Miracle-dz/UniFAR-FTUs huggingface dataset:
Siderophile Element Abundances in Karavannoe: Implications for the Origin of the Eagle Station Pallasites

Introduction: The link between chondritic meteorites and differentiated meteorites is an important goal that is often elusive, with the exception of isotopic finger-printing [e.g., 1-2]. To understand the paleomagnetism of CV chondrites models of a partially differentiated asteroid, with a carbonaceous chondritic surface and a differentiated interior, have been proposed [3-4]. Chemical tests of this model supported the idea that CV chondrites may be linked to the Eagle Station pallasite trio (ESP) on the basis of siderophile element measurements of metal from Eagle Station and Cold Bay [5]. The range of chemical fractionation in the ESP meteorites is rather limited, so the recent discovery of a new member, Karavannoe [6], provides the opportunity for an improved test using siderophile elements. Olivine from the Karavannoe pallasite has oxygen isotope compositions and mineral chemistry (Fe/Mn~97, Fa~20) that identify it as the fourth member of the Eagle Station Pallasites (ESP). Further, the metal in Karavannoe is plessite with swathing kamacite around the olivines [6]. This is important since the main challenge to chemical fingerprinting of pallasites by laser ablation ICP-MS [5] is coarse subsolidus exsolution of kamacite and taenite [7]. For example, the siderophile element data for Cold Bay are affected by the preferential dissolution of kamacite during weathering so that measured siderophile element patterns have a strong taenite overprint [8]. Analytical Methods and Samples: A 19 mm x 12 mm sawn slab of Karavannoe with minimal weathering was received from the Russian Academy of Sciences Committee on Meteorites, mounted in epoxy, and polished on one side exposing >50% metal with weathering restricted to the olivine-metal contacts. Siderophile elements were determined by rastering three olivinefree metallic areas each ~3-4 mm. Laser ablation ICPMS analysis were performed with a New Wave UP193FX excimer laser system coupled to a Thermo Element XR at the Plasma Analytical Facility, Florida State University. A 100 μm beam spot scanned at 1025 μm/s, 50 Hz repetition rate, 2 GW/cm fluence, was used. Other aspects of the measurement are identical to those previously described [5]. Results: The siderophile element data for Karavannoe are given in Table 1, together with results for Eagle Station, shown in Fig. 1. The success of measuring small areas by laser ablation and estimating the bulk metal composition in a pallasite is judged in terms of obtaining meaningful representation of kamacite and plessite (in the case of Karavannoe) or taenite. Fig. 2 shows the correlation between the (Co/Ni)CI and the (As/Au)CI ratios. Kamacite concentrates Co and As, while taenite concentrates Ni and Au. Individual analyses of Cold Bay cover a broad range of composition, while analyses of Eagle Station and Karavannoe are nearly constant at chondritic ratios of Co/Ni.
seIsmIc measurements In unstable sea clIFF areas

Introduction. Sea cliffs are high-risk elements in the Mediterranean area due to the diffused landslide processes that affect sites of touristic relevance as well as buildings which are part of the cultural heritage. The Favignana Island (Sicily, Italy) represents a significant case study as several sea cliffs located in its eastern part are involved in landslide processes where porous carbonate grainstones overlying plastic clay deposits widely outcrop (Falconi et al., 2015). More in particular, the western sector of Cala Rossa Bay was selected as a test site as its geological setting predisposes a large lateral spreading responsible for instabilities of the sea cliff, associated to falls and topples of different-size rock blocks.
An Analysis of the Effects of Blood Pressure and Antihypertensive Drugs on Heart Disease

Background: The American College of Cardiology (ACC), American Heart Association (AHA) and other organizations announced a new hypertension guideline (2017 ACA/AHA Guideline) in November 2017. However, other organizations such as the European Society of Cardiology and European Society of Hypertension maintained their diagnostic thresholds. It is necessary to evaluate the effects of blood pressure (BP) and antihypertensive drugs on the probability of having heart disease (HD). Data and Methods: The effects of BP, antihypertensive drugs and other factors on the probability of undergoing HD treatment were analyzed. We used a dataset containing 83,287 medical check-up and treatment records obtained from 35,504 individuals in 5 fiscal years. The probit models were used in the study. Considering the possibility of endogeneity problems, different types of models were used. Results: We could not find evidence that a higher systolic BP increased the probability of undergoing HD treatment. However, diastolic BP increased the probability in most of the models. Taking antihypertensive drugs also increased the probability of undergoing HD treatment. Diabetes was another important risk factor. Conclusion: The results of this study did not support the new 2017 ACC/AHA Guideline. It is necessary to choose proper drugs and methods to reduce the risks of side effects. Limitations: The dataset was observatory, the data were obtained from just one medical society, and sample selection bias might exist.
isual inspection of independent components : Defining a procedure for artifact emoval from fMRI data

