Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting and Tracking Coordinated Groups in Dense, Systematically Moving, Crowds

We address the problem of detecting and tracking clusters of moving objects in very noisy environments. Monitoring a crowded football stadium for small groups of individuals acting suspiciously is an example instance of this problem. In this example the vast majority of individuals are not part of a suspicious group and are considered as noise. Existing spatio-temporal cluster algorithms are only capable of detecting small clusters in extreme noise when the noise objects are moving randomly. In reality, including the example cited, the noise objects move more systematically instead of moving randomly. The members of the suspicious groups attempt to mimic the behaviors of the crowd in order to blend in and avoid detection. This significantly exacerbates the problem of detecting the true clusters. We propose the use of Support Vector Machines (SVMs) to differentiate the true clusters and their members from the systematically moving noise objects. Our technique utilizes the relational history of the moving objects, implicitly tracked in a relationship graph, and a SVM to increase the accuracy of the clustering algorithm. A modified DBSCAN algorithm is then used to discover clusters of highly related objects from the relationship graph. We evaluate our technique experimentally on several data sets of mobile objects. The experiments show that our technique is able to accurately and efficiently identify groups of suspicious individuals in dense crowds.
Transitioning Normalcy

In this article, we present findings from a review and synthesis of historical and contemporary research to examine the concept of diversity leadership in higher education as it pertains to African American administrators at predominantly White colleges and universities. Through the use of critical race theory, we first argue that to understand the leadership disparity of African Americans and other administrators of color in higher education, one must begin by examining the cultural context in which predominantly White institutions originate, exist, and operate through the intersection of group relations. Second, we argue that due to a historical pattern of exclusivity, the title of administrator is considered whiteness property in higher education. As a consequence, the disparity between African American administrators and their White counterparts has become an organizational norm in higher education. Last, we posit that if true diversity leadership is to exist within the administrative rankings at predominantly White institutions, the conceptualization and inclusion of minority experiences must not only inform stakeholders but also shape the recruitment, retention, and assessment of minority representation at the university administrative level.
Genomic Selection in Multi-environment Crop Trials

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers.
Facial Expression Classification using Visual Cues and Language

In this work, we attempt to tackle the problem of correlating language with facial expressions to learn in an unsupervised manner, the adjectives used to describe emotions. The problem is divided into two parts i) a supervised method for classifying facial emotions using visual cues and ii) an unsupervised algorithm to extract keywords out of commentary on videos depicting facial expressions. We use a method based on Gabor filters and Support Vector Machines to classify emotions into 7 categories Anger, Surprise, Sadness, Happiness, Disgust, Fear and Neutral. We explore various dimensionality reduction and feature selection methods like PCA and AdaBoost. The Extended Cohn-Kanade database [7] is used for testing the algorithms. We achieve an accuracy of 94.72% for a 7-way forced choice SVM classifier after feature selection using Adaboost which is a significant improvement over many previous successful approach based on PCA and LDA and Local Binary Patterns. In the next step, we obtain commentary on 40 videos depicting 4 emotions Anger, Sadness, Happiness and Surprise and cluster keywords obtained using a maximum co-occurrence method to discover descriptors for these emotions.
When the Big Fish Turns Small

The purposes of this study were to (a) examine the presence and prevalence of the big-fish-little-pond effect (BFLPE) in summer programs for the gifted, (b) identify group and individual difference variables that help predict those who are more susceptible to the BFLPE, and (c) put the possible BFLPE on academic self-concept in a larger context of self-concept stability and change during adolescence. Longitudinal data were gathered from adolescents participating in a summer program for the gifted over a 3-year period. The results indicate no prevalent patterns of declines in academic self-concepts after participating in summer programs, though suspected cases of BFLPE can be identified, and there was evidence pointing to the moderation of the BFLPE by gender and self-esteem. Longitudinal patterns of self-concept stability and change also show no consistent pattern of long-term effects on self-concept. Implications of these findings are discussed that highlight developmental, social, and individual conditions under which the BFLPE may exert itself and conditions under which it may be mitigated.
The Paradoxes of Neoliberalism: Migrant Korean Sex Workers in the United States and “Sex Trafficking”

