Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and Opportunities with Big Data

- We are living in an era of big data – an age of huge information. Big Data incorporate endless information. Big Data is getting larger in industries and providing better business. It has changes the world in the terms of predicting customer’s behavior. Another buzz word these days is social networks and relation between two of these is very obvious yet complicated. Both Big Data and Social network are interdependent to each other as most of the data is generating from social networking sites but not all the Big Data is useful. The actual challenge of Big Data is not collecting it but managing it and making sense out of it. Such huge data is becoming a new technology focus both in science and in industry and motivate technology shift to data centric architecture and operational models. There is a vital need to define the basic information/semantic models, architecture components and operational models that together comprise a so-called Big Data Ecosystem. This paper mainly focuses on introducing the concept of big data, the terminology used and the architectural details of the big data ecosystem. Researchers and practitioners are trying to look into the future of big data so that more and more benefit can be taken out of the large amount of data. Hadoop - MapReduce is getting prominent in the field of Big Data. Big Data is being used in several research areas related to health-care, location based services, satellite information usage as well as online advertising and retail marketing. This also tries to establish a connect between big data, online social networking, Hadoop, MapReduce.
Tax Competition and the Nature of Capital

The standard race-to-the-bottom result is curious in one respect. If a nation wants to attract foreign capital, providing the optimal level of public amenities (and thus charging the optimal tax rate) would seem optimal. This conjecture fails in the standard tax competition model since foreign capital ignores host nation amenities. While this assumption is reasonable for physical capital, other forms of capital (human capital) tend to move with their owner, so amenities matter. We show that when factors move with their owners, symmetric international tax competition may leads to the socially optimal rate. This result can be thought of as a corollary of the Tiebout efficiency hypothesis.
LUlZ VICENTE FERREIRA DA SILVA FILHO, JOSE EDUARDO LEVI*, CHRISTINA NAOMI ODA BENTOf, SONIA REGINA TESTA DA SILVA RAMOS and TATIANA ROZOV

This report describes a PCR primer pair that targets the aZgD GDP mannose gene of Pseudomonas aeruginosa and produces a specific 520-bp PCR product useful for R aeruginosa identification. This PCR assay was tested with 182 isolates of I? aeruginosa and 20 isolates of other bacterial species, and demonstrated 100% specificity and sensitivity. The test was also able to detect I? aeruginosa directly in clinical samples such as sputum or throat swabs obtained from cystic fibrosis patients. The combination of this primer with a universal bacterial primer, acting as a control to assess DNA quality in the sample, resulted in a robust PCR method that can be used for rapid l? aeruginosa detection.
The orchids of Timor: checklist and conservation status

A checklist of the Orchidaceae of Timor is presented, with emphasis on the eastern half of the island (East Timor), based on historical herbarium collections and recent botanical explorations. This list comprises 38 genera with 66 species, including 15 new genera and 32 new species records for this island. Moreover, four new species are described: Bulbophyllum sundaicum, Habenaria ankylocentron, Habenaria cauda-porcelli, and Pterostylis timorensis. Of these, we consider the finding of a new species of Pterostylis to be especially noteworthy, because this species seems to be more closely related to certain Australian members of the genus than to the Malesian ones, suggesting earlier contacts of Timor with Australia. Four new synonyms are proposed: Calanthe veratrifolia var. timorensis J.J.Sm. (C. triplicata), Habenaria cornuta Span. (H. giriensis), H. grandis Benth. ex Ridl. (Peristylus goodyeroides), and H. mutica Span. (H. elongata). The best represented genus is Habenaria, with 13 species, followed by Dendrobium with four, and Bulbophyllum with three. Because of insufficient or sterile material, it was not possible to identify, or describe as new, 20 different taxa. The conservation status of the ten endemic species, plus six possible new undescribed species and two non-endemic, but threatened, species, was assessed using the World Conservation Union (IUCN) criteria, and categories of threat were proposed. Seven endemic species are considered to be Critically Endangered and two Endangered. One of the nonendemic species is considered to be Critically Endangered, and the other Endangered. The survival of some of these species might be less insecure if an effective application of Regulation project N.2000/19 on protected areas (UNTAET/REG/ 2000/19) was implemented and maintained, because most of these species were collected in areas considered for protection under this Regulation. Further studies are required, however, in order to complete our knowledge of the diversity and population dynamics of this interesting part of Timor’s biodiversity. © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 157, 197–215.
Foreign and local elite-led land acquisitions in Madagascar

