Sum Of Squares Test Research Articles

An improved evaluation method of industrial noise based on level of noise pollution and kurtosis-weighted cumulative noise exposure

While industry development has improved people's lives, industrial noise has also caused negative impacts. Industrial noise cannot be avoided in industrial environments. It is essential to accurately evaluate industrial noise. Most existing industrial noise evaluation methods consider the factors of industrial noise but ignore the factors of human perception and cannot accurately reflect the subjective auditory perception of humans. The paper proposes an industrial noise evaluation method, LCINE, based on level of noise pollution (LNP) and kurtosis-weighted cumulative noise exposure. First, statistical regression is used to determine the LNP constant based on improved Robinson's method. The consideration of both industrial noise and individual worker in improved method makes the constant suitable for evaluating industrial noise. Second, the improved LNP is combined with kurtosis to determine the intensity evaluation item. Kurtosis is used to capture the extremity of outliers and amplitude variations effectively in statistics, so kurtosis accurately reflects sound peaks and intensity here. Then, the exposure time evaluation item is determined by combining kurtosis with exposure time. Finally, the normalization method is used to allocate theweights of the intensity evaluation item and the exposure time evaluation item, which can unify the measurement units and reduce the adverse effects caused by extreme data. The superiority of LCINE is verified through methods including correlation test, paired-samples t test, partial regression sum of squares test, and subjective evaluation. The results indicate that the method LCINE can more accurately evaluate industrial noise and is more consistent with the subjective auditory perception of humans.

Goodness-of-fit tests for modified Poisson regression possibly producing fitted values exceeding one in binary outcome analysis.

Modified Poisson regression, which estimates the regression parameters in the log-binomial regression model using the Poisson quasi-likelihood estimating equation and robust variance, is a useful tool for estimating the adjusted risk and prevalence ratio in binary outcome analysis. Although several goodness-of-fit tests have been developed for other binary regressions, few goodness-of-fit tests are available for modified Poisson regression. In this study, we proposed several goodness-of-fit tests for modified Poisson regression, including the modified Hosmer-Lemeshow test with empirical variance, Tsiatis test, normalized Pearson chi-square tests with binomial variance and Poisson variance, and normalized residual sum of squares test. The original Hosmer-Lemeshow test and normalized Pearson chi-square test with binomial variance are inappropriate for the modified Poisson regression, which can produce a fitted value exceeding 1 owing to the unconstrained parameter space. A simulation study revealed that the normalized residual sum of squares test performed well regarding the type I error probability and the power for a wrong link function. We applied the proposed goodness-of-fit tests to the analysis of cross-sectional data of patients with cancer. We recommend the normalized residual sum of squares test as a goodness-of-fit test in the modified Poisson regression.

Impact of Remittance, Money Supply and Inflation on Economic Growth of Nepal: Using Autoregressive Distributed Lag Model (ARDL)

Remittances have become a major source of funding in developing countries. A time series analysis was conducted by taking the 25 years data of economic growth as a dependent variable while remittance, money supply and Inflation as independent variables form the annual report of Economic survey of Nepal (2020/21). The autoregressive distributive lag (ARDL) was used to study the relationship among the variables. The trend of economic growth and total percentage of economic growth is in increasing order. The relation between then was found as LN(Economic Growth) =8.0740 +0.220*LNREM + 0.3123 *LNM2-0.0802*LNINF. The stability test of long-run coefficient including short run was studied using ARDL model and are confirmed using Cumulative Sum chart (CUSUM) and cumulative sum of squares test (CUSUMSQ) test. Finding shows that there is long run positive relationship between remittance, money supply, inflation on economic growth of Nepal. From the analysis it is clear that coefficients of error correction are highly significant this indicate that adjustment to longterm equilibrium in the dynamic model and ARDL model showed all the independent variables had positive impact on economic growth of Nepal.

Trends and Contributing Factors in Medicolegal Cases Involving Spine Surgery.

