Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of the contact angle of silica nanoparticles at the air–water interface on the mechanical properties of the layers composed of these particles

We have studied the properties (surface pressure, compression and shear moduli, texture) of silica nanoparticle layers at the air–water interface. Particle hydrophobicity or, equivalently, the contact angle between particles, air and water, is the main factor that influences surface organization and surface elastic moduli. The surface layers are denser for particles of higher hydrophobicity. The compression and shear moduli, as well as the yield and melt strains, present a maximum for contact angles around 90°. The dependence of the mechanical properties on particle hydrophobicity is closely related to the foamability and stability of the foams made from dispersions.
Ion energy characteristics downstream of a high power helicon

The High Power Helicon eXperiment operates at higher powers (37 kW) and lower background neutral pressure than other helicon experiments. The ion velocity distribution function (IVDF) has been measured at multiple locations downstream of the helicon source and a mach 3–6 flowing plasma was observed. The helicon antenna has a direct effect in accelerating the plasma downstream of the source. Also, the IVDF is affected by the cloud of neutrals from the initial gas puff, which keeps the plasma speed low at early times near the source.
Distribution of Pb and Zn in slices of human bone by synchrotron µ-XRF

Synchrotron radiation-induced micro x-ray fluorescence analysis (µ-XRF) at HASYLAB beamline L was used to determine the distribution of Pb and other trace elements in slices of human bone. Using a focused synchrotron x-ray beam of about 15 µm in diameter it was found that Pb was mostly located at the outer border of the cortical bone in various samples. Ratios of Pb intensities of cortical and trabecular bone varied from 0.027 for hip head to 0.408 for proximal tibia. Additionally Ca, Zn and Sr distributions were simultaneously recorded. A remarkable association between Pb and Zn content could be observed. Copyright © 2004 John Wiley & Sons, Ltd.
AN ANALYSIS OF FOURTH DERIVATIVE SPECTRA

Abstract— –Fourth derivative spectra of chloroplast at – 196°C, obtained by four sequential differentiations of the absorption spectrum, were examined to determine the conditions for optimal signal‐to‐noise ratio and resolution. An appreciable improvement in the signal‐to‐noise ratio was found when the four differentiating intervals were nearly but not exactly equal. The process of differentiating digitized data with the computer was explored in order to define the rules for optimization of the fourth derivative curves.
Exploring Blockchain Peer-to-Peer Networks

The rise of cryptocurrencies like Bitcoin and Ethereum attracts a lot of attention, also from attackers. In order to secure blockchain systems, one ﬁrst needs to understand their networks. And this is what we try to do in this thesis. We compare degrees, clustering coeﬃcients, shortest paths and closeness centrality of simulated Bitcoin and Ethereum networks. Furthermore, we build a theoretical model to calculate these properties in theory and compare them to the results of simulations. We ﬁnd that the centrality of a node is dependant on the time it was added and that Ethereum-like networks have a linear construction process, which leads to high clustering.
Thermal behaviour and physico-chemical characterization of synthetic and natural iron hydroxyphosphates

The thermal behaviour of five hydroxyphosphates, lipscombite [Fe3(PO4)2(OH)2], barbosalite [Fe3(PO4)2(OH)2], giniite [Fe5(PO4)4(OH)2· 2H2O], rockbridgeite Fe5(PO4)3(OH)5] and Fe4(PO4)3(OH)3, has been studied. Thermogravimetric analysis revealed the hydroxyphosphates to have distinct behaviours: some underwent dehydroxylation between 623 and 893 K like other phosphates [lipscombite, barbosalite, Fe4(PO4)3(OH)3], while rockbridgeite and giniite differed. Rockbridgeite, which appeared to contain only iron(III) ions, underwent a first partial dehydroxylation at only 438 K, while giniite totally dehydroxyated only at between 623 and 823 K. Comparison of the results obtained by thermogravimetric analysis with those obtained by other techniques, including chemical analysis, X-ray diffraction and Mossbauer spectroscopy, allowed us to propose the existence of a new solid solution for the giniite compound and to confirm that previously observed for rockbridgeite. The solid solution of the former corresponds to a variation in composition due to dehydroxylation–hydration : FeIII4+xFeII1–x(PO4)4(OH)2–x(2 +x)H2O with 0 < x < 1. The latter corresponds to a variation in the composition due to dehydroxylation–oxidation : FeIII4+xFeII1–x(PO4)3(OH)5–xOx with 0 < x < 1. In both cases, Mossbauer spectroscopy indicates that Fe2+ or Mn2+ substituents may be localized on the different crystallographic sites of the structures.
Calpric : Automated Classification of Privacy Policy Using Deep Active Learning and Crowdsourcing Techniques by Wendy ( Wenjun )

