Miracle-dz/UniFAR-FTUs huggingface dataset:
Local development through social and territorial innovation: An exploratory case study

This investigation aims to examine innovation in a selected successful Portuguese social venture (The Cooperative Terra Cha) and to analyse the extent to which innovative social ventures are able to contribute to local development. Specifically, the paper highlights the activities developed by the social organization in response to the needs of particular (micro) segments of society and illustrates which key factors triggered the success of the examined social initiative. A case study methodology is used to describe the distinctive characteristics and strategies pursued by the managers of the social venture and to establish the links between the opportunities for social innovation and the territory. The data collected for the study were triangulated from desk research and from in-depth semi-structured interviews conducted with privileged actors. The results show that social innovation is a viable strategy to revitalize the region’s socio-economic tissue, through the creation of new economic activities and consequently local employment that are based on the village’s traditional activities. This strategy seeks to achieve sustainable economic growth and well-being for the people of the region. However, to be successful, the strategy demands a deep knowledge of existing social problems as well as the availability of endogenous local resources and capabilities for use by social entrepreneurs. In this context, social innovation should be a participatory process, in which different entities and the beneficiaries of social programs were active players.
Generation of Azotobacter vinelandii strains defective in siderophore production and characterization of a strain unable to produce known siderophores

Summary: Siderophore-negative mutants of Azotobacter vinelandii were generated by insertional mutagenesis with a Tn5 construct containing a promoterless luxAB fusion. The use of this construct, delivered on a suicide plasmid by conjugation, allowed the selection of mutations in iron-repressible genes by virtue of the expression of iron-regulated bioluminescence. Although many iron-regulated mutants were selected, only a few could be easily identified as defective in siderophore production. These included a non-fluorescent azotobactin-negative phenotype (strain D27), and strain F196, which had lost the ability to produce the catechol siderophores azotochelin and aminochelin as well as the lower-affinity chelator 2,3-dihydroxybenzoic acid. Strain D27 had normal production of catechol siderophores, while strain F196 produced 2·5 times as much azotobactin as the wild-type. Two other mutants demonstrated normal catechol levels and either low or relatively unrepressed azotobactin levels. Transformation of the DNA from strain F196 into another spontaneously obtained azotobactin-negative strain (UA1) resulted in strain P100, which was unable to produce the known siderophores. Unlike the wild-type and other siderophore-deficient mutants, this strain was unable to grow in the presence of the iron chelator ethylenediamine di-(o-hydroxyphenylacetic acid) (EDDHA; 50 mUg ml-1) unless stored iron was carried over in the inoculum. Strain P100 did grow on iron-limited medium containing EDDHA when the catechol or azotobactin siderophores were provided exogenously. However, strain P100 gave a positive result in the chrome azurol-S assay (CAS), a non-specific assay for siderophores. The CAS activity was iron-repressible and strain P100 was able to grow and accumulate more iron from the insoluble iron minerals FeS, vivianite and Fe3O4 than was available by simple diffusion or exchange. Therefore, it appears that iron-limited A. vinelandii produces an as yet unidentified low-affinity non-conventional (non-catechol, non-hydroxamate) siderophore.
de Sitter symmetries and inflationary scalar-vector models

In this paper, we study the correspondence between a field theory in de Sitter space in D-dimensions and a dual conformal feld theory in a euclidean space in (D - 1)-dimensions. In particular, we investigate the form in which this correspondence is established for a system of interacting scalar and a vector fields propagating in de Sitter space. We analyze some necessary (but not sucient) conditions for which conformal symmetry is preserved in the dual theory in (D - 1)-dimensions, making possible the establishment of the correspondence. The discussion that we address in this paper is framed on the context of inationary cosmology. Thusly, the results obtained here pose some relevant possibilities of application to the calculation of the fields’s correlation functions and of the primordial curvature perturbation \zeta, in inationary models including coupled scalar and vector fields.
Market Power of the German Beer Industry on Export Markets - An Empirical Study -

In this paper the existence and magnitude of market power for the German beer exporters is tested. Two theoretical approaches to model incomplete competition on international markets are employed, the ? pricing to market? (PTM) model the ? residual demand elasticity? (RDE) approach. Estimations for both models over the period from 1991 to 1998 reveal incompatible results regarding the underlying theoretical models and with respect to the approach that is used. While significant market power is indicated in the PTM model, the RDE approach signalizes perfect competition. This leads to the conclusion that the underlying theoretical models have to be extended to consistently match the observed market solutions in this case.
Analysis and manipulation of the data set obtained from the study of pre-primary education development using machine learning

