Miracle-dz/UniFAR-FTUs huggingface dataset:
Zoometric characterization and body condition score in Canarian camel breed

espanolLa conservacion, mejora y uso racional de los recursos geneticos animales locales y su diversidad son propositos prioritarios a nivel nacional e internacional de evidente caracter legitimo. Reconocida en situacion de amenaza, la raza camellar canaria (Camelus dromedarius) se encuentra marginalmente reducida a las islas orientales del archipielago. Su uso queda restringido fundamentalmente a la explotacion turistica y, de forma esporadica, a labores variadas en el ambito agropecuario. La caracterizacion morfoestructural y zoometrica del camello canario es una tarea clave que permitira la identificacion de aquellos caracteres o rasgos fenotipicos implicados en la actividad productivo-economica de estos animales con el fin de recuperar posibles nuevos nichos funcionales. La presente propuesta metodologica se enmarca en un contexto de oportunidad y resurgimiento de una potencial industria de produccion con el asentamiento de las bases para un programa de recuperacion y cria selectiva de esta raza camellar a traves de su sustentabilidad funcional. EnglishConservation and sustainable management of local animal genetic resources and their diversity are priority tasks within a national and international framework. Officially listed as a threatened native breed, Canarian camels (Camelus dromedarius) are marginally reduced to the eastern islands of the archipelago and mainly used in touristic activities; sporadically, these animals are used for production of food and other products. Morphostructural and zoometric characterization of Canarian camel will lead to the identification of those genetic-based characters or features involved in productive functional activities. The present methodological proposal is framed into a context of opportunity and resurgence of a potential production industry throughout the establishment of the baselines for a sustainable selective breeding program in this livestock species.
BESTMAP: behavioural, Ecological and Socio-economic Tools for Modelling Agricultural Policy

Half of the European Union (EU) land and the livelihood of 10 million farmers is threatened by unsustainable land-use intensification, land abandonment and climate change. Policy instruments, including the EU Common Agricultural Policy (CAP) have so far failed to stop this environmental degradation. BESTMAP will: 1) Develop a behavioural theoretical modelling framework to take into account complexity of farmers’ decision-making; 2) Develop, adapt and customize a suite of opensource, flexible, interoperable and customisable computer models linked to existing data e.g. LPIS/IACS and remote sensing e.g. Sentinel-2; 3) Link economic, individual-farm agent-based, biophysical ecosystem services and biodiversity and geostatistical socio-economic models; 4) Produce a simple-to-use dashboard to compare scenarios of Agri-Environmental Schemes adoption; 5) Improve the effectiveness of future EU rural policies’ design, monitoring and implementation.
GliFlix : Using Movie Subtitles for Language Learning

We introduce GliFlix , a new user interface aiming to enhance foreign language literacy as the users watch foreign-dubbed films. To reduce cognitive load and thus enhance learning, GliFlix presents “augmented subtitles,” selectively highlighting foreign words spoken in the films together with the users’ primary-language subtitles. To demonstrate the usefulness of GliFlix ’s augmented subtitles, we conducted a preliminary within-subjects study with 10 users, which showed that augmented subtitles potentially are preferred to the conventional one-language subtitle and may result in higher rates of foreign vocabulary acquisition.
UTILIZATION OF SOME NATURAL PLANT SOURCES IN THE PRODUCTION OF SOME NEW SHEETS

This study was carried out to produce new products ( sheets)from some popular natural plant sources such as tamarind( Tamarindus indcia L,) carob pods (Ceratonia Siliqua L ) and red roselle (Hibiscus sabdariffa L) as well as mixture of them. These sheets were prepared from tamarind, carob pods, mixes of tamarind and red Roselle (1:1 w/w) and mixes of tamarind, carob pods and red Roselle (4:1:1 w/w/w). Total soluble solids were increased to 18.0 % by sucrose. The dried sheets were evaluated chemically, physically and organoliptically at zero time, then after storage at room temperature for 4 and 8 months respectively. Data of pannel tests revealed that all reconstituted popular natural drinks of sheets showed a good score for color, taste, odour and palatability. It was also found through this study that storage at room temperature for 8 months had effects on the chemical and physical properties of all sheets
Application of natural zeolite in wastewater treatment: A review

The environmental pollution is a major problem over the world. The large amount of pollutants formed during various industrial processes reaches the ecosystem. Thus, heavy metals, oils and other organic compounds are responsible for water contamination. It is known that heavy metals have toxic effect on the environment. Additionally, they are non-degradable and have ability to reach the living organisms through the food chain. Among different methods, the adsorption is widely used in wastewater treatment due to simplicity of the process and efficiency in the removal of pollutants. Natural zeolites from different deposits have shown good selectivity for heavy metal ions. Additionally, they are environmentally friendly, low-cost and have high ion exchange capacity.
LUT School of Business and management

