Miracle-dz/UniFAR-FTUs huggingface dataset:
Health inequalities in Japan between 1986 and 2007

Background: Despite concerns about widening social inequalities during the past 20 years of economic stagnation in Japan, evidence on health inequalities is sparse. Whether health inequalities are widening or narrowing, and what factors contribute to inequalities, remains unclear. Aim: To describe temporal trends in health inequalities between 1986 and 2007 and to investigate the contribution of material, behavioural, psychosocial and social relational factors to health inequalities in Japan. Methods: A series of eight triennial nationally representative sample surveys was analysed (n=398,303). Household income and a novel theory-driven social classification were used to calculate trends in relative and slope indices of inequality [RII and SII, respectively] in self-rated fair or poor [suboptimal] health. The contribution of mediating factors to the social gradient in suboptimal health was investigated in the 2001 sample. Results: In men, temporal trends in income RII narrowed over the period (RII declined 1.2% per year, p=0.008). Stable inequalities were observed in women’s income SII. Men’s income SII and women’s income RII showed marginally significant narrowing time trends. Inequalities by social class were constant in both genders. After imputation for missing household income, narrowing trends in income RII and SII were evident (annual declines: men 1.2%, women 1.1% for RII; both genders 0.1% for SII; all p<0.05, n=490,632). Overall, there were V-shaped time trends in age-standardised self-rated suboptimal health in both genders (quadratic term: men p<0.001, women p=0.005), with the lowest prevalence in early/mid 1990s. Mediating factors analysed altogether accounted for 20% in men’s and 44% in women’s income inequalities in self-rated suboptimal health in 2001. Conclusions: Health inequalities according to household income showed narrowing trends, but persisted over the study period. The prevalence of suboptimal health increased since the early/mid 1990s. Changes in the distribution of mediating factors over the period might have influenced the time trends observed.
Compartmentation of Cyclic Nucleotide Signaling in the Heart: The Role of Cyclic Nucleotide Phosphodiesterases

G protein–coupled receptors (GPCRs) play an integral role in the signal transduction of an enormous array of biological phenomena, thereby serving to modulate at a molecular level almost all components of human biology. This role is nowhere more evident than in cardiovascular biology, where GPCRs regulate such core measures of cardiovascular function as heart rate, contractility, and vascular tone. GPCR/ligand interaction initiates signal transduction cascades, and requires the presence of the receptor at the plasma membrane. Plasma membrane localization is in turn a function of the delivery of a receptor to and removal from the cell surface, a concept defined most broadly as receptor trafficking. This review illuminates our current view of GPCR trafficking, particularly within the cardiovascular system, as well as highlights the recent and provocative finding that components of the GPCR trafficking machinery can facilitate GPCR signaling independent of G protein activation. (Circ Res. 2006;99:570-582.)
Convergence rates for density estimation with Bernstein polynomials

Mixture models for density estimation provide a very useful set up for the Bayesian or the maximum likelihood approach. For a density on the unit interval, mixtures of beta densities form a flexible model. The class of Bernstein densities is a much smaller subclass of the beta mixtures defined by Bernstein polynomials, which can approximate any continuous density. A Bernstein polynomial prior is obtained by putting a prior distribution on the class of Bernstein densities. The posterior distribution of a Bernstein polynomial prior is consistent under very general conditions. In this article, we present some results on the rate of convergence of the posterior distribution. If the underlying distribution generating the data is itself a Bernstein density, then we show that the posterior distribution converges at nearly parametric rate (log n)/√n for the Hellinger distance. If the true density is not of the Bernstein type, we show that the posterior converges at a rate n -1/3 (log n) 5/6 provided that the true density is twice differentiable and bounded away from 0. Similar rates are also obtained for sieve maximum likelihood estimates. These rates are inferior to the pointwise convergence rate of a kernel type estimator. We show that the Bayesian bootstrap method gives a proxy for the posterior distribution and has a convergence rate at par with that of the kernel estimator.
The significance of music in the performance of svikwembu ritual practices amongst the Shangana Tsonga people of semi-urban southern Mozambique