Artifacts in functional magnetic resonance imaging (fMRI) data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis’ demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to
What does the patient experience during a COGNISION ® testing session ?

Cognitive disorders such as age-related dementias are notoriously difficult to diagnose accurately, especially in the early stages. Even at NIHsponsored Alzheimer’s Disease Centers, diagnostic sensitivity ranges from 70.9% to 87.3%, while specificity is only 44.3% to 70.8%[1]. This clearly demonstrates the need for more reliable tools to help with these complex diagnoses. Standard neuropsychological tests may be useful to elucidate specifically impaired cognitive domains; however, they do not provide physiological measures related to the underlying etiology. Modern electrophysiological techniques such as Quantitative EEG (QEEG) and Event-Related Potentials (ERP) are becoming the forefront in neurodiagnostic testing and provide physiological evidence of disease in the absence of clear psychometric results.
Visual quality after pseudophakic monovision in cataract patients

Objective: To observe the effect of pseudophakic monovision (MV) on the visual quality of cataract patients. Methods: A total of 68 patients diagnosed as cataract were divided into MV group (n=34) and control group (n=34) according to patients’ surgical will. Moreover, MV group was divided into near-vision group (n=14) and far-vision group (n=20), according to their dominant eye. All patients were implanted with Tecnis ZCB00. In the MV group, the refractive error of the biometry calculation was programmed for 0-0.5D in the far vision eye and -1.5D-2.0D in the near vision eye; in the control group, both eyes were 0-0.5D. Near, middle-distance and distance visions as well as contrast sensitivity, distance and near stereopsis, VF-14 score, and rate of with no need for optical eyewear were observed in follow-up. Results: Firstly, there were significant differences in the middle-distance and near binocular visions 3 months after operation (P<0.001), but there was no significant difference in distance, middle distance and near visions between the far-vision group and the near-vision group. Secondly, the difference in contrast sensitivity at each spatial frequency was not significant between the MV group and the control group both in bright and dark environments, while the far-vision group had higher the contrast sensitivity than the near-vision group at spatial frequency of 0.9 cpd, 1.5 cpd and 3.0 cpd in both environments. Thirdly, the near stereopsis in MV group was better than that in control group (P<0.001), but there was no significant difference in distance stereopsis between the two above groups. There were also no significant differences in both distance and near stereopsis between the far-vision group and the near-vision group. Next, the VF-14 scores of MV group and control group were higher 3 months after operation than those of pre-operation, and the MV group enjoyed significantly higher postoperative score compared with the control group. While there was no significant difference in VF-14 between the far-vision group and the near-vision group preoperatively and postoperatively. Lastly, rate of no need for optical eyewear in MV group was higher than that in control group, while there was no significant difference between the far-vision group and the near-vision group. Conclusion: Pseudophakic MV can achieve favorable visual quality after operation, and no significant difference was found in visual quality and quality of life between patients with a far-vision dominant eye and with a near-vision dominant eye.
MINING IN CUSTOMER SEGMENTATION

The paper analyzes the possibilities of applying data mining techniques to improve customer segmentation. The aim of customer segmentation is to identify and profile lead, average and other company customers and to optimize and tailor future marketing actions so the right message can reach the right customer. Different techniques and models are applied in customer segmentation, like factor and cluster analysis in analyzing company customer data. In order to get required benefits from large data volumes stored in databases or data warehouses and to find hidden relationships between data, authors used cluster analysis, one of the data mining techniques. Data mining is a process of extracting previously unknown and potentially useful and hidden patterns from large databases. The main objective of the paper is to identify the high/medium/low-profit, high/medium/low-value and low/medium/high-risk customers by one of the data mining technique customer clustering. It presents results of empirical research related to data mining in customer segmentation made in a production company which produces and distributes products like dry fruits, nuts, seeds and cereals for the market of South-East Europe.
Phylogeography of Pachygrapsus transversus ( Gibbes , 1850 ) : The effect of the American continent and the Atlantic Ocean as gene flow barriers and recognition of Pachygrapsus socius Stimpson 1871 as a valid species

