On two-sample data analysis by exponential model

We discuss two-sample problems and the implementation of a new two-sample data analysis procedure. The proposed procedure is based on the concepts of mid-distribution, design of score functions, components, comparison distribution, comparison density and exponential model. Assume that we have a random sample X1, . . . ,Xm from a continuous distribution F(y) = P(Xi y), i = 1, . . . ,m and a random sample Y1, . . . ,Yn from a continuous distribution G(y) = P(Yi y), i = 1, . . . ,n. Also assume independence of the two samples. The two-sample problem tests homogeneity of two samples and formally can be stated as H0 : F = G. To solve the two-sample problem, a number of tests have been proposed by statisticians in various contexts. Two typical tests are the two-sample t?test and the Wilcoxon's rank sum test. However, since they are testing differences in locations, they do not extract more information from the data as well as a test of the homogeneity of the distribution functions. Even though the Kolmogorov-Smirnov test statistic or Anderson-Darling tests can be used for the test of H0 : F = G, those statistics give no indication of the actual relation of F to G when H0 : F = G is rejected. Our goal is to learn why it was rejected. Our approach gives an answer using graphical tools which is a main property of our approach. Our approach is functional in the sense that the parameters to be estimated are probability density functions. Compared with other statistical tools for two-sample problems such as the t-test or the Wilcoxon rank-sum test, density estimation makes us understand the data more fully, which is essential in data analysis. Our approach to density estimation works with small sample sizes, too. Also our methodology makes almost no assumptions on two continuous distributions F and G. In that sense, our approach is nonparametric. Our approach gives graphical elements in two-sample problem where exist not many graphical elements typically. Furthermore, our procedure will help researchers to make a conclusion as to why two populations are different when H0 is rejected and to give an explanation to describe the relation between F and G in a graphical way

Norie (Game)

Korean culture the lives of children in past generations were strongly influenced by folk song. They heard their mother's lullabies and later sang those songs with their peers. Such songs can be called Korean children's folk songs. These songs are anonymous and are not bound by any forms or lyrical rules. Orally taught and handed down from generation to generation, they typically use only 4-5 pitches. My piece Norie ("Game," in Korean) is based on a famous children's game song, "Yeo-u-ya Yeo-u-ya, Mo-ha-ni?" (Fox, Fox, What Are You Doing?). Children in the game pick one "Fox" and ask questions, which the Fox must answer while singing the song. The lyrics are "Over the first hill, there is no Fox, over the second hill, there is no Fox, over the third hill, there is a Fox" and the Fox is questioned. "Fox, Fox, What are you doing?" "I am sleeping." "Sleepyhead." "I am washing." "Dandy." "I am eating." "What are you eating?" "It's a Frog." "Dead or alive?" "It's alive (dead)." If the Fox says "It's alive," then children run away. When the Fox catches one of the players, the game continues with a new Fox. Norie (Game) is a set of Variations for orchestra using this folk song as a theme and a point of departure. Three Clarinets present the theme after the introduction of 45 measures. The scene in which children run away after hearing "It's alive" is presented at rehearsal mark C. From rehearsal D there are five variations incorporating inverted intervals, varied rhythms, varied modes, several points of imitation, and various ostinato, a repeated pattern, techniques. The third variation (rehearsal mark I) is a slow section in which the folk tune is presented by Marimba and strings. In the final measures each instrument plays the question "Dead or alive?" in different rhythms and Norie concludes with the answer, "It's alive.

On two-sample data analysis by exponential model

We discuss two-sample problems and the implementation of a new two-sample data analysis procedure. The proposed procedure is based on the concepts of mid-distribution, design of score functions, components, comparison distribution, comparison density and exponential model. Assume that we have a random sample X1, . . . ,Xm from a continuous distribution F(y) = P(Xi y), i = 1, . . . ,m and a random sample Y1, . . . ,Yn from a continuous distribution G(y) = P(Yi y), i = 1, . . . ,n. Also assume independence of the two samples. The two-sample problem tests homogeneity of two samples and formally can be stated as H0 : F = G. To solve the two-sample problem, a number of tests have been proposed by statisticians in various contexts. Two typical tests are the two-sample t?test and the Wilcoxon's rank sum test. However, since they are testing differences in locations, they do not extract more information from the data as well as a test of the homogeneity of the distribution functions. Even though the Kolmogorov-Smirnov test statistic or Anderson-Darling tests can be used for the test of H0 : F = G, those statistics give no indication of the actual relation of F to G when H0 : F = G is rejected. Our goal is to learn why it was rejected. Our approach gives an answer using graphical tools which is a main property of our approach. Our approach is functional in the sense that the parameters to be estimated are probability density functions. Compared with other statistical tools for two-sample problems such as the t-test or the Wilcoxon rank-sum test, density estimation makes us understand the data more fully, which is essential in data analysis. Our approach to density estimation works with small sample sizes, too. Also our methodology makes almost no assumptions on two continuous distributions F and G. In that sense, our approach is nonparametric. Our approach gives graphical elements in two-sample problem where exist not many graphical elements typically. Furthermore, our procedure will help researchers to make a conclusion as to why two populations are different when H0 is rejected and to give an explanation to describe the relation between F and G in a graphical way

