Miracle-dz/UniFAR-FTUs huggingface dataset:
Partial Access Control Permissions and Rights

In order to satisfy the Principle of Least Privilege in large enterprises which employ Role Based Access Control systems a large number of roles must be defined. Role management can become a demanding and complex task in such situations. This paper introduces the concepts of Partial Access Control Permissions (Partial Permissions) and Partial Access Control Rights (Partial Rights) which enable the number of roles to be reduced and role management burdens to be eased. Partial permissions are linked permissions which are applied simultaneously to two or more roles. The rights defined in a partial permission only become active when an access request triggers a sufficient number of linked partial permissions. Partial permissions enable permissions to be given to any combination of roles. For example, if a hospital patient is attended by clinicians with a "treating team" role and the hospital has a "doctor" role, a partial permission applied to the two roles is only triggered during an access request from a doctor who is on the treating team. Similarly, a Full Right is triggered when a complete set of Partial Rights are activated. Partial rights provide a means for incorporating consent and authorisation into the access control system, as well as facilitating the application of general access control rules to groups of associated roles.
Prepared for submission to JHEP Leading Singularities and Classical Gravitational Scattering

In this work we propose to use leading singularities to obtain the classical pieces of amplitudes of two massive particles whose only interaction is gravitational. Leading singularities are generalizations of unitarity cuts. At one-loop we find that leading singularities obtained by multiple discontinuities in the t-channel contain all the classical information. As the main example, we show how to obtain a compact formula for the fully relativistic classical one-loop contribution to the scattering of two particles with different masses. The non-relativistic limit of the leading singularity agrees with known results in the post-Newtonian expansion. We also compute a variety of higher loop leading singularities including some all-loop families and study some of their properties. ar X iv :1 70 5. 10 26 2v 1 [ he pth ] 2 9 M ay 2 01 7
Time Series Classification with Recurrent Neural Networks

Deep learning techniques showed promising results in time series classification. This work summarizes the achievements of deep neural networks in the problem of univariate time series classification and studies the application of recurrent neural networks to the problem. An experimental part evaluates the classification quality of different recurrent models over a collection of 85 UCR datasets and compares them with the existing feedforward baselines and between each other.
Combining folksonomies and automatic information techniques for LO semantic indexing

The actual changes produced in the e-Learning field are being driven by two primary facts: the first one is the steady increase of information creation and the second is the new collaborative framework of the Web 2.0. While LO (Learning Objects) repositories are mare and more extensive, the automatic tools for search and location of proper learning content in these repositories, based on semantic tags are not yet effective. This article proposes a system architecture that combines automatic techniques of information retrieval with the user's collaborative annotation of the documents, for the semantic indexing of LO in a repository. Collaborative tagging provides real meaning derived from the learning experiences in real user's communities and improves LO reusability in new learning contexts.
A chitosan scaffold infused with neurotrophin-3 and human umbilical cord mesenchymal stem cells suppresses inflammation and promotes functional recovery after spinal cord injury in mice

Despite the severe consequences of spinal cord injuries (SCI), effective treatments are lacking. In this study, the ability of chitosan/neurotrophin-3 (NT3) scaffolds seeded with human umbilical cord mesenchymal stem cells (hUC-MSCs) to treat SCI was investigated. The structure of chitosan/NT3 scaffolds and their effects on proliferation were detected by scanning electron microscopy and MTT assays. The scaffold was implanted into the injured site of SCI mouse models to evaluate its treatment ability. After 8 weeks, locomotor functional recovery was evaluated based on Basso mouse scale (BMS) assessment scores and a CatWalk automated quantitative gait analysis. The density and shape of nissl’s body were measured by Nissl staining. The expression of ionized calcium-binding adapter molecules 1 (Iba1) and inflammatory cytokine levels were analyzed. Isolated hUC-MSCs exhibited abundant expression of mesenchymal stem cell surface markers (CD73, CD90, and CD105). The chitosan/NT3 scaffold had a dense shell and a porous core, which did not affect hUC-MSC proliferation. The chitosan/NT-3+hUC-MSCs treatment significantly improved indicators of locomotion ability, and promoted neuron regeneration. The chitosan/NT3+hUCMSCs treatment inhibited Iba-1 expression, suppressed microglia activation, reduced MIP-1β, IL-6, IL-17, MCP-1, and MIP-1α levels, and increased IL-10 levels. The ability of chitosan/NT3+hUC-MSCs to promote SCI recovery was stronger than those of chitosan/NT3 and chitosan+hUC-MSCs. Chitosan/NT3+hUC-MSCs treatment could reduce inflammation, silence microglia, promote neuron regeneration, and enhance the recovery of neurological function after SCI. Thus, these scaffolds open new and promising avenues for SCI treatment.
A Robust Local Spectral Descriptor for Matching Non-Rigid Shapes With Incompatible Shape Structures

