Miracle-dz/UniFAR-FTUs huggingface dataset:
A ug 2 01 9 Magnetic phase transitions of insulating spin-orbit coupled Bose atoms in one-dimensional optical lattices

We consider the insulating spin-orbit coupled Bose atoms confined within one-dimensional optical lattices and explore their ground-state magnetic phase transitions. Under strong interactions, the charge degrees of atoms are frozen and the system can be described by an anisotropic XXZ Heisenberg chain with Dzyaloshinskii-Moriya interaction and transverse field. We apply the matrix product state method to obtain low-energy states and analyze the lowest energy gaps and the ground-state magnetization and correlations. We find when the transverse field is absent, the ground state is a gapped ferromagnetic phase with long-range correlation in the z-direction if the interspin s-wave interacting strength is stronger than that of the intraspin one, otherwise it is a gapless Luttinger liquid (LL) phase with algebraic decaying correlation. When the transverse field is turned on, the gapless LL phase is broken, there emerges a long-range correlated phase with ferromagnetic, antiferromagnetic or spiral order, which depends on the DM interaction strength. We believe our study provides a complete understanding of the interplay between SOC and quantum magnetism of spinor atoms in optical lattices.
Golay-Littlewood Problem

Identifying binary sequences {} whose autocorrelations {} are jointly as small as possible, for fixed , is important for engineering design purposes. The “best” sequences are those with the largest merit factor  . As an example, the sequence 1−1 1−1 1 1−1−1 1 1 1 1 1 has the largest  value 16912 = 140833 among all such with  = 12. As another example, the sequence 1−1 1 1−1 1 1 1−1−1−1 has the largest  value 12110 = 121 among all such with  = 10. No other merit factor exceeding 10 is known for any ; a proof that 16912 and 12110 are the maximum possible values for  is still open.
EFFICIENCY WITH ENDOGENOUS POPULATION GROWTH BY MIKHAIL GOLOSOV,

In this paper, we generalize the notion of Pareto efficiency to make it applicable to environments with endogenous populations. Two efficiency concepts are proposed: Pefficiency and A-efficiency. The two concepts differ in how they treat potential agents that are not born. We show that these concepts are closely related to the notion of Pareto efficiency when fertility is exogenous. We prove a version of the first welfare theorem for Barro–Becker type fertility choice models and discuss how this result can be generalized. Finally, we study examples of equilibrium settings in which fertility decisions are not efficient, and we classify them into settings where inefficiencies arise inside the family and settings where they arise across families.
Permasalahan optimasi sering digunakan untuk mendapatkan suatu solusi yang ideal atau optimal dari permasalahan yang bersifat linier atau nonlinier. Pada pemrograman nonlinier mempunyai area yang lebih luas untuk dilakukan suatu penelitian, mengingat model- model nonlinier seringkali memiliki bentuk

The basis concept of penalty function at the optimum solving problem is changing the constrained problems to the unsconstrained problems by adding a penalty parameter to the objective function of the problems. The addition of penalty parameter will result in increasing the objective function as the limitation is approached. This research conducts an application of solving problem on nonlinear programmer (one of solving problems form) without function penalty inside. The penalty function chosen is Barrier Function, with its variants. Then, this research also conducts an analysis to the solving problems of nonlinear programmer. The research result shows that application function of Barrier Adaptive which is combined with Interior-Point Algorithm has a better result and time computation than other Barrier functions.
Larval Ascaris suum migration and diagnostic value in pigs

Study focused on diagnostic alternatives of Ascaris suum infection in 162 pigs in slaughterhouse. The range and infestation intensities of Ascaris suum infection depend on age, period and method of examination. Coproscopic examinations from 162 samples showed 124 of them (76.54%) positive for Ascaris suum eggs. Coproscopic examinations resulted the most efficient and offer the possibility of epidemiological estimates. From the samples were found with injuries as a result of migration process 49 pigs or 30.24% of the sample surveyed. During the macroscopic examination of the intestine of pigs were found with the adult parasite in 78 heads or 48.14% of the examined pigs. This value was about 20% lower than the value of coproscopic examination, but about 20% higher than the value of the examination of the milk liver spots. During of the macroscopic and microscopic examination in lungs were found with signs of pneumonia and parasitic larva migration in the lung parenchyma and the bronchi, 58 heads or 35,8% of the examined pig lungs. In pigs when parasitic pneumonia detected, the nose leaks were examined for the presence and number of larvae. From 162 nose tampons examined resulted positive for the presence of Ascaris suum migration larvae 26 pigs (16.04%) from the total of examined heads. Post-mortem examinations in slaughterhouses at pigs resulted efficient, low cost and provide sufficient data for Ascaris suum infection.
1 . 1 QUANTITATIVE SEMANTICS IN 18 TH CENTURY SWEDEN