This research investigates the significance of music in svikwembu. one of the most regularly used ritual practices amongst the Shangana Tsonga people of southern Mozambique, specifically in the Maputo province. The significance and importance of music is applied to all practitioners of svikwembu. SviJcwembu includes trance (spirit possession), divination, consultation (leu pahla), exorcism (kufemba) and healing practices. Music activity has different functions in each of the above-mentioned practices. Specific instruments (gocha, ngoma, ntxomana, and whistle) and styles of music (Ndau, Nguni, mahlonga and Monhe) are used and performed in these set ritual practices. TIle main purpose of this thesis is to find out why music has to be performed in order to establish communication between the practitioners of the medium of svikwembu (traditional healers) and spirits (Ndau, Nguoi, mahlonga and Monbe). This thesis aims to fill a gap in the field of knowledge concerning music, trance and spirit possession of the Shangana Tsonga of southern Mozambique.
Optical Properties of Reflected Light From Leaves: A Case Study From One Species

The reflection property of targets is the fundamental signal for applications of optical remote sensing of the earth’s surface. In this paper, we measured the photometric and polarimetric characteristics of 15 leaves with different properties from one plant species (i.e., Pachira aquatica) using a laboratory goniospectrometer system and used the bidirectional reflectance factor (BRF) and the bidirectional polarized reflectance factor (BPRF) to describe the reflection of these leaf samples. The results illustrated that the BRF can be replaced by the <inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula> parameter reflectance factor (<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>pRF) when the extinction of the polarizer is considered. Subsequently, the BRF model was fit to the <inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>pRF measurements at selected wavelengths, and the inverted refractive index was used in a BPRF model, which has been proposed to simulate the polarization of surfaces. We found that the modeled photometric results of all the leaves matched well with our measurement results over all the measurement directions, while the modeled polarimetric results of the leaves gave a good agreement with the measurements at the forward scattering directions. Moreover, the degree of linear polarization (Dolp) of the leaf, which is derived from the ratio between BPRF and <inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>pRF, can also be effectively computed by the combination of BPRF and BRF models in the forward scattering directions. These findings suggested that more attention should be dedicated to the combination of BRF and BPRF of leaves in the future because we can completely describe the essential optical properties of the light reflected by leaves via the polarimetric measurement. This paper indicates that the polarimetric measurement is a beneficial method for optical remote sensing applications and helps us deepen the understanding of the optical properties of leaves.
Reliability of the Discounting Inventory: An extension into substance-use population

: Recent research introduced the Discounting Inventory that allows the measurement of individual differences in the delay, probabilistic, effort, and social discounting rates. The goal of this investigation was to determine several aspects of the reliability of the Discounting Inventory using the responses of 385 participants (200 non-smokers and 185 current-smokers). Two types of reliability are of interest. Internal consistency and test-retest stability. A secondary aim was to extend such reliability measures beyond the non-clinical participant. The current study aimed to measure the reliability of the DI in a nicotine-dependent individuals and non–nicotine-dependent individuals. It is concluded that the internal consistency of the DI is excellent, and that the test–retest reliability results suggest that items intended to measure three types of discounting were likely testing trait, rather than state, factors, regardless of whether “non-smokers” were included in, or excluded from, the analyses (probabilistic discounting scale scores being the exception). With these cautions in mind, however, the psychometric properties of the DI appear to be very good.
VARIABILITY OF SPATIO-TEMPORAL SEA SURFACE TEMPERATURE IN NORTHERN WATERS OF CENTRAL JAVA, INDONESIA