Constructing a robust and discriminative local descriptor for 3D shape is a key component of many computer vision applications. Although existing learning-based approaches can achieve good performance in some specific benchmarks, they usually fail to learn enough information from shapes with different shape types and structures (e.g., spatial resolution, connectivity, transformations, etc.) Focusing on this issue, in this paper, we present a more discriminative local descriptor for deformable 3D shapes with incompatible structures. Based on the spectral embedding using the Laplace-Beltrami framework on the surface, we first construct a novel local spectral feature which shows great resilience to change in mesh resolution, triangulation, transformation. Then the multi-scale local spectral features around each vertex are encoded into a `geometry image', called vertex spectral image, in a very compact way. Such vertex spectral images can be efficiently trained to learn local descriptors using a triplet neural network. Finally, for training and evaluation, we present a new benchmark dataset by extending the widely used FAUST dataset. We utilize a remeshing approach to generate modified shapes with different structures. We evaluate the proposed approach thoroughly and make an extensive comparison to demonstrate that our approach outperforms recent state-of-the-art methods on this benchmark.
How Can the Organizational Commitment of Pakistan Railways’ Employees Be Improved? The Moderating Role of Psychological Capital

The purpose of this research is twofold: frstly it was planned to examine the relatonship and impact of peer-relatonship on organizatonal commitment by means of and without the moderatng role of psychological capital. Secondly, the researchers aimed to examine the associaton of organizatonal culture and organizatonal commitment, similarly, by way of and without the moderatng eﬀect of psychological capital. This study is cross-sectonal by nature in which data were collected from the operatonal staﬀ of Pakistan railways. While investgatng the moderatng impact of psychological capital on the associaton of peer relatonship and organizatonal commitment, it was found that psychological capital strengthens the relatonship of peer relatonship and organizatonal commitment; and also strengthens the relatonship of organizatonal culture and organizatonal commitment as well.
Antifolates Folates and Can Mediate Cellular Resistance against The Human Multidrug Resistance Protein MRP 5 Transports

Members of the multidrug resistance protein family, notably MRP1-4/ABCC1-4, and the breast cancer resistance protein BCRP/ABCG2 have been recognized as cellular exporters for the folate antagonist methotrexate (MTX). Here we show that MRP5/ABCC5 is also an antifolate and folate exporter based on the following evidence: (a) Using membrane vesicles from HEK293 cells, we show that MRP5 transports both MTX (KM = 1.3 mmol/L and VMAX = 780 pmol per mg protein per minute) and folic acid (KM = 1.0 mmol/L and VMAX = 875 pmol per mg protein per minute). MRP5 also transports MTX-glu2 (KM = 0.7 mmol/L and VMAX = 450 pmol per mg protein per minute) but not MTX-glu3. (b) Both accumulation of total [ H]MTX and of MTX polyglutamates were significantly reduced in MRP5 overexpressing cells. (c) Cell growth inhibition studies with MRP5 transfected HEK293 cells showed that MRP5 conferred high-level resistance (>160-fold) against the antifolates MTX, GW1843, and ZD1694 (raltitrexed) in short-term (4 hours) incubations with high drug concentrations; this resistance was proportional to the MRP5 level. (d) MRP5-mediated resistance (8.5and 2.1-fold) was also found in standard longterm incubations (72 hours) at low concentrations of ZD1694 and GW1843. These results show the potential of MRP5 to mediate transport of (anti)folates and contribute to resistance against antifolate drugs. (Cancer Res 2005; 65(10): 4425-30)
BUILDING LOCAL EQUATIONS OF MOTION TO MODEL CHAOTIC DATASETS

