Miracle-dz/UniFAR-FTUs huggingface dataset:
ALAMEDA Ecosystem: Centering Efforts in Software Testing Development

One of the most important and critical aspects to improve the quality assurance in software is to improve the testing process by utilizing techniques and tools, which will enhance the software testing process, making it more effective and efficient. This chapter presents ALAMEDA ecosystem, a software package that centers its efforts in software testing development and is a result from a real-world project. ALAMEDA provides support to lifecycles focused on the generation, implementation, and testing organization from the earliest stages of software development. In addition, the ecosystem provides an environment of rating the degree of compliance of organizations with the International Standard for Testing ISO/IEC-29119. It is proposed as a tool to use during the various iterations that may occur in an agile software development process.
problem solving in the teacher initial training , integrating cognitive and affective aspects

Our work is based on two premises. The first is that affective factors (beliefs, attitudes, and emotions) influence teaching and learning mathematics, and problem solving in particular. The second is that initial teacher education is an important element in the process of improving overall educational practice. On this basis, our research group has been working on evaluating the influence of affect in mathematics problem solving for prospective teachers, and on designing and implementing a program of metacognitive intervention that integrates cognitive and affective factors. The present communication describes our research in this line.
Constructing Signal Transduction Networks Using Multiple Signaling Feature Data

Signal transduction networks (STN), as complex biological systems, are crucial for interand intra-cellular signaling. The essence of STN is underlain in some signaling features scattered in various data sources, and the biological components overlapping among STN. The integration of those signaling features presents a challenge. In this paper, we introduce an effective method that combine various signaling data features, and detect out the components overlapping among STN. This work has two main contributions. Many structured data of signaling features, i.e., protein-protein interaction networks, domain-domain interactions, signaling domains, and protein functions, have been extracted and combined to comprehensively construct STN. Those heterogenous data are known to be significant and useful in STN construction. The uncertain components overlapping among STN have already been found, using soft-clustering. We did the experiments with five biological processes in the Reactome database. Those processes were reconstructed with small errors. The experiment results were promising to discover new STN in system biology.
Label-Less: A Semi-Automatic Labelling Tool for KPI Anomalies

KPI (Key Performance Indicator) anomaly detection is critical for Internet-based services to ensure the quality and reliability. However, existing algorithms’ performance in reality is far from satisfying due to the lack of sufficient KPI anomaly data to help train and evaluate these algorithms. In this paper, we argue that labeling overhead is the main hurdle to obtain such datasets.Thus we novelly propose a semi-automatic labelling tool called Label-Less, which minimizes the labeling overhead in order to enable an ImageNet-like large-scale KPI anomaly dataset with high-quality ground truth. One novel technique in Label-Less is robust and rapid anomaly similarity search, which saves operators from scanning and checking the long KPIs back and forth for abnormal patterns or label consistency. In our evaluations using 30 real KPIs from a large Internet company, our anomaly similarity search achieves the best F-score of 0.95 on average, and a real-time per-KPI response time (less than 0.5 second). Overall, the feedback from deployment in practice shows that Label-Less can reduce operators’ labeling overhead by more than 90%.
In vitro Production of Silymarin from Silybum marianum L.

Silybum marianum L. is a wild medicinal herbal plant in Jordan. It is widely used in folk medicine due to its high content of silymarin. In vitro production of silymarin was experimented at different concentrations (0.0, 0.4, 1.0, 1.6 or 2.0 mg/l) of growth regulators (6-furfurylaminopurine (kinetin), 6-benzylaminopurine (BA), or 6-(gamma,gamma- Dimethylallylamino) purine (2ip)) and different concentrations (15, 30,45,60 mg/l) of carbon sources (glucose, fructose, and sucrose). HPLC (High Performance Liquid Chromatography) analysis was used to identify silymarin components. In vitro grown S. marianum on MS (Murashige and Skoo 1962) medium supplemented with (1.6 mg/l) kinetin and (0.1 mg/l) 1-Naphthaleneacetc acid (NAA) gave the highest silymarin content of (0.84%) silybin and (0.49%) silydanin as compared with cultures grown on hormone-free MS media which contained (0.36%) silybin and (0.30%) silydanin. In vitro grown S. marianum on MS medium supplemented with (2.0 mg/l) BA and 0.1 mg/l NAA yielded (0.67%) silybin and (0.37%) silydanin, while MS media supplemented with (1.0 mg/l) of 2iP gave (0.72%) silybin and (0.24%) silydanin. Otherwise, the in vivo (wild) grown shoots of S. marianum gave (1.07%) for silybin and (0.46%) sildyanin. Among carbon source, glucose at (45 g/l) gave (1.63%) of silymarin content. Results indicated a significant use of in vitro grown cultures for silymarin production.
Predicting the richness of aquatic beetles and bugs in a semi-arid mediterranean region

