Miracle-dz/UniFAR-FTUs huggingface dataset:
University of Groningen Tracking and regulation in the behavioral framework

Given a plant together with an exosystem generating the disturbances and the reference signals, the problem of asymptotic tracking and regulation is to find a controller such that the plant variable tracks the reference signal regardless of the disturbance acting on the system. If a controller achieves this design objective, we call it a regulator for the plant with respect to the given exosystem. In this paper, we formulate the asymptotic tracking and regulation problem in the behavioral framework, with control by interconnection. © 2011 Elsevier Ltd. All rights reserved.
Allium Cepa Juice Prevented Oxidative Stress-Mediated Metabolic Disorder Following Chronic Lead Acetate Exposure in Male Rats

Results: Exposure to LA caused significant reduction in high density lipoprotein (HDL), calcium, superoxide dismutase (SOD), catalase and glutathione (GSH) and also resulted to a significant increase in total cholesterol (TC), low density lipoprotein (LDL), triglyceride (TG), very low density lipoprotein (VLDL), lipid profile ratios, atherogenic index of plasma (AIP), sodium ions, potassium ions, chloride ions and malondialdehyde (MDA). ACJ treated rats showed a significantly reduced TC, TC/HDL, LDL/HDL and potassium and a significant increase in SOD, catalase and GSH. LA+ACJ group exhibited significantly low LDL/HDL ratio and a significantly high SOD but there was no significant change in TC, LDL, TG, VLDL, AIP, sodium, potassium, chloride, MDA, catalase and GSH.
DOES INTERNATIONAL OPENNESS AFECT PRODUCTIVITY OF LOCAL FIRMS ? EVIDENCE FROM SOUTHERN EUROPE 1

This paper examines the role of international openness on the change of firm productivity in Southeastern Europe (SEE). This is a crucial question for middle income countries. Using firmlevel data for six transition economies over the period 1994-2002, we identify whether foreign ownership and propensity to trade with more advanced countries can bring about higher learning effects. We find that (i) foreign ownership has helped at restructuring and enhancing productivity of local firms in four out of six countries, (ii) exporting to advanced markets has a larger impact on productivity growth in four countries, especially when firm’s absorptive capacity is taken into account, (iii) in contrast, exporting to the less competitive markets of exYugoslavia seems to affect negatively the productivity growth in three countries, and (iv) learning effects from importing follow a similar path than exporting. Our results suggest that trade liberalisation is not uniformly beneficial. Regional composition of trade flows and absorptive capacity of local firms matter. Trade liberalisation within the SEE region thus may not provide a substitute for a general trade liberalisation and access to the more competitive markets of OECD countries.
Implementing Spectral Methods for Multiway Sparse Cuts

Finding clusters of vertices in a graph has many applications, such as in data analysis and image processing. We investigated a particular algorithm from [5], which we call the LRTV algorithm, for solving the k-sparse cuts problem, which is related to finding clusters in graphs. We implemented the LRTV algorithm and made attempts to improve it, although we were ultimately unable to generate clear improvements. We also compared the performance of the LRTV algorithm to the graph partitioning algorithms METIS and Chaco. In this work, we observe some trends in the relative performance of the LRTV algorithm, based on general characteristics of the graphs being used. We also discuss potential issues with these experiments and suggest areas of future work for this project.
Foreign Direct Investment in Africa : What are the Key Factors of Attraction aside from Natural Resources ?

This input, essentially empirical by nature, analyses the FDI determinants in Africa independently from the already clearly identified attraction of natural resources. Do powers of anticipation as to the general prospects for these economies influence incoming flows of capital? What role is played by socio-political instability connected to the social consequences caused by conflicts? Are the processes of regionalization enhancing the appeal of countries that are going down that path? From a panel of 28 African countries, the results from estimations obtained using the Hausman-Taylor method of instrumental variables show that the impact of projections on any ongoing decision to invest in the continent is not statistically significant. Our results also show that, although negative, the direct correlation between social risk, a proxy of sociopolitical instability, and flows of foreign investment is not systematically significant. However, the fact remains that these instabilities undermine national competencies (human capital) and compound certain ills such as HIV/Aids, whose impact on foreign investment increases along a negative curve in the presence of social risk. However, the simultaneous introduction of regionalization processes into our estimations tends to lower the adverse effects of instability on certain explicative FDI variables.
The Influence of Triarchic Intelligence Model in Mathematics Intervention on the Students ’ Mathematics Performance