Madagascar stands out as the country that almost leased out 1.3 million hectares (ha) of farmland in 2009 to a South Korean corporation. The media frenzy surrounding the ‘land grab’ captured the international community given the size, length, and objective of the land deal. International media revealed that the corporation had leased the land for 99 years and planned to grow maize to export back to Korea. The project never materialized after it was cancelled due to political and social unrest. The Daewoo deal was just one of many investments in the agricultural sector within the past few years in the resource-rich country of Madagascar.
Preference Dependency Grammar and its Packed Shared Data Structure "Dependency Forest"

Preference dependency grammar (PDG) is a framework for integrating morphological, syntactic, and semantic analyses. PDG provides packed shared data structures that can efficiently encompass all possible interpretations at each level of sentence analyses with preference scores. Using the structure, PDG can calculate a globally optimized interpretation for the target sentence. This paper first gives an overview of the PDG framework by describing the base model of PDG, which is a sentence analysis model, called a “multi-level packed shared data connection model. ” Then this paper describes packed shared data structures, e.g., headed parse forests and dependency forests, adopted in PDG. Finally, the completeness and soundness of the mapping between the parse forest and the dependency forest are revealed.
EtCO 2 -Based Biofeedback Method of Breath Regulation Increases Speech Fluency of Stuttering People

Respiratory disturbances frequently accompany stuttering. Their influence on lung ventilation can be assessed by measurement of the end-tidal CO 2 concentration (EtCO 2 ). The effectiveness of the CO 2 -based visual feedback method of breath regulation (VF) designed for stuttering therapy was tested in this study. The aim of the study was to answer the question if the VF helps to reduce respiratory disturbances in stuttering and increase speech fluency. 20 stuttering volunteers aged 13–45 years took part in the 3-parts test consisting of: 1. speaking without any techniques improving speech fluency, 2. learning the VF method, 3. VF-assisted speaking. The CO 2 /time signal and an acoustic signal of an utterance were recorded during the test. Significant increase of FE – the factor of breath ergonomics during speaking (based on both signals), from 47% to 71% ( P P < 0.01) were received for VF-assisted utterances compared to the utterances without VF assistance. The results indicate that the VF can help to eliminate respiratory disturbances in stuttering and increase speech fluency.
The (Not So) Puzzling Behavior of Angel Investors

Angel investors fund start-ups in their earliest stages, which creates a contracting environment rife with uncertainty, information asymmetry, and agency costs in the form of potential opportunism by entrepreneurs. Venture capitalists also encounter these problems in slightly later-stage funding, and use a combination of staged financing, preferred stock, board seats, negative covenants, and specific exit rights to respond to them. Curiously, however, traditional angel investment contracts employ none of these measures, which appears inconsistent with what financial contracting theory would predict. This article explains this (not so) puzzling behavior on the part of angel investors, and also explains the recent move toward venture capital-like contracts as angel investing becomes more of a professional endeavor.
Implementing Genetic Algorithm to solve Facility Location Problem

Facility location problem is the problem of finding optimal location for facilities in a plane consisting of demand points so that each demand point has at least one facility at a distance no more than some permissible distance. Facility location problem has its wide spread application in all areas. The problem of Facility location arises when it is to be decided where to locate a printer, server, ware house or where to open a new store of a business chain. Facility location problem have several application in telecommunication, transportation, distribution etc. This widespread application of Facility Location Problem has invited many researchers to try their hand to solve the problem. The problem of Facility Location is a well known NP-hard problem and various heuristics have been proposed over the time to solve the problem. There exist multiple variants of the facility location problem like p-center problem or p-median problem. Here in this paper, we have attempted to solve the well known p- median problem. We use genetic algorithm to solve the capacitated version of p-median problem.
The ant fauna of the Pilbara Bioregion, Western Australia

The ant fauna of the Pilbara Bioregion, which covers an area of ca. 179,000 km 2 , is reviewed. During surveys undertaken between May 2003 and September 2006, ants were one of the taxonomic groups to receive special attention. The total number of ant species recorded from 24 survey areas was 245, and these were placed in 37 genera and 9 subfamilies. Ants recorded from single quadrats ('singletons') accounted for 18.8% of the species. The most speciose genera were Camponotus (36 spp.), Iridomyrmex (31 spp.) and Melophorus (30 spp.). Based on current knowledge, 43% are purely Eremaean, 8% are primarily Bassian, 6% are primarily Torresian, nearly 17% occur over two of Australia's three biogeographic divisions, and 25% are widespread over all three. At a quadrat level, there was no significant correlation between richness and any environmental variable, while clustering analysis revealed weak environmental correlations with ant assemblage composition. The classification at survey area level identified six groupings of ants; three climatic variables associated with these groupings were identified, namely annual temperature, precipitation in the coldest quarter of the year and annual precipitation.
Decision Orientations towards Shopping and Buying among Young-Adult Malays in the Universities