Predicting the richness of aquatic beetles and bugs in a semi-arid mediterranean region The southeastern Iberian Peninsula is a semi-arid region recognised as an area of high aquatic biodiversity. Water beetles (Coleoptera) and water bugs (Hemiptera) are two of the region's most thoroughly studied insect groups. An exhaustive database of aquatic beetles and bugs from the Region of Murcia (SE Spain) and a set of 33 variables were employed for two related purposes: a) to describe the sampling effort conducted in the study area on these groups in order to identify zones with reliable inventories and b) with this information as a base, to forecast the distribution of species richness for each group. Theoretical estimates were based on the Clench function applied to the accumulated number of samples and were constructed with general linear models (GLM). The following results were obtained: 1) the percentage of grid cells that can be considered to be well sampled in the study area (143 10 ×10 km UTM grid cells) is approximately 14 % for beetles and 22 % for bugs; 2) well-surveyed cells are evenly distributed according to the previously defined physioclimatic subareas, which enable the use of these grid cells for modelling the richness distribution; and 3) a more accurate picture of the actual richness patterns for both groups is shown by the analysis. These results were combined to identify key areas where future sampling efforts must be focused.
A longitudinal study of language learners’ images about Russia

Abstract Several studies in the field of applied linguistics have explored images held by language learners about a target language country. However, for the most part, these studies focused on learners of modern European languages, such as German, Spanish and French and they were conducted in Western educational contexts. Besides, none of the previous investigations attempted to conduct a systematic classification of the language learners’ images. The present longitudinal study addressed these gaps in the research literature. It explored images about Russia held by Malaysian learners of the Russian language in a large university in East Malaysia. This article reports the findings of three questionnaire surveys conducted in 2004, 2007 and 2010. It was found that the images about Russia held by the participants were diverse and clustered around eight countryrelated aspects. Content of some categories of images was stable and changed little over time. Other categories were more fluid and more prone to change. The paper concludes with a discussion of pedagogical implications that can be derived from the findings.
Excitation of microseisms

Excitation of microseisms is generally considered to be due to pressure change at ocean bottom, for which Longuet‐Higgins derived his celebrated formula in 1950. Use of this formula is an approximation, however. Comparison with a more rigorous normal‐mode formula shows that this conventional approach is acceptable for ocean depths less than 1 km but fails in deep oceans. On the other hand, there seems to be a multitude of evidence that source region for double‐frequency microseim is near the coast and thus is generally in shallow water. An evidence from buoy data for nonlinearity in ocean waves is presented to support this view. If a source region is in shallow water, use of the Longuet‐Higgins pressure formula at ocean bottom for the excitation of microseisms is justified, although one should pay attention to ocean depths very carefully.
Comparison of Two Possible Evolutionary Mechanisms of the 62 tRNA Codon Sequences

The tRNAs were divided into 62 groups based on the codons they carried and networks were constructed. Phylogenetic trees were constructed in parallel and antiparallel directions based on the parameters of these networks. Point mutations were found in the codon sites in the same clusters in the entire parallel and antiparallel phylogenetic trees, whereas there was no evidence of a complementary duplication mechanism in the corresponding antiparallel phylogenetic trees. The codons of isoaccepting tRNAs were found in neighboring clusters or distributed within a very small distance so the codons with only one base difference remained very close, which was perfectly consistent with the hypothesis that a new tRNA gene could be recruited from an isoaccepting group via another point mutation.
The Effect of Heat Processing and pH on PCR Detection of Genetically Modified (GM) Soy in Meat Products

