Miracle-dz/UniFAR-FTUs huggingface dataset:
The Perfect Boundary Approximation Technique Facing the Big Challenge of High Precision Field Computation

Computational tools for the design of accelerating structures are in use since decades. While highly accurate methods exist for quasi two dimensional cavities, fully three dimensional modeling with high precision is still a ‘big challenge’. The most widely used computer code in this area is MAFIA, basing on the Finite Integration Theory (FIT, [1,2]). While being well known for its robustness and reliability, MAFIA nevertheless suffers somewhat from a deficiency in being able to model very complicated 3Dcavities including curved boundaries with high precision. In this paper we present two recently developed algorithms, facing this challenge within FIT: the usage of generalized non-orthogonal computational grids (NOFIT), and the so-called Perfect Boundary Approximation (PBA) technique. Both methods represent consistent extensions of FIT, preserving all important properties as second order accuracy and stability of the transient solver. Especially the PBA technique reveals to be a highly efficient method, as it combines easy-to-use Cartesian grids with a perfect approximation of boundaries. We compare MAFIA with the PBA technique for typical accelerator components, and it turns out, that the PBA technique is more than one order of magnitude faster than the conventional method if many non Cartesian metallic boundaries appear inside the modeled structure.
The fluvial and geomorphic context of Indian Knoll, an Archaic shell midden in West‐Central Kentucky

Indian Knoll is the largest Archaic shell midden excavated by WPA archaeologists in Kentucky. Situated in a large alluvial valley, the site is not associated with a known river shoal as might be expected, making its fluvial and geomorphic setting of interest. Based on sediment cores and auger samples, undisturbed portions of the site remain despite extensive excavations. In undisturbed portions, a shell‐bearing layer is overlain by a shell‐free midden layer. Profiles of organic matter and calcium carbonate content for both layers are similar to those of other Green River shell middens. New radiocarbon determinations date the shell deposit at 5590–4530 cal yr B.P. Analysis of mussel species collected from the Indian Knoll indicates that shell fishing took place in a swiftly flowing, shallow to moderately deep setting of the main river channel. Overall, the prehistoric river setting adjacent to Indian Knoll was characterized by deeper water on average with variable but finer‐grained substrate compared to other Green River shell midden sites. © 2002 Wiley Periodicals, Inc.
Seasonal shift of foraging habitat among farmland breeding Eurasian Curlews Numenius arquata

The importance of landscape heterogeneity for farmland birds is widely recognized, but the underlying processes remain unclear. Here I investigate the distribution of foraging and non-foraging Eurasian Curlews over agricultural treatment classes during the breeding season. The results show that Eurasian Curlews used grassland for foraging early in the breeding season but shifted to cereal fields later. Contrastingly, the distribution of non-foraging Eurasian Curlews over treatment classes rarely deviated from random. I conclude that relative foraging habitat quality changed among the investigated agricultural treatment classes and that landscapes containing more than one treatment class have higher overall quality for Curlews. Preserving or creating landscapes with a mix of different kinds of commercially managed fields is a relatively cheap and easily accepted farmland bird conservation measure.
Hybridization between cultivated sunflower Helianthus annuus L . and wild perennial species Helianthus pumilus Nuttall

Helianthus pumilus Nuttall was included in hybridization programs with the cultivated sunflower Helianthus annuus L. The investigation encompassed the period 2000-2007. The results showed that the two species crossed, but the crossability rate was low. Seeds were obtained at both directions of crossing and hybrid plants only in the direct crosses. The F1 plants had an intermediate type of heritability, but they resembled the wild species in their most important biomorphological characteristics. All plants showed an annual cycle of growth in contrast to the wild perennial species. It was established that H. pumilus carried Rf genes for CMS PET-1, genes controlling the resistance to diseases such as downy mildew and phomopsis and the parasite broomrape, and genes controlling quantitative seed oil content. As a result of self-pollination, sib-pollination of the F1 plants and backcrossing with cultivated sunflower, F2, BC1 and the next hybrid progenies (F3-F7 and next to F5ВС1) were obtained. Some of the obtained hybrid forms were included in a program for developing lines for heterosis breeding in sunflower.
Investigation of solvent effect on photophysical properties of some sulfonamides derivatives