This study endeavors to examine the influence of the triarchic intelligence on students’ mathematics performance as embedded in academic intervention through counseling program which focuses on maximizing students’ innate abilities known as natural intelligence and compensating their weaknesses through reinforcements. Traditional reinforcement was applied to control group while experimental group underwent triarchic intervention involving analytical, creative, and practical based instructions. Students who were exposed to triarchic intervention showed significant improvements in their mathematical skills and performance. In general, triarchically based intervention was superior against traditional reinforcement.
Type-Preserving Compilation of FGJ

Parametric polymorphism has been one of the most requested language features in the Java developer community. Previous work in integrating this feature into Java has paid much attention to the compatibility with existing JVM. This extra constraint leads to either inefficiencies or compromises in type safety during the translation. We present a typepreserving encoding of Featherweight Generic Java (FGJ) in an extension of FLINT – a simple, implementable typed intermediate language used in the optimizing compiler for SML/NJ. Our encoding faithfully translates type parameterization in FGJ into polymorphic constructs in the target language, thus maintaining type safety without introducing inefficiencies like code expansion or runtime overhead of unnecessary downcasts. The formal translation from FGJ allows comprehensible type-preserving proofs, and could serve as a starting point for extending the translation to the full Generic Java.
Source Code Repository Data Extraction Parse Source Code Identify Self-Admitted Technical Debt Identifying Defects in SATD Files Identifying Defects in SATD Changes

Technical debt refers to incomplete or temporary workarounds that allow us to speed software development in the short term at the cost of paying a higher price later on. Recently, studies have shown that technical debt can be detected from source code comments, referred to as self-admitted technical debt. Researchers have examined the detection, classification and removal of self-admitted technical debt. However, to date there is no empirical evidence on the impact of self-admitted technical debt on software quality. Therefore, in this paper, we examine the relation between selfadmitted technical debt and software quality by investigating whether (i) files with self-admitted technical debt have more defects compared to files without self-admitted technical debt, (ii) whether self-admitted technical debt changes introduce future defects, and (iii) whether self-admitted technical debt-related changes tend to be more difficult. We measured the difficulty of a change using well-known measures proposed in prior work such as the amount of churn, the number of files, the number of modified modules in a change, as well as the entropy of a change. An empirical study using five open source projects, namely Hadoop, Chromium, Cassandra, Spark and Tomcat, showed that: i) there is no clear trend when it comes to defects and self-admitted technical debt, although the defectiveness of the technical debt files increases after the introduction of technical debt, ii) self-admitted technical debt changes induce less future defects than none technical debt changes, however, iii) selfadmitted technical debt changes are more difficult to perform, i.e., they are more complex. Our study indicates that although technical debt may have negative effects, its impact is not only related to defects, rather making the system more difficult to change in the future.
Detection of Texture-less Occluded Objects by Deformable Part Modals

Detection of objects in images has been a popular area of research in computer vision. Researchers have been working on the automatic detection of both fully visible and occluded objects. In this thesis work, detection of occluded objects is further examined. This work targets occluded objects which are simple in shape and do not contain complex textures. Texture-rich objects are, in general, more easily detected; but occlusion of texture-less objects is a more challenging task. In this work we focus on the texture-free occluded images of mugs and cups. This thesis examines the effectiveness of part-based detection technique for the detection of these texture-less occluded objects. We believe that this approach is more effective than traditional approaches that look for the color and edges/shape of the objects only. The difficulty arises because the extent of occlusion is not uniform and occlusion is usually caused by cluttered environments creating shadows and many unpredictable edges. These issues decrease the performance of edge and color based detectors to a great extent. Our approach uses state-of-the-art deformable part models [11] that are applied to histograms of oriented gradients [7] as features. Instead of considering occlusion in general terms, we quantitatively define the degree of occlusion in percentage and train a latent SVM formulation on a mixture of occlusion models. Due to the lack of availability of a standardized occlusion dataset, we have used the well-known ETHZ shape classes dataset [16] along with flickr images to create a synthetic dataset of occluded mugs and cups. The proposed methodology is compared with the shape-
Publications 2008-0101 Adapting ADtrees for High Arity Features

ADtrees, a data structure useful for caching sufficient statistics, have been successfully adapted to grow lazily when memory is limited and to update sequentially with an incrementally updated dataset. For low arity symbolic features, ADtrees trade a slight increase in query time for a reduction in overall tree size. Unfortunately, for high arity features, the same technique can often result in a very large increase in query time and a nearly negligible tree size reduction. In the dynamic (lazy) version of the tree, both query time and tree size can increase for some applications. Here we present two modifications to the ADtree which can be used separately or in combination to achieve the originally intended space-time tradeoff in the ADtree when applied to datasets containing very high arity features.
Quantifying the toxicity of mixtures of metals and metal-based nanoparticles to higher plants