Genetic and morphometric comparisons among a few specimens of the littoral crab Pachygrapsus transversus have revealed marked intraspecific differences between three different coastlines (Cuesta and Schubart, 1998). Here we build on the previous study by presenting a more comprehensive analysis covering the entire range of this species from the Galapagos Islands to Israel, based on 195 specimens for morphometric analysis and 39 individuals for genetic comparisons of the 16S mtDNA. It is confirmed that marked genetic differences are present between three major coastlines (eastern Pacific, western and eastern Adantic), whereas along single coastlines there is mostly high genetic homogeneity. Morphometric analyses also allow distinction of adult specimens from the three coastlines. In contrast, larval morphological and morphometric differences were less consistent and cannot be used to separate zoea I stages from the different megapopulations. In addition to the genetic separation of populations from different coastlines, this study provides new evidence for less marked, but consistent genetic differentiation between European and northern African populations of P. transversus on one hand, and central African ones on the other. However, by far the most prominent genetic differences within this complex are those between Pacific and all Atlantic populations, probably dating back to separation of these populations during the closure of the Panama Isthmus roughly three million years ago. Based on morphological and genetic differences outlined in this study, we revalidate the species name Pachygrapsus socius Stimpson, 1871 for all Pacific representatives of P. transversus.
Safety analysis of turbo-roundabouts using the SSAM technique

The Surrogate Safety Analysis Module (SSAM) is a software application that reads trajectories files generated by microscopic simulation programs and calculates surrogate measures of safety corresponding to each vehicle-to-vehicle interaction. This approach eliminates the subjectivity associated with the conventional conflict analysis technique and allows assessing the safety of a facility under a controlled environment, before the occurrence of accidents. This study has two main parts: the first addresses the conceptual validation of SSAM by comparing its outputs against wellestablished accident prediction models; in the second part SSAM is used to evaluate the safety benefits of three roundabout layouts – single-lane, two-lane and turbo-roundabout. This work allows two main conclusions: despite some limitation related to the nature of current traffic microsimulation models, SSAM analysis is a very promising approach to access the safety of new facilities or innovative layouts; based on a limited conceptual validation, it was found that the safety performance of a turboroundabout is similar to a single-lane, but with the advantage of offering much higher capacity levels.
Research : Evaluation in the Lens of Big Data Analytics

Given the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists conducting DSR are also challenged with identifying suitable evaluation mechanisms for their data products. Hence, this conceptual research paper is set out to address the following questions. Does big data analytics impact how evaluation in DSR is conducted? If so, does it lead to a new type of evaluation or a new genre of DSR? We conclude by arguing that big data analytics should influence how evaluation is conducted, but it does not lead to the creation of a new genre of design research.
USING CONCEPT MAPPING TECHNIQUE TO PROMOTE THE CREATION AND IMPLEMENTATION OF SCIENCE CAREER-RELATED SCENARIOS – THE MULTICO PROJECT EXPERIENCE

The purpose of this paper is to illustrate the use of concept mapping to create science career-related scenarios as part of a teaching approach to raising middle school students career awareness. The paper shows the role played by concept mapping in aiding the construction of a scenario. Within the project, 4 scenarios were created, each focusing on one science subject, but at the same time involved an interdisciplinary problem setting related to a socially relevant issue. The scenarios formed the 1st part of a theoretically justified 3-stage model teaching approach, which encompassed a created context (motivating students at the beginning of lessons by means of a scenario), de-contextualizing (gaining new conceptual science) and re-contextualizing (incorporating the science learning in socio-scientific decision making based on issues arising from the initial scenario). Within the project, the scenarios were utilised in a longitudinal study on middle school students (grade 7-9) with each intervention following the 3-stage teaching approach. In general, science teachers found the concept map support useful as they learned, in addition to creating scenarios, how to relate social issues with science learning and how to introduce science careers within lessons.
A NEW APPROACH FOR SOLVING THE NAVIER-STOKES EQUATIONS FOR COMPRESSIBLE FLOWS USING FOURIER COLLOCATION PSEUDOSPECTRAL METHOD

Abstract. The purpose of the present work is to expose a new methodology for solving the Navier-Stokes equations for compressible flows by using the pseudo-spectral Fourier collocation method, in the particular case of an isothermal and two-dimensional flow. Due to high values associated with the density gradient, spectral methods show several problems when solving this type of flow. Compressible flows are very important in several applications, such as turbomachinery and aerodynamics, and due to its importance, new methods for solving these equations are still being developed. Therefore, any contribution for this field is crucial for the development of new CFD methods.
1-1-2018 DEXTER : Disease-Expression Relation Extraction from Text

Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression–disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our textmined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential VC The Author(s) 2018. Published by Oxford University Press. Page 1 of 17 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. (page number not for citation purposes) Database, 2018, 1–17 doi: 10.1093/database/bay045
Behavioural interventions to reduce the transmission of HIV infection among sex workers and their clients in low- and middle-income countries

Behavioural interventions appear to reduce the rates of transmission of sexually transmitted infections such as gonorrhoea, syphilis, genital warts, and chlamydial infections among sex workers in lowand middleincome countries. The interventions were also found to be effective in increasing knowledge about risks. However, none of the interventions significantly reduced the incidence of HIV infection.
Scalable inference of discrete data: User behavior, networks and genetic variation

Abstract : Recent years have seen explosive growth in data, models and computation. Massive data sets and sophisticated probabilistic models are increasingly used in the fields of high-energy physics, biology genetics and in personalization applications; however, many statistical algorithms remain inefficient impeding scientific progress. In this thesis, we present several efficient statistical algorithms for learning from massive discrete data sets. We focus on discrete data because complex and structured activity such as chromosome folding in three dimensions, human genetic variation, social network interactions and product ratings are often encoded as simple matrices of discrete numerical observations. Our algorithms derive from a Bayesian perspective and lie in the framework of directed graphical models and mean- field variational inference. Situated in this framework, we gain computational and statistical efficiency through modeling insights and through subsampling informative data during inference. We begin with additive Poisson factorization models for recommending items to users based on user consumption or ratings. These models provide sparse latent representations of users and items and capture the long-tailed distributions of user consumption. We use them as building blocks for article recommendation models by sharing latent spaces across readership and article text. We demonstrate that our algorithms scale to massive data sets, are easy to implement and provide competitive user recommendations. Then, we develop a Bayesian nonparametric model in which the latent representations of users and items grow to accommodate new data. In the second part of the thesis, we develop novel algorithms for discovering overlapping communities in large networks.
The role of postoperative radiotherapy for completely resected pIIIA-N2 non-small cell lung cancer patients with different clinicopathological features: a systemic review and meta-analysis

Background: The role of postoperative radiotherapy (PORT) in completely resected pathological stage IIIA-N2 (pIIIA-N2) non-small cell lung cancer (NSCLC) remains controversial. This meta-analysis aimed to assess the effect of PORT in patients with pIIIA-N2 NSCLC on the basis of clinicopathological features. Methods: The PubMed, PubMed Central (PMC), Embase, Web of Science, and Cochrane Library were searched for relevant studies. The main outcomes were overall survival (OS) and disease-free survival (DFS), which were compared using the hazard ratio (HR). Results: One randomized trial and 12 retrospective studies were eligible for the analysis. PORT significantly improved both OS [HR = 0.85; 95% confidence interval (CI): 0.79-0.92] and DFS (HR = 0.57; 95% CI: 0.38-0.85) compared with non-PORT treatment in patients with multiple N2 metastases or multiple N2 station involvement. No significant difference in either OS (HR = 1.03; 95% CI: 0.86-1.24) or DFS (HR = 1.08; 95% CI: 0.70-1.65) was found between PORT and non-PORT groups for patients with single N2 station involvement. No significant heterogeneity was observed. No significant differences in OS were observed between PORT and non-PORT groups for patients of different ages, sex, tumor sizes or pT stages, and histological types. Conclusions: The findings of this meta-analysis supported a role for PORT in patients with completely resected pIIIA-N2 NSCLC having multiple N2 metastases and favored withholding PORT to patients with single N2 station involvement. Further prospective randomized controlled trials are needed to confirm the findings.