Normal Regression Research Articles

Response of a wave-dominated coastline and delta to antecedent conditioning and fluctuating rates of postglacial sea-level rise

In the context of rising sea levels, wave-dominated coasts and deltas are among the most threatened of coastal landforms. The study of submerged deltas, in tandem with other drowned wave-dominated shoreline sequences, can shed light on the long-term coastal behaviour of these threatened shorelines when subject to high-end scenarios of relative sea-level rise. Using ultra high-resolution seismic reflection data and gravity core samples, this paper investigates the post-glacial stratigraphic development and architecture of the shelf off southern Mozambique. We document several well-preserved beachrock/aeolianite palaeo-shoreline complexes from water depths of −100, −75 and −60 m, interpreted as representing the positions of former sea-level slowstands or stillstands. These overlie the regional subaerial unconformity associated with the last glacial maximum and are linked to two phases of deltaic deposition. Pro-deltaic deposits on the outer shelf were linked with the period of sea-level stability attributed to the −100 m shoreline, while proximal delta front deposits on the inner- to mid-shelf are linked to a slowstand evident in the local sea level record at −40 m. Well-developed lower delta plain facies overlie both shoreline and delta front facies and show evidence of strong channelisation during normal regression of the delta. These are overlain across the shelf by isolated and stranded pieces of the now relict shoreface, trapped to seaward by the shoreline complexes. The more proximal parts of the shelf are in turn overlain by fluvial-derived muddy facies of the current prodeltas of the area.The preservation of shoreline and delta deposits was enhanced by intervening rapid increments in sea-level rise associated with meltwater pulses 1A (−100 m) and 1B,(−60 m) though the preservation of the −75 shoreline feature, in spite of modest rates of Older Dryas base-level change, points toward other factors such as rapid cementation as dominant in this instance. The region's high sediment supply exerted a primary control on shelf preservation by dampening the erosive extent of wave-ravinement. Variations in antecedent gradient are responsible for much of the documented along-shelf and down-dip depositional variability: low-gradient settings promoted the development of broad coastal plains and strongly wave-dominated deltaic facies, while steeper areas of the shelf favoured the development of coastal landforms in relatively narrow complexes fronted by deep-water deltaic deposits. Steeper areas of the shelf also tend be characterised by an embayed along-coast profile that locally mitigates wave-energy, reinforcing the influence of inherited gradient.Once preserved, drowned coastal barriers introduced an additional geological control as post-glacial sediment became trapped between these features on the outer shelf. The dispersal of modern sediments is strongly influenced by the hydrodynamic regime Delagoa Bight, under which fluvial muds are transported northeastward along the shelf by a persistent inner-mid shelf counter-current. A considerable proportion of the modern sediment budget is lost off-shelf where the shelf narrows.This study shows that low antecedent gradients foster gentle coastal profiles predisposed to delta overstepping. Though local topographic knickpoints can aid in preserving the delta during submergence, they do not buffer the delta from the general effects of inundation which include drowning of the delta top. Once overstepped, the former delta can be overlain by distal deltaic sediments associated with the higher sea level and associated fluvial and oceanographic forcing quite different from earlier phases of delta construction.

Multiple imputation strategies for a bounded outcome variable in a competing risks analysis.

In patient follow‐up studies, events of interest may take place between periodic clinical assessments and so the exact time of onset is not observed. Such events are known as “bounded” or “interval‐censored.” Methods for handling such events can be categorized as either (i) applying multiple imputation (MI) strategies or (ii) taking a full likelihood‐based (LB) approach. We focused on MI strategies, rather than LB methods, because of their flexibility. We evaluated MI strategies for bounded event times in a competing risks analysis, examining the extent to which interval boundaries, features of the data distribution and substantive analysis model are accounted for in the imputation model. Candidate imputation models were predictive mean matching (PMM); log‐normal regression with postimputation back‐transformation; normal regression with and without restrictions on the imputed values and Delord and Genin's method based on sampling from the cumulative incidence function. We used a simulation study to compare MI methods and one LB method when data were missing at random and missing not at random, also varying the proportion of missing data, and then applied the methods to a hematopoietic stem cell transplantation dataset. We found that cumulative incidence and median event time estimation were sensitive to model misspecification. In a competing risks analysis, we found that it is more important to account for features of the data distribution than to restrict imputed values based on interval boundaries or to ensure compatibility with the substantive analysis by sampling from the cumulative incidence function. We recommend MI by type 1 PMM.

