Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptions of Structural Injustice and Efficacy: Participation in Low/Moderate/High-Cost Forms of Collective Action

Prior studies on perceptions of structural disadvantage and injustice, efficacy, and collective action have suffered from two major limitations: (1) they have used single country samples, usually of economically advanced countries, and (2) generally theorized and investigated perceptions of structural injustice and efficacy separately. Drawing on value-expectancy theory, we provide an integrated theory to predict direct and conditional effects of efficacy and perceptions of structural disadvantage and injustice on collective action within countries. To address the limitations of previous research, we use cross-national data of 29 countries, including economically advanced and less advanced nations, to test how well these hypotheses explain within-country variation in collective action. We find that internal efficacy is significantly and positively associated with low and moderate-cost collective action, whereas organizational embeddedness, a proxy for political efficacy, is significantly and positively associated with low-, moderate-, and high-cost collective action. Perceptions of legitimate and unjust structural disadvantage are also positively associated with all types of collective action. Importantly, the positive effects of both types of efficacy on high-cost collective action are conditional on perceptions of structural injustice. That is, participation in high-cost collective action is more likely for those who are both efficacious and perceive structural disadvantage as unjust.
Employability and Related Context Prediction Framework for University Graduands: A Machine Learning Approach

In Sri Lanka (SL), graduands’ employability remains as a national issue due to the increasing number of graduates produced by higher education institutions each year. Thus, predicting the employability of university graduands can mitigate this issue since graduands can identify what qualifications or skills they need to strengthen up in order to find a job of their desired field with a good salary, before they complete the degree. The main objective of the study is to discover the plausibility of applying machine learning approach efficiently and effectively towards predicting the employability and related context of university graduands in SL by proposing an architectural framework which consist of four modules; employment status prediction, job salary prediction, job field prediction and job relevance prediction of graduands while also comparing performance of classification algorithms under each prediction module. Series of machine learning algorithms such as C4.5, Naive Bayes and AODE have been experimented on the Graduand Employment Census - 2014 data. A pre-processing step is proposed to overcome challenges embedded in graduand employability data and a feature selection process is proposed in order to reduce computational complexity. Additionally, parameter tuning is also done to get the most optimized parameters. More importantly this study utilizes several types of Sampling (Oversampling, Undersampling) and Ensemble (Bagging, Boosting, RF) techniques as well as a newly proposed hybrid approach to overcome the limitations caused by the class imbalance phenomena. For the validation purposes, wide range of evaluation measures was used to analyze the effectiveness of applying classification algorithms and class imbalance mitigation techniques on the dataset. Experimented results indicated that RandomForest has recorded the highest classification performance for 3 modules, achieving the selected best predictive models under hybrid approach having a ROC AUC interpretation as an ‘Excellent’ experiment, while a C4.5 Decision Tree model under Ensemble approach has been selected as the best model of other module (Salary Prediction module).
Intelligent speed adaptation: acceptance and driver behaviour on rural roads

The PROSPER (Project for Research On Speed adaptation Policies on European Roads) project, funded by the European Commission within the 5th framework program, was initiated to find answers concerning efficiency, public support, and implementation of road speed management methods, particularly Intelligent Speed Adaptation (ISA) in Europe. A part of the PROSPER project was to examine the effect of Human Machine Interaction (HMI) design for ISA could on driving behaviour and acceptance. Therefore, sixty-four experienced drivers participated in two experiments (32 each), in a moving-base research driving simulator. During the simulated runs with ISA, the speed limit was communicated through the ISA system. The ISA system consisted of an indication of the speed limit on the speedometer, and a gas pedal that could either be used as a haptic or tactile pedal, or as a dead throttle. Two versions of the haptic gas pedal were examined in experiment (a): a low-force ISA (easy to overrule, informative in nature) and a high-force ISA (stronger counter force, more compulsory in nature). Two other configurations were tested in experiment (b): a tactile pedal (a vibration on the gas pedal, informative in nature) and a dead throttle (completely restraining the driver from exceeding the speed limit). It was hypothesised that the closer to an informative type of ISA, the higher acceptance and the smaller the effects on driving behaviour would be. This hypothesis appeared to be valid, although for both driving behaviour and acceptance, not all four HMIs could be ranked unambiguously on the scale from no ISA to full ISA. In sharp curves, drivers appeared to chose a driving speed below the speed limit, irrespective of ISA. The specific road environment scenarios that were inserted to examine presupposed compensatory behaviour for experienced delay, indicated no signs of compensatory driving behaviour. Finally, it is concluded that the most promising sustainable and safety-improving approach in the future is the use of intelligent electronic systems such as ISA combined and integrated in the whole design of the road traffic system consisting of both the geometric design and dynamic traffic management.
ENSO MODULATIONS ON STREAMFLOW CHARACTERISTICS