Soybean is the most cultivated GM crop worldwide, being planted on 47% of the global GM crop area. However, GM crops have not been widely publicly accepted. Thus, countries have established regulations for the labeling of GM foods to inform consumer decision making. In 2010, regulations on GM foods began to be enforced in Turkey. To meet these legislation requirements, the development of reliable detection methods is an important priority in this research area. PCR-based methods are most commonly used for this purpose. However, processing factors (low pH, heat etc.) affect DNA quality and thus the sensitivity of PCR. The aim of this study was to evaluate the combined effects of heat and pH on the detection of GM soy in meat products. We found that the combined effects of heat and low pH affect the detection limit, but low levels of GM soy can still be detected after processing.
The Colorado Plateau Coring Project (CPCP): 100 Million Years of Earth System History

1. Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York 10964, USA 2. Earth and Planetary Sciences, Rutgers University, Piscataway, New Jersey 08854, USA 3. Department ofEarth and Planetary Sciences, University ofNew Mexico, Albuquerque, New Mexico 87131 , USA 4. Martin-Luther-Universitiit Halle-Wittenberg, Institut fiir Geowissenschaften, 06120 Halle (Saale), Germany 5. Department of Geology, Northern Arizona University, Flagstaff Arizona 86011, USA 6. Department of Geosciences, University of Arizona, Tucson, Arizona 85721, USA 7. Utah Museum of Natural History, 1390 E. Presidents Circle, Salt Lake City, Utah 84112, USA 8. Laboratory of Palaeobotany and Palynology, Utrecht University, Budapestlaan 4, 3584 CD Utrecht, Netherlands 9. Centro de Geosciencias, Campus Juriquilla UNAM, Queretaro, 76230 Mexico 10. Berkeley Geochronology Center, 2455 Ridge Rd., Berkeley, CA 94709, USA 11. Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing 210008, China
Using of Multidimensional Statistical Method to Analyse of Heavy Metals Contaminated Soil

Environmental pollution has recently become one of the key social issues. Deterioration of the environment with varying degrees of devastation in individual regions negatively contributes to public health and the quality of the entire ecosystem. Due to its use of agrochemicals, the agriculture itself along with individual industries cause the soil pollution with heavy metals. The paper investigates the degree of heavy metal contamination of agricultural soil in selected Slovakian districts over a monitored period of time. Selected multidimensional statistical methods were applied to analyze and evaluate the degree of soil contamination.
Effect of Wet Cupping on Serum Lipids Profile Levels of Hyperlipidemic Patients and Correlation with some Metal Ions

The present study was conducted to evaluate the effect of cupping therapy on serum lipid profile concentration and correlated to some trace elements (Cu, Zn, and Mn). Thirty one men (35 to 55 years old), with hyperlipidemia and without antihyperlipidemic drug or high energy diet consumption for the duration of the study were subjected to cupping. The serum for total cholesterol, triglyceride, lipoprotein (HDL, LDL) and trace elements concentration was collected from brachial veins, and determined before cupping and then once a week for two weeks after cupping. Patients with hyperlipidemia who subjected for cupping show a significantly decrease (p≤0.05) in total cholesterol, LDL cholesterol, and LDL/HDL ratio by comparison before cupping, while there were no significant differences in serum HDL cholesterol and triglyceride concentrations. Zn concentration and Cu/Zn ratio show a highly significant difference (p<0.001) after cupping and also showed a significant correlation with serum lipids profile after cupping, especially zinc metal.
A Model for the Mixing of Black Carbon Aerosols and Mineral Dust Particles in the Atmosphere