Liquidity has been researched globally and locally increasingly in the 21st century. One of the innovations for this is liquidity-adjusted CAP-model (LCAPM). It has been found that local factors are determining considerable part of the liquidity premium and the differences between markets are significant. However, research in the Finnish stock market is limited and the results differ as the methodologies vary. The aim of this research is to study the price of liquidity risk in the Finnish stock market and see how the methodology affects the results. The research period is from the beginning of 2002 till the end of 2018 and research data consists daily observations of 176 stocks. Liquidity is measured with Closing Percent Quoted Spread and the price of liquidity risk using unconditional LCAPM. The results suggest that two of the three systematic components of liquidity risk are priced along with the expected illiquidity. This means that investors in the Finnish stock market want a premium for holding illiquid stocks and if their illiquidity co-moves with the market illiquidity and return. The size of the liquidity premium in Finland is on the same level with the emerging markets. Compared to the prior studies in Finland it seems like the choice for illiquidity proxy is strongly driving the results. When it comes to the size of the liquidity premium, the use of whether the conditional or unconditional LCAPM is affecting greatly. Author: Title: School: Degree programme: Supervisor:
The relationship between the quality of working life and critical thinking of nurses in Milad Hospital of Isfahan, Iran

BackgroundThe quality of working life depends on the working conditions of the staff, and the decline in the quality of nurses' working life leads to a decline in the delivery of clinical services.ObjectivesThe purpose of this study was to determine the relationship between qualities of working life and critical thinking in nurses.MethodsThe present study is descriptive-correlational that was conducted on 123 nurses working in Milad Hospital in Isfahan. The data collection tools included demographic information questionnaire, Nursing Critical Thinking in Clinical Practice Questionnaire, and Quality of Nursing Work Life Scale. Data collection was carried out during December, 2018. The data were analyzed in SPSS software version 23 using descriptive statistics including mean, standard deviation, and frequency as well as analytical statistics including Pearson correlation coefficient.ResultsAccording to the results, a majority of the participants in the present study were females (52%). The score of nurses' critical thinking was found to be 319.76. The total average of nurses' quality of working life was reported as 138.70. Based on these results, there was no significant relationship between quality of working life and critical thinking in nurses.ConclusionThe results of this study indicated that the critical thinking of nurses is good, and the quality of working life is moderate. There was also no relationship between critical thinking and quality of working life
COMPUTER VISION METHOD FOR GUITARIST FINGERING RETRIEVAL

This article presents a method to visually detect and recognize ﬁngering gestures of the left hand of a guitarist. This method has been developed following preliminary manual and automated analysis of video recordings of a guitarist. These ﬁrst analyses led to some important ﬁndings about the design methodology of such a system, namely the focus on the effective gesture, the consideration of the action of each individual ﬁnger, and a recognition system not relying on comparison against a knowledge base of previously learned ﬁngering positions. Motivated by these results, studies on three important aspects of a complete ﬁngering system were conducted. One study was on ﬁn-ger tracking, another on strings and frets detection, and the last on movement segmentation. Finally, these concepts were integrated into a prototype and a system for left hand ﬁngering detection was developed.
Critical Challenges of Cultural Competence Professional Development

Driven by increasing inequities in health, education and social outcomes for Aboriginal people, cultural competence professional development has become more commonplace in many organizations. There are hundreds, possibly thousands, of cultural awareness, cultural sensitivity, or cultural competence professional development workshops held throughout Australia each year. However, there is an uncertainty about whether some professional development approaches improve one’s knowledge, skills and attitudes towards diverse cultures. This article presents one of the key findings of a doctoral study which explored early years educators’ understandings of cultural competence and presents several viewpoints towards professional development. This article calls for approaches to professional development that move beyond passive transmission modes of learning towards localized, participatory models that encourage engagement with local community to privilege a diversity of voices and that also inspires critical self-reflection.
Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach

Motivated by applications to machine learning and imaging science, we study a class of online and stochastic optimization problems with loss functions that are not Lipschitz continuous; in particular, the loss functions encountered by the optimizer could exhibit gradient singularities or be singular themselves. Drawing on tools and techniques from Riemannian geometry, we examine a Riemann–Lipschitz (RL) continuity condition which is tailored to the singularity landscape of the problem’s loss functions. In this way, we are able to tackle cases beyond the Lipschitz framework provided by a global norm, and we derive optimal regret bounds and last iterate convergence results through the use of regularized learning methods (such as online mirror descent). These results are subsequently validated in a class of stochastic Poisson inverse problems that arise in imaging science.
Context-Sensitive Intelligent Cueing

