Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure of Dense Colloidal Liquids in Tight Spaces

We use three-dimensional confocal microscopy to study the structure of a dense colloidal liquid confined between two parallel glass plates. The colloidal sample is at a volume fraction of 50% and is a binary mixture of 2 μm and 3 μm diameter particles to prevent crystallization. The plate separation ranges from 50 small particle diameters to 3 small particle diameters. While particles form layers immediately adjacent to the confining walls, we otherwise see little influence of the confinement on structure.
A New Heuristic for Feature Selection by Consistent Biclustering

Given a set of data, biclustering aims at finding simultaneous partitions in biclusters of its samples and of the features which are used for representing the samples. Consistent biclusterings allow to obtain correct classifications of the samples from the known classification of the features, and vice versa, and they are very useful for performing supervised classifications. The problem of finding consistent biclusterings can be seen as a feature selection problem, where the features that are not relevant for classification purposes are removed from the set of data, while the total number of features is maximized in order to preserve information. This feature selection problem can be formulated as a linear fractional 0-1 optimization problem. We propose a reformulation of this problem as a bilevel optimization problem, and we present a heuristic algorithm for an efficient solution of the reformulated problem. Computational experiments show that the presented algorithm is able to find better solutions with respect to the ones obtained by employing previously presented heuristic algorithms.
Experimental Study on Effect of Lime and Cement Stabilizers on Geotechnical Properties of Lateritic Soil

ABSTRACT This study examined the effect of lime and cement as stabilizers on the geotechnical properties of the lateritic soil in Ogiso quarters, Benin City, Edo state of Nigeria. The lateritic soil samples, which were obtained from the street prone to erosion in Ogiso quarters, using the disturbed sampling method, were transported to the Geotechnical laboratory Department of Civil Engineering, University of Benin. The preliminary tests were performed on the samples for classification and identification purposes using the American Association of State Highway and Transportation Officials (AASHTO) classification system. They were stabilized using lime and cement stabilizers at 2,4,6,8 and 10% by weight of the soil samples so as to analyze the performance of the stabilized agents on the lateritic soil. The laboratory tests, which included natural moisture content, specific gravity, particle sieve analysis, Atterberg limits, compaction and California bearing ratio (CBR) were carried out in accordance with the British standard (BS) method of test for soil in Civil Engineering. The result of the study has shown that the lateritic soil in the sample location is reddish brown in colour and belong to A-2-6 group with liquid limit, plastic limit and plasticity index values obtained as 33.20%, 14.14% and 19.06% respectively. The specific gravity of the soil sample is 2.53. The natural moisture content is 15.1%. The Optimum moisture content (OMC) and Maximum dry density (MDD) are 13.3% and 1.75g/cm 3
Self-regulation and self-efficacy for the improvement of listening proficiency outside the classroom

ABSTRACT This paper reports on a qualitative inquiry into Japanese students’ self-regulated learning processes to improve their listening proficiency outside the classroom in an English as a foreign language context. Four Japanese university students with different levels of self-efficacy and listening outcomes were closely examined from a social cognitive perspective. The analysis of the data gathered from learning diaries, interviews and other self-reports showed that (1) the students with high self-efficacy were specific, diverse and frequent in their self-regulated processes, while their peers with low self-efficacy were not active in these processes and (2) in particular, a self-efficacious student who made greater listening progress exhibited sophisticated metacognitive strategy use in his entire self-regulated learning process, which was likely to promote effective self-regulatory cycles. These results shed light on the potential interactions between self-regulation, self-efficacy and language gains in the self-instructional learning setting. The implications of these findings for language teachers and learners are discussed.
Analysis of Hand Synergies for Inverse Kinematics Hand Tracking

We present a method for real-time bare hand tracking that utilizes natural hand synergies to reduce the complexity and improve the plausibility of the hand posture estimation. The hand pose and posture are estimated by fitting a virtual hand model to the 3D point cloud obtained from a Kinect camera using an inverse kinematics approach. We use real human hand movements captured with a Vicon motion tracking system as the ground truth for deriving natural hand synergies based on principal component analysis. These synergies are integrated in the tracking scheme by optimizing the posture in a reduced parameter space. We show that this synergistic hand tracking approach improves runtime performance and increases the quality of the posture estimation.
Immediate and Persistent Effects of Temperature on Oxygen Consumption and Thermal Tolerance in Embryos and Larvae of the Baja California Chorus Frog, Pseudacris hypochondriaca

