Miracle-dz/UniFAR-FTUs huggingface dataset:
USING DEA MODEL FOR SPATIAL DISTRIBUTION ANALYSIS OF SOME DEVELOPMENT INDICES IN IRAN

Among the aims of each country or society for its people, receiving welfare and comfort as well as amending the lags and generally providing a better life could be mentioned. To meet these aims, the societies need a sustainable development in which all the dimensions of the development are taken into account simultaneously. Recognizing and analyzing the conditions of the regions based on the environmental, economic, social, and cultural backgrounds are the first steps in the process of regional development planning. Accordingly, the regions' dead locks and limitations will be determined and it could be possible to embark on removing them. Discussing some points about sustainable development and degree of development in Iran, the present article, using statistical analysis and Data Envelopment Analysis (DEA) which is considered as one of the known methods for measuring performance and also is used for performance evaluation of homology units, attempts to analyze and classify some development indices of provinces in Iran by using GIS and SPSS.
The early stages of fungal succession in Pinus sylvestris phloem and sapwood infested by Tomicus piniperda

Fungal invasion of Scots pine phloem and sapwood was investigated during a period of 15 weeks following attack by the pine shoot beetle, Tomicus piniperda (L.). The study was conducted in Mielec-Mościska, where the pine trees were heavily damaged by shot-feeding of T. piniperda. In order to determine the species richness and occurrence frequency of fungi associated with T. piniperda in temporal succession, living and trap trees infested by T. piniperda were used. Results revealed great diversity of fungi associated with T. piniperda, including 3758 cultures and 57 fungi species. The most important groups of fungi were the blue-stain fungi and molds, including mainly Penicillium, Trichoderma and Mucor genera. Among ophiostomatoid fungi, Ophiostoma minus and O. piceae were the dominant species. Occasionally isolated species were Leptographium lundbergii, L. procerum, L. wingfieldii, Graphium pycnocephalum and Graphium sp. ‘W’. Molds and pathogenic O. minus were the first invaders of both phloem and sapwood, however molds were more frequently isolated from phloem and sapwood at a depth of 5 mm. Ophiostoma piceae and L. lundbergii followed O. minus in the sapwood invasion. These species were successively replaced by L. wingfieldii, L. procerum and Graphium species in the later stages of fungal invasion in pine sapwood. Additional key words: blue-stain fungi, molds, ophiostomatoid fungi. Address: R. Jankowiak, M. Kurek, Agriculture University of Cracow, Department of Forest Pathology, Al. 29 Listopada 46, 31-425 Cracow, Poland, e-mail: rljankow@cyf-kr.edu. pl
Entrepreneurs’ social identity and the preference of causal and effectual behaviours in start-up processes

Abstract This paper examines how the social identity of an entrepreneur influences his or her behaviour when engaged in new venture formation. Building on the typology of entrepreneurial identities developed by Fauchart and Gruber, this study examines the relationship between the social identity of the entrepreneur and subsequent entrepreneurial behaviour using a mixed-method approach. Based on interviews with entrepreneurs in six start-ups within the tourism sector and on previous literature, three hypotheses were developed regarding the relationship between entrepreneurial identity and entrepreneurial behaviour (causation, effectuation). Subsequently, the hypotheses were tested using a survey among a sample of entrepreneurs who registered a new firm in 2013. The study finds that the entrepreneurial identity influences whether the individual predominantly engages in effectual or causal behaviour. Hence, the study contributes by focusing on entrepreneurial identity as an important factor shaping the behaviours of entrepreneurs. In addition, we add to the understanding of entrepreneurs as a heterogeneous group. Entrepreneurs vary in terms of their identity, and this variation has consequences for their entrepreneurial behaviour. Finally, by adopting a mixed-method approach, this study benefits from and contributes to the interaction of qualitative and quantitative data in entrepreneurship research.
Chapter 44 Use of neutron imaging for proton exchange membrane fuel cell ( PEMFC ) performance analysis and design

Over the last decade, proton exchange membrane fuel cells (PEMFCs) have become the subject of intensive research activity, as the technology offers a viable alternative to power sources based on hydrocarbon combustion. Water management stands out as one of the key remaining performance, durability, and cost challenges, because it influences the properties of the materials used in the membrane-electrode assembly (MEA), gas diffusion layer (GDL), and bipolar plates; drives the selection of fuel cell operating conditions (temperature, pressure, relative humidity, and reactant stoichiometric ratios); and impacts bipolar plate and hardware design as well as specification of ancillary components, such as the airand hydrogen (or reformate)-handling equipment, humidifiers, etc. In the event that high-temperature, low-humidity proton exchange membranes become viable, there will still be a need to accommodate the presence of liquid water under startup, shutdown, and transient load conditions, and for low ambient temperature performance. Therefore, a strong and sustained need for diagnostic methods that enable measurement of liquid water within an operating fuel cell is expected. A variety of methods have been advanced for monitoring the in situ liquid water content, as recently summarized by St. Pierre. Neutron imaging has several inherent advantages that make it among the most versatile diagnostic methods: • The high neutron cross section of hydrogen, coupled with the low neutron cross section of common fuel cell construction materials, provides an acceptably high signal-to-noise level without significant deviation from a standard fuel cell design and material set. • High spatial resolution, on the order of 100 μm or less. • High temporal resolution, on the order of 10 s or less. • Large imaging area, on the order of 10 cm × 10 cm.
A Species‐Specific Approach to Modeling Biological Communities and Its Potential for Conservation