The focus of my dissertation research is on the evaluation of different delivery formats of electronic notifications. In contrast to the breadth of work addressing the question of when a notification should be issued, my work addresses the less studied question of how to issue a notification. In particular, I explore the question of whether individual preferences for notifications are affected by delivery in different contexts, which differs from prior work, most of which focused on evaluation of notifications with respect to performance. Initial results indicate that (1) on-screen notifications can be categorized as highly or moderately intrusive relative to one another, and that (2) while general preference trends between the presentation of a notification and the associated context are exhibited within the data, the relative desirability of a given visual notification is widely varied among individuals and across contexts. Included in my planned work to address this issue is an in-situ study of both the desirability and effectiveness of various visual and auditory notifications, as well as the exploration of machine learning tools for tailoring the presentation and modality of a notification to a computer user’s individual preferences.
Performance Analysis of Statistical and Structural Pattern Recognition Methods

: Pattern Recognition (PR) may effectively explain the recognition or perception of the pattern in the picture. It seeks to extract image information to classify its contents. Inputs take the form of digitized, valued binary 2D images or textures that contain the classified sequence. The analysis and recognition of patterns such as images and textures become increasingly complex and multi-faceted. The reason is that the patterns to be analyzed generally change from simple to complex and because we have to treat heavy variation patterns and heavy noise. It is therefore suggested that sophisticated pattern analysis techniques be built to deal with these difficulties. Pattern recognition is a research field which studies systems ' functioning and design that recognize patterns in data. Three basic approaches to the recognition of patterns are analysed here: statistical pattern recognition, structural pattern recognition and recognition of neural patterns. In the statistical approach, the recognition is focused on decision limits defined by statistical distribution of patterns in the feature space. Each pattern class is defined in the structural (syntactic) approach by a structural definition or representation. The recognition is carried out in accordance with the structural similarity. This is because the important information is not only the characteristics but also the relationships that exist between the features. The artificial neural networks are able to form complex decision regions for pattern recognition with the neural network approach. The present work includes the study of methods for pattern recognition in texture classifications.
EARNING QUALITY AND TAX PLANNING: EVIDENCE ON INDONESIA LISTED COMPANY

This study aims at determining the effect of tax planning, profit growth and firm size on earnings quality and also to test the effect of tax planning as moderating variable to influence of profit growth, size and earnings quality. This research is different from previous research, the difference is that this research makes tax planning as a moderation so that it can see whether tax planning can strengthen or weaken the influence of profit growth and firm size on earnings quality.The data used is secondary data from Indonesian listed manufacturing companies, hypothesis testing using regression model with partial least square test. This study shows that profit growth directly affects earnings quality and firm size does not affect earnings quality, but after being moderated by tax planning the size of the company has a significant effect on earnings quality. This research finding add understanding in assessing earnings quality with the influence of tax planning so that it can be used as a decision-making consideration.
Playing the Zombie: Participation and Interpassivity in Gothic XR

Marina Warner states that the concept of the zombie ‘embodies the condition of our time’ as it represents contemporary experiences of selfhood shaped by new technologies (2006: 357–8). In this paper I argue that, due to the interactive and immersive qualities of XR, the concept of the zombie in some recent Gothic expressions does not just represent contemporary experience of selfhood but is a development of an ‘interpassive’ role we play in everyday life (Pfaller 1996; Žižek 2008). Interpassivity is seen to be the ‘underside’ to interactivity, degrading any authentic experience or contribution of the individual. In some cases, the interpassive role in Gothic participatory experiences can be seen to be a cathartic extension of this everyday interpassive experience. However, the addition of a sadistic element to this role can lead to a ‘zombie-participant’ experience, which is a perverse and Gothic resistance to interpassivity. The paper focuses on two XR events that strive to reclaim the authentic self in what can be interpreted as a plight to recover the authenticity of individual experience within the closed loop of XR experience. The first is Whist (2017) by AΦE, where there is an attempt to reify the self through the trigger of the participant’s gaze. This results in an interpassive experience that demotes agency: rather than interpret the self, Freudian discourse is seen to ‘stand in’ for it, thus reflecting an interpassive state. The second is Doom Room (2018) by Makropol, where there is an attempt to reclaim the soul through re-birth via self-sacrifice. ‘Doom Room’ entwines the story of interpassivity with a sadistic interactive design, resulting in a destabilisation of ‘self’ that ultimately resists the interpassive experience.
D6.3: 1st Prototype of the Self-Healing and Patch Generation Component: FastFixSH

