Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Local Low-rank Matrix Approximation for Recommendation

Low-rank matrix approximation (LRMA) has attracted more and more attention in the community of recommendation. Even though LRMA-based recommendation methods (including Global LRMA and Local LRMA) obtain promising results, they suffer from the complicated structure of the large-scale and sparse rating matrix, especially when the underlying system includes a large set of items with various types and a huge amount of users with diverse interests. Thus, they have to predefine the important parameters, such as the rank of the rating matrix and the number of submatrices. Moreover, most existing Local LRMA methods are usually designed in a two-phase separated framework and do not consider the missing mechanisms of rating matrix. In this article, a non-parametric unified Bayesian graphical model is proposed for Adaptive Local low-rank Matrix Approximation (ALoMA). ALoMA has ability to simultaneously identify rating submatrices, determine the optimal rank for each submatrix, and learn the submatrix-specific user/item latent factors. Meanwhile, the missing mechanism is adopted to characterize the whole rating matrix. These four parts are seamlessly integrated and enhance each other in a unified framework. Specifically, the user-item rating matrix is adaptively divided into proper number of submatrices in ALoMA by exploiting the Chinese Restaurant Process. For each submatrix, by considering both global/local structure information and missing mechanisms, the latent user/item factors are identified in an optimal latent space by adopting automatic relevance determination technique. We theoretically analyze the model’s generalization error bounds and give an approximation guarantee. Furthermore, an efficient Gibbs sampling-based algorithm is designed to infer the proposed model. A series of experiments have been conducted on six real-world datasets (Epinions, Douban, Dianping, Yelp, Movielens (10M), and Netflix). The results demonstrate that ALoMA outperforms the state-of-the-art LRMA-based methods and can easily provide interpretable recommendation results.
Is the Performance of Snapdragon Plants ( Antirrhinum majus L . ) Influenced by Some Bio-Stimulators under Salinity Stress ?

This study was carried out during the two seasons of 2014/2015 and 2015/2016, at the nursery of the Ornamental Hort. Dept., Fac. Agric. , Cairo Univ., Egypt. The aim of this research was to determine the influence of foliar application of three anti-salinity agents: chitosan, setter-2 and citric acid on growth, flowering and chemical composition of Antirrhinum majus L. plants exposed to salinity stress. The plants were irrigated with saline water containing NaCl at the concentrations of 20, 40, 60 and 80 mM, while the control plants irrigated with tap water. Plants irrigated with different salinity levels were foliar sprayed every two weeks with chitosan, setter-2 or citric acid at the concentration of 2000 ppm. The results revealed that raising salt concentration to 40 mM or more decreased plant height, leaf area, shoot fresh and dry weights, inflorescences length and inflorescences fresh weight. All salt concentrations increased number of leaves/plant and root length, while had no significant effect on stem diameter and inflorescences dry weight. Increasing salt concentrations from 20 to 80 mM decreased total chlorophylls, total carbohydrates and N, P and K %, while increased proline content, Na and Cl% in leaves. Foliar application of chitosan or setter-2 significantly increased the most growth and flowering parameters, total carbohydrates and N, P and K % and reduced the accumulation of proline content, Na and Cl% and appeared to be more effective than citric acid in this respect. Under the different concentrations of salinity, in most case, treating plants with chitosan or setter-2 improved most of the studied growth and flowering traits, increased total carbohydrates, N, P and K % while reduced the accumulation of proline content, Na and Cl % in leaves at the highest salt concentration compared to control (plants only irrigated with salt concentrations). From these results it can be conducted that the adverse effects of salinity on A. majus could be alleviated by foliar application of chitosan or setter-2 at the concentration of 2000 ppm.
Learn How to Cook a New Recipe in a New House: Using Map Familiarization, Curriculum Learning, and Bandit Feedback to Learn Families of Text-Based Adventure Games