The Empirical Orthogonal Function (EOF) methodis widely used in various studies for many different disciplines, and one application of this method is for oceanography research. EOF is used to obtain the dominant mode of the data and to evolve in time and space. This method can reduce a large number of the variable from original data to a few variables without substantially reducing the original information of data. The purpose of this study is to examine the EOF method for reducing sea surface temperature (SST) data. Subsequently, by analyzing the dominant pattern of temporal and spatial of SST. The analysis of SST was conducted on The North Waters of Central Java for 180 months ( January 2003 – December 2017). This analysis produced several principal components that were called EOF mode. For each EOF, there is a variable which is contained by two information the pixel data and the eigenvector. The pixel data described spatial variability and eigenvector which presented the time series variability. Basic selection of EOF mode depends on the percentage of eigenvalues. The percentage of contribution will give the selection rules of EOF mode that retains most of the information from the original data. This analysis resulted from the three dominant modes with the largest variances in several EOF. The modes explained 30.6 %, 27.1% and 18.9% of the total variance for the first, second and third mode, respectively. Therefore, the first mode represented the majority data.
CONVOLUTIONAL LONG-SHORT TERM MEMORY NETWORKS MODEL FOR LONG DURATION EEG SIGNAL CLASSIFICATION

Background and objective: Deep learning structures have recently achieved remarkable success in the field of machine learning. Convolutional neural networks (CNN) in image processing and long-short term memory (LSTM) in the time-series analysis are commonly used deep learning algorithms. Healthcare applications of deep learning algorithms provide important contributions for computer-aided diagnosis research. In this study, convolutional long-short term memory (CLSTM) network was used for automatic classification of EEG signals and automatic seizure detection. Methods: A new nine-layer deep network model consisting of convolutional and LSTM layers was designed. The signals processed in the convolutional layers were given as an input to the LSTM network whose outputs were processed in densely connected neural network layers. The EEG data is appropriate for a model having 1-D convolution layers. A bidirectional model was employed in the LSTM layer. Results: Bonn University EEG database with five different datasets was used for experimental studies. In this database, each dataset contains 23.6[Formula: see text]s duration 100 single channel EEG segments which consist of 4097 dimensional samples (173.61[Formula: see text]Hz). Eight two-class and three three-class clinical scenarios were examined. When the experimental results were evaluated, it was seen that the proposed model had high accuracy on both binary and ternary classification tasks. Conclusions: The proposed end-to-end learning structure showed a good performance without using any hand-crafted feature extraction or shallow classifiers to detect the seizures. The model does not require filtering, and also automatically learns to filter the input as well. As a result, the proposed model can process long duration EEG signals without applying segmentation, and can detect epileptic seizures automatically by using the correlation of ictal and interictal signals of raw data.
Orlicz spaces on hypergroups

For a locally compact hypergroup K and a Young function φ, we study the Orlicz space L(K) and provide a sufficient condition for L(K) to be an algebra under convolution of functions. We show that a closed subspace of L(K) is a left ideal if and only if it is left translation invariant. We apply the basic theory developed here to characterize the space of multipliers of the Morse–Transue space M(K). We also investigate the multipliers of L(S, πK), where S is the support of the Plancherel measure πK associated to a commutative hypergroup K.
Circulating Cell-Free DNA Enables Noninvasive Diagnosis of Heart Transplant Rejection