Retrospective descriptive study. The aim of this study was to describe closed medicolegal cases involving physicians and spine surgery in Canada from a trend and patient safety perspective. Spine surgery is a source of medicolegal complaints against surgeons partly owing to the potential severity of associated complications. In previous medicolegal studies, researchers applied a medicolegal lens to their analyses without applying a quality improvement or patient safety lens. The study comprised a 15-year medicolegal trend analysis and a 5-year contributing factors analysis of cases (civil legal and regulatory authority matters) from the Canadian Medical Protective Association (CMPA), representing an estimated 95% of physicians in Canada. Included cases were closed by the CMPA between 2004 and 2018 (trends) or 2014 and 2018 (contributing factors). We fit a linear trend line to the annual rates of spine surgery cases per 1000 physician-years of CMPA membership for physicians in a neurosurgery or orthopedic surgery specialty. We then applied an ANOVA type III sum of squares test to determine the statistical significance of the annualized change rate over time. For the contributing factors analysis, we reported descriptive statistics for patient and physician characteristics, patient harm, and peer expert criticisms in each case. Our trend analysis included 340 cases. Case rates decreased significantly at an annualized change rate of -4.7% (P = 0.0017). Our contributing factors analysis included 81 civil legal and 19 regulatory authority cases. Most patients experienced health care-related harm (89/100, 89.0%). Peer experts identified intraoperative injuries (29/89, 32.6%), diagnostic errors (14/89, 15.7%), and wrong site surgeries (16/89, 18.0%) as the top patient safety indicators. The top factor contributing to medicolegal risk was physician clinical decision-making. Although case rates decreased, patient harm was attributable to health care in the majority of recently closed cases. Therefore, crucial opportunities remain to enhance patient safety in spine surgery.Level of Evidence: 4.

Conditional quantile change test for time series based on support vector regression

The task of detecting a structural change in conditional quantiles of time series with time-varying volatilities is vital in the field of financial time series, especially risk management. Therefore, in this study, we aim to construct a change point test to detect a quantile change by hybridizing the cumulative sum of squares test with the support vector quantile regression. Compared to the test employing the standard quantile regression, this approach not only provides more robust property against a high degree of nonlinearity of time series but also exhibits better performance for the datasets contaminated with high-frequency noises, as demonstrated in our simulation study. It also has merits to provide more diverse interpretations and a deeper understanding of financial time series than the volatility change point test, as illustrated in a real data analysis of three financial indices, namely, S&P500, Nasdaq composite index, and the stock price of Apple Inc.

The root canal shaping ability of WaveOne and Reciproc versus ProTaper Universal and Mtwo rotary NiTi systems

Aim: The aim of this study is to compare the root canal shaping ability of two reciprocating instruments: WaveOne and Reciproc versus two rotary instruments – ProTaper Universal (PTU) and Mtwo. Materials and Methods: A total of 160 simulated root canals in resin blocks were constructed with two curvatures located at two positions creating four different combinations: 20°/8 mm, 20°/12 mm, 40°/8 mm, and 40°/12 mm. Canals were prepared using continuous rotation (PTU and Mtwo) or reciprocating (WaveOne and Reciproc) instruments according to the manufacturer's recommendations. Each system was used to prepare 10 canals of each shape. Each file or a set of files was used to prepare one canal. Using Image Analysis Software, pre- and post-instrumentation matching images were superimposed and analyzed for canal width and transportation. Instrument fractures, time of preparation, and change in working length were also recorded. The effect of instrument and canal type on shaping ability were analyzed using two-way ANOVA test followed by post hoc Pearson Chi-square test and sum of squares test at level of significance 5%. Results: The largest mean canal width and transportation values were associated with the Mtwo system (P Conclusions: Continuous rotation and reciprocating files were safe and maintained the original canal anatomy. However, continuous rotation instruments have a higher tendency for canals transportation and aberrations, especially with larger curvatures. Reciprocating files were faster than continuous rotation files in shaping simulated root canals in resin blocks.

A Novel Lack-of-Fit Assessment as a System Suitability Test for Potency Assays.

