Miracle-dz/UniFAR-FTUs huggingface dataset:
Case Studies of Gastric, Lung, and Oral Cancer Connect Etiologic Agent Prevalence to Cancer Incidence.

Obtaining detailed individual-level data on both exposure and cancer outcomes is challenging, and it is difficult to understand and characterize how temporal aspects of exposures translate into cancer risk. We show that, in lieu of individual-level information, population-level data on cancer incidence and etiologic agent prevalence can be leveraged to investigate cancer mechanisms and to better characterize and predict cancer trends. We use mechanistic carcinogenesis models [multistage clonal expansion (MSCE) models] and data on smoking, Helicobacter pylori (H. pylori), and HPV infection prevalence to investigate trends of lung, gastric, and HPV-related oropharyngeal cancers. MSCE models are based on the initiation-promotion-malignant conversion paradigm and allow for interpretation of trends in terms of general biological mechanisms. We assumed the rates of initiation depend on the prevalence of the corresponding risk factors. We performed two types of analysis, using the agent prevalence and cancer incidence data to estimate the model parameters and using cancer incidence data to infer the etiologic agent prevalence as well as the model parameters. By including risk factor prevalence, MSCE models with as few as three parameters closely reproduced 40 years of age-specific cancer incidence data. We recovered trends of H. pylori prevalence in the United States and demonstrated that cohort effects can explain the observed bimodal, age-specific pattern of oral HPV prevalence in men. Our results demonstrate the potential for joint analyses of population-level cancer and risk factor data through mechanistic modeling. This approach can be a first step in systematically testing relationships between exposures and cancer risk when individual-level data is lacking.Significance: Analysis of trends in risk-factor prevalence and cancer incidence can shed light on cancer mechanisms and the way that carcinogen exposure through time shapes the risk of cancer at different ages.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/78/12/3386/F1.large. jpg Cancer Res; 78(12); 3386-96. ©2018 AACR.
3D MODELLING OF A HISTORICAL BUILDING USING CLOSE-RANGE PHOTOGRAMMETRY AND REMOTELY PILOTED AIRCRAFT SYSTEM (RPAS)

Abstract. The photogrammetric survey of architectural Cultural Heritage is a very useful and standard process in order to obtain accurate 3D data for the documentation and visualization of historical buildings. In particular, the integration of terrestrial close-range photogrammetry and Remotely Piloted Aircraft Systems (RPASs) photogrammetry allows to create accurate and reliable 3D models of buildings and to monitor their state of conservation. The use of RPASs has indeed become more popular in Cultural Heritage survey to measure and detect areas that cannot normally be covered using terrestrial photogrammetry or terrestrial laser scanner. The paper presents the results of a photogrammetric survey executed to document the monumental complex of Villa Lampedusa ai Colli in Palermo (Italy), one of the most important historical buildings of the town. An integrated survey by close-range photogrammetry and RPAS photogrammetry was planned and carried out to reconstruct the 3D digital model of the monumental complex. Different images configurations (terrestrial, aerial nadiral, aerial parallel and oblique to the facades) have been acquired; data have been processed to verify the accuracy of the photogrammetric survey as regards the camera calibration parameters and the number of Ground Control Points (GCPs) measured on building facades. A very detailed 3D digital model and high-resolution ortho-images of the facades were obtained in order to carry out further analysis for historical studies, conservation and restoration project. The final 3D model of Villa Lampedusa ai Colli has been compared with a laser scanner 3D model to evaluate the quality of the photogrammetric approach. Beyond a purely metric assessment, 3D textured model has employed to generate 2D representations, useful for documentation purpose and to highlight the most significant damaged areas. 3D digital models and 2D representations can effectively contribute to monitor the state of conservation of historical buildings and become a very useful support for preliminary restoration works.
Physical and Chemical Properties of Pomegranate (Punica granatum L.) Fruit in Maturation Stage

