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Let K be a number field and, for an integral ideal q of K, let χ be a character of the narrow ray class group modulo q. We establish various new and improved explicit results, with effective dependence on K,q and χ, regarding the zeros of the Hecke L-function L(s,χ), such as zero-free regions, Deuring–Heilbronn phenomenon, and zero density estimates.
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Strains of Cyanobacteria isolated from mats of 9 thermal springs of Greece have been studied for their taxonomic evaluation. A polyphasic taxonomic approach was employed which included: morphological observations by light microscopy and scanning electron microscopy, maximum parsimony, maximum likelihood and Bayesian analysis of 16S rDNA sequences, secondary structural comparisons of 16S–23S rRNA Internal Transcribed Spacer sequences, and finally environmental data. The 17 cyanobacterial isolates formed a diverse group that contained filamentous, coccoid and heterocytous strains. These included representatives of the polyphyletic genera of Synechococcus and Phormidium, and the orders Oscillatoriales, Spirulinales, Chroococcales and Nostocales. After analysis, at least 6 new taxa at the genus level provide new evidence in the taxonomy of Cyanobacteria and highlight the abundant diversity of thermal spring environments with many potential endemic species or ecotypes.
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A common problem in modern genetic research is that of comparing the mean vectors of two populations–typically in settings in which the data dimension is larger than the sample size–where Hotelling’s test cannot be applied.
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In order to investigate the origins of the Universe, it is necessary to carry out full sky surveys of the temperature and polarisation of the Cosmic Microwave Background (CMB) radiation, the remnant of the Big Bang. Missions such as COBE and Planck have previously mapped the CMB temperature, however in order to further constrain evolutionary and inflationary models, it is necessary to measure the polarisation of the CMB with greater accuracy and sensitivity than before.
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Individual-based models (IBM) simulate populations and communities whose dynamics are shaped by the properties, interactions and behaviour of the constituent organisms as well as the corresponding abiotic boundary conditions. Structurally realistic IBM can provide insights into the functioning of such systems and predict the effects of variable scenarios. We suggest complementing IBM with machine learning (ML) methods in order (i) to visualise correlation patterns between model inputs and model outputs, (ii) to provide simulation-based decision tools for non-modellers, and (iii) to derive information about factors difficult to obtain in the field on the basis of data that are more readily measurable. On top of this, ML methods can complement the established pattern-oriented modelling approach used to analyse the behaviour of IBM and to detect model uncertainties. As an example to demonstrate the strength of an IBM-ML connection, we combined the individual-based Plant Interaction Model (Pi model) with self-organising feature maps (SOM) – a special type of ML. Based on simulation experiments with complete knowledge of the simulated system, the SOM was trained and used to visualise the nonlinear relationship between two IBM inputs (namely the mode of below-ground competition and below-ground resource limitation) and two model outputs (the mortality rate and the Clark Evans Index of the spatial distribution of plants). Our study also highlights an application of the SOM to infer the modes of below-ground competition (either symmetric or asymmetric) from the remaining measurable variables (resource limitation, mortality rate and Clark Evans Index). This procedure was successful in 92% of cases, revealing its great potential as a means to assess parameters difficult to measure in nature. This example shows that SOM are powerful tools to revert the hierarchy of variables and to generalise dependencies of parameters in individual based modelling.
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Remotely sensed data provides information on river morphology useful for examining channel change at yearly-to-decadal time scales. Although previous studies have emphasized the need to distinguish true geomorphic change from errors associated with image registration, standard metrics for assessing and summarizing these errors, such as the root-mean-square error (RMSE) and 90th percentile of the distribution of ground control point (GCP) error, fail to incorporate the spatial structure of this uncertainty. In this study, we introduce a framework for evaluating whether observations of lateral channel migration along a meandering channel are statistically significant, given the spatial distribution of registration error. An iterative leave-one-out cross-validation approach was used to produce local error metrics for an image time series from Savery Creek, Wyoming, USA, and to evaluate various transformation equations, interpolation methods, and GCP placement strategies. Interpolated error surfaces then were used to create error ellipses representing spatially variable buffers of detectable change. Our results show that, for all five sequential image pairs we examined, spatially distributed estimates of registration error enabled detection of a greater number of statistically significant lateral migration vectors than the spatially uniform RMSE or 90th percentile of GCP error. Conversely, spatially distributed error metrics prevented changes from being mistaken as real in areas of greater registration error. Our results also support the findings of previous studies: second-order polynomial functions on average yield the lowest RMSE, and errors are reduced by placing GCPs on the floodplain rather than on hillslopes. This study highlights the importance of characterizing the spatial distribution of image registration errors in the analysis of channel change.