Biotic Ligand Models (BLM) explicitly accounting for hypothetical interactions with biotic ligands and bioavailability as dictated by water chemistry have been developed for various metals and different organisms. It is only recently that BLMs for plants have received increasing attention. Lettuce is one of the most important vegetable crops in the world. This study investigated the impacts of Ca, Mg, K, Na and pH, on acute toxicity of Ni and Cd to butter-head lettuce seedlings (Lactuca sativa L.). Four day assays with the root elongation inhibition as the endpoint were performed in hydroponic solutions. Magnesium was found to be the sole cation significantly enhancing the median inhibition concentration (IC50) of Ni with increasing concentration. By incorporating the competitive effects of Mg, the Ni-toxicity prediction was improved significantly as compared to the total metal model (TMM) and the free ion activity model (FIAM). The conditional stability constants derived from the Ni-BLM were log KMgBL=2.86, log KNiBL=5.1, and f 50% NiBL =0.57. A slight downtrend was observed in the 4-d IC50 of Cd at increasing H concentrations, but this tendency was not consistent and statistically significant (p = 0.07) over the whole range. The overall variations of Cd-toxicity within the tested Na, K, Ca and Mg concentration ranges were relatively small and not statistically significant. Eighty percent of lettuce root elongation inhibition (REI) by Cd could be explained using both TMM and FIAM instead of BLM in the present study. Thus, the mechanistically underpinned models for soil quality guidelines should be developed on a metal-specific basis across different exposure conditions.
Feature extraction & Motion segmentation Kinematic structure generation 1 st order : Topology 2 nd order : Kinematic correlation 3 rd order : Combinatorial motion Hypergraph Matching Resulting Correspondences

In this paper, we present a novel framework for finding the kinematic structure correspondences between two articulated objects in videos via hypergraph matching. In contrast to appearance and graph alignment based matching methods, which have been applied among two similar static images, the proposed method finds correspondences between two dynamic kinematic structures of heterogeneous objects in videos. Thus our method allows matching the structure of objects which have similar topologies or motions, or a combination of the two. Our main contributions can be summarised as follows: (i) casting the kinematic structure correspondence problem into a hypergraph matching problem by incorporating multi-order similarities with normalising weights, (ii) introducing a structural topology similarity measure by aggregating topology constrained subgraph isomorphisms, (iii) measuring kinematic correlations between pairwise nodes, and (iv) proposing a combinatorial local motion similarity measure using geodesic distance on the Riemannian manifold. We demonstrate the robustness and accuracy of our method through a number of experiments on synthetic and real data, outperforming various other state of the art methods. Our method is not limited to a specific application nor sensor, and can be used as building block in applications such as action recognition, human motion retargeting to robots, and articulated object manipulation amongst others.
Recruits Comparison in a Category-Learning Task

Generating explanations can be highly effective in promoting category learning; however, the underlying mechanisms are not fully understood. We propose that engaging in explanation can recruit comparison processes, and that this in turn contributes to the effectiveness of explanation in supporting category learning. Three experiments evaluated the interplay between explanation and various comparison strategies in learning artificial categories. In Experiment 1, as expected, prompting participants to explain items’ category membership led to (a) higher ratings of self-reported comparison processing and (b) increased likelihood of discovering a rule underlying category membership. Indeed, prompts to explain led to more selfreported comparison than did direct prompts to compare pairs of items. Experiment 2 showed that prompts to compare all members of a particular category (“group comparison”) were more effective in supporting rule learning than were pairwise comparison prompts. Experiment 3 found that group comparison (as assessed by self-report) partially mediated the relationship between explanation and category learning. These results suggest that one way in which explanation benefits category learning is by inviting comparisons in the service of identifying broad patterns.
High Throughput Phenotyping with 3 D CNNs in Ladder Networks

Phenotyping plays an important role in creating new plant hybrids to increase crop yield for food. Current phenotyping techniques use 2D images which cannot capture the 3D nature of plants. Our model extracts features from 3D plant models to improve modern phenotyping. To address the difficulty of collecting labels, we also propose a new architecture of CNNs that can be trained in a semi-supervised setting. These prediction targets are regression problems.
The New York City Teaching Fellows Program: A Case Study in Alternative Certification in Mathematics

The purpose of this study is to understand the mathematical content knowledge new teachers have before and after taking a mathematics methods course in the New York City Teaching Fellows program. Further, the purpose is to understand attitudes toward mathematics Teaching Fellows have over the course of the semester. Findings revealed a significant increase in mathematical content knowledge and positive attitudes toward mathematics. Relationships were found between attitudes and self-efficacy. Finally, Teaching Fellows found that classroom management was the biggest issue in their teaching, and that problem solving and numeracy were the most important topics addressed in the methods course. posttest ( M = 3.33, SD = 0.410) and posttest PMTE ( M = 2.94, SD = 0.486) with r = 0.491, n = 42, and p = 0.001. No correlation found between mathematics attitude scores and MTOE scores.
Income Inequality and Natural Resources August 2016