Bioassay data analysis is used to determine the potency of protein therapeutics. To properly determine potency, the experimental data need to be fitted to a model that adequately describes the observed dose-response relationship. Typical models include 4-parameter logistic curve fits, 5-parameter logistic curve fits or parallel line analysis. Lack-of-fit assessment can be used as a measure of potency assay system suitability to ensure appropriate closeness of the chosen model fit to the experimental data. We present a novel lack-of-fit approach that overcomes the shortcomings of previously described lack-of-fit tests, such as the conventional analysis of variance (ANOVA) F-test and the lack-of-fit sum of squares test. Simulation studies and examples are used to assess the performance of the new lack-of-fit test. The results show that the described lack-of-fit approach can effectively reject poorly fitted data while retaining well-fitted data, and has advantages in potency assay applications where instrument-to-instrument variability in absolute readout is expected.LAY ABSTRACT: Potency assays are analytical procedures used for characterization as well as release and stability analysis in drug development and for approved products. Dose-response data generated from a drug sample and a well-characterized reference standard are evaluated to determine the potency of the drug sample relative to the reference standard. In order to obtain a potency determination, dose-response data need to be fitted to a proper model that adequately describes the observed dose-response relationship. There are different options described to assess the goodness-of-fit of the data. One approach is the goodness-of-fit assessment based on F-test. This approach compares the lack-of-fit error (representing the discrepancy between observed data and fitted curve) to the pure error (representing the random noise between replicate measurement) to determine if the observed lack-of-fit error can be attributed to random noise. A limitation of goodness of fit assessments via F-test lies in its propensity to penalize precise data (small lack-of-fit error can be considered significantly high if the assay has exceptionally low pure error) and accept undesirable noisy data (large undesirable lack-of-fit error can be considered insignificant due to large pure error). An alternative approach based on lack-of-fit sum of squares is only applicable to certain types of assays where the magnitude of measurements is consistent across different instruments given that the lack-of-fit sum of squares will increase when the magnitude of the assay signal measurements increase, even if the relative magnitude of assay data versus fitted curve remains the same. We introduce here a novel approach that overcomes the limitations of F-test and sum of squares-based approaches. This new approach will effectively reject poor data and retain good data, and it is independent of differences in absolute readout across instruments.

Expression quantitative trait loci (eQTLs) in microRNA genes are enriched for schizophrenia and bipolar disorder association signals.

Schizophrenia (SZ) and bipolar disorder (BD) have substantial negative impact on the quality of human life. Both, microRNA (miRNA) expression profiling in SZ and BD postmortem brains [and genome-wide association studies (GWAS)] have implicated miRNAs in disease etiology. Here, we aim to determine whether significant GWAS signals observed in the Psychiatric Genetic Consortium (PGC) are enriched for miRNAs. A two-stage approach was used to determine whether association signals from PGC affect miRNAs: (i) statistical assessment of enrichment using a Simes test and sum of squares test (SST) and (ii) biological evidence that quantitative trait loci (eQTL) mapping to known miRNA genes affect their expression in an independent sample of 78 postmortem brains from the Stanley Medical Research Institute. A total of 2567 independent single nucleotide polymorphisms (SNPs) (R2 > 0.8) were mapped locally, within 1 Mb, to all known miRNAs (miRBase v. 21). We show robust enrichment for SZ- and BD-related SNPs with miRNAs using Simes (SZ: p ≤ 0.0023, BD: p ≤ 0.038), which remained significant after adjusting for background inflation in SZ (empirical p = 0.018) and approached significance in BD (empirical p = 0.07). At a false discovery rate of 10%, we identified a total of 32 eQTLs to influence miRNA expression; 11 of these overlapped with BD. Our approach of integrating PGC findings with eQTL results can be used to generate specific hypotheses regarding the role of miRNAs in SZ and BD.

