementia, vascular dementia, frontotemporal dementia). Clinical diagnosis included all-cause (unspecified) dementia, as defined by any version of the Diagnostic and Statistical Manual of Mental Disorders (DSM); International Classification of Diseases (ICD) and the Clinical Dementia Rating. At least three authors screened all citations.Two authors handled data extraction and quality assessment. We performed meta-analysis using the hierarchical summary receiver-operator curves (HSROC) method and the bivariate method. We retrieved 24,310 citations after removal of duplicates. We reviewed the full text of 317 full-text articles and finally included 70 records, referring to 48 studies, in our synthesis. We were able to perform meta-analysis on 28 studies in the community setting (44 articles) and on 6 studies in primary care (8 articles), but we could not extract usable 2 x 2 data for the remaining 14 community studies, which we did not include in the meta-analysis. All of the studies in the community were in asymptomatic people, whereas two of the six studies in primary care were conducted in people who had symptoms of possible dementia. We judged two studies to be at high risk of bias in the patient selection domain, three studies to be at high risk of bias in the index test domain and nine studies to be at high risk of bias regarding flow and timing. We assessed most studies as being applicable to the review question though we had concerns about selection of participants in six studies and target condition in one study.The accuracy of the MMSE for diagnosing dementia was reported at 18 cut points in the community (MMSE score 10, 14-30 inclusive) and 10 cut points in primary care (MMSE score 17-26 inclusive). The total number of participants in studies included in the meta-analyses ranged from 37 to 2727, median 314 (interquartile range (IQR) 160 to 647). In the community, the pooled accuracy at a cut point of 24 (15 studies) was sensitivity 0.85 (95% confidence interval (CI) 0.74 to 0.92), specificity 0.90 (95% CI 0.82 to 0.95); at a cut point of 25 (10 studies), sensitivity 0.87 (95% CI 0.78 to 0.93), specificity 0.82 (95% CI 0.65 to 0.92); and in seven studies that adjusted accuracy estimates for level of education, sensitivity 0.97 (95% CI 0.83 to 1.00), specificity 0.70 (95% CI 0.50 to 0.85). There was insufficient data to evaluate the accuracy of the MMSE for diagnosing dementia subtypes.We could not estimate summary diagnostic accuracy in primary care due to insufficient data. The MMSE contributes to a diagnosis of dementia in low prevalence settings, but should not be used in isolation to confirm or exclude disease. We recommend that future work evaluates the diagnostic accuracy of tests in the context of the diagnostic pathway experienced by the patient and that investigators report how undergoing the MMSE changes patient-relevant outcomes.

Exercise improves cognitive function in aging patients

PubMed Central

Hu, Jian-Ping; Guo, Yan-Hua; Wang, Feng; Zhao, Xin-Ping; Zhang, Quan-Hai; Song, Qing-Hua

2014-01-01

A decline in cognitive ability commonly occurs among older individuals. This study sought to explore the restorative effects of exercise in older patients with existing cognitive disabilities. Ninety-six patients with mild cognitive impairment were placed in an exercise program for six months. Following completion of the program, participants were assessed via the Chinese Mini Mental Status Examination (MMSE), Activity of Daily Living (ADL) assessment, and body movement testing and compared to a control group of patients with mild cognitive impairment who did not participate in the exercise program (N = 102). Statistical analyses were performed using the Student’s t-test and chi-square test to compare results between groups. Compared with control group, patients who exercised showed improved cognitive function in immediate memory (p < 0.001) and delayed recall (p = 0.004) function. In addition, activities associated with daily living showed improvement (p < 0.001), as did body movement (p < 0.05), arm stability (p < 0.001), and the appearance of rotation (p < 0.05). Based on these results, we conclude that participation in an exercise program can improve patients’ cognitive function, physical abilities, and body movement capacity. PMID:25419345

Error Covariance Penalized Regression: A novel multivariate model combining penalized regression with multivariate error structure.

PubMed

Allegrini, Franco; Braga, Jez W B; Moreira, Alessandro C O; Olivieri, Alejandro C

2018-06-29

A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS). Copyright © 2018 Elsevier B.V. All rights reserved.

Robust Least-Squares Support Vector Machine With Minimization of Mean and Variance of Modeling Error.

PubMed

Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui

2017-06-13

The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.

[Correlates of change in cognitive function during a two-year follow-up period in a comprehensive health examination for the community-dwelling elderly for the prevention of geriatric syndromes and bed-ridden state].