Abstract: Community‐level approaches to biological conservation are now recognized as a major advance in most current single‐species conservation and management practices. Existing approaches for modeling bio‐ logical communities, have limited utility, however, because they commonly examine community metrics ( e.g., species richness, assemblage “types” ) and consequently do not consider the identity of the species that compose the community. This is a critical shortcoming because the functional differences among species ultimately translate into the differential vulnerability of biological communities to natural and human‐related environmental change. To address this concern I present a novel, species‐specific approach to modeling communities using a multiresponse, artificial neural network. This provides an analytical approach that facilitates the development of a single, integrative model that predicts the entire species membership of a community while still respecting differences in the functional relationship between each species and its environment. I used temperate‐lake fish communities to illustrate the utility of this modeling approach and found that predictions of community composition by the neural network were highly concordant with observed compositions of the 286 study lakes. Average similarity between observed and predicted community composition was 80% ( 22 out of the 27 species correctly classified ), and the model predicted a significant portion of the community composition in 91% of the lakes. I discuss the importance of the lake habitat variables for predicting community composition and explore the spatial distribution of model predictions in light of recent species invasions. The proposed modeling approach provides a powerful, quantitative tool for developing community predictive models that explicitly consider species membership, and thus each species' functional role in the community. Such models will contribute significantly to the study and conservation of biological communities.
The Political Economy of Poland's Trade Policy: Empirical Verification of the Grossman-Helpman Model

This paper analyzes rent-seeking behavior in trade policy based on the Grossman-Helpman (1994) framework. Our empirical implementation deals with Polish trade policy in the late 1990s. We use the instrumental variable approach to estimate the model, accounting for possible endogeneity of the regressors. Our results suggest that lobbies were important in the process of Polish trade policy formation in the period under consideration. The degree of the lobbies' influence is, however, significantly lower than in the case of the United States. The model seems to perform better for most-favored-nation cases than preferential tariffs. In the former case, our estimates are in line with the original theory.
Short-term traffic flow prediction using a methodology based on autoregressive integrated moving average and genetic programming

The accurate short-term traffic flow forecasting is fundamental to both theoretical and empirical aspects of intelligent transportation systems deployment. This study aimed to develop a simple and effective hybrid model for forecasting traffic volume that combines the AutoRegressive Integrated Moving Average (ARIMA) and the Genetic Programming (GP) models. By combining different models, different aspects of the underlying patterns of traffic flow could be captured. The ARIMA model was used to model the linear component of the traffic flow time series. Then the GP model was applied to capture the nonlinear component by modelling the residuals from the ARIMA model. The hybrid models were fitted for four different time-aggregations: 5, 10, 15, and 20 min. The validations of the proposed hybrid methodology were performed by using traffic data under both typical and atypical conditions from multiple locations on the I-880N freeway in the United States. The results indicated that the hybrid models had better predictive performance than utilizing only ARIMA model for different aggregation time intervals under typical conditions. The Mean Relative Error (MRE) of the hybrid models was found to be from 4.1 to 6.9% for different aggregation time intervals under typical conditions. The predictive performance of the hybrid method was improved with an increase in the aggregation time interval. In addition, the validation results showed that the predictive performance of the hybrid model was also better than that of the ARIMA model under atypical conditions.
ADMK: AN AD HOC COMPONENT FOR ASPECT AND DOMAIN BASED MOBILE RANKING

In the present era, mobile phone is a huge market, where day by day a new brand and lot of models of mobile phones are releasing, among which choosing one best mobile is a tremendous task. Where we take the problem of choosing a mobile phone by our technique ADMK (Aspect and Domain based Mobile ranking). A variety of Sources of information about the model of mobile phones being launched in market are available, where some of the websites provide rich and valuable knowledge for users and companies. But review of products can be often fuzzy and confused. This can be effectively done by Aspect determination from different text reviews available in the social media. Firstly, it identify the aspects to be considered to rate the product. Some of the aspects like Camera, RAM, Processor, and Memory are more important than USB port, buttons, panel, design. Free text reviews are extracted from the website using web Crawler. These reviews are processed to find out the opinion of the user on each aspect. The opinion of the customer on the important aspects will have great impact on the overall rating of the product. So by finding the weight of the aspect we will rank the aspects according to their influence on the overall rating of the product. By considering the different parameters like weight of the aspect, Classifier Rating will calculate the rating more accurately. This will provide the users to by the truthful product through online-shopping.
Integrating mindfulness skills training into a brief outpatient treatment for substance abusing youth

