Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing an international industrial hygiene database of exposures among workers in the asphalt industry.

OBJECTIVES The objective of this project was to construct a database of exposure measurements which would be used to retrospectively assess the intensity of various exposures in an epidemiological study of cancer risk among asphalt workers. METHODS The database was developed as a stand-alone Microsoft Access 2.0 application, which could work in each of the national centres. Exposure data included in the database comprised measurements of exposure levels, plus supplementary information on production characteristics which was analogous to that used to describe companies enrolled in the study. RESULTS AND DISCUSSION The database has been successfully implemented in eight countries, demonstrating the flexibility and data security features adequate to the task. The database allowed retrieval and consistent coding of 38 data sets of which 34 have never been described in peer-reviewed scientific literature. We were able to collect most of the data intended. As of February 1999 the database consisted of 2007 sets of measurements from persons or locations. The measurements appeared to be free from any obvious bias. CONCLUSIONS The methodology embodied in the creation of the database can be usefully employed to develop exposure assessment tools in epidemiological studies.
Paxos at war

The optimistic latency of Byzantine Paxos can be reduced from three communication steps to two, without using public-key cryptography. This is done by making a decision when more than (n + 3f)/2 acceptors report to have received the same proposal from the leader, with n being the total number of acceptors and f the number of the faulty ones. No further improvement in latency is possible, because every Consensus algorithm must take at least two steps even in benign settings. Moreover, if the leader is correct, our protocol achieves the latency of at most three steps, even if some other processes fail. These two properties make this the fastest Byzantine agreement protocol proposed so far. By running many instances of this algorithm in parallel, we can implement Vector Consensus and Byzantine Atomic Broadcast in two and three steps, respectively, which is two steps faster than any other known algorithm.
CODEX: a robust and secure secret distribution system

CODEX (COrnell Data Exchange) stores secrets for subsequent access by authorized clients. It also is a vehicle for exploring the generality of a relatively new approach to building distributed services that are both fault-tolerant and attack-tolerant. Elements of that approach include: embracing the asynchronous (rather than synchronous) model of computation, use of Byzantine quorum systems for storing state, and employing proactive secret sharing with threshold cryptography for implementing confidentiality and authentication of service responses. Besides explaining the CODEX protocols, experiments to measure their performance are discussed.
Discussion of Ability Cultivation of Computational Thinking in Course Teaching

Computational thinking is taken for the fundamental skills for everyone, not just computer scientist, to learn and use. It remains to be explored in many aspects how to understand the essence of computational thinking and how cultivate the computational thinking ability of students. In the view of course teaching of computer science, this paper discusses the perception of the essence of computational thinking and presents a method for the cultivation of the computational thinking ability by using courses as carrier, and a case study of the course Data Structures and Algorithms.
Distribution of Dendritic Cells in Normal Human Salivary Glands

Dendritic cells (DC) are believed to contribute to development of autoimmune sialadenitis, but little is known about their distribution in normal salivary glands. In this study, DC were identified and their distribution was determined in normal human parotid and submandibular glands. For light microscopy, salivary gland sections were stained with H&E or immunocytochemically using antibodies to DC markers. Transmission electron microscopy (TEM) was used to evaluate the ultrastructural characteristics of DC. In H&E sections, elongated, irregularly shaped nuclei were occasionally seen in the striated and excretory duct epithelium. Immunolabeling with anti-HLA-DR, anti-CD11c and anti-S100 revealed DC with numerous processes extending between ductal epithelial cells, often close to the lumen. Morphometric analyses indicated that HLA-DR-positive DC occupied approximately 4–11% of the duct wall volume. Similar reactive cells were present in acini, intercalated ducts and interstitial tissues. TEM observations revealed cells with indented nuclei containing dense chromatin, pale cytoplasm with few organelles, and lacking junctional attachments to adjacent cells. These results indicate that DC are abundant constituents of normal human salivary glands. Their location within ductal and acinar epithelium suggests a role in responding to foreign antigens and/or maintaining immunological tolerance to salivary proteins.
Journal of Economic Behavior & Organization Raising the Price of Talk: an Experimental Analysis of Transparent Leadership

Does transparent leadership promote cooperative groups? We address this issue using a public goods experiment with exogenously selected leaders who are able to send non-binding contribution suggestions to the group. To investigate the effect of transparency in this setting we vary the ease with which a leader's actions are known by the group. We find leaders' suggestions encourage cooperation in all treatments, but that both leaders and their group members are more likely to follow leaders' recommendations when institutions are transparent so that non-leaders can easily see what the leader does. Consequently, transparency leads to significantly more cooperation, higher group earnings and reduced variation in contributions among group members.
Deep ADMM-Net for Compressive Sensing MRI