PubMed

Iwasa, Hajime; Suzuki, Takao; Yoshida, Yuko; Kwon, Jinhee; Yoshida, Hideyo; Kim, Hunkyung; Sugiura, Miho; Furuna, Taketo

2006-11-01

We explored correlates of change in cognitive function during a two-year follow-up period among the community-dwelling elderly in Japan, using a population-based prospective approach. The participants analyzed in the present study were 260 men and 222 women aged 70 to 84 years at baseline, living in an urban Japanese community. Data such as change in cognitive function during two years (calculated by subtracting baseline Mini-Mental State Examination [MMSE] score from follow-up MMSE score: a negative value means a decrease in MMSE scores during the two-year period) as an outcome variable, age, education, hearing and vision problems, IADL deficit (measured by the Tokyo Metropolitan Institute of Gerontology of Index of Competence), problems related to memory complaint, living alone, hemoglobin level, as explanatory variables, and the baseline MMSE score, depressive status (measured by the Mini-International Neuropsychiatric Interview), chronic conditions (hypertension, stroke, and diabetes mellitus) as covariates, were collected during a comprehensive health examination survey for the elderly. We conducted multivariate regression analysis by genders to explore correlates of change in cognitive function. The results showed that higher age (beta = -0.18), presence of hearing problem (beta = -0.21), presence of IADL deficit (beta = -0.15), and memory complaint (beta = -0.20) in men, and higher age (beta = -0.27), low education level (beta = -0.25) and lower hemoglobin level (beta = 0.16) in women, were significantly associated with change in cognitive function when adjusting for the potential confounders. These factors may be reliable predictors for cognitive decline.

Distinct Patterns of Cognitive Aging Modified by Education Level and Gender among Adults with Limited or No Formal Education: A Normative Study of the Mini-Mental State Examination.

PubMed

Xie, Haiqun; Zhang, Chengguo; Wang, Yukai; Huang, Shuyun; Cui, Wei; Yang, Wenbin; Koski, Lisa; Xu, Xiping; Li, Youbao; Zheng, Meili; He, Mingli; Fu, Jia; Shi, Xiuli; Wang, Kai; Tang, Genfu; Wang, Binyan; Huo, Yong

2016-01-01

Dementia is increasingly prevalent due to rapid aging of the population, but under-recognized among people with low education levels. This is partly due to a lack of appropriate and precise normative data, which underestimates cognitive aging in the use of screening tools for dementia. We aimed to improve the precision of screening for cognitive impairment, by characterizing the patterns of cognitive aging and derived normative data of the Mini-Mental State Examination (MMSE) for illiterate and low-educated populations. This community-based study included data from 2,280 individuals aged 40 years or older from two rural areas. Multiple linear modeling examined the effect of aging on cognition reflected by the MMSE, stratified by education level and gender. Threshold effect of age on cognition was performed using a smoothing function. The majority of participants (60.4%) were illiterate or had attended only primary school (24.6%). The effect of aging on cognition varied by gender and education. Primary-school educated females and males remained cognitively stable up to 62 and 71 years of age, respectively, with MMSE score declining 0.4 and 0.8 points/year in females and males thereafter. Illiterates females scored 2.3 points lower than illiterate males, and scores for both declined 0.2 points/year. According to these results, normative data stratified by age, education and gender was generated. This study suggests gender and educational differences exist in cognitive aging among adults with limited or no formal education. To improve screening precision for cognitive impairment with the use of MMSE in low-educated population, age, gender, and education level should be considered.

Benefits of use, and tolerance of, medium-chain triglyceride medical food in the management of Japanese patients with Alzheimer's disease: a prospective, open-label pilot study.

PubMed

Ohnuma, Tohru; Toda, Aiko; Kimoto, Ayako; Takebayashi, Yuto; Higashiyama, Ryoko; Tagata, Yuko; Ito, Masanobu; Ota, Tsuneyoshi; Shibata, Nobuto; Arai, Heii