Calpric: Automated Classification of Privacy Policy Using Deep Active Learning and Crowdsourcing Techniques Wendy (Wenjun) Qiu Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2020 Privacy policies are statements that notify users of the services’ data practices. However, few users are willing to read through policy texts due to the length and complexity. While there are existing privacy policy analysis tools based on machine learning, a large labeled training set is needed to achieve a high classification accuracy. Most existing policy corpora are labeled by skilled human annotators, requiring a significant amount of labor hours and effort. In this paper, we leverage active learning and crowdsourcing techniques to develop an automated classification tool named Calpric (Crowdsourcing Active Learning PRIvacy Policy Classifier), which is able to perform annotation equivalent to those done by skilled human annotators with high accuracy while minimizing the labeling cost. On average, our model is able to achieve the same F1 score using only 45.3% of the original labeling effort, and addresses the class imbalance issue of existing datasets.
Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics

Infrastructure-as-code (IaC) is the DevOps practice enabling management and provisioning of infrastructure through the definition of machine-readable files, hereinafter referred to as IaC scripts. Similarly to other source code artefacts, these files may contain defects that can preclude their correct functioning. In this paper, we aim at assessing the role of product and process metrics when predicting defective IaC scripts. We propose a fully integrated machine-learning framework for IaC Defect Prediction, that allows for repository crawling, metrics collection, model building, and evaluation. To evaluate it, we analyzed 104 projects and employed five machine-learning classifiers to compare their performance in flagging suspicious defective IaC scripts. The key results of the study report Random Forest as the best-performing model, with a median AUC-PR of 0.93 and MCC of 0.80. Furthermore, at least for the collected projects, product metrics identify defective IaC scripts more accurately than process metrics. Our findings put a baseline for investigating IaC Defect Prediction and the relationship between the product and process metrics, and IaC scripts’ quality.
Long-term changes in tropospheric ozone

Tropospheric ozone changes are investigated using a selected network of surface and ozonesonde sites to give a broad geographic picture of long-term variations. The picture of long-term tropospheric ozone changes is a varied one in terms of both the sign and magnitude of trends and in the possible causes for the changes. At mid latitudes of the S.H. three time series of 20 years in length agree in showing increases that are strongest in the austral spring (August–October). Profile measurements show this increase extending through the mid troposphere but not into the highest levels of the troposphere. In the N.H. in the Arctic a period of declining ozone in the troposphere through the 1980s into the mid-1990s has reversed and the overall change is small. The decadal-scale variations in the troposphere in this region are related in part to changes in the lowermost stratosphere. At mid latitudes in the N.H. , continental Europe and Japan showed significant increases in the 1970s and 1980s. Over North America rises in the 1970s are less than those seen in Europe and Japan, suggesting significant regional differences. In all three of these mid latitude, continental regions tropospheric ozone amounts appear to have leveled off or in some cases declined in the more recent decades. Over the North Atlantic three widely separated sites show significant increases since the late-1990s that may have peaked in recent years. e front matter r 2006 Elsevier Ltd. All rights reserved. mosenv.2006. 01.029 ing author. Tel. : +1303 497 6676; fax: +1 303 497 5590. ess: samuel.j.oltmans@noaa.gov (S.J. Oltmans).
Parsing Penn Chinese Treebank Based on Lexicalized Model