The photophysical properties of new sulfonamides synthesized recently were investigated in different solvents. Shifts in the absorption and fluorescence spectra of both compounds (S10 and S11) occurred depending on the solvents used. Ground and excited state dipole moments of the molecules were calculated using the spectral shifts of the compounds in different solvents and polarity function of solvents, respectively. They were 1.32 and 1.46 D for S10 and 1.71 and 4.89 D for S11. These results suggested that the excited state dipole moments are greater than those in ground state for both molecules. This means that the dyes were more polar in excited state compared with ground state. It was concluded that the changes in the dipole moments arise from both solvent--solute interaction and solvent polarity.
THE EFFECTS OF DIET-INDUCED OBESITY O N REGIONAL BRAIN IRO N BIOLOGY by

The importance of iron homeostasis is particularly apparent in the brain where deficiencies result in impaired cognition and accumulations are associated with neurodegenerative diseases. Obesity is associated with increased risks for altered iron status systemically as well as neurodegenerative disease, but the effects of obesity on iron biology in the brain have yet to be studied. The following study examined the effect of obesity on brain iron biology by focusing on changes in regional brain iron concentration and the expression of iron metabolism proteins at two time points in a mouse model of obesity. C57BL/6J mice were fed a high fat diet for 6 or 20 weeks post weaning to induce obesity. Samples were collected at each time point, analyzed, and compared to control animals fed a low fat diet. The results indicated that obesity was sufficient to attenuate age-related changes in iron concentration seen in control animals between 6 and 20 weeks in the midbrain and thalamus, but not the hippocampus or striatum. Further, markers of neurodegeneration (i.e., alpha-synuclein mRNA expression, F2-isoprostanes) were increased in the midbrain at 20 weeks in high fat fed mice as compared to controls. These results support previous findings that brain iron biology responds to environmental
Using Online Knowledge Sources for Semantic Noun Clustering

In this paper, we compare different sources of internet knowledge for automatic semantic noun clustering. Two knowledge sources are used: a search-enginequery Hearst-pattern (Hearst, 1992) hypernym generator based on (Kozareva et al., 2008) and (Evans, 2003) and the humanlabeled Wikipedia page categories. To fully explore the open-domain flexibility of internet-knowledge-based clustering, six different datasets were clustered, including two samples of the CoNLL 2003 Named Entity dataset, three samples of intra-domain nouns, and a widely crossdomain list. Clustering was performed with the open source package Cluto1. The results show that while clustering performance varies across domains, the addition of Wikipedia information universally increases both coverage and F-measure.
Validity and Reliability of Food Safety Knowledge and Practices Questionnaire among Food Handlers

Majority of food borne disease outbreaks resulted from poor knowledge and malpractice during food preparation. Therefore, there is a need to develop a valid and reliable tool to measure the knowledge and practice towards safe food preparation that contribute to this outbreak. A cross-sectional study was conducted to determine the validity and reliability of the Food Safety Knowledge and Practice questionnaire among food handlers in the primary school canteen operated in Kelantan. Item analysis was conducted to determine the difficulty and discrimination indexes of 40 knowledge items. Construct validity and reliability assessment was done on 30 items that measure four types of food preparation practices; personal hygiene; food hygiene and safety; environmental sanitation; and food storage. Ninetyfour food handlers completed the self-administered questionnaires. Item analysis revealed 6 items was answered correctly by more than 80%, and another 6 items correctly answered by less than 20% respondents. The discrimination index showed 9 items scored below 0.20. Considering the usefulness and practicality of the deleted items, 9 items were re-included resulted in 31 items retained under food safety knowledge section. Exploratory factor analysis of food safety practice section showed three factors with eigen values above 1 accounted for 48.6% of the variance. Nineteen problematic items were removed and remaining 11 items were loaded above 0.40. The internal consistency reliability was good with overall Cronbach's Alpha value was 0.724. This study proposes the Food Safety Knowledge and Practice questionnaire is Nik Rosmawati et al. 2015 Health and the Environment Journal, 2015, Vol 6, No 1 pp 11-30 12 a valid and reliable measure of knowledge and practice among food handlers toward safe food preparation.
An overview of flow-research - a current project of the EFRN