Compressive Sensing (CS) is an effective approach for fast Magnetic Resonance Imaging (MRI). It aims at reconstructing MR image from a small number of under-sampled data in k-space, and accelerating the data acquisition in MRI. To improve the current MRI system in reconstruction accuracy and computational speed, in this paper, we propose a novel deep architecture, dubbed ADMM-Net. ADMM-Net is defined over a data flow graph, which is derived from the iterative procedures in Alternating Direction Method of Multipliers (ADMM) algorithm for optimizing a CS-based MRI model. In the training phase, all parameters of the net, e.g., image transforms, shrinkage functions, etc., are discriminatively trained end-to-end using L-BFGS algorithm. In the testing phase, it has computational overhead similar to ADMM but uses optimized parameters learned from the training data for CS-based reconstruction task. Experiments on MRI image reconstruction under different sampling ratios in k-space demonstrate that it significantly improves the baseline ADMM algorithm and achieves high reconstruction accuracies with fast computational speed.
A study of pupil detection and tracking by image processing techniques for a human eye-computer interaction system

The pupil detection and tracking is an important step for developing a human-computer interaction system. To develop a human eye-computer interaction system, we examine pupil detection and tracking by image processing techniques. In the image processing techniques, the illumination directly influences the image quality in general. If influences of illumination is little, we can obtain an image of good image quality. The subsequent image processing techniques are expected almost to succeed. In this paper, in order to avoid the influences of illumination, we have tried to combine the hardware constitution of an infrared light-emitting diode (LED) light, a sensitive infrared camera, and an infrared (IR) filter. In the experiment with this hardware constitution, we investigate the effects of the pupil detection and tracking by image processing techniques for a human eye-computer interaction system.
A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees

Decision trees are among the most popular pattern types in data mining due to their intuitive representation. However, little attention has been given on the definition of measures of semantic similarity between decision trees. In this work, we present a general framework for similarity estimation that includes as special cases the estimation of semantic similarity between decision trees, as well as various forms of similarity estimation on classification datasets with respect to different probability distributions defined over the attribute-class space of the datasets. The similarity estimation is based on the partitions induced by the decision trees on the attribute space of the datasets. We use the proposed framework in order to estimate the semantic similarity of decision trees induced from different subsamples of classification datasets; we evaluate its performance with respect to the empirical semantic similarity, which we estimate on the basis of independent hold-out test sets. The availability of similarity measures on decision trees opens a wide range of possibilities for meta-analysis and meta-mining of the data mining results.
3D Animation Compression Using Affine Transformation Matrix and Principal Component Analysis

This paper investigates the use of the affine transformation matrix when employing principal component analysis (PCA) to compress the data of 3D animation models. Satisfactory results were achieved for the common 3D models by using PCA because it can simplify several related variables to a few independent main factors, in addition to making the animation identical to the original by using linear combinations. The selection of the principal component factor (also known as the base) is still a subject for further research. Selecting a large number of bases could improve the precision of the animation and reduce distortion for a large data volume. Hence, a formula is required for base selection. This study develops an automatic PCA selection method, which includes the selection of suitable bases and a PCA separately on the three axes to select the number of suitable bases for each axis. PCA is more suitable for animation models for apparent stationary movement. If the original animation model is integrated with transformation movements such as translation, rotation, and scaling (RTS), the resulting animation model will have a greater distortion in the case of the same base vector with regard to apparent stationary movement. This paper is the first to extract the model movement characteristics using the affine transformation matrix and then to compress 3D animation using PCA. The affine transformation matrix can record the changes in the geometric transformation by using 4 × 4 matrices. The transformed model can eliminate the influences of geometric transformations with the animation model normalized to a limited space. Subsequently, by using PCA, the most suitable base vector (variance) can be selected more precisely.
Energy efficient resources allocations for wireless communication systems

The energy consumption level of the telecommunication process has become a new consideration in resource management scheme. It is becoming a new parameter in the resource management scheme besides throughput, spectral efficiency, and fairness. This work proposes a power control scheme and user grouping method to keep the rational energy consumption level of the resource management scheme. Inverse water-filling power allocation is a power allocation scheme that optimizes the energy efficiency by giving the power to the user which have good channel conditions. The user grouping method becomes the solution for carrier aggregation (CA) scheme that prevents edge cell user get the resources from the high-frequency carrier. This can prevent energy wastage in the transmission process. This power control scheme and user grouping method can optimize the spectral and energy efficiency without increasing the time complexity of the system.
Berberine Inhibits Invasion and Metastasis of Colorectal Cancer Cells via COX-2/PGE2 Mediated JAK2/STAT3 Signaling Pathway

