Miracle-dz/UniFAR-FTUs huggingface dataset:
Resting State Distinguish Human Ventral Tegmental Area from Substantia Nigra

Dopaminergic networks modulate neural processing across a spectrum of function from perception to learning to action. Multiple organizational schemes based on anatomy and function have been proposed for dopaminergic nuclei in the midbrain. One schema originating in rodent models delineated ventral tegmental area (VTA), implicated in complex behaviors like addiction, from more lateral substantia nigra (SN), preferentially implicated in movement. However, because anatomy and function in rodent midbrain differs from the primate midbrain in important ways, the utility of this distinction for human neuroscience has been questioned. We asked whether functional definition of networks within the human dopaminergic midbrain would recapitulate this traditional anatomical topology. We first developed a method for reliably defining SN and VTA in humans at conventional MRI resolution. Hand-drawn VTA and SN regions-of-interest (ROIs) were constructed for 50 participants, using individually-localized anatomical landmarks and signal intensity. Individual segmentation was used in seed-based functional connectivity analysis of resting-state functional MRI data; results of this analysis recapitulated traditional anatomical targets of the VTA versus SN. Next, we constructed a probabilistic atlas of the VTA, SN, and the dopaminergic midbrain region comprised (SN plus VTA) from individual hand-drawn ROIs. The combined probabilistic (VTA plus SN) ROI was then used for connectivity-based dual-regression analysis in two independent resting-state datasets (n=69 and n=79). Results of the connectivitybased, dual-regression functional segmentation recapitulated results of the anatomical segmentation, validating the utility of this probabilistic atlas for future research. Corresponding Author: R. Alison Adcock, B203 Levine Science Research Center, Duke University, Box 90999, Durham, NC 27708, USA, Phone: (919) 681 – 7486, Fax: (919) 681-0815, alison.adcock@duke.edu. Conflicts of Interest: The authors have no conflicts of interest to report Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. HHS Public Access Author manuscript Neuroimage. Author manuscript; available in PMC 2015 October 15. Published in final edited form as: Neuroimage. 2014 October 15; 100: 580–589. doi:10.1016/j.neuroimage. 2014.06. 047. A uhor M anscript
Information-theoretic approaches for sensor selection and placement in sensor networks for target localization and tracking

In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor networks for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.
Keep Calm and Play On: The Effects of Grit, Mindfulness, and Goal Orientation on Sport Anxiety and Performance

Achievement motivation theory suggests there are two primary approaches to achievement tasks: to appear competent or to develop a skill. These two different approaches to performance yield different affective and behavioral responses. Athletes holding a performance goal orientation tend to respond to challenges with behaviors exemplifying learned helplessness and increased anxiety. Athletes holding a mastery goal orientation tend to respond to challenges with greater effort and experience less sport-related anxiety. Individual athlete factors, such as grit, mindfulness, and achievement orientation may influence how athletes experience their environment and their levels of sport anxiety, and may interact with athletes' achievement motives to influence performance. I used hierarchical multiple regressions to test the main effects of feedback and mindfulness, and feedback and goal orientation, to determine if either mindfulness or goal orientation moderated the effects of feedback on performance. I also used simple regression to determine the relative predictive strength of mindfulness, grit, and goal orientation on athletes' experience of sport anxiety. Mindfulness, but not goal orientation, was a significant moderator of the feedback-shooting performance relationship, but particularly for athletes low in mindfulness; mastery-goal orientation, independently of feedback, was also a significant predictor of task performance. Mindfulness also emerged as the strongest predictor of reduced sport anxiety. These results suggest that, for athletes low in mindfulness, mastery-involving feedback may be especially helpful. Further, mindfulness may also reduce athlete's sport-related concentration disruption, worry, and somatic anxiety.
Classification into Readability Levels : Implementation and Evaluation

The use for a readability classification model is mainly as an integrated part of an information retrieval system. By matching the user's demands of readability to the documents with the corresponding readability, the classification model can further improve the results of, for example, a search engine. This thesis presents a new solution for classification into readability levels for Swedish. The results from the thesis are a number of classification models. The models were induced by training a Support Vector Machines classifier on features that are established by previous research as good measurements of readability. The features were extracted from a corpus annotated with three readability levels. Natural Language Processing tools for tagging and parsing were used to analyze the corpus and enable the extraction of the features from the corpus. Empirical testings of different feature combinations were performed to optimize the classification model. The classification models render a good and stable classification. The best model obtained a precision score of 90.21\% and a recall score of 89.56\% on the test-set, which is equal to a F-score of 89.88.
CoDIMS-G: a data and program integration service for the grid