Twelve pomegranate (Punica granatum L.) cultivars obtained from different growing regions of Iran were analyzed for their physical and chemical properties. These properties included fruit fresh weight, volume and density, peel thickness, soluble solids (TSS), titratable acidity (TA), EC, pH, vitamin C, ellagic acid content of juice and peel, total antioxidant activity of peel and juice and etc. Fruit weight ranged from 103.38 to 505.00 g and fruit volume from 99.41 to 547.88 cm . Similarly, average fruit density ranged from 3 0.91 g.cm to 1.04 g.cm and peel thickness of the fruit was recorded from 1.60 to 6.01 mm. Reducing sugars 33 ranged between 13.89 to 29.83 g/100 ml, total soluble solids ranged from 15.17 to 22.03 (°Brix) and titratable acidity ranged between 0.35% and 3.36% in pomegranate juices. pH and vitamin C content also ranged between 2.75-4.14 and 9.68-17.45 mg/100 ml, respectively. According to the results of HPLC, ellagic acid content of juice and peel ranged between 1-2.38 mg/100 ml and 10-50.00 mg/100 g, respectively. Total antioxidant activity measured by FRAP assay with a range of 225.17-705.50 (mmol/100 g) and 157.33-419.33 (mmol/100 ml) in peel and juice, respectively.
CONSTRUCTION AND BEHAVIORAL VALIDATION OF SUPERSTITION SCALE 1

The main goal of this study was to create an instrument for assessing tendency towards superstition-related beliefs and behavior and validate it in real life situations. Superstition was considered and analyzed as an attitude toward specific objects of the superstition. In the first part of the study, a sample of superstitious beliefs and behaviors was collected, after which the former list was reduced to 44 descriptions, based on the average familiarity. A preliminary version of the instrument was administered to 266 participants. The factor analysis suggested a presence of one main factor and three highly correlated sub-factors. In the last part of the study, in order to validate the instrument through behavioral variables, the final version of the instrument was administered to a different sample and subjects were put in two situations that challenged their potential superstitious behavior (passing below or going around a ladder in a computer laboratory; forward a chain e-mail for good luck). Group of participants that exhibited at least one superstitious behavior and the group of participants that did not, differed significantly in the average superstition score.
Long‐Term Time‐Dependent Probabilities for the Third Uniform California Earthquake Rupture Forecast (UCERF3)

The 2014 Working Group on California Earthquake Probabilities (WGCEP 2014) presents time-dependent earthquake probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3). Building on the UCERF3 time-in- dependent model published previously, renewal models are utilized to represent elastic- rebound-implied probabilities. A new methodology has been developed that solves applicability issues in the previous approach for unsegmented models. The new meth- odology also supports magnitude-dependent aperiodicity and accounts for the historic open interval on faults that lack a date-of-last-event constraint. Epistemic uncertainties are represented with a logic tree, producing 5760 different forecasts. Results for a variety of evaluation metrics are presented, including logic-tree sensitivity analyses and comparisons to the previous model (UCERF2). For 30 yr M ! 6:7 probabilities, the most significant changes from UCERF2 are a threefold increase on the Calaveras fault and a threefold decrease on the San Jacinto fault. Such changes are due mostly to differences in the time-independent models (e.g., fault-slip rates), with relaxation of segmentation and inclusion of multifault ruptures being particularly influential. In fact, some UCERF2 faults were simply too long to produce M 6.7 size events given the segmentation assumptions in that study. Probability model differences are also influential, with the implied gains (relative to a Poisson model) being generally higher in UCERF3. Accounting for the historic open interval is one reason. Another is an effective 27% increase in the total elastic-rebound-model weight. The exact factors influencing differences between UCERF2 and UCERF3, as well as the relative im- portance of logic-tree branches, vary throughout the region and depend on the evalu- ation metric of interest. For example, M ! 6:7 probabilities may not be a good proxy for other hazard or loss measures. This sensitivity, coupled with the approximate nature of the model and known limitations, means the applicability of UCERF3 should be evaluated on a case-by-case basis.
An introduction to phenomenological research