A data set on ‘Preprimary education’ consisting of eleven hundred and fourteen data was collected from IED BRAC University. At the end of the study the students were tested out of eighteen and scored according to their performance . The entire data set was divided in three groups, and the results were classified in four parts. The first data set consisted of the socio economic attributes and the result obtained from the test, the second data set contained other likely attributes which could possibly have affected the results, like the education of parents, siblings, average education of student’s families etc. The third and final data set consisted of the marks they scored in each question and the net total mark obtained, to test their readiness. The results were classified into four groups called fully prepared, partially prepared, unprepared and needs help and they were categorized accordingly. An attribute relation file format, a format which is compatible with WEKA was made of each data set, before taking input. Once input was taken, these data sets were analyzed using several machine learning algorithms. The main goal of analyzing the data was to test whether or not the preprimary education prepares the students for primary education. The algorithms used in analyzing the data set were Super vector machine: Sequential Maximization Optimization, Multilayer perceptron: Back propagation algorithm, Naive Bayes algorithm, Random tree and random forest. The results obtained from each algorithm were compared and the algorithm performing the best was selected.
First-principles-based predictive simulations of B diffusion and activation in ion implanted Si

We present a kinetic Monte Carlo model for boron diffusion, clustering and activation in ion implanted silicon. The input to the model is based on a combination of experimental data and ab initio calculations. The model shows that boron diffusion and activation are low while vacancy clusters are present in the system. As the vacancy clusters dissociate, boron becomes substitutional and the active fraction increases rapidly. At the same time, the total boron diffusion length also increases rapidly while interstitial clusters ripen. The final burst of boron diffusion occurs as the large interstitial clusters dissolve, but most of the transient diffusion of the implanted boron has already taken place by this time. We show that these results are in excellent agreement with experimental data on annealed dopant profiles and dopant activation as function of annealing time.
Profitability and causality of order imbalance based trading strategy in hedge stocks

In general, investors trade for two reasons: to hedge for risk sharing and to speculate on the private information. Previous researches suggest that the dynamic relation between volume and return lies in the underlying motivations. For aggressive investors, their hedging actions (i.e. rotation) tend to result in abrupt price soaring and subsequent reversal in a short period of time. In this paper, by introducing the criteria of stationary price, declining volume and price range, we try to screen the potential hedge targets and develop the associated trading strategies. The results indicate that for samples with maximum loss below 5%, they reveal a paradox of high potential upside and low downside. We find that three sectors account for more than half of the hedge samples, which implies that hedgers seem to prefer specific sectors when screening potential rotation targets. We also document that the practice of “clearing the floats” plays a very important role in analyzing the waiting period for hedges and most price jumps, and also reversals are associated with volume augmentation. With intraday time varying GARCH specification, we investigate the relation between order imbalance and return. The evidences show that order imbalance indeed presents positively significant influence on returns. However, the relationship between order imbalance coefficients and market cap fails to present negatively significance. In order to explain the profitability of order imbalance based strategy, we examine the causal relationship between return and order imbalance. We find that order imbalance is a good indicator of price discovery under our nested causality framework.
Bulk Renormalization Group Flows and Boundary States in Conformal Field Theories

We propose using smeared boundary states $e^{-\tau H}|\cal B\rangle$ as variational approximations to the ground state of a conformal field theory deformed by relevant bulk operators. This is motivated by recent studies of quantum quenches in CFTs and of the entanglement spectrum in massive theories. It gives a simple criterion for choosing which boundary state should correspond to which combination of bulk operators, and leads to a rudimentary phase diagram of the theory in the vicinity of the RG fixed point corresponding to the CFT, as well as rigorous upper bounds on the universal amplitude of the free energy. In the case of the 2d minimal models explicit formulae are available. As a side result we show that the matrix elements of bulk operators between smeared Ishibashi states are simply given by the fusion rules of the CFT.
Observations of Surface Fault Rupture from the 1906 Earthquake in the Context of Current Practice