This article examines the paradoxes of neoliberalism through two migrant sex workers’ negotiation of the transnational disciplinary regimes of morality, national security, and humanitarianism. We take as our point of departure their active resistance to the label of “victims of sex trafficking. ” From a close analysis of their migration journey and their experiences in the United States, we come to understand these women as defiant neoliberal subjects. We argue that global anti-trafficking initiatives as they have taken shape in the twenty-first century are part of neoliberal governance. The women’s sexual labor subjects them to the scrutiny and penalty of the state. Yet they see themselves as self-sufficient, self-responsible, and self-enterprising individuals. We locate these tensions within three paradoxes of neoliberalism: the apparent amorality of neoliberalism and its facilitation of a conservative moral agenda; the depoliticization of social risks and the hyperpoliticization of national security; and the continuous creation and ravaging of vulnerable populations coupled with the celebration of humanitarian/philanthropic responses from governmental and NGO sectors. Juxtaposing these women’s self-making projects with the transnational state apparatus to combat “sex trafficking,” we gain insights into how individual pursuits and state practices intersect at this neoliberal moment—despite their different purposes.
Response Time Under Monetary Incentives: The Ultimatum Game

This paper studies the response times of experimental subjects playing the Ultimatum game in a laboratory setting using monetary incentives. We find that proposals are not significantly correlated with response time, whereas responders' behavior is positively and significantly correlated. Hence, consistent with Rubisntein (forthcoming) we find that response times may capture relevant cognitive processes. However, the use of monetary incentives causes a reversal of his findings. These results have implications for the information about cognitive mechanisms that can be obtained from response times.
Domain Adaptation with Topical Correspondence Learning

A serious and ubiquitous issue in machine learning is the lack of sufficient training data in a domain of interest. Domain adaptation is an effective approach to dealing with this problem by transferring information or models learned from related, albeit distinct, domains to the target domain. We develop a novel domain adaptation method for text document classification under the framework of Non-negative Matrix Factorization. Two key ideas of our method are to construct a latent topic space where a topic is decomposed into common words shared by all domains and words specific to individual domains, and then to establish associations between words in different domains through the common words as a bridge for knowledge transfer. The correspondence between cross-domain topics leads to more coherent distributions of source and target domains in the new representation while preserving the predictive power. Our new method outperformed several state-of-the-art domain adaptation methods on several benchmark datasets.
Multilevel Approaches to Nonconforming FiniteElement Discretizations of Linear Second OrderElliptic Boundary Value

We consider adaptive multilevel techniques for nonconforming nite element dis-cretizations of second order elliptic boundary value problems. In particular, we will focus on two basic ingredients of an eecient adaptive algorithm. The rst one is the iterative solution of the arising linear system by preconditioned conjugate gradient methods and the second one is an a posteriori error estimator for the global discretization error. Both element-oriented and edge-oriented estimators will be investigated. Their local contributions will serve as an indicator within the reenement process. Finally, some numerical results will be presented. They illustrate the performance of the preconditioners as well as the reenement process.
Simulation Environment For An Autonomous And Decentralized Multi-agent Robotic System

An autonomous and decentralized system called ACTRESS (ACTor based Robot and Equipment Synthetic System) is being under development as an intelligent robot system which can execute high level tasks. ACTRESS is composed of multiple robotic agents. Each robotic agent is called "robotor". A robotor may be a robot, a computing system and any other equip- ments. While researching in this field, many research issues need to have solutions, such issues may include, the communication among the agents and protocols, cooperation among a group of agents, describing the tasks to be executed, multi-agent motion planning, multi-agent task planning, task description, human interface role, solving deadlocks . etc. The aim of this paper is to develop a simulation environment for an autonomous and decentralized multi-agent robotic system. For this purpose, it is neces- sary to simulate and analyze the main functions of each agent, design and analysis of the actions to be carried out by each agent, analyzing their real time behavior with a variety of situations considering their environ- ment and the treatment of unexpected events. Also, it is aecessary to find out an efficient strategy to realize effective means for the agents to form a cooperating manner that support task execution and problem solv- ing. In parallel with the mentioned purposes the ACTRESS structure is simulated as functions and behavior using the developed simulation environment. This simulation includes a group of mobile robots, human interface and global environment manager. Then, software integration that deal with various aspect of the overall problem is developed. Different experi- ments are performed to analyze the performance of each individual robotor and the overall system.
Climatologists’ Communication of Climate Science to the Agricultural Sector