2016-01-01

This is the first clinical trial of this type in Japan, designed to analyze two important aspects of Alzheimer's disease (AD) management using medium-chain triglycerides. Axona was administered for 3 months (40 g of powder containing 20 g of caprylic triglycerides). We used an indurating, four-step dose-titration method (from 10 to 40 g per day) for 7 days before the trial, and examined the tolerance and adverse effects of this intervention. We also investigated its effect on cognitive function in mild-to-moderate AD patients. This was a clinical intervention in 22 Japanese patients with sporadic AD at a mild-to-moderate stage (ten females, 12 males), mean age (± standard deviation) 63.9 (±8.5) years, Mini-Mental State Examination (MMSE) score, 10-25, seven patients were ApoE4-positive. During Axona administration, we examined changes in cognitive function by obtaining MMSE and AD assessment-scale scores. Intolerance and serum ketone concentrations were also examined. The tolerance of Axona was good, without severe gastrointestinal adverse effects. Axona did not improve cognitive function in our sample of AD patients, even in those patients without the ApoE4 allele. However, some ApoE4-negative patients with baseline MMSE score ≥14 showed improvement in their cognitive functions. The modified dose-titration method, starting with a low dose of Axona, decreased gastrointestinal adverse effects in Japanese patients. Axona might be effective for some relatively mildly affected patients with AD (with cognitive function MMSE score of ≥14 and lacking the ApoE4 allele).

Development of a tool for assessment and care planning for dementia-related problem behaviors in home and community-based services programs: the Problem Behavior Inventory.

PubMed

Phillips, V L; Diwan, Sadhna; Egner, Amanda

2002-01-01

To describe development, validity, and application of the Problem Behavior Inventory (PBI), a tool to assess dementia-related problem behaviors (DRPBs) in community-based populations. Demographic, contact, and disease-specific data were extracted from client files from a Medicaid-funded home and community-based services program. Primary caregivers completed standard surveys relating to the care recipients' memory, mood, and behaviors. The client (care recipient) completed the Mini-Mental Status Exam (MMSE). Cognitively impaired clients, enrolled in the Community Care Services Program (CCSP) during a reference month, and their primary caregivers, were identified by CCSP case managers for participation in the study. Primary caregivers completed the Revised Memory and Behavior Problem Checklist (RMBPC). Clients screening positive for the presence of DRPBs based on caregiver responses to the RMBPC were then assessed using the Problem Behavior Inventory (PBI). Within the CCSP sample, the most prevalent behavior was appearing sad or depressed (67%), while the most frequent behavior was seeking attention, occurring at least daily in 58% of the group. The most bothersome behaviors were being sexually inappropriate, wandering, and misbehaving in public. Examination by behavior category (physical, verbal, mood, etc.) revealed a strong relationship between level of bother and behavior frequency. Frequency of verbal behaviors was positively related to MMSE scores, whereas frequency of ADL-related behaviors was inversely related to MMSE scores. Bother scores were not associated with MMSE scores. This study documents that the PBI is a valid, useful, and feasible tool for assessing DRPBs in community populations. Case managers using the PBI can determine specific problem behavior areas among client populations and for individual clients and institute client-specific interventions to address each issue.

Migraine is associated with better cognition in the middle-aged and elderly: the Rotterdam Study.

PubMed

Wen, K; Nguyen, N T; Hofman, A; Ikram, M A; Franco, O H

2016-10-01

Converging evidence suggests that migraine has, in part, a vascular basis. In turn, vascular pathology is a strong risk factor for cognitive decline. In this population-based study, we studied cognition amongst individuals with and without migraine. In 6708 participants of the Rotterdam Study, migraine was assessed using a validated questionnaire. Cognition was assessed by the Mini Mental State Examination (MMSE) and a dedicated cognitive test battery. Participants were classified as non-migraineurs (n = 5399), migraineurs (n = 1021) or probable migraineurs (n = 288). Multivariable linear regression was used to cross-sectionally evaluate the association between migraine and cognition, adjusting for age, sex and cardiovascular risk factors. Additionally, we stratified the analysis by sex and by migraine subtype. Migraineurs had higher mean MMSE scores [unstandardized regression coefficient 0.21, (95% confidence interval, 0.08; 0.34)] and global cognition [0.10 (0.04; 0.15)] than non-migraineurs. This difference was particularly marked for migraineurs with aura [MMSE: 0.39 (0.13; 0.66); global cognition: 0.13 (0.01; 0.24)]. Migraineurs performed better on tests of executive function and fine motor skills amongst specific cognitive domains. The difference in MMSE between migraineurs and non-migraineurs was greater in women [0.25 (0.10; 0.40)] than in men [0.13 (-0.15; 0.40)], whereas the difference in global cognition was similar in men and women [0.15 (0.04; 0.27) and 0.09 (0.02; 0.15), respectively]. Migraineurs, particularly migraineurs with aura, tend to score higher in cognition tests than non-migraineurs. More studies are needed to corroborate these findings. © 2016 EAN.