We consider the task of learning to play families of text-based computer adventure games, i.e., fully textual environments with a common theme (e.g. cooking) and goal (e.g. prepare a meal from a recipe) but with different specifics; new instances of such games are relatively straightforward for humans to master after a brief exposure to the genre but have been curiously difficult for computer agents to learn. We find that the deep Q-learning strategies that have been successfully leveraged for superhuman performance in single-instance action video games can be applied to learn families of text video games when adopting simple strategies that correlate with human-like learning behavior. Specifically, we build agents that learn to tackle simple scenarios before more complex ones using curriculum learning, that familiarize themselves in an unfamiliar environment by navigating before acting, and that explore uncertain environments more thoroughly using contextual multi-armed bandit decision policies. We demonstrate improved task completion rates over reasonable baselines when evaluating on never-before-seen games of that theme.
Land use change as a determinant of the European agricultural vulnerability confronted with pollinator decline

Insect pollination is essential for the production of a large array of crops. In the last decade, there has been evidence of a worldwide pollinator decline. A major pressures for this decline seem to be land use change and agricultural intensification. Yet the policy response is not as fast as it should be. One can explain this reluctance by the low visibility of this impact into the agricultural sector in the near future. This paper analyzes the evolution in next years of the European agricultural vulnerability confronted with pollinator decline through the evolution of land use change. The vulnerability of agriculture to insect pollination loss is a combination of three indicators: 1) the economic value of insect pollination, 2) the vulnerability ratio, and 3) the social welfare loss. The evolution of these indicators until 2080 have been estimated in three scenarios: Growth Applied Strategy (GRAS), Business As Might Be Usual (BAMBU) and Sustainable European Development Goal (SEDG). The overall result is that the European agricultural vulnerability will increase in the near future in all scenarios and thus we demonstrate that policy is needed to protect pollinators.
DYE INDUSTRIAL SLUDGE WITH THE HELP OF EISENIA FETIDA

The spread of textile waste effluents into water inhabiting the aquatic habitat and general health of the public residing in that area. This study was an attempt to convert the DIS (Dye industrial sludge) into vermicompost, which in turn could be used to improve the physical, chemical and biological properties of the soil exploration, five different concentration of DIS: 5 g/kg, 10 g/kg, 20 g/kg, 30 g/kg, and 40 g/kg were vermitreated employing the earthworm Eisenia fetida waste from the DIS was elucidated. Among the nutrients, po DIS at higher concentration of 30 g/kg and 40 g/kg. total nitrogen was maximum in DIS vermitreated using Eisenia fetida. Heavy metals like Zn, Cu, Fe, Mn, Cr, and Pb elevated in the treated group when compared to cont total magnesium, total Zinc, total copper, total manganese of the vermicomposted DIS were found to be significantly elevated when compared to the control.
Effects of MRI-Detected Brain Lesions After Left Atrial Catheter Ablation for Atrial Fibrillation: Long-Term Results of the MACPAF

Bei dem eingereichten Manuskript handelt es sich um die Publikation „Neuropsychological Effects of MRI-Detected Brain Lesions After Left Atrial Catheter Ablation for Atrial Fibrillation: Long-Term Results of the MACPAF Study“, die im Journal „Circulation: Arrhythmia & Electrophysiology“ im August 2013 erschienen ist. Die Arbeit entstand im Rahmen meiner kumulativen Dissertationsarbeit, welche ich dieses Jahr einreiche. Weitere Veröffentlichungen der MACPAF-Studie, an denen ich beteiligt war, finden Sie in der Publikationsliste meines Lebenslaufs. Eine kurze Zusammenfassung der MACPAFStudie können Sie ebenfalls dem Anhang entnehmen.
DETERMINANTS AND EFFECTS OF STRUCTURAL ECONOMIC CHANGE ON EMPLOYMENT AND INCOME INEQUALITY IN EAST KALIMANTAN Author ’ s Name and Affiliation