Abstract. The nature of chaotic dynamical systems makes predicting the future behavior of such systems difficult, specifically in the case of discrete datasets. This paper will present some methods to overcome this problem. By deconstructing the data into locally linear clusters and building low dimensional bases for each cluster, radial basis functions can be used to rebuild the dynamics of the system and predict future behavior.
Inter-speci W c synchrony of two contrasting ungulates : wild boar ( Sus scrofa ) and roe deer ( Capreolus capreolus )

Very few studies on ungulates address issues of inter-speciWc synchrony in population responses to environmental variation such as climate. Depending on whether annual variation in performance of ungulate populations is driven by direct or indirect (trophic) interactions, very diVerent predictions regarding the pattern of inter-speciWc synchrony can be derived. We compared annual autumn body mass variation in roe deer (Capreolus capreolus) and wild boar (Sus scrofa) from Poland over the period 1982–2002, and related this to variation in winter and summer climate and plant phenological development [the Normalized DiVerence Vegetation Index (NDVI), derived from satellites]. Roe deer fawns (»1.3 kg increase from year 1982 to 2002) and yearlings both increased markedly in mass over years. There was also an increase for wild boar mass over years (»4.2 kg increase for piglets from 1982 to 2002). Despite our failure to link annual body mass to spring or winter conditions or the NDVI, the body mass of roe deer and wild boar Xuctuated in synchrony. As this was a Weld roe deer population, and since wild boar is an omnivore, we suggest this may be linked to annual variation and trends in crop structure (mainly rye). We urge future studies to take advantage of studying multiple species in order to gain further insight into processes of how climate aVect ungulate populations.
The Impact of Antecedent Variables on Strategic Renewal Capability : An Empirical Investigation of Software Businesses in Thailand

Abstract Strategic renewal capability has been viewed as one of the key components that influence organizational outcomes. The objective of this study is to investigate five influential variables on strategic renewal capability; forward-looking vision, learning utilization, resources complementarity, technology growth and market change. In this research, 156 software businesses in Thailand were chosen as a target population for this study. Data were collected and analyzed in the formulation of hypotheses and the hypothesized relationships among variables were then examined using ordinary least square (OLS) regression analysis. Results suggest that almost all antecedents are positively related to the strategic renewal capability except forward-looking vision. This study concluded by identifying a range of theoretical and managerial contributions, and also made suggestions for future research Keywords : Strategic Renewal Capability , Forward-Looking Vision, Learning Utilization, Resources Complementarity, Technology Growth, Market Change
The new green revolution : Bridging the gap between science and society

By combining scientific excellence with social involvement, M. S. Swaminathan has put himself in the tradition of the great agricultural researchers such as Von Liebich, Vavilov, De Vries, Haber and his friend and colleague Norman Borlaug that have defeated the Spectre of Malthus. His ability to use his knowledge and insights to find solutions for complex social problems made him one of the founding fathers of the Green Revolution. And one of the first that saw the drawbacks of the extensive use of water, fertilizer and pesticides that came along with it. He became a staunch advocate for the Evergreen Revolution towards an eco-friendly, resource-poor, sustainable agriculture that is based on science and technology and aims for nutrition security for all. Challenged with the perspective of feeding 9 or 10 billion people with sufficient and nutritious food and producing enough raw materials for the developing bio-based economy we have to keep on learning by doing research and combining its results with the experience of farmers and others. Yet there seems to be a lack of belief - at least in Europe - in human learning; a general distrust in science, which might lead to paralysis in agricultural development. Hence the biggest challenge is to bridge the gap between the sciences and society and to engage society in the development of science to meet the challenges of tomorrow.
DRD1-DRD5 expression profiles in arthritis rheumatoid patients using real time PCR.