The purpose of the phenomenological approach is to illuminate the specific, to identify phenomena through how they are perceived by the actors in a situation. In the human sphere this normally translates into gathering ‘deep’ information and perceptions through inductive, qualitative methods such as interviews, discussions and participant observation, and representing it from the perspective of the research participant(s). Phenomenology is concerned with the study of experience from the perspective of the individual, ‘bracketing’ taken-for-granted assumptions and usual ways of perceiving. Epistemologically, phenomenological approaches are based in a paradigm of personal knowledge and subjectivity, and emphasise the importance of personal perspective and interpretation. As such they are powerful for understanding subjective experience, gaining insights into people’s motivations and actions, and cutting through the clutter of taken-for-granted assumptions and conventional wisdom.
Automated spectral domain approach of quasi-periodic denoising in natural images using notch filtration with exact noise profile

The domain of noise fading from digital images, by virtue of its enormous appellation amongst the researchers, stands out uniquely in the recent research field of image processing over the last few decades. Periodic noises are unintended spurious signals which often agitate an image during acquisition/transmission, thereby resulting in repetitive patterns having spatial dependency and extensively demeaning visual excellence of the image. However, high amplitude noisy spectral components are clearly noticeable from the remaining uncorrupted ones in the corresponding Fourier transformed corrupted image spectrum. Hence, it is easier to distinguish and minimise those noisy components using an appropriate thresholding and filtration technique. Therefore, to start with, a simple yet elegant model of the noise-free natural image has been developed from the corrupted one followed by a proper thresholding method to get the noisy bitmap. Finally, an elegant adaptive sinc restoration filter with the concept of extracting the exact shape of a noise spectrum profile has been applied in the filtration phase. The performance of the proposed algorithm has been assessed both visually and statistically with other state-of-the-art algorithms in the literature in terms of various performance measurement attributes, providing evidence of achieving more effective restoration with considerable lower computational time.
Phylogenetic Relationships of Spiruromorph Nematodes (Spirurina: Spiruromorpha) In North American Freshwater Fishes

Abstract Nematodes are common in the parasite communities of North American freshwater fishes, and the majority of them belong to 1 conventional order, Spirurida Chitwood, 1933. Within the Spirurida, the superfamilies Habronematoidea Chitwood and Wehr, 1932 and Thelazioidea Sobolev, 1949 have undergone considerable diversification. The dominant families of these 2 superfamilies, Cystidicolidae Skrjabin 1946 and Rhabdochonidae Railliet, 1916, respectively, are particularly common, widely distributed, and diverse, especially in North America, yet their phylogenetic relationships remain largely unexplored. In this study, we use near complete sequences of the 18S rRNA genes (SSU rDNA) from species in 6 genera (Capillospirura Skrjabin, 1924, Cystidicola Fischer, 1798, Salmonema Moravec, Santos and Brasil-Sato, 2008, Rhabdochona Railliet, 1916, Spinitectus Fourment, 1883, and a putative new cystidicolid in mooneyes, Hiodontidae), along with a species of Hedruris Nitzsch, 1812 from newts as a surrogate for the fish parasite Hedruris tiara VanCleave and Mueller, 1932, to explore their phylogenetic relationships. These sequences, together with available sequences from a range of other nematodes, including fish nematodes in other groups (Camallanoidea and ‘Seuratoidea'), were analyzed using Bayesian inference and maximum likelihood. The results from both analyses indicate, for the first time, support for the close relationships of the sturgeon parasite Capillospirura with Ascarophis van Beneden, 1871 and Cystidicola; the relationship of the cystidicolid from Hiodontidae with Salmonema of salmonid fishes; the monophyly of the 2 dominant spiruridan genera of fishes, Rhabdochona and Spinitectus; and for previous relationships among Nearctic Spinitectus spp. The results also indicate a closer relationship of Rhabdochona and Spinitectus than is suggested by their conventional classification and reject the monophyly of Habronematoidea, Thelazioidea, and Cystidicolidae. Hedruridae appears to be an early branching lineage of spirurins. Finally, the pattern of association between the fish parasites in this study and their hosts indicates, with few exceptions, ecologically driven diversification events involving host shifting not related to the phylogenetic relationships of their hosts.
Description of predicative nouns in a Modern Greek financial corpus