Corrigendum to “Forced or normal regression signals in a lacustrine basin? Insights from 3D stratigraphic forward modeling in the SW Pannonian Basin” [Global and Planetary Change, 196 (2021), in press

Corrigendum to “Forced or normal regression signals in a lacustrine basin? Insights from 3D stratigraphic forward modeling in the SW Pannonian Basin” [Global and Planetary Change, 196 (2021), in press

MODELLING OF THE IMPACT OF FREE TRADE ON THE ECONOMIC DEVELOPMENT OF THE COUNTRY

The article reveals the essence of the concept of "free trade" and identifies the main tools of this policy. The method of calculating the index of free trade is studied, the dynamics of the index of free trade of Ukraine for 2011-2020 and the dynamics of the components of this index are analyzed. Determining the impact of key factors on the level of GDP with the help of economic and mathematical tools allows you to form and propose ways to increase the level of economic development for Ukraine. Purpose. The aim of the study is to assess the impact of free trade on the development of the country's economy using methods of economic and mathematical modeling. Method (methodology). To study the impact of free trade on the economic development of the country, several models based on panel data were built. Gross domestic product was chosen as the result variable, with independent factors such as exports and imports, inflation, net foreign direct investment, labor, and the free trade index. In the study of panel data, the normal regression model (combined), the fixed effects model, and the random effects model were constructed. The constructed models were tested using the Hausman, Broysch-Pagan and Wald test. The comparative analysis of modeling results is carried out. Results. The results showed the high accuracy of the constructed models and show that free trade, expressed by the index of free trade, has a negative impact on the economic development of the country, expressed in gross domestic product.

Model diagnostics for censored regression via randomized survival probabilities

Residuals in normal regression are used to assess a model's goodness-of-fit (GOF) and discover directions for improving the model. However, there is a lack of residuals with a characterized reference distribution for censored regression. In this article, we propose to diagnose censored regression with normalized randomized survival probabilities (RSP). The key idea of RSP is to replace the survival probability (SP) of a censored failure time with a uniform random number between 0 and the SP of the censored time. We prove that RSPs always have the uniform distribution on (0, 1) under the true model with the true generating parameters. Therefore, we can transform RSPs into normally distributed residuals with the normal quantile function. We call such residuals by normalized RSP (NRSP residuals). We conduct simulation studies to investigate the sizes and powers of statistical tests based on NRSP residuals in detecting the incorrect choice of distribution family and nonlinear effect in covariates. Our simulation studies show that, although the GOF tests with NRSP residuals are not as powerful as a traditional GOF test method, a nonlinear test based on NRSP residuals has significantly higher power in detecting nonlinearity. We also compared these model diagnostics methods with a breast-cancer recurrent-free time dataset. The results show that the NRSP residual diagnostics successfully captures a subtle nonlinear relationship in the dataset, which is not detected by the graphical diagnostics with CS residuals and existing GOF tests.

Analysis of SF-6D Health State Utility Scores: Is Beta Regression Appropriate?

Background: Typically, modeling of health-related quality of life data is often troublesome since its distribution is positively or negatively skewed, spikes at zero or one, bounded and heteroscedasticity. Objectives: In the present paper, we aim to investigate whether Bayesian beta regression is appropriate for analyzing the SF-6D health state utility scores and respondent characteristics. Methods: A sample of 126 Lebanese members from the American University of Beirut valued 49 health states defined by the SF-6D using the standard gamble technique. Three different models were fitted for SF-6D via Bayesian Markov chain Monte Carlo (MCMC) simulation methods. These comprised a beta regression, random effects and random effects with covariates. Results from applying the three Bayesian beta regression models were reported and compared based on their predictive ability to previously used linear regression models, using mean prediction error (MPE), root mean squared error (RMSE) and deviance information criterion (DIC). Results: For the three different approaches, the beta regression model was found to perform better than the normal regression model under all criteria used. The beta regression with random effects model performs best, with MPE (0.084), RMSE (0.058) and DIC (−1621). Compared to the traditionally linear regression model, the beta regression provided better predictions of observed values in the entire learning sample and in an out-of-sample validation. Conclusions: Beta regression provides a flexible approach to modeling health state values. It also accounted for the boundedness and heteroscedasticity of the SF-6D index scores. Further research is encouraged.