The objectives from this research are to knowing and analyzing the influence of natural resources revenue-sharing, government capital expenditure, investment, road infrastructure towards labor absorption either direct or indirectly through economic structure comprise primary, secondary, and tertiary sectors.This research also examines influence of labor absorption towards income imbalance directly in East Kalimantan. From the 14 districts/cities in East Kalimantan province, this study takes totally sample of 13 districts/cities, namely Balikpapan, Samarinda, Bontang, Berau City, West Kutai regency, East Kutai regency, Penajam Paser Utara, Pasir Malinau, Nunukan, Bulungan, and Tarakan. Type of data used in this research is secondary data in the form of time series of the 2001-2012 annual in each districts/city (as many as 13 districts/cities). This study used the approach path analysis as a technique to analyze the structural relationships. Development of the modelin this study was to examine the relationship between exogenous and endogenous variables, simultaneously. Based on research result, revealed that there is an affected result that relate to the impact of determinants economic structure changes in East Kalimantan.
Human Capital and Income Inequality: New Facts and Some Explanations

This paper computes an updated data set on human capital inequality for 146 countries from 1950 to 2010. Using the new indicators, we document several facts regarding the evolution of income and human capital inequality. The main findings reveal that, in spite of a marked reduction in human capital inequality around the world, the inequality in the distribution of income has hardly changed. In many regions, the income Gini coefficient was almost the same in 2005 as it had been in 1960. In order to find explanations for this puzzle, we first estimate the distribution of wages using recent estimates of rates of return to years of schooling. We find an inverted U-shape relationship between these two Gini coefficients that can be explained by a composition effect resulting from the fall in the share of population with no schooling. When we analyze the sensitivity of our results to different assumptions on the returns to years of schooling, we find the returns do not affect the inverted U-shape in developing countries, where the share of illiterates is high. We also show that exogenous forces such as skill-biased technological progress have offset the effects of the fall in education inequality, which therefore represents an alternative explanation for the low correlation between the changes in labor income and education inequality across countries.
Proﬁtability of banana cultivation under agricultural credit in Narsingdi district of Bangladesh

Agricultural credit can play important role by providing the needed liquidity to farmers who do not have sufﬁcient investable funds to exploit the opportunity. The present study analyses the adequacy, utilization patterns and repayment status of credit, the proﬁtability and show the relationship between proﬁtability and loan size of Banana cultivation in sadar upazila of Narsingdi district of Bangladesh. Primary data were collected from randomly selected 60 borrowers of the different NGOs who cultivate Banana in the study area. Data were collected through direct interviewing using pre-tested semi-structure interview schedule. Both tabular and econometric techniques were used to analyze the data. Average amount of loan received were Tk. 13750, 23100, 35100 for the small, medium, and large categories of borrowers, respectively. The overall average amount of loan received was 85.4% of applied amount. Most of the credit amount was utilized for farming purposes. Status shows that repayment rate was highly satisfactory. Multiple regression models indicate that amount of loan received and level of education of the respondents were signiﬁcant factors affecting loan repayment. It was estimated that overall average annual total cost of production of Banana per hectare was about Tk. 557710 while gross return and net returns were about Tk. 931024 and Tk. 373313, respectively. The overall beneﬁt-cost ratio of Banana cultivation was 1.67. The relationship between loan size and proﬁtability of Banana cultivation indicated that medium size loan receiver farmers were more proﬁtable compare to the small and large amount of loan receiver farmers. The ﬁndings of the study indicated that reasonable amount of credit ensures farmers to proﬁtable farming activities. The ﬁndings of this study will be helpful for ﬁnancial institutions ofﬁcials and policy makers to formulate the loan disbursement policies related to agricultural credit in Bangladesh.
Finding generalized near-repdigit squares

with the repeated digit 0 ≤ a < b. Obláth’s problem is to determine all decimal repdigits which are also perfect powers. Trivially, the single-digit perfect powers 4, 8 and 9 satisfy this criteria. Obláth [1] proved that any other such number must be a repunit, that is, having every digit equal to 1. Bugeaud and Mignotte [2] completed his problem by showing a repunit in base 10 cannot be a perfect power. Similarly, a near-repdigit to base b is a number having all digits but one equal in base b. Generalizing this, we define an n-near-repdigit to be a number with all equal digits except for an n digit streak of a different digit. A k-digit n-near-repdigit to base b has the general form
Mirroring the Gap Between Theory and Practice: ELT Juniors’ Auto-Criticism on their Teaching