Syntactic parsing is one of the most important technologies of natural language processing. The development of Penn Chinese Treebank (CTB) spurred the research of Chinese parsing. This paper describes a lexicalized statistical Chinese parser. First, a lexicalized model based on hidden Markov model is proposed for part of speech tagging. Second, a well-known lexicalized model i.e. the head-driven model is adapted to parse the automatically POS tagged Chinese sentences. The construction of the parser is described, and the effects of details that can make great difference in the parsing performance are analyzed. On sentences of length less than 100 words, the parser performances at 80.08% precision and 78.45% recall on, surpassing the best published results.
Risks and Benefits of Using Social Media in Dermatology: Cross-sectional Questionnaire Study

Background Dermatological information on social media is often presented by nondermatologists. Increasing the online engagement of trained dermatologists may improve information quality, patient education, and care. Objective Our study assesses dermatologists’ perceptions of social media and patterns of use to identify barriers limiting engagement. Methods In our cohort study, a 36-item online survey was distributed to dermatologists in the United States; responses were captured on a 1-100 sliding scale. Results Of 166 initiated surveys, 128 valid responses were submitted. Dermatologists showed greater concern for social media risk-related issues (mean 77.9, SD 15.1) than potential benefits (mean 61.8, SD 16.4; P<.001). Leading concerns were poor patient care, nonevidence-based information, and breaching patient privacy. Benefits included interphysician collaboration, patient education, and public health awareness. The most avid and enthusiastic social media users were millennials (mean total optimism score 67.5, SD 14.9) and baby boomers (mean total optimism score 63.1, SD 11.2) compared with Generation X dermatologists (mean total optimism score 52.2, SD 16.3, P<.001). Of 128 dermatologists, 103 (82.4%) plan on increasing their social media use (P=.003). Predictors showing an intent to increase future social media use were younger age, integration into professional use, and an optimistic view (r2=.39; P<.001). Conclusions Dermatologists perceive the risk of social media to be considerable but still intend to increase its use, likely recognizing the value and importance of social media to the field.
Climate-Smart Agriculture in Peru + vr.indd

Peru is a megadiverse country, with richness in life zones (84), climates, and genetic diversity of wild and agricultural species. Development and scaling out of CSA practices that focus on research and recovery of this richness and dissemination of traditional crops would build resilience of agricultural systems, improve productivity, and contribute to nutrition and food security. The preservation and transference of ancestral adaptation practices for soil conservation (e.g., platforms, terraces) and water retention (e.g., canals, ponds) are important for mainstreaming CSA.
Biotic and Abiotic Factors of Sperm nDNA Fragmentation in Farm Animals

Infertility and subfertility are among the global challenges of our time. Fertility in livestock farming is not only biologically important, it is also economically important. The aim of this study was to study the effect of these factors on sperm chromatin nucleus and to assess the impact of the fragmentation index degree on bull reproductive performance. The influence of abiotic factors such as ambient temperature, the level of geomagnetic activity and the biotic factor-infectious diseases of male reproductive organs - was studied. At high ambient temperatures (28-30°C), the proportion of sperm with damaged DNA increased by 70% compared to temperatures below 15°C. A Multivariate Analysis Of Variance (MANOVA) confirmed the influence of the geomagnetic activity factor on the degree of nuclear DNA fragmentation in bull sperm cells (level p<0.05). During the summer period, on days with increased geomagnetic activity, the Nuclear DNA fragmentation index in the samples studied was 20.5%. In some of the samples studied, this index exceeded 38% and the coefficient of variation for this index reached 44%. The proportion of sperm cells with abnormal movement also increased during geomagnetic activity. The content of such sperm cells reached 9.1% in bull semen ejaculates obtained during the winter period. More than 12% of sperm had non-progressive movement in summer semen obtained with a K-index ≥5.0, which was 83.8% higher than with a K-index ≤1.0. High geomagnetic activity and temperature and infection of the reproductive organs lead to pathological changes in spermatozoa, an increase in the proportion of spermatozoa with damaged nuclear DNA and a decrease in fertility.
The Mediating of Financial Control on the Relationship between Transformational Leadership and Economic Development in Saudia Arabia