Many important insights are embedded in the detailed observations of surface rupture of the 1906 San Francisco earthquake, during which surface faulting interacted with pipelines, earth embankments, and buildings. Lessons gleaned from the 1906 rupture, combined with parallel and new insights from recent earthquakes, illustrate how various geologic conditions alter the surface expression of faulting and how surface fault rupture interacts with engineered systems. Geologic and engineering procedures can be employed to evaluate the hazards associated with surface faulting and to develop sound designs. Illustrative examples are used to demonstrate how the hazards associated with surface fault rupture can be addressed. Effective design measures include constructing earth fills to partially absorb underlying ground movements; isolating foundations from the underlying ground movements; and designing strong, ductile foundations that can accommodate some deformation without compromising the functionality of the structure.
The Role of Learning the Japanese Kuku Multiplication Chant in Simple Arithmetic Operations

In Japanese primary schools, children are required to learn the kuku (“nine nines”) method of multiplication during the formal course of mathematics. When learning, they are taught to recite it as though reciting a Chinese poem or chanting. In the present study, we undertook an experiment designed to examine the role of learing the Japanese kuku multiplication chant in arithmetic operations by requiring the participants to solve the three types of simple arithmetic problems. In each problem presentation, an equation of simple addition (e.g., 3 (three) added to 4 (four) makes 7 (seven)), of simple multiplication (e.g., 3 (three) multiplied by 4 (four) is 12 (twelve)), or of kuku (e.g., 3 (three) 4 (fours) 12 (twelve)) was auditorily presented with either the addend or augend in the addition, or the multiplicand or multiplier in the multiplication or kuku always being acoustically masked by peep sounds so that the participants did not hear the numbers masked. Comparison of the latency to their answer across the three types of problems revealed that as a consequence of learning kuku, a learner could produce the answers for the arithmetic multiplication problems as well as the answers for the kuku problems relatively more easily as compared to the arithmetic addition problems. Implications of the results are argued with reference to the cognitive load theory, a theory of learning and education which underwent substantial development and expansion during last two decades.
Identification of Functional and In silico Positional Differentially Expressed Genes in the Livers of High- and Low-marbled Hanwoo Steers

This study identified hepatic differentially expressed genes (DEGs) affecting the marbling of muscle. Most dietary nutrients bypass the liver and produce plasma lipoproteins. These plasma lipoproteins transport free fatty acids to the target tissue, adipose tissue and muscle. We examined hepatic genes differentially expressed in a differential-display reverse transcription-polymerase chain reaction (ddRT-PCR) analysis comparing high- and low-marbled Hanwoo steers. Using 60 arbitrary primers, we found 13 candidate genes that were upregulated and five candidate genes that were downregulated in the livers of high-marbled Hanwoo steers compared to low-marbled individuals. A BLAST search for the 18 DEGs revealed that 14 were well characterized, while four were not annotated. We examined four DEGs: ATP synthase F0, complement component CD, insulin-like growth factor binding protein-3 (IGFBP3) and phosphatidylethanolamine binding protein (PEBP). Of these, only two genes (complement component CD and IGFBP3) were differentially expressed at p<0.05 between the livers of high- and low-marbled individuals. The mean mRNA levels of the PEBP and ATP synthase F0 genes did not differ significantly between the livers of high- and low-marbled individuals. Moreover, these DEGs showed very high inter-individual variation in expression. These informative DEGs were assigned to the bovine chromosome in a BLAST search of MS marker subsets and the bovine genome sequence. Genes related to energy metabolism (ATP synthase F0, ketohexokinase, electron-transfer flavoprotein-ubiquinone oxidoreductase and NADH hydrogenase) were assigned to BTA 1, 11, 17, and 22, respectively. Syntaxin, IGFBP3, decorin, the bax inhibitor gene and the PEBP gene were assigned to BTA 3, 4, 5, 5, and 17, respectively. In this study, the in silico physical maps provided information on the specific location of candidate genes associated with
Determination of the cut-off level of apparent diffusion coefficient values in the detection of prostate cancer

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Link Label Prediction in Signed Citation Network