Farming is a risky business. Climate science information can assist agriculture in formulating management decisions that hedge against uncertainty and risks. Climatologists are key actors in communicating historical trends and forecast information. Interviews and surveys of climatologists in the North Central Region reveal that they are providing accurate and objective information but are likely to let the science speak for itself. This suggests missed opportunities to communicate climate science in ways that make science relevant to decision maker beliefs, values, and practical applications. Furthermore, more active engagement with agriculture could increase colearning necessary for effective adaptive management under increasingly variable climate conditions.
The Sociopolitical Dimensions of Wolf Management and Restoration in the United States

This article examines the political cultural context and sociopolitical dimensions of wolf management and restoration in the United States. Drawing on the experiences of various wolf programs throughout the country, including New England, the Northern Rockies, Upper-Midwest, Southwest, and Yellowstone National Park, it documents how wolves are often used as a political symbol and surrogate for a number of socially significant policy issues. It also examines the politics of problem definition in the policymaking process. A “politics” model of public policy is used as an analytical framework to examine the following dimensions that are inextricably tied to the debate over wolf management and recovery: land use and the politics of ecosystem management; wilderness preservation; The Wildlands Project and the role of conservation biology in political decisionmaking; the merits and future of the Endangered Species Act; rural culture, concerns and interests; and the contested role of science and public participation in wildlife policymaking and management. The article ends with a discussion of how these sociopolitical and contextual variables affect political decisionmakers and those responsible for wolf management.
A quasi-experimental study of the differences in performance and clinical reasoning using individual learning versus reciprocal peer coaching

Peer assisted learning such as Reciprocal Peer Coaching (RCP) is being used more frequently in the clinical education of physiotherapists. The efficacy of this learning approach on clinical performance and reasoning, however, has not been evaluated with much rigour. The purpose of this research is to measure the impact of this method on clinical performance and reasoning in two groups of students. One group examined a simulated patient (SP) individually. The other group examined the SP as a reciprocal peer coaching (RPC) dyad. Sixty-two third year physiotherapy students participated in this study. Twenty individual students and twenty-one dyads each evaluated a SP with shoulder pathology. Clinical performance and reasoning were measured. Students in the RPC group significantly outperformed their peers in the individual learning group in the categories of physical examination, communication, and clinical reasoning. The cognitive support that RPC provides novices during patient encounters is a valuable educational support tool. By incorporating more peer coaching in clinical education environments, it is possible to influence the clinical performance and reasoning of novices in a positive manner, thus enhancing the development of clinical competency.
Complete Genome Sequence of Bradyrhizobium sp. Strain CCGE-LA001, Isolated from Field Nodules of the Enigmatic Wild Bean Phaseolus microcarpus

ABSTRACT We present the complete genome sequence of Bradyrhizobium sp. strain CCGE-LA001, a nitrogen-fixing bacterium isolated from nodules of Phaseolus microcarpus. Strain CCGE-LA001 represents the first sequenced bradyrhizobial strain obtained from a wild Phaseolus sp. Its genome revealed a large and novel symbiotic island.
An Evidence-Based Assessment of Faith-Based Programs: Do Faith-Based Programs “Work” to Reduce Recidivism?

Faith-based organizations administer many of the prison-based programs aimed at reducing recidivism. Many of these organizations also manage treatment programs for substance abusers, at-risk juveniles, and ex-offenders. Much of the research on religiosity and delinquency indicates that the two are inversely related. Therefore, it seems plausible that faith-based programs, which are rooted in religious organizations, may be effective tools for reducing deviant and criminal behavior. However, it is unclear whether the empirical evidence supports such a claim. This study is an evidence-based assessment of the effectiveness of faith-based programs for reducing recidivism. The results of this study indicate that faith-based programs “work” to reduce recidivism. Directions for future research are discussed.
Using Magnitude Estimation Scaling in Business Communication Research