The developmental environment has significant immediate effects on phenotypes, but it may also persistently or permanently shape phenotypes across life history. This study examined how developmental temperature influenced embryonic and larval phenotypes of Baja California chorus frog (Pseudacris hypochondriaca), an abundant amphibian in southern California and northern Baja California. We collected egg clutches from native ponds in northern San Diego County within 24 h of fertilization, and clutches were separated and distributed between constant temperatures of 10, 15, 20, and 25°C for incubation. Oxygen consumption rate (V˙O2), developmental stage, and embryo and yolk masses were measured throughout development. Time to 50% hatch, survival at 50% hatch, and hatch duration were determined. Development rate was strongly affected by temperature, with warmer temperatures reducing time to hatch and hatch duration. Survival to hatch was high across all temperatures, >90%. Mass-specific V˙O2 of embryos either remained constant or increased throughout development, and by hatching energy demand was significantly increased at higher temperatures. There were limited temperature effects on growth, with embryo and yolk dry mass similar between temperatures throughout embryonic development. To examine long-term effects of embryonic temperature, we reared hatchlings from each temperature until onset of larval feeding. Once feeding, larvae were acclimated to 20 or 25°C (>2 weeks). Following acclimation to 20 or 25°C, we measured larval mass-specific V˙O2 and critical thermal maximum (CTMax) at a common developmental stage (Gosner stages 32–36, “hindlimb toe differentiation”). Embryonic temperature had persistent effects on larval V˙O2 and CTMax, with warmer temperatures generally resulting in similar or higher V˙O2 and CTMax. This partially supported a “warmer is better” effect of embryonic incubation temperature. These results suggest that in a thermally robust amphibian species, temperature may program the phenotype during early development to construct traits in thermal tolerance and energy use that may persist. Overall, P. hypochondriaca displays a thermally robust phenotype, and it is possible that amphibians that possess a wider range of phenotypic plasticity will be relatively more successful mitigating effects of climate change.
Gross Worker Flows in the Presence of Informal Labor Markets: Evidence from Mexico, 1987-2002

This paper applies recent advances in the study of labor market dynamics to a representative developing country with a large unregulated of “informal” sector. It confirms the relevance of the recent mainstream models and debates surrounding gross worker flows to the developing country context, and offers a new view of the role of the informal sector and its role in labor market adjustments. It finds, first, that the formal salaried sector shows the same procyclical job finding rate and mildly countercyclical separation behavior identified in the recent US literature by Shimer (2005a) and Hall (2005). The unregulated informal sector, however, shows reasonable acyclicality in the job finding rate coupled with sharp countercyclical movements in the job separation rate, consistent with standard small firm dynamics and Davis and Haltiwanger (1992 and 1999). The differential behavior of regulated and unregulated sectors, and the finding of relative wage rigidity in the former, sheds suggestive light on the debate surrounding countercyclical job finding behavior in the US. Second, the patterns of worker transitions between all sectors, formal and informal correspond to the job-to-job dynamics observed in the US and not to the traditional idea of informality constituting the inferior sector of a segmented market. That said, the counter cyclical job finding in the formal sector combined with the acyclical job finding in informality does lead to the latter absorbing relatively more labor during downturns, even as its increased separation rates drive movements in unemployment.
Recognition of expression variant faces using masked log-Gabor features and Principal Component Analysis

In this article we propose a method for the recognition of faces with different facial expressions. For recognition we extract feature vectors by using log-Gabor filters of multiple orientations and scales. Using sliding window algorithm and variances -based masking these features are extracted at image regions that are less affected by the changes of facial expressions. Extracted features are passed to the Principal Component Analysis (PCA) -based recognition method. The results of face recognition experiments using expression variant faces showed that the proposed method could achieve higher recognition accuracy than many other methods. For development and testing we used facial images from the AR and FERET databases. Using facial photographs of more than one thousand persons from the FERET database the proposed method achieved 96.6-98.9% first one recognition rate and 0.2-0.6% Equal Error Rate (EER).
Religious identity and sense of belonging among Rowan University Muslim students

v List of Figures . ix List of Tables . x Chapter I: Introduction . 1 Statement of the Problem . 1 Purpose of the Study . 3 Significance of the Study . 3 Assumptions and Limitations . 4 Operational Definitions . 5 Research Questions . 5 Organization of Remaining Chapters . 6 Chapter II: Review of Literature . 8 Foundations of Identity Research . 8 College Student Identity . 11 Campus Climate . 13 Religious and Ethnic Identity . 14 Racial and Cultural Identity Development . 17 Muslim Identity Studies . 18 Islam and Muslims in America . 22 Effects of 9/11 and Islamophobia . 25
Analysis of Genetic Structure of Wild and Cultured Giant Freshwater Prawn (Macrobrachium rosenbergii) Using Newly Developed Microsatellite