1Unit Applied Psychology, Ruhr-Universität Bochum, Germany; e-mail: corinna.peifer@rub.de 2Department of Psychology, Linnaeus University, Växjö, Sweden; 3EA 4354 CIREL, Univ. Lille, F-59000 Lille, France; 4Department of Psychology, Goldsmiths University of London, Great Britain; 5School of Psychology, University of Minho, Braga, Portugal; 6Faculty of Human and Social Sciences, University Fernando Pessoa, Porto, Portugal; 7Department of Education, University of Aarhus, Denmark; 8Eindhoven School of Education, Eindhoven University of Technology, Netherlands; 9Institute of Psychology Henri Pieron, Université Paris 5 René Descartes, France; 10Department of Cultural Heritage and Environment, University of Milan, Italy; 11IESE Business School, University of Navarra, Spain; 12Department of Psychology, Università Cattolica del Sacro Cuore of Milan, Italy
A General Framework for Diagnosis Prediction via Incorporating Medical Code Descriptions

Diagnosis prediction aims to predict the future health status of patients according to their historical visit records, which is an important yet challenging task in healthcare informatics. Existing diagnosis prediction approaches mainly employ recurrent neural networks (RNNs) with attention mechanisms to make predictions. However, these approaches ignore the importance of code descriptions, i.e., the medical definitions of diagnosis codes. We believe that taking diagnosis code descriptions into account can help the state-of-the-art models not only to learn meaningful code representations, but also to improve the predictive performance. Thus, in this paper, we propose a simple, but general diagnosis prediction framework, which includes two basic components: diagnosis code embedding and predictive model. To learn the interpretable code embeddings, we apply convolutional neural networks (CNNs) to model medical descriptions of diagnosis codes extracted from online medical websites. The learned medical embedding matrix is used to embed the input visits into vector representations, which are fed into the predictive models. Any existing diagnosis prediction approach (referred to as the base model) can be cast into the proposed framework as the predictive model (called the enhanced model). We conduct experiments on two real medical datasets: the MIMIC-III dataset and the Heart Failure claim dataset. Experimental results show that the enhanced diagnosis prediction approaches significantly improve the prediction performance.
Latitudinal and vertical distribution of bromine monoxide in the lower stratosphere from Scanning Imaging Absorption Spectrometer for Atmospheric Chartography limb scattering measurements

[1] Vertical profiles of stratospheric bromine monoxide (BrO) in the 15–30 km range are retrieved from SCIAMACHY limb scatter data over the globe. First validation comparisons with the balloon-borne SAOZ-BrO and LPMA/DOAS instruments indicate retrieval biases of � 20% or less. Propagated spectral fitting uncertainties lead to a precision approaching � 25% on a 2 km grid at 25 km. This worsens at higher altitudes because of reduced signal and at lower altitudes because of the reduced penetrability of the atmosphere. In terms of volume mixing ratio (VMR), the single profile precision increases from � 4 pptv at 17 km to � 8 pptv at 27 km. Repeatability, an alternative indicator of precision, is 2–3 pptv for SCIAMACHY retrievals and independent of altitude. The BrO stratospheric number density peak generally lies 5 ± 2 km above the tropopause. In the tropics, the stratospheric BrO VMR generally increases with increasing altitude. The observed stratospheric BrO global distribution is generally consistent with previous balloon measurements but does not agree well with results of a model that uses Bry inferred only from the observed breakdown of long-lived bromoalkanes (i.e., methyl bromide and halons). We find best agreement with the observed vertical and latitudinal distribution of BrO for model results that include an 8.4 ± 2 pptv contribution to stratospheric Bry, most of which is expected from the breakdown of VSL (very short lived) bromocarbons, in addition to the � 16 pptv contribution from longer-lived sources. This suggests that stratospheric Bry exceeds 20 pptv. Profiles of Bry profiles derived from the balloon measurements of BrO also suggest Bry is in excess of 20 pptv, but the uncertainty and variability of these results do not allow us to definitively rule out this concentration. We find typical BrO VMRs of � 4 pptv at 15 km in the tropical tropopause layer, suggesting that a significant portion of the bromine from VSL bromoalkane sources may be carried across the tropopause in the form of inorganic decomposition products. We discuss a variety of VSL bromocarbons species that may be contributing to the elevated concentrations of stratospheric BrO.
Overdominance in Mammals Muscle Hypertrophy Phenotype , the Only Known Example of Polar Identification of the Single Base Change Causing the Callipyge