The association between orthostatic hypotension and cognitive state among adults 65 years and older who underwent a comprehensive geriatric assessment

PubMed Central

Punchick, Boris; Freud, Tamar; Press, Yan

2016-01-01

Abstract The prevalence of cognitive impairment and orthostatic hypotension (OH) increases with age, but the results of studies that assessed possible associations between them are inconsistent. The aim of this study is to assess possible associations between cognitive impairment and OH in patients ≥65 years of age who underwent a comprehensive geriatric assessment. A retrospective analysis was conducted of the computerized medical records of the study population from 2005 to 2013. Data collected included blood pressure measurements that enabled the calculation of OH, results of the mini-mental state examination (MMSE), results of the Montreal cognitive assessment (MoCA) test, and cognitive diagnoses that were determined over the course of the assessment. The rate of OH in the study population of 571 adults was 32.1%. The mean MMSE score was 22.5 ± 5.2 among participants with OH and 21.6 ± 5.8 among those without OH (P = 0.09). The absence of a significant association between OH and MMSE remained after adjusting the MMSE score for age and education level. The mean MoCA score was 16.4 ± 5.0 among participants with OH and 16.4 ± 4.8 among those without (P = 0.33). The prevalence of OH was 39% among participants without cognitive impairment, 28.9% among those with mild cognitive impairment (MCI), and 30.6% among those with dementia (P = 0.13). There was no association between OH and cognitive impairment in adults who underwent a comprehensive geriatric assessment. PMID:27442658

Racial and sex differences in associations between activities of daily living and cognition in community-dwelling older adults.

PubMed

Garrett, Stephanie L; Sawyer, Patricia; Kennedy, Richard E; McGuire, Dawn; Simon, Roger P; Strothers, Harry S; Allman, Richard M

2013-12-01

To examine the association between function measured according to activities of daily living (ADLs), instrumental activ1ities of daily living (IADLs), and cognition assessed according to Mini-Mental State Examination (MMSE) scores of older African-American and non-Hispanic white community-dwelling men and women. Cross-sectional study assessing associations between self-reported ADL and IADL difficulty and MMSE scores for race- and sex-specific groups. Homes of community-dwelling older adults. A random sample of 974 African-American and non-Hispanic white Medicare beneficiaries aged 65 and older living in west-central Alabama and participating in the University of Alabama at Birmingham Study of Aging, excluding those with reported diagnoses of dementia or with missing data. Function, based on self-reported difficulty in performing ADLs and IADLs, and cognition, using the MMSE. Multivariable linear regression models were used to test the association between function and cognition in race- and sex-specific groups after adjusting for covariates. Mini-Mental State Examination scores were modestly correlated with ADL and IADL difficulty in all four race- and sex-specific groups, with Pearson correlation coefficients ranging from −0.189 for non-Hispanic white women to −0.429 for African-American men. Correlations between MMSE and ADL or IADL difficulty in any of the race- and sex-specific groups were no longer significant after controlling for sociodemographic factors and comorbidities. Mini-Mental State Examination was not significantly associated with functional difficulty in older African-American and non-Hispanic white men and women after adjusting for sociodemographic factors and comorbidities, suggesting a mediating role in the relationship between cognition and function. © 2013, Copyright the Authors Journal compilation © 2013, The American Geriatrics Society.

Cognitive function and dementia in six areas of England and Wales: the distribution of MMSE and prevalence of GMS organicity level in the MRC CFA Study. The Medical Research Council Cognitive Function and Ageing Study (MRC CFAS).

PubMed

1998-03-01

This two-stage prevalence survey involved geographically delimited areas, four urban (Liverpool, Newcastle, Nottingham and Oxford) and two rural (Cambridgeshire and Gwynedd), including institutions. Stratified random population samples of people in their 65th year and above, from Family Health Service Authorities were studied. The sample was stratified (65-74 years and > or = 75) to provide equal numbers. In Liverpool equal numbers in 5 year age groups were taken. After an initial screening interview, approximately 20% were selected on the basis of age, AGECAT organicity confidence level and MMSE score to proceed to a detailed assessment interview from which the full AGECAT organicity confidence level could be derived. Major influences on MMSE were confirmed as age, sex, social class and educational level. Estimates of prevalence of AGECAT O3 and above for each centre and the entire sample according to age are given, based on 1991 Census population structure, and suggest that around half a million (543,400) people in England and Wales would be defined as case level by this method. The five centres employing the same methodology showed no heterogeneity in prevalence. Prevalence of cognitive impairment and dementia appear not to vary widely across the centres examined in this study, which provides stable estimates by age and sex for AGECAT O3 and above, and norms for MMSE. Using these estimates as an indication of the size of the population affected, around 550,000 individuals in England and Wales would be expected to be suffering from dementia of mild or greater severity.

