Miracle-dz/UniFAR-FTUs huggingface dataset:
Micro-scale characterization of fluid flow in a uniform particle pack using coupled discrete element-lattice Boltzmann method

Particle scale investigation of geo-mechanical phenomena using numerical simulations has increasingly attracted the attention of researchers stimulated by recent advances in computational capacities. In this paper, the pore scale characteristics of flow in a particulate soil pack is investigated. A randomly distributed pack of uniform particles is created using a discrete element simulation of 500 particles with 9mm diameter settling freely into a box. Then the lattice-Boltzmann method is utilized to simulate a constant flow passing through the particle pack with a wide range of Reynolds numbers from 10-4 to 18. Subsequently, the pressure loss occurred in the flow when it passes through the particles is studied to characterize the transformation of flow conditions from laminar to turbulent mode. The pore scale characteristics of the flow, e.g. fow tortuosity, are then compared to those of pack scale, e.g. fluid pressure difference between base and top of the particle pack to acquire more understanding on transforming from laminar to turbulent flow in micro (pore scale) and macro (pack) levels. Furthermore, the effects of flow rates demonstrated by Reynolds numbers are examined on the drag forces applied on particles. Discussions on the micro-scale behaviour of flow in porous media based on the results obtained from numerical simulations are provided.
TOWARDS A SCALABLE ESPINA FOR NEUROSCIENCE DATA ANALYSIS

ESPINA is an image segmentation tool designed to analyse microscopy images in order to identify neuronal structures and to produce 3D models of these structures. This tool allows to display three-dimensional volumes using auto-stereoscopic monitors. It was initially designed for workstations, but when data volume management or its processing complexity makes unfeasible the implementation of the new tools on these computers, it is necessary to resort to computing servers that delimit response times or by means of scalable solutions and algorithmic optimizations. This paper analyses the migration of this tool from the original implementation to a scalable solution and describes the experience achieved during the development of the workstation version. The proposed alternative is a distributed version of the tool that delegate heavy-computational processes to a cluster, improving the performance of the system in a master/slave architecture.Copyright © 2011 by ASME
Simulating Long Range Transport of Radioactive Aerosols Using a Global Aerosol Transport Model

ABSTRACTStudy of long range transport of radioactive gases and aerosols is necessary to estimate radiological impact to the members of public and environment during nuclear reactor accidents. In the present work, an attempt has been made to employ an atmospheric circulation model that predicts meteorological parameters at the regional and global scales, and a transport model that utilizes these meteorological parameters for the radioactive aerosol dispersion. Non-hydrostatic Icosahedral Atmospheric Model (NICAM) coupled with Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) is adapted to fulfil this objective, which is used for simulating effects of conventional aerosols on atmospheric pollution and climate system. As an illustrative case study, global simulation is carried out for a horizontal resolution of ~110 km to model the dispersion of radioactive aerosol (35S, 131I and 137Cs) releases from the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. The results obtained from this case study are compared with the available literature data and other simulation results. The statistical analyses show that the comparisons are better for locations far away (> 150 km) from the emission location, and the results are further discussed. Continuous run of this system will help in predicting the activity concentration in forecast mode, and it may be used for decision support, particularly in the case of long range transport (> 100 km).
Domestic demand, export and economic growth in Bangladesh: A cointegration and VECM approach

Using cointegration and error-correction mechanism techniques, this paper investigated the causal relationship between domestic demand, export and economic growth using data pertaining to Bangladesh’s final household consumption and government consumption as a measure of domestic demand, real exports, and real GDP over the period 1971–2011. It is found that final household consumption, final government consumption and export influence short-run and long-run economic growth. Thus, there is a dynamic relationship among domestic demand, export, and economic growth in Bangladesh. Moreover, economic growth in Bangladesh has an impact on its domestic demand and exports in the short-run, but in the long-run economic growth has an impact on final household consumption only.
Orlan: Millennial Female

The French performance artist Orlan has acquired both fame and infamy for her performances. A multimedia artist since the 1960s, she embarked at the beginning of the 1990s on a project of body modification through plastic surgery, the basic premise of which was to transform herself into a digitally designed pastiche of the greatest icons of female beauty in Western art. Orlan's project has sparked intense debate in the visual arts, among feminists, and among those concerned with medical ethics, as it raises complex questions about sexuality, beauty, subjectivity, gender and technology. This book addresses all these issues, and focuses on the interrelations of dress, body and culture in Orlan's work since the 1960s. Surgical performances represent the most extreme phase of Orlan's artistic practice, but she has made extensive and varied use of costume throughout her career.Using the 'body theory' and theories of monstrosity developed by feminist, gender and film theorists, and the work of philosophers Luce Irigaray and Gilles Deleuze, the author examines the challenges Orlan's performance art poses to its viewers. Anyone working in the fields of gender, the visual arts or cultural studies will find this book and the questions it raises provocative and enlightening.
A real-time intrusion detection system for the Windows environment