Access the most recent version at doi: 2002 12: 1496-1506; originally published online Sep 13, 2002; Genome Res. Randy L. Jirtle and Timothy P.L. Smith Brad A. Freking, Susan K. Murphy, Andrew A. Wylie, Simon J. Rhodes, John W. Keele, Kreg A. Leymaster, Overdominance in Mammals Muscle Hypertrophy Phenotype, the Only Known Example of Polar Identification of the Single Base Change Causing the Callipyge
Theory and Practice of Atom-Density Representations for Machine Learning

The applications of machine learning techniques to chemistry and materials science become more numerous by the day. The main challenge is to devise representations of atomic systems that are at the same time complete and concise, so as to reduce the number of reference calculations that are needed to predict the properties of different types of materials reliably. This has led to a proliferation of alternative ways to convert an atomic structure into an input for a machine-learning model. We introduce an abstract definition of chemical environments that is based on a smoothed atomic density, using a bra-ket notation to emphasise basis set independence and to highlight the connections with some popular choices of descriptors for describing atomic systems. The correlations between the spatial distribution of atoms and their chemical identities are computed as inner products between these descriptor kets, which can be given an explicit representation in terms of the expansion of the atom density on orthogonal basis functions, that is equivalent to the smooth overlap of atomic positions (SOAP) descriptors, but also in real space, corresponding to $n$-body correlations of the atom density. Within this formalism it is possible to further tune the behavior of the descriptors by introducing operators that represent the correlations between structure, composition, and the target properties. We present examples of how this optimization could be formulated as a generalization of the SOAP descriptors.
Vivaspin ultrafiltration: A new approach for high resolution measurements of colloidal and soluble iron species

Vivaspin6® ultrafiltration units with molecular weight “cut‐off” membranes of 5, 10, 30, 50, and 100 kDa were used together to examine the size distribution of newly formed iron (Fe) colloids in natural seawater samples and in the presence of several different Fe chelators with varying Fe binding strength. Artificial Fe chelators, such as TAC, and 2 kDG, when added at equimolar levels to Fe, supported the formation of a continuum of Fe‐ligand colloids between 5 and 100 kDa. More than 90% of the added 55Fe in these solutions occurred in Fe aggregates/particles larger than 100 kDa. The strong siderophore DFO held the majority of the added 55Fe in the “truly” soluble fraction ≤ 5 kDa, whereas 90% of 55Fe added to UV‐irradiated seawater was converted into Fe colloids with a size between 50 to 100 kDa (5–6 nm). Membranes with ≥ 10 kDa showed similar “cut‐off” properties on natural seawater samples collected in the water column off the Peruvian coast. Fe solubility determined with these membranes was approximately six times greater than Fe solubility determined with the 5 kDa membrane and the 0.02 µm syringe filters. This suggests that a seamless size continuum of organic chelators (≤5 kDa‐10 kDa) is present in these seawaters and that estimates of ligand production based on 0.02 µm Anotop solubility experiments underestimates the abundance of soluble/colloidal ligands. Regarding these results, we recommend the use of Vivaspin 5 kDa membranes to separate the “truly” soluble from the colloidal Fe fraction.
Assessment of Abdominal Adiposity and Organ Fat with Magnetic Resonance Imaging