El Nino Southern Oscillation (ENSO) has been linked to climate and hydrologic anomalies throughout the world. This paper presents how ENSO modulates the basic statistical characteristics of streamflow time series that is assumed to be affected by ENSO. For this we first considered hypothetical series that can be obtained from the original series at each station by assuming non-occurrence of El Nino events in the past. Instead those data belonging to El Nino years were simulated by the Radial Based Artificial Neural Network (RBANN) method. Then we compared these data to the original series to see a significant difference with respect to their basic statistical characteristics (i.e., variance, mean and autocorrelation parameters). Various statistical hypothesis testing methods were used for four different scenarios. Consequently if there exist a significant difference, then it can be inferred that the ENSO events modulate the major statistical characteristics of streamflow series concerned. The results of this research were in good agreement with those of the previous studies.
Hormonal and Immunological responses to Coleus forskohlii treatment in Female Rats with Experimentally Polycystic Ovaries Syndrome

Polycystic ovaries syndrome (PCOS) is one of the most prevalent causes of reproductive failure. Its pathogenesis may be hormonal and immune disorder with hyperactivity of the sympathetic nervous system. The present study was conducted to demonstrate the effect of coleus forskohlii roots extract (CFE) in modulating the levels of some hormones and immune parameters of rats with androgen induced PCOS. Fifty immature female albino rats were divided into control group and androgen treated group that injected subcutaneously with 60 mg/kg BW/day androgen (Cidotestone) for 35 days to induce PCOS. Each group was subdivided into two subgroups. The first two subgroups received saline and 25 mg/kg BW of CFE, respectively while the other two subgroups received the same doses of Cidotestone and Cidotestone + CFE, respectively for 3 weeks. Blood samples were collected at the end of the experiment to estimate the levels of corticosterone, beta endorphin, total leucocytic count (TLC), cluster of differentiation 4 (CD + 4), cluster of differentiation 8 (CD + 8), interleukin 2 (IL-2), interleukin 3 (IL-3), interleukin 4 (IL-4), immunoglobulin G (IgG) and immunoglobulin A (IgA). The results revealed a significant decrease in the concentrations of β endorphin, IL-2, TLC, CD + 4, CD + 8 and IgG, while corticosterone and IL-4 showed a significant increase in the androgen induced PCOS group. Rats treated with Cidotestone + CFE displayed normal values of all tested parameters except corticosterone, suggesting role of CFE in mediating both humoral and cellular immunity.
Statistical machine translation in the translation curriculum: overcoming obstacles and empowering translators

In this paper we argue that the time is ripe for translator educators to engage with Statistical Machine Translation (SMT) in more profound ways than they have done to date. We explain the basic principles of SMT and reflect on the role of humans in SMT workflows. Against a background of diverging opinions on the latter, we argue for a holistic approach to the integration of SMT into translator training programmes, one that empowers rather than marginalises translators. We discuss potential barriers to the use of SMT by translators generally and in translator training in particular, and propose some solutions to problems thus identified. More specifically, cloud-based services are proposed as a means of overcoming some of the technical and ethical challenges posed by more advanced uses of SMT in the classroom. Ultimately the paper aims to pave the way for the design and implementation of a new translator-oriented SMT syllabus at our own University and elsewhere.
Solutions of two-dimensional integral equation systems by using differential transform method

In this paper, two-dimensional differential transform (TDDT) is applied to solve integral equation systems. If the solution of the system considered as a terms of the series expansion of known functions, then this method catches the exact solution. To show capability and robustness of the proposed method, some systems of two-dimensional integral equations are solved.
What We Know and Don’t Know About Corporate Social Responsibility

The authors review the corporate social responsibility (CSR) literature based on 588 journal articles and 102 books and book chapters. They offer a multilevel and multidisciplinary theoretical framework that synthesizes and integrates the literature at the institutional, organizational, and individual levels of analysis. The framework includes reactive and proactive predictors of CSR actions and policies and the outcomes of such actions and policies, which they classify as primarily affecting internal (i.e., internal outcomes) or external (i.e., external outcomes) stakeholders. The framework includes variables that explain underlying mechanisms (i.e., relationship- and value-based mediator variables) of CSR–outcomes relationships and contingency effects (i.e., people-, place-, price-, and profile-based moderator variables) that explain conditions under which the relationship between CSR and its outcomes change. The authors’ review reveals important knowledge gaps related to the adoption of different theoretical orientations by researchers studying CSR at different levels of analysis, the need to understand underlying mechanisms linking CSR with outcomes, the need for research at micro levels of analysis (i.e., individuals and teams), and the need for methodological approaches that will help address these substantive knowledge gaps. Accordingly, they offer a detailed research agenda for the future, based on a multilevel perspective that aims to integrate diverse theoretical frameworks as well as develop an understanding of underlying mechanisms and microfoundations of CSR (i.e., foundations based on individual action and interactions). The authors also provide specific suggestions regarding research design, measurement, and data-analytic approaches that will be instrumental in carrying out their proposed research agenda.
Modèles de regression en présence de compétition Aurélien Latouche