This paper reports on a corpus-based description of predicative nouns in a register-diversified financial corpus. Structural linguistics (Chomsky 1981) and register analysis (Biber & Conrad 2009) are the theoretical backgrounds of this research. As predicative noun, we define a noun derived from a verb, an adjective or a noun that occurs in support verb constructions (Gross 1981). In order to identify the predicative nouns occurring in a Modern Greek financial corpus we applied (a.) five Lexicon-Grammar tables containing predicative nouns, along with their distributional and transformational properties (Tziafa 2012); (b.) 122 finite state automata (Ioannidou 2013), representing noun phrases.
Distributed Parallel Architecture for "Big Data"

This paper is an extension to the "Distributed Parallel Architecture for Storing and Processing Large Datasets" paper presented at the WSEAS SEPADSâ€™12 conference in Cambridge. In its original version the paper went over the benefits of using a distributed parallel architecture to store and process large datasets. This paper analyzes the problem of storing, processing and retrieving meaningful insight from petabytes of data. It provides a survey on current distributed and parallel data processing technologies and, based on them, will propose an architecture that can be used to solve the analyzed problem. In this version there is more emphasis put on distributed files systems and the ETL processes involved in a distributed environment.
Ophiostomatoid fungi isolated from fallen shoots of Scots pine pruned by Tomicus species in Poland

Ophiostomatoid fungi are known to be associated with Tomicus spp. on Pinus sylvestris . However, very little is actually known about the fungi present in the pine shoots damaged by these insects. The aim of this study was to survey species of Ophiostoma s.lato associated with fallen shoots of Scots pine pruned by Tomicus spp. in Poland. The study was conducted in four pure Scots pine stands in southern and south-western part of the country. Fungi were identified based on morphology and DNA sequence comparison for two gene (the ITS rDNA region and s–tubulin). In total, 64 isolates obtained, represent seven species of ophiostomatoid fungi, including their asexual states of the genera. Two of them, Ophiostoma sp. 1 and Sporothrix sp. 1 probably represent new taxa. All species were found at very low frequencies. Among them, Ophiostoma minus, Ophiostoma sp. 1 and Sporothrix sp. 1 were the most frequently isolated, with a frequency of 2.0%. Occasionally, isolated species included Leptographium piriforme, Ophiostoma canum, Ophiostoma floccosum and Grosmannia cucullata -like. Association of species of Ophiostoma s. lato with Tomicus spp. and the taxonomic status of two new species are discussed.
CF-based optimisation for saliency detection

In view of the observation that saliency maps generated by saliency detection algorithms usually show similarity imperfection against the ground truth, the authors propose an optimisation algorithm based on clustering and fitting (CF) for saliency detection. The algorithm uses a fitting model to represent the quantitative relationship between ground truth and algorithm-generated saliency maps. The authors use the K -means method to cluster the images into k clusters according to the similarities among images. Image similarity is measured in terms of scene and colour by using the GIST and colour histogram features, after which the fitting model for each cluster is calculated. The saliency map of a new image is optimised by using one of the fitting models which correspond to the cluster to which the image belongs. Experimental results show that their CF-based optimisation algorithm improves the performance of various single image saliency detection algorithms. Moreover, the improvement achieved by their algorithm when using both CF strategies is greater than the improvement achieved by the same algorithm when not using the clustering strategy. In addition, their proposed optimisation algorithm can also effectively optimise co-saliency detection algorithms which already consider multiple similar images simultaneously to improve saliency of single images.
The Historic Development and Incorporation of Four Assisted Reproductive Technologies Shaping Todays IVF Industry