Scenery Picture Memory Test: A new type of quick and effective screening test to detect early stage Alzheimer’s disease patients

PubMed Central

Takechi, Hajime; Dodge, Hiroko H

2010-01-01

Aim It is highly desirable to develop a neuropsychological screening test which is sensitive to the early stage of Alzheimer’s disease (AD), and is easy to administer at the primary care physician’s (PCP’s) office. Methods Participants were 128 AD patients and 54 healthy volunteers. Brief cognitive screening tests were administered to the participants including the Mini-Mental State Examination (MMSE), Clock Drawing Test (CDT), Verbal Fluency Test (VFT), a Verbal Category Cued Memory test (CCMT) and the Scenery Picture Memory Test (SPMT). In the SPMT, a scenery picture of a living room containing 23 familiar objects was used. The administration of the SPMT comprised the first shallow memory session (Pict 1) and the second deep memory session (Pict 2). The area under the receiver–operator curve (AUC) was used to compare the efficacy of SPMT with other cognitive tests. Results Pict 1, which requires less than 2 min to complete, had the same AUC as Pict 2, and showed significantly larger AUC than MMSE, CDT and VFT for all (MMSE 19–23) and very mild (MMSE ≥ 24) AD patients. When we conducted the similar analysis separately for those younger than 75 years and those aged 75 years or older, we obtained the same results as above among the older age group. Pict 1 showed larger AUC than CCMT in overall sample and also in the older age group, although the difference was not statistically significant. Conclusion The SPMT could be useful for detection of mild and very mild AD in settings even where time is limited. PMID:20446933

Aging-Related Oxidative Stress: Positive Effect of Memory Training.

PubMed

Pesce, Mirko; Tatangelo, Raffaella; La Fratta, Irene; Rizzuto, Alessia; Campagna, Giovanna; Turli, Cinzia; Ferrone, Alessio; Franceschelli, Sara; Speranza, Lorenza; Patruno, Antonia; Ballerini, Patrizia; De Lutiis, Maria Anna; Felaco, Mario; Grilli, Alfredo

2018-02-01

The cognitive impairment characterizing the phenotype of older adults has been related to the efficiency of the antioxidant system. This study aimed at investigating the effect of memory training (MT) on memory, global cognitive functioning, and the oxidant and antioxidant capacity of plasma. We recruited 52 healthy subjects aged over 60. Twenty-nine subjects were submitted to 6-months of MT (Experimental Group, EG), and 23 were used as a Control Group (CG). Global cognitive functioning was assessed by the Mini-Mental State Examination (MMSE) and Short- and Long-Term Memory (STM and LTM, respectively) by the Rey Auditory Verbal Learning Test (RAVLT) at baseline (T0) and after 6-months (T1). Meanwhile, Reactive Oxygen Metabolites derivative compounds (d-ROMs), Biological Antioxidant Potential (BAP), and their ratio were evaluated on plasma. Results showed that the MMSE and RAVLT scores improved in EG at T1. At the same time, the d-ROMs levels significantly decreased, while the BAP and BAP/d-ROMs ratio showed an opposite trend. In both groups, the MMSE and LTM scores were negatively associated with d-ROMs levels, and positively correlated with BAP levels and the BAP/d-ROMs ratio. When we considered the Δvalue (Δvariable = variable post-MT minus variable pre-MT) in EG, the ΔMMSE and ΔLTM scores were negatively associated to Δd-ROMs, and positively to ΔBAP and ΔBAP/dROM. In conclusion, our results suggest that MT improves memory and global cognitive functioning. These processes were significantly associated to increase in resistance against oxidative stress at the plasma level in healthy older adults. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Association between oxidized low-density lipoprotein and cognitive impairment in patients with ischemic stroke.

