Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of space and time changes of NDVI ( biomass ) in Armenia ’ s mountain ecosystems using remote sensing data

This study of vegetation biomass for different areas in the mountain ecosystems of Armenia was implemented for the vegetation period of 2013. The research was done based on time series of Normalized Difference Vegetation Index (NDVI) as NDVI images have been proven to be a powerful tool to monitor biomass growth during the last decade. NDVI, which can be directly calculated from Landsat satellite data, is related to vegetation canopy characteristics. This NDVI-based research of different-aspect slopes at 1850–3150 m have indicated that during vegetation period the highest biomass is detected on north facing slopes at altitudes of 2300–2400 m, and the lowest – on south facing slopes at altitudes of 2000–2100 m. High correlation coefficients between NDVI values of southwest slopes and absolute altitudes of localities are detected in April and August, whereas variation in NDVI values depending on the altitude is nonlinear.
Lawrence Berkeley National Laboratory Recent Work Title An Asynchronous Task-based Fan-Both Sparse Cholesky Solver Permalink

Systems of linear equations arise at the heart of many scientific and engineering applications. Many of these linear systems are sparse; i.e., most of the elements in the coefficient matrix are zero. Direct methods based on matrix factorizations are sometimes needed to ensure accurate solutions. For example, accurate solution of sparse linear systems is needed in shift-invert Lanczos to compute interior eigenvalues. The performance and resource usage of sparse matrix factorizations are critical to time-to-solution and maximum problem size solvable on a given platform. In many applications, the coefficient matrices are symmetric, and exploiting symmetry will reduce both the amount of work and storage cost required for factorization. When the factorization is performed on large-scale distributed memory platforms, communication cost is critical to the performance of the algorithm. At the same time, network topologies have become increasingly complex, so that modern platforms exhibit a high level of performance variability. This makes scheduling of computations an intricate and performance-critical task. In this paper, we investigate the use of an asynchronous task paradigm, one-sided communication and dynamic scheduling in implementing sparse Cholesky factorization (symPACK) on large-scale distributed memory platforms. Our solver symPACK relies on efficient and flexible communication primitives provided by the UPC++ library. Performance evaluation shows good scalability and that symPACK outperforms state-of-the-art parallel distributed memory factorization packages, validating our approach on practical cases. Keywords-Cholesky; factorization; dynamic scheduling; asynchronous; task; UPC++; one-sided communications
RAPD based genetic diversity, agronomic characters, and nutrition content of Timor Leste kidney bean (Phaseolus vulgaris) genotypes

Abstract. Vidal MC, Setiawan A, Wahyu Y. 2019. RAPD based genetic diversity, agronomic characters, and nutrition content of Timor Leste kidney bean (Phaseolus vulgaris) genotypes. Biodiversitas 20: 2612-2619. The productivity of kidney beans (Phaseolus vulgaris L.) in Timor Leste is relatively low and needs to be improved. The increase in kidney bean yield through plant breeding, however, can only be obtained if information the genetic diversity of breeding materials is available. This study aimed to characterize agronomic characters, to assess genetic diversity and nutrient content of kidney bean in Timor Leste. The materials used in this study were 13 Timor Leste and 2 Indonesian genotypes as controls. The experimental design for the field trial was a complete randomized block design with three replications. The treatment was 13 kidney bean genotypes. The results showed that there were significant variations in agronomic characters among the genotypes tested. Result from phylogenetic trees based on the Random Amplified Polymorphic DNA (RAPD) indicated that the genetic material understudied can be grouped into three main groups. The Indonesian genotype belongs to a different group from Timor Leste genotypes. Direct selection based on seed yields produced the best eight East Timor genotypes, TL-RO3, TL-LUN, TL-LM, TL-R10, TL-LL, TL-RW, TL-LB, TL-LB, and TL-Umabano. The nutritional content of the kidney bean genotype from Timor Leste was similar to that of the Indonesian genotype. The carbohydrate content of the Timor Leste genotype was considered high (average = 59.95%), while the average fat content is low (1.71%) and the average protein content was quite moderate (18.08%).
Using Three-Dimentional Image Technology to Enhance Students ’ Learning

The study aimed to apply three-dimensional image technology to the learning of information technologies and e-Commerce technologies, and evaluate students’ learning performance as a consequence. Participants were 65 students from a vocational school of commerce. The teaching activities emphasized the instruction of students to help them to explore topics related to e-business and information technologies, whilst using the three-dimensional image system, thus strengthening the integration of e-business and information technologies applications. The research instruments included a rubric for a marketing project, teaching feedback from a teacher, and learning feedback from students. The results showed that integrated applications and training in information technologies can promote the use of technology by vocational school commerce students. Most students could adequately use the animation techniques of three-dimensional imagery to give a rich presentation of the features of commodities, and were able to implement marketing strategies to express marketing originality whilst displaying their technology learning skills. Also, both the teacher and the students expressed their support and recognition for the application of three-dimensional image technology.
Stability Enhancement of Doubly Fed Induction Generator Using a Linear Quadratic Regulator

194 Abstract— This paper proposes a linear quadratic regulator to stabilize the rotor speed of the doubly-fed induction generator which oscillates as a result of noises in the input speed. The speed loop in the conventional vector control is reduced ignoring doubly-fed induction generator converter dynamics. Laplace transform of the closed-loop speed control is used to design an optimal controller based on the linear quadratic regulator to damp oscillations of the speed caused by measurement noise in the reference input. The state-space linearization of the system is presented. The strategy is aimed at reducing variations in rotor speed and electromagnetic torque during fault and achieve stable operation thereafter. In the paper linear quadratic regulator is compared with vector control and pole placement controller in terms of performances. The proposed controller improves the transient behavior of the induction machine when subjected to measurement noise. The recommended procedure maintains the stability of the wind generator during and after measurement noise. Results show the robustness of the linear quadratic regulator over other methods in tracking the reference values.
FDI and Unemployment , a Growth Perspective 11 / 2018

4 Zusammenfassung . 4
The SPHINCS + Signature Framework Full version , September 23 , 2019

We introduce SPHINCS+, a stateless hash-based signature framework. SPHINCS+ has significant advantages over the state of the art in terms of speed, signature size, and security, and is among the nine remaining signature schemes in the second round of the NIST PQC standardization project. One of our main contributions in this context is a new few-time signature scheme that we call FORS. Our second main contribution is the introduction of tweakable hash functions and a demonstration how they allow for a unified security analysis of hash-based signature schemes. We give a security reduction for SPHINCS+ using this abstraction and derive secure parameters in accordance with the resulting bound. Finally, we present speed results for our optimized implementation of SPHINCS+ and compare to SPHINCS-256, Gravity-SPHINCS, and Picnic.
Migration and product sophistication in Italian provinces

In this paper we study the role of migrants in shaping the production structure of host countries. More specifically, we provide the first empirical evidence on the linkage between migration and product sophistication in Italy. By exploiting variation across Italian provinces in the presence of migrants and export structure over the period 2002-2013, we show that provinces recording a higher share of migrants undergo a reduction of the sophistication level of manufacturing exports. This finding is robust to a number of alternative specifications and to the control for omitted variables and reverse causality. We show that one channel of the negative migration-sophistication nexus originates from the impact of the presence of migrants on new entrepreneurial activities. By exploring data on business demography by sector and province we show, indeed, that migration favours the creation of new firms disproportionally more in less sophisticated sectors.
diviz : a tool for modeling , processing and sharing algorithmic workflows in MCDA

The diviz software is a tool for modeling, processing and sharing Multiple Criteria Decision Aid (MCDA) techniques. The target user community of diviz reaches from researchers to teachers and students via practitioners. One of the principal features of diviz is to ease the comparison of results produced from different methods and algorithms on the same decision problem instance.
Prediction of Academic Talent Capacity Based on Gradient Boosting Decision Tree

Talent introduction is an important force of academic development in universities. As the core of talent introduction, prediction of academic talent capacity is an essential and valuable research. However, it is hard to apply traditional statistical methods to extract knowledge from the mass and multi-dimensional talent information. Data mining approaches as up-to-date and efficient technologies are good at analyzing information, extracting patterns or rules from a big dataset and then making a prediction based on the relationship among extracted information. In this study, a series of data mining approaches are employed to evaluate the academic capacity of talent and to analyze the correlation between features. The Principal Component Analysis and Random Forest are used to feature extraction for improving the accuracy of prediction. A classical classification model, Gradient Boosting Decision Tree, is used as the primary analytic model to prediction. In order to validate the effectiveness of the model, other five classification models are used to conduct a comparative experiment based on prediction accuracy values and the F-measure metric. Further, to investigate the contribution of some important features, we make a marginal utility analysis of important features which have a high correlation with academic talent capacity. The experiment results reveals the important features for academic capacity and the positive factors for the academic production of talents.
FIRST REPORT ON THE FLORA OF DAMS AND WATER BREAKERS IN AN ARID DESERT OF THE UNITED ARAB EMIRATES

This paper provides the first comprehensive checklist of vascular plant flora of dams and water breakers in hyper-arid desert habitats of the United Arab Emirates (UAE). Surveys in 66 dams and water breakers were conducted to explore flora of these areas. A total of 248 plant species belonging 170 genera distributed in 50 families were recorded. Among these, two regionally endemic species Pulicaria edmondsonii and Schweinfurthia imbricata, in addition to 34 rare species, were recorded from the study area. The chorological analysis showed that the floristic composition is dominated by SaharoArabian elements, with 149 species. The life form spectrum indicated that therophytes were the most represented (46%) and Helophytes was the least represented life form group. Analysis of plant growth form shows that the occurrence of annual plants was high, followed by the perennials.
The PcG protein HPC 2 inhibits RBP-J-mediated transcription by interacting with LIM protein KyoT 2

The DNA-binding protein recombination signal-binding protein-Jk (RBP-J) plays a key role in transcriptional regulation by targeting the intracellular domain of Notch (NIC) and the Epstein–Barr virus nuclear antigen 2 (EBNA2) to specific promoters. In the absence of the Notch signaling, RBP-J acts as a transcriptional suppressor through recruiting co-suppressors such as histone deacetylase (HDAC). KyoT2 is a LIM domain protein that suppresses the RBP-J-mediated transcriptional activation. In the current study, we show that the polycomb group (PcG) protein HPC2, which functions as a transcriptional suppressor, is a candidate of KyoT2-binding proteins. To confirm the physical and functional interaction between KyoT2 and HPC2, we carried out yeast two-hybrid, GST-pull down, coimmunoprecipitation, as well as mammalian two-hybrid assays. Our results showed HPC2 and KyoT2 interacted both in vitro and in vivo, probably through the C-terminal fragment of HPC2 and LIM domains of KyoT2. In addition, we also found that overexpression of HPC2, not only inhibited transactivation of a RBP-J-dependent promoter by NIC, but also transactivation by RBP-J–VP16, a constitutively active form of RBP-J. Taken together, our results suggested that KyoT2 might inhibit the RBP-J-mediated transactivation through NIC by recruiting co-suppressors such as HPC2. 2005 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Abstrak—Status gizi merupakan keadaan tubuh sebagai akibat konsumsi makanan dan penggunaan zat gizi. Status gizi

Abstrak—Status gizi merupakan keadaan tubuh sebagai akibat konsumsi makanan dan penggunaan zat gizi. Status gizi dipengaruhi oleh konsumsi makanan dan penggunaan zat-zat gizi di dalam tubuh. Pada penelitian ini dilakukan analisis status gizi menggunakan regresi logistik ordinal dan Support Vector Mechine (SVM). Berdasarkan hasil penelitian dengan regresi logistik ordinal, menunjukkan bahwa variabel prediktor yang berpengaruh terhadap status gizi adalah jumlah konsumsi, usia, pekerjaan kepala keluarga, daerah,dan karbohidrat, untuk model kategori laki-laki, sedangkan pada model kategori perempuan adalah jumlah konsumsi, pekerjaan kepala keluarga, daerah, dan protein. Berdasarkan variabel prediktor tersebut, maka dapat diketahui bahwa metode SVM dengan fungsi kernel RBF mampu mengklasifikasikan status gizi mencapai 54,69% untuk kategori laki-laki dan 53,01% untuk kategori perempuan untuk provinsi Bengkulu dan 53,85% untuk kategori laki-laki dan 68,75% untuk kategori perempuan untuk provinsi Sulawesi Barat.
Momentum Profits and Macroeconomic Risk 1

We propose that measurement problems are responsible for existing findings associating macroeconomic risk with stock price momentum. For instance, Liu and Zhang (2008) find that the growth rate of industrial production “plays an important role in driving momentum profits. ” In contrast, we show that winners and losers only differ in factor exposure during January when losers massively outperform winners. During months where momentum exists, winner and loser exposures offset nearly completely. Similar findings apply to other macroeconomic risk factor variables. Furthermore, the magnitude of macroeconomic risk premia appear to seasonally vary contra momentum. JEL Classification: G12, E44
Maternal English Language Proficiency and Obesity among Young Children of Immigrants

Past research indicates that children of immigrants may be an especially vulnerable group for unhealthy weight gain (Van Hook and Baker 2010), despite their advantage in early life factors associated with lower obesity (birth weight, breast feeding, exclusive parental care) and lower weight status of parents (Lara et al., 2005). Using the Early Childhood Longitudinal Study-Birth Cohort, we examine whether maternal English language proficiency is associated with child’s weight status at 5 years old. Similar to past research, we find that children of low English-proficiency immigrants are the heaviest. However, children of high English-proficiency immigrants have a lower weight status than children of natives. Socioeconomic factors account for the higher weight status of children of low English-proficiency immigrants compared to high English-proficiency immigrants. Early life factors and maternal health habits account for the lower weight status of children of high English-proficiency immigrants compared to children of natives. Past Literature and Theoretical Background Immigrants tend to have much better health than the native born population on many health outcomes, especially in regards to infant health and pregnancy outcomes. Foreign born Hispanic mothers are more likely to breastfeed, have lower odds of infant mortality, are less likely to smoke, drink, or use illicit drugs during pregnancy, and less likely to have low birth weight or early gestational age children (Lara et al., 2005; Singh, Kogan, and Dee, 2007). Breast feeding, prenatal smoking, and low birth weight have all been identified as determinants of obesity (Bergmann et al., 2003). However, these better health behaviors and outcomes do not translate into lower weight status among their children. Past research on young children has consistently found that children of foreign born parents have higher prevalence of obesity and higher growth in BMI from childhood to adolescence, especially among the more recently arrived immigrants, and this remains significant after controlling for race/ethnicity, socioeconomic factors, and family characteristics (Van Hook and Baker 2010; Van Hook and Ballistreri 2007; Li et al., 2010; Van Hook et al., 2009). Parental acculturation likely has both positive and negative effects on children’s health. For example, past research suggests that children of immigrants may be especially vulnerable to developing unhealthy weight gain because immigrant mothers are more likely to view heavier child figures as ideal, more likely to underestimate their children’s weight status, and less likely to view child obesity as a health concern (Crawford et al., 2004; Fuentes-Afflick and Hassel 2008; Sosa 2011; Bayles 2010; Ariza et al., 2004). Focus group interviews with immigrant mothers indicate they are more likely to view child thinness as a health concern rather than overweight. They associated thinness with malnutrition and intestinal infections (Crawford et al, 2004). These factors may result in children becoming heavier if
How do Corporate Tax Incentives affect Firm-Level Performance ? A Propensity Score Matching Analysis in Dominican Republic

This paper evaluates the impact of fiscal incentives on firm performance in the Dominican Republic. In recent years, the Dominican government has approved several new corporate tax benefits. While the literature on value-added tax incentives is extensive, the impact of corporate tax incentives is less explored and is the subject of an ongoing debate. Using firm-level panel data from 2006 to 2015, an analysis based on a propensity score matching is carried out in order to investigate the aforementioned relationship considering some opportunely selected financial indicators as a proxies of firm’s performance. As to the effects on outcomes the results show and make in evidence that the exemption from the Corporate Income Tax positively impacts the firm ’s welfare. This evidence persists for both the Nearest Neighbour Matching than the Radius Matching and supports the balancing test.
1 Cooperating , Fast and Slow : Testing the Social Heuristics Hypothesis . 1

Are humans intuitively cooperative, or do we need to deliberate in order to be generous to others? The Social Heuristics Hypothesis (SHH) proposes that fast instinctive decision making promotes cooperation in social dilemmas. In this paper, we conduct a novel time-pressure experiment to shed light on the cognitive underpinnings of cooperation. Although we find no evidence for a time-pressure effect when considering all subjects, our results, together with a re-analysis of independent data, indicate that a single factor – payoff comprehension – accounts for some studies failure to replicate the finding that fast and intuitive decision making promotes cooperation. Given payoff comprehension, the SHH predicts behavior well. We believe this finding provides a unifying interpretation of the conflicting results in the literature.
Generating an Informed Virtual Geographic Environment through Cell Merging in order to Geosimulate the Propagation of Zoonoses

Zoonoses (infectious diseases transmitted from insects to animal and to humans) such as Lyme disease is a concern for public health authorities, especially after their proliferation due to global warming. Notwithstanding the obvious influence of geographic features (as for example the suitability of geographic areas on the species’ biological processes such as survival, feeding and breeding), they are not integrated in currently available zoonosis simulations based on mathematical compartment models which specify the characteristics of the transitions between the different stages (e.g. eggs, larvae, adults, inflected, etc.) of the involved species. Hence, there is a need for a software to simulate such a propagation taking into account the geographic characteristics of the landscape and the spatial behaviors (and interactions) of the involved species. In this context, we propose a novel approach using an informed Virtual Geographic Environment (VGE) composed of a set of cells in which the transitions of the different biological stages of the involved populations, as well as their interactions can be simulated plausibly. In order to reflect in the VGE the landscape’s influence on the biological phenomena, we automatically generate the VGE cells from vector-based land-cover data provided by a Geographic Information System. The cells are obtained by a stepwise aggregation of landcover polygons selected according to biologically relevant qualitative criteria such as the survival suitability of a cell for a given species. For geosimulation purposes one critical issue, discussed in the paper, is to significantly reduce the huge number of land-cover polygons that are associated with the studied geographic areas. We propose a threshold-based merging algorithm which iteratively reduces the number of polygons while generating a spatial subdivision composed of cells with the maximal size and suitability for a given biological phenomenon. Our approach also enhances each cell with qualitative information about the relative geographic orientation of its neighbors. The resulting informed VGE provides the foundation for the simulation of a variety of spatial-temporal phenomena such as the migration of birds importing infected insects (i.e. juvenile ticks in the case of Lyme disease) and the survival of tick colonies in suitable