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This study evaluates the impact of a national-level subsidized loan program, ACCES (Access with Quality to Higher Education), on a number of higher education outcomes (i.e., increase in enrollment rates, decrease in dropout rates, and increase in academic performance) of low-income students. The program intends to tackle Colombia’s wide disparities in access to postsecondary education by socioeconomic status and by region. We use national-level data along with a regression discontinuity design (RDD) to estimate the impact of the program. We provide intent to treat and the local average treatment effect estimates of the program on enrollment and dropout rates, and on academic performance. Our RDD design takes advantage of the fact that the beneficiaries of the program are selected based on a government mandated procedure to rank individuals at the “department” (similar to geographic regions in the U.S.) level based on a cutoff score in their high school exit exams. The results confirm that the program has been effective in terms of increasing the potential number of low-income students at the margin who would have enrolled in college, decreasing the number of students who dropped out, and increasing their academic outcomes. Nonetheless, the effects of the credit program on enrollment exhibit the largest magnitude and with clearly positive heterogeneous impact on the poorest applicants. The results are less compelling for dropout, yet in the expected direction.
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Diabetes and diabetes-related complications are major causes of morbidity and mortality worldwide and contribute substantially to health care costs. Proper care can prevent or delay vascular complications in people with type 2 diabetes. We sought to examine whether a diabetes pay-for-performance (P4P) program under Taiwan's National Health Insurance program decreased risk of macrovascular complications in type 2 diabetes patients, and associated risk factors.
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Bayesian estimators are developed and compared with the maximum likelihood estimators for the two-piece location–scale models, which contain several well-known distributions such as the asymmetric Laplace distribution, the two-piece normal distribution, and the two-piece Student-t distribution. For the validity of Bayesian analysis, it is essential to use priors that could lead to proper posterior distributions. Specifically, reference priors with partial information have been considered. A sufficient and necessary condition is established to guarantee the propriety of the posterior distribution under a general class of priors. The performance of the proposed approach is illustrated through extensive simulation studies and real data analysis.
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Recording of the historic edifice using the state-of-the-art geodetic and geophysical techniques brings easier visualisation in form of a three-dimensional (3D) model, thus allowing better understanding of its historical construction by the public and non-experts. We have applied this approach at the Church of St. George, one of the most significant religious buildings in south-western Slovakia, which dominates a silhouette of the town Svätý Jur. The geodetic survey allowed to record the actual state of the church. The church exterior was surveyed using a total station. Due to the intricate shape of the interior components of the church, it was decided to use a terrestrial laser scanner to generate the point cloud data, which were processed into floor plan, elevations, sectional 2D drawings and 3D model. The geophysical survey was carried out in the interior of the church in order to identify potential subsurface anthropogenic structures. Microgravity and ground penetrating radar (GPR) methods were selected as the most effective geophysical tools for such task. In microgravity data processing we focused on the calculation and removal of the gravitational effects of the building masses. The main negative gravity anomalies of interest in the nave, which also have been confirmed by GPR measurements, are interpreted as medieval crypts. Another very important outcome of the geophysical survey is the discovery of the west wall foundations of the oldest Romanesque construction. From each geophysical data acquired we derived 3D polygonal models, which are compared to achieve more realistic picture of the subsurface structures. Verification of these structures by means of archaeological excavation has not been carried out yet.
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