Grid services provide an important abstract layer on top of heterogeneous components (hardware and software) that take part into a Grid environment. In this scenario, applications, like scientific visualization, require access to data of non-conventional data types, like fluid path geometry, and the evaluation of special user programs on these data. In order to support such applications we are developing CoDIMS-G, which is a data and program integration service for the Grid. CoDIMS-G provides users transparent access to data and programs distributed on the Grid, as well as dynamic resource allocation and management. We conceived a new node scheduling algorithm and designed an adaptive distributed query engine for the grid environment.
Andreas Goes to Africa: A Comparative Historical Study of the Teachers for East Africa Programs

This article uses a comparative historical approach to examine the Teachers for East Africa (TEA) and the Teacher Education in East Africa (TEEA) programs, an influential educational development effort that involved U.S. and British college graduates in East African schools and colleges during the decade of 1961–1971. Drawing on postcolonial theory and Andreas Kazamias’s humanistic view of education, the “Paideia of the soul,” it explores how U.S. teachers interpreted the education system they encountered in Kenya, Tanzania, and Uganda at the end of the colonial era, seeking to made sense of a radically different system of schooling. The comparison of U.S. and British teachers’ views on pedagogy in this critical historical period as discerned in the TEA and TEAA archive illustrates deep fissures in the putative edifice of “Western” education.
The Analysis and Mapping of Cyclic Circuits with Boolean Satisfiability

The accepted wisdom is that combinational circuits must have acyclic (i.e., loop-free or feed-forward) topologies. And yet simple examples suggest that this need not be so. Prior work advocated the design of cyclic combinational circuits (i.e., circuits with loops or feedback paths). A methodology was proposed for optimizing circuits by introducing cycles at the technologyindependent stage of synthesis. Efficient synthesis is predicated on efficient analysis. Prior methods for analysis were based on binary decision diagrams (BDDs). In this paper, a much more efficient technique is proposed based on Boolean satisfiability (SAT). Validation is performed both at a network level, in terms of functional dependencies, as well as at a gate level, after mapping to a library. When mapping breaks the validity of a combinational circuit, SAT-based analysis returns satisfying assignments; these assignments are used to modify the mapping in order to ensure that the circuit remains combinational. The effectiveness of the analysis and mapping algorithms is demonstrated on standard benchmarks.
Domain Specific Life Satisfaction in the Dual Careers of Junior Elite Football Players: The Impact of Role Strain

Using a holistic perspective on athlete talent development, this study examines the impact of role strain on the life satisfaction in various life domains of junior elite Australian Rules Football players. One hundred and twelve talent-identified male Australian Rules Football players (Mage = 16.8; SD = .71) completed measures of role strain and multidimensional life satisfaction. The results indicated that role strain explained twelve to twenty-four percent of the variance in life satisfaction in the players’ life domains. Experiences of role strain related to the players’ dual careers were associated with decreased life satisfaction in sport, friendships, family, yourself, and global life satisfaction domains. Situations in which the players perceived that their abilities were underutilized were also negatively associated with life satisfaction across various life domains. This study thus evidences the importance of a domain specific, holistic approach to investigate the life satisfaction in junior athletes’ dual careers.
To earn or to learn? Why the women from Navan Traveller Education Centre returned to learning.

In July 2012 the Navan Traveller Education Centre closed its doors for the last time. The centre had been providing learning and training opportunities to members of the Traveller community in Meath for over 20 years. This thesis asks the Reseach Question – Why did the Women of Navan Traveller Centre returned to learning following the closure of the Traveller Training Centre in Navan, Co Meath. This thesis challenges many of our preconcieved ideals concerning the motivations of Women in the Irish Traveller Community,and particularly why they accessed learning through the centre. In conjunction with the exploration of why the Traveller Women returned to learning this thesis will also explore the creation and evolution of the Navan Traveller Womens Development Group and the role it played in helping the women shape their own future
Transcriptome-Based Analysis of Dof Family Transcription Factors and Their Responses to Abiotic Stress in Tea Plant (Camellia sinensis)

