Miracle-dz/UniFAR-FTUs huggingface dataset:
THE RELATION BETWEEN THE FOAMABILITY OF PVC PASTES AND THE QUALITY OF A PVC POLYMER

The mechanical foaming of poly(vinylchloride) (PVC) pastes is made possible by the presence of surfactants, which secure the formation of a PVC foam and its stability at the next processing. The efficiency of the surfactants that are employed in this technology may be evaluated on the basis of viscosity difference between the descending and rising part of the viscosity curve for the PVC pastes in the region of low shear rates. This criterion, the validity of which has been proven by a correlation with the rate of degradation of the foam structure, is based on the hypothesis of the formation of a spatial network of molecular and supermolecular clusters of the soap surfactant, which is insoluble in the nonaqueous medium of the PVC paste. The criterion of the viscosity difference serves to assess the pastes of different types of PVC such as Vestolit B 7021, Pevikon D 61, AST 66, and Slovinyl K 72. In connection with the foamability of PVC pastes, it is the effect of a residual emulsifier and the character of particles in terms of their average size and distribution that are discussed.
MODELING DYNAMIC FRACTURE USING LARGE-SCALE ATOMISTIC SIMULATIONS

We review a series of large-scale molecular dynamics studies of dynamic fracture in brittle materials, aiming to clarify questions such as the limiting speed of cracks, crack tip instabilities and crack dynamics at interfaces. This chapter includes a brief introduction of atomistic modeling techniques and a short review of important continuum mechanics concepts of fracture. We find that hyperelasticity, the elasticity of large strains, can play a governing role in dynamic fracture. In particular, hyperelastic deformation near a crack tip provides explanations for a number of phenomena including the “mirror-misthackle” instability widely observed in experiments as well as supersonic crack propagation in elastically stiffening materials. We also find that crack propagation along interfaces between dissimilar materials can be dramatically different from that in homogeneous materials, exhibiting various discontinuous transition mechanisms (mother-daughter and mother-daughter-granddaughter) to different admissible velocity regimes.
An efficient method for multi-level approximate logic synthesis under error rate constraint

Approximate computing is an emerging design paradigm targeting at error-tolerant applications. It trades off accuracy for improvement in hardware cost and energy efficiency. In this paper, we propose a novel approach for multi-level approximate logic synthesis under error rate constraint. The basic idea of our approach is to pick nodes in a Boolean network and shrink them by approximating their factored-form expressions. We propose two different algorithms to implement the basic idea. The first algorithm iteratively picks the most effective node at present to shrink. Its drawback lies in that it may need a large number of iterations. To overcome this drawback, the second algorithm formulates a knapsack problem to pick multiple nodes for shrinking simultaneously. It is still iterative, but the number of iterations is greatly reduced. We apply the two algorithms to MCNC benchmarks and arithmetic circuits including adders and multipliers. The experimental results demonstrated that our algorithms perform better in area saving and are 1.7 and 5.9 times faster, respectively, compared with the state-of-the-art approach.
Convergence of Trust-Region Methods Based on Probabilistic Models

In this paper we consider the use of probabilistic or random models within a classical trust-region framework for optimization of deterministic smooth general nonlinear functions. Our method and setting differs from many stochastic optimization approaches in two principal ways. Firstly, we assume that the value of the function itself can be computed without noise, in other words, that the function is deterministic. Second, we use random models of higher quality than those produced by the usual stochastic gradient methods. In particular, a first order model based on random approximation of the gradient is required to provide sufficient quality of approximation with probability $\geq 1/2$. This is in contrast with stochastic gradient approaches, where the model is assumed to be “correct” only in expectation. As a result of this particular setting, we are able to prove convergence, with probability one, of a trust-region method which is almost identical to the classical method. Moreover, the new method is si.
Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci

To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including “growth factor binding,” “matrix interaction,” and “smooth muscle contraction. ” We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.
Lexical URL analysis for discriminating phishing and legitimate websites

A study that aims to evaluate the practical effectiveness of website classification by lexically analyzing URL tokens in addition to a novel tokenization mechanism to increase prediction accuracy. The study analyzes over 70,000 legitimate and phishing URLs collected over 6 months period from PhishTank1, Khalifa University HTTP logs and volunteers using an experimental HTTP proxy server. A statistical classification model is then constructed and evaluated to measure the practical effectiveness of the lexical URL analysis presented in this paper.
Monolithic all-solid-state dye-sensitized solar cells