1. PhD Student, Department of Medical Genetic & Immunology, National Institute for Genetic Engineering and Biotechnology, Tehran, Iran 2. Assistant Professor of Immunogenetic, Department of Medical Genetic & Immunology, National Institute for Genetic Engineering and Biotechnology, Tehran, Iran 3. Assistant Professor of Rheumatology, Department of Rheumatology, University of Shahid Beheshti Medical Sciences, Tehran, Iran 4. Professor of Immunogenetic, Institut national de la sante et de la recherché Medicale (INSERM) Paris, France 5. Assistant Professor of Child Hematology & Oncology, Department of Hematology & Oncology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Competitive mode: Vertical control and contractual design in the poultry industry - a comparative study between Brazil and Denmark

How do you see the competition in your industry? How do you see your business dealing with the actual situation? Thereare of course several and different answers to these questions, depending on your competitive mode. Maybe it is a choice of market strategy, cost strategy, resource-based strategy, institutional strategy, or my choice of approach,namely a structural strategy. More precisely, I am looking at the economic organization of production, what Williamson (1991) names second-order economizing – regarding the governance structures. We are not doing the mathematics in trying to calculate efficiency, losses or benefits, as we do not have access to that kind of data. In some countries it would be possible to get hold of economic data that would make it possible to calculate possible benefits, while in other countries, companies are not required to go public with their accountings. You will find that companies deliberately tamperwith their financial statements (‘cook their books’), when asked about details in the economy of the production. Going along with the possibilities, what we do want to achieve is a better understanding of why different governance structures are chosen within the same industry. In this article we look at two companies engaged in large-scale industrial production,where one company is located in Brazil and the other in Denmark. The setups of the companies are completely different, where in Brazil strong vertical integration and control is emphasized, this is not equally prominent in Denmark.
Sudden interaction quench in the quantum sine-Gordon model

We study a sudden interaction quench in the weak-coupling regime of the quantum sine-Gordon model. The real time dynamics of the bosonic mode occupation numbers is calculated using the flow equation method. While we cannot prove results for the asymptotic long-time limit, we can establish the existence of an extended regime in time where the mode occupation numbers relax to twice their equilibrium values. This factor two indicates a non-equilibrium distribution and is a universal feature of weak interaction quenches. The weak-coupling quantum sine-Gordon model therefore turns out to be on the borderline between thermalization and non-thermalization.
Exchange Rate Exposure of Sectoral Returns and Volatilities: Further Evidence from Japanese Industrial Sectors

In this paper we argue that the commonly employed exposure coefficient/beta is inadequate for capturing the entire impact of exchange rate changes on firms' future operating cash flows. Instead, we employ the bivariate Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroskedasticity mean model to investigate four aspects of exchange rate exposure, including sensitivity of stock returns to exchange rate changes, sensitivity of stock returns to the volatility of exchange rate changes, sensitivity of conditional variance of returns to exchange rate volatility, and the dynamic conditional correlation between returns and exchange rate changes, respectively, using data from 10 industrial sectors in Japan. We find significant evidence of such exchange rate exposure which is not captured by the conventional measure. The diagnostic statistics confirm the adequacy of our model, and, hence, the robustness of the results.
Development of Nonlinear Transfer Matrix Method for Inelastic Analyses of Beams

The objective of this study is to develop a material-nonlinear-analysis algorithm based on the transfer matrix method (TMM). This newly developed algorithm can be used to perform nonlinear analyses of continuous beam systems. The nonlinear transfer matrix is derived from the general frame stiffness matrix and the Gauss-Lobatto integration scheme is employed for numerical integration. In the TMM, the system equation has a constant number of system unknowns regardless of the total degree-of-freedom number in the structure and the system response (either linear or nonlinear). As a result, TMM can be used efficiently both for linear and nonlinear structural analyses. In this study, a secant nonlinear algorithm required in nonlinear TMM is employed due to its good compromise between the convergence rate and numerical stability. To verify accuracy and efficiency of the developed TMM, four numerical examples are selected and analyzed. The analysis results are compared with those obtained by the highly accurate flexibility-based frame model in terms of global and local responses.
Automatic Voice and Speech Recognition System for the German Language with Deep Learning Methods