PubMed

Wang, A; Liu, J; Meng, X; Li, J; Wang, H; Wang, Y; Su, Z; Zhang, N; Dai, L; Wang, Y; Wang, Y

2018-01-01

The association between oxidized low-density lipoprotein (oxLDL) and cognitive impairment is unclear. This study aimed to investigate the potential association between oxLDL and cognitive impairment among patients with acute ischemic stroke. We measured the levels of oxLDL and recorded the Mini-Mental State Examination (MMSE) score in patients with acute ischemic stroke who were recruited from the Study of Oxidative Stress in Patients with Acute Ischemic Stroke. Cognitive impairment was defined as an MMSE score of <24. The association between oxLDL and cognitive impairment was assessed by multivariate logistic or linear regression analysis. Other clinical variables of interest were also studied. A total of 3726 patients [1287 (34.54%) female] were included in this study, with a mean age of 63.62 ± 11.96 years. After adjusting for potential confounders in our logistic regression model, each SD increase in oxLDL was associated with a 26% increase in the prevalence of cognitive impairment (odds radio, 1.26; 95% confidence interval, 1.13-1.39; P < 0.0001). Similarly, higher oxLDL was associated with lower MMSE scores, with a 0.56-point decrease in MMSE score for every SD increase in oxLDL in a linear regression analysis (β = -0.56; 95% confidence interval, -0.81 to -0.32; P < 0.0001). There were no significant interactions between oxLDL and age, sex or education levels for cognitive impairment (all interactions, P > 0.05). Elevated levels of oxLDL were associated with a higher prevalence of cognitive impairment in patients with ischemic stroke. © 2017 EAN.

Regression-Based Estimates of Observed Functional Status in Centenarians

PubMed Central

Mitchell, Meghan B.; Miller, L. Stephen; Woodard, John L.; Davey, Adam; Martin, Peter; Burgess, Molly; Poon, Leonard W.

2011-01-01

Purpose of the Study: There is lack of consensus on the best method of functional assessment, and there is a paucity of studies on daily functioning in centenarians. We sought to compare associations between performance-based, self-report, and proxy report of functional status in centenarians. We expected the strongest relationships between proxy reports and observed performance of basic activities of daily living (BADLs) and instrumental activities of daily living (IADLs). We hypothesized that the discrepancy between self-report and observed daily functioning would be modified by cognitive status. We additionally sought to provide clinicians with estimates of centenarians’ observed daily functioning based on their mental status in combination with subjective measures of activities of daily living (ADLs). Design and Methods: Two hundred and forty-four centenarians from the Georgia Centenarian Study were included in this cross-sectional population-based study. Measures included the Direct Assessment of Functional Status, self-report and proxy report of functional status, and the Mini-Mental State Examination (MMSE). Results: Associations between observed and proxy reports were stronger than between observed and self-report across BADL and IADL measures. A significant MMSE by type of report interaction was found, indicating that lower MMSE performance is associated with a greater discrepancy between subjective and objective ADL measures. Implications: Results demonstrate associations between 3 methods of assessing functional status and suggest proxy reports are generally more accurate than self-report measures. Cognitive status accounted for some of the discrepancy between observed and self-reports, and we provide clinicians with tables to estimate centenarians’ performance on observed functional measures based on MMSE and subjective report of functional status. PMID:20974657

Cognitive function and walking velocity in people with dementia; a comparison of backward and forward walking.

PubMed

Johansson, Hanna; Lundin-Olsson, Lillemor; Littbrand, Håkan; Gustafson, Yngve; Rosendahl, Erik; Toots, Annika

2017-10-01

How forward and backward walking, both central to everyday life, relate to cognition are relatively unexplored in people with dementia. This study aimed to investigate if forward and backward walking velocity respectively, associated with global cognition and executive function in people with dementia, and whether the association differed according to walking aid use or dementia type. Using a cross-sectional design, 161 participants (77% women), a mean Mini-Mental State Examination (MMSE) score of 15, and mean age of 85.5years and living in nursing homes were included. Self-paced forward walking (FW) and backward walking (BW) velocity over 2.4m was measured. Global cognitive outcome measurements included MMSE and Alzheimer Disease Assessment Scale - Cognitive subscale (ADAS-Cog). Executive function was measured using Verbal Fluency (VF). In comprehensively adjusted multivariate linear regression analyses, FW was independently associated with VF (p=0.001), but not MMSE (p=0.126) or ADAS-Cog (p=0.818). BW was independently associated with VF (p=0.043) and MMSE (p=0.022), but not ADAS-Cog (p=0.519). Interaction analyses showed that the association between BW velocity and executive function were stronger in participants who walked without a walking aid. No associations differed according to dementia type. In conclusion, executive function appears important to walking velocity, both forward and backward, in people with dementia with mild to moderately severe cognitive impairment. Global cognitive function was associated with backward walking only, perhaps due to it being more challenging. The association between BW velocity and executive function differed according to use of walking aids, which appeared to attenuate the association. Copyright © 2017 Elsevier B.V. All rights reserved.

