Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic impact of legal stability on the Galician wind energy sector

Title: Economic impact of legal stability on the Galician wind energy sector Name: Pedro Varela Vázquez; María del Carmen Sánchez Carreira (supervisor) Affiliation: University of Santiago de Compostela Year of enrolment: 2011; Expected final date: December 2014 E-mail address: pedro.varela. vazquez@usc.es; carmela.sanchez@usc.es; The energy sector depends heavily on public regulation and it is required to guarantee a minimum remuneration, because of its capital-intensive condition. Renewable energies sources are not an exception and they could make easier the industrial diversification and job creation. Hence, the stability of the regulation framework, especially in the case of new energy sources, is essential due to its positive impact on the emergence and consolidation steps. As several studies show, instability could cause a reduction, or even a shutdown, in their development and economic contribution. Then, it is crucial to quantify the socioeconomic costs of common changes in regulation. The main aim of this paper consists of analysing the economic impact of wind energy regulation instability on the Galician economy. The wind energy sector was one of the most important drivers in the regional economy and there are no quantitative studies focused on this issue. Galicia is a Spanish north-west region with the highest wind energy installed capacity, with roughly 3.300 on-shore MW in 2012, but in a steady state from 2008 due to a legislative shutdown. Wind energy and hydroelectric power represent the main renewable sources. This paper underlines the importance of long-term policies and clear guidelines in the development of wind energy in terms of its economic impact. Concerning the theoretical framework, it is based on the National System of Innovation (NSI) approach. We also use the input-output analysis by means of the examination of the value chains in the wind energy. In addition, we update the productive structures through a variation of the RAS procedure (biproportional matrix balancing technique) which uses efficiently the available data within the period 2000-2010. The data was gathered from official institutions and completed with qualitative interviews with private and public stakeholders. The main results show significant negative effects on the macroeconomic variables throughout the same period when the instability in the regulation framework became more evident.
DEFICIT WATERING REDUCES PLANT GROWTH TO A SMALLER EXTENT WITH ARBUSCULAR MYCORRHIZAL ASSOCIATION THAN WITHOUT IT FOR NON-INVASIVE GRASS SPECIES BUT NOT FOR INVASIVE GRASS SPECIES

Symbiotic associations with the soil microbiota, particularly with arbuscular mycorrhizal fungi (AMF), might ameliorate the effects of environmental stress on plants, and this capacity may be different for resident and alien species. In a growth room pot experiment we tested if imposed water deficit leads to greater growth reduction in the absence of AMF than in the presence of AMF for two non-invasive resident (Danthonia alpina, Chrysopogon gryllus) and two invasive (Calamagrostis epigejos, Cynodon dactylon) grass species from semiarid temperate grasslands in Hungary. Both deficit watering and soil sterilization decreased biomass accumulation, but the non-invasive Danthonia and Chrysopogon performed better when grown in intact soil containing AMF than in sterilized soil. In contrast, the invasive Calamagrostis and Cynodon displayed mostly no difference in growth and biomass accumulation between intact and sterilized soil when subjected to water deficit. When plants were grown well-watered but deprived of AMF symbionts, both Danthonia and Chrysopogon achieved poorer growth than in AMF containing soil, while neither Calamagrostis nor Cynodon displayed any reduction. These results indicate that the influence of deficit watering was ameliorated by the presence of AMF in the soil for the resident non-invasive species, while not for the invasive species.
PAX 4 Enhances Beta Cell Differentiation of Human Embryonic Stem Cells