Berberin, extracted from Chinese herbal medicine Coptis chinensis, has been found to have anti-tumor activities. However, the underlying mechanisms have not been fully elucidated. Our current study demonstrated that berberin inhibited the in vitro and in vivo growth, migration/invasion of CRC cells, via attenuating the expression levels of COX-2/PGE2, following by reducing the phosphorylation of JAK2 and STAT3, as well as the MMP-2/-9 expression. We further clarified that an increase of COX-2/PGE2 expression offset the repressive activity of Berberin on JAK2/STAT3 signaling, and a JAK2 inhibitor AZD1480 blocked the effect of COX-2/PGE2 on MMP-2/-9 expression. In summary, Berberin inhibited CRC invasion and metastasis via down-regulation of COX-2/PGE2- JAK2/STAT3 signaling pathway.
An Novel Hybrid Method for Effectively Classifying Encrypted Traffic

Classifying encrypted traffic is critical to effective network analysis and management. While traditional payload- based methods are powerless to deal with encrypted traffic, machine learning methods have been proposed to address this issue. However, these methods often bring heavy overhead into the system. In this paper, we propose a hybrid method that combines signature-based methods and statistical analysis methods to address this issue. We first identify SSL/TLS traffic with signature matching methods, and then apply statistical analysis to determine concrete application protocols. Our experimental results show that the proposed method is able to recognize over 99% of SSL/TLS traffic and achieve 94.52% in F-score for protocols identification.
The Role of Personality Traits through Habit and Intention on Determining Future Preferences of Public Transport Use

A complex set of factors may affect transportation mode choice. While earlier studies have often considered objective factors in determining preferences of public transport use as a sustainable transportation, subjective factors such as personality traits are underexplored. Therefore, this study aimed to investigate the influence of personality traits on the number of future public transport use. Additionally, “car habit” and “intention toward using public modes” were considered to be important. For this purpose, a case study from departure passengers at Imam Khomeini International Airport (IKIA, Tehran, Iran) was conducted between January and February 2015 at IKIA. Results of structural equation modeling (SEM) shows that only neuroticism and extraversion personality traits were significant in determining future public transportation mode choice. However, the model indicates that these traits indirectly influence intention and car habit. Neuroticism was found to have a total effect of −0.022 on future public transport use, which represents a negative association with public transport use, while extraversion positively influenced future public transport use with a total effect of 0.031. Moreover, the results found interestingly that car access had a better fit to the data than the number of cars in household (NCH); both had significant positive effect on car habit, but only car access had a significant influence on intention. Furthermore, the effect of socio-demographic variables such as age, gender, educational level, income level, and body mass index (BMI) were determined to be significant in identifying choice of future transport mode to airports, which is explained in the discussion section of this paper.
Determination of antioxidant capacity using different acidified solvents and element contents of Allium tuncelianum: A regional and varietal study on endemic edible garlic

Abstract Allium tuncelianum (Tunceli garlic), an endemic and threatened plant species in the Tunceli province of Eastern Turkey, is an important native source for local people. The antioxidant activities of the acidified extracts of water, acetonitrile, methanol, and ethanol of Allium tuncelianum were investigated using five antioxidant capacity tests. The results indicated that methanol extract efficiencies of garlic samples using the ABTS, CUPRAC, and reducing power capacities were higher than the other extracts. Water extract and acetonitrile extract values were highest for total phenolic content and metal chelating activities, respectively. Moreover, the element contents such as calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn), sodium (Na), and zinc (Zn) of Allium tuncelianum samples digested by microwave and ashing ovens were determined by flame atomic absorption spectrophotometry and the results were compared statistically. The Ca, Cu, K, Mg, and Zn concentrations using the microwave method were found to be higher than the ashing procedure. However, the Fe, Mn, and Na concentrations using the ashing method were found to be higher than those using the the microwave protocol.
Getting through the day and still having a smile on my face! How do students define success in the university learning environment?