Research using attitude / behavior correlation to predict behavior of subjects in situa tions significant to business communication generally produces low to moderate cor relations that explain relatively small amounts of the variance among variables. Researchers sometimes depend on large sample sizes to produce variation measurable as statistically significant. Magnitude estimation scaling, a method tracing its origin to the field of psychophysics, has had some interesting results in social science re search. This article critically analyzes the technique for its potential use in business communication research. The result finds that the 12-15 percent increase in explained variance by magnitude estimation over categorical scaling methods may be useful in theory building, but may not be sufficient to justify the added expense necessary to en sure data integrity for applied business communication research.
What determines the van der Waals coefficient β in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations?

Recently a semiempirical method has been proposed by Åqvist et al. 1 , 2 , 3 to calculate absolute and relative binding free energies. In this method, the absolute binding free energy of a ligand is estimated as ΔGbind = α〈V boundel − V freeel 〉 + β〈V boundvdw − V freevdw , where V boundel and V boundvdw are the electrostatic and van der Waals interaction energies between the ligand and the solvated protein from an molecular dynamics (MD) trajectory with ligand bound to protein and V freeel and V freevdw are the electrostatic and van der Waals interaction energies between the ligand and the water from an MD trajectory with the ligand in water. A set of values, α = 0.5 and β = 0.16, was found to give results in good agreement with experimental data. Later, however, different optimal values of β were found in studies of compounds binding to P450cam 4 and avidin. 5 The present work investigates how the optimal value of β depends on the nature of binding sites for different protein‐ligand interactions. By examining seven ligands interacting with five proteins, we have discovered a linear correlation between the value of β and the weighted non‐polar desolvation ratio (WNDR), with a correlation coefficient of 0.96. We have also examined the ability of this correlation to predict optimal values of β for different ligands binding to a single protein. We studied twelve neutral compounds bound to avidin. In this case, the WNDR approach gave a better estimate of the absolute binding free energies than results obtained using the fixed value of β found for biotin‐avidin. In terms of reproducing the relative binding free energy to biotin, the fixed‐β value gave better results for compounds similar to biotin, but for compounds less similar to biotin, the WNDR approach led to better relative binding free energies. Proteins 1999;34:395–402. © 1999 Wiley‐Liss, Inc.
Interaction on the Web: Scholars' Judgment of Information Quality and Cognitive Authority

This paper reports on a study of scholars’ judgments of information quality and cognitive authority when interacting with information in the World Wide Web. This is the second in a series of studies on information quality and cognitive authority in the Web. The first study obtained data through retrospective accounts, and this study collected the data based on actual searching behaviors. Multiple data collection methods were utilized, combining verbal protocols during the searches, search logs, and post-search interviews. The scholars, recruited from diverse discipline areas, conducted four searches regarding four different tasks: research project, travel, medicine, and computer price. It was found that the subjects made two kinds of judgments: before they looked at some web pages (predictive judgment) and after they looked at it (evaluative judgment). Their judgments were analyzed in terms of facets indicating information quality, cognitive authority, topical interests, aesthetic aspects, and affective aspects. The factors influencing each judgment of quality and authority were identified, including major categories in characteristics of information objects, characteristics of sources, knowledge, and situation.
Venation Skeleton-Based Modeling Plant Leaf Wilting

A venation skeleton-driven method for modeling and animating plant leaf wilting is presented. The proposed method includes five principal processes. Firstly, a three-dimensional leaf skeleton is constructed from a leaf image, and the leaf skeleton is further used to generate a detailed mesh for the leaf surface. Then a venation skeleton is generated interactively from the leaf skeleton. Each vein in the venation skeleton consists of a segmented vertices string. Thirdly, each vertex in the leaf mesh is banded to the nearest vertex in the venation skeleton. We then deform the venation skeleton by controlling the movement of each vertex in the venation skeleton by rotating it around a fixed vector. Finally, the leaf mesh is mapped to the deformed venation skeleton, as such the deformation of the mesh follows the deformation of the venation skeleton. The proposed techniques have been applied to simulate plant leaf surface deformation resulted from biological responses of plant wilting.