Background: Human embryonic stem cells (HESC) readily differentiate into an apparently haphazard array of cell types, corresponding to all three germ layers, when their culture conditions are altered, for example by growth in suspension as aggregates known as embryoid bodies (EBs). However, this diversity of differentiation means that the efficiency of producing any one particular cell type is inevitably low. Although pancreatic differentiation has been reported from HESC, practicable applications for the use of b-cells derived from HESC to treat diabetes will only be possible once techniques are developed to promote efficient differentiation along the pancreatic lineages. Methods and Findings: Here, we have tested whether the transcription factor, Pax4 can be used to drive the differentiation of HESC to a b-cell fate in vitro. We constitutively over-expressed Pax4 in HESCs by stable transfection, and used Q-PCR analysis, immunocytochemistry, ELISA, Ca microfluorimetry and cell imaging to assess the role of Pax4 in the differentiation and intracellular Ca homeostasis of b-cells developing in embryoid bodies produced from such HESC. Cells expressing key b-cell markers were isolated by fluorescence-activated cell sorting after staining for high zinc content using the vital dye, Newport Green. Conclusion: Constitutive expression of Pax4 in HESC substantially enhances their propensity to form putative b-cells. Our findings provide a novel foundation to study the mechanism of pancreatic b-cells differentiation during early human development and to help evaluate strategies for the generation of purified b-cells for future clinical applications. Citation: Liew CG, Shah NN, Briston SJ, Shepherd RM, Khoo CP, et al. (2008) PAX4 Enhances Beta-Cell Differentiation of Human Embryonic Stem Cells. PLoS ONE 3(3): e1783. doi:10.1371/journal.pone. 0001783 Editor: Thomas Zwaka, Baylor College of Medicine, United States of America Received November 1, 2007; Accepted February 6, 2008; Published March 12, 2008 Copyright: 2008 Liew et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by grants from the Juvenile Diabetes Research Foundation (HDM, KEC, MJD, PWA), the Medical Research Council (UK) (KEC, HDM, MJD), the Biological and Biotechnical Research Council (UK) (HDM, PWA) and Novo Nordisk Research Foundation (KEC). KEC is supported by a Joint MRC/ JDRF Career Development Fellowship in Stem Cell Research. The authors are grateful to Mark Jones for cell sorting. Competing Interests: The authors have declared that no competing interests exist. * E-mail: karen.e. cosgrove@manchester.ac. uk (JC); p.w. andrews@sheffield.ac. uk (PW) ¤ Current address: UCI Stem Cell Research Center, University of California Irvine, Irvine, California, United States of America . These authors contributed equally to this work.
! " # " % ! " # " & " # : Shirts " & : Pants " %

Identifying mix-and-match relationships between fashion items is an urgent task in a fashion e-commerce recommender system. It will significantly enhance user experience and satisfaction. However, due to the challenges of inferring the rich yet complicated set of compatibility patterns in a large e-commerce corpus of fashion items, this task is still underexplored. Inspired by the recent advances in multirelational knowledge representation learning and deep neural networks, this paper proposes a novel Translation-based Neural Fashion Compatibility Modeling (TransNFCM) framework, which jointly optimizes fashion item embeddings and category-specific complementary relations in a unified space via an end-to-end learning manner. TransNFCM places items in a unified embedding space where a category-specific relation (category-comp-category) is modeled as a vector translation operating on the embeddings of compatible items from the corresponding categories. By this way, we not only capture the specific notion of compatibility conditioned on a specific pair of complementary categories, but also preserve the global notion of compatibility. We also design a deep fashion item encoder which exploits the complementary characteristic of visual and textual features to represent the fashion products. To the best of our knowledge, this is the first work that uses category-specific complementary relations to model the category-aware compatibility between items in a translationbased embedding space. Extensive experiments demonstrate the effectiveness of TransNFCM over the state-of-the-arts on two real-world datasets.
ASHESI UNIVERSITY COLLEGE CLASSIFICATION AND QUANTIFICATION OF MALARIA PARASITES USING CONVOLUTIONAL NEURAL NETWORKS UNDERGRADUATE THESIS