Forced or normal regression signals in a lacustrine basin? Insights from 3D stratigraphic forward modeling in the SW Pannonian Basin

Abstract The overall geometry of sedimentary basins is driven by a complex interplay between subsidence, water-level variations, sedimentation rates and basin-margin topography. Seaward movement of the shoreline is driven by either high sediment input or by base-level drop. The influence of the specific driving mechanisms is often overwritten by subsequent burial and compaction effects or it is below the resolution of observational data. Our main aim is to describe and discuss the influence of these internal and external forcing factors and demonstrate their sedimentary response, particularly the related unconformities and clinoform geometries in a deep lacustrine setting. To this aim, 3D numerical simulations were performed using DionisosFlow stratigraphic forward modeling software. Models are constrained by seismic and well data from the Drava Basin part of the SW Pannonian Basin, Central Europe. A wide range of parameters, such as subsidence rates, lake-level curves and sedimentation rates were compared and analyzed. Post-rift subsidence and inversion of the basin have been simulated together with the main sedimentary transport routes. Our calculation infers that paleo-water depth could have reached ca. 1300 m in the deepest parts of the basin. Furthermore, our models show that differential compaction, subsidence and lateral variations of the sediment supply result in apparently descending shelf-edge trajectories and onlapping clinoform surfaces that are often misinterpreted as base-level drops. By analyzing the sedimentary response to different climatic variations, we argue that there is no direct indication of a major base-level drop in the Drava Basin, which was much larger than the seismic resolution, i.e. 40–50 m. Modeling also infers that autoretreat and autocyclic variations are more effective at low sediment supply and higher amplitude lake-level variations.

Bayesian information criterion approximations to Bayes factors for univariate and multivariate logistic regression models.

Schwarz's criterion, also known as the Bayesian Information Criterion or BIC, is commonly used for model selection in logistic regression due to its simple intuitive formula. For tests of nested hypotheses in independent and identically distributed data as well as in Normal linear regression, previous results have motivated use of Schwarz's criterion by its consistent approximation to the Bayes factor (BF), defined as the ratio of posterior to prior model odds. Furthermore, under construction of an intuitive unit-information prior for the parameters of interest to test for inclusion in the nested models, previous results have shown that Schwarz's criterion approximates the BF to higher order in the neighborhood of the simpler nested model. This paper extends these results to univariate and multivariate logistic regression, providing approximations to the BF for arbitrary prior distributions and definitions of the unit-information prior corresponding to Schwarz's approximation. Simulations show accuracies of the approximations for small samples sizes as well as comparisons to conclusions from frequentist testing. We present an application in prostate cancer, the motivating setting for our work, which illustrates the approximation for large data sets in a practical example.

Modeling paleogeographic scenarios of the last glacial cycle as a base for source-to-sink studies: An example from the northwestern shelf of the South China Sea

Sea-level (SL) data from the Last Glacial Cycle (LGC) have been superimposed on to digital elevation models of the South China Sea (SCS) and adjacent areas, to generate regional paleogeographic scenarios related to 4th- to 5th-order Milankovitch climate cycles. These scenarios—at 123, 65, 60.5, 56, 20, and 0.5 kyr BP—showed that the SCS functioned as an oceanographic interface between the Pacific and Indian oceans during the LGC. A Late Pleistocene paleo-river delta (Hainan delta) offshore west of Hainan Island (China) was an important sediment routing system on the NW shelf of the SCS. To understand the origin of the Hainan delta better, paleo-reliefs of DEM56kyrBP and DEM65kyrBP were reconstructed, using seismic stratigraphy, sedimentology, and back-stripping methods. Geostatistical and geometric models of clinoforms and delta geometry, as well as the courses of the reconstructed paleo-distributary channels and paleo-river valleys, supported the interpretation that most delta sediment could be regarded as erosional products from Hainan Island. We hypothesized that an intensification of sediment supply outpaced SL rise during the Marine Isotopic Stages 4/3 transition, resulting in a normal regression during the formation of the Hainan delta. Morphodynamic modeling and meteorological data reanalysis further supported our interpretation that shifts in the Asian Monsoon system—combined with local meteorological effects on Hainan Island and with global SL changes—were the main drivers for the sediment source-to-sink systems at the NW SCS continental margin, during the LGC.