As a low-cost photovoltaic technology, dyesensitized solar cell (DSSC) has attracted widespread attention in the past decade. During its development to commercial application, decreasing the production cost and increasing the device stability take the most importance. Compared with conventional sandwich structure liquid-state DSSCs, monolithic all-solid-state mesoscopic solar cells based on mesoscopic carbon counter electrodes and solid-state electrolytes present much lower production cost and provide a prospect of long-term stability. This review presents the recent progress of materials and achievement for all-solid-state DSSCs. In particular, representative examples are highlighted with the results of our monolithic all-solid-state mesoscopic solar cell devices and modules.
Unequal Access to Higher Education in the Czech Republic: The Role of Spatial Distribution of Universities

We explore a potential source of human capital spatial disparities: the unequal access to tertiary education caused by the absence/presence of a local university. Because the entrance to a university is a sequential process in the Czech Republic we model both a student's decision to apply to a university and the admission process. Two possible sources of unequal access to university are distinguished: cost savings and informational advantages for those residing close to a university. Estimation results suggest that the presence of a university per se is not driving student's decision to apply. Further we find that information advantage due to university proximity plays a significant role in the admission process. However this advantage is specific to the field of study, and becomes stronger in the case of highly oversubscribed study fields. To equalize the chance of admission, policy makers should consider geographical expansion of the system of universities accompanied by the expansion of university programs.
Web service based model for inter-agent communication in multi-agent systems: A case study

Service oriented architecture (SOA) is a widely used model for enterprise application integration, mainly due to the presence of accepted standards and tools required to implement web services. While the service oriented architecture provides an elegant model for interoperability, it does not define a computational model for building the endpoints of complex distributed services it exposes in a typical enterprise application. On the other hand, software agent technology provides powerful models such as the Belief-Desire-Intention (BDI) model that allows developers to build distributed systems with enhanced reasoning capabilities. We propose a web services based communication model for inter-agent communication allowing heterogeneous agents in a multi agent system to freely collaborate. We specifically focus on goal and beliefset sharing in BDI based agents. By providing a web services based interface, we allow agents as well as non-agent based services in a distributed system to yield the benefits of agent technology. Applicability of this proposition is demonstrated by designing and implementing a prototype multi-agent system for flood forecasting.
Excitation source and low level descriptor features fusion for emotion recognition using SVM and ANN

Emotion recognition is a challenging task with many applications in healthcare and human-machine interaction. In this study we propose to fuse two sets of features for emotion recognition at the classification level. A set of features that includes LPCC and MFCC extracted from LP-residual samples and Wavelet Octave Coefficient Of Residual (WOCOR) is proposed in this study as excitation source features. The proposed set of features is fused with 6552 LLDs using SVM and ANN classifiers. The experiments are tested on a newly acquired emotional speech database in Kurdish language, the Berlin emotional speech database, and the Aibo database. The experiments demonstrate that the fusion of the proposed excitation source features with the common LLDs can achieve better recognition accuracies than what is reported in the state-of-the-art studies.
Comparison of two methods to assess physical activity prevalence in children: an observational study using a nationally representative sample of Scottish children aged 10–11 years

Objectives To describe the objectively measured levels of physical activity (PA) and sedentary time in a nationally representative sample of 10–11-year-old children, and compare adherence estimates to the UK PA guidelines using two approaches to assessing prevalence. Design Nationally representative longitudinal cohort study. Setting Scotland wide in partnership with the Growing up in Scotland (GUS) study. Data collection took place between May 2015 and May 2016. Participants The parents of 2402 GUS children were approached and 2162 consented to contact. Consenting children (n=1096) wore accelerometers for 8 consecutive days and 774 participants (427 girls, 357 boys) met inclusion criteria. Primary and secondary outcome measures Total PA (counts per minute, cpm); time spent sedentary and in moderate-to-vigorous PA (MVPA); proportion of children with ≥60 min MVPA on each day of wear (daily approach); proportion of children with ≥60 min of MVPA on average across days of wear (average approach)—presented across boys and girls, index of multiple deprivation and season. Results Mean PA level was 648 cpm (95% CI, 627 to 670). Children spent 7.5 hours (7.4–7.6) sedentary/day and 72.6 min (70.0–75.3) in MVPA/day. 11% (daily) and 68% (average) of children achieved the recommended levels of PA (P<0.05 for difference); a greater proportion of boys met the guidelines (12.5% vs 9.8%, NS; 75.9% vs 59.5%, P<0.001); guideline prevalence exhibited seasonal variation. No significant socioeconomic patterning existed across any outcome measure. Conclusions PA estimates are significantly influenced by the analytical method used to assess prevalence. This could have a substantial impact on the evaluation of interventions, policy objectives and public health investment. Existing guidelines, which focus on daily PA only may not further our understandings about the underlying construct itself. Gender differences exist within this age-group, suggesting greater investment, with particular consideration of seasonality, is needed for targeted intervention work in younger children.
A robust elliptical head tracker