Malaria is currently one of the most deadly diseases in the world. While there are different treatment methods for the disease, the search for new drugs against malaria is still a very important area of research. One of the main challenges in manufacturing drugs against malaria is efficiently evaluating the performance of the drugs on the parasites since it requires, amongst others, precise measurements of the parasite growth-stages as well as their counts in blood smear images. The current gold-standard for making such detail diagnosis is manual microscopy which is tedious. This research showed that convolutional neural networks can be used to identify the different growth-cycle stages of Plasmodium parasites, even in situations where there is little data. Employing a variety of data augmentation techniques and transfer learning, a semantic segmentation model was built to discriminate between trophozoites, gametocytes and normal red blood cells with an accuracy of 85.86% in 353 Giemsa-stained thin blood smears. The results showed that it is possible to perform dense predictions on Giemsa-stained thin blood smears using convolutional neural networks.
Low-frequency tremor and slow slip around the probable source region of the Tokai Earthquake – A new indicator for the Tokai Earthquake prediction provided by unified seismic networks in Japan –

Enhancement of seismic networks in the Japan Islands of these years revealed occurrence of deep low-frequency continuous tremors of a belt distribution in the southwest Japan, where the subducting Philippine Sea plate reaches depths of 25–40 km. The source region of the tremor is assumed to correspond to boundary region between oceanic and island crusts close to mantle wedge. The east end of the belt tremor distribution is adjacent to the probable source region of the Tokai Earthquake. A slow-slip event has continued in the west of the source region of the Tokai Earthquake since 2000. Synchronous activation of the tremor and slow-slip speed was observed in 2003. This suggests some relationship between the slow-slip and the tremor activity. We expect that the tremor activity could be a new valuable indicator for the Tokai Earthquake prediction. The long duration of the tremor indicates existence of fluid relating to its generation. The most probable fluid is considered to be water produced by dehydration of chlorite and formation of clinopyroxene in the oceanic crust on the basis of data from high pressure and temperature experiments. The northern border of the belt distribution is possibly rimmed by the edge of the mantle wedge because serpentine formation absorbs fluid water.
Clusterer in the Context of Image Segmentation

Image segmentation by clustering represents a classical use-case of unsupervised learning. A key aspect of this problem is that instances that are being clusters may have various types and thus requesting specific algorithms that implement particular distance functions and quality metrics. This paper presents an improved version of MTree clusterer that has been tested in the context of image segmentation in the same setup as a new recently k-MS algorithm. The redesigned MTree algorithms allows many levers for setup so that many configurations are available depending on the particularities of the tackled problem. The experimental results are promising especially as compared with the ones from previous MTree version and also as compared with classical clustering algorithms or newly developed k-MS algorithm. Further improvements in terms of available algorithms for configuration and algorithmic efficiency of integrations may lead the way to a general purpose clusterer that may be used for processing various data types.
Potential use of endophytic bacterial and fungi as bio fertilizer to promote plant growth in tissue culture banana

Banana is of special need to human society and are ranked as fourth most important food in the word after rice, maize. In Kenya, production of banana is constrained by among others declining soil fertility due to repeatedly application of fertilizers. Sustainable complementary response to declining soil fertility would be to increase the biological inputs of nutrients by exploitation of microorganisms. Endophytes which are mutualistic symbionts living asymptomatically within plant tissues have been reported to have beneficial effects on plant growth, therefore the effect of three endophytic Bacterial isolate (Bacillus subtilis and Serratia nematodhiphila), Fungal isolate (Trichoderma asperrellum), originating from Kenya were evaluated by inoculating on Grand Naine and William Hybrid banana cultivars under greenhouse condition at weaning stage and after two months for fifteen weeks. Plant responses to endophyte treatment was assessed on plant height, girth, number of functional leaves, fresh and dry roots weight. Improved growth of all parameters was observed for plants inoculated with endophytes when compared to the control. The study shows that the endophytes tested as growth promoters were found to have a significant effect in both cultivar plantlets. All treatments showed promising growth promoting properties. Isolate TR (Trichoderma asperellum) induced the largest increases in plant height 129.2cm (Graid Naine) 114.0cm ( William Hybrid) ) at 15th week , however all the treatment did not differ significantly in other growth parameter (Pseudo stem diameter, and total number of leaves ) at P= 0.05. The study shows that endophytes have potential to enhance growth of tissue-cultured banana plants.
1 Temperature and UV light affect the activity of marine cell-1 free enzymes 2 3