Absolute Quantitation of Cardiac 99mTc-Pyrophosphate Using Cadmium-Zinc-Telluride–Based SPECT/CT

The primary aims of this study were to determine the correlation between absolute quantitative 99mTc-pyrophosphate metrics and traditional measures of cardiac amyloid burden and to measure the intraobserver repeatability of the quantitative metrics. Methods: We studied 72 patients who underwent 99mTc-pyrophosphate SPECT/CT using a novel general-purpose cadmium-zinc-telluride-based SPECT/CT system. The clinical standard for these studies is visual grading (with grades of 0, 1, 2, and 3 indicating myocardial uptake absent, less than rib uptake, equal to rib uptake, or more than rib uptake, respectively). A visual grade of 2 or more was considered positive. For 72 patients, SUVmax, SUVmean, cardiac amyloid activity (CAA; i.e., SUVmean × left ventricular [LV] volume), and percentage injected dose (%ID) were calculated, and visual grading was performed. The correlation was determined between the 4 quantitative metrics or visual grades and the LV mass index (LVMI) (indexed to body surface area on echocardiography, 67 patients). For a subset of 11 patients, the correlation was determined between the visual or quantitative metrics and the extracellular volume (ECV) on cardiac MRI. Normal linear regression was used to compare the standardized association of each of the 4 quantitative metrics with LVMI, as a surrogate for amyloid burden. Receiver-operating-characteristic curve analysis was used to determine the diagnostic accuracy of quantitative metrics, using visual grading as the reference standard. The intraobserver repeatability of generating quantitative metrics was also determined. Results: All 4 quantitative metrics were highly accurate, with an area under the receiver-operating-characteristic curve of more than 0.96 for diagnosis of transthyretin cardiac amyloidosis. SUVmax, SUVmean, CAA, %ID, and visual grade were moderately positively correlated with LVMI (r = 0.485 for %ID) and strongly positively correlated, albeit in a small cohort, with ECV (r = 0.873, SUVmax). Intraobserver repeatability was excellent, with less than a 2% coefficient of variation for SUVmax, %ID, and CAA and 3.8% for SUVmean All 4 quantitative metrics had a standardized effect of more than 0.324 on LVMI; the largest standardized effect was 0.485, for %ID. Conclusion: In this first (to our knowledge) study of 99mTc-pyrophosphate cardiac imaging using a novel cadmium-zinc-telluride SPECT/CT scanner, SUVmax, SUVmean, CAA, and %ID measured by absolute quantitation of 99mTc-pyrophosphate were moderately correlated with LVMI and strongly correlated, albeit in a small cohort, with ECV. The intraobserver repeatability of generating the quantitative metrics was excellent.

Model Averaging and Its Use in Economics

The method of model averaging has become an important tool to deal with model uncertainty, for example in situations where a large amount of different theories exist, as are common in economics. Model averaging is a natural and formal response to model uncertainty in a Bayesian framework, and most of the paper deals with Bayesian model averaging. The important role of the prior assumptions in these Bayesian procedures is highlighted. In addition, frequentist model averaging methods are also discussed. Numerical techniques to implement these methods are explained, and I point the reader to some freely available computational resources. The main focus is on uncertainty regarding the choice of covariates in normal linear regression models, but the paper also covers other, more challenging, settings, with particular emphasis on sampling models commonly used in economics. Applications of model averaging in economics are reviewed and discussed in a wide range of areas including growth economics, production modeling, finance and forecasting macroeconomic quantities. (JEL C11, C15, C20, C52, O47).