ABSTRACT The expression ‘student success’ has gained traction in the university sector and has been applied to various aspects of the higher education (HE) learning trajectory. Yet, ‘success’ is an amorphous term that means distinctive things to various stakeholders in any educational undertaking. When the literature on this field is examined, it is surprising that the ways in which students themselves articulate success within the university have rarely been explored in qualitative depth. This article details a study that applies the Capabilities Approach to understand how individual learners reflected upon success and how understandings of this concept might be used to enrich and inform the HE environment. The participants were all first in their families to come to university and approaching completion of their degree studies. This article draws on surveys and interviews to discuss students’ conceptions of ‘being successful’ in response to explicit questions on how they defined ‘success’ and whether they personally regarded themselves as successful in their student role. The deeply embodied ways students referred to success, often contextualised to their particular biographies and social realities, can inform how institutions better engage and support first-in-family students.
A Distance-Based Method for the Evaluation of Interest point Detection Algorithms

Many approaches in computer vision are based on point detection algorithms. In the literature, a wide variety of such algorithms are available. Therefore, it is an important task to evaluate existing and newly developed point detection algorithms. Up to now, this process was done by means of several methods. In this paper, we recall current point detection evaluation techniques, and motivated by their insufficiency for certain applications, we present a new application-oriented method which is based on distances between sets of points.
An E cient Algorithm for Text Data Mining with Optimal String Patterns

We study a data mining problem in a large collection of unstructured texts based on association rules over subwords of texts. A two-word association rule is an expression such as (TATA, 30, AGGAGGT)) C that expresses a rule that if a text contains a subword followed by another subword with distance no more than k then a condition C will holds with a probability. We present an e cient algorithm for computing frequent patterns that optimizes the con dence with respect to a given collection of texts. The algorithm runs in time O(mn 2 log 2 n) and in space O(kmn log n), wherem and n are the number and the total length of classi cation examples, respectively, and k is a small constant around 30 50. The algorithm employs the su x tree data structure from string pattern matching and the orthogonal range query techniques from computational geometry. We also give a faster version that runs in time O(mn 2 ) and in space O(kmn).
Kinematic and stiffness analysis of the Orthoglide, a PKM with simple, regular workspace and homogeneous performances

The Orthoglide is a Delta-type PKM dedicated to 3-axis rapid machining applications that was originally developed at IRCCyN in 2000-2001 to meet the advantages of both serial 3-axis machines (regular workspace and homogeneous performances) and parallel kinematic architectures (good dynamic performances and stiffness). This machine has three fixed parallel linear joints that are mounted orthogonally. The geometric parameters of the Orthoglide were defined as function of the size of a prescribed cubic Cartesian workspace that is free of singularities and internal collision. The interesting features of the Orthoglide are a regular Cartesian workspace shape, uniform performances in all directions and good compactness. In this paper, a new method is proposed to analyze the stiffness of overconstrained Delta-type manipulators, such as the Orthoglide. The Orthoglide is then benchmarked according to geometric, kinematic and stiffness criteria: workspace to footprint ratio, velocity and force transmission factors, sensitivity to geometric errors, torsional stiffness and translational stiffness.
Characterization and performance investigation of nanoscale MOSFETs

A novel RF-MOSFET (Radio Frequency Metal Oxide Semiconductor Field Effect Transistor) model with PTM (Predictive technology model) for 90 nm CMOS (Complementary Metal Oxide Semiconductor) technology is presented. A simple and accuracy method is developed to directly extract all the high frequency parasitic effect from measured S-parameter biased at zero and linear region. This model is proposed to overcome some of short channel effects at nano-scale highly dopped drain and source based on the conventional small signal MOSFET (Metal Oxide Semiconductor Field Effect Transistor) equivalent circuit, RF (Radio Frequency) characterization of CMOS (Complementary Metal Oxide Semiconductor) has been taken up in terms of RF Figure of Merits. The excellent correspondence is achieved between simulated and measured S-parameter (Scattering parameter) from 1GHz to 10 GHz frequency range.
Omitted factors in audio circuit design

Traditional measurements of audio amplifiers use test signals that do not represent conditions of actual use. TIM measurement is one factor in improving the correlation between audible and measurable differences in circuitry. Additionally, many circuits incorporate non-linear elements that appear to be distortionless at conventional measurement frequencies, but can be significant sources of distortion when subsonic or supersonic frequencies are included. This paper describes some of these non-linear elements and their effects on actual circuit performance.
Fiber Continuity: An Anisotropic Prior for ODF Estimation

The accurate and reliable estimation of fiber orientation distributions, based on diffusion-sensitized magnetic resonance images is a major prerequisite for tractography algorithms or any other derived statistical analysis. In this work, we formulate the principle of fiber continuity (FC), which is based on the simple observation that the imaging of fibrous tissue implies certain expectations for the measured images. From this principle we derive a prior for the estimation of fiber orientation distributions based on high angular resolution diffusion imaging (HARDI). We demonstrate on simulated, phantom, and in vivo data the superiority of the proposed approach. Further, we propose another application of the FC principle, named FC flow, a method to resolve complex crossing regions solely based on diffusion tensor imaging (DTI). The idea is to infer directional information in crossing regions from adjacent anisotropic areas.