A method is presented for robust head tracking in highly cluttered environments. The head's projection onto a 3D depth map of the scene is modelled as an ellipse whose position and size are constantly updated by a local search. Ellipse detection is performed on depth discontinuities using Chamfer Distance. The resultant system is a real-time, illumination and head-rotation invariant robust head tracker. The approach can be easily generalized further to perform tracking or detection of objects of different shapes e.g. hands.
Augmenting synthetic aperture radar with space time adaptive processing

Wide-area persistent radar video offers the ability to track moving targets. A shortcoming of the current technology is an inability to maintain track when Doppler shift places moving target returns co-located with strong clutter. Further, the high down-link data rate required for wide-area imaging presents a stringent system bottleneck. We present a multi-channel approach to augment the synthetic aperture radar (SAR) modality with space time adaptive processing (STAP) while constraining the down-link data rate to that of a single antenna SAR system. To this end, we adopt a multiple transmit, single receive (MISO) architecture. A frequency division design for orthogonal transmit waveforms is presented; the approach maintains coherence on clutter, achieves the maximal unaliased band of radial velocities, retains full resolution SAR images, and requires no increase in receiver data rate vis-a-vis the wide-area SAR modality. For Nt transmit antennas and N samples per pulse, the enhanced sensing provides a STAP capability with Nt times larger range bins than the SAR mode, at the cost of O(log N) more computations per pulse. The proposed MISO system and the associated signal processing are detailed, and the approach is numerically demonstrated via simulation of an airborne X-band system.
Use of bypass cement dust for production of glass ceramic materials

Abstract Bypass cement dust from the Rabigh plant in Saudi Arabia was examined for use in the preparation of technical coloured glass and glass ceramic materials. The bypass cement dust made up about 57 wt-% of the batch constituents, depending on composition. The bypass composition was sometimes modified by additions of other ingredients such as silica sand, granite and magnesite. Batches were melted and then cast into glass, which was subjected to heat treatment to induce crystallisation. Techniques including differential thermal analysis, polarising light microscopy, X-ray diffraction and indentation microhardness testing were then applied. The obtained coloured glass and glass ceramic materials possess very high hardness, indicating high abrasion resistance, and making them suitable for many applications under aggressive mechanical conditions.
Secure AES Coprocessor Against Power Analysis for Wireless Sensor Networks

Cryptographic coprocessors for wireless sensor nodes are resource-constrained devices, which require low power and a small size. Besides, with the advent of side channel attacks, resistance to such attacks becomes another major requirement. This paper describes a low-cost and high-security Advanced Encryption Standard (AES) coprocessor implementation and an optimization scheme for Wireless Sensor Networks (WSN) systems. The compact architecture of AES is applied to optimize the size of AES circuits. Its impact on the security against power analysis attack is analyzed, which is important for many WSN applications. A novel method, using inhomogeneous S-Boxes instead of fixed S-Boxes, is proposed to resist power analysis attacks. The AES coprocessor was implemented with UMC 0.25 mum 1.8v CMOS standard cell library and power analysis experiments were conducted. The results demonstrate that our proposed design has very low hardware cost and enhances the AES secure characteristics effectually.
Low Velocity Friction Compensation and Feedforward Solution based on Repetitive Control

One of the most significant sources of tracking error for an X-Y table is static friction, a nonlinear disturbance. Static friction, or stiction, occurs when an axis makes a zero velocity crossing, i.e. when an axis reverses direction. In traversing a circular profile for example. an X-Y table encounters zero velocity crossings at ninety degree intervals around the circle, leaving relatively large tracking errors referred to as "quadrant glitches". To eliminate errors caused by stiction, repetitive control, a subclass of learning control, is employed. Experiments are conducted on the X-Y bed of a CNC milling machine. The repetitive controller is implemented digitally in the position servo loop. The velocity loop is closed internally by an analog PI servo which is part of the original controller of the CNC milling machine. The repetitive controller undergoes successive passes in tracking a profile containing a zero velocity crossing. The repetitive controller contains an internal periodic signal generator which receives the error over repetitive cycles and generates a compensating input for cancellation of the repetitive disturbance. Experimental data indicates that perfect velocity tracking can be achieved in twelve cycles or less. Of particular interest is the velocity command input generated by repetitive control. The input contains feedforward information for developing perfect trajectoris at low velocities. An analysis for using the feedforward information for zero velocity crossings at different local accelerations is developed.
A unified framework for approximating and clustering data