9 Microbial extracellular enzymatic activity (EEA) is the rate-limiting step in the degradation of organic matter in 10 the oceans. These extracellular enzymes exist in two forms, cell-bound which are attached to the microbial cell 11 wall, and cell-free which are completely free of the cell. Contrary to previous understanding, cell-free 12 extracellular enzymes make up a substantial proportion of the total marine EEA. Little is known about these 13 abundant cell-free enzymes, including what factors control their activity once they are away from their sites 14 (cells). Experiments were run to assess how cell-free enzymes (excluding microbes) respond to ultraviolet 15 radiation (UVR) and temperature manipulations, previously suggested as potential control factors for these 16 enzymes. The experiments were done with New Zealand coastal waters and the enzymes studied were alkaline 17 phosphatase [APase], β-glucosidase, [BGase], and leucine aminopeptidase, [LAPase]. Environmentally relevant 18 UVR (i.e., in situ UVR levels measured at our site) irradiances reduced cell-free enzyme activities up to 87% 19 when compared to controls, likely a consequence of photodegradation. This effect of UVR on cell-free enzymes 20 differed depending on the UVR fraction. Ambient levels of UV radiation (KJ) were shown to reduce the activity 21 of cell-free enzymes, for the first time. Elevated temperatures (15°C) increased the activity of cell-free enzymes 22 up to 53% when compared to controls (10°C), likely by enhancing the catalytic activity of the enzymes. Our 23 results suggest the importance of both UVR and temperature as control mechanisms for cell-free enzymes. Given 24 the projected warming ocean environment and the variable UVR light regime, it is possible there could be major 25 changes in the activity of cell-free EEA and their contribution to organic matter remineralization in the future. 26
1 R & D investment behavior during a crisis : What is the role of subsidies ?

This study empirically investigates the effect of public subsidies on R&D investment behavior of Swiss firms during the financial crisis 2008. We analyze whether recipients of public R&D funds alter investment behavior by giving up, preponing, postponing or not changing their R&D investments. By disentangling specific firm behaviors, this study goes beyond previous research on the effectiveness of subsidies. Our results show that public ly subsidized firms do not engage in significantly higher R&D activity. This effect of public grants on subsidized firms might indicate partial crowding out of private R&D expenditures by public subsidies. Second, our results also show that public funds may induce firms to prepone R&D investments which can be interpreted as anti-cyclical investment behavior implying windfall gains by public innovation grants.
On the Balancedness of m-Sequencing Games Herbert Hamers Flip Klijn

This paper studies m-sequencing games that arise from sequencing situations with m parallel and identical machines. These m-sequencing games, which involve n players, give rise to m-machine games, which involve m players. Here, n corresponds to the number of jobs in an m-sequencing situation, and m corresponds to the number of machines in the same m-sequencing situation. We prove that an m-sequening game is balanced if and only if the corresponding m-machine game is balanced. Furthermore, it is shown that m-sequencing games are balanced ifm ∈ {1, 2}. Finally, ifm ≥ 3, balancedness is established for two special classes of m-sequencing games. Journal of Economic Literature Classification Number: C71
Measurement of Thermal Properties at the Interface of Graphene and Bi 2 Te 3 Substrate

Graphene, a two-dimensional hexagonal honey comb lattice, has been attracted tremendous attentions due its extremely high thermal and electrical, mechanical properties. Owing to these superior properties, there have been many attempts to exploit graphene to practical applications since it was discovered in 2004. Among many research area, thermoelectric field is known as one of the promising research field that graphene can be applied. On the other hand, bismuth telluride (Bi2Te3) is one of the representative thermoelectric materials due to the high thermoelectric performance at the room temperature. For this reason, Bi2Te3 has been already used in various research area and commercial devices, such as thermoelectric generator, peltier cooler. Recently, a Graphene-Bi2Te3 composite, synthesized in the thermoelectric field, has been experimentally proved to exhibit an enhanced thermoelectric
The Impact of the Philadelphia Beverage Tax on Purchases and Consumption by Adults and Children