This study examines the direct empirical relationship between transformational leadership and economic development among 377 managers in private and public sectors in the Eastern Area. Moreover, the research identifies the significance of financial control as a plausible mediator in the relationship between transformational leadership and economic development. In this study, financial control and transformational leadership, are posited as having an influence on economic development in the Eastern Area. For data analysis and hypothesis testing, Structural Equation Modelling, and several statistical methods such as the maximum likelihood estimate and regression technique were utilized to understand the dimensionality of the variables. This study adopted a systematic random sampling to select managers who work in private and public sectors to conduct the study by using a quantitative method. The managers were selected to answer these questions because of their knowledge and experience which involves in this area. The results show that that transformational leadership (Idealized Influence) positively influenced economic development, while (motivation) was found to have a negative effect on economic development. Also, they show that (Idealized Influence and motivation) positively influenced financial control. Moreover, financial control was found to be a significant mediating factor in the relationship between transformational leadership and economic development in the private and public sectors of the Eastern Area. Transformational leadership was were found to be negative mediating factors in the relationship between financial control and economic development in the private and public sectors of the Eastern Area. This study also contributes to the body of knowledge in regards to providing tools and concepts for educating current and future managers about effective methods to improve their perspective probability or chances of achieving economic development. Based on the study’s findings, transformational leadership and financial control significantly affect economic development, and it is recommended that organizations provide the necessary training to their leaders and managers, and recruiter managers who have skills leadership and management that will contribute to effective leadership, extra effort, satisfaction and achieve economic development, which can lead organizations to acquire and maintaining consistently high economic performances and successfully.
A web-based collaborative virtual reality environment for distance learning

-Recent years have seen the emergence of virtual reality environments intended for learning activities. This situation gives rise to new innovative teaching practices and tools which exploit the possibilities oﬀered by immersion, 3D interaction, sense of presence and virtual reality ﬂow. The advantages for using these environments have been demonstrated in several scientiﬁc studies for general learning activities. We present the speciﬁcations of a web-based virtual reality environment designed speciﬁcally for collaborative learning situations in a distance learning context. The environment makes it possible to address the issue of learner isolation caused by spatial and temporal distance, and to improve the user experience of distance learners. Our framework is based on a 3-tier architecture and recent web technologies (A-Frame, WebRTC) to ensure stable connections between users and a greater ﬂexibility.
Title Quadrupolar D‒A‒D diketopyrrolopyrrole-based small molecule for ternary blend polymer solar cells

A quadrupole diketopyrrolopyrrole (DPP)-based small molecule (DPP4T-Cz) was designed and synthesized to enhance absorption coefficient, and then employed as the third component to improve the light harvesting of polymer solar cells based on a blend of poly(3hexylthiophene) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM). Because of an enhanced absorption coefficient of more than 10 cm, the photon harvesting efficiency was improved effectively in the near infrared (near-IR) range by using only a small amount of DPP4TCz (3.4 wt%) into the P3HT:PCBM binary blend polymer solar cells. Interestingly, the photocurrent generation was also enhanced in the visible range by the long-range energy transfer from P3HT to DPP4T-Cz molecules. As a result, the short-circuit current density (JSC) and power conversion efficiency (PCE) of P3HT:PCBM:DPP4T-Cz ternary blend devices were enhanced by more than 30% compared to those of P3HT:PCBM binary control devices. These findings suggest that quadrupole DPP-based molecules are one of the effective light-harvesting materials for ternary blend polymer solar cells.
Rotation Detection in Finger Vein Biometrics using CNNs