4 In 1743, a collection of 90 hymns, entitled Songs of Zion, was published in Sweden, This publication soon became the storm center of a religious controversy which is of particular interest to the social scientist because in the course of it there were foreshadowed many of the methods of content analysis, which have found systematic expression only during the past decades. In fact, if not in name, participants in this debate were concerned with many of the problems, which concern today’s content analyst: the identification of key symbols, the division of content into favorable, unfavorable and neutral categories, the coding of values, and other related problems. Indeed, the controversy revolved around the formula, which has become so familiar to students of communication: Who said what to whom, how and with what effect? The Songs of Zion appeared at a time when the powerful State Church (Lutheran) was struggling against German pietistic influences. Pietism, stressing faith rather than ritual, was making substantial inroads among the orthodox in Sweden, when the influences of still another German religious movement began to be felt. This movement was that of the Moravian Brethren, led by the Count von Zinzendorf. At first, the orthodox Lutheran clergy welcomed the Moravian ideas, believing that they might provide a spiritual means of bringing the pietistic dissenters back into the fold. It was not long, however, before the State Church recognized the Moravians as enemies rather than allies. Publication of the first edition of the Songs of Zion seems to have occurred without appreciable controversy. The Swedish State Censor found the hymns to be somewhat odd, and neither beautiful nor superior to those in the Hymnal of the Established Church, but since they were already being used in manuscript form he allowed them to be printed. Nobody seemed disturbed that the authors of these hymns were unknown.
Semantic Object Recognition in Digital Images

In a digital image, each object is composed of segments with different shapes and colors. In order to recognize an object, e.g. a car or a book, it is necessary to find out, which segments are typical for this object and in which neighborhood of other segments they occur. If a typical segment in a characteristic neighborhood is found, this segment is part of the object to be recognized or the object itself. Typical adjacent segments for a certain object define the whole object in the image. Following this idea, we introduce a procedure that learns typical segment configurations for a given object class by training with example images of the desired object. A hierarchical composition of segment clusters enables model building, taking into account the spatial relations of the segments in the image. The procedure employs methods from machine learning, namely clustering and decision trees, and from computer vision, e.g. image pyramid segmentation and contour signatures.
Trustful Mechanism for Sharing the Cost of Multicast Transmissions

The issue of sharing the cost of multicast transmissions was considered before, and two systems, Marginal Cost (MC) and Shapley Value (SH), were proposed to unravel it. Albeit them two are strategyproof systems, the disseminated conventions actualizing them are helpless to control via independent hubs. We propose a conveyed Shapley Value instrument in which the taking part hubs don't have motivating forces to go amiss from the component details. We demonstrate that the proposed component is a dedicated execution of the Shapley Value instrument. We tentatively explore the execution of the current and the proposed cost-sharing systems by actualizing and conveying them on PlanetLab. We think about the execution time of MC and SH systems for the Tamper-Proof and Autonomous Node models. We additionally concentrate the merging and versatility of the instruments by fluctuating the quantity of hubs and the quantity of clients per hub. We demonstrate that the MC systems produce a littler income contrasted with the SH components, and in this way, they are not appealing to the substance supplier. We likewise demonstrate that expanding the quantity of clients per hub is advantageous for the frameworks actualizing the SH components from both computational and financial points of view.
THE UNIVERSITY OF CHICAGO EXAMPLES OF REPRESENTATION STABILITY PHENOMENA A DISSERTATION SUBMITTED TO THE FACULTY OF THE DIVISION OF THE PHYSICAL SCIENCES IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF MATHEMATICS BY RITA JIMÉNEZ ROLLAND

In this thesis we consider some sequences of groups or spaces {Xn}n∈N and are interested in how the degree i cohomology H(Xn; Q) changes as the parameter n increases. Our main examples are: • the cohomology of the moduli space of n-pointed curves of genus g, • the cohomology of the pure mapping class group of surfaces and some manifolds of higher dimension, and • the cohomology of classifying spaces of some diffeomorphism groups. We do not expect that our sequences satisfy (co)homological stability, meaning that the (co)homology groups are isomorphic for large n, because of existence of nontrivial symmetries. We prove, in Chapter 3, that in each case we have a sequence of Sn-representations which is uniformly representation stable in the sense of Church–Farb. This condition puts strong constraints on the rate of growth of the representations and the patterns of irreducible Snrepresentations occurring. In particular this result applied to the trivial Sn-representation implies rational “puncture homological stability” for the mapping class group Modg . In Chapter 4 we apply the theory of finitely generated FI-modules developed by Church, Ellenberg and Farb to our examples. We introduce the notion of FI[G]-module and use it to strengthen and give new context to results on representation stability discussed in Chapter 3. With this approach we conclude that for each sequence of representations the characters are polynomial and find bounds on their degree. As a consequence we obtain that the Betti numbers of these spaces and groups are polynomial. Finally, rational homological stability of certain wreath products is obtained.
A Sliding Mode Control Law for Epipolar Visual Servoing of Differential-Drive Robots