The concept of assisted reproductive technologies was most notably derived from the late 19th Century experiments of Sir Walter Heape who successfully transplanted rabbit embryos. Interestingly, it was not until the late 1940’s and 1950’s that renewed interests in rabbit embryo transfer and cryobiology occurred. The history behind developing effective procedures can be fascinating, though few could be more accidental than Dr. Chris Polge’s discovery of glycerol (1948), from a mislabeled bottle of sugar solutions, being an effective cryoprotective agent for sperm freezing. The purpose of this review paper is to discuss four key scientific breakthrough technologies occurring between 1985 and 1995, which ultimately shaped the future of today’s human in vitro fertilization (IVF) industry. More importantly, this paper highlights the foundation of underlying related discoveries and some unique stories involving their development and publication. In the end, this paper emphasizes the value of understanding scientific discovery timetables and the eventual re-discovery in the hands and minds of creative, determined and dedicated scientists, as history tends to repeat itself before its useful application is realized.
Population drivers of a Thalia democratica swarm: insights from population modelling

The small salp, Thalia democratica, is known globally to form dense swarms, yet the physiological and oceanographic factors that influence the magnitude and occurrence of these swarms are poorly understood. In this study, two numerical models were used to explore T. democratica population dynamics. A Lefkovitch matrix model identified that the survival of juvenile oozoids was the most important population metric promoting population growth and a size-structured population model was developed to further explore the dynamics of T. democratica. The size-structured model tracks cohorts of four life stages and incorporates size-dependent reproduction and mortality. Model outputs of average generation time and mean abundances of each life stage corresponded well to previously reported values. Factors that promote juvenile oozoid abundance were the most sensitive parameters influencing salp abundance. A 10-year time-series simulation using this population model identified that salp abundances in the Tasman Sea are proportionally higher in winter and spring, consistent with previous studies. This model shows that temperature and phytoplankton concentration are sufficient drivers of large-scale patterns of salp abundance across season and latitude. These results demonstrate the importance of future research focusing on identifying the environmental conditions that influence the size at which females reproduce.
DYNAMIC GESTURE RECOGNITION FOR NATURAL HUMAN SYSTEM INTERACTION

This paper addresses two problems: 3d dynamic gesture recognition and gesture misallocation. In order to solve these problems, we propose a new approach which combines Hidden Markov Models (HMM) and Dynamic Time Warping (DTW). The proposed approach has two main phases; first, recognizing gestures using a hidden Markov model. Second, avoiding misallocation by rejecting gestures based on a threshold computed using DTW. Our database includes many samples of five gestures obtained with a Kinect and described by depth information only. The results show that our approach yields good gesture classification without any misallocation and it is robust against environmental constraints.
Dynamic background subtraction method based on spatio-temporal classification

The dynamic background will cause extremely negative effects on background subtraction and is difficult to eliminate. This study proposes a dynamic background subtraction method based on a spatio-temporal classification which mainly contains two key steps: temporal and spatial classifications. For temporal classification, the closest pixel sampling algorithm is used to sample background pixels in groups, which avoids centralised sampling and a complicated mathematical modelling process. For the background model obtained by group sampling, the pixels which are similar to the detected pixel are classified into the same category. According to the number of pixels in this category, the label (foreground or background) of the detected pixel can be determined thus a coarse foreground mask is obtained. For spatial classification, considering the correlation between dynamic background pixels and neighbouring pixels, a square window can be set for each foreground pixel in the coarse mask, and then all pixels in the window classified. According to the labels of these classified pixels, a more accurate foreground mask is obtained. The experiments on public datasets demonstrate that the proposed method outperforms other state-of-the-art methods.