The process when freshly emitted black carbon particles are forming clusters and the mixing of these black carbon clusters and mineral dust particles has been simulated for a two-dimensional system. This has been done by combining diffusion-limited cluster aggregation and multifractal turbulent velocity fields. A simple model where the mineral dust particles drive the deposition of black carbon has been developed and investigated, suited for quantifying the deposition of black carbon aerosols in dry, desert-like areas such as Sahara or the Arabian peninsula. This is of interest as it is assumed that the lifetime of black carbon particles in the soil of these areas are very long. The deposition of black carbon may change the albedo of the surface of the Earth, which may effect both local weather and the climate. The results from the model, although uncertain, indicate that the lifetime of black carbon in the atmosphere with respect to uptake on larger dust aerosols is short enough to allow a substantial fraction of the BC emitted (mostly from flaring from oil/gas extraction) to be deposited in the high albedo desert regions where emissions occur.
BEHAVIOURAL INTENTION: MEDIATOR OF EFFORT EXPECTANCY AND ACTUAL SYSTEM USAGE

The purpose of this study was to examine the mediating role of behavioural intention on the relationship between effort and actual system usage. There was a system usage ranging from 20 percent to 30 percent for students and 15 percent to 20 percent for staff, which could be attributed to behavioural intention as a mediator and effort expectancy. The study employed a cross-sectional research design to provide a snap shot of the relationship between effort expectancy, behavioural intention and actual usage of the system. Quantitative research approach with descriptive and analytical research strategies was used. The study considered a population of 13,922 EIS intended only at the MUBS main campus and the sample comprised of 390 intended EIS users based on the sample determination approach by Yamane (1973). Simple random sampling was used to grant an equal chance for inclusion of each intended EIS user in the sample. It was then analyzed using a Statistical Package for Social Sciences (SPSS). Pearson’s correlation, regression analysis, Sobel test and Medgraph were used to establish relationship between study variables and to test mediation, respectively. Findings showed that there was a significant positive mediating effect of behavioural intention (BI) on the relationship between Effort Expectancy (EE) and Actual Usage (AU). The type of mediation was partial as EE predicts AU directly and indirectly through BI. There were also significant positive relationships between effort expectancy, behavioural intention to use and actual usage of the system. It was concluded that behavioural intention to use is a mediator of effort expectancy and actual system usage. It was recommended further that organizations pay attention to users’ pre-disposition to use systems as they link their effort expectancy to actual system usage.
Free layers and singular jumps in some singularly perturbed boundary value problems with turning points

where q = 0 or I < q < 2, s is a, fixed positive infinitesimal, T, A, and B are standard values, g(x) is a smooth standard function, and the interval [A, B] contains zeros of 9(x). Such boundary value problems arise in many different applied contexts as in the study of exit time problems for stochastic differential equations (cf. Matkowsky [11]) in the case q = 1. Other applications of such problems occur when q = 0, in reactiondiffusion and phase transition models (cf. Fife [8]), in the study of contrast structures (cf. Butuzov and Vasil'eva [4]), and also in problems related to critical paths of Feynman integrals (cf. McLaughlin [12, 13]). The behavior of the solutions of (1), (2) presents interesting features because of narrow boundary and interior layer regions where the solution changes rapidly. Determining the limiting behavior and the location of the internal layers exhibited by the solutions presents both analytical and computational challenges when the boundary value problem is an autonomous problem like (1), (2). In this paper, we shall give sufficient conditions for the existence of solutions of (1), (2) with either boundary layers or internal layers by assuming that the interval [A, B] contains "turning points" e^, where g(ei) = 0 with i = 1,. , n, such that the classical Rankine-Hugoniot condition, 2. + 1 g(s)ds = 0, / fails to determine the location U of the shock layer which joins the two equilibrium states UL = ei and UR = e^+i. We will also determine the location of the internal layers as a function of the number n of turning points e^ e [A,B], the position of e^ E [A,B], and the order ri of each turning point e^. (e^ is a zero of order r^ if g^\ei) = 0 for j = 0,. ,ri — 1 and ^(eO^O.) Depending on the order of the turning points, solutions of (1), (2) are shown to exhibit essentially two types of behavior. Turning points of different orders provide
The Analysis of Impoliteness Strategies Found in Carnage Movie Script (Analisis Strategi Ketidaksantunan Yang Ditemukan dalam Skrip Film Carnage)