The observation that countries highly endowed with natural resources often struggle with undesirable economic (e.g. low growth) and social problems has produced a large body of literature on the so-called resource curse over the last decades. One possible relationship that has been investigated is, whether resource abundance affects income inequality. This has been scrutinized to a much lesser extent than the effect on growth, and moreover, no agreement has been reached concerning the direction of the effect, given that it exists. This paper uses the Standardized World Income Inequality Database, the largest and probably most comparable dataset of Gini values, to determine the effect of resource abundance on income inequality. It dinstinguishes between a pure effect of resource abundance and an effect of resource intensity/dependence, a differentiation that has probably not received enough attention in the empirical resource curse literature in general. I examine whether resource abundance or resource intensity influences income inequality and whether the effect depends on the quality of institutions, which might turn a resource curse into a resource blessing. I find that neither resource abundance nor resource dependence influences income inequality significantly and that there is no effect of natural resouces that depends on the level of institutional quality.
Detecting hate speech on Twitter A comparative study on the naive Bayes classifier

Hate speech and cyberbullying on social media platform Twitter is a growing issue, and to combat this they turn to machine learning and computer science. This study will investigate and compare different configurations for the naive Bayes classifier when classifying hate speech on Twitter. We have achieved a data set of nearly 13000 tweets, some containing hate speech, and trained and tested our classifier with different configurations. The study shows that character level n-grams outperform word level ngrams, and the optimal size n-gram for character level is using combinations between 1-3.
Timing for delivering individualized patient education intervention to Coronary Artery Bypass Graft patients: A RCT Author:

Background: The primary focus of this study is on the timing of the delivery of education to patients who had CABG surgery. Aim: To determine the efficacy of an individualized telephone patient education intervention, delivered at two different points in time (12 days pre-discharge versus 1-2 days post-discharge) in enhancing the CABG patient’s knowledge of self-care behaviours, performance of self-care behaviours, and symptom frequency. Method: A randomized clinical trial that included a convenience sample of first time CABG patients. Individuals who received education pre-discharge were compared to individuals who received education post-discharge on the outcomes. Results: Results indicated no statistically significant difference in outcomes between the two time points. As well, anxiety levels were found to be significantly higher in the predischarge group than the post-discharge group. Conclusions: The individualized nature of the educational intervention may have accounted for non-significant findings reported in outcomes between the two time points. Practice Implications: Nurses may consider assessing anxiety levels prior to delivery of educational interventions, implement interventions aimed at reducing anxiety levels, and provide individualized teaching.
Evidence-based HRM : a Global Forum for Empirical Scholarship Investigating and explaining organizational antecedents of PSM

Purpose – First, the purpose of this paper is to contribute to the public service motivation (PSM) literature by increasing the limited knowledge of organizational antecedents of PSM. Second, by combining PSM with insights from self-determination theory (SDT), the paper aims to elucidate the link through which high-performance work systems (HPWS) relate to PSM. Design/methodology/approach – Using a survey, the authors investigated nurses’ perceptions of HPWS, PSM, and the satisfaction of basic psychological needs in four different German hospitals. Findings – The results of this study provide empirical evidence that PSM is influenced by several HR practices and the three basic psychological needs autonomy, relatedness, and competence, which in turn are influenced by certain HR practices as well. Basic psychological needs do not fully mediate the relationship between HPWS and PSM. Research limitations/implications – Four dimensions of HPWS are measured by a single item and the results are based on a German sample. They therefore might not apply to other countries. Future research will benefit from using a more corroborated measurement instrument of HPWS in different countries. Practical implications – This study offers useful insights for HR managers in the nursing sector on the question how PSM can be fostered effectively. Originality/value – This study adds to the limited knowledge of organizational antecedents of PSM by including ideas from HRM into the study of PSM. Second, by combining PSM with insights from psychology (SDT), this study sheds light on the mediating mechanisms which help to explain how HPWS relate to PSM; a conceptual model explaining the HPWS-PSM relationship is developed and tested.
Inverse number in dagaare

This chapter examines the inverse number system in Dagaare (Gur; Niger–Congo). Inverse number systems possess a number morpheme which for some nouns encodes the plural interpretation while for others it encodes the singular interpretation. This chapter argues that a principled lexical semantic classification underlies the inverse number strategy in Dagaare, guiding whether for a particular noun the inverse morpheme codes the singular or the plural interpretation. The chapter further explores the functional grounding of inverse number, in terms of frequency and individuation, and presents a formal semantic account of the inverse number system.