Tea plant (Camellia sinensis (L.) O. Kuntze) is affected by abiotic stress during its growth and development. DNA-binding with one finger (Dof) transcription factors (TFs) play important roles in abiotic stress tolerance of plants. In this study, a total of 29 putative Dof TFs were identified based on transcriptome of tea plant, and the conserved domains and common motifs of these CsDof TFs were predicted and analyzed. The 29 CsDof proteins were divided into 7 groups (A, B1, B2, C1, C2.1, C2.2, and D2), and the interaction networks of Dof proteins in C. sinensis were established according to the data in Arabidopsis. Gene expression was analyzed in “Yingshuang” and “Huangjinya” under four experimental stresses by qRT-PCR. CsDof genes were expressed differentially and related to different abiotic stress conditions. In total, our results might suggest that there is a potential relationship between CsDof factors and tea plant stress resistance.
Diversity in a Sino-French Company in Beijing: How Do Employees Manage Their Multilingual Practices?

Summary Sometimes the idea of multilingualism is connected to understanding problems that can potentially slow down the progress of professional activity in international workplaces. However, social actors often find solutions locally to cope with issues associated with multicultural contexts. Keeping in mind the management of cultural and linguistic diversity, I set out to study how social actors organize talk-in-interaction and coordinate participation in multilingual work meetings. To allow mutual understanding and carry out their work, social actors use various resources such as ad hoc interpreting practices during professional interactions. Drawing on my conversational analysis (CA) background, I will examine how members of a Sino-French company in Beijing use ad hoc interpreting practices and English as a lingua franca (ELF) as methods to resolve the linguistic asymmetries present in a multicultural context where ELF is not always taken for granted. Through analysis of several naturally occurring conversations, I will examine the methods, and verbal and multimodal resources used by ad hoc translators to keep work going and manage each member’s participation.
Self-Awareness as Metacognition about Own Self Concept

Implementation of agency in a cognitive system implies that certain beliefs, values and/or goals represented in the system become, if implicitly, attributed to the self of the agent. When the cognitive system becomes explicitly aware of this attribution, it acquires a self-regulation capacity allowing it to control, modify and develop its self-concept together with the attitudes attributed to the self, adjusting to dynamically changing contexts and personal experience. The leverage of self-awareness understood in this sense consists in increased robustness, flexibility and integrity of the cognitive system, as illustrated by a paradigm of self-regulated learning.
Stability of Coalitions in Belief

Coalition stability is an important concept in coalition formation. One common assumption in many stability criteria in non-transferable utility games is that the preference of each agent is publicly known, so that a coalition is said to be stable if there is no objections by any sub-group of agents according to the publicly known preferences. However, in many applications including some software agent applications, this assumption is not realistic. Instead, intelligent agents are modeled as individuals with private belief and decisions are made according to those beliefs instead of common knowledge. Such belief based agents architectures have impacts on the coalition’s stability which are not reflected in the current stability criteria. In this paper, we extend the classic stability concept of the core by proposing a new belief based stability criterion which we labeled the belief-based core, and give examples to illustrate how the new concept can be used to provide both ex-ante and ex-post analysis of coalition formation mechanism.
Topical Application of Sadat-Habdan Mesenchymal Stimulating Peptide (SHMSP) Accelerates Wound Healing in Diabetic Rabbits

Objective. Diminished wound healing is a common problem in diabetic patients due to diminished angiogenesis. SHMSP was found to promote angiogenesis. The present study was carried out to examine the effect of this peptide in healing of wounds in diabetic rabbits. Materials and Methods. Twenty male New Zealand rabbits were used in this study. Diabetes mellitus was induced and the rabbits were randomly divided into two equal groups: control group and peptide group. A-full thickness punch biopsy was made to create a wound of about 10 mm on the right ears of all rabbits. Every day, the wound was cleaned with saline in control groups. In the peptide group, 15 mg of SHMSP was applied after cleaning. On day 15th, all animals were sacrificed, and the wounds were excised with a rim of 5 mm of normal surrounding tissue. Histo-pathological assessment of wound healing, inflammatory cell infiltration, blood vessel proliferation, and collagen deposition was performed. Results. There were no deaths among the groups. There was significant increase in wound healing, blood vessel proliferation and collagen deposition, and significant decrease in inflammatory cell infiltration in the peptide group compared to the control group. Conclusion. Topical application of SHMSP improves wound healing in diabetic rabbits.
The Optical Redshift Survey. II. Derivation of the Luminosity and Diameter Functions and of the Density Field

