Miracle-dz/UniFAR-FTUs huggingface dataset:
ACE: Asynchronous and Concurrent Execution of Complex Smart Contracts

Smart contracts are programmable, decentralized and transparent financial applications. Because smart contract platforms typically support Turing-complete programming languages, such systems are often said to enable arbitrary applications. However, the current permissionless smart contract systems impose heavy restrictions on the types of computations that can be implemented. For example, the globally-replicated and sequential execution model of Ethereum requires low gas limits that make many computations infeasible. In this paper, we propose a novel system called ACE whose main goal is to enable more complex smart contracts on permissionless blockchains. ACE is based on an off-chain execution model where the contract issuers appoint a set of service providers to execute the contract code independent from the consensus layer. The primary advantage of ACE over previous solutions is that it allows one contract to safely call another contract that is executed by a different set of service providers. Thus, ACE is the first solution to enable off-chain execution of interactive smart contracts with flexible trust assumptions. Our evaluation shows that ACE enables several orders of magnitude more complex smart contracts than standard Ethereum.
Design , Synthesis and Evaluation of N-Aryl Carboxamide Derivatives as Potential AntiProliferative Effect on the Pulmonary Artery Smooth Muscle Cells

A new series of compounds, cinnamamide’s and 2-hydroxy-N-arylbenzamide’s derivatives, were synthesized by condensation reaction of cinnamic acid chlorides and salicylic acid chlorides with amino-aryl’s derivatives. The chemical structure of these compounds was confirmed by means H NMR and C NMR. All of the compounds were assayed for anti-proliferative effect on isolated pulmonary arterial smooth muscle cells (PA-SMCs) by BrdU incorporation. We found that compounds: 5, 6, 9-13 and 16, showed marked inhibition of PA-SMCs proliferation. Structure–activity relationship analysis showed that compounds benzamide’s derivatives have better inhibitory effects than the others. Keyword: Cinnamide; N-Aryl-Carboxamide; Pulmonary arterial hypertension; Pulmonary arterial smooth muscle cells; Heteroarylamines
Variability Normalization via Hierarchical Deep Neural Networks for Online Handwritten Chinese Character Recognition

This paper presents a novel irrelevant variability normalization (IVN) approach via hierarchical deep neural networks (HDNNs) and prototype-based classifier for online handwritten Chinese character recognition. The recent insight of deep neural network (DNN) is the deep architecture with large training data can bring the best performance in many research areas. The architecture design of our proposed hierarchical deep neural networks focuses on both “depth” and “width” of artificial neural network. Specifically for the multivariate regression, HDNN consists of multiple subnets, which is empirically more powerful than DNN. In this work, HDNN is adopted as a nonlinear feature transform to normalize the feature vector of handwritten samples with irrelevant variabilities to a target prototype. The effectiveness of proposed method is verified on a Chinese handwriting recognition task. Furthermore, we have an very interesting observation that DNN-based IVN can not even bring performance gain over the prototype-based classifier while HDNN-based IVN yields significant improvements of recognition accuracy.
On Laughter Intensity Level : Analysis and Estimation

This work focuses on laughter intensity level, the way it is perceived and suggests ways to estimate it automatically. In the first part of this paper, we present a laughter intensity database which is collected through online perception tests. Participants are asked to rate the overall intensity of laughs. Presented laughs are either audio only or visual only or audiovisual. Statistical analysis show that the perceived intensity is significantly higher when the modality is visual only and suggests that the audio cue might have the biggest influence on laughter intensity perception.We also show that the order by which the modalities are presented to the raters may influence the perception of laughter intensity. In the second part, different estimation/classification techniques were tested including GMM-based mapping and common classification techniques. A set of features were defined, extracted and tested for classification. Results show that the estimation of the global audio laughter intensity is possible with good classification performances.
Analyzing the similarities of actions based on video clustering

In this paper, we propose a novel approach to represent a verb as a set of attribution vectors. Similarities between verbs are defined as distances between their representative attribution vectors sets. By ranking distances between these sets, several pairs of verbs which are visually similar are found from a collection of verbs. We then use dendrogram to illustrate the similarities between verbs pairs. Each verb is drawn as a leaf node in a dendrogram. By counting number of nodes between leaf nodes and height of connected branches, similarities can be easily estimated.
Evaluation of forecasting approaches using hybrid multi-criteria decision-making models