In a prospective cohort study of heart transplant recipients, sequencing-based quantification of donor-derived DNA in plasma of recipients noninvasively diagnosed transplant rejection. Donor DNA Indicates Transplant Rejection Not all heart transplants succeed, but early detection of organ rejection could spare the patient severe adverse events and graft dysfunction. De Vlaminck et al. devised a noninvasive, sequencing-based method to monitor and predict rejection, relying on the presence of donor DNA in recipient blood plasma. The fraction of donor DNA is naturally elevated 1 day after transplant (because organ transplants are essentially genome transplants), and these levels decline exponentially over the course of the week, if the organ is accepted. The authors noted that patients who rejected their new heart had high levels of donor DNA even months after transplant. In a prospective trial, elevated donor DNA was detected months before the rejection episode, suggesting that such noninvasive analysis tools could be used in lieu of an invasive biopsy, to let doctors know which patients are likely to reject their transplanted organ. Monitoring allograft health is an important component of posttransplant therapy. Endomyocardial biopsy is the current gold standard for cardiac allograft monitoring but is an expensive and invasive procedure. Proof of principle of a universal, noninvasive diagnostic method based on high-throughput screening of circulating cell-free donor-derived DNA (cfdDNA) was recently demonstrated in a small retrospective cohort. We present the results of a prospective cohort study (65 patients, 565 samples) that tested the utility of cfdDNA in measuring acute rejection after heart transplantation. Circulating cell-free DNA was purified from plasma and sequenced (mean depth, 1.2 giga–base pairs) to quantify the fraction of cfdDNA. Through a comparison with endomyocardial biopsy results, we demonstrate that cfdDNA enables diagnosis of acute rejection after heart transplantation, with an area under the receiver operating characteristic curve of 0.83 and sensitivity and specificity that are comparable to the intrinsic performance of the biopsy itself. This noninvasive genome transplant dynamics approach is a powerful and informative method for routine monitoring of allograft health without incurring the risk, discomfort, and expense of an invasive biopsy.
COMBINING QUANTITATIVE AND PARTICIPATORY METHODS IN CONJOINT ANALYSIS - DESIGNING MICROSAVINGS IN NORTHERN VIETNAM

More and more microfinance institutions have come to recognize the need to pro vide microsavings services both as a much-valued service by their clients and as a long-term source of refinancing capital for themselves. This has led to growing inte rest in savings, referred to by Vogel (1984) as the 'forgotten half of microfinance. Empirical research has shown that the rural poor save financially. Nevertheless, savings services must be designed appropriately to respond to the poor's demand characteristics. Savings in Vietnam were boosted during the last decade. However, this develop ment has bypassed rural areas. The Vietnam Bank for Agriculture and Rural Development (VBARD) is the only supplier of savings schemes in rural areas. However, savings services of the VBARD are not attractive to rural clients. Yet, Vietnam's rural population has a true demand for microsavings services; they need to be still further developed. The development of demand driven microfinance services requires the involvement of the rural poor by participatory research methods. Conjoint Analysis (CA) is a marketing research method that combines quantitative and quali tative aspects and requires involving the potential clients in a participatory process at different stages of the research process. The stages and intensity of target group involvement in the CA will be analyzed and policy recommendations for the design of demand driven micro-savings schemes will be discussed. The results of this paper strongly support the view that rural households in developing countries, even the poor and poorest, demand microsavings services. This finding contrasts the Vietnamese government's and the formal financial sector's views.
Impact of Strong Spatial Correlation on the Capacity Scaling of Massive MIMO

In this paper, the capacity scaling of multicell massive MIMO systems is investigated in the presence of spatially correlated fading. In particular, we focus on the strong spatial correlation regimes where the covariance matrix of each user channel vector has a rank that scales sublinearly with the number of base station antennas, as the latter grows to infinity. We also consider the case where the covariance eigenvectors corresponding to the non-zero eigenvalues span randomly selected subspaces. For this channel model, referred to as the “random sparse angular support” model, we characterize the asymptotic capacity scaling law in the limit of large number of antennas. In order to achieve the capacity results, spatial (de)spreading based on the second-order channel statistics plays a pivotal role in terms of pilot decontamination and interference suppression. A remarkable result is that even when the number of users per cell scales linearly with base station antennas in multicell environments, unlimited capacity is achievable under the sparse angular support model as long as the effective signal-to-noise ratio is away from zero.
Subjective Effects of Thiopental in Young Adults with and without a Family History of Alcoholism.