Mindfulness training has increasingly been implemented in substance abuse treatment regimes with the goal of relapse prevention. Among the available treatments, Motivational Interviewing (MI) is reported to be the most effective form of treatment for transitional-age youths. However, there is a paucity of research investigating the effects of mindfulness skills training on sobriety maintenance in this population. Objectives: The goal of the current study was to assess the effects of MI with the addition of mindfulness skills training on substance use behaviours and clinical outcomes in outpatient youths between the ages of 16 and 24. Methods: Sixty-six eligible participants were randomly assigned to a Treatment-as-usual (TAU) group or a TAU plus mindfulness training (TAU+M) group. Substance use days, impulse/addictive behaviors, confidence to resist urges, emotion regulation, psychiatric symptom severity, and mindfulness was assessed at baseline, post-treatment and at 3-month follow-up. Results: Days of substance-use did not change across group; however, both treatment groups reported decreased severity of psychiatric symptoms at 3-month follow-up. Participants in the TAU+M group further displayed decreased impulsive/addictive behaviors and increased confidence to resist urges at follow-up compared to the TAU group. Interestingly, the TAU group displayed greater changes in mindfulness than the TAU+M group. Conclusions and Implications: Overall, adding mindfulness to MI seems to provide benefits in the treatment of substance abusing youths.
A Model for Product Development Performance Monitoring Based on Analytic Network Process

A well-designed performance measurement system can assess the impact of product development on the whole company. To this end, a set of suitable product development measures can provide valuable information for managing the activities and continuous improvement of the product development process. In this paper, via our literature review, we first establish the gaps with regards to the product development performance measurement. Then, we identify performance criteria for assessing product development process effectiveness based on competitive priorities (cost, quality, flexibility, delivery and innovation) followed by an ANP analysis to develop a model for Product Development Performance Monitoring (PDPM). Finally, using a two tier survey setting, the validity and reliability of the PDPM model are ascertained, and field data for its usage as an assessment tool for product development is demonstrated. The field study was conducted by participation of a sample of manufacturing companies in Turkey.Copyright © 2009 by ASME
How Three Tasmanian Teachers Use and Respond to Emotion in the Secondary English Classroom

This paper explores how three secondary English teachers use and respond to emotion in the classroom. By examining the perceptions and experiences of three experienced teachers, valuable insights can be gained in relation to the significance and subsequent impact of these teachersʼ own emotions, their studentsʼ emotions and the value and significance of emotion in the secondary English discipline. According to Arnon and Reichel (2007), programs for teacher education are being “extensively challenged and intensively re-worked” (p. 443). This evolution in teacher education is, at least in part, the result of changing perspectives of both the ʻidealʼ teacher and the most appropriate means of preparing trainee teachers for the demands of the modern classroom (Arnon & Reichel, 2007; Cochran-Smith & Fries, 2001). One of these demands was clearly articulated in the findings of the Australian Scholarships Group (ASG) Student Social and Emotional Health Report (Bernard, Stephanou, & Urbach, 2007). It revealed that “significant percentages of students are experiencing social and emotional difficulties during their schooling” (p. 5), a finding which supports the contention that greater emphasis must be placed upon “the significance of studentsʼ social and emotional health and wellbeing during teacher training” (Bernard, 2007, p. 122). The findings of this study are particularly relevant for English teachers, given that English is the only compulsory subject in which teachers have significant opportunity to nurture emotional development and understanding, which has been shown to be of significant benefit to increasing student motivation, engagement and cognitive development. This is not to suggest that other opportunities for the nurturing and development of emotional development and understanding can not occur within broader aspects of personal and social learning; rather this is acknowledging the unique opportunity that exists for this to occur within subject English. Secondary English teachers need to recognise the implications of emotion within their classroom and the means by which it might be effectively utilised to benefit secondary English learning. This integration must be more than a small challenge to the oft repeated dictum that a new teacher ʻshould not smile before Easterʼ, for an understanding of the role of emotion must underpin the entire educative experience. For as Sutton (2005) states, “teachersʼ emotional experiences and expression influence their classroom effectiveness” (p. 232) and thus they will inform their professional practice from their very first days in the classroom. This paper provides insights into the significance of how these experiences and expressions specifically impact upon secondary English classroom teaching practice and learning. By examining their perceptions and experiences we can gain valuable insights into the value and significance of emotion into secondary English in the classroom context.
Quantifying the skewed distribution of activity in virtual communities within a longitudinal study