In this paper, a robust control technique (Sliding Mode Control) is proposed to be used in order to perform visual servoing for differential-drive mobile robots using the classical teach-by-showing strategy. We propose a commuted sliding mode control law that exploits the epipolar geometry. The major contribution of the paper is the design of a control law that solves the problem of passing through a singularity induced by the epipoles maintaining bounded inputs. Moreover, the designed control is able to drive the robot to the target even when it just starts on the singularity. The proposed approach does not need a precise camera calibration due to the robustness of the control system under uncertainty in parameters. It also ensures entire correction of both orientation and lateral error even with noise in the image. The effectiveness of our approach is tested via simulations.
Blind spot monitoring at night-time using rear-view camera

The blind spot monitoring (BSM) is one of the key functions of advanced driver assistance system (ADAS). In this paper, we propose vision-based blind spot detection and tracking algorithm which is applicable at night-time. The feature of highly bright blobs due to the headlights of behind vehicle is employed for the detection of vehicles in blind spot area, because the appearance-based approach that can be used at daytime is not any more appropriate. We calculate the motion vectors of detected blobs to find an approaching vehicle and make headlight grouping to estimate its position by use of the projection map. We can successfully generate an alarm signal by detection and tracking the overtaking vehicle in blind spot area at night-time.
THE POTENTIAL OF CAROTENOIDS FROM MARINE TROPICAL MICROALGAE IN THE HEALING PROCESS OF GASTRITIS

Health professionals have consistently advocated the daily consumption of five portions of fruit and vegetables as a means of protecting against the pathogenesis of degenerative diseases including coronary heart disease, cancers and other free radical-mediated conditions (Kritchevsky et al., 1999). Fruit and vegetables contain a wide range of compounds including the antioxidant vitamins C and E, minerals, phenolics and carotenoids. Carotenoids are natural pigments, providing orange, yellow, red and purple colours throughout the natural world. These pigments are produced by all higher plants, along with some bacteria and algae (Britton et al., 1995). They are derived from the terpenoid family and are biosynthetically related to other secondary metabolites such as tocopherols and ubiquinones. Within plant tissue they are associated with photosynthetic membranes and are involved in photo-protection and light energy assimilation (Britton et al., 1995).
Detecting Masquerades with Principal Component Analysis Based on Cross Frequency Weights

In this paper, several cross frequency weights are used for extracting attributes of audit events. Principal Component Analysis (PCA) are then employed to discover the interrelationships and dependencies among features in a large number of variables and also to reduce the high dimensionality of these variables. Command data are used in the experiments for masquerade detection and the results demonstrate the effectiveness and efficiency of the method.
Year 13 students’ reasoning from an eikosogram: an exploratory study

Education research on probability frequently raises concerns about the lack of effective strategies for teaching and learning probability. Using an interactive eikosogram, a visual representation of a two-way table of information, we explore Year 13 students’ reasoning, interaction and comprehension behaviours associated with the display. In this paper we focus on four students as they explored data on their own. Although the students had difficulties posing investigative questions and reasoning from the eikosogram, we conjecture that the eikosogram may have the potential to assist proportional reasoning and the verbalization of simple, conditional and joint probability stories from data. To elucidate the reasoning that can be stimulated when students interact with an eikosogram we present an eikosogram graphicacy framework.
Fast neighbor search with keywords

Keyword-based search in text-rich multi-dimensional datasets facilitates many novel applications and tools. In this paper, we consider objects that are tagged with keywords and are embedded in a vector space. For these datasets, we study queries that ask for the tightest groups of points satisfying a given set of keywords. We propose a novel method called ProMiSH (Projection and Multi Scale Hashing) that uses random projection and hash-based index structures, and achieves high scalability and speedup. We present an exact and an approximate version of the algorithm. Our experimental results on real and synthetic datasets show that ProMiSH has up to 60 times of speedup over state-of-the-art tree-based techniques.
CLEF 2019 : Overview of the Replicability and Reproducibility Tasks

Reproducibility has become increasingly important for many research areas, among those IR is not an exception and has started to be concerned with reproducibility and its impact on research results. This paper describes our second attempt to propose a lab on reproducibility named CENTRE, held during CLEF 2019. The aim of CENTRE is to run both a replicability and reproducibility challenge across all the major IR evaluation campaigns and to provide the IR community with a venue where previous research results can be explored and discussed. This paper reports the participant results and preliminary considerations on the second edition of CENTRE@CLEF 2019.
Factors influencing the long-term unemployment level and development in the European Union