The giant freshwater prawn (GFP), Macrobrachium rosenbergii, is one of the most critical crustacean species cultured in Southeast Asia. Investigation of the genetic structure of current commercial stocks allows GFP breeding programs to better manage crosses and germplasm banks as well as to promote the rational use of GFP. In the present study, we aimed to characterize and use 17 microsatellite loci, including 12 novel loci derived from GFP transcriptome data, to assess genetic diversity in a wild (Myanmar) and six cultured populations (i.e., four Chinese (Zhejiang, Guangxi, and Guangdong A and B), one Malaysian, and one Thailand’s cultured population). The results showed that the number of alleles per locus ranged from 3 to 18. The mean observed heterozygosity (0.363 ± 0.048) was less than the expected heterozygosity (0.637 ± 0.048). The mean values of polymorphism information content among the seven populations were > 0.5 (ranging from 0.110 to 0.915). These cultured populations exhibited reduced genetic diversity when compared with that of the wild population. Pair-wise genetic differentiation ranged from 0.006 to 0.131 within the seven populations. The dendrogram based on genetic distance showed that six cultured populations were distributed on the same major branch, suggesting that they have a close genetic distance, whereas the wild population was distributed on an independent branch. The results provide a baseline assessment of genetic diversity in some available stocks and lay a foundation for future research efforts toward genetic monitoring and selective breeding.
Efficient Methods for Out-of-Core Sparse Cholesky Factorization

We consider the problem of sparse Cholesky factorization with limited main memory. The goal is to efficiently factor matrices whose Cholesky factors essentially fill the available disk storage, using very little memory (as little as 16 Megabytes (MBytes)). This would enable very large industrial problems to be solved with workstations of very modest cost. We consider three candidate algorithms. Each is based on a partitioning of the matrix into panels. The first is a robust, out-of-core multifrontal method that keeps the factor, the stack, and the large frontal matrices on disk. The others are left-looking methods. We find that straightforward implementations of all of them suffer from excessive disk I/O for large problems that arise in interior-point algorithms for linear programming. We introduce several improvements to these simple out-of-core methods and find that a left-looking method that nevertheless uses the multifrontal algorithm for portions of the matrix (subtrees of the supernodal elimination tree whose multifrontal stack fits in memory) is very effective. With 32 Mbytes of main memory, it achieves over 77% of its in-core performance on all but one of our 12 test matrices (67% in that one case), even though the size of the factor is, in all cases, hundreds of millions or even billions of bytes.
State Feedback Stabilization with Guaranteed Transient Bounds

We analyze under which conditions linear time-invariant state space systems can be stabilized by static linear state feedback such that prescribed transient bounds hold pointwise in time for the trajectories of the closed loop system. We introduce the concepts of (M,β)-stability and quadratic (M,β)-stability which guarantee a transient bound M along with a decay rate β < 0. Necessary and sufficient conditions for quadratic (M,β)-stabilizability are derived which can be expressed in terms of linear matrix inequalities. A full characterization of general (M,β)-stabilizability is still missing. However, we obtain necessary and sufficient criteria under which a given system can be transformed by linear state feedback into a closed loop system generating a strict contraction semigroup with respect to the spectral norm.
Spatial Equilibrium with Unemployment and Wage Bargaining: Theory and Estimation

In this paper, we present a spatial equilibrium model where search frictions hinder the immediate reallocation of workers both within and across local labour markets. Because of the frictions, firms and workers find themselves in bilateral monopoly positions when determining wages. Although workers are not at each instant perfectly mobile across cities, in the baseline model we assume that workers flows are sufficient to equate expected utility across markets. We use the model to explore the joint determination of wages, unemployment, house prices and city size (or migration). A key role of the model is to clarify conditions under which this type of spatial equilibrium setup can be estimated. We then use U.S. data over the period 1970-2007 to explore the fit of model and it quantitative properties of the model. Our main goal is to highlight forces that influence spatial equilibria at 10 year intervals.
A performance evaluation of the collection tree protocol based on its implementation for the Castalia wireless sensor networks simulator

Many wireless sensor network applications rely on the availability of a collection service to route data packets towards a sink node. The service is typically accessed through welldefined interfaces so as to hide the details of its implementation. Providing for efficient network operation, however, often requires investigating the interplay between specific collection services and application-level algorithms. To enable a smooth evaluation of these mutual dependencies, we implemented a reference collection protocol, known as CTP, as a module for the Castalia wireless sensor networks simulator. Castalia is a wellknown and widely used simulator but its standard distribution only provides for a basic collection module. By implementing a more advanced protocol like CTP we extend and improve the application scope of Castalia. In this report, we describe our implementation and present a study of the performance of CTP. All the software modules developed in the context of this work are available upon request from the authors.
A Graph Coloring Algorithm for Large Scheduling Problems.