DIFFERENTIAL OVARIAN RESPONSE TO GONADOTROPIN PREPARATIONS DESPITE SIMILAR OVARIAN RESERVE: MENOPUR IN GNRH (GONADOTROPIN RELEASING HORMONE) ANTAGONIST SINGLE EMBRYO TRANSFER - HIGH RESPONDER (MEGASET-HR) TRIAL ANALYSIS

Assess possible interactions between treatment group [highly-purified human menopausal gonadotropin (HP-hMG) or recombinant follicle stimulation hormone (r-FSH)] and ovarian reserve as indicated by baseline levels of anti-Müllerian Hormone (AMH) on the number of oocytes retrieved. Post-hoc analysis of a randomized, open-label, assessor-blind, non-inferiority trial conducted at 31 U.S. trials sites. 620 ovulatory women aged 21-35y with BMI 18-30 kg/m2 and serum anti-Müllerian hormone (AMH) ≥5 ng/mL were randomized 1:1 to a 150 IU start dose of HP-hMG (N=311) or rFSH (N=309) in a GnRH antagonist cycle with dose adjustments based upon response from day 6 onward. Human chorionic gonadotropin (hCG) was used to trigger oocyte maturation (GnRH agonist if at high risk of ovarian hyperstimulation syndrome [OHSS]). Central laboratory serum hormone measurements were measured at baseline and stimulation days: 6, day of/after trigger. Fresh transfer of a single blastocyst was performed in hCG-triggered cycles; all embryos were frozen if the risk of OHSS was high. Live births resulting from all fresh and any frozen transfers occurring within 6 months of randomization were collected. A normal regression model was used to explore interactions between treatment group and baseline AMH on the number of oocytes retrieved. Demographics across treatment arms were similar (mean patient age: 30 years for both; HP-hMG, rFSH mean [SD] BMI: 24.4 [3.3], 24.3 [3.4] kg/m2; AMH: 7.8 [3.6], 7.5 [2.4] ng/mL; antral follicle count: 30.5 [15.5], 31.0 [12.2]). The average number of oocytes per patient in the rFSH arm (22.2 [11.54]) was significantly higher than in the HP-hMG arm (15.1 [10.12]) as were serum estradiol levels at stimulation days 6 and trigger and OHSS rates, described previously.1 Cumulative live birth rates were similar between treatment groups at 51.5% and 50.6% in rFSH and HP-hMG arms respectively. A positive effect of baseline AMH levels on the number of oocytes retrieved was identified and differed statistically by treatment group (p value=0.032); subjects with higher baseline level of AMH had a larger ovarian response to rFSH versus HP-hMG. For every 1.6 ng/ml (11.1 pmol/L) increase in baseline AMH, rFSH stimulation results in one extra oocyte versus HP-hMG in predicted high-responders. Increasing baseline AMH was associated with higher oocyte yields but no difference in cumulative live birth rates in rFSH vs HP-hMG treated patients, with an accompanying increase in OHSS rates also observed in the rFSH arm. This unexpectedly exaggerated ovarian response, which is positively correlated with increasing ovarian reserve based upon the well-established biomarker AMH, highlights a key distinction between the gonadotropin preparations evaluated, creating opportunities for further optimization of stimulation.

Stabilized combustion of circular fuel duct with liquid oxygen

This research is an investigation of the flame spread opposed to a liquid oxidizer flow in a solid fuel duct. Several firing tests were conducted using liquid oxygen as the oxidizer and solid poly methyl methacrylate (PMMA) as the fuel. The results indicate that the flame spread rate decreased with increasing oxidizer port velocity and decreasing port diameter. This study reveals through visual confirmations and empirical correlations of the flame spread rate that the flame spread opposed to liquid oxygen in a solid fuel duct can be classified as stabilized combustion. Extinction and abnormal regression were observed when oxidizer port velocity was high and port diameter was small. Furthermore, the cooling of the solid fuel by the liquid oxygen flow had a strong effect on the transition between normal regression and extinction, or abnormal regression. A model of the flame spread rate which considers the heat balance at the fuel surface assuming a fully developed thermal boundary layer is introduced and shown to agree well with the experimental results. Lastly, it is revealed that the difference in kinematic viscosity between liquid oxygen and gaseous oxygen is the main reason dependency of port diameter on flame spread rates differs between the liquid oxygen tests in this study and gaseous oxygen tests in previous studies.