The learning processes that every consumer goes through would be the determining factors to the decisions a consumer makes when one is purchasing a product or paying for a service. Consumer educators and those involved with consumer interest studies in general consider the above statement as extremely obvious even though one might assume that consumers’ learning and decision-making are a related phenomenon. In essence, such relationship has not been systematically explored in consumer research (Sproles & Sproles, 1990). As the number of product increases and the variety of goods available in the stores and shopping malls multiplies, this helps to broaden-up consumer choices. Similarly, with the availability of multi-component products and electronic purchasing capabilities not only it has broadened the sphere of consumer choice, it also adds complication in making a purchase decision. Based on the examination of the types of consumer decision-making styles in the literature, an instrument was developed to measure the “general orientations toward shopping and buying” and samples from undergraduate students from several universities in the northern region of West Malaysia were used.
THE INFLUENCE OF TREE SPACING IN HEARTWOOD CONTENT IN EUCALYPTUS GLOBULUS LABILL.

Heartwood content was studied in 27 Eucalyptus globulus Labill. trees with spacings 3 x 3, 3 x 2, and 2 x 1 (m x m), with 9 years, from a 1 st rotation spacing trial. The height attained by heartwood increased with total tree height independently of spacing, and reached on average 45%, 59%, and 62% of total height, respectively, for spacings 2 x 1, 3 x 2, and 3 x 3. In all the spacings, the heartwood radius decreased gradually along tree height, and the radial thickness of sapwood remained practically constant at approximately 16 mm in the lower part of the stem (<35% of height), and increased upwards. Sapwood thickness did not depend on tree growth rate, remaining constant for all tree diameters. Heartwood diameter increased with tree diameter, with larger trees showing more heartwood regardless of spacing. Sapwood thickness was not correlated with tree radius, but sapwood area showed a good linear regression. The proportion of heartwood volume increased with spacing from 20.3% to 41.1% of tree volume, respectively for 2 x 1 and 3 x 3 spacings.
DEGENERATIONS OF (1, 7)-POLARIZED ABELIAN SURFACES

The moduli space of $(1,7)$-polarized abelian surfaces with a level structure was shown by Manolache and Schreyer to be rational with compactification the variety of powersum presentations of the Klein quartic curve. In this paper the possible degenerations of the abelian surfaces corresponding to degenerations of powersum presentations are classified.
FX market illiquidity and funding liquidity constraints

Using a data for 20 exchange rates over 13 years, we construct two measures of the common component of liquidity across currencies, transaction costs and market depth. Funding liquidity constraints impact on both aspects of FX market liquidity, after controlling for global volatility, FX market returns and seasonality. Funding liquidity relates to market declines when suppliers to liquidity face capital tightness and to the recent crisis when liquidity dry-ups were severe. The analysis on individual currencies with diverse riskiness conrms that a shock to speculator capital leads to a reduction in market liquidity that is stronger for illiquid currencies.
Seasonal and Annual Impacts of Climate Change on Watershed Response Using an Ensemble of Global Climate Models

Climate change impacts watershed hydrology and contributes to alteration of hydrologic regimes in streams. However, global climate models (GCMs) operate at spatial and temporal scales that are too large to capture important watershed-scale hydrologic shifts. A method of disaggregating monthly ensemble GCM data into temperature and precipitation data series for daily, watershed-specific hydrologic simulations with SWAT was developed and assessed in the Soldier Creek watershed in northeast Kansas. A stochastic weather generator (WINDS) was employed to produce a baseline scenario (no changes from late 20th century conditions) and two scenarios based on ensemble means of 15 GCMs representing future conditions (A2 storyline) referred to as the 2050 and 2100 scenarios. Future hydrologic regimes exhibited non-linear annual and monthly responses in hydrologic budget components, such as surface runoff, baseflow, and soil moisture, to temperature and precipitation changes. For the 2050 scenario, the combination of higher temperatures along with decreased annual precipitation and increased spring precipitation resulted in higher surface runoff, baseflow, and streamflow in May and June with a longer drought season later in summer. The significant decrease in streamflow, runoff, and baseflow for the 2100 scenario reflected an increase in monthly and annual temperature rather than a direct result of precipitation decline. The 2100 scenario also produced a reduction in low-flow duration, an increase in the number of drought occurrences, and a decrease in flood frequency and duration. In retrospect, use of the stochastic weather generator to temporally downscale monthly GCM results while incorporating site-specific climate variability (such as occurs with convective storms often missed in coarse-resolution GCM data) produced more meaningful analysis of hydrological impacts, which is critical to predicting and understanding the impacts of climate change. Although this method allowed simulation of future-climate shifts based on GCM-simulated monthly shifts, it could not simulate potential shifts in climate patterns within a month, such as changes in transitional probabilities that govern the intensity and distribution of storms with months. In future work, translation of regional climate model responses into WINDS stochastic parameter adjustments will allow more accurate and efficient simulation. The severity of the increased drought and decreased flood responses simulated in this study would not be anticipated by review of precipitation trends alone nor by analysis of annual hydrologic responses alone. Similarly, many critical hydrologic responses reflected interactions between climate variables (e.g., precipitation and temperature) at sub-annual temporal scales, which highlights the need to consider climatic interactions in future studies of climate change impacts.
A tool for manufacturers to find opportunity in the circular economy - www.circulareconomytoolkit.org

Living on a finite planet and operating in a linear take-make-dispose system is placing pressure on our resources and is burdening businesses through increased material costs and scarcity of materials. In a more ‘circular’ economy, materials are continuously reused to minimise resource depletion. Although academic research has focused on key areas such as remanufacturing and ecodesign, no practical tools have been identified for manufacturers interested in the circular economy. How can manufacturers identify opportunities to create products and services that align with circular economy principles. Building on literature, surveys from the automotive industry and case examples, a tool was developed to assist companies in their move to a circular economy. The tool shows benefits, guidelines and examples for each opportunity, as well as key challenges. Workshops were held with manufacturers across industries to test the tool. These workshops resulted in forty opportunities identified. To make the work widely accessible, the CircularEconomyToolkit.org website was created. In the first month it was launched, the site received 3,338 visits across 76 countries, giving insight into the wider demographics of people interested in the circular economy. Universities and government agencies have been using the tool and workshops. This research took insights from the automotive sector. Future research will investigate the use and development of the toolkit in different sectors.
EFFICIENT WIDE BASELINE STRUCTURE FROM MOTION

Abstract. This paper presents a Structure from Motion approach for complex unorganized image sets. To achieve high accuracy and robustness, image triplets are employed and (an approximate) camera calibration is assumed to be known. The focus lies on a complete linking of images even in case of large image distortions, e.g., caused by wide baselines, as well as weak baselines. A method for embedding image descriptors into Hamming space is proposed for fast image similarity ranking. The later is employed to limit the number of pairs to be matched by a wide baseline method. An iterative graph-based approach is proposed formulating image linking as the search for a terminal Steiner minimum tree in a line graph. Finally, additional links are determined and employed to improve the accuracy of the pose estimation. By this means, loops in long image sequences are implicitly closed. The potential of the proposed approach is demonstrated by results for several complex image sets also in comparison with VisualSFM.
Constrained Factor Models for High-Dimensional Matrix-Variate Time Series

Abstract High-dimensional matrix-variate time series data are becoming widely available in many scientific fields, such as economics, biology, and meteorology. To achieve significant dimension reduction while preserving the intrinsic matrix structure and temporal dynamics in such data, Wang, Liu, and Chen proposed a matrix factor model, that is, shown to be able to provide effective analysis. In this article, we establish a general framework for incorporating domain and prior knowledge in the matrix factor model through linear constraints. The proposed framework is shown to be useful in achieving parsimonious parameterization, facilitating interpretation of the latent matrix factor, and identifying specific factors of interest. Fully utilizing the prior-knowledge-induced constraints results in more efficient and accurate modeling, inference, dimension reduction as well as a clear and better interpretation of the results. Constrained, multi-term, and partially constrained factor models for matrix-variate time series are developed, with efficient estimation procedures and their asymptotic properties. We show that the convergence rates of the constrained factor loading matrices are much faster than those of the conventional matrix factor analysis under many situations. Simulation studies are carried out to demonstrate finite-sample performance of the proposed method and its associated asymptotic properties. We illustrate the proposed model with three applications, where the constrained matrix-factor models outperform their unconstrained counterparts in the power of variance explanation under the out-of-sample 10-fold cross-validation setting. Supplementary materials for this article are available online.
Enhancing knowledge retention in higher education: A case of the University of Zambia

The purpose of this study was to investigate how knowledge retention may be enhanced at the University of Zambia (UNZA). A quantitative case study design employing a triangulation of data collection methods was used. Data were collected using interviews and questionnaires. Purposive sampling was used to determine participants for the interviews whilst stratified random sampling was employed to select the respondents for the questionnaire. The quantitative and qualitative data that was analysed using SPSS® indicates that UNZA lacked certain knowledge retention practices that might enable it to retain operational relevant knowledge. In view of the findings, the study recommends the adoption of a knowledge retention framework that could be embedded in UNZA’s knowledge management policy.