A new graph coloring algorithm is presented and compared to a wide variety of known algorithms. The algorithm is shown to exhibit O(n 2) time behavior for most sparse graphs and thus is found to be particularly well suited for use with large-scale scheduling problems. In addition, a procedure for generating large random test graphs with known chromatic number is presented and is used to evaluate heuristically the capabilities of the algorithms discussed.
Generalized Extraction of Real-Time Parameters for Homogeneous Synchronous Dataflow Graphs

Many embedded multi-core systems incorporate both dataflow applications with timing constraints and traditional real-time applications. Applying real-time scheduling techniques on such systems provides real-time guarantees that all running applications will execute safely without violating their deadlines. However, to apply traditional real-time scheduling techniques on such mixed systems, a unified model to represent both types of applications running on the system is required. Several earlier works have addressed this problem and solutions have been proposed that address acyclic graphs, implicit-deadline models or are able to extract timing parameters considering specific scheduling algorithms. In this paper, we present an algorithm for extracting real-time parameters (offsets, deadlines and periods) that are independent of the schedulability analysis, other applications running in the system, and the specific platform. The proposed algorithm: 1) enables applying traditional real-time schedulers and analysis techniques on cyclic or acyclic Homogeneous Synchronous Dataflow (HSDF) applications with periodic sources, 2) captures overlapping iterations, which is a main characteristic of the execution of dataflow applications, 3) provides a method to assign offsets and individual deadlines for HSDF actors, and 4) is compatible with widely used deadline assignment techniques, such as NORM and PURE. The paper proves the correctness of the proposed algorithm through formal proofs and examples.
The effects of social-exclusion inducing stereotype threat

Stereotype threat occurs when one may feel as if they are confirming or representing a selfcharacteristic or a negative stereotype of one’s group. Social exclusion has been shown to threaten the need to belong. Both stereotype threat and social exclusion have many common links: Each affects an individual’s self-views, feelings, and each impact one’s ability to focus cognitive faculties to perform well on cognitive tests. This thesis sought to explain how social exclusion would increase the perceived threat on related tests of sociability. As such, participants were included or excluded during an online social game, and then received an ordinary or diagnostic test of sociability. It was hypothesized that social exclusion would have negative effects on reports of social needs compared to the act of inclusion, and being excluded would influence performance on a measure of sociability. Results indicated support only for the social needs. It was also hypothesized that diagnostic tests for sociability would produce more stereotype threat and reported stress than pilot tests. Results indicated marginal support for this second hypothesis. It was also suggested that the most threat would be seen for participants who were both excluded and given a diagnostic test as compared to participants who were not excluded or not given a diagnostic test. That hypothesis, however, was not supported. Implications for theoretical connections between social exclusion and stereotype threat are discussed.
Motivational Consequences of Perceived Velocity in Consumer Goal Pursuit

The authors explore the interplay between consumers’ progress levels toward attaining a goal and the perceived velocity in progressing toward the goal to determine consumers’ motivation for further goal pursuit. The authors propose that when progress toward attaining a goal is low, consumers are primarily concerned about the question “Can I get there? ” Thus, a high (vs. low) perceived velocity in progressing suggests greater expectations of goal attainment, resulting in greater motivation for pursuing the goal. However, when consumers have achieved sufficient progress and are approaching the end point, their attainment of the goal is relatively secured, so they become more concerned about the question “When will I get there? ” and focus more on whether they are effectively reducing the remaining discrepancy so that they can attain the goal quickly. In this case, a low (vs. high) perceived velocity in progressing elicits greater motivation because it suggests that continued effort is needed to ensure a speedy attainment. Empirical evidence from lab and field experiments supports this hypothesis.
Numeric Input Relations for Relational Learning with Applications to Community Structure Analysis

Most work in the area of statistical relational learning (SRL) is focussed on discrete data, even though a few approaches for hybrid SRL models have been proposed that combine numerical and discrete variables. In this paper we distinguish numerical random variables for which a probability distribution is defined by the model from numerical input variables that are only used for conditioning the distribution of discrete response variables. We show how numerical input relations can very easily be used in the Relational Bayesian Network framework, and that existing inference and learning methods need only minor adjustments to be applied in this generalized setting. The resulting framework provides natural relational extensions of classical probabilistic models for categorical data. We demonstrate the usefulness of RBN models with numeric input relations by several examples. In particular, we use the augmented RBN framework to define probabilistic models for multi-relational (social) networks in which the probability of a link between two nodes depends on numeric latent feature vectors associated with the nodes. A generic learning procedure can be used to obtain a maximum-likelihood fit of model parameters and latent feature values for a variety of models that can be expressed in the high-level RBN representation. Specifically, we propose a model that allows us to interpret learned latent feature values as community centrality degrees by which we can identify nodes that are central for one community, that are hubs between communities, or that are isolated nodes. In a multi-relational setting, the model also provides a characterization of how different relations are associated with each community.