In our age, technological developments are accompanied by certain problems associated with them. Security takes the first place amongst such kind of problems. In particular, such biometric systems as authentication constitute the significant fraction of the security matters. This is because sound recordings having connection with the various crimes are required to be analyzed for forensic purposes. Authentication systems necessitate transmission, design and classification of biometric data in a secure manner. In this study, analysis of German language employed in the economy, industry and trade in a wide spread manner, has been performed. In the same vein, the aim was to actualize automatic voice and speech recognition system using Mel Frequency Cepstral Coefficients (MFCC), MelFrequency Discrete Wavelet Coefficients (MFDWC) and Linear. Prediction Cepstral Coefficient (LPCC) taking German sound forms and properties into consideration. Approximately 2658 German voice samples of words and clauses with differing lengths have been collected from 50 males and 50 females. Features of these voice samples have been obtained using wavelet transform. Feature vectors of the voice samples obtained have been trained with such methods as Boltzmann Machines and Deep Belief Networks. In the test phase, owner of a given voice sample has been identified taking the trained voice samples into consideration. Results and performances of the algorithms employed in the study for classification have been also demonstrated in a comparative manner.
UNIVERSITY OF TAMPERE School of Management FACTORS AFFECTING EMPLOYEES’ SATISFACTION AND LOYALTY FOR GOVERNMENT AGENCIES IN THE WARD PEOPLE’S COMMITTEE OF DISTRICT 8, HO CHI MINH CITY – VIETNAM

The purpose of this study is to examine the factors affecting civil servants satisfaction and loyalty at 5 Wards of People's Committee of District 8, Ho Chi Minh City. The study was performed in two phases, qualitative research and main research based on survey results from 200 employees. Research results show that there are three factors affect Employee satisfaction is Empowerment, Compensation, and Training. In which, factors that have the greatest impact Compensation satisfaction. The study results also showed that satisfaction has a positive linear relationship with loyalty. From the results of the study, proposed some recommendations to enhance the satisfaction and loyalty of the staff at the Ward People's Committee of District 8, Ho Chi Minh City, in which Government needs to particular attention to improving salaries system, other factors are empowerment, training also should be concerned.
Cylinders with square cross-section: wake instabilities with incidence angle variation

The wakes behind square cylinders with variation in incidence angle are computed over a range of Reynolds numbers to elucidate the three-dimensional stability and dynamics up to a Reynolds number of Re = 300, based on the projected height of the inclined square cylinder. Three-dimensional instability modes are predicted and computed using a linear stability analysis technique and three-dimensional simulations, respectively. Depending on the incidence angle, the flow is found to transition to three-dimensional flow through either a mode A instability, or a subharmonic mode C instability. The mode A instability is predicted as the first-occurring instability at incidence angles smaller than 12° and greater than 26°, with the mode C instability predicted between these incidence angles. At a zero-degree angle of incidence, the wake instabilities closely match modes A, B and a quasi-periodic mode predicted in earlier studies behind square and circular cylinders. With increasing angle of incidence, the three-dimensional wake transition Reynolds number first increases from Re = 164 as the mode A instability weakens, before decreasing again beyond an incidence angle of 12° as the wake becomes increasingly unstable to the mode C instability, and then again to the mode A instability as the incidence angle approaches 45°. A spanwise autocorrelation analysis from computations over a cylinder span 20 times the square cross-section side length reveals that beyond the onset of three-dimensional instabilities, the vortex street breaks down with patterns consistent with spatio-temporal chaos. This effect was more pronounced at higher incidence angles.