Miracle-dz/UniFAR-FTUs huggingface dataset:
An individual–orientated model of the emergence of despotic and egalitarian societies

Single behavioural differences between egalitarian and despotic animal societies are often assumed to reflect specific adaptations. However, in the present paper, I will show in an individual–orientated model, how many behavioural traits of egalitarian and despotic virtual societies arise as emergent characteristics. The artificial entities live in a homogeneous world and only aggregate, and upon meeting one another and may perform dominance interactions in which the effects of winning and losing are self–reinforcing. The behaviour of these entities is studied in a similar way to that of real animals. It will be shown that by varying the intensity of aggression only, one may switch from egalitarian to despotic virtual societies. Differences between the two types of society appear to correspond closely to those between despotic and egalitarian macaque species in the real world. In addition, artificial despotic societies show a clearer spatial centrality of dominants and, counter–intuitively, more rank overlap between the sexes than the egalitarian ones. Because of the correspondence with patterns in real animals, the model makes it worthwhile comparing despotic and egalitarian species for socio–spatial structure and rank overlap too. Furthermore, it presents us with parsimonious hypotheses which can be tested in real animals for patterns of aggression, spatial structure and the distribution of social positive and sexual behaviour.
Empirical Study on the Urbanization Promoting the Chinese Economic Growth

This paper select the section data of China's 31 provinces, autonomous regions and municipalities directly under the Central Government in the year of 2011, use the Eviews6.0 metrology software, set up the production function model, and change it into the econometric model to empirical test theoretical model of the urbanization development to promote economic growth and its related the theoretical conclusions. At significant level of 1%, the regression parameters of the urbanization development and capital and labor are all significant not 0 ,and at the significance level 1%, the urbanization rate increasing 1 percentage, the output GDP increasing 0.66 percent, while the output elasticity of capital and labor are 0.71 and 0.37 respectively.
Hybrid Transactional and Analytical Processing Databases: A Systematic Literature Review

Hybrid Transactional and Analytical Processing databases (HTAP, OLxP) are an emerging sector of databases combining Online Transactional Processing and Online Analytical Processing in the same system. Such databases yield many advantages like the reduction of the total cost of ownership or the elimination of redundant data sets for analytical and live data. Therefore, both Gartner and Forrester Research see disruptive potential in HTAP databases. While following a common goal, the database architectures of HTAP databases are quite diverse. The solutions range from scaled-up single server systems, using Multi Version Concurrency Control to keep their data consistent while at the same time executing thousands of queries, to scaledout clusters of many servers using last writer wins approaches to allow even faster transactional processing. The development of HTAP databases resulted in various advances in the database sector like the creation of new index and data structures or improvements of existing concurrency control implementations. This paper provides a comprehensive summary of these implementations, giving an overview of the last decade of research on the emerging sector of HTAP Processing databases and discussing fundamental involved technologies. Keywords—Hybrid Transactional Analytical Processing; HTAP; Database; Literature Study; OLxP.
Studies on Bioefficacy of Aqueous Plant Extracts against Pectobacterium carotovorum causing Black Leg and Soft Rot of Potato

Potato (Solanum tuberosum) is considered as the most potential and nutritionally superior crop for fighting against hunger in both developing and under developed countries. Globally potato diseases mainly revealed the presence of 30 fungal, 7 bacterial and 36 viral diseases causing loss individually or collectively to the crop. The blackleg and soft rot cased by Pectobacterium carotovorum is an important disease of potato of the country, damaging the crop during pre and post emergence stage, growing period, harvest and post harvest operations like storage, transport and also at consumer level. The disease was found to be severe in immaturely harvested and peeled tubers while transported under poorly ventilated condition and under normal package of practices, i.e. 4% in north western International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 10 (2020) Journal homepage: http://www.ijcmas. com
Effect of Different Sources of Nutrient and NPK Levels on Growth, Yield Attributes and Productivity of Wheat (Triticum aestivum) in a Vertisol