Statistical methods to compare batch flotation grade-recovery curves and rate constants

Grade-recovery curves obtained from kinetic batch flotation testing are, like any other measurement, subject to experimental error. This leads to uncertainty in the true position of each cumulative grade-recovery point, the curve itself, and the kinetics. This uncertainty is rarely if ever taken into account when interpreting such curves, in particular when comparing curves obtained under different conditions. This paper proposes a methodology to deal with this problem.The standard formula is used to establish true confidence intervals for the grade and recovery at each replicated timed concentrate point, and the 2-sample t-test is used to compare these point values between tests conducted under different conditions. The properties of the grade-recovery curves can be compared by fitting an appropriate model to the two data sets and using a bootstrap to create distributions of differences between the model parameters and the model predictions of recovery at any chosen concentrate grade, reflecting the uncertainty in the original data. It is then easy to construct hypothesis tests on the parameter differences and on the mean difference at the chosen grade(s) between the two curves. The same approach can be used to construct confidence intervals on the fitted curves and to test differences in estimated flotation rates. An extra sum of squares test can be used to compare the fitted grade-recovery curves as a whole. Details of the methods are presented, suitable for spreadsheets.These methods are relatively easy to apply but require that all batch flotation tests be replicated. The alternative (single tests under each condition) ignores the existence of experimental error and renders the data susceptible to subjective and perhaps erroneous interpretation. Using these methods it is not unusual to find that grade-recovery curves thought to represent truly different flotation performance are not in fact statistically different, especially at the longer flotation times (high recoveries).

DECLINE IN US OUTPUT GROWTH VOLATILITY: A WAVELET ANALYSIS*

The aim of the paper is to determine (endogenously) whether the volatility of the US output growth rate has changed since the late 1940s. By applying the discrete wavelet transform to the annualized quarter‐to‐quarter output growth series, we test the homogeneity of the variance on a scale‐by‐scale basis. A version of the Normalized and Centered Cumulative Sum of Squares test, adapted to wavelets, leads us to reject the null of constant variance in the two levels of decomposition of the highest resolution and to locate a single break in 1982. The economic implications are explored.

Alternative splicing of CTP:phosphoethanolamine cytidylyltransferase produces two isoforms that differ in catalytic properties

CTP:phosphoethanolamine cytidylyltransferase (Pcyt2) catalyzes the rate-controlling reaction of the CDP-ethanolamine (Kennedy) pathway. We have previously established that Pcyt2 is encoded by a single gene that can be alternatively spliced from an internal exon into two transcripts, designated Pcyt2alpha and Pcyt2beta. Little is currently known about the regulation of Pcyt2. Here, we functionally express both murine Pcyt2 (mPcyt2) transcripts and investigate the roles of the two proteins in the regulation of mPcyt2 activity. We demonstrate that the tagged and purified alpha and beta proteins differ significantly in their kinetic properties. The K(m) of mPcyt2alpha for phosphoethanolamine was 318.4 microM, compared with 140.3 microM for mPcyt2beta. The maximal velocities of the alpha and beta isoforms at saturating conditions for both substrates were 138.0 and 114.4 nmol/min/mumol enzyme, respectively. When phosphoethanolamine was used at a fixed concentration of 1 mM, the K(m) of mPcyt2alpha for CTP was 102.0 microM and that of mPcyt2beta was 84.09 microM. Using a combination of nondenaturing PAGE, gel filtration chromatography, and immunoprecipitation, we provide evidence that mPcyt2alpha and mPcyt2beta proteins can form both homodimeric and heterodimeric complexes. We show that alternative splicing of the mPcyt2 transcript is ubiquitous but could also be regulated in a tissue-specific manner, producing a variable ratio of mPcyt2alpha/mPcyt2beta mRNAs. The expression of two distinct protein isoforms maybe an important mechanism by which Pcyt2 activity is regulated.

Noise and the Trading Mechanism: the Case of SETS

Abstract On 20 October 1997 the London Stock Exchange introduced a new trading system called SETS. This system was to replace the dealer system SEAQ, which had been in operation since 1986. Using the iterative sum of squares test introduced by Inclan and Tiao (1994), we investigate whether there was a change in the unconditional variance of opening and closing returns, at the time SETS was introduced. We show that for the FTSE‐100 stocks traded on SETS, on the days following its introduction, there was a widespread increase in the volatility of both opening and closing returns. However, no synchronous volatility changes were found to be associated with the FTSE‐100 index or FTSE‐250 stocks. We conclude therefore that the introduction of the SETS trading mechanism caused an increase in noise at the time the system was introduced.