Finger vein recognition deals with the identification of subjects based on their venous pattern within the fingers. The recognition accuracy of finger vein recognition systems suffers from different internal and external factors. One of the major problems are misplacements of the finger during acquisition. In particular longitudinal finger rotation poses a severe problem for such recognition systems. The detection and correction of such rotations is a difficult task as typically finger vein scanners acquire only a single image from the vein pattern. Therefore, important information such as the shape of the finger or the depth of the veins within the finger, which are needed for the rotation detection, are not available. This work presents a CNN based rotation detector that is capable of estimating the rotational difference between vein images of the same finger without providing any additional information. The experiments executed not only show that the method delivers highly accurate results, but it also generalizes so that the trained CNN can also be applied on data sets which have not been included during the training of the CNN. Correcting the rotation difference between images using the CNN's rotation prediction leads to EER improvements between 50-260% for a well-established vein-pattern based method (Maximum Curvature) on four public finger vein databases.
Microhabitat heterogeneity enhances soil macrofauna and plant species diversity in an AshField 1 Maple woodland 2 3

1 Maple woodland 2 3 Victoria J. Burtonab*, Paul Eggletona 4 aSoil Biodiversity Group, Life Sciences Department, The Natural History Museum, Cromwell Road, 5 London SW7 5BD, UK 6 bImperial College London, South Kensington Campus, London SW7 2AZ, UK 7 *corresponding author email v.burton@nhm.ac. uk 8 9 Abstract 10 The high biodiversity of soil ecosystems is often attributed to their spatial heterogeneity at multiple 11 scales, but studies on the small-scale spatial distribution of soil macrofauna are rare. This case study 12 of an Ash-Field Maple woodland partially converted to conifer plantation investigates differences 13 between species assemblages of soil and litter invertebrates, and plants, using multivariate 14 ordination and indicator species analysis for eleven microhabitats. 15
Optimization of Reaction Conditions in a Fluidized‐Bed for Silane Pyrolysis

The fluidized-bed chemical vapor deposition (CVD) process for polycrystalline silicon production is considered to be the most attractive alternative to the conventional bell-jar process. In order to obtain stable operation, high space-time-yields and high purity of the product several obstacles have to be eliminated. Reaction conditions must be optimized to avoid the homogeneous decomposition of silane and minimize silicon dust formation. The effect of temperature, silane partial pressure, gas velocity and the size of bed particles has to be identified. These dependencies and the interaction between hydrodynamics and kinetics of homogeneous and heterogeneous CVD-reactions were studied in a laboratory-scale fluidized-bed reactor.
Commenting on poverty online: A corpus-assisted discourse study of the Suomi24 forum

This paper brings new insight to poverty and social exclusion through an analysis of how poverty-related issues are commented on in the largest online discussion forum in Finland: Suomi24 (‘Finland24’). For data, we use 32,407 posts published in the forum in 2014 that contain the word köyhä (‘poor’) or a predefined semantically similar word. We apply the Corpus-Assisted Discourse Studies (CADS) method, which combines quantitative methods and qualitative discourse analysis. This methodological solution allows us to analyse both large-scale tendencies and detailed expressions and nuances on how poverty is discussed. The quantitative analysis is conducted with topic modelling, an unsupervised machine learning method used to examine large volumes of unlabelled text. Our results show that discussions concerning poverty are multifaceted and can be broken down into several categories, including politics; money, income and spending; and unequal access to goods. This 1 Lehti is the corresponding author. Lehti and Luodonpää-Manni are first authors with equal contribution.
Toward an integrated strategy to understand mechanisms across 2 species for chemical safety assessment

Claudia Rivetti , Timothy E. H. Allen , James B. Brown , Emma Butler , Paul L. Carmichael 5 , John K. Colbourne , Matthew Dent , Francesco Falciani , Lina Gunnarsson , Steve Gutsell 6 , Joshua A. Harrill , Geoff Hodges , Paul Jennings , Richard Judson , Aude Kienzler , 7 Luigi Margiotta-Casaluci , Iris Muller , Stewart F. Owen , Cecilie Rendal , Paul J. Russell 8 , Sharon Scott , Fiona Sewell , Imran Shah , Ian Sorrel , Mark R. Viant , Carl 9 Westmoreland , Andrew White , Bruno Campos 1* 10