This study is aimed to analyze the types of impoliteness and the factors that influence the use of impoliteness strategies in a movie script. The data source of this research are taken from a movie script entitled Carnage directed by Roman Polanski (2011) This study describes the types of impoliteness used by the characters in Carnage. This research uses qualitative method because the data of this research are in the form of utterances produced by the characters of Carnage. This research uses Culpeper’s theory of impoliteness strategy and theory of context to analyze impoliteness data found in the movie script. The results of this research show that there are five types of impoliteness strategies used by the characters in Carnage, they are: bald on record impoliteness, negative impoliteness, positive impoliteness, sarcasm or mock politeness and withhold politeness. The writer also found that there are three factors that influence the characters to use impoliteness strategy. The first factor is a conflict interest between the speaker and the hearer, the second is intimacy or closeness between the speaker and hearer and the last factor is power distance between the speaker and hearer.
Total Phenols and Antioxidant Activities of Some Herbal Teas and In Vitro Bioavailability of Black Tea Polyphenols

In recent years, studies on phenolic compounds and antioxidant activities of foods have increased due to the inverse relationship between degenerative diseases and consumption of polyphenol rich foods. To clarify the controversy related to if antioxidant activity can be supplied in vivo, the necessity for data on bioavailability of phenolic compounds are considered. The aim of the study was to determine total phenols and antioxidant activities of sage, linden flower, fresh nettle, dried nettle leaves and black tea infusions which are popular beverages in the Mediterranean region and also to evaluate antioxidant activities of standard phenolic compounds (catechin, ferulic acid, quercetin) and Trolox for comparison. Moreover, another goal was to determine in vitro bioavailability of black tea. Both black tea infusion and black tea dialysate inhibited ABTS radical cation oxidation by 99.43% and 42% respectively. Infusions of sage, linden flower, fresh nettle, dried nettle leaves inhibited ABTS radical cation oxidation by 39.61%, 96.70%, 70.80% and 95.50% respectively. Although total phenols of black tea dialysate decreased by 96.48%, total antioxidant activity decreased by 57.76%. Ten M catechin and 10M quercetin showed 100% inhibition on ABTS radical cation oxidation. However, Trolox and ferulic acid showed 100% inhibition at 20 M concentrations. Total antioxidant activity of a cup of black tea was found to be equal to 10 μM of quercetin, 10 μM of catechin, 20 μM of Trolox and 20 μM of ferulic acid. Total antioxidant activity of black tea dialysate was slightly higher than both 5 M of Trolox and 5 M of ferulic acid.
Unified Framework for Data Mining using Frequent Model Tree

Abstract: Data mining is the science of discovering hidden patterns from data. Over the past years, a plethora of data mining algorithms has been developed to carry out various data mining tasks such as classification, clustering, association mining and regression. All the methods are ad-hoc in nature, and there exists no unifying framework which unites all the data mining tasks. This study proposes such a framework which describes a data modelling technique to model data in a manner that can be used to accomplish all kinds of data mining tasks. This study proposed a novel algorithm known as Frequent Model (FM)-Growth, based on Frequent pattern (FP)-Growth algorithm. The algorithm is used to find frequent patterns or models from data. These models will then be used to carry out various data mining tasks such as classification, clustering. The advantage of these frequent models is that they can be used as it is with any data mining task irrespective of the nature of the task. The algorithm is carried out in two stages. In the first stage, we grow the FM-tree from the data and in the second stage, we extract the frequent models from the FM-tree. The accuracy of the proposed algorithm is high. However, the algorithm is computationally expensive when searching for frequent models in high volume and high dimensional data. The reason of expensiveness is that it needs to travel all the nodes of a tree. The study suggests measures to be taken to improve the efficiency of the overall process using dictionary data structure. Keywords: Data Mining, Frequent Pattern Recognition Unified Framework, Classification, Clustering, FPGrowth tree.