234 words) PURPOSE: In the analysis of competing risks outcomes, there is still an open debate with regards to the use of a regression model, either the cause-specific Cox model or the model proposed by Fine and Gray for the hazard associated with the cumulative incidence function. Our purpose was to further detail the implications of either choice when estimating the benefit of a new treatment on delaying the outcome of interest in this competing risks setting. PATIENTS AND METHODS: Differences are exemplified first through the risk set associated with each model, using an easily understandable graphical representation. Then, differences are illustrated using a real data sample from the randomized clinical trial ALFA 9000 conducted in acute myeloid leukemia to assess the benefit on relapse-free interval of timed-sequential induction over the standard treatment. RESULTS: Estimated adjusted treatment benefit could be modified by the handling of competing risks outcomes, with disappearance of statistical significance when using a cause-specific model (p= 0.13) as compared to the use of Fine and Gray model (p= 0.05). CONCLUSION: Differences in quantities of interest could help in selecting the regression model to be used. If effect on instantaneous hazard is that of interest, the cause-specific model is to be used, while if we are only interested in modeling the effect of covariate on the probability of a particular outcome, the Fine and Gray model is that of choice.
The Puzzle of Insular Domains: A Longitudinal Study of Knowledge Structuration and Innovation in Biotechnology Firms

In this study we explain the puzzle of insular domains: insular domains are niches where new innovation is built on the knowledge within the domain. Given the nature of knowledge needed for new innovation in an insular domain the puzzle is why do new firms enter these niches? In a longitudinal sample of 128 biotechnology start-ups founded from 1980 to 1999 we explain why start-ups enter insular domains and how the start-ups develop technology capabilities.
STUDY ON SITE CONDITIONS BASED ON TOPOGRAPHIC SLOPE

Abstract. The travel-time averaged shear-wave velocity to a depth of 30m (Vs30) below the Earth’s surface is widely used to classify sites in many building codes. Vs30 is also used to estimate site classification in recent ground-motion prediction equations (GMPEs), and the distribution of Vs30 has been mapped in a region or country. An alternative method has recently been proposed for evaluating global seismic site conditions or Vs30, from the SRTM (Shuttle Radar Topography Mission) DEMs (digital elevation models). The basic premise of the method is that the topographic slope can be used as a reliable proxy for Vs30 in the absence of geologically and geotechnically based site-condition maps through correlations between Vs30 measurements and topographic gradient. Here, we use different resolutions (3 arcsec, 30 arcsec) DEM data to get Vs30 data separately, analyze and compare the difference of Vs30 data and site conditions obtained from different resolution DEM data. Shandong Province in eastern China and Sichuan Province in Western China are studied respectively. It is found that the higher resolution data is better at defining spatial topographic features than the 30c data, but less improvement in its correlation with Vs30.
CAN MISPRICING OF ASSET GROWTH EXPLAIN THE ACCRUALS ANOMALY

Recent research suggests that the mispricing of asset growth can explain the accruals anomaly. We reexamine this issue by focusing on the role of accounting manipulations in stock mispricing. Specifically, we hypothesize that accounting manipulations are at the root of the accruals anomaly but play an insignificant role in the asset growth anomaly. Our large sample results strongly support our hypothesis, suggesting that investors can benefit from exploiting both anomalies instead of one.
Incorporation of Local Knowledge in the Identification of Ria de Aveiro Lagoon Ecosystem Services (Portugal)