: This document reports on a new version of the FastFix D6.3 deliver-able, i.e. implementation of the 1st prototype of the FastFix self-healing and patch generation components. The initial goal of this deliverable has been modiﬁed in order to allow earlier implementation of the self-healing, hence an earlier evaluation of both the FastFIX self-healing and patch generation approaches. First this document recalls in Section 2 the main objectives and expected functionalities of these components, that will be developed as part of the FastFix project. Three main features of the self-healing components (model extraction, patch generation and runtime supervision) and their requirements are presented. Section 3 describes the current implementation of these features, corresponding to the delivery of this 1st prototype. It mainly focuses on the model extraction aspect on which the other ones are relying on. The extracted models are Finite State Machines (FSM). Section 3.2 describes the structure of these components and the constructs and speciﬁcities of the Java programming languages that it takes into account in order to extract Finite State Machines. The functionalities and usage of the implemented features are illustrated with an example in Section 4.1. Finally, Section 4 provides scalability results and describes the next steps to be performed from the implementation detailed in Section 3 in order to achieve the objectives described in Section 2.
Copy number variations of MMP-9 are prognostic biomarkers for hepatocellular carcinoma

Background This study aimed to investigate the effect of matrix metalloproteinase-9 (MMP-9) copy number variations (CNVs) on hepatocellular carcinoma (HCC) poor prognosis and recurrence. Methods A total of 35 patients were collected between January 2016 and December 2018. The copy number and expression level of MMP-9 were measured in 35 HCC tumor tissues and 35 paired adjacent non-tumor tissues using digital polymerase chain reaction (dPCR) and quantitative reverse transcription polymerase chain reaction (RT-qPCR), respectively. Results Our results showed that MMP-9 expression was significantly upregulated in HCC tumor tissues compared to adjacent non-tumor tissues (5.521±9.545 versus 1.000±0.000, P=0.0047). Interestingly, MMP-9 CNVs only existed in tumor tissues (15/35 versus 0/35, P=0.002). A breakdown analysis by the occurrence of CNVs in tumor tissues had shown that there were significant differences between CNVs group and non-CNVs group in the expression levels of tissue alpha-fetoprotein (AFP) (P=0.015), tumor size (P<0.001), differentiation (P<0.001), microvascular invasion (MVI) (P=0.009), and clinical stage (P<0.001). Receiver operating characteristic (ROC) curves showed that MMP-9 CNVs and expression were significant predictors of HCC [P<0.0001, area under the curve (AUC) =0.76]. Conclusions Our results demonstrated that MMP-9 CNVs were a promising diagnostic biomarker for HCC.
Influence of dietary Moringa oleifera on broilers performance, intestinal microbial population and humoral immune competence

This study was designed to evaluate the effect of using different levels of phytobiotic containing Moringa oleifera (M. oleifera) leaf powder (MOLP) on broiler chickens body growth performance parameters, intestinal microbial population, and the humoral immune response. Day-old Hubbard broiler chicks (n = 200) were randomly allocated into 4 treatment diet. Basal diet was supplied with treatments T0, T1, T2 and T3 representing (0, 1%, 5% and 7.5% MOLP); respectively. Chickens were kept under observation for 5 weeks. Body performance parameters, total viable bacterial and coliform counts and humoral immune response to Newcastle disease (ND) virus vaccine were detected using the haemagglutination inhibition (HI) test. The results revealed significant (P < 0.05) improvement in performance parameters in groups supplemented with dietary MOLP. However, the best significant (P < 0.05) performance was observed in the group fed 1% MOLP. There was no significant (P < 0.05) difference among treatments considering the total viable intestinal bacterial and coliform counts. Significant (P < 0.05) increase in the means of HI in dietary MOLP supplemented groups was observed, where the highest means were seen in 1% MOLP treated birds. In conclusion, dietary supplementation with MOLP could improve the performance parameters and the immune response while reducing the total viable intestinal bacterial and coliform counts of broiler chickens. The study recommended using of dietary level of 1% MOLP to improve performance, intestinal health, and immune competence.
High-level architecture for a digital oilfield: features of the transition to data-driven decision management

This paper is devoted to the design of a distributed heterogeneous data warehouse of a digital oilfield. With increasing amounts of data collected from intelligent controllers and sensors, the lack of mechanisms for combining data from different sources and providing them to consumers affect the overall management efficiency. In addition, without it is impossible making the next logical step – the effective application of intelligent analysis methods. The paper describes the high-level architecture, as well as subsystems of operational management and decision support. The presented data are intermediate results of the project “Digital oilfield heterogeneous distributed data warehouse for informational support of decision-making processes”.