Link label prediction is the problem of predicting the missing labels or signs of all the unlabeled edges in a network. For signed networks, these labels can either be positive or negative. In recent years, di↵erent algorithms have been proposed such as using regression, trust propagation and matrix factorization. These approaches have tried to solve the problem of link label prediction by using ideas from social theories, where most of them predict a single missing label given that labels of other edges are known. However, in most real-world social graphs, the number of labeled edges is usually less than that of unlabeled edges. Therefore, predicting a single edge label at a time would require multiple runs and is more computationally demanding. In this thesis, we look at link label prediction problem on a signed citation network with missing edge labels. Our citation network consists of papers from three major machine learning and data mining conferences together with their references, and edges showing the relationship between them. An edge in our network is labeled either positive (dataset relevant) if the reference is based on the dataset used in the paper or negative otherwise. We present three approaches to predict the missing labels. The first approach converts the label prediction problem into a standard classification problem. We then, generate a set of features for each edge and then adopt Support Vector Machines in solving the classification problem. For the second approach, we formalize the graph such that the edges are represented as nodes with links showing similarities between them. We then adopt a label propagation method 5 to propagate the labels on known nodes to those with unknown labels. In the third approach, we adopt a PageRank approach where we rank the nodes according to the number of incoming positive and negative edges, after which we set a threshold. Based on the ranks, we can infer an edge would be positive if it goes a node above the threshold. Experimental results on our citation network corroborate the e cacy of these approaches. With each edge having a label, we also performed additional network analysis where we extracted a subnetwork of the dataset relevant edges and nodes in our citation network, and then detected di↵erent communities from this extracted subnetwork. To understand the di↵erent detected communities, we performed a case study on several dataset communities. The study shows a relationship between the major topic areas in a dataset community and the data sources in the community.
A User-Centered Evaluation of a University Website

Usability of a website used to be of very little or no weight at all for the company or academe it represents. With the changing time and increase of Internet users, usability is now a major consideration as website, though virtual, plays an important role for the company or university it represents. This study illustrates the process of assessing a university website. The value of doing usability testing and how it enriches the user experience is presented. Learning about the user and their satisfaction in all aspects of the website is learned through the testing process. A five- phased usability testing methodology is discussed that resulted into qualitative and quantitative data for the researchers study. These data were transformed into information through analysis in accordance to the type of data collected. These findings were then interpreted into concrete website usability assessment. The result showed that the methodology chosen and the test plan it produced was able to output website usability problems that can help assess and greatly improve a university website's usability. Lastly, study recommendations were presented being that usability should be a never ending endeavor for a user- concerned university. 
A privacy by design approach to lifelogging

Technologies that enable us to capture and publish data with ease are likely to pose new concerns about privacy of the individual. In this article we exam- ine the privacy implications of lifelogging, a new concept being explored by early adopters, which utilises wearable devices to generate a media rich archive of their life experience. The concept of privacy and the privacy implications of lifelogging are presented and discussed in terms of the four key actors in the lifelogging uni- verse. An initial privacy-aware lifelogging framework, based on the key principles of privacy by design is presented and motivated.
Vehicular emissions of organic particulate matter in Sao Paulo, Brazil

2 Oyama, B.S., Andrade, M.F. , Herckes, P., Dusek, U. , Röckmann, T. , Holzinger, R. 3 1 Institute of Astronomy, Geophysics and Atmospheric Sciences, University of Sao Paulo, Sao 4 Paulo, Brazil 5 2 Institute for Marine and Atmospheric Research, University of Utrecht, Utrecht, the 6 Netherlands 7 3 School of Molecular Sciences, Arizona State University, Tempe, United States 8 4 Center for Isotope Research, University of Groningen, Groningen, the Netherlands 9
Structural and electrical properties of barium strontium titanate thin fi lms for tunable microwave applications

The dependence of dielectric permittivity on the applied electric field, high dielectric constant and low cost makes barium strontium titanate (BST) a promising ferroelectric material for applications in tunable microwave devices. High tunability and low dielectric loss is desired for tunable microwave devices. The primary objective of this research was to optimize the tunability and dielectric loss of BST thin films at microwave frequencies with different deposition techniques. Ba0.5Sr0. 5TiO3 thin films were grown on Pt/TiO2/SiO2/Si, by pulsed laser deposition (PLD) and sputtering. Parallel plate capacitor structures were designed using ADS and fabricated. The microstructural and phase analysis of the BST films were performed using X-ray diffraction (XRD) method. The diffraction patterns are attributed to cubic (perovskite) crystal system. The analysis of surface morphology was done using atomic force microscopy.