Bu çalışma İngiliz Dili Eğitimi Bölümü 3. Sınıf öğrencilerin öğretmenlik uygulamalarına dair farkındalıklarını hızlandırmak amacıyla ‘Çocuklara İngilizce Öğretimi’ dersinde yapılan mikro öğretim uygulamalarını incelemektedir. Bu uygulamalar sırasında toplam 72 öğrencinin en sık kullandığı 45 olumlu veya olumsuz öğretmen davranışı tanımlanmış ve bu davranışlar temel alınarak, hayali bir öğretmenin bir dersinin metni yaratılmıştır. Sonrasında bu hayali ders metni bir sınav formunda öğrencilere verilerek 45 öğretmen davranışından istedikleri herhangi 20 tanesini olumlu ya da olumsuz olarak yorumlamaları istenmiştir. Sınav kâğıtlarının analizinde öğrencilerin mikro öğretim sunularında gözlemlenen öğretmenlik davranışları ile aynı davranışların kâğıt üzerindeki yorumlamaları arasında bir uyumsuzluk olduğu gözlemlenmiştir. Öğrencilerle kuram ve uygulama arasındaki boşluğun nedenleri, dört aylık bu sürecin öğretmenliklerine dair anlayışlarına olan etkileri tartışılmıştır. Bu tartışmaların saha notları çalışmanın bir diğer veri kaynağı olarak kullanılmıştır. Öğrencilerin deneyim ve güven eksiklikleri, utangaçlık, heyecan ve sınav üzerinde yapılan değerlendirmenin öğrencilerin geldikleri sistemle uyuşuyor olması çalışma sonuçlarına yön veren etkenler olarak ortaya çıkmıştır.
HETEROGENEOUS BELIEFS , STOCHASTIC VOLATILITY AND VOLATILITY SKEW

The paper represents an initial effort to unfold some the determinants of the implied volatility skew in financial (derivative) markets. We propose a simple explanation of the implied volatility asymmetrical behavior, both by means of mathematical derivations and empirical analysis. In particular, traders’ use of the widely accepted Black– Scholes formula with a measure of stock volatility that they calculate accordingly to their subjective and heterogeneous beliefs is a determinant of the implied volatility skew. The analysis provides also new characterizations of the behavior of the equilibrium option price that holds promise for practical modeling and forecasting.
OF PIGMENTS AND ACTIVITY OF ANTIOXIDANT ENZYMES IN RICE PLANTS PRETREATED WITH SODIUM NITROPRUSSIDE AND EXPOSED TO CLOMAZONE

The pre-treatment of rice seeds with sodium nitroprusside (SNP) was used to investigate the effect of exogenous nitric oxide on the pigment content and the activity of antioxidant enzymes during the inhibition of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway by the herbicide clomazone. The seeds were soaked in SNP solution (200 mM) for one and 10 hours and sprayed with clomazone, at postseeding and at the needle-point, with 612 (experiment 1) and 1,224 g a.i. ha-1 (experiment 2). The control of both factors received distilled water. Carotenoids, chlorophylls a, b and total, superoxide dismutase (SOD), guaiacol peroxidase (POD) and the correlation between the variables were evaluated in the shoot of the plants. When compared to the control (no SNP), the imbibition for one hour increased carotenoid and total chlorophyll content by 24 and 54%, respectively, in experiment 1, where clomazone was applied in post-seeding. In the absence of the herbicide, the values were 37 and 59% higher. The SOD and POD activity, respectively, was increased by 48 and 51%, when the seeds were soaked for 10 hours and exposed to 612 g a.i. ha-1 of clomazone in post-seeding application. In a similar condition, in experiment 2, there were no changes in enzyme activity. Seed pretreatment with SNP increases the carotenoid and chlorophyll contents in rice plants, even with the inhibition of the MEP pathway by clomazone. The behavior of the SOD and POD activity indicates that other mechanisms besides the increase in the photosynthetic pigment contents are involved in the detoxification of the reactive oxygen species induced by the mode of action of clomazone.
Heritability of methane production and genetic correlations with milk yield and body weight in Holstein-Friesian dairy cows