This paper presents a prototype real-time intrusion detection system (IDS) for the Windows platform. It combines data mining and intrusion detection techniques to detect intrusions from sequences of native API calls. It analyses Windows native API calls in real-time using the probabilistic cover coefficient clustering algorithm. We intentionally used a simple, computationally-fast algorithm that is able to incorporate historical data into the detection process while still allowing the IDS to run in real-time. We demonstrate our prototype using artificial intrusion sequences. Although the test data produced a number of false positives, no false negatives were recorded.
Extrapolation methods for accelerating unsteady partitioned fluid-structure interaction simulations

The advantages of an unsteady implicit partitioned Fluid-Structure Interaction Scheme are, especially for large time step sizes, accompanied by a high number of inner iterations needed. This work investigates the use of extrapolation techniques in between time steps to obtain a smaller number of inner iterations. In contrast to previous works not only the structural displacement but also the fluid field variables are considered for extrapolation. The different extrapolation approaches are compared within a numerical benchmark.
The differential roles of brand credibility and brand prestige in consumer brand choice

This study explores how brand credibility and brand prestige affect brand purchase intention and empirically investigates how the combinatory mechanism of brand credibility and brand prestige materialize across multiple product categories. The proposed model of six latent constructs is tested with structural equation modeling analysis: brand credibility, brand prestige, perceived quality, information costs saved, perceived risk, and brand purchase intention. The results suggest that both brand credibility and brand prestige positively influence brand purchase intention through perceived quality, information costs saved, and perceived risk under different product categories representing the high and low self-expressive nature. Several implications for advertising messages and brand positioning strategies are discussed. © 2010 Wiley Periodicals, Inc.
Aluminene as highly hole‐doped graphene

Monolayer structures made up of purely one kind of atom are fascinating. Many kinds of honeycomb systems including carbon, silicon, germanium, tin, phosphorus and arsenic have been shown to be stable. However, so far the structures are restricted to group-IV and V elements. In this work we systematically investigate the stability of monolayer structures made up of aluminium, in four different geometric configurations (planar, buckled, puckered and triangular), by employing density functional theory‐based electronic structure calculation. Our results on cohesive energy and phonon dispersion predict that only the planar honeycomb structure made up of aluminium is stable. We call it ‘aluminene’ according to the standard naming convention. It is a metal. Results of electronic band structure suggest that it may be regarded as a highly hole-doped graphene. We also present the tight-binding model and the Dirac theory to discuss the electronic properties of aluminene.
The effects of Geography Information System (GIS) based teaching on underachieving students’ mastery goal and achievement

Recent studies indicate that the number of students electing to study Geography in Malaysian upper secondary schools, and their level of achievement in the subject, has declined. The main factor appears to be a lack of motivation. Yet there has been little research into the impact of instructional methods on Geography students’ motivation and their learning outcomes. This study applies a concurrent triangulation mixed method model to determine the effect of GIS based teaching on underachieving students’ achievement and their motivation to learn Geography. The quantitative data were collected through a quasi-experimental design while the qualitative data were collected through students’ interviews. The treatment groups included 44 students and control group with 40 students. For the treatment group, a unit on the type and distribution of world vegetation was given with GIS-based lesson material. For the control group, the same subject matter was presented using the traditional teaching methods. The quantitative evaluation showed the mastery goal and achievement post-test mean score of experiment group student participants’ are significantly higher than control group student participants. The evaluations of student participants’ interviews are consistent with quantitative findings. The triangulation of the quantitative and qualitative data reveals that GIS-based teaching had a more positive effect as compared to traditional teaching methods in enhancing participants’ mastery goal learning motivation and achievement in the topics being taught in the classroom. Thus, it is possible to draw overall conclusion that GIS based teaching has positively impact the student participants’ achievement and motivation to learn Geography.
Global Convergence of the Alternating Projection Method for the Max-Cut Relaxation Problem

The Max-Cut problem is an NP-hard problem. Extensions of von Neumann's alternating projections method permit the computation of proximity projections onto convex sets. The present paper exploits this fact by constructing a globally convergent method for the Max-Cut relaxation problem. The feasible set of this relaxed Max-Cut problem is the set of correlation matrices, hence the correlation problem is also considered.
Comparative Study on Knowledge Transfer Among Different Networks: a Social Capital Perspective