Predicting adulteration of Palm oil with Sudan IV dye using shortwave handheld spectroscopy and comparative analysis of models

Shortwave handheld NIR spectroscopy coupled with multivariate algorithm was attempted to simultaneously classify and measure Sudan IV dye adulteration in palm oil samples. K-nearest neighbour (KNN) was used to develop a classification model to discriminate between authentic palm oil samples and Sudan IV dye adulterated (0.10−0.002 % w/w) ones. Principal component regression (PCR), partial least square regression (PLSR) and support vector machine regression (SVMR) algorithms were comparatively employed to quantify the addition of Sudan IV dye in authentic palm oil samples. The models were evaluated by the classification rate (R), correlation co-efficient in the calibration set/prediction set (Rp2/Rc2), and root mean square error of calibration/prediction (RMSEC/P). The developed multiplicative scatter correction plus KNN technique was found to accurately classify where R = 95.48 % and 97.00 % in the calibration set and prediction set respectively. Among the quantification model developed for measuring Sudan IV dye, standard normal variant preprocessing plus partial least square regression (SNV-PLSR) gave the best performance at Rc2 = 0.91, Rp2 = 0.90 and RMSEC = 0.0841, RMSEP = 0.0868 while standard normal variant preprocessing plus principal component regression gave Rc2 = 0.90, Rp2 = 0.90 and RMSEC = 0.0846, RMSEP = 0.870. The findings have proved that, the integrity of palm oil samples can be certified rapidly and nondestructively in terms of the presence of Sudan IV by using short wave handheld NIR spectroscopy. This offers the opportunity for incorporating NIR spectroscopy into mobile phone devices to enhance mobile detection.

A comparison of residual diagnosis tools for diagnosing regression models for count data

BackgroundExamining residuals is a crucial step in statistical analysis to identify the discrepancies between models and data, and assess the overall model goodness-of-fit. In diagnosing normal linear regression models, both Pearson and deviance residuals are often used, which are equivalently and approximately standard normally distributed when the model fits the data adequately. However, when the response vari*able is discrete, these residuals are distributed far from normality and have nearly parallel curves according to the distinct discrete response values, imposing great challenges for visual inspection.MethodsRandomized quantile residuals (RQRs) were proposed in the literature by Dunn and Smyth (1996) to circumvent the problems in traditional residuals. However, this approach has not gained popularity partly due to the lack of investigation of its performance for count regression including zero-inflated models through simulation studies. Therefore, we assessed the normality of the RQRs and compared their performance with traditional residuals for diagnosing count regression models through a series of simulation studies. A real data analysis in health care utilization study for modeling the number of repeated emergency department visits was also presented.ResultsOur results of the simulation studies demonstrated that RQRs have low type I error and great statistical power in comparisons to other residuals for detecting many forms of model misspecification for count regression models (non-linearity in covariate effect, over-dispersion, and zero inflation). Our real data analysis also showed that RQRs are effective in detecting misspecified distributional assumptions for count regression models.ConclusionsOur results for evaluating RQRs in comparison with traditional residuals provide further evidence on its advantages for diagnosing count regression models.

Adoption of crop insurance in Ghana: an application of the complementary log-log truncated Poisson double-hurdle model

PurposeThe aim of this paper is to identify the factors that influence rice farmers' decisions to adopt crop insurance and premium payments (willingness to pay [WTP] amounts). The paper also demonstrates the usefulness of the complementary log-log (cloglog) truncated Poisson double-hurdle model as an alternative hurdle model.Design/methodology/approachThe study first investigated the nature of the dependent variable, which had non-normal residuals and was overdispersed. The probit truncated normal regression double-hurdle model was tried but it failed the normality and homoscedasticity tests; hence, the cloglog truncated Poisson double-hurdle model was employed in the study.FindingsAn estimated 61% of respondents would purchase crop insurance, despite farmers not having prior experience with this product. Amongst others, the factors that influence insurance adoption amongst rice farmers are the share of rice in total income, reliability perception of crop insurance schemes and the probability of failure to achieve target yields. The latter helps the authors to address adverse selection, a central issue to the viability of such an insurance programme. The determinants of farmers' WTP are also identified.Research limitations/implicationsSampling was limited to farmers using irrigation and living in one region of Ghana, which may limit the study’s wider applicability.Originality/valueAs far as the authors are aware, this study is the first to select the appropriate hurdle model based on established properties of the dependent variable on this topic – crop insurance decisions.

Efektivitas E-Service Quality dan Customer Feedback terhadap Keputusan Menggunakan Aplikasi Reddoorz

The purpose of this study was to determine how consumers’ decisions in using the RedDoorz application, and to find out how the effectiveness of e-service quality in the RedDoorz application as well as customer feedback on the RedDoorz application. This research uses descriptive and associative methods and uses a nonprobability sampling technique that's is purposive sampling. By distributing questionnaires to 130 respondents with a survey on the city of Sukabumi, data collection was done by collecting primary and secondary data, researchers conducted questionnaires testing using validity and reliability tests, also using the classic assumption test that is the Kolmogorov Smirnov normality test to determine residual values normal or reverse regression. The data analysis technique used is a simple correlation coefficient, multiple correlation coefficient, simple linear regression, multiple linear regression, and hypothesis testing using a partial test ( T-test) and simultaneous test ( F test). From the results of the questionnaire, analysis can be declared valid and reliable, as well as the results in testing the normality test of the total population expressed normal distribution. The results of the analysis conducted by researchers are the influence of e-service quality on decision using the RedDoorz application, also the influence of customer feedback on decision using the RedDoorz application, decision using the application can be explained by e-service quality can also be explained by customer feedback, including in the simultaneous test of e-service quality and customer feedback both influence the decision to use the RedDoorz application.

Screening of factors affecting somatic callusing and embryo induction in Allium cepa L. through Plackett–Burman methodology

Induction of embryonic callus through available asexual explant culture is applied in the protection and maintenance of cytoplasmic-male sterility and in the maintenance of other lines of onion (Allium cepa L.). Usage of the Plackett?Burman (PB) experimental design has been suggested as a screening method for many variables that influence the desired induction. In order to overcome limitations of standard experimental designs and prioritization of media culture components, a systematic investigation was carried out using the PB design. In this investigation, the effects of different factors such as 2,4-D, putrescine, carbohydrate sources (maltose, sorbitol, and sucrose), silver nitrate, glutamine, and glycine concentrations were assayed on callus and embryo induction through mature zygotic embryo explant culture. Out of the eight medium components screened, the four components of putrescine, glutamine, 2,4-D, and glycine were found to contribute positively to the callus production with a maximum production rate of 97.14%. The normal plot and linear regression equation with positive largest coefficient showed that putrescine had the highest significant positive effect with 200 mg/L and three elements comprising 2,4-D and glycine showing a significant reducing effect on callus induction. In embryonic callus induction, a wide range of responses were observed from 0% to 100% in the 21 trials. Results of linear regression data showed that among the eight elements, 2,4-D, glutamine, and glycine had significant effects on embryo production. Glycine and 2,4-D had the highest (26.34%) and the lowest (8.33%) contribution to explaining embryonic callus induction, respectively. A wide range of responses (0 to 44.1 mg) were observed in the Plackett-Burman design with respect to the fresh weight. The regression analysis for the Plackett-Burman design (PBD) demonstrated that glycine, sorbitol, and sucrose were of high influence on the fresh weight (P ≤ 0.05). Glycine (31.4%) and sucrose (6.7%) were found to have the highest and lowest contribution to the fresh weight of callus, respectively. Thus, this practical article seeks to show some helpful statistical approaches to typical problems in data analyses of tissue culture research.

How much systems-tract scale, three-dimensional stratigraphic variability is present in sequence stratigraphy?: An answer from the middle Miocene Pearl River Mouth Basin

Prior sequence stratigraphic methods mainly employed two-dimensional (2-D) stacking patterns to reconstruct stratigraphic frameworks. The future of sequence stratigraphy will pay more attention to systems-tracts scale and three-dimensional (3-D) stratigraphic variability. Using 1.2 × 104 km2 (4.63 × 103 mi2) 3-D seismic data, tied to regional 2-D seismic lines and 21 boreholes, the present study examines systems-tract scale and 3-D stratigraphic variability of the 14.8–13.8 Ma Pearl River shelf-margin to deep-water sedimentary prisms. The studied prisms were divided into four main systems tracts, namely, highstand systems tract (HST), falling-stage systems tract (FSST), lowstand systems tract (LST), and transgressive systems tract (TST). Each systems tract is represented by a given clinoformal architecture and stacking pattern: (1) clinothem sets with aggradation to progradation are HST, (2) clinothem sets with progradation to degradation (PD) are FSST, (3) clinothem sets with progradation to aggradation (PA) are LST, and (4) clinothem sets with retrogradation are TST, LST, or HST. In addition, Pearl River FSST and LST display downdip stratigraphic variabilities which are regionally manifested in at least three ways: (1) shelf-edge deltas linked downdip to basin-floor fans, (2) shelf-edge deltas linked downdip without fans, and (3) basin-floor fans linked updip that lack deltas. In along-strike orientation, the Pearl River FSST could exhibit low-angle progradation, not just PD stacking. The LST could present retrogradational stacking, not just PA stacking. Therefore, the physical position of a systems tract is reemphasized in terms of assigning a given systems tract. The concepts of three systems tracts are then revised for chronostratigraphic significance. The LST is the lowermost systems tract of a sequence, presenting a normal regression of the shoreline as its diagnostic characteristic and including contemporaneous stratigraphic units laterally. The HST is the upper systems tract of a sequence, providing a normal regression of the shoreline as its diagnostic characteristic and including contemporaneous stratigraphic units laterally. The TST is the middle systems tract of a sequence, generating a backstep of the shoreline and excluding contemporaneous onlapping units of both the LST and HST laterally. The FSST has not been revised because FSST may be a supply-independent feature.

The Migratory Properties and Numbers of T Regulatory Cell Subsets in Circulation Are Differentially Influenced by Season and Are Associated With Vitamin D Status.

The control of peripheral immune responses by FOXP3+ T regulatory (Treg) cells is essential for immune tolerance. However, at any given time, Treg frequencies in whole blood can vary more than fivefold between individuals. An understanding of factors that influence Treg numbers and migration within and between individuals would be a powerful tool for cellular therapies that utilize the immunomodulatory properties of Tregs to control pathology associated with inflammation. We sought to understand how season could influence Treg numbers and phenotype by monitoring the proportion of natural thymus-derived Tregs (nTregs) defined as (CD3+CD4+CD25+FOXP3+CD127–/low) cells as a proportion of CD4+ T cells and compared these to all FOXP3+ Tregs (allTregs, CD3+CD25+FOXP3+CD127–/low). We were able to determine changes within individuals during 1 year suggesting an influence of season on nTreg frequencies. We found that, between individuals at any given time, nTreg/CD4+ T cells ranged from 1.8% in February to 8.8% in the summer where median nTreg/CD4 in January and February was 2.4% (range 3.75–1.76) and in July and August was 4.5% (range 8.81–3.17) p = 0.025. Importantly we were able to monitor individual nTreg frequencies throughout the year in donors that started the year with high or low nTregs. Some nTreg variation could be attributed to vitamin D status where normal linear regression estimated that an absolute increase in nTreg/CD4+ by 0.11% could be expected with 10 nmol increase in serum 25 (OH) vitamin D3 (p = 0.005, 95% CI: 0.03–0.19). We assessed migration markers on Tregs for the skin and/or gut. Here cutaneous lymphocyte associated antigen (CLA+) expression on CD25+FOXP3+CD4+/CD4+ was compared with the same population expressing the gut associated integrin, β7. Gut tropic CD25+FOXP3+β7+Tregs/CD4+ had similar dynamics to nTreg/CD4+. Conversely, CD25+FOXP3+CLA+Tregs/CD4+ showed no association with vitamin D status. Important for cellular therapies requiring isolation of Tregs, the absolute number of β7+CD4+CD25+FOXP3+Tregs was positively associated with 25(OH)vitamin D3 (R2 = 0.0208, r = 0.184, p = 0.021) whereas the absolute numbers of CLA+CD4+CD25+FOXP3+Tregs in the periphery were not influenced by vitamin D status. These baseline observations provide new opportunities to utilize seasonal variables that influence Treg numbers and their migratory potential in patients or donors.