The demand forecast is the most influential input into enterprise activities planning thus creating a challenging issue for Demand Planning experts in model selection. Models including quantitative, qualitative and hybrid forecasting methods have been developed and are widely used. The literature reveals the use of several case-dependent error measures to evaluate forecasting accuracy, however, these performance indicators may at times differentiate in results making it more difficult in determining the most appropriate forecasting model for the users’ needs. This paper presents the development of two hybrid multi-criteria decision making approaches, AHP-TOPSIS and ANP-TOPSIS, to evaluate and rank the relative performances based on error measures of alternate forecasting models. Validation is provided through an industrial application using empirical data from a plastic bag manufacturer based on five models; three regression forecast models and two hybrid demand forecast models using expert judgement. Results illustrate that subjective adjustment by experts of mathematical forecasts consistently gives a higher ranking due to proximity to the ideal solution, and that collaborative adjustment limits the risk of outliers due to forecasting errors that could be done by a single decision maker.
A Two-level Intrusion Detection System for Industrial Control System Networks using P4

The increasing number of attacks against Industrial Control Systems (ICS) have shown the vulnerability of these systems. Many ICS network protocols have no security mechanism and the requirements on high availability and real-time communication make it challenging to apply intrusive security measures. In this paper, we propose a two-level intrusion detection system for ICS networks based on Software Deﬁned Networking (SDN). The ﬁrst level consists of ﬂow and Modbus whitelists, leveraging P4 for efﬁcient real-time monitoring. The second level is a deep packet inspector communicating with an SDN controller to update the whitelists of the ﬁrst level. We show by experiments in an emulated environment that our design has only a small impact on communication latencies in the ICS and is efﬁcient against Modbus/TCP oriented attacks.
Competences of Undergraduate Computer Science Students

The paper presents two approaches to the development of a Computer Science Competence Model for the needs of curriculum development and evaluation in Higher Education. A normativetheoretical approach is based on the AKT and ACM/IEEE curriculum and will be used within the recommendations of the German Informatics Society (GI) for the design of CS curricula. An empirically oriented approach refines the categories of the first one with regard to specific subject areas by conducting content analysis on CS curricula of important universities from several countries. The refined model will be used for the needs of students’ e-assessment and subsequent affirmative action of the CS departments.
Scalable Convolutional Neural Network for Image Compressed Sensing

Recently, deep learning based image Compressed Sensing (CS) methods have been proposed and demonstrated superior reconstruction quality with low computational complexity. However, the existing deep learning based image CS methods need to train different models for different sampling ratios, which increases the complexity of the encoder and decoder. In this paper, we propose a scalable convolutional neural network (dubbed SCSNet) to achieve scalable sampling and scalable reconstruction with only one model. Specifically, SCSNet provides both coarse and fine granular scalability. For coarse granular scalability, SCSNet is designed as a single sampling matrix plus a hierarchical reconstruction network that contains a base layer plus multiple enhancement layers. The base layer provides the basic reconstruction quality, while the enhancement layers reference the lower reconstruction layers and gradually improve the reconstruction quality. For fine granular scalability, SCSNet achieves sampling and reconstruction at any sampling ratio by using a greedy method to select the measurement bases. Compared with the existing deep learning based image CS methods, SCSNet achieves scalable sampling and quality scalable reconstruction at any sampling ratio with only one model. Experimental results demonstrate that SCSNet has the state-of-the-art performance while maintaining a comparable running speed with the existing deep learning based image CS methods.
Ursolic acid suppresses the invasive potential of colorectal cancer cells by regulating the TGF-β1/ZEB1/miR-200c signaling pathway

Ursolic acid (UA) is a biologically active compound, commonly used in traditional Chinese medicine (TCM). It has been reported to exhibit strong anticancer properties against a variety of cancers. Our previous studies showed that UA promoted apoptosis in colorectal cancer (CRC) cells and inhibited cellular proliferation and angiogenesis. However, the effect and underlying molecular mechanism of UA in CRC progression remain unclear. In the present study, the role of UA in suppressing the migration and invasion of human colon cancer HCT116 and HCT-8 cells was investigated, using Transwell assays. In addition, to evaluate whether the anticancer properties of UA were mediated by the regulation of a double-negative feedback loop consisting of the transforming growth factor-β1 (TGF-β1)/zinc finger E-box-binding homeobox (ZEB1) pathway and microRNA (miR)-200a/b/c, reverse transcription-quantitative PCR and western blot analysis were performed. The results indicated that UA treatment significantly suppressed cellular growth, migration and invasion in HCT116 and HCT-8 cells in a dose-dependent manner. Furthermore, following UA treatment, several crucial mediators of the TGF-β1 signaling pathway, including TGF-β1, phosphorylated (p)-Smad2/3, p-focal adhesion kinase and ZEB1, were significantly downregulated in the HCT116 and HCT-8 cell lines compared with the control group. Furthermore, the ratio of N-cadherin/E-cadherin, two proteins directly downstream of the TGF-β1 signaling pathway, was found to be downregulated in UA treated CRC cells. Finally, UA significantly upregulated miR200a/b/c, with miR-200c exhibiting the highest increase in expression levels following UA treatment. Collectively, the present study suggested that inhibition of CRC cell invasion by UA occurred via regulation of the TGF-β1/ZEB1/miR-200c signaling network, which may be one of the mechanisms by which UA appears to be an effective therapeutic agent against colon cancer.
Occlusion Management in VR: A Comparative Study

VR applications rely on the user's ability to explore the virtual scene efficiently. In complex scenes, occlusions limit what the user can see from a given location, and the user has to navigate the viewpoint around occluders to gain line of sight to the hidden parts of the scene. When the disoccluded regions prove to be of no interest, the user has to retrace their path, making scene exploration inefficient. Furthermore, the user might not be able to assume a viewpoint that would reveal the occluded regions due to physical limitations, such as obstacles in the real world hosting the VR application, viewpoints beyond the tracked area, or viewpoints above the user's head that cannot be reached by walking. Several occlusion management methods have been proposed in visualization research, such as top view, X-ray, and multiperspective visualization, which help the user see more from the current position, having the potential to improve the exploration efficiency of complex scenes. This paper reports on a study that investigates the potential of these three occlusion management methods in the context of VR applications, compared to conventional navigation. Participants were required to explore two virtual scenes to purchase five items in a virtual Supermarket, and to find three people in a virtual parking garage. The task performance metrics were task completion time, total distance traveled, and total head rotation. The study also measured user spatial awareness, depth perception, and simulator sickness. The results indicate that users benefit from top view visualization which helps them learn the scene layout and helps them understand their position within the scene, but the top view does not let the user find targets easily due to occlusions in the vertical direction, and due to the small image footprint of the targets. The X-ray visualization method worked better in the garage scene, a scene with a few big occluders and a low occlusion depth complexity’ and less well in the Supermarket scene, a scene with many small occluders that create high occlusion depth complexity. The multi-perspective visualization method achieves better performance than the top view method and the X-ray method, in both scenes. There are no significant differences between the three methods and the conventional method in terms of spatial awareness, depth perception, and simulator sickness.
Explaining work-life conflict of men and women across Europe-disentangling the impact of social policy

127 words) Although many studies that examine work-family conflict issues, empirical results on the impact of social policy on individual‟s work-family conflict are still inconclusive. In addition, the different impacts of family policies on the work-family conflict levels for men and women have not yet been examined in depth. This paper examines the impact of family policy on work-family conflict of men and women using data from 2007 across 28 European countries. Results show that family policies do impact work-family conflict of both men and women, but this is mostly done indirectly through the impact social policy has on job demands and resources of individuals. This is especially true for women, where when job demands and resources are taken into account, we do not observe large differences across countries.
Post-focus compression is not automatically transferred from Korean
 to L2 English*

Korean and English are both known to show on-focus pitch range expansion and post-focus pitch range compression (PFC). But it is not clear if this prosodic similarity would make it easy for Korean speakers to learn English focus prosody. In the present study, we conducted a production experiment using phone number strings to examine whether Korean learners of English produce a native-like focus prosody. Korean learners of English were classified into three groups (advanced, intermediate and low) according to their English proficiency and were compared to native speakers. Results show that intermediate and low groups of speakers did not increase duration, intensity, and pitch in the focus positions, nor did they compress those cues in the post-focus positions. Advanced speakers noticeably increased the acoustic cues in the focus positions to a similar extent as native speakers. However, their performance in post-focus positions was quite far from that of native speakers in terms of pitch and excursion size. These results thus demonstrate a lack of positive transfer of focus prosody from Korean to English in L2 learning, and learners may have to relearn it from scratch, which is consistent with a previous finding. More importantly, the results provide further support for the view proposed in other works that acoustic properties of PFC were not easily transferred from one language to another.
Crest: Novel Ocean Rendering Techniques in an Open Source Framework

We present Crest, an open source ocean renderer implemented in Unity3D which showcases a number of novel techniques in mesh generation, shape representation and surface shading. To generate the geometry we extend clipmapping with continuous level of detail, and a strip of skirting geometry to extend to the horizon. The surface is composed of non-overlapping tiles which support frustum culling. To maintain screen space mesh density, we show how to scale the mesh horizontally when camera changes height, without noticeable pops. We also implement a simple heuristic for placing the detail center in front of the viewer which is robust to all view positions and directions. We render ocean shape on the GPU into displacement textures, arranged to match the density and placement of the geometry LODs. We limit the number of Gerstner wavetrains added if the wavelengths are too short for each shape texture to avoid aliasing and unnecessary work. We also use ping-pong render targets to simulate the wave equation to add a dynamic layer of motion. For shading, we show that normal map UVs can be scaled with the geometry LOD rings to achieve detail close to viewer, as well as preventing the glassy flat appearance of insufficient detail in the mid to far distance, and eliminating visible repetition. For foam we add additional render targets alongside the shape textures and use feedback render passes to emulate dissipation. Finally, we'll show results from applying depth peeling to achieve non-trivial light transport paths through multiple surfaces.
OUTLINING THE PORT HEDLAND STYLE : A DISTINCTIVE LOCAL SIGNATURE WITHIN THE BROADER SHARED ICONOGRAPHIES OF THE PILBARA , NORTHWEST AUSTRALIA

__________________________________________________________________________ This paper explores the use of style to define homogeneity and heterogeneity within and across rock art provinces in the Pilbara, focusing on the Port Hedland region of northwest Australia. It is proposed that within the Port Hedland rock art repertoire there are two styles: a heterogeneous and distinct local style, distinguished by highly variable anthropomorphs, marine fauna and material culture items, set against a dominant homogeneous style including geometric and track motifs. These two distinct components within the one rock art body have been argued to represent both localised signalling of territoriality, and broader inter-group bounding. The relationship between these two components are examined to understand how Port Hedland was positioned within the chains of stylistic connection across the broader Pilbara region. JOURNAL OF THE ANTHROPOLOGICAL SOCIETY OF SOUTH AUSTRALIA Volume 40, December 2016 7
Evaluating the extremely elderly at a pulmonary function clinic for the diagnosis of respiratory disease: frequency and technical quality of spirometry

ABSTRACT Objective: To determine the frequency of spirometry in elderly people, by age group, at a pulmonary function clinic, to assess the quality of spirometry in the extremely elderly, and to determine whether chronological age influences the quality of spirometry. Methods: This was a cross-sectional retrospective study evaluating information (spirometry findings and respiratory questionnaire results) obtained from the database of a pulmonary function clinic in the city of Aracaju, Brazil, for the period from January of 2012 to April of 2017. In the sample as a whole, we determined the total number of spirometry tests performed, and the frequency of the tests in individuals ≥ 60 years of age, ≥ 65 years of age, and by decade of age, from age 60 onward. In the extremely elderly, we evaluated the quality of spirometry using criteria of acceptability and reproducibility, as well as examining the variables that can influence that quality, such a cognitive deficit. Results: The sample comprised a total of 4,126 spirometry tests. Of those, 961 (23.30%), 864 (20.94%), 102 (2.47%), and 26 (0.63%) were performed in individuals ≥ 60, ≥ 65, ≥ 86, and ≥ 90 years of age (defined as extreme old age), respectively. In the extremely elderly, the criteria for acceptability and reproducibility were met in 88% and 60% of the spirometry tests (95% CI: 75.26-100.00 and 40.80-79.20), respectively. The cognitive deficit had a negative effect on acceptability and reproducibility (p ≤ 0.015 and p ≤ 0.007, respectively). Conclusions: A significant number of elderly individuals undergo spirometry, especially at ≥ 85 years of age, and the majority of such individuals are able to perform the test in a satisfactory manner, despite their advanced age. However, a cognitive deficit could have a negative effect on the quality of spirometry.
Some Basic Concepts of Part Standardization and Parts Library 2 . 1 Basic concept of part standardization

Product design standardization is a prevailing approach to promote the speed and quality of product development. Facts have proven that only cross-enterprise and large-scope standardization can exert the effect of standardization sufficiently. The traditional statistical methods of parts spectrum only apply within the enterprises; thus, a new approach is required for part standardization in a large scope. In this study, a folk evaluation approach for part standardization is proposed. This approach combines the philosophy of web 2.0 into the webbased parts library to facilitate part standardization in a large scope. According to the differences of evaluation data sources, the folk evaluation method includes two methods, namely, digg-based evaluation and user requirement-based evaluation. The technique details are discussed in this study, and the instance cases are conducted to demonstrate the method.
653 GPS / GLONASS COMBINED PRECISE POINT POSITIOINING FOR HYDROGRAPHY – CASE STUDY ( ASWAN , EGYPT )

Global Positioning System (GPS) is ideally suited for inshore and offshore positioning because of its high accuracy and the short observation time required for a position fix. Precise point positioning (PPP) is a technique used for position computation with a high accuracy using a single GNSS receiver. It relies on highly accurate satellite position and clock data that can be acquired from different sources such as the International GNSS Service (IGS). PPP precision varies based on positioning technique (static or kinematic), observations type (single or dual frequency) and the duration of observations among other factors. PPP offers comparable accuracy to differential GPS with safe in cost and time. For many years, PPP users depended on GPS (American system) which considered the solely reliable system. GLONASS’s contribution in PPP techniques was limited due to fail in maintaining full constellation. Yet, GLONASS limited observations could be integrated into GPS-based PPP to improve availability and precision. As GLONASS reached its full constellation early 2013, there is a wide interest in PPP systems based on GLONASS only and independent of GPS This paper investigates the performance of kinematic PPP solution for the hydrographic applications in Egypt based on GPS/GLONASS combined constellations as well as investigation the performance of kinematic PPP solution based on GLONASS constellation solely.