This paper examines how social capital dimensions of networks affect the transfer of knowledge between network members. There are different characteristics of social capital among three network types: MNCs, strategic alliances and industrial clusters. Based on comparing dimension of social capital among three network types, we links structural, cognitive, and relational dimensions for the three network types with knowledge transfer between network members. At last, using a social capital framework, this paper compares the conditions that promoting knowledge transfer for the different network types. Keywords-network; knowledge transfer; social capital
IMAGE ANALYSIS FOR MODELLING SHEAR BEHAVIOUR

Through laboratory research performed over the past ten years, many of the critical links between fracture characteristics and hydromechanical and mechanical behaviour have been made for individual fractures. One of the remaining challenges at the laboratory scale is to directly link fracture morphology of shear behaviour with changes in stress and shear direction. A series of laboratory experiments were performed on cement mortar replicas of a granite sample with a natural fracture perpendicular to the axis of the core. Results show that there is a strong relationship between the fracture’s geometry and its mechanical behaviour under shear stress and the resulting damage. Image analysis, geostatistical, stereological and directional data techniques are applied in combination to experimental data. The results highlight the role of geometric characteristics of the fracture surfaces (surface roughness, size, shape, locations and orientations of asperities to be damaged) in shear behaviour. A notable improvement in shear understanding is that shear behaviour is controlled by the apparent dip in the shear direction of elementary facets forming the fracture.
Reinterpreting Form Bionic Design and its Application in Design Innovation with Multiple Methods

This paper expounds the background and market demands of the application of Form Bionic Design (FBD) in design innovation. Then it analyses the advantages of FBD and existing misunderstandings on its definition and application, leading to the topic on how to correctly understand the classification of Bionic Design. Also it clarifies the significance of the integration of Bionic Design, proposing that FBD should follow the requirements of users and Design Hardpoints (DHPs). Then through a series of design cases it introduces the application of FBD compromised with several special methods, which includes Userexperiencing in simulation, Modular Design for system optimization and Keywords on style positioning. Meanwhile it respectively discusses the purpose, the function and particular application of each method, providing practical reference for its particular combination with FBD.
Aquatic and semi-aquatic Hemiptera of three oxbow lakes of Cachar District, Assam, N. E India and their role as bioindicator

Aquatic insects comprise taxonomically diverse and ecologically important and interesting group of animals in fresh water systems. Among them the aquatic and semi-aquatic Hemiptera occupies an important position. Over the Cachar plain the River Barak has an extremely meandering course forming large number of oxbow lakes locally known as anua. For the present study Gandhinagar anua, Bekirpar anua and Shibnarayanpur anua were selected from the district. Insects were collected seasonally by standard methods from all the possible substrata during 2012-13. The study recorded 8 families of both infra-orders Nepomorpha and Gerromorpha. Nepomorpha families were higher in number which included Corixidae, Nepidae, Notonectidae, Pleidae and Belostomatidae while family Gerridae, Veliidae and Mesoveliidae were recorded from Gerromorpha. Various biomonitoring scoring indices like BMWP THAI , ASPT THAI and NLBI were used to assess the ecosystem health of the oxbow lakes. This study finds that Gandhinagar anua is in relatively better condition, but also requires attention as human activity determines the fate of an ecosystem.
A Scalable Method for a Particular Scheduling Problem Based on Boolean Satisfiability

In recent years, people made a lot of progress for solving Boolean satisfiability problem. Existing solvers have been successful in dealing with problems with thousands of Boolean variables in reasonable amount of time. And there is a trend to use Boolean satisfiability solvers to deal with practical problems. In this paper, we investigate a method for reducing a particular type of scheduling problem to Boolean satisfiability. Hence we are able to use existing solvers to solve practical scheduling problems and get good performance. Introduction Boolean satisfiability problem is considered one of the most classical problems in computing. Traditionally, it is the first NP-complete problem and has been receiving a lot of attention. But the nature of the problem determines that it is nearly impossible to find any tractable method for solving this problem. However, in the last two decades, people made huge progress in solving Boolean satisfiability problem [1,2,3,4]. Some major techniques involve watched-literal technique [5] and clause learning technique [6]. Due to these advanced techniques, existing Boolean satisfiability solvers are able to perform well on practical problems. These problems may contain thousands of Boolean variables, or even millions in some cases. So there is a trend to use Boolean satisfiability solvers to tackle problems of practical interests. In this paper, we propose a method, which can reduce a scheduling problem to Boolean satisfiability problem. The idea is as follows. In some process of manufacturing, there are some jobs to be done and some limited resources to use. There are some constraints, which say a particular job can only use some particular resources, but there may be alternative resources. For example, to complete job A, one may either use material M1 and line L1, or use material M2 and line L4. And the goal is to find a way of taking maximum use of available resources to complete all the jobs, subject to the constraints. We will encode the constraints using Boolean formulas. Thus, the scheduling problem can be reduced to a Boolean satisfiability problem. The rest of the paper is structured as follows. The next section explains precisely what problem we are trying to solve. And then we briefly review Boolean satisfiability problem and methods for solving the problem. In the following section, we explain our method for reducing the scheduling problem to Boolean satisfiability problem. Then we conclude in the last section.
Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

Abstract. The Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) ensemble ozone simulations for the present day from the 2000 decade simulation results are evaluated by a state-of-the-art multi-constituent atmospheric chemical reanalysis that ingests multiple satellite data including the Tropospheric Emission Spectrometer (TES), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Measurement of Pollution in the Troposphere (MOPITT) for 2005–2009. Validation of the chemical reanalysis against global ozonesondes shows good agreement throughout the free troposphere and lower stratosphere for both seasonal and year-to-year variations, with an annual mean bias of less than 0.9 ppb in the middle and upper troposphere at the tropics and mid-latitudes. The reanalysis provides comprehensive spatiotemporal evaluation of chemistry-model performance that compliments direct ozonesonde comparisons, which are shown to suffer from significant sampling bias. The reanalysis reveals that the ACCMIP ensemble mean overestimates ozone in the northern extratropics by 6–11 ppb while underestimating by up to 18 ppb in the southern tropics over the Atlantic in the lower troposphere. Most models underestimate the spatial variability of the annual mean lower tropospheric concentrations in the extratropics of both hemispheres by up to 70 %. The ensemble mean also overestimates the seasonal amplitude by 25–70 % in the northern extratropics and overestimates the inter-hemispheric gradient by about 30 % in the lower and middle troposphere. A part of the discrepancies can be attributed to the 5-year reanalysis data for the decadal model simulations. However, these differences are less evident with the current sonde network. To estimate ozonesonde sampling biases, we computed model bias separately for global coverage and the ozonesonde network. The ozonesonde sampling bias in the evaluated model bias for the seasonal mean concentration relative to global coverage is 40–50 % over the western Pacific and east Indian Ocean and reaches 110 % over the equatorial Americas and up to 80 % for the global tropics. In contrast, the ozonesonde sampling bias is typically smaller than 30 % for the Arctic regions in the lower and middle troposphere. These systematic biases have implications for ozone radiative forcing and the response of chemistry to climate that can be further quantified as the satellite observational record extends to multiple decades.
Application of deconvolution to images from the EGRET gamma-ray telescope

The EGRET gamma-ray telescope has left a legacy of unidentified astronomical sources. Most likely, many of the galactic plane sources will be rotation-powered pulsars. Firm identification has been difficult, given the instrument's poor spatial resolution. The problem is exacerbated by the energy dependant Point Spread Function (PSF) and low numbers of source counts. The main method of identifying sources to-date has been a maximum likelihood method. We have taken a different approach, namely that of regularized deconvolution with a spatially invariant PSF, which is used in optical astronomy and medical X-ray imaging. This technique revealed that wavelet denoising of residuals produced smooth, relatively artefact-free images with improved spatial location. Our source location using standard centroiding produced an improvement in relative spatial location, ranging from 10:1 to 2:1 proportional to source strength. Wavelet deconvolution simultaneously achieves background smoothing, while improving sharpness of the resolved objects. The photon-sparse nature of these images makes them an ideal test bed for such techniques. Although deconvolution does not ordinarily conserve flux, in this instance the flux determination is unaffected in all but the most crowded regions. Finally, we show that the energy dependent PSF can be used to identify objects with a restricted range of energy spectra.
Modeling Temporal Evidence from External Collections

Newsworthy events are broadcast through multiple mediums and prompt the crowds to produce comments on social media. In this paper, we propose to leverage on this behavioral dynamics to estimate the most relevant time periods for an event (i.e., query). Recent advances have shown how to improve the estimation of the temporal relevance of such topics. In this approach, we build on two major novelties. First, we mine temporal evidences from hundreds of external sources into topic-based external collections to improve the robustness of the detection of relevant time periods. Second, we propose a formal retrieval model that generalizes the use of the temporal dimension across different aspects of the retrieval process. In particular, we show that temporal evidence of external collections can be used to (i) infer a topic's temporal relevance, (ii) select the query expansion terms, and (iii) re-rank the final results for improved precision. Experiments with TREC Microblog collections show that the proposed time-aware retrieval model makes an effective and extensive use of the temporal dimension to improve search results over the most recent temporal models. Interestingly, we observe a strong correlation between precision and the temporal distribution of retrieved and relevant documents.