Greenhouse gases originating from the dairy sector, including methane (CH4), contribute to global warming. A possible strategy to reduce CH4 production is to use genetic selection. This requires genetic parameters for CH4 production and correlations with production traits. Data were available on 184 Holstein-Friesian cows. Methane production was measured in the milking robot during milking from December 2009 to April 2010. In total 2,456 observations for CH4 production were available. Milk yield (MY) and body weight (BW) were obtained at every milking from November 2008 to October 2010. In total 4,567 observations for milk yield and 4,570 observations for BW were available. Restricted maximum likelihood, using random regression models, was used to analyze the data. Heritability (standard error given in parentheses) for CH4 production ranged from 0.12 (0.16) to 0.45 (0.11), and genetic correlations with MY ranged from 0.49 (0.12) to 0.54 (0.26). The positive genetic correlation between CH4 production and milk yield indicates that care needs to be taken when genetically selecting for lower CH4 production, to avoid a decrease in MY at the animal level. However, this study shows that CH4 production is moderately heritable and therefore progress through genetic selection is possible.
Challenges Related to Studying L 2 Collocational Use in Professional

Little is known about the complex process of L2 incidental vocabulary acquisition from listening and the factors that contribute to its success. To expand our knowledge in this area, the present study investigated the impact of five learner-related variables on L2 incidental vocabulary acquisition from listening. These variables were gender, L2 vocabulary knowledge, amount of L2 listening (for academic purposes and pleasure), level of enjoyment, and (self-reported) level of comprehension. Ninety-nine Iranian English as a foreign language (EFL) learners at pre-intermediate levels of English proficiency were randomly assigned to a listening group and a control group. Sixteen target words were chosen in a graded reader and were then replaced by 16 English-like non-words. The participants listened to the graded reader containing the 16 non-words and completed a vocabulary post-test immediately after the listening session. The posttest measured participants’ knowledge of five different dimensions of word knowledge at the level of recognition. The findings revealed that while gender and amount of L2 listening appear to have no impact on incidental vocabulary gains from listening, L2 vocabulary knowledge, level of enjoyment, and level of comprehension are important facilitating factors.
Direct Touch Gaze Input Mid-Air Gestures Proxemics Wearable Speech Input

There has been a consistent push towards exploring novel input, display, and feedback technologies for sensemaking of data. However, most visual analytic systems in the wild that go beyond a traditional desktop just utilize commercial large displays with direct touch, since they require the least effort to adapt from the desktop/mouse setting. There is a plethora of device technologies that are yet to be tapped. Through this paper, we want to bring attention to available modalities for input for visual exploration within immersive display environments. These can be environments that contain multiple wall and floor displays, or projections to create immersion. We first isolate the low-level interaction tasks performed by a user based on a usage scenario for visual exploration. We focus on egocentric visual exploration in these environments, and introduce input modalities that enable interactions directly between a human body and objects of interest on the interface without a mediator in the middle (e.g., a handheld smartphone). Based on this, we identify affordances of different input modalities—touch, speech, proxemics, gestures, gaze, and wearable—in terms of the interaction tasks from the envisioned scenario. Finally, we discuss how modalities can be combined to complement each other and leverage their advantages in the immersive environment. By doing so, this paper provides guidelines for new system developers to utilize the best input technologies for their immersive analytics applications.
Explicit Control of Feature Relevance and Selection Stability Through Pareto Optimality

I Increasing stability . Ensemble feature selection : selects features that are selected the most accross different selection runs. Instance weighting : weights training instances according to their importance to feature evaluation. Model selection: takes stability into account in the fitting of the meta-parameters. ⇒ No fine control of the accuracy-stability trade-off. I Stability measure [1]