Given a set F of n positive functions over a ground set X, we consider the problem of computing x* that minimizes the expression ∑f ∈ Ff(x), over x ∈ X. A typical application is shape fitting, where we wish to approximate a set P of n elements (say, points) by a shape x from a (possibly infinite) family X of shapes. Here, each point p ∈ P corresponds to a function f such that f(x) is the distance from p to x, and we seek a shape x that minimizes the sum of distances from each point in P. In the k-clustering variant, each x\in X is a tuple of k shapes, and f(x) is the distance from p to its closest shape in x. Our main result is a unified framework for constructing coresets and approximate clustering for such general sets of functions. To achieve our results, we forge a link between the classic and well defined notion of ε-approximations from the theory of PAC Learning and VC dimension, to the relatively new (and not so consistent) paradigm of coresets, which are some kind of "compressed representation" of the input set F. Using traditional techniques, a coreset usually implies an LTAS (linear time approximation scheme) for the corresponding optimization problem, which can be computed in parallel, via one pass over the data, and using only polylogarithmic space (i.e, in the streaming model). For several function families F for which coresets are known not to exist, or the corresponding (approximate) optimization problems are hard, our framework yields bicriteria approximations, or coresets that are large, but contained in a low-dimensional space. We demonstrate our unified framework by applying it on projective clustering problems. We obtain new coreset constructions and significantly smaller coresets, over the ones that appeared in the literature during the past years, for problems such as: k-Median [Har-Peled and Mazumdar,STOC'04], [Chen, SODA'06], [Langberg and Schulman, SODA'10]; k-Line median [Feldman, Fiat and Sharir, FOCS'06], [Deshpande and Varadarajan, STOC'07]; Projective clustering [Deshpande et al., SODA'06] [Deshpande and Varadarajan, STOC'07]; Linear lp regression [Clarkson, Woodruff, STOC'09 ]; Low-rank approximation [Sarlos, FOCS'06]; Subspace approximation [Shyamalkumar and Varadarajan, SODA'07], [Feldman, Monemizadeh, Sohler and Woodruff, SODA'10], [Deshpande, Tulsiani, and Vishnoi, SODA'11]. The running times of the corresponding optimization problems are also significantly improved. We show how to generalize the results of our framework for squared distances (as in k-mean), distances to the qth power, and deterministic constructions.
Antigenic Characterization of Embryo Stage of Setaria Cervi

Filariasis is a serious health hazard affecting millions of people in tropical and subtropical regions of developing countries including India. The specific diagnosis and control measures are essential for effective management of the disease. It has been shown earlier that the excretorysecretory products of filarial parasitescontain diagnostically important embryo antigens; therefore, it would be important to identify and characterize the embryo stage antigens having potential for serodiagnosis of human filariasis. In the present study efforts were made to analyse the protein and antigenic pattern of embryo stage of Setaria cervi, the bovine filarial parasite. The S. cervi embryos (ScEmb) were isolated by dissecting adult female worms and purified using Percoll gradient. The SDSPolyacrylamide gel electrophoresis revealed15-18 protein bands in S. cervi embryo somatic extract in molecular weight range of 6.5 – 200 kDa. The polyclonal antibodies produced against S. cervi embryo showed significantly high reactivity with ScEmbantigens as well aswith antigens fromadult and microfilarialstages. The 10-14 protein bandsof S. cervi embryo were recognized by anti-ScEmb polyclonal antibodies in immunoblotting.These studies revealed some qualitative and quantitative differences among the antigenic pattern of three stage of S.cervi. The S.cervi embryos exhibited high reactivity with antibodies present in filarial patients’ serathereby suggesting the presence of some antigens common/cross-reactive with human filarial parasite. The protein bands of 60 kDa, 45 kDa, 29 kDa and 27 kDa of S. cervi embryo stage were recognized by filarial patients serum pool and may have diagnostic utility in human lymphatic filariasis Manuscript received January 10, 2016; revised June 2