Virtual Communities (ViCs) are subject of interest for quite some time now [Hagel and Armstrong, 1997, Garton, et al., 1997, Rheingold, 1993]. Recently, ViCs in the form of Social Network Services like MySpace or StudiVz received a lot of attention. Though, fairly little is known about the temporal evolution of virtual communities and the changes in the communication activity of its users. The research described here is an explorative study examining the communication activity of members of two virtual communities on a longitudinal basis. For that purpose, a graph theoretical model by Pennock et al. [2002] is used which unites “Random Network Theory” and “Scale-free Networks”. This model allows the operationalization of the empirical distribution functions of the communication activity in ViCs with only one free parameter. That parameter – the mixing factor α – represents the ratio between the antagonists heterogeneity and homogeneity. The nonlinear curve fitting of the empirical distribution functions shows a predominance of preferential over uniform binding in both communities. Participants prefer to communicate with community members having already a lot of communication partners, while members with low activity are less attractive. This phenomenon is less strong in the smaller ViC B. The members of ViC B have almost twice as many connections as those of ViC A. ViC B represent a tighter network which might lead to the more homogeneous distribution of its activity. In both communities the mixing factor α and therefore the level of heterogeneity shows quite stable over time.
Randomized Jumplists With Several Jump Pointers

In 2003, a dictionary data structure called jumplist has been introduced by Bronnimann, Cazals and Durand. It is based on a circularly closed (singly) linked list, but additional jump-pointers are added to provide shortcuts to parts further ahead in the list. The original jump-and-walk data structure by Bronnimann, Cazals and Durand only introduces one jump-pointer per node. In this thesis, I add one more-jump pointer to each node and present algorithms for generation, insertion and search for the resulting data structure. Furthermore, I try to evaluate the effects on the expected search costs and the complexity of the generation and insertion. It turns out that the two-jump-pointer variant of the jumplist has a slightly better prefactor (1.2 vs. 2) in the leading term of the expected internal path length than the original version and despite the more complex structure of the two-jump-pointer variant compared to the regular jumplist, the complexity of generation and insertion remains linearithmic.
THE EPSILON ERIDANI SYSTEM RESOLVED BY MILLIMETER INTERFEROMETRY

We present observations of ϵ Eridani from the Submillimeter Array (SMA) at 1.3 mm and from the Australia Telescope Compact Array at 7 mm that reach an angular resolution of ∼4″ (13 AU). These first millimeter interferometer observations of ϵ Eridani, which hosts the closest debris disk to the Sun, reveal two distinct emission components: (1) the well-known outer dust belt, which, although patchy, is clearly resolved in the radial direction, and (2) an unresolved source coincident with the position of the star. We use direct model-fitting of the millimeter visibilities to constrain the basic properties of these two components. A simple Gaussian shape for the outer belt fit to the SMA data results in a radial location of 64.4 − 3.0 + 2.4 ? > AU and FWHM of 20.2 − 8.2 + 6.0 ? > AU (fractional width Δ ? > R/R = 0.3). Similar results are obtained taking a power law radial emission profile for the belt, though the power law index cannot be usefully constrained. Within the noise obtained (0.2 mJy beam−1), these data are consistent with an axisymmetric belt model and show no significant azimuthal structure that might be introduced by unseen planets in the system. These data also limit any stellocentric offset of the belt to <9 AU, which disfavors the presence of giant planets on highly eccentric (>0.1) and wide (10's of AU) orbits. The flux density of the unresolved central component exceeds predictions for the stellar photosphere at these long wavelengths, by a marginally significant amount at 1.3 mm but by a factor of a few at 7 mm (with brightness temperature 13000 ± 1600 K for a source size of the optical stellar radius). We attribute this excess emission to ionized plasma from a stellar corona or chromosphere.
Modeling Strategies for Developing Treatment Response Indices

To find biosignatures of treatment response, clinicians are interested in identifying patient features at baseline that predict dierential response to different treatment. The treatments could be drug and placebo, or dierent drugs. These dierential predictors may be termed “moderators of treatment eect”, because the dierences between the ecacies of the treatments depend on the levels of those predictors. It is common in clinical research to model the outcome as a linear function of the predictor and to test for significance of the interaction between treatment and the predictors in order to find moderators of treatment eect. Also, typically, moderators are identified either one by one, using one model for each potential predictor, or from a large model which includes all potential predictors and their 2way interactions with treatment, but not interactions between the potential predictors. However, neither of these modeling strategies aids in the determination of combinations of patient characteristics that could be used to select patients who have high probability to respond to a given drug. In this talk we present flexible methods that extend the existing approaches for identification of dierential predictors of treatment response in two directions: