Miracle-dz/UniFAR-FTUs huggingface dataset:
Fiscal Adjustment and Income Inequality: Sub-National Evidence from Brazil

The paper combines state-level fiscal data with household survey data to assess the links between sub-national fiscal policy and income inequality in Brazil over the period 1995-2011. The results indicate that a tighter fiscal stance at the sub-national level is not associated with a deterioration in inequality measures. This finding contrasts with the conclusions of several papers in the burgeoning literature on the effects of fiscal consolidation on inequality using national data for OECD economies. In addition, the authors find that a tighter stance is typically positively associated with a measure of"shared prosperity". Hence, the results caution against extrapolating policy implications of the literature focusing on advanced economies to other settings.
On the Realization of Asymmetric High Radix Signed Digital Adder using Neural Network

This paper proposes an asymmetric high-radix signed-digital (AHSD) adder for addition on the basis of neural network (NN) and shows that by using NN the AHSD number system supports carry-free(CF) addition. Besides, the advantages of the NN are the simple construction in high speed operation. Emphasis is placed on the NN to perform the function of addition based on the novel algorithm in the AHSD number system. Since the signed-digit number system represent the binary numbers that uses only one redundant digit for any radix r  2, the high-speed adder in the processor can be realized in the signed-digit system without a delay of the carry propagation. A Novel NN design has been constructed for CF adder based on the AHSD (4) number system is also presented. Moreover, if the radix is specified as r = 2, where m is any positive integer, the binary-to-AHSD(r) conversion can be done in constant time regardless of the wordlength. Hence, the AHSD-to-binary conversion dominates the performance of an AHSD based arithmetic system. In order to investigate how NN design based on the AHSD number system achieves its functions, computer simulations for key circuits of conversion from binary to AHSD (4) based arithmetic systems are made. The result shows the proposed NN design can perform the operations in higher speed than existing CF addition for AHSD.
Scalable Stochastic Kriging with Markovian Covariances

Stochastic kriging is a popular technique for simulation metamodeling due to its exibility and analytical tractability. Its computational bottleneck is the inversion of a covariance matrix, which takes $O(n^3)$ time in general and becomes prohibitive for large n, where n is the number of design points. Moreover, the covariance matrix is often ill-conditioned for large n, and thus the inversion is prone to numerical instability, resulting in erroneous parameter estimation and prediction. These two numerical issues preclude the use of stochastic kriging at a large scale. This paper presents a novel approach to address them. We construct a class of covariance functions, called Markovian covariance functions (MCFs), which have two properties: (i) the associated covariance matrices can be inverted analytically, and (ii) the inverse matrices are sparse. With the use of MCFs, the inversion-related computational time is reduced to $O(n^2)$ in general, and can be further reduced by orders of magnitude with additional assumptions on the simulation errors and design points. The analytical invertibility also enhance the numerical stability dramatically. The key in our approach is that we identify a general functional form of covariance functions that can induce sparsity in the corresponding inverse matrices. We also establish a connection between MCFs and linear ordinary differential equations. Such a connection provides a flexible, principled approach to constructing a wide class of MCFs. Extensive numerical experiments demonstrate that stochastic kriging with MCFs can handle large-scale problems in an both computationally efficient and numerically stable manner.
The knowledge graph as the default data model for learning on heterogeneous knowledge

In modern machine learning, raw data is the pre-ferred input for our models. Where a decade ago data scien-tists were still engineering features, manually picking out the details they thought salient, they now prefer the data in their raw form. As long as we can assume that all relevant and ir-relevant information is present in the input data, we can de-sign deep models that build up intermediate representations to sift out relevant features. However, these models are often domain specific and tailored to the task at hand, and therefore unsuited for learning on heterogeneous knowledge: informa-tion of different types and from different domains. If we can develop methods that operate on this form of knowledge, we can dispense with a great deal of ad-hoc feature engineering and train deep models end-to-end in many more domains. To accomplish this, we first need a data model capable of ex-pressing heterogeneous knowledge naturally in various do-mains, in as usable a form as possible, and satisfying as many use cases as possible. In this position paper, we argue that the knowledge graph is a suitable candidate for this data model. This paper describes current research and discusses some of the promises and challenges of this approach.
Say, display, replay: Erving Goffman meets Oscar Wilde

Script: Jean-Remi Lapaire, Universite Bordeaux Montaigne, France Choreography: Jean Magnard Reader: Jean-Remi Lapaire Performers: Hugo Dabadie, Florian Escoubet, Julie Guede, Eleonora Martiian, Marie Nahon, Celine Salcho It is a fact of our human condition that, for most of us, our daily life is spent in the immediate presence of others; in other words, that whatever they are, our doings are likely to be, in the narrow sense, socially situated. Erving Goffman (1982)Other peop.
Freshwater input and abrupt deglacial climate change in the North Atlantic

Greenland ice-core records indicate that the last deglaciation (~7 - 21 ka) was punctuated by numerous abrupt climate reversals, involving temperature changes of up to 5-10oC within decades. However the cause behind many of these events is uncertain. A likely candidate may have been the input of deglacial meltwater, from the Laurentide ice sheet (LIS), to the high latitude North Atlantic, which disrupted ocean circulation and triggered cooling. Yet the direct evidence of meltwater input for many of these event has so far remained undetected. In this study, we use the geochemistry (paired Mg/Ca-δ18 O) of planktonic foraminifera from a sediment core south of Iceland to reconstruct the input of freshwater to the northern North Atlantic during abrupt deglacial climate change. Our record can be placed on the same timescale as ice-cores and therefore provides a direct comparison between the timing of freshwater input and climate variability. Meltwater events coincide with the onset of numerous cold intervals, including the Older Dryas (14.0 ka), two events during the Allerod (at ~13.1 and 13.6 ka), the Younger Dryas (12.9 ka), and the 8.2 ka event, supporting a causal link between these abrupt climate changes and meltwater input. During the Bolling-Allerod warm interval, we find that periods of warming are associated with an increased meltwater flux to the northern North Atlantic, which in turn induces abrupt cooling, a cessation in meltwater input, and eventual climate recovery. This implies that feedback between climate and meltwater input produced a highly variable climate. A comparison to published data sets suggests that this feedback likely included fluctuations in the southern margin of the LIS causing rerouting of LIS meltwater between southern and eastern drainage outlets, as proposed by Clark et al. [Science, 2001, v293, 283-287].
Habitat degradation increases functional originality in highly diverse coral reef fish assemblages

As anthropogenic and natural disturbances intensify, there is mounting concern about the loss of functionally important or unique species. Functional redundancy, or the presence of several different species occupying similar functional niches, can provide insurance against diversity loss, but evidence for this effect is rare. Likewise, the ways in which functional redundancy patterns respond to disturbances are poorly known, impeding a thorough understanding of community-level dynamics post disturbance. Here, we use an extensive reduction of hard coral cover following a tropical cyclone to explore the response of a highly diverse reef fish assemblage to habitat degradation. We demonstrate that despite clear trait value-specific susceptibility of fishes to the disturbance, five of six functional indices (including functional richness and evenness) showed no relationship with habitat degradation. In contrast, functional originality, which quantifies the average functional uniqueness of species within an assemblage, increased post disturbance, exhibiting a negative, albeit weak, relationship with decreasing coral cover. The increase in functional originality is simultaneously driven by the loss of functionally similar species in susceptible groups (predominantly small planktivorous and omnivorous species that associate with live coral habitat) and the addition of functionally unique species in groups that benefit from the disturbance (large, non-territorial species feeding on algal turfs, detritus, and invertebrates). Our findings suggest that coral reefs with high coral cover can foster fish assemblages with low functional originality (i.e., high functional redundancy), therefore preventing detectible changes in some of the most commonly applied functional indices post disturbance. However, we caution that the limited resolution of trait-based approaches may mask the loss of functionally unique species and that, with an increase in functional originality, post disturbance assemblages may be less suited to adequately maintain certain ecosystem functions in the face of future disturbances. Thus, there is an urgent need for further exploration of the dynamics between disturbances, functional redundancy, and ecosystem functioning.
Personality Traits and Learning Styles of Secondary School Students in Serbia.

This paper is concerned with the personality dimensions and learning styles of secondary school students, attending grammar and technical vocational school. The aim of the study is to examine differences in personality traits and learning styles between students from these types of schools, as well as to determine the predictive power of personality traits for certain learning styles of students. The sample consists of 240 fourth-year students attending grammar (120) and secondary technical school (120). Research variables were measured by NEO PI-R Personality Inventory (according to Five-factor model) and Index of Learning Styles (developed within Felder-Silverman’s model). The results show that grammar school students, compared with technical school students, have higher level of all personality dimensions except the Neuroticism, which is higher in technical school students. Grammar school students have higher measures of Sensor, Active and Sequential styles than students from technical school. Multiple regression analysis has shown that certain learning styles could be predicted by some personality traits. In grammar school sub-sample Openness seems to be the best predictor while Consciousness is significant predictor of learning styles in technical school. The findings are discussed in the light of possibility for better understanding the personality-learning-teaching relationships that could contribute to more effective individualization of teaching process.
Vegetative Filter Strip Design for Grassed Areas Treated with Animal Manures

Vegetative filter strips (VFS) are a low-cost management option that have been demonstrated to be effective in reducing runoff transport of fertilizer constituents applied to grassed areas (pasture or meadow). Runoff quality studies involving fertilizers applied to grassed areas suggest that VFS can be designed by assuming that (1) only infiltration is responsible for pollutant removal, (2) the first post-application runoff event is most important from a water quality perspective (enabling a design event approach), and (3) no pollutant build-up that degrades VFS performance will occur. The purpose of this study was to develop a VFS design algorithm for grassed areas that uses available information on the water quality dynamics of these systems to simplify the design process to the greatest degree practical. The design algorithm consists of the SCS (1972) Curve Number method for runoff estimation and the Overcash et al. (1981) equation for predicting concentrations of pollutants exiting a VFS as a function of VFS and runoff parameters. The procedure can be used to determine the VFS length required to meet either an allowable pollutant runoff concentration or allowable pollutant mass transport. As an alternative, the process can be used to determine VFS length required to achieve given relative reductions in incoming pollutant runoff concentrations and mass transport. This algorithm can be used quickly and with minimal data to determine the VFS length requirement necessary to provide any desired degree of effectiveness given inputs such as incoming pollutant runoff concentration, background pollutant runoff concentration, soil hydrologic properties, and design storm parameters. Charts are presented that eliminate the need for computations in selected cases.
Maternal Sensitive Determinants of Nutritional Status Among Children Below Five Years in Obunga Slums

Malnutrition remains a major proxy determinant of child mortality common among under five children and account for about one-third of malnourished cases worldwide. This chronic condition is a severe public health problem in sub-Saharan Africa that requires continuous critical attention. This study explored maternal sensitive factors that are important in the etiology of malnutrition with urban slum setting. The study was conducted among 400 eligible households systematically samples at random. Analysis was based hierarchical regression with principal axis factoring for selective variables. Psychosocial indicators did not have any observable association with nutritional status. Seeking immediate medical attention from the nearest health facility (HSB-1) and Average duration of introducing a child to the first liguid in hours (FP-4) significantly reduced stunting. Clean my hands with running water and soap before feeding a child (FHP-1) significantly reduced stunting among other indicators. HSB-1 somehow increased stunting. Wasting was significantly reduced by HSB-1 but increased by consulting a private doctor to examine a child (HSB-3). Underweight had no association at all with all indicators of maternal factors except at crude odds ratio level where FHP-1and HSB-1 were somewhat associated with underweight. In conclusion, this study revealed that food hygiene practice, health seeking behavior and feeding practice were all significant associates of stunting (p<0.05). Wasting was only associated with health seeking behaviour (p<0.05) while underweight had association with food hygiene practice and health seeking behaviour (p<0.05). However, it is noted that in these factor domains only selected indicator measures exhibited significant associations.
Morphological Diversity of Populations of the Genus Prosopis in the Semiarid Chaco of Northern Cordoba and Southern Santiago Del Estero

The objective of this study consisted in the characterization of morphological variability presented in the Prosopis population in the corridor that unites the semiarid with the arid region in Argentina. In this region, four species of Prosopis get in contact (P. chilensis, P. flexuosa, P. alba and P. nigra). Due to the fact that these species make fertile hybrids, this corridor has an enormous diversity. The mother’s allowed the differentiation of five morphologic groups, which from the point of view of classic taxonomy have been classified in 16 taxa. Only groups 3 and 4 presented intermediate characteristics. The morphologic study of the descendants showed that the regrouping of the intermediate groups had a high error rate. This fact reaffirms the condition of intermediate groups. The canonical correlation analysis between the morphologic variables of the mothers and the seedlings revealed that each morphologic group had its own association of canonical variables between mothers and their seedlings, and that the variability observed in the set of the mothers and their seedlings follows a certain order. The enormous existing morphologic diversity in the Prosopis populations of the semi-arid Chaco of the north of Cordoba and southeast of Santiago del Estero was ordered in five morphologic groups. The descendant’s morphologic studies confirmed the existence of the defined morphologic-genetic groups.
A Conjecture on the Origin of Gravity

In this paper, we argue that a certain kind of discreteness of space-time may imply the existence of gravity as a geometric property of space-time described by general relativity (GR). In particular, the dynamical relationship between matter and space-time holds true not only for macroscopic objects, but also for microscopic particles. This argument provides a possible basis for Einstein's theory of gravity. Moreover, the Einstein gravitational constant in GR can be determined by the minimum intervals of discrete space-time. Lastly, we note that this new analysis may have some further implications for a complete theory of quantum gravity. NeuroQuantology | September 2013 | Volume 11 | Issue 3 | Page 405-409
EFFECT OF CONVERSION OF FOREST LAND TO THE TEA GARDENS ON THE ORGANIC CARBON NITROGEN AND PHOSPHORUS IN THE SOIL (CASE STUDY: NORTH OF IRAN)

Conversion of forest land to the tea gardensis one of the important human interferences in natural ecosystems, which is effective on ecosystem processes particularly soil. In order to effect the conversion of forest land to the tea garden, on some physical and chemical properties of the soil (nitrogen, organic carbon, phosphorus, carbon to nitrogen ratio, carbon to phosphorus ratio), Series 2 Gamble in the area of watershed 26 forests were selected. The systematic random sampling method for soil and 0 to 30 cm depth was used. A total of 40 soil samples (20 samples for each region) to measure soil parameters were taken and transferred to the laboratory. After normalization of the data, by using Kolmogorov-Smirnov method, using the software SPSS 18, in order to evaluate and compare the average data related to all parameters considered for the soil in two fields of forest and tea garden, the Non-paired t test was used. The results showed that, Carbon to nitrogen ratio, and the ratio of carbon to soil phosphorus in forested area is more than tea gardens area, and on the contrary, the percentage of organic carbon, nitrogen and phosphorus content in tea garden soil is more than forested areas, which it shows increasing soil quality due to conversion of forest land to the tea gardens in the forested areas destroyed.
Learning Strategies Predicting the Perception of Social Presence of Distance Education Students

Bu arastirma uzaktan egitim ogrencileri icin oldukca onemli olan sosyal bulunusluk ve oz-duzenlemenin e-ogrenme surecinde bir biri ile iliskisini ortaya koymak amaciyla planlanmistir. Bu baglamda ogrencilerin sosyal bulunusluk algilarini yordayan ogrenme stratejileri belirlenmeye calisilmistir. Tarama modeline gore yurutulen arastirma, kullanilan veri toplama araclarindaki sorulara uygun sekilde yanitlar veren 61 ogrenciden elde edilen veriler ile gerceklestirilmistir. Verilerin toplanmasinda; gudulenme ve ogrenme stratejileri olcegi, sosyal bulunusluk olcegi ve yazarlar tarafindan gelistirilen kisisel bilgi formu kullanilmistir. Verilerin cozumlenmesinde ise; betimsel istatistikler, adimsal regresyon analizi ve iliskisiz orneklemler icin tek faktorlu varyans analizi kullanilmistir. Arastirma sonuclari ogrencilerin ortak bulunusluk algilarinin; duzenleme ve yardim isteme ile, etkileme algilarinin; duzenleme, yardim isteme ve emek yonetimi ile, kaynastirma algilarinin; yardim isteme, duzenleme ve emek yonetimi ile ve son olarak sosyal bulunusluk algilarinin ise; duzenleme, yardim isteme ve emek yonetimi ile yordanabilecegini gostermistir. Ayrica ogrencilerin sosyal bulunusluk algilari; cinsiyet, sinif ve bolum degiskenlerine gore anlamli bir farklilik gostermemistir.
Measuring the Local Twist Angle and Layer Arrangement in Van der Waals Heterostructures

The properties of Van der Waals (VdW) heterostructures are determined by the twist angle and the interface between adjacent layers as well as their polytype and stacking. Here, the use of spectroscopic low energy electron microscopy (LEEM) and micro low energy electron diffraction (µLEED) methods to measure these properties locally is described. The authors present results on a MoS2/hBN heterostructure, but the methods are applicable to other materials. Diffraction spot analysis is used to assess the benefits of using hBN as a substrate. In addition, by making use of the broken rotational symmetry of the lattice, the cleaving history of the MoS2 flake is determined, that is, which layer stems from where in the bulk.
Kuwil method for spectral clustering algorithm

The open issues and challenges that exist while using the spectral clustering algorithm (SCA) have led to its limited spread in practical life. This paper proposes to find an easier, faster and more accurate method to implement SCA that will lead to its wide use by statisticians, researchers, institutions and others. I suggest a new method called ‘Kuwil method’ for SCA on any dataset points without needing estimation or evaluation of any parameters or the use of linear algebra, not even the k_mean algorithm. The main aim is to apply an algorithm that relies on distance laws among points only. The algorithm by the Kuwil method has been applied a number of times on real data from the warehouse European Economic Association (http://ec.europa.eu/eurostat/data/database) and on unreal data. The results were highly efficient in terms of time, effort and simplification. It eliminates the problem of parameters and increases the effectiveness to give static results obtained from the first execution. No errors were seen from functions in the MATLAB language such as eigenvalues, eigenvector and k_mean.
Growth of Electoral Fraud in Non-Democracies: The Role of Uncertainty

Electoral fraud has become an integral part of electoral competition both in established democracies and less-than-democratic regimes. In this paper I study electoral fraud in the non-democratic setting. First, I present evidence of fraud sustainability and growth over the lifetime of non-democratic regimes in post-Soviet and Sub-Saharan countries. Second, I provide a theoretical model that explains the observed tendency of growing fraud. Specifically, in a probabilistic voting model of electoral competition with falsifications, a corrupt incumbent faces two types of uncertainty: uncertainty about voters’ attitude towards fraud and uncertainty about his true support, captured by a purely random component in the voters’ utility over candidates. The model predicts that when uncertainty is sufficiently large, higher uncertainty about voters’ fraud intolerance provides weaker incentives to commit fraud. Over time the incumbent becomes more certain about voters’ reaction to fraud because of learning through Bayesian updating and, thus, as the deterrent role of fraud intolerance uncertainty declines, the incentives to commit fraud become stronger, providing a growing fraud profile.