Effect of pH on the production of lipolyzed butter oil by a calf pregastric esterase immobilized in a hollow-fiber reactor: I. uniresponse kinetics.

A calf pregastric esterase immobilized in a hollow-fiber reactor was employed to hydrolyze milkfat, thereby producing a lipolyzed butteroil. The reaction kinetics can be modeled by a two-parameter model of the general Michaelis-Menten form based on a ping-pong bi-bi mechanism; the rate of enzyme deactivation can be modeled as a first-order reaction. The initial concentration of accessible glyceride bonds, [G](O), was estimated by complete saponification of the substrate butteroil as 2400 mM. An extra sum of squares test indicated that not only the parameters of the kinetic generalized Michaelis-Menten model, but also the deactivation-rate constant varied significantly with pH. The optimum pH, for lypolysis is near 6.0 at a temperature of 40 degrees C because at this pH the rate of deactivation of the esterase is minimized.

Determination of peroxide value in thermally oxidized crude palm oil by near infrared spectroscopy

AbstractA near infrared (NIR) spectroscopic method was developed to measure peroxide value (PV) in crude palm oil (CPO). Calibration standards were prepared by oxidizing CPO in a fermentor at 90°C. A partial least squares (PLS) calibration model for predicting PV was developed based on the NIR spectral region from 1350 to 1480 nm with reference to single‐point baseline at 1514 nm. The optimization of calibration factors was guided by the predicted residual error sum of squares test. The standard error of calibration obtained was 0.156 over the analytical range of 2.17–10.28 PV and the correlation coefficient (R2) was 0.994. The method was validated with an independent set of samples which was prepared in the same manner on a different day. A linear relationship between the American Oil Chemists’ Society and the NIR methods was obtained with R2 of 0.996 and standard error of performance of 0.17. This study has demonstrated that the prediction of PV in the NIR region is possible. The method developed is rapid, with total analysis time less than 2 min, is environmentally friendly, and its accuracy is generally good for quality control of CPO.

Tests for Distributed, Nonfocal Brain Activations

Most approaches to detecting changes in functional brain images assume that activations are focal or very localized. However, the brain's response to cognitive of sensorimotor challenge may be spatially or anatomically distributed. In this paper we consider the use-fulness of a test based on the mean sum of squares of statistical parametric maps. The performance of this test is evaluated using simulated and real data and is compared to the γ 2 test, a test of the size of the activated region, and a focal activation test based on the intensity of local maxima. We demonstrate that the mean sum of squares test is more sensitive to nonfocal signals and propose that it could be used to complement approaches that are more sensitive to focal activations.

Unweighted Sum of Squares Test for Proportions

The x2 test for proportions (or for independence in a 2 x m contingency table) requires that expected frequencies are not too small. An alternative to amalgamating low frequencies is to retain them but to give them less weight in the analysis. The resulting modified x2 test is also motivated by a likelihood argument based on a random effects model for the true proportions. The test works well in an example concerning error rates in computer records.

Determination of polychlorinated biphenyls using multiple regression with outlier detection and elimination.

A method for the analysis of capillary column polychlorinated biphenyl (PCB) data using regression analysis with outlier checking and elimination, COMSTAR, is presented and evaluated. This algorithm determines the best combination of the commercial PCB mixtures which best fits the chromatographic fingerprint of the sample by excluding weathered and contaminated PCB components from its final determination. Subsequently, significance testing on the final determination is performed. The extra sum of squares test is used for outlier testing. The chief advantage of COMSTAR over other PCB analysis method is its ability to discern more accurately the amount of PCB present in a sample when weathered and contaminated or enriched PCB components exist in the chromatographic data.