The paper deals with the factors influencing the long-term unemployment rate in the European Union countries in 2001-2010. The applied factors were selected in compliance with the economics of labour market theory and cover three areas: economic environment (GDP growth in market prices, inflation), tax area (tax wedge), social benefit (net replacement ratio) and labour market flexibility (fixedterm contracts, part-time contracts). The panel model estimation has been implemented through a panel regression analysis for two homogenous groups (EU-15 countries and „new countries“ – EU-12). The period preceding an economic crisis and a period of economic crisis have been investigated. The results show that the labour market flexibility influences the long-term unemployment rate in the strongest negative way, then there is evident a positive impact of the tax wedge followed by the macroeconomic environment impact. The negative impact of economic growth operates in these groups with the same intensity, the tax burden in the EU15 countries is higher and vice versa with an increase in the share of part-time workers long-term unemployment decreases markedly in the EU12. The same positive economic growth will contribute to a deeper decrease of long-term unemployment. In the crisis period the positive impact of tax burden is reduced and we also monitor the increasing impact of the proportion of part-time jobs.
Patterns in the Innovative Activities of Ghanaian Manufacturing and Services Firms

Innovative activities of firms differ with respect to their orientation, intensity, use of internal and external knowledge as well as the factors that necessitated the innovation. Using firm-level data for Ghana, an attempt was made to describe patterns in the innovative activities of Ghanaian Manufacturing and Services firms based on a cluster analysis of some innovation measures. The main aim was to establish which innovative activities were widespread, identify which types of firms tend to be more innovative and ascertain the basic determinants of innovation along any established pattern. Without a proper understanding of these issues, policy makers may easily be misled or made to divert relevant innovation policy away from the needs of firms that needed them the most. The exercise yielded three innovation clusters (patterns), which were characterised by some firm specific-information. One main finding of the study is the establishment of low correspondence between firms that shared similar innovation characteristics (clusters) and sectors. This suggests individual firms seem to dispose of a certain degree of freedom in selecting economically viable innovation strategies even under similar economic and/or technological conditions. More importantly, results from the study suggests that some underlying firm-specific microeconomic processes overcome pressures in the technological nvironment towards homogenous behaviour by firms, even in the same sector.
Design and Develop Semantic Textual Document Clustering Model

The utilization of textual documents is spontaneously increasing over the internet, email, web pages, reports, journals, articles and they stored in the electronic database format. It is challenging to find and access these documents without proper classification mechanisms. To overcome such difficulties we proposed a semantic document clustering model and develop this model. The document pre-processing steps, semantic information from WordNet help us to be bioavailable the semantic relation from raw text. By reminding the limitation of traditional clustering algorithms on the natural language, we consider semantic clustering by COBWEB conceptual clustering. Clustering quality and high accuracy were one of the most important aims of our research, and we chose F-Measure evaluation for ensuring the purity of clustering. However, there still exist many challenges, like the word, high spatial property, extracting core linguistics from texts, and assignment adequate description for the generated clusters. By the help of Word Net database, we eliminate those issues. In this research paper, there have a proposed framework and describe our development evaluation with evaluation.
Vulnerabilities in SaaS Layer of Cloud Computing

Cloud computing services are being leveraged to a great extent in the industry today, extensive research is being conducted by multi-national companies on its integration into their infrastructure, and services are being implemented to as to make data and applications available to customers from anywhere around the world with access to the internet. However with the rise in popularity of this service, customers and clients have raised concerns on the security, authenticity, and availability of services, which they are paying for either individually or for an organization. These concerns further intensify when services are made available in the public cloud infrastructure, using the Software as a Service (SaaS) layer of cloud computing. The public cloud infrastructure is designed such that authorized access is not limited to a closed group or organization but to the general public, which may include malicious users. Software applications in the SaaS layer in this infrastructure are at a greater risk of exploitation due to its ease of access and availability of the service. This research aims to identify the vulnerabilities in the SaaS layer of the cloud model, which will help to not only raise awareness of the current vulnerabilities existent in the cloud model, but will also help to identify future risks which could compromise user data.
Chapter 5 Animal abundances across state and community forests of Jaintia Hills Introduction

A large number of vertebrate species are at the greatest risk today primarily because of deforestation (Geist & Lambin, 2002), poaching and local hunting (Wright & Duber, 2001; Wright, 2003). Local hunting is one of the main drivers of biodiversity loss in tropical forests (Milner-Gulland & Bennett, 2003) and in synergy with other disturbances such as logging and habitat loss can have disastrous impacts on species conservation (Laurance & Useche, 2009). Prolonged local hunting pressures, even at seemingly low intensities, can trigger species extinction rates (Corlett, 2007) rendering even undisturbed, primary forest habitats ‘empty’ (Redford, 1992; Bodmer et al., 1997).