Wheat (Triticum aestivum) is one of the most important cereal crop of India followed by rice. In India wheat is grown in 30.41 mha with annual production of 92.29 MT and productivity of 3034 kg ha -1 (Anonymous 2018). In Madhya Pradesh, is grown in an area of 5.91 mha with production of 17.69 MT and productivity of 2993 kg ha -1 (Anonymous 2015-16). The food grain requirement in India is gradually increasing every year and it may reach around 350 MT due to increasing population pressure expected to 1.8 billion up to 2050 (Khatkar et al., 2016).
Hydrological modelling in a changing world

Changing hydrological conditions due to climate, land use and infrastructure pose significant ongoing challenges to the hydrological research and water management communities. While, traditionally, hydrological models have assumed stationary conditions, there has been much progress since 2005 on model parameter estimation under unknown or changed conditions and on techniques for modelling in those conditions. There is an analogy between extrapolation in space (termed Prediction in Ungauged Basins, PUB), and extrapolation in time (termed Prediction in Ungauged Climates, PUC) that can be exploited for estimating model parameters. Methods for modelling changing hydrological conditions need to progress beyond the current scenario approach, which is reliant upon precalibrated models. Top-down methods and analysis of spatial gradients of a variable of interest, instead of temporal gradients (a method termed ‘Trading space for time’) show much promise for validating more complex model projections. Understanding hydrological processes and how they respond to change, along with quantification of parameter estimation and modelling process uncertainty will continue to be active areas of research within hydrology. Contributions from these areas will not only help inform future climate change impact studies about what will change and by how much, but also provide insight into why any changes may occur, what changes we are able to predict in a realistic manner, and what changes are beyond the current predictability of hydrological systems.
Bacterial taxa associated with adherence to Mediterranean diet in a Spanish population

: The Mediterranean diet (MD) is recognised as one of the healthiest diets worldwide and is associated with the prevention of cardiovascular and metabolic diseases, among others. Dietary habits are considered one of the strongest modulators of the gut microbiota, which seems to play a significant role in the health and disease of the host. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and habitual dietary intake in 360 Spanish adults of the Obekit cohort (normal weight, overweight and obese subjects). Dietary intake and adherence to the MD tests together with faecal samples were collected from each subject. Faecal 16S rRNA sequencing was performed and checked against the dietary habits. MetagenomeSeq was the statistical tool applied to analyse at the species taxonomic level. Results from this study confirm that a strong adherence to the MD increases the population of some beneficial bacteria, improving microbiota status towards a healthier pattern. Bifidobacterium animalis is the species with the strongest association with the MD. One of the highlights is the positive association between several SCFA-producing bacteria and high adherence to the MD. In conclusion, this study shows that MD, fibre, legumes, vegetables, fruit and nuts intakes are associated with an increase in butyrate-producing taxa such as Roseburia faecis, Ruminococcus bromii and Oscillospira (Flavonifractor) plautii .
The good, the bad and the interesting: Integrating a third-party provider into ALL services at a regional university

Supporting students in their learning while transitioning into university has always been a key responsibility of academic language and learning (ALL) professionals. However, the changing demands for ALL support in the contemporary tertiary environment has required a shift in practice. Over the last eight years, one regional university has redefined the role of learning advisors by taking a whole of institution approach to ALL development and pursuing a multilayered model for practice that builds staff capacity and develops confident, agentic learners. As part of a diversified suite of activities, the university has engaged the services of a third-party provider to provide after-hours, online tutorial support to students. This paper presents findings from a qualitative study conducted by the university in 2018, which evaluates the impact of the diversification of ALL services on the practices of ALL professionals, including the benefits and challenges of using third-party providers. The study revealed that while there are some benefits, learning advisors and academic staff expressed reservations about the provider’s effectiveness and usefulness. Findings suggest that students need clarification about the different feedback services available to them and guidance on seeking, interpreting, and applying feedback. The study highlights the need to carefully plan the integration of third-party services within a broader framework of feedback processes and offers insights into how ALL practitioners can best guide students and staff to appropriately use third-party services while avoiding the pitfalls.
Training general-purpose audio tagging networks with noisy labels and iterative self-verification

This paper describes our submission to the first Freesound generalpurpose audio tagging challenge carried out within the DCASE 2018 challenge. Our proposal is based on a fully convolutional neural network that predicts one out of 41 possible audio class labels when given an audio spectrogram excerpt as an input. What makes this classification dataset and the task in general special, is the fact that only 3,700 of the 9,500 provided training examples are delivered with manually verified ground truth labels. The remaining non-verified observations are expected to contain a substantial amount of label noise (up to 30-35% in the “worst” categories). We propose to address this issue by a simple, iterative self-verification process, which gradually shifts unverified labels into the verified, trusted training set. The decision criterion for self-verifying a training example is the prediction consensus of a previous snapshot of the network on multiple short sliding window excerpts of the training example at hand. On the unseen test data, an ensemble of three networks trained with this self-verification approach achieves a mean average precision (MAP@3) of 0.951. This is the second best out of 558 submissions to the corresponding Kaggle challenge.
Exact solution and the multidimensional Godunov scheme for the acoustic equations

The acoustic equations derived as a linearization of the Euler equations are a valuable system for studies of multi-dimensional solutions. Additionally they possess a low Mach number limit analogous to that of the Euler equations. Aiming at understanding the behaviour of the multi-dimensional Godunov scheme in this limit, first the exact solution of the corresponding Cauchy problem in three spatial dimensions is derived. The appearance of logarithmic singularities in the exact solution of the 4-quadrant Riemann Problem in two dimensions is discussed. The solution formulae are then used to obtain the multidimensional Godunov finite volume scheme in two dimensions. It is shown to be superior to the dimensionally split upwind/Roe scheme concerning its domain of stability and ability to resolve multi-dimensional Riemann problems. It is shown experimentally and theoretically that despite taking into account multi-dimensional information it is, however, not able to resolve the low Mach number limit.
3.09 Nanostructures and Surface-Enhanced Raman Spectroscopy

This chapter was originally published in Comprehensive Nanoscience and Technology, published by Elsevier, and the attached copy is provided by Elsevier for the author’s benefit and for the benefit of the author’s institution, for non-commercial research and educational use including without limitation use in instruction at your institution, sending it to specific colleagues who you know, and providing a copy to your institution’s administrator.
Exploring Users’ Self-Disclosure Intention on Social Networking Applying Novel Soft Computing Theories

In recent years, users have increasingly focused on the privacy of social networking sites (SNS); users have reduced their self-disclosure intention. To attract users, SNS rely on active platforms that collect accurate user information, even though that information is supposed to be private. SNS marketers must understand the key elements for sustainable operation. This study aims to understand the influence of motivation (extrinsic and intrinsic) and self-disclosure on SNS through soft computing theories. First, based on a survey of 1108 users of SNS, this study used a dominance-based rough set approach to determine decision rules for self-disclosure intention on SNS. In addition, based on 11 social networking industry experts’ perspectives, this study validated the influence between the motivation attributes by using Decision-Making Trial and Evaluation Laboratory (DEMATEL). In this paper, the decision rules of users’ self-disclosure preference are presented, and the influences between motivation attributes are graphically depicted as a flow network graph. These findings can assist in addressing real-world decision problems, and can aid SNS marketers in anticipating, evaluating, and acting in accord with the self-disclosure motivations of SNS users. In this paper, practical and research implications are offered.
Biased towards food

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Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title Dynamic Task Selection in Aviation Training Permalink

While the aviation domain is exemplary for its complex cognitive skills, the pace of automation steadily increases making it crucial to train people as effectively as possible. Over the last three decades training programs have evolved a strong focus on personalized dynamic whole-tasks. Adapting training to the individual student’s progress is believed to be strongly related to increased training efficiency (Salden, Paas, & van Merriënboer, 2006). Four studies investigated a variety of personalized training methods. Results confirm the hypothesis that personalized instruction can have beneficial effects for the training of complex cognitive skills.
Logical-Depth-Oriented Reversible Logic Synthesis

Boolean reversible logic has applications in various research areas including quantum computing. In this paper, a synthesis method for reversible logic is proposed which concentrates on two objectives, namely logical depth and quantum cost. To this end, the input specification is represented in a cycle form, and a set of three distinct subsets of input cycles are distinguished for parallel execution where the first set is executed on the first n input qubits and the remaining two sets are applied on the set of 2n ancillae. The final results are constructed on the main qubits. For each set, the cycle-based synthesis method is applied equipped with negative-control gates and parallel gate execution. Experimental results on the attempted benchmarks demonstrate more than 50% improvement in the logical depth with less than 2% increase in the quantum cost on average.
The potential effects of the ECCAS Free Trade Area on Trade Flows

Analyzing some trade indicators and estimating a gravity model, this paper assesses the potential effects of an effective implementation of the ECCAS FTA. Launched since January 2004, the ECCAS FTA is not yet established: the main reforms that should be undertaken by the various members are still awaited. The results show that the potential for increasing intra-ECCAS trade, following the FTA, is limited by the narrow range of goods produced and exported by members; the fact that members have comparative advantages for similar products in which they are not important consumers; and the low complementarity in their trade profiles. To accelerate industrial development through a pooling of productive resources and capacities could improve the complementarity of the production structures in the sub-region and thus, increase the possibilities of intra-industry trade, key of intra-trade growth in model FTA.
FOR DISCOVERY OF NONSEQUENTIAL PROTEIN STRUCTURE SIMILARITIES

An increasing number of protein structures are becoming available that either have no known function or whose functional mechanism is unknown or incomplete. Using experimental methods alone to explore these proteins in order to determine their functional mechanism is unfeasible. For this reason, much research has been put into computational methods for predicting the function of proteins [5,14,31,34,44,53]. One such computational method is functional inference by homology, where annotations from a protein with known function are transferred onto another protein on the basis of sequence or structural similarities. Protein sequence comparisons have been used as a straightforward method for functional inheritance. If two proteins have a high level of sequence identity, frequently the two proteins have the same or related biological functions. This observation has been used as a basis for transferring annotations from a protein that is well characterized to a protein with unknown function when the two proteins have high sequence similarity [3,4,45]. Frequently, only the protein residues that are near the functional region of the protein are under evolutionary pressure for conservation. Therefore, the global sequence similarity may be relatively low while local regions within the two sequences maintain a higher level of sequence similarity. In this case, probabilistic models such as profiles have been constructed using only the local regions of high sequence similarity [3,32,28].
Calcium as a Plant Nutrient

Calcium (Ca) is an essential plant nutrient responsible for the integrity of cells and plant structure, yet it is generally neglected, because it is available in plenty in most cultivated soils. It is therefore not applied as a fertilizer to crops except in groundnut. In acid soils, where it is limiting, it is applied in large amounts as a soil amendment as lime. In sodic soil, where excess of Na creates problems in crop production Ca is applied as gypsum, another soil amendment. When applied in large amounts as lime or gypsum, Ca nutrition is already taken care of and thus there is no need of annual application as a fertilizer. Nevertheless its importance as a plant nutrient cannot be ignored.
Basic properties of magnetohydrodynamic turbulence in the inertial range

We revisit the issue of the spectral slope of magnetohydrodynamic (MHD) turbulence in the inertial range and argue that the numerics favour a Goldreich–Sridhar −5/3 slope rather than a −3/2 slope. We also perform precision measurements of the anisotropy of MHD turbulence and determine the anisotropy constant CA= 0.34 of Alfvenic turbulence. Together with the previously measured Kolmogorov constant CK= 4.2, or 3.3 for a purely Alfvenic case, it constitutes a full description of the MHD cascade in terms of spectral quantities, which is of high practical value for astrophysics.
A Closer Look at the Student Achievement Trends in the District of Columbia between 2006-07 and 2012-13. CALDER Working Paper No. 119.

In this paper, we present a closer look at the student achievement trends in the District of Columbia between 2006-07 and 2012-13. We have three main conclusions. First, we find that overall, math scores in the District have improved. The improvements in reading scores during this time frame, however, were primarily limited to the first year after the PERAA implementation. While almost all student subgroups have experienced test score gains in math, these improvements were higher among the more affluent black and Hispanic students. Second, we find that these observed trends in math scores persist even after controlling for the cross-cohort differences in observed student characteristics. In particular, the estimates indicate that less than 10 percent of the year-to-year improvements in test scores can be attributed to the changing student composition in the District over this time frame. Finally, we show that existing students have also experienced gains in math even though the students who are new to the District’s public school system score at higher levels on standardized tests when compared to existing students.