ABSTRACT Sousa, L.P., Lillebø A.I., Gooch G.D. , Soares J.A. , Alves F.L. , 2013. Incorporation of Local Knowledge in the Identification of Ria de Aveiro Lagoon Ecosystem Services (Portugal). Coastal lagoons, such as Ria de Aveiro, are of strategic importance as they play a crucial role in almost all biogeochemical processes that sustain the biosphere and provide a variety of services, which are essential to the human wellbeing. Due to their potential vulnerability, to the increased human-related activities and pressures, the management of these systems requires an integrated and ecosystem based approach with close engagement of civil society. It is in this context that this research aims to include the population knowledge in the identification of Ria de Aveiro ecosystem services. In the scope of the EU-FP7 LAGOONS project 9 Focus Groups with the coastal lagoon inhabitants have been developed, in order to combine different scientific disciplines with local knowledge and stakeholders' views. In these sessions the participants freely discussed the topic of ‘Ria de Aveiro', and identified the types of uses and activities, discussed the current management model, and presented some recommendations for the future. This paper uses this privileged contact and proximity with local population to analyse the ecosystem services that participants indirectly identified. Relevant examples are the use of the lagoon for recreation, fishing or education-research activities. In terms of results, participants mainly identified provisioning and cultural services; however, even indirectly, they show some concerns regarding regulation and support services. Participants recognized the dependency of their uses and activities to a healthy ecosystem. The incorporation of their knowledge and concerns in the Ria de Aveiro management strategies is very important, since it has a pedagogical role and if people identify themselves with the decisions, they will accept them and enforce the compliance by the various users of Ria.
Innovating without traditional intellectual property protection : comparing proprietary and FLOSS solutions

The issue of innovation processes taking place in t he software sector is currently widely debated. Challenging questions arise about what products/ser vices have to be considered innovative, and whether a specific artefact is innovative or not. I n this framework, the widespread success of the Free/Open Source Software (FOSS) put forward new re search issues, dealing with whether and how programs developed according to the new product ion paradigm turn out to be more innovative than traditional ones. In this framework, this pape r aims at contributing to the literature by addressing three main research questions: (i) are s oftware solutions produced by Small and Medium Enterprises (SMEs) innovative? (ii) What kin ds of innovations are implemented? And, finally, (iii) are programs based on FOSS more inno vative than proprietary ones? Basing on a sample of 134 software solutions produc e by Italian SMEs and using an original methodology to asses the problem of evaluating inno vati n in the software field, we provides some first insights of what emerges if we set aside the traditional innovation indicators and endower to build alternative metrics, specifically developed t o target the complexity of the innovation processes in the software markets.
Examination on total ozone column retrievals by Brewer spectrophotometry using different processing software

Abstract. The availability of long-term records of the total ozone content (TOC) represents a valuable source of information for studies on the assessment of short- and long-term atmospheric changes and their impact on the terrestrial ecosystem. In particular, ground-based observations represent a valuable tool for validating satellite-derived products. To our knowledge, details about software packages for processing Brewer spectrophotometer measurements and for retrieving the TOC are seldom specified in studies using such datasets. The sources of the differences among retrieved TOCs from the Brewer instruments located at the Italian stations of Rome and Aosta, using three freely available codes (Brewer Processing Software, BPS; O3Brewer software; and European Brewer Network (EUBREWNET) level 1.5 products) are investigated here. Ground-based TOCs are also compared with Ozone Monitoring Instrument (OMI) TOC retrievals used as an independent dataset since no other instruments near the Brewer sites are available. The overall agreement of the BPS and O3Brewer TOC data with EUBREWNET data is within the estimated total uncertainty in the retrieval of total ozone from a Brewer spectrophotometer (1 %). However, differences can be found depending on the software in use. Such differences become larger when the instrumental sensitivity exhibits a fast and dramatic drift which can affect the ozone retrievals significantly. Moreover, if daily mean values are directly generated by the software, differences can be observed due to the configuration set by the users to process single ozone measurement and the rejection rules applied to data to calculate the daily value. This work aims to provide useful information both for scientists engaged in ozone measurements with Brewer spectrophotometers and for stakeholders of the Brewer data products available on Web-based platforms.
Mechanical properties of sisal fibre reinforced urea- formaldehyde resin composites

Alkali-treated sisal fibres were used as novel reinforcement to obtain composites with self-synthesized urea- formaldehyde resin as matrix phase. The composites were prepared by means of compression molding, and then the effects of sisal loading on mechanical properties such as impact strength, flexural strength, and wear resistance were investigated. In addition, water uptake was studied and structural features were revealed by the scanning electron microscopy (SEM). The composite with 30 wt% sisal fibres gives excellent flexural strength, water absorption, and especially the wear resist- ance showing that it has the most superior bonding and adhesion of all the composites. In particular, the highest value 9.42 kJ/m2 of charpy impact strength is observed in the composite with 50 wt% sisal fibre. SEM micrographs of impact fractured and worn surfaces clearly demonstrate the interfacial adhesion between fibre and matrix. This work shows the potential of sisal fibre (SF) to improve the composite wear resistance and to be used in fibreboard.