Detection of Absorbing Aerosol Using Single Near-UV Radiance Measurements from a Cloud and Aerosol Imager

The Ultra-Violet Aerosol Index (UVAI) is a practical parameter for detecting aerosols that absorb UV radiation, especially where other aerosol retrievals fail, such as over bright surfaces (e.g., deserts and clouds). However, typical UVAI retrieval requires at least two UV channels, while several satellite instruments, such as the Thermal And Near infrared Sensor for carbon Observation Cloud and Aerosol Imager (TANSO-CAI) instrument onboard a Greenhouse gases Observing SATellite (GOSAT), provide single channel UV radiances. In this study, a new UVAI retrieval method was developed which uses a single UV channel. A single channel aerosol index (SAI) is defined to measure the extent to which an absorbing aerosol state differs from its state with minimized absorption by aerosol. The SAI qualitatively represents absorbing aerosols by considering a 30-day minimum composite and the variability in aerosol absorption. This study examines the feasibility of detecting absorbing aerosols using a UV-constrained satellite, focusing on those which have a single UV channel. The Vector LInearized pseudo-spherical Discrete Ordinate Radiative Transfer (VLIDORT) was used to test the sensitivity of the SAI and UVAI to aerosol optical properties. The theoretical calculations showed that highly absorbing aerosols have a meaningful correlation with SAI. The retrieved SAI from OMI and operational OMI UVAI were also in good agreement when UVAI values were greater than 0.7 (the absorption criteria of UVAI). The retrieved SAI from the TANSO-CAI data was compared with operational OMI UVAI data, demonstrating a reasonable agreement and low rate of false detection for cases of absorbing aerosols in East Asia. The SAI retrieved from TANSO-CAI was in better agreement with OMI UVAI, particularly for the values greater than the absorbing threshold value of 0.7

Network-Level Structural Abnormalities of Cerebral Cortex in Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (T1DM) usually begins in childhood and adolescence and causes lifelong damage to several major organs including the brain. Despite increasing evidence of T1DM-induced structural deficits in cortical regions implicated in higher cognitive and emotional functions, little is known whether and how the structural connectivity between these regions is altered in the T1DM brain. Using inter-regional covariance of cortical thickness measurements from high-resolution T1-weighted magnetic resonance data, we examined the topological organizations of cortical structural networks in 81 T1DM patients and 38 healthy subjects. We found a relative absence of hierarchically high-level hubs in the prefrontal lobe of T1DM patients, which suggests ineffective top-down control of the prefrontal cortex in T1DM. Furthermore, inter-network connections between the strategic/executive control system and systems subserving other cortical functions including language and mnemonic/emotional processing were also less integrated in T1DM patients than in healthy individuals. The current results provide structural evidence for T1DM-related dysfunctional cortical organization, which specifically underlie the top-down cognitive control of language, memory, and emotion. © 2013 Lyoo et al

Basic Fibroblast Growth Factor Activates MEK/ERK Cell Signaling Pathway and Stimulates the Proliferation of Chicken Primordial Germ Cells

BACKGROUND: Long-term maintenance of avian primordial germ cells (PGCs) in vitro has tremendous potential because it can be used to deepen our understanding of the biology of PGCs. A transgenic bioreactor based on the unique migration of PGCs toward the recipients' sex cord via the bloodstream and thereby creating a germline chimeric bird has many potential applications. However, the growth factors and the signaling pathway essential for inducing proliferation of chicken PGCs are unknown. METHODOLOGY/PRINCIPAL FINDINGS: Therefore, we conducted this study to investigate the effects of various combinations of growth factors on the survival and proliferation of PGCs under feeder-free conditions. We observed proliferation of PGCs in media containing bFGF. Subsequent characterization confirmed that the cultured PGCs maintained expression of PGC-specific markers, telomerase activity, normal migrational activity, and germline transmission. We also found that bFGF activates the mitogen-activated protein kinase kinase/extracellular-signal regulated kinase (MEK/ERK) signaling. Also, the expression of 133 transcripts was reversibly altered by bFGF withdrawal. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that chicken PGCs can be maintained in vitro without any differentiation or dedifferentiation in feeder free culture conditions, and subsequent analysis revealed that bFGF is one of the key factors that enable proliferation of chicken PGCs via MEK/ERK signaling regulating downstream genes that may be important for PGC proliferation and survival

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning models for the prediction of massive hemorrhage and a scoring system which is applicable to new patients. Data were retrospectively collected from patients aged >18 years who had undergone liver transplantation. These data included emergency information, donor information, demographic data, preoperative laboratory data, the etiology of hepatic failure, the Model for End-stage Liver Disease (MELD) score, surgical history, antiplatelet therapy, continuous renal replacement therapy (CRRT), the preoperative dose of vasopressor, and the estimated blood loss (EBL) during surgery. The logistic regression model was one of the best-performing machine learning models. The most important factors for the prediction of massive hemorrhage were the disease etiology, activated partial thromboplastin time (aPTT), operation duration, body temperature, MELD score, mean arterial pressure, serum creatinine, and pulse pressure. The risk-scoring system was developed using the odds ratios of these factors from the logistic model. The risk-scoring system showed good prediction performance and calibration (AUROC: 0.775, AUPR: 0.753)

Atmospheric correction of DSCOVR EPIC: version 2 MAIAC algorithm

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) provides multispectral images of the sunlit disk of Earth since 2015 from the L1 orbit, approximately 1.5 million km from Earth toward the Sun. The NASA’s Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been adapted for DSCOVR/EPIC data providing operational processing since 2018. Here, we describe the latest version 2 (v2) MAIAC EPIC algorithm over land that features improved aerosol retrieval with updated regional aerosol models and new atmospheric correction scheme based on the ancillary bidirectional reflectance distribution function (BRDF) model of the Earth from MAIAC MODIS. The global validation of MAIAC EPIC aerosol optical depth (AOD) with AERONET measurements shows a significant improvement over v1 and the mean bias error MBE = 0.046, RMSE = 0.159, and R = 0.77. Over 66.7% of EPIC AOD retrievals agree with the AERONET AOD to within ± (0.1 + 0.1AOD). We also analyze the role of surface anisotropy, particularly important for the backscattering view geometry of EPIC, on the result of atmospheric correction. The retrieved BRDF-based bidirectional reflectance factors (BRF) are found higher than the Lambertian reflectance by 8–15% at 443 nm and 1–2% at 780 nm for EPIC observations near the local noon. Due to higher uncertainties, the atmospheric correction at UV wavelengths of 340, 388 nm is currently performed using a Lambertian approximation.Published versio

Resting-state prefrontal EEG biomarker in correlation with postoperative delirium in elderly patients

Postoperative delirium (POD) is associated with adverse outcomes in elderly patients after surgery. Electroencephalography (EEG) can be used to develop a potential biomarker for degenerative cerebral dysfunctions, including mild cognitive impairment and dementia. This study aimed to explore the relationship between preoperative EEG and POD. We included 257 patients aged >70 years who underwent spinal surgery. We measured the median dominant frequency (MDF), which is a resting-state EEG biomarker involving intrinsic alpha oscillations that reflect an idle cortical state, from the prefrontal regions. Additionally, the mini-mental state examination and Montreal cognitive assessment (MoCA) were performed before surgery as well as 5 days after surgery. For long-term cognitive function follow up, the telephone interview for cognitive status™ (TICS) was performed 1 month and 1 year after surgery. Fifty-two (20.2%) patients were diagnosed with POD. A multivariable logistic regression analysis that included age, MoCA score, Charlson comorbidity index score, Mini Nutritional Assessment, and the MDF as variables revealed that the MDF had a significant odds ratio of 0.48 (95% confidence interval 0.27–0.85). Among the patients with POD, the postoperative neurocognitive disorders could last up to 1 year. Low MDF on preoperative EEG was associated with POD in elderly patients undergoing surgery. EEG could be a novel potential tool for identifying patients at a high risk of POD