Low intakes of carotene, vitamin B2 , pantothenate and calcium predict cognitive decline among elderly patients with diabetes mellitus: The Japanese Elderly Diabetes Intervention Trial.

PubMed

Araki, Atsushi; Yoshimura, Yukio; Sakurai, Takashi; Umegaki, Hiroyuki; Kamada, Chiemi; Iimuro, Satoshi; Ohashi, Yasuo; Ito, Hideki

2017-08-01

The present study aimed to examine whether nutrient intakes predicted cognitive decline among elderly patients with diabetes mellitus. This study evaluated data from a 6-year prospective follow up of 237 elderly patients (aged ≥65 years) with diabetes mellitus, and the associations of baseline nutrient intakes with cognitive decline. Cognitive decline was defined as a ≥2-point decrease in the Mini-Mental State Examination (MMSE) score. Intakes of food and nutrients were assessed using a validated food frequency questionnaire, and were compared between patients with cognitive decline and intact cognition. Analysis of covariance and logistic regression analysis were used to compare the changes in the MMSE score during the follow up among intake tertile groups for each nutrient. Compared with men with intact cognition, the men with cognitive decline had lower baseline intakes of calcium, vitamin A, vitamin B 2 , pantothenate, soluble fiber, green vegetables and milk. However, no significant associations between cognitive decline and nutrient intakes were observed among women. After adjusting for age, body mass index, glycated hemoglobin levels, history of severe hypoglycemia, previous stroke and baseline MMSE score, we found that cognitive decline was significantly associated with low intakes of carotene, vitamin B 2 , pantothenate, calcium and green vegetables. Multiple logistic regression analysis showed that intakes of nutrients and green vegetables predicted cognitive decline after adjusting for age, body mass index, glycated hemoglobin levels, baseline MMSE score, and incident stroke during the follow up. These findings suggest that sufficient intakes of carotene, vitamin B 2 , pantothenate, calcium and vegetables could help prevent cognitive decline among elderly men with diabetes mellitus. Geriatr Gerontol Int 2017; 17: 1168-1175. © 2016 Japan Geriatrics Society.

Predictors of cognitive impairment assessed by Mini Mental State Examination in community-dwelling older adults: relevance of the step test.

PubMed

Muscari, Antonio; Spiller, Ilaria; Bianchi, Giampaolo; Fabbri, Elisa; Forti, Paola; Magalotti, Donatella; Pandolfi, Paolo; Zoli, Marco

2018-07-15

Several predictors of cognitive impairment assessed by Mini Mental State Examination (MMSE) have previously been identified. However, which predictors are the most relevant and what is their effect on MMSE categories remains unclear. Cross-sectional and longitudinal study using data from 1116 older adults (72.6 ± 5.6 years, 579 female), 350 of whom were followed for 7 years. At baseline, the following variables were collected: personal data, marital status, occupation, anthropometric measures, risk factors, previous cardiovascular events, self-rated health and physical activity during the last week. Furthermore, routine laboratory tests, abdominal echography and a step test (with measurement of the time needed to ascend and descend two steps 20 times) were performed. The associations of these variables with cross-sectional cognitive deficit (MMSE < 24) and longitudinal cognitive decline (decrease of MMSE score over 7 years of follow-up) were investigated using logistic regression models. Cross-sectional cognitive deficit was independently associated with school education ≤ 5 years, prolonged step test duration, having been blue collar or housewife (P ≤ 0.0001 for all) and, with lower significance, with advanced age, previous stroke and poor recent physical activity (P < 0.05). Longitudinal cognitive decline was mainly associated with step test duration (P = 0.0001) and diastolic blood pressure (P = 0.0002). The MMSE categories mostly associated with step test duration were orientation, attention, calculation and language, while memory appeared to be poorly or not affected. In our cohort of older adults, step test duration was the most relevant predictor of cognitive impairment. Copyright © 2018 Elsevier Inc. All rights reserved.