We quantify the effects of Galactic extinction on the derived luminosity and diameter functions and on the density field of a redshift sample. Galaxy magnitudes are more affected by extinction than are diameters, although the effect on the latter is more variable from galaxy to galaxy, making it more difficult to quantify. We develop a maximum-likelihood approach to correct the luminosity function, the diameter function and the density field for extinction effects. The effects of random and systematic photometric errors are also investigated. The derived density field is robust to both random and systematic magnitude errors as long as these are uncorrelated with position on the sky, since biases in the derived selection function and number counts tend to cancel one another. Extinction-corrected luminosity and diameter functions are derived for several subsamples of the {\it Optical Redshift Survey} (ORS). Extinction corrections for the diameter-limited subsamples are found to be unreliable, possibly due to the superposition of random and systematic errors. The ORS subsamples are combined using overall density scaling factors from a full-sky redshift survey of \iras\ galaxies, allowing the reconstruction of the optical galaxy density field over most of the sky to 8000 \kms.
Analytical model for semantic overlay networks in peer-to-peer systems

The hit rate of basic Peer-to-Peer protocols can be increased by using semantic metadata to transform the network structure or construct an overlay network. These semantic protocols benefit from the observation that the pattern of the stored or queried documents depends on the fields of interest of the nodes in the network. However, the performance of such networks highly depends on boundary conditions. These conditions determine both the probability of a successful query and the network traffic generated by the queries. In this paper, we will propose an analytical model that calculates the success rate of a query in a peer-to-peer system with a semantic overlay network. With the model, it is possible to optimize these systems by finding the appropriate values for the boundary conditions when designing the network or at runtime. The model has also been validated with a series of simulations.
Towards Multi-way Join Evaluating with Indexing Partition Support in Map-Reduce

In the era of "big data", the emergence and increasing adoptions of the related enabling technologies make it possible for Map-Reduce to accommodate DSS (Decision Support Systems) load, which is commonly targeted for high-performance Data Warehouse analyses in the context of RDBMS. However, the non-predetermined mapping of the Map-Reduce tasks to the physical machines makes it difficult to utilize the pre-partitioned and indexing techniques of DBMS to improve the data locality. In this paper, towards multi-way join evaluating OLAP (Online Analysis Processing) workloads, we introduce table partitioning by reference to Map-Reduce. For avoiding the dispersion of the initial tuples that belong to the same segment keys, we present a detailed description of the data organization model that partitions the dominated tables by cascade reference constraints. In order to push multiple joins on these clustered partitions down to the map task, we design a one-pass multi-way join algorithm along with its optimization implementations for the major Map-Reduce stages. We conduct an empirically study with TPCH benchmark on different scales of clusters, and experimentally verify the high efficiency of the proposed optimization model.
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Case-Based Reasoning research has reached a state where a large number of basic problems seems to be “solved”. However, techniques originally developed for CBR applications are being applied in systems that are not CBR systems in the original meaning of the word. This paper wants to extend the traditional view of CBR to overcome its former limitations, to open new fields of research, and to open new application areas. This is achieved by generalizing the classical similarity measure to a utility measure that does not depend on problem descriptions taken from experience any more.
Parameterized Convolution Filtering in a Field Programmable Gate Array

This paper discusses the simple idea of parameterized program generation of convolution filters in an FPGA. Applications in image processing include real-time video and desktop publishing. An example 2-D filter pipeline is assembled from a set of multipliers and adders, which are in turn generated from a canonical serial-parallel multiplier stage. The need for more powerful FPGA development tools is discussed using an analogy to software development.
A Hybrid Exact Algorithm for the TSPTW

TheTraveling Salesman Problem with Time Windows (TSPTW) is the problem of finding a minimum-cost path visiting a set of cities exactly once, where each city must be visited within a specific time window. We propose a hybrid approach for solving the TSPTW that merges Constraint Programming propagation algorithms for the feasibility viewpoint (find a path), and Operations Research techniques for coping with the optimization perspective (find the best path). We show with extensive computational results that the synergy between Operations Research optimization techniques embedded in global constraints, and Constraint Programming constraint solving techniques, makes the resulting framework effective in the TSPTW context also if these results are compared with state-of-the-art algorithms from the literature.