As the prevalence of obesity and type II diabetes continues to rise, accurate tools for quantifying abdominal body and organ fat are critically needed to assist researchers investigating therapeutic and preventive measures against obesity and its comorbidities. Fat accumulation in the liver, pancreas, and skeletal muscles are indicators of diabetes, the metabolic syndrome, and obesity. In addition to organ fat, the distribution of abdominal subcutaneous and visceral adipose tissue play critical roles in determining one’s metabolic profile and health risks. Rapid comprehensive human body fat quantification remains an unsolved problem and unmet need. Magnetic resonance imaging (MRI) is the most promising modality to address such challenge. MRI is non-invasive, utilizes no ionizing radiation, provides 3D visualization of the anatomy, has immense flexibility in tissue contrast mechanisms, is safely repeatable across longitudinal studies without restrictions, and is applicable to cohorts of all ages, particularly children and adolescents. This chapter provides the reader with an overview of MRI techniques for measuring abdominal adiposity and organ fat. The described methods are useful in preventive medicine for early detection of health risks, in studies for identifying changes in subcutaneous and visceral adipose tissue volumes due to intervention, such as bariatric surgery and diet, and in comparing trends between gender and ethnicity groups. The chapter is divided into several sections. It begins with a description of MRI principles. This provides the reader with basic knowledge and familiarizes them with terminology. Next, emphasis is placed on specific MRI approaches such as T1-weighted imaging and magnetic resonance spectroscopy (MRS) as well as state-of-the-art chemical shift imaging (CSI) techniques that are used to assess body and organ fat. Each technique is discussed in detail and compared to its counterparts. Following this description of imaging methodologies, post-processing and image analysis procedures for extracting adipose tissue depot volumes and percent organ fat content from abdominal MRI data using commercially available software are explained. The advantages and disadvantages of each MRI approach with respect to imaging parameters, spatial resolution, subject motion, scan time, and appropriate fat quantitative endpoints are emphasized. The benefits and challenges of contiguous 3D
Impact of uncertainties in atmospheric mixing on simulated UTLS composition and related radiative effects

[1] The upper troposphere/lower stratosphere (UTLS) region plays an important role in the climate system. Changes in the structure and chemical composition of this region result in particularly large changes in radiative forcings of the atmosphere. Quantifying the processes that control UTLS composition (e.g., stratosphere-troposphere exchange) therefore represents a crucial task. We assess the influence of uncertainties in the atmospheric mixing strength on global UTLS distributions of greenhouse gases (water vapor, ozone, methane, and nitrous oxide) and associated radiative effects. The study is based on multiannual simulations with the Chemical Lagrangian Model of the Stratosphere (CLaMS) driven by ERA-Interim meteorological data and on a state-of-the-art radiance code. Mixing, the irreversible part of transport, is controlled by the local horizontal strain and vertical shear of the atmospheric flow. We find that simulated radiative effects of water vapor and ozone, both characterized by steep gradients in the UTLS, are particularly sensitive to uncertainties of the atmospheric mixing strength. Globally averaged radiative effects are about 0.72 and 0.17 W/m2for water vapor and ozone, respectively. For ozone, the largest impact of mixing uncertainties is observed in the extra-tropical lower stratosphere.
Section 2. Relaxation theory and data treatment Anomalous diffusion and relaxation in macromolecular systems

Scaling, namely the algebraic (power-law) dependence of measured properties on frequency or time is of wide-spread occurrence in polymeric systems. In this work we highlight its connection to fractional calculus. As examples of systems that obey scaling, we discuss here linear and fractal generalized Gaussian structures. On the other hand, non-scaling behavior is also found in many realistic situations. In the second part of the paper we consider as example of nonscalingbehavior the relaxation of small-world networks. Detailed measurements, such as provided by dielectric spectroscopy or mechanical relaxation can help to determine the basic, mesoscopic properties of the substances under investigation. 2002 Elsevier Science B.V. All rights reserved.