Background: The development of alcohol use disorders is genetically influenced, and may be mediated through differences in the subjective response to alcohol. There is some evidence to suggest that response differences to alcohol could be conveyed by heritable differences in GABAA receptors. The purpose of this study was to investigate whether individuals with a family history positive (FHP) for alcohol dependence would experience alterations in response to the GABAA receptor agonist thiopental, in comparison to family history negative (FHN) subjects. Methods: 73 subjects (24 FHP and 49 FHN) between the ages of 21 and 30 years were administered subanesthetic doses of the GABAA receptor agonist thiopental and placebo on two separate test days. Various alcoholrelated measures were administered, including those examining subjective effects, coordination, and cognition. Results: Sub-anesthetic doses of thiopental produced alcohol-like subjective effects, as well as alcohol-like impaired coordination and cognition in healthy subjects. While there were no significant main effects in subjective, coordination, or cognitive effects between FHP and FHN individuals, analysis of peak effects suggested FHP had blunted sedative, but not stimulant effects compared to FHN. Conclusion: Thiopental produced alcohol-like effects and perceived similarities to alcohol in healthy individuals. Subtle differences in sedative effects are consistent with reports of blunted FHP response to the negative but not stimulant effects of alcohol. Future studies are needed to better understand how this insight informs our understanding of the heritable risk for alcoholism and the treatment of alcohol use disorders.
Marine viral populations detected during a nutrient induced phytoplankton bloom at elevated pCO 2 levels

During the PEeCE III mesocosm experiment in 2005 we investigated how the virio-plankton community responded to increased levels of nutrients (N and P) and CO 2. We applied a combination of flow cytometry, Pulsed Field Gel Electrophoresis and degenerated PCR primers to categorize and quantify individual viral populations, and to 5 investigate their temporal dynamics. Species specific and degenerated primers enabled us to identify two specific large dsDNA viruses, EhV and CeV, infecting the haptophytes Emiliania huxleyi and Crysochromulina ericina, respectively. Some of the viral populations detected and enumerated by flow cytometry did not respond to altered CO 2-levels, but the abundance of EhV and an unidentified dsDNA virus de-10 creased with increasing CO 2 levels. Our results thus indicate that CO 2 conditions may affect the marine pelagic food web at the viral level. Our results also demonstrate that in order to unravel ecological problems as how CO 2 and nutrient levels affect the relationship between marine algal viruses and their hosts, we need to continue the effort to develop molecular markers used to identify both hosts and viruses.
Cloud Optical Properties from the Multifilter Shadowband Radiometer (MFRSRCLDOD). An ARM Value-Added Product

The microphysical properties of clouds play an important role in studies of global climate change. Observations from satellites and surface-based systems have been used to infer cloud optical depth and effective radius. Min and Harrison (1996) developed an inversion method to infer the optical depth of liquid water clouds from narrow band spectral Multifilter Rotating Shadowband Radiometer (MFRSR) measurements (Harrison et al. 1994). Their retrieval also uses the total liquid water path (LWP) measured by a microwave radiometer (MWR) to obtain the effective radius of the warm cloud droplets. Their results were compared with Geostationary Operational Environmental Satellite (GOES) retrieved values at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site (Min and Harrison 1996). Min et al. (2003) also validated the retrieved cloud optical properties against in situ observations, showing that the retrieved cloud effective radius agreed well with the in situ forward scattering spectrometer probe observations. The retrieved cloud optical properties from Min et al. (2003) were used also as inputs to an atmospheric shortwave model, and the computed fluxes were compared with surface pyranometer observations.
The influence of broadcast tape-recorded calls on captures of fall migrant Northern Saw-whet Owls (Aegolius acadicus) and Long-eared Owls (Asio otus)

Nocturnal netting operations have been conducted at the Hawk Ridge Nature Reserve since 1972. From 1988 to 1992 a recording of human whistles simulating the calls of fall migrant Northern Saw-whet Owls (Aegolius acadicus) was broadcast on a random, on or off, half-night basis. Mist net captures of Saw-whet Owls increased about fourfold during the broadcast sessions, while captures of Long-eared Owls (Asio otus) decreased as much as 24 percent.