Numerous U.S. cities have recently enacted taxes on sweetened beverages. To examine the effects of the beverage tax of 1.5 cents per ounce in Philadelphia, we surveyed adults and children in Philadelphia and nearby comparison communities both before the tax and nearly one year after implementation. We find that the tax reduced purchases in Philadelphia stores and that Philadelphia residents increased purchases of taxed beverages outside of the city. The tax reduced the frequency of adults' soda consumption by 31 percent, but had no detectable impacts on adults' consumption of other beverages. The tax had no detectable impact on children's consumption of soda or all taxed beverages, although children who were frequent consumers prior to the tax reduced their consumption after the tax.
SHORTFALL IN THE HIGHLY SPECIALIZED B 2 B IT INNOVATION

Expectation shortfall is a common occurrence in outsourcing. Prior literature suggests that strategies such as strict contract terms and proper evaluation of the vendor capabilities are adopted to avoid expectation shortfall. However, in the case of highly specialised technical products custom made to vendor requirements (i.e., B2B IT innovation), traditional strategies in managing outsourcing projects may not work as expected. This is mainly due to the complexity of the product requirements and the inability to assess the scope of the project in depth at the beginning. In this research, we adopt the vendor’s perspective to better understand how organizations in the highly specialized B2B IT innovation handle outsourced projects to avoid expectation shortfall. We uncover a dynamic innovation process which the client and the vendor go through. In addition, we suggest strategies to achieve B2B IT innovation in a win-win scenario while elucidating reasons of failure.
Flood risk assessment in urban catchments using multiple 1 regression analysis 2 3

7 8 Flood assessment in urban catchments is usually addressed through the combination of 9 Geographic Information Systems (GIS) and stormwater models. However, the coupled use of 10 these tools involves a level of detail in terms of hydrological modelling which can be beyond 11 the scope of overall flood management planning strategies. This research consists of the 12 development of a methodology based on Multiple Regression Analysis (MRA) to assess flood 13 risk in urban catchments according to their morphologic characteristics and the geometrical 14 and topological arrangement of the drainage networks into which they flow. Stormwater 15 models were replaced by a combination of Multiple Linear Regression (MLR), Multiple Non16 Linear Regression (MNLR) and Multiple Binary Logistic Regression (MBLR), which enabled 17 identifying influential parameters in the maximum runoff rates generated in urban catchments, 18 modelling the magnitude of peak flows across them and estimating flood risk in the nodes of 19 sewer networks, respectively. The results obtained through a real urban catchment located in 20 Espoo (Finland), demonstrated the usefulness of the proposed methodology to provide an 21 accurate replication of flood occurrence in urban catchments due to intense storm events 22 favored by Climate Change, information that can be used to plan and design preventive 23 drainage strategies. 24 25
A state-of-the-art review of micron scale spatially resolved residual stress analysis by ring-core milling and other techniques

Quantification of residual stress gradients can provide great improvements in understanding the complex interactions between microstructure, mechanical state, mode(s) of failure and structural integrity. Highly focused local probe non-destructive techniques such as X-ray Diffraction (XRD), electron diffraction or Raman spectroscopy have an established track record in determining spatial variations of the relative changes in residual stress with respect to a reference state for many structural materials. However, the interpretation of these measurements in terms of absolute stress values requires a strain-free sample often difficult to obtain due to the influence of chemistry, microstructure or processing route. With the increasing availability of Focused Ion Beam (FIB) instruments, a new approach has been developed known as the micro-scale ring-core Focused Ion Beam - Digital Image Correlation (FIB-DIC). This technique is becoming the principal tool for quantifying absolute in-plane residual stresses. It can be applied to a broad range of materials: crystalline and amorphous metallic alloys and ceramics, polymers, composites and